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Where does transcranial magnetic stimulation (TMS) stimulate Modelling of induced field maps for

ORIGINAL ARTICLE

Where does transcranial magnetic stimulation (TMS)stimulate?Modelling of induced ?eld maps for some common cortical and cerebellar targets

Janine D.Bijsterbosch ?Anthony T.Barker ?

Kwang-Hyuk Lee ?P.W.R.Woodruff

Received:24October 2011/Accepted:21May 2012/Published online:8June 2012óInternational Federation for Medical and Biological Engineering 2012

Abstract Computational models have been be used to estimate the electric and magnetic ?elds induced by transcranial magnetic stimulation (TMS)and can provide valuable insights into the location and spatial distribution of TMS stimulation.However,there has been little trans-lation of these ?ndings into practical TMS research.This study uses the International 10-20EEG electrode place-ment system to position a standard ?gure-of-eight TMS coil over 13commonly adopted https://www.wendangku.net/doc/af3526552.html,ing a ?nite element method and an anatomically detailed and realistic head model,this study provides the ?rst pictorial and numerical atlas of TMS-induced electric ?elds for a range of coil positions.The results highlight the importance of subject-speci?c gyral folding patterns and of local thick-ness of subarachnoid cerebrospinal ?uid (CSF).Our mod-elling shows that high electric ?elds occur primarily on the peaks of those gyri which have only a thin layer of CSF above them.These ?ndings have important implications for inter-individual generalizability of the TMS-induced elec-tric ?eld.We propose that,in order to determine with

accuracy the site of stimulation for an individual subject,it is necessary to solve the electric ?eld distribution using subject-speci?c anatomy obtained from a high-resolution imaging modality such as MRI.

Keywords Transcranial magnetic stimulation á

Electric ?eld áCerebrospinal ?uid áFinite element method áSite of stimulation

1Introduction

Since the ?rst demonstration of transcranial magnetic stimulation (TMS)in 1985[1],the technique has been widely adopted to transiently alter neural excitability in the human brain.In TMS,a brief,but intense electric current ?ows through a coil positioned over the subject’s head.The resultant time-varying magnetic ?eld induces an electric ?eld in the underlying tissue by Faraday’s law of electromagnetic induction.This electric ?eld can directly depolarize neurons leading to an action potential or can result in transient changes in the threshold for future action potentials [2].Hence,TMS can be used,for example,in research to investigate the causal relationship between activation in a target cortical region and its function as measured in behavioural tests [3–5].Previous human physiological studies have shown that neural stimulation mainly occurs in areas where the amplitude of the induced electric ?eld is high [6–8].Hence,an understanding of the location and extent of the induced electric ?elds resulting from different positions of the TMS coil on the head should inform the use of TMS and aid in the understanding of its capabilities and limitations.This paper seeks to provide TMS users with a pictorial and numerical description of the location and distribution

J.D.Bijsterbosch and A.T.Barker contributed equally to this work.

Electronic supplementary material The online version of this article (doi:10.1007/s11517-012-0922-8)contains supplementary material,which is available to authorized users.

J.D.Bijsterbosch (&)áK.-H.Lee áP.W.R.Woodruff

Shef?eld Cognition and Neuroimaging Laboratory (SCANLab),Academic Clinical Psychiatry,University of Shef?eld,The Longley Centre,Norwood Grange Drive,Shef?eld S57JT,UK e-mail:Janine.Bijsterbosch@https://www.wendangku.net/doc/af3526552.html,

A.T.Barker (&)

Department of Medical Physics and Clinical Engineering,Royal Hallamshire Hospital,Shef?eld S102JF,UK e-mail:a.t.barker@shef?https://www.wendangku.net/doc/af3526552.html,

Med Biol Eng Comput (2012)50:671–681DOI 10.1007/s11517-012-0922-8

of these?elds that occur in a representative brain model for a range of commonly used coil positions.

In air,or in electrically homogeneous material,the maximum electric?eld induced by the commonly used ?gure-of-eight coil geometry occurs directly under the centre of the coil,at the point where the two circular parts overlap[9,10].In practice,the location and extent of the induced?elds are affected by many parameters such as skull thickness and geometry and the electrical properties of different tissue types.In addition,TMS parameters such as the electric current in the coil(both waveform and duration),and the coil shape and winding geometry all affect the resultant induced?elds and their biological potency[11–15].Several approaches have been used in an attempt to measure the induced electric?eld or neural responses resulting from TMS.Motor evoked potentials induced by TMS over the primary motor cortex have been used to investigate the effect of various TMS parameters and to assess intra-subject reliability[16–18].Intra-cranial recordings using implanted electrodes in monkeys and humans have been used to show the differences in response due to cortical depth and coil angle and orien-tation[19,20].Electroencephalography(EEG)and neu-roimaging methods such as positron emission tomography (PET)and functional magnetic resonance imaging(fMRI) have been used to measure neural activity associated with TMS[21–24].More recently,an animal model has been developed that has the potential to facilitate future testing of stimulation parameters,coil positioning and treatment effects over time[25].The?ndings from these studies will aid the understanding for the effect of TMS on neural tissue,but they are predicated on having a readily observable metric directly related to the neuronal stimu-lus.Therefore,a full characterization of TMS-induced electric?elds for a range of different cortical stimulation targets is currently beyond the scope of neuroimaging https://www.wendangku.net/doc/af3526552.html,putational models of induced electric ?eld,whilst having their own limitations,are able to provide an alternative insight into the stimulus resulting from TMS and may be used either by themselves or in combination with animal model testing to optimize the use of TMS in future clinical and non-clinical research.

In early computational models of TMS-induced elec-tric?eld,the brain was commonly represented as an in?nite half-plane or perfect sphere[26–30].Recent models that take account of detailed head geometry, tissue electrical conductivity and electrical anisotropy approach a more realistic(in vivo)representation of the human brain.For example,Wagner et al.[31]used a ?ve-layered model to show that boundaries between tissues of different conductivities can strongly affect the distribution of the induced?eld.In contrast,it has been shown that white matter?bre anisotropy has only min-imal effects on the intensity and distribution of the electric?elds induced in grey matter[32,33].Although recent advances in modelling provide valuable insights into the induced?eld distribution following TMS,there has been little translation of this knowledge into practical TMS research.This study seeks to provide TMS users with a practical pictorial and numerical description of the location and distribution of stimulation that occurs in a representative brain model.To achieve this,the TMS coil is positioned over several frequently adopted target regions,including the primary motor cortex,pre-motor cortex,dorsolateral prefrontal cortex,temporo-parietal cortex,posterior parietal cortex and the medial and lat-eral cerebellum.The Tailarach coordinate system is used to describe the location and extent of the induced electric ?eld for each target[34].In the discussion,we consider the issues surrounding the generalization of these electric ?eld distribution results to different subjects.

2Methods

2.1Model

The numerical evaluation of the induced electric?eld was performed using the?nite element method as implemented in the low frequency solver of the simulation software package SEMCAD(version13.2,SPEAG,Switzerland). All models utilized a high-resolution model of an adult human head(male,age34)from the SEMCAD‘Virtual Family’[35].The‘Virtual Family’comprises two adult and two child whole body models based on high-resolution MR scans and a novel semi-automated segmentation tool. The subjects were chosen to have sizes and body masses close to current worldwide(adults)and German(children) averages[35].We assigned electrical conductivities to the tissue types,based on the established and widely used database of Gabriel et al.[36],via the inbuilt SEM-CAD parametric database at a frequency of4kHz (this approximates the fundamental frequency of a typical TMS repetitive stimulator current waveform,which is approximately sinusoidal).The Gabriel database is also available online at:https://www.wendangku.net/doc/af3526552.html,r.it/tissprop/htmlc lie/htmlclie.htm,and can be interrogated both by tissue type and excitation frequency.The Gabriel values for the key tissue types are:skull(0.020S/m),cerebrospinal?uid (CSF,2.00S/m),cerebral grey matter(0.108S/m),white matter(0.066S/m)and cerebellar grey matter(0.128S/m). The results shown in the remainder of this paper are the electric?elds calculated in cerebral and cerebellar grey matter.

2.2Simulation methodology

The TMS coil geometry was based on the Magstim Com-pany Ltd‘double70’coil.This coil has a?gure-of-eight geometry with each winding consisting of nine turns hav-ing a mean diameter of70mm.The centre of the coil was located tangentially to the surface of the scalp at each target position.In the computer model,each turn of wire was represented by a thin circular loop having a radius equal to that of the centre of the real turn.Each turn was excited by a sinusoidal current of5kA peak at4kHz, these?gures being an approximation to the waveform from a typical magnetic stimulator(for example,the Magstim Rapid,Magstim Co.Ltd,Dyfed,Wales)at full output.The choice of coil current amplitude does not affect the resul-tant spatial distribution of induced?eld;its absolute amplitude will merely scale linearly with the coil current. The induced?eld amplitude will scale with excitation frequency if the tissue conductivities are not frequency dependent.In practice,the tissue conductivities are fre-quency dependent,but not dramatically so in the relevant range(for example,the Gabriel database grey matter conductivity varies between0.106and0.110S/m over a frequency range of3–5kHz and the CSF conductivity remains unchanged).Hence,the modelling results pre-sented here will not depend critically on the frequency chosen.Two examples of the effect of different tissue conductivity assumptions on the induced electric?eld are described later.

Thirteen target TMS positions were chosen based on commonly used locations in neuroscienti?c research(Table S1in the Supplementary Material).For six of the targets (left and right primary motor cortex,DLPFC and superior parietal cortex),the coil was located using previously reported Talairach coordinates of the International10-20 system[37].In the left and right pre-motor cortices,the target position was identi?ed by moving the coil2cm anterior and1cm medial from the primary motor cortex position[38].The left and right temporo-parietal targets were chosen as the midpoint between T3and P3and between T4and P4,respectively[37,39].Cerebellar target positions were located by placing the coil1cm below the inion(medial cerebellum)and3cm to the left or right of this position(lateral cerebellum)[40,41].The exact location of the coil was adjusted to the local geometry of the head model,such that the coil housing was on,and tangential to,the scalp surface.For each coil position,a grey matter intersection point was determined by project-ing a line along the coil central axis(i.e.orthogonal to the plane of the coil windings)from the midpoint between the coils towards the brain and determining the nearest grey matter surface location.Talairach coordinates of the coil locations and grey matter intersection points(Table S1in the Supplementary Material)and of all results were obtained using the SEMCAD‘Talairach Tool’.For primary and pre-motor targets,the coil was oriented such that a line joining the centres of the two coils that comprised the ?gure-of-eight con?guration was approximately perpen-dicular to the AC–PC line(the line through the anterior and posterior commissure).When using a standard?gure-of-eight coil,this orientation would mean that the handle of the coil points backwards.For all other cortical targets,this line was positioned at an approximately45°angle to the AC–PC line.In cerebellar targets,the line joining the centres of the two coils was positioned parallel to the coronal plane.

In addition to the13target positions described above, four further computation models were run.The?rst two additional models assessed the effects of:(1)coil orienta-tion and(2)individual differences in cortical folding pat-terns.To address the effect of coil orientation,the left primary motor cortex target was repeated with the coil rotated such that the line joining the centres of the two coils was aligned parallel to the AC–PC line(90°rotation to the original orientation).The centre of the coil housing was kept tangential to the scalp surface in both coil orientations. Secondly,the original left primary motor cortex target(the line joining the centre of the two coils perpendicular to the AC–PC line)was repeated on a different high-resolution computer model of the human head(female,age26years) [35].The Talairach coordinates of the coil centres were adjusted minimally in order for the coil to rest on the scalp surface(Table S1in the Supplementary Material).The remaining two additional models tested the effect of dif-ferences in tissue electrical conductivities,by altering the ratio between grey matter and CSF conductivity values.For each coil position,the electric?eld intensities in cerebral and cerebellar grey matter calculated in SEMCAD were exported and post-processed in Matlab(details of this processing can be found in the Supplementary Material). 3Results

3.1Maximum induced electric?eld

Electric?eld intensities were calculated throughout the entire model space.In practice,the highest electric?eld intensities were primarily located on the grey matter sur-face,at the boundary between grey matter and CSF.Fig-ures1and2show examples of the TMS-induced electric ?eld distribution on the grey matter surface for two of the modelled coil positions.Figures showing the?eld distri-bution for the other models can be found in the Supple-mentary Material(S1–S11).Table S2(Supplementary Material)summarizes the results of the maximum induced

electric ?elds for each of the 13TMS targets.The average distance between the centre of the coil on the scalp surface measured along the coil central axis to its intersection with the grey matter surface was 16.3mm (range:11–23mm);this is a measure of cortical depth at each coil position (Table S1in the Supplementary Material).The lateral distance from this grey matter intersection point under-neath the coil to the location of the peak electric ?eld in grey matter was on average 16.5mm (range 4–57mm)and provides a measure of lateral displacement over the grey matter surface.The average intensity of the peak electric ?eld for the coil drive current and frequency used in the model was 809V/m (range:427–1485V/m).Relative intensity (normalized to the maximum in the left primary motor cortex coil position)is also tabulated as a compar-ative measure of relative ?eld strength for different coil positions.The effect of different excitation frequencies is not expected to be large but,for values that differ by more than approximately ±50%from the representative value of 4kHz chosen here,the models should be resolved using the appropriate values of tissue conductivity for the new frequency.

There was a signi?cant inverse correlation between the peak electric ?eld intensity and cortical depth (i.e.the distance from the scalp surface along the coil central axis to its intersection with the grey matter surface:R =-0.65,p =0.004).In contrast,there was no correlation between the peak intensity and lateral displacement (i.e.the distance from the grey matter intersection point to the peak electric ?eld location:R =-0.02,p =0.9).Hence,the electric ?eld intensity was related to cortical depth,but not to distance from the coil axis,which is consistent with the modest ‘focality’of the ?gure-of-eight con?gu-ration [42

Fig.1TMS-induced electric ?elds in the left primary motor cortex.The induced electric ?eld strength is shown on a rendered view of the grey matter surface in the full range (a 0–100%of 1,289V/m)and in the threshold range (b 50–100%of 1,289V/m).The view is presented looking down the central axis of the coil.The green concentric circles represent the geometry of individual coil turns that were modelled.Note that some darkening of the cortical structure occurs at the centre of each coil wing in a and b .This darkening is caused by local minima in the electric ?eld results,which have been used to illuminate and thus reveal the cortical structure.c ,d Voxels with supra-threshold electric ?eld intensity induced in grey matter (in red )are shown on coronal slices through the peak electric ?eld (c )and through the local maximum of the cluster with the next highest electric ?eld strength (d ).Grey matter is shown in grey and CSF is shown in cyan .The coordinates shown are those of the peak electric ?eld voxels in the relevant cluster (the coordinates and the units on the axes are in Talairach space).We have chosen to show the ?gures such that they include the whole head in order to facilitate localization and interpretation of the results.However,the high resolution of the ?gures allows further inspection of ?ner details (color ?gure online)

3.2Supra-threshold electric ?eld clusters

A clustering analysis has been performed,the details of which are given in the Supplementary material.The sum-med volume of the supra-threshold voxels (de?ned as those having C 50%of the peak electric ?eld)in grey matter was on average 92.7mm 3(range 11–180mm 3).These supra-threshold voxels were clustered to explore the spatial dis-tribution of the induced electric ?eld.Tables S3and S4(Supplementary Material)summarize the local maximum and the size of all supra-threshold clusters for cortical and cerebellar targets.Additional results of smaller clusters (\3mm 3)are provided in Tables S6and S7of the Sup-plementary Material.3.3Effects of coil orientation

To assess the effect of the orientation of the coil relative to the head,the coil was positioned over one site,the left primary motor cortex,in two different orientations:(1)the line joining the centres of the two coils that comprised the ?gure-of-eight con?guration,approximately perpendicular to the AC–PC line (Figs.1,2)this line parallel with the AC–PC line (Fig.3)(90°difference between 1and 2).In the latter position,the maximum electric ?eld intensity was lower (1,069vs.1,289V/m)and the summed total size of supra-threshold voxels was larger (89.3vs.69.6mm 3)

compared with the other coil orientation.Additionally,the distance between the location of the peak electric ?eld differed by 8.6mm between these two orientations.These variations are likely to be caused by the interaction of the change in induced current direction and the gyral geome-try.Table S5in the Supplementary Material compares the spatial distribution of the supra-threshold electric ?elds in both models.

3.4Effects of individual differences in cortical folding To investigate the generalizability of the induced electric ?eld to other individuals,the left M1coil position (coil oriented perpendicular to the AC–PC line,Fig.1)was also performed on a model of the female brain provided by the Virtual Family tool (Fig.4);[35].Results indicated that the intensity of the peak electric ?eld was lower (765vs.1,289V/m),as was the summed total size of supra-threshold voxels (51.7vs.69.6mm 3)in the female head model compared with the male head model.The reduction in electric ?eld intensity may,in part,be due to cortical depth,which was greater in the female head model (16.3mm compared with 12.1mm in the male head model).The location of the peak electric ?eld in the female model was 10.3mm removed from the peak electric ?eld in the male model,re?ecting differences in gyral structure.Table S5in the Supplementary Material compares

the

prefrontal cortex.The induced electric ?eld strength is shown on a rendered view of the grey matter surface in the full range (a 0–100%of 804V/m)and in the threshold range

(b 50–100%of 804V/m).Please refer to the legend of Fig.1for further details

1,069V/m).Please refer to the legend of Fig.1for further details

Fig.4TMS-induced electric

(b50–100%of765V/m). Please refer to the legend of

Fig.1for further details

distribution of the supra-threshold electric ?eld into clusters.

3.5Effects of differences in tissue electrical

conductivity

A comparison was performed to determine the effect of conductivity differences between grey matter and CSF on the resultant amplitude and distribution of the induced electric ?eld.The left M1coil position (coil oriented per-pendicular to the AC–PC line,Fig.1)was also performed on the same model of the male brain,but with the electrical conductivity of CSF set to be identical to that of grey matter (0.128S/m).The results revealed that the peak electric ?eld decreased from 1,289to 339V/m when the conductivities were set to be equal and the resultant electric ?elds were more diffuse,without obvious peaks on gyri (Fig.5).This model shows that the difference in electrical conductivity between the CSF and the grey matter led to an ‘ampli?cation’of about 3.8times and hence this factor is primarily responsible for the peak ?elds observed on gyral surfaces rather than being due to these regions being closer to the stimulating coil than other brain areas.

We have chosen to use the conductivity ?gures of Gabriel et al.[36,43,44]throughout this work because of their established nature.However,other authors have chosen somewhat different values.For example,Miranda et al.have used conductivities of CSF =1.79S/m,grey matter =0.32S/m and white matter =0.15S/m as opposed to our values of 2.0,0.108and 0.0659S/m,respectively [33,45,46].We have compared the electric ?eld distributions resulting from tissue conductivity values derived from Gabriel et al.with those resulting from the tissue conductivity values used by Miranda et al.Figure 6shows the resultant ?eld patterns for the left M1coil

position (Fig.1)using these alternative values to show the extent to which the resultant ?eld patterns depend on the conductivity values chosen.

4Discussion

The aim of this study was to provide a compendium of induced electric ?eld patterns and amplitudes

following

Fig.5Effects of differences in tissue electrical conductivity.The induced electric ?eld strength on the grey matter surface is shown when the conductivity of CSF is set to a realistic value (left )compared with the same model,but with the electrical conductivity of CSF set to be identical to the electrical conductivity of grey matter (right ).The

scale ranges from 0to 100%of 1,289V/m.This model shows that the difference in electrical conductivity between the CSF and the grey matter led to an ‘ampli?cation’of some 3.8times and to a less diffuse spatial distribution of the induced electric

?eld

Fig.6Effects of different ratios of electrical conductivity.The induced electric ?eld strength in the left primary motor cortex is shown when tissue conductivity values were assigned based on previous modelling studies [33,45,46],instead of the comprehensive Gabriel database [36,43,44]that was used elsewhere throughout this work.Results are shown on a rendered view of the grey matter surface in the full range (0–100%of 808V/m)and can be compared to the results presented in Fig.1a

transcranial magnetic stimulation over multiple commonly adopted cerebral and cerebellar targets using a head model representative of a normal male adult.The electric?elds induced by13different coil positions are summarized in Figs.1and2and in the Figures and Tables in the Sup-plementary Material.Taken together,the?ndings indicate that for most coil positions,the supra-threshold electric ?eld includes,but is not restricted to,the target cortical region.In the remainder of the discussion,we highlight the most important factors that contribute to the electric?eld distribution and discuss the generalizability of these results to individual subjects.

4.1Subarachnoid cerebrospinal?uid

Our?ndings suggest that subarachnoid cerebrospinal?uid (CSF)distribution has a major effect on the location of peak TMS-induced electric?elds.The conductivity of CSF is considerably greater than the conductivity of any brain tissue(by a factor of15–30at4kHz[36]).Therefore,the TMS-induced current preferentially follows a least-resis-tance path through CSF rather than through adjacent,less conductive,tissues resulting in relatively high currents in the CSF.Where the CSF layer thins,for example between the peaks of gyri and the skull,these induced CSF currents (which by their intrinsic physics properties have to be ‘continuous’)become largely concentrated in the restricted CSF area above the gyral peaks resulting in high electric ?elds on their surface.As a result,high induced electric ?elds are primarily found in grey matter regions adjacent to areas of reduced or thinning CSF thickness.For all coil positions,supra-threshold electric?elds occur in grey matter regions underneath the centre of the TMS coil. However,the peak electric?elds can occur in grey matter regions some distance from the centre of the coil due to this ‘amplifying effect’caused by a local reduction in CSF thickness.This‘CSF ampli?cation effect’can be seen,for example,when the coil is positioned over the right DLPFC (Fig.2).The CSF thickness was relatively great directly underneath the right DLPFC coil position,and the peak electric?eld region occurred where the CSF was thinner some distance from the coil centre.This example,along with similar results included in the Supplementary Mate-rial,shows that TMS-induced electric?elds are strongly affected by the distribution and thickness of CSF.

We showed a three to fourfold increase in the electric ?eld intensity when realistic tissue differences in conduc-tivity were used compared with a model in which the electrical conductivities of grey matter and CSF were set to be equal(Fig.5).Thus,the electric?eld peaks shown throughout this paper are due primarily to these conduc-tivity differences and CSF thinning,rather than being due to decreased cortical depth at the surface of the gyri and the resultant closer proximity to the stimulating coil.The conductivity values that we assigned to grey matter,white matter and CSF were derived from extensive and com-prehensive measurements of the dielectric properties of human tissues rigorously performed by Gabriel and col-leagues[36,43,44].Different conductivity values that have a smaller ratio between grey matter and CSF have been used by other authors[33,45,46].The effect of these different conductivity values on TMS-induced electric ?elds can be seen in Fig.6and shows broadly similar, although somewhat more diffuse,?eld patterns.This result also indicates that a deviation of±several kHz from the representative frequency of4kHz for the coil excitation waveform will not lead to large changes in the?ndings reported here,as the resultant frequency-dependent chan-ges in tissue conductivities are smaller than those used to create Fig.6[36].

Table S2in the Supplementary Material shows that a hemispheric asymmetry in lateral displacement(greater displacement in the right than in the left hemisphere), similar to that in the DLPFC,was found for all cortical targets except for the temporo-parietal cortex.A previous study has reported a signi?cant increase in subarachnoid CSF volume in the right hemisphere compared with the left hemisphere in a large group of healthy volunteers[47].The right-lateral increase in subarachnoid CSF occurred adja-cent to areas of reduced grey and white matter volume and this anatomical asymmetry is associated with a functional lateralization,for example in handedness and language function.The human head model that was used in this study displayed a comparable hemispheric asymmetry in subarachnoid CSF volume(6.7%more CSF voxels in the right than in the left hemisphere),which may explain the difference in lateral displacement of the peaks of electric ?eld between the right and left hemisphere.Additionally,it has been reported that the resting motor threshold is sig-ni?cantly higher when measured over the right motor hotspot compared with the left motor hotspot,which may also be related to increased subarachnoid CSF volume[48]. Taken together,these results suggest that the focal preci-sion of TMS-induced electric?elds in grey matter may be less when stimulating the right hemisphere compared with the left hemisphere.

Our results show that supra-threshold TMS-induced electric?elds extent beyond the target cortical regions (Table S3and S4,Supplementary Material).This may lead to unwanted stimulation in neighbouring areas of grey matter.For example,when the TMS coil is positioned over the cerebellum,the results show widespread supra-thresh-old electric?elds in the occipital lobe of the cerebral cortex (Supplementary Figures S6to S8).These results suggest that TMS over the cerebellum may lead to stimulation of visual regions such as the primary and secondary visual

cortices,as well as to cerebellar stimulation.In line with the preceding discussion,these distant regions of supra-threshold electric?eld in the visual cortices are caused by local thinning of the CSF.Hence,future studies that apply TMS over the cerebellum should take into account that the induced stimulation may extent to the visual cortex.

In this work,our modelling results have led us to focus on the in?uence of local changes in CSF thickness upon electric?eld intensity induced in grey matter tissue by TMS.We have not modelled the anisotropy of white matter caused by the orientation of directed?bres,because pre-vious studies have explicitly addressed the effect of this on induced electric?eld strength in neighbouring grey matter tissue and have found such effects to be minimal[32,33, 49].This lack of effect is likely to be due to a combination of the strong‘ampli?cation’effect at the grey matter–CSF boundary being independent of the white matter properties, coupled with grey and white matter conductivities being closer in magnitude than those of grey matter and CSF.A recent study suggests that?bre directionality may interact with gyral orientation and with the direction of the induced current,leading to subtle changes in the electric?eld in the grey matter[49].Whilst such complex interactions are of interest to gain a full understanding of TMS-induced electric?elds,they are beyond the scope of the present study.Nonetheless,recent advances in the acquisition and analysis of diffusion tensor imaging data may facilitate future research into the intricate interplay between brain tissues and thus shed further light on the neural effects induced by TMS[50–53].

4.2Gyral geometry

Supra-threshold electric?eld regions were primarily loca-ted on the surface of gyri,which is consistent with a recent study[49].Therefore,subject-speci?c gyral geometry may limit the inter-individual generalizability of electric?eld location and spatial distribution derived from a speci?c anatomical model.This suggestion is supported by our ?nding that the intensity and spatial distribution of supra-threshold electric?eld varied between two different(male and female)human head models(Table S5in the Supple-mentary Material and Figs.1and4).Our results suggest that considerable inter-individual differences in the inten-sity and spatial distribution of TMS-induced electric?elds are likely to occur due to individual differences in gyral folding patterns and the concomitant effect these have on the thickness of the CSF layer above them.Such inter-subject variability in the peak amplitudes and spatial dis-tribution of supra-threshold electric?elds may help to explain variability of TMS effects over different subjects within studies and the variation in reproducibility between studies.

A further factor that in?uences the spatial distribution of TMS-induced electric?elds is the coil orientation.To test the effect of coil orientation,we repeated the left primary motor target modelling with the coil in two different ori-entations(aligned with,or perpendicular to the AC–PC line).The results show that more regions in pre-motor and somatosensory cortices are stimulated when the coil is aligned with the AC–PC line as compared to when the coil is rotated by90°(Table S5in the Supplementary Material and Figs.1and2).This difference in the pattern of exci-tation is due to the relative orientation of the gyri to the path of current?ow.These?ndings are consistent with a recent modelling study[54]and with previous empirical work that showed differences in motor threshold depending on the orientation of the coil[55].The‘ampli?cation’effect is greatest on the peaks of gyri which run perpen-dicular to the path of the induced current in the CSF.Thus, because rotating the coil changes the direction of the induced current,it also tends to cause gyri having different orientations to experience greater‘ampli?cation’.This can be seen in Figs.1a and3a where there is a trend for electric ?eld maxima to occur along gyri approximately perpen-dicular to a line running between the two coil windings (which is the direction of maximum induced current in a homogeneous medium).

To optimize stimulation of the target cortical region and to minimize unwanted stimulation of neighbouring areas, future studies may bene?t from the use of computational models to decide on the optimal coil position and orien-tation for individual subjects.For example,whilst it is usual to centre the coil over the target region,such mod-elling would enable the effect of placing the coil off-centre and changing its orientation to be explored to minimize induced currents in an adjacent region,whilst not signi?-cantly affecting the electric?eld in the target region.

4.3Implications for future research

The?ndings of this study show that electric?elds induced by TMS are dependent on cortical depth,gyral folding patterns and on the thickness of the CSF layer that covers gyri and may therefore vary considerably between different subjects.Whilst the numerical value of these effects are inevitably dependent on such factors as the precision of the tissue segmentation algorithm applied to the head model, the general observation that localized CSF thinning leads to an ampli?cation of the electric?eld intensity in surround-ing grey matter tissue remains valid regardless of minor changes in tissue assignment and conductivities.

In use,the spatial selectivity of TMS can be greater than indicated in these results.For example,when obtaining a response from a hand muscle at motor threshold,slight movements of the coil(of the order of1–2mm)can result

in a diminished or lost response.This apparent spatial selectivity occurs not due to intrinsic focality of the induced?eld,but rather to the binary nature of neural depolarization coupled with TMS stimulation being at threshold level.Hence,a small change in induced?eld amplitude,caused by a small movement of the coil,can be suf?cient to drop the stimulus below the neural threshold resulting in the response being lost.This hyperacuity phenomenon is routinely exploited in TMS research.At higher stimulation strengths,the induced?eld patterns(as expressed by,for instance,the50%threshold)can be both widespread and discontinuous.

The potential sources of inter-individual variability pre-sented in this work have signi?cant implications for the application of TMS.Although it has been shown that the use of neuronavigation methods improves the ef?cacy of TMS [56–58],these methods are based on the assumption that the peak induced electric?eld occurs underneath the centre of the?gure-of-eight coil.Our?ndings show that this assumption may not always be valid.In the future,neuro-navigation methods could be improved by calculating the induced electric?eld based on the tissue geometry and CSF distribution obtained from an MRI scan of each individual. This,however,requires high-resolution anatomical scans (ideally voxels of0.5mm3or smaller)being available, coupled with accurate tissue segmentation of these scans, particularly in the vicinity of the CSF–grey matter–skull interface regions and a signi?cant computational load. Given the technical challenges and resources required, future research is needed to investigate the feasibility and usefulness of fully personalized TMS coil placement. Acknowledgments J.Bijsterbosch is supported by a Medical Research Council Ph.D.studentship.We thank Dr.Pedro Crespo Valero from SEMCAD for his assistance in optimizing the SEMCAD Talairach tool for use in this work.A.T.B.and J.D.B.contributed equally to this work and jointly discussed the results and implications.

A.T.

B.conceived the study,designed and ran the models and com-mented extensively on the manuscript at all stages.J.D.B.contributed to the design of the models,designed and performed the post-pro-cessing of the modelling data and wrote the manuscript.K-H.L.and P.W.R.W.supervised J.D.B.and commented on the manuscript. References

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电源磁芯尺寸功率参数.doc

电源磁芯尺寸功率参数

常用电源磁芯参数 MnZn 功率铁氧体 EPC 功率磁芯特点：具有热阻小、衰耗小、功率大、工作频率宽、重量轻、结构合理、易表面贴装、屏蔽效果好等优点，但散热性能稍差。用途：广泛应用于体积小而功率大且有屏蔽和电磁兼容要求的变压器，如精密仪器、程控交换机模块电源、导航设备等。 EPC型功率磁芯尺寸规格磁芯型号Type 尺寸Dimensions(mm) A B C D Emin F G Hmin EPC10/8 10.20±0.20 4.05±0.30 3.40±0.20 5.00±0.20 7.60 2.65±0.20 1.90±0.20 5.30 EPC13/13 13.30±0.30 6.60±0.30 4.60±0.20 5.60±0.20 10.50 4.50±0.30 2.05±0.20 8.30 EPC17/17 17.60±0.50 8.55±0.30 6.00±0.30 7.70±0.30 14.30 6.05±0.30 2.80±0.20 11.50 EPC19/20 19.60±0.50 9.75±0.30 6.00±0.30 8.50±0.30 15.80 7.25±0.30 2.50±0.20 13.10 EPC25/25 25.10±0.50 12.50±0.30 8.00±0.30 11.50±0.30 20.65 9.00±0.30 4.00±0.20 17.00 EPC27/32 27.10±0.50 16.00±0.30 8.00±0.30 13.00±0.30 21.60 12.00±0.30 4.00±0.20 18.50 EPC30/35 30.10±0.50 17.50±0.30 8.00±0.30 15.00±0.30 23.60 13.00±0.30 4.00±0.20 19.50 EPC39/39 39.00±0.50 19.60±0.30 15.60±0.30 18.00±0.30 30.70 14.00±0.30 10.00±0.30 24.50 EPC42/44 42.40±1.00 22.00±0.30 15.00±0.40 17.00±0.30 33.50 16.00±0.30 7.40±0.30 26.50

公路电动栏杆机控制模块维修简述

公路电动栏杆机控制模块维修简述目前，公路自动栏杆机控制模块主要是Magnetic的自动栏杆机控制模块，这种控制模块采用了先进的微处理器技术和可靠的开关控制技术，系统集成度高，逻辑功能强，满足公路环境下的应用。下面简单介绍栏杆机控制模块面板的功能与接线，栏杆机控制模块中的数字代表意义和接法如下： “1”表示接电源L（火线）220V AC； “2”表示接电源N（零线）； “3”表示电源线地线； “4”表示电机接地线PE； “5”表示电机公共绕组U，接电机公共绕组U； “6”表示电机落杆绕组V，接电机绕组V； “7”表示电机升杆绕组W，接电机绕组W； “8、9”表示降压减速阻容（R=5Ω/25W C=2uF/AC450V，电阻和电容串联）； “10、11”表示电机运行电容（4uF/AC450V）； “17”表示电源输出24VDC接地线； “18”表示电源输出 24VDC正极； “19”表示控制信号共用线（+24VDC）； “20”表示开脉冲，和控制信号共用线（+24VDC）短接有效； “21”表示环路感应器2输入（用于车辆到时自动抬杆，用于6、8模式）； “22”表示关脉冲，和控制信号共用线（+24VDC）短接有效； “23”表示抬杆、落杆限位开关输入信号； “24”表示安全开关，接常闭触点；断开时，系统不会执行落杆动作； “25”表示控制信号共用线（+24VDC）,同“19”功能一样； “26”表示档杆状态输出公共触点； “27、28”完全等同于“20、22”，常开触点（300ms）； “29”表示抬杆状态输出触点； “30”表示落杆状态输出触点； “31、32”表示报警输出，为常开触点。栏杆机控制模块长期处于工作状态，每天控制栏杆上下达几千次以上，是栏杆机易损元件之一，下面简单介绍几点常见的故障和维修方法，供大家参考：首先，在维修栏杆机控制模块之前，务必将故障设备的灰尘清除干净，养成这个习惯可以让你检查和维修故障更快速、准确。故障一控制模块无电现象控制模块电源长期处于带电中，供电系统元件容易老化，容易出现无供电现象。这种情况一般先观察，所谓观察就是用眼睛看。注意观察栏杆机控制模块的外观、形状上有无什么异常，电器元件（如变压器、电容、电阻等）有无出现变形、断裂、松动、磨损、冒烟、腐蚀等情况。其次是鼻子闻，一般轻微的气昧是正常的，如果有刺鼻的焦味，说明某个元器件被烧坏或击穿，应替换相应的元器件。最后用手试，当然是触摸绝缘的部分，有无发热或过热，用手去试接头有无松动，以确定设备运行状况以及发生故障的性质和程度。如某站01#车道出现控制模块无电，经测试是电源保险管（250V 4A）烧毁。在更换前

各种开关电源变压器各种高频变压器参数EEEEEEEIEI等等的参数

功率铁氧体磁芯常用功率铁氧体材料牌号技术参数 EI型磁芯规格及参数

PQ型磁芯规格及参数 EE型磁芯规格及参数 EC、EER型磁芯规格及参数

1,磁芯向有效截面积：Ae 2,磁芯向有效磁路长度：le 3,相对幅值磁导率：μa 4,饱和磁通密度：Bs 1磁芯损耗：正弦波与矩形波比较一般情况下，磁芯损耗曲线是按正弦波+/-交流(AC)激励绘制的，在标准的和正常的时候，是不提供极大值曲线的。涉及到开关电源电路设计的一个共同问题是正弦波和矩形波激励的磁芯损耗的关系。对于高电阻率的磁性材料如类似铁氧体，正弦波和矩形波产生的损耗几乎是相等的，但矩形波的损耗稍微小一些。材料中存在高的涡流损耗（如大一般情况下，具有矩形波的磁芯损耗比具有正弦波的磁芯损耗低一些。但在元件存在铜损的情况下，这是不正确的。在变压器中，用矩形波激励时的铜损远远大于用正弦波激励时的铜损。高频元件的损耗在铜损方面显得更多，集肤效应损耗比矩形波激励磁芯的损耗给人们的印象更深刻。举个例子，在 20kHz、用17#美国线规导线的绕组时，矩形波激励的磁芯损耗几乎是正弦波激

励磁芯损耗的两倍。例如，对于许多开关电源来说，具有矩形波激励磁芯的 5V、20A和30A输出的电源，必须采用多股绞线或利兹(Litz)线绕制线圈，不能使用粗的单股导线。 2Q值曲线所有磁性材料制造厂商公布的Q值曲线都是低损耗滤波器用材料的典型曲线。这些测试参数通常是用置于磁芯上的最适用的绕组完成的。对于罐形磁芯，Q值曲线指出了用作生成曲线时的绕组匝数和导线尺寸，导线是常用的利兹线，并且绕满在线圈骨架上。对于钼坡莫合金磁粉芯同样是正确的。用最适合的绕组，并且导线绕满了磁芯窗口时测试，则Q值曲线是标准的。Q值曲线是在典型值为5高斯或更低的低交流(AC)激励电平下测量得出的。由于在磁通密度越高时磁芯的损耗越大，故人们警告，在滤波电感器工作在高磁通密度时，磁芯的Q值是较低的。3电感量、AL系数和磁导率在正常情况下，磁芯制造厂商会发布电感器和滤波器磁芯的AL系数、电感量和磁导率等参数。这些AL的极限值建立在初始磁导率范围或者低磁通密度的基础上。对于测试AL系数，这是很重要的，测试AL系数是在低磁通密度下实施的。某些质量管理引入检验部门，希望由他们用几匝绕组检查磁芯，并用不能控制频率或激励电压的数字电桥测试磁芯。几乎毫不例外，以几百高斯、若干

磁芯参数参看

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栏杆机说明书

MAGSTOP MIB 2O／3O／40 栏杆机及MAGTRONIC MLC 控制器操作指导 @1999年马格内梯克控制系统(上海)有限公司地址：上海浦东新区宁桥路999号二幢底西层邮编：201206 电话：(21)58341717 传真：(21)58991233

目录 1. 系统概述 2 1.1 停车场系统的布局 2 1. 2 系统组件概述 2 2 安全 3 2.1一般安全信息3 2.2 建议用途 3 2.3 本手册中使用的安全标志3 2.4 操作安全 4 2.5 技术发展 4 2.6 质量保证 4 3. 装配及安装 5 3.1 构筑安装地基 5 3.2 安装感应线圈 6 3.3 安装机箱 8 3.4 安装栏杆机臂 8 3.5 基本机械结构 9 3.6 设置及校准弹簧 9 3.7 校准栏杆机臂位置 10 4. 电源连接 10 5. MLC控制器 11 5.1 命令发生器：在不同操作模式下的连接及功能 12 5.2 MLC控制器的操作 14 5.3 MLC控制器显示信息的解释 14 5.4 MLC控制器的复位 14 5.5 栏杆机的操作 15 5.6 编制及读取操作数据 16 5.7 校准感应线圈 18 6. 初始化操作 19 6.1 委托程序 19 6.2 在启动过程中显示的信息 19 7. 技术数据 21 7.1 栏杆机 21 7.2 控制器 21 8. 附录 22 8.1校准角度传感器及优化栏杆机的动作22 8.2 校准安全设备的角度 24 8.3 读取时间计数器 25 8.4 读取操作循环计数器 25 8.5 读取制动设置 25 8.6 复位情况的说明 26 8.7 测试模式 27 8.8 校准传感器 28 9. 技术支持 28 10. 备用零部件 29

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EPC25 EPC30 EF(D)30 ETD29 EER28(L) 30-50WEI28 EER28(L) ETD29 EF(D)30 EER35 50-70WEER28L ETD34 EER35 ETD39 70-100WETD34 EER35 ETD39 EER40 E21 摘自 InternationalRectifier,AN1018- “应用 IRIS40xx 系列单片集成开关 IC 开关电源的反激式变压器设计” B、ELYTON公司https://www.wendangku.net/doc/af3526552.html, 型号输出功率（ W） <5 5-10 10-20 20-50 50-100 100-200 200-500 500-1K

EI EI12.5 EI16 EI19 EI25 EI40 -- EI50 EI60 EE EE13 EE16 EE19 EE25 EE40 EE42 EE55 EE65 EF EF12.6 EF16 EF20 EF25 EF30 EF32 EFD -- EFD12 EFD15 EFD20 EFD25 EFD30 EPC -- EPC13 EPC17 EPC19 EPC25 EPC30 EER EER9.5 EER11 EER14.5 EER28 EER35 EER42 EER49 -- ETD ETD29 ETD34 ETD44 ETD49 ETD54 -- EP EP10 EP13 EP17 EP20 -- RM RM4 RM5 RM6 RM10 RM12 POT POT1107 POT1408 POT1811 POT2213POT3019 POT3622 POT4229 -- PQ -- -- -- PQ2016 PQ2625 PQ3230 PQ3535 PQ4040 EC ---------------------------- -- EC35 EC41 EC70 摘自 PowerTransformers OFF-LINE Switch Mode APPLICATION NOTES

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Magnetic TOLL栏杆机中文说明书

9 电气连接 9.1 安全请参照18页，第2.6节“专业安全和特殊危险”中的安全注意事项。电压危险一般警告

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在施工过程中，必须穿戴以下几种保护装备： ■工作服 ■保护手套 ■安全鞋 ■保护头盔。 9.2安装电保护设备根据地区或当地的规定，安全设备需要提供给客户。通常有以下几种：■漏电保护器 ■断路器 ■ EN 60947-3的可锁定的2极开关。 9.3连接电源线电压危险注意！电源线的导线截面在1.5到4mm2 之间。要遵守国家关于导线长度和相关电缆截面积的规定.

危险！电压有致命的危险！ 1.断开栏杆机系统电源。确保系统断电。确保机器不会再启动。接线的准备—剥电缆外皮和铁芯绝缘 2.照下图剥开电源线和磁芯图37：剥电源供应线。 1 电位 2 零线 3 地线安置电源线 3.照下图，把电源线正确安装在相应的终端线夹上。也可参照，163页，第17.1节的“接线图”。 ■在机箱中正确安装电源线。此电源线不可连接移动部件。 ■用两个束线带固定电源线。图38 安置电源线 1 电源线

2 束线带 3 束线带的金属突出物连接电源线图39：连接电源线 1 电源线的终端线夹 2 电位L 3 零线 N 4 地线 PE 9.4连接控制线路（信号设备）以下连接对控制和反馈端有效： ■控制栏杆机的8个数码输入 ■反馈信息的4个数码输出 ■反馈信息的6个继电器输出。3个常开，3个转换触点。危险！电压有致命危险！ 1.断开栏杆机系统电源。确保系统断电并不会重启。连接控制线 2.将控制线穿过穿线孔。 ■在机箱中合理的放置控制线。控制线不可进入可移动部件。 ■安装控制线夹和绑线。通过轻微按压或移动，线夹可以在轨道上移动到预期的位置。绑线可以绑扎在金属突出物上。 3. 根据接线图连接控制线。请参照163页，第17.1节的“接线图”。

磁芯参数表

常用磁芯参数表【EER磁芯】 ■ 用途：高频开关电源变压器、匹配变压器、扼流变压器等。【EE磁芯】 ■ 用途：电源转换用变压器及扼流圈、通讯及其他电子设备变压器、滤波器、电感器及扼流圈、脉冲变压器等。

【ETD磁芯】 ■ 用途：电源转换用变压器及扼流圈、通讯及其他电子设备变压器、滤波器。【EI 磁芯】 ■ 用途：高频开关电源变压器、功率变压器、整流变压器、电压互感器等。【ET 磁芯】 ■ 用途：滤波变压器【EFD 磁芯】 ■ 用途：高频开关电源变压器器、整流变压器、开关变压器等。

【UF 磁芯】 ■ 用途：整流变压器、脉冲变压器、扼流变压器、电源变压器等。【PQ 磁芯】 ■ 用途高频开关电源变压器、整流变压器等。【RM 磁芯】 ■ 用途：高频开关电源变压器、整流变压器、屏蔽变压器、脉冲变压器、脉冲功率变压器、扼流变压器、滤波变压器。【EP 磁芯】 ■ 用途：功率变压器、宽频变压器、屏蔽变压器、脉冲变压器等。

【H 磁芯】 ■ 用途：宽带变压器、脉冲变压器、脉冲功率变压器、隔离变压器、滤波变压器、扼流变压器、匹配变压器等。软磁铁氧体磁芯形状与尺寸标准(一) 软磁铁氧体磁芯形状软磁铁氧体是软磁铁氧体材料和软磁铁氧体磁芯的总称。软磁铁氧体磁芯是用软磁铁氧体材料制成的元件或零件，或是由软磁铁氧体材料根据不同形式组成的磁路。磁芯的形状基本上由成型（形）模具决定，而成型（形）模具又根据磁芯的形状进行设计与制造。磁芯按磁力线的路径大致可分两大类；磁芯按具体形状分，有各种各样：磁芯按磁力线路径分类磁芯按使用时磁化过程所产生磁力线的路径可分为开路磁芯和闭路磁芯两类。第一类为开路磁芯。这类磁芯的磁路是开启的（open magnetic circuits），通过磁芯的磁通同时要通过周围空间（气隙）才能形成闭合磁路。开路磁芯的气隙占磁路总长度的相当部分，磁阻很大，磁路中的部分磁通在达到气隙以前就已离开磁芯形成漏磁通。因而，开路磁芯在磁路各个截面上的磁通不相等，这是开路磁芯的特点。由于开路磁芯存在大的气隙，磁路受到退磁场作用，使磁芯的有效磁导率μe比材料的磁导率μi有所降低，降低的程度决定于磁芯的几何形状及尺寸。开路磁芯有棒形、螺纹形、管形、片形、轴向引线磁芯等等。IEC 1332《软磁铁氧体材料分类》标准中称开路磁芯为OP类磁芯。第二类磁芯为闭路磁芯。这类磁芯的磁路是闭合的（closed magnetic circuits），或基本上是闭合的。IEC 1332称闭路磁芯为CL类磁芯。磁路完全闭合的磁芯最典型的是环形磁芯。此外，还有双孔磁芯、多孔磁芯等等。

栏杆机控制器

MLC 580C N ,5131/04.02Phone:+49 7622/695-5Fax:+49 7622/695-602 e-mail:info@ac-magnetic.de https://www.wendangku.net/doc/af3526552.html,

Magnetic Control Systems Sdn.Bhd.No.16, Jalan Kartunis U1/47Temasya Ind.Park, Section U140150 Shah Alam, Selangor Darul Ehsan, Malaysia Phone:(+60) 3 / 55691718eMail: info@https://www.wendangku.net/doc/af3526552.html,.my Magnetic Control Systems (Shanghai) Co. Ltd.999 Ning-qiao Road, Bldg. 2W/1F Pudong New Area Shanghai 201206, China Phone:(+86) 21/ 58 341717eMail: magnetic@https://www.wendangku.net/doc/af3526552.html, Magnetic Automation Pty. Ltd.19 Beverage Drive Tullamarine, Victoria 3043, Australia Phone:(+61) 3 / 93 30 10 33eMail: info@https://www.wendangku.net/doc/af3526552.html, Magnetic Automation Corp.3160 Murrell Road Rockledge, FL 32955, USA Phone:(+1) 321/ 635 85 85eMail: info@https://www.wendangku.net/doc/af3526552.html, Magnetic Autocontrol Pvt.Ltd.Calve Chateau, 2B, IInd Floor Kilpauk 322 Poonamallee High Road IND Chennai, 600010 / India Phone:(+91) 44 6400 443eMail: magneticsales@https://www.wendangku.net/doc/af3526552.html,

德国magnetic栏杆机常见故障分析

德国Magnetic栏杆机的常见故障分析德国Magnetic自动栏杆机的核心部分是MLC控制器，控制器设置的正确与否直接影响栏杆机的正常工作。当栏杆机工作不正常时，请先确认是否是栏杆机的问题，是栏杆机哪个部分出现问题（如机械部分或控制部分），建议先将其他车道工作正常栏杆机控制器换到本车道，以确认是否是控制器出现问题；如果互换控制器后栏杆机工作正常，那么就确认本车道控制器有问题，请参照工作正常的控制器设置即可；如控制器重新设置后仍不能解决问题，请将控制器返回厂家维修。以下是德国Magnetic自动栏杆机控制器的几种常见设置，可供参考。 1、控制器黑色按键和白色按键的作用： ?黑键：1）、手动控制抬杆； 2）、控制器编程时改变数值； 3）、控制器编程完毕后保存 ?白键：1）、手动控制落杆； 2）、控制器编程时确认数值； 3）、控制器编程完毕后不保存。 ?编程时，同时按下黑键和白键后数值下边出现光标。 ?同时按下黑键和白键持续四秒钟，控制器重启。 2、MLC控制器复位： ?同时按下黑键和白键持续四秒钟； ?将圆盘转至F，确认后可恢复到出厂设置； ?详见中文说明书第14页。 3、控制器圆盘开关各位置的功能位置0：普通操作模式位置1：程序代码 1—8

位置2：转矩时间 1—30秒位置3：栏杆机开启时间 1—255秒位置4：感应线圈A灵敏度 O一9 (0最小，9最大) 位置5：感应线圈B灵敏度 0—9(0最小，9最大) 位置6：检测器模式A0—8(见功能说明表) 位置7：检测器模式B0—8(见功能说明表) 位置8：感应线圈A／B频率 1 0，000Hz一90，000Hz 位置9：备用位置A：计数模式位置B：备用位置C：备用位置D：硬件错误控制器 16进制错误代码位置E：语种选择德、英、法、西位置F：出厂设置重设所有操作数据 4、模式设置：将圆盘转至1，控制器有8种操作模式可供选择；详见中文说明书第16页。 5、控制器编程过程：（1）将圆盘开关转到所需位置；（2）同时按下黑色按键和白色按键；（3）使用黑色按键将数字滚动显示为所需的数值（光标位于正在变化的数字下方）；（4）按下白色按键存储选中的数值或者将光标移到右边的一格；（5）按下黑色按键确认最终的数值或者按下白色按键取消输入的数值。注意：完成编程后，请将圆盘开关转回到“0”位置（即普通操作模式） 6、感应线圈灵敏度设置：将圆盘转至4或5（设置线圈A转至4，线圈B转至5）；一般情况下灵敏度选择4-6，不宜太高或太低。详见中文说明书第16页。 7、检测器A、B的开启和关闭将圆盘开关转至6和7分别设置检测器A、B的状态，如果A、B线圈都没有使用或只使用了一个检测器，那么就要关闭没有使用的检测器（将检测器A、B的数值设置为0，是关闭状态；检测器开启时数值是应该是1或2，一般用2。） 8、校准传感器/优化栏杆机动作

开关电源参数计算

（1）输入电压：185V AC~240V AC （2）输出电压1：+5VDC ，额定电流1A ，最小电流750mA ；（3）输出电压2：+12VDC ，额定电流1A ，最小电流100mA ；（4）输出电压3：-12VDC ，额定电流1A ，最小电流100mA ；（5）输出电压4：+24VDC ，额定电流1.5A ，最小电流250mA ；（6）输出电压纹波：+5V ，±12V ：最大100mV （峰峰值）；+24V ：最大250mV （峰峰值）（7）输出精度：+5V ，±12V ：最大± 5%；+24V ：最大± 10%；（8）效率：大于80% 3. 参数计算（1）输出功率： 5V 112V 1224V 1.565 out P A A A W =?+??+?= （3-1）（2）输入功率： 6581.2580%0.8 out in P W P W = == （3-2）（3）直流输入电压：采用单相桥式不可控整流电路 (max)240VAC 1.414=340VDC in V =? （3-3） (min)185VAC 1.414=262VDC in V =? （3-4）（4）最大平均电流： (m a x ) (m i n )81.25 0.31262in in in P W I A V V == = （3-5）（5）最小平均电流： (min)(max) 81.250.24340 in in in P W I A V = = = （3-6）（6）峰值电流：可以采用下面两种方法计算，本文采用式（3-8）的方法。

(min)max (min)(min)225581.25 1.550.4262out out out Pk C in in in P P P W I I A V D V V V ?== ====? （3-7） min 5.5 5.581.25 1.71262out Pk C in P W I I A V V ?== == （3-8）（7）散热：基于MOSFET 的反激式开关电源的经验方法：损耗的35%是由MOSFET 产生，60%是由整流部分产生的。开关电源的损耗为： (180%)81.25 20%16.25D in P P W W =?-=?= （3-9） MOSFET 损耗为： 35%16.2535% 5.69D MOSFET D P P W W -=?=?= （3-10）整流部分损耗： (5)55( )60%()16.2560%0.756565D V D W W P P W W W W +=??=??= （3-11） (12)12122()60%2()16.2560% 3.66565D V D W W P P W W W W ±=???=???= （3-12） (242)3636()60%()16.2560% 5.46565D V D W W P P W W W W +=??=??= （3-13）（8）变压器磁芯：采用天通的EER40/45，饱和磁通密度Bs 在25℃时大于500mT ，在100℃时大于390mT 。窗口有效截面积Ae=152.42mm 2。所以，取 max 11 0.390.222 s B B T T = =?≈ （3-14） Ae=152.42mm 2 （3-15）（9）开关电源频率： 40f khz = （3-16）（10）开关电源最大占空比： max 0.4D = （3-17）

磁芯各参数详解

一、磁芯初始磁导率磁感应强度与磁场强度的比值称为磁导率。初始磁导率高：相同圈数感值大，反之亦然；初始磁导率高：相同电流下容易饱和，反之亦然；初始磁导率高：低频特性好，高频差，反之亦然；初始磁导率高：相同产品价格高，反之亦然； 1、磁导率的测试仪器功能磁导率的测量是间接测量，测出磁心上绕组线圈的电感量，再用公式计算出磁心材料的磁导率。所以，磁导率的测试仪器就是电感测试仪。在此强调指出，有些简易的电感测试仪器，测试频率不能调，而且测试电压也不能调。例如某些电桥，测试频率为100Hz 或1kHz，测试电压为0.3V，给出的这个0.3V并不是电感线圈两端的电压，而是信号发生器产生的电压。至于被测线圈两端的电压是个未知数。如果用高档的仪器测量电感，例如Agilent 4284A精密LCR测试仪，不但测试频率可调，而且被测电感线圈两端的电压及磁化电流都是可调的。了解测试仪器的这些功能，对磁导率的正确测量是大有帮助的。 2、材料磁导率的测量方法和原理说起磁导率μ的测量，似乎非常简单，在材料样环上随便绕几匝线圈，测其电感，

找个公式一算就完了。其实不然，对同一只样环，用不同仪器，绕不同匝数，加不同电压或者用不同频率都可能测出差别甚远的磁导率来。造成测试结果差别极大的原因，并非每个测试人员都有精力搞得清楚。本文主要讨论测试匝数及计算公式不同对磁导率测量的影响。 2.1 计算公式的影响大家知道，测量磁导率μ的方法一般是在样环上绕N匝线圈测其电感L，因为可推得L的表达式为： L=μ0 μN 2A/l （1）所以，由（1）式导出磁导率的计算公式为： μ=Ll/μ0N 2A（2）式中：l为磁心的磁路长度，A为磁心的横截面积。对于具有矩形截面的环型磁芯，如果把它的平均磁路长度l=π（D+d）/2就当作磁心的磁路长度l，把截面积A=h（D-d）/2，μ0=4π×10-7都代入（2）式得二、饱和磁通密度 1.什么是磁通：磁场中垂直通过某一截面的磁感应线总数，称为磁通量（简称磁通） 2.什么是磁通密度：单位面积垂直通过的磁感应线的总数（磁通量）称为磁通密度，磁通密度即磁感应强度。

电源磁芯尺寸功率参数

EPC功率磁芯电气特性及有效参数

注：AL值测试条件为1KHz,0.25v,100Ts,25±3℃ Pc值测试条件为100KHz,200mT,100℃ EE、EEL、EF型功率磁芯

特点：引线空间大，绕制接线方便。适用围广、工作频率高、工作电压围宽、输出功率大、热稳定性能好用途：广泛应用于程控交换机电源、液晶显示屏电源、大功率UPS逆变器电源、计算机电源、节能灯等领域。 EE、EEL、EF型功率磁芯尺寸规格 Dimensions(mm)尺寸磁芯型号TYP A B C D Emin F EE5/5.3/2 5.25±0.15 2.65±0.15 1.95±0.15 1.35±0.15 3.80 2.00±0.15 EE8.3/8.2/3.6 8.30±0.30 4.00±0.25 3.60±0.20 1.85±0.20 6.00 3.00±0.15 EE10/11/4.8 10.20±0.30 5.60±0.30 4.80±0.25 2.50±0.257.50 4.40±0.30 EE12.8/15/3.6 12.70±0.307.40±0.30 3.60±0.25 3.60±0.258.60 5.50±0.30 EE13/12/6 13.20±0.30 6.10±0.30 5.90±0.30 2.70±0.309.80 4.70±0.30 EE13/13W 13.00±0.40 6.50±0.30 9.80±0.30 3.60±0.209.00 4.60±0.20 EE16/14/5 16.10±0.407.10±0.30 4.80±0.30 4.00±0.3011.70 5.20±0.20 EE16/14W 16.10±0.407.25±0.30 6.80±0.30 3.20±0.3512.50 5.60±0.30 EE19/16/5 19.10±0.408.00±0.30 4.85±0.30 4.85±0.3014.00 5.60±0.30 EE19/16W 19.30±0.408.30±0.307.90±0.30 4.80±0.3014.00 5.70±0.30 EE22/19/5.7 22.00±0.509.50±0.30 5.70±0.30 5.70±0.3015.60 5.70±0.30 EE25/20/6 25.40±0.5010.00±0.30 6.35±0.30 6.35±0.3018.60 6.80±0.30

开关电源磁芯主要参数

第5章开关电源磁芯主要参数 5.1 概述 5.1.1 在开关电源中磁性元件的作用这里讨论的磁性元件是指绕组和磁心。绕组可以是一个绕组，也可以是两个或多个绕组。它是储能、转换和/或隔离所必备的元件，常把它作为变压器或电感器使用。作为变压器用，其作用是：电气隔离；变比不同，达到电压升、降；大功率整流副边相移不同，有利于纹波系数减小；磁耦合传送能量；测量电压、电流。作为电感器用，其作用是：储能、平波、滤波；抑制尖峰电压或电流，保护易受电压、电流损坏的电子元件；与电容器构成谐振，产生方向交变的电压或电流。 5.1.2 掌握磁性元件对设计的重要意义磁性元件是开关变换器中必备的元件，但又不易透彻掌握其工作情况（包括磁材料特性的非线性，特性与温度、频率、气隙的依赖性和不易测量性）。在选用磁性元件时，不像电子元件可以有现成品选择。为何磁性元件绝大多数都要自行设计呢？主要是变压器和电感器涉及的参数太多，例如：电压、电流、频率、温度、能量、电感量、变比、漏电感、磁材料参数、铜损耗、铁损耗等等。磁材料参数测量困难，也增加了人们的困惑感。就以Magnetics公司生产的其中一种MPP铁心材料来说，它有10种μ值，26种尺寸，能在5种温升限额下稳定工作。这样，便有10×26×5= 1300种组合，再加上前述电压、电流等电参数不同额定值的组合，将有不计其数的规格，厂家为用户备好现货是不可能的。果真有现货供应，介绍磁元件的特性、参数、使用条件的数据会非常繁琐，也将使挑选者无从下手。因此，绝大多数磁元件要自行设计或提供参数委托设计、加工。本章将介绍磁元件的一般特性，针对使用介绍设计方法。结合线性的具体形式的设计方法，以后还将进一步的介绍。 5.1.3 磁性材料基本特性的描述磁性材料的特性首先用B-H平面上的一条磁化曲线来描述。以μ表示B/H，数学上称为斜率，表示为tanθ=B/h；电工上称为磁导率，如图5.1所示。由于整条曲线多处弯曲，因此有多个μ值称呼。另外，从不同角度考查也有不同称呼。

栏杆机

栏杆机 3.5基本机械结构 1.栏杆机臂 2.设置弹簧拉力的调节螺丝，带有安全夹 3.凸缘轴的紧固柄 4.橡胶缓冲块 5.连接件 6.电机的紧固柄警告：弹簧收紧后，弹簧及栏杆机臂对驱动装置（BDU）是加了相当大的力并因此产生了潜在的发生伤害的危险。因此任何对于栏杆机臂驱动装置（BDU）的工作，必须在弹簧未被收紧并且栏杆机臂确保安全或被卸下的情况下才可以进行！ 3.6测试/校准弹簧所有栏杆机在生产工厂中都根据原配的栏杆机臂做了设置.但在使用时安装完栏杆机臂后进行栏杆机的第一次操作前,应该检查栏杆机臂的设置。在栏杆机臂的重量被弹簧施加的拉力所平衡的情况下，栏杆机才可以正确运作。因此任何对于栏杆机臂的变动都必须根据如下步骤进行重新校准。测试弹簧设置： 1.打开栏杆机箱体的门，卸下安装板，开启并取去封盖。 2.拔下电源插头。 3.手工将栏杆机臂调到约45°C角的位置后放开手。如果栏杆机臂稳定在此位置不动，说明此时弹簧的调整是正确。校准弹簧设置： 1．取下两个弹簧调节螺杆上的两个安全夹。同时拧紧或放松左右两根调节螺杆直至栏杆机臂在45°C角的位置保持稳定。 2．重新装上调节螺杆安全夹。例外情况: 当栏杆机被设置为在发生电源故障的情况下自动打开，就需要比上面提到的更大的弹簧拉力（只有在栏杆机臂长度最大为3.5M 的情况下）。请注意如果栏杆机在生产工厂中特别设置为这种打开方式，那么栏杆机臂在水平终点位置时不会锁止！ 3.7校准栏杆机臂位置要校准栏杆机臂位置（例如，在施加过度的力之后），请根据如下步骤进行： 1.打开栏杆机箱体的门，卸下安装板，开启并取出封盖。 2.按下黑色按键升起栏杆机臂。 3.将MLC控制器前面板上的旋转选择开关(图S0227)转到位置“1” 4.松开凸缘轴的紧固柄上的两个紧固螺钉，使得可以用手将栏杆机臂重新定位。 5.校准栏杆机臂的位置（垂直位置）。 6.使用扭矩扳手重新拧紧两个紧固螺钉（72Nm）. 7.将MLC控制器选择开关(图S0227)转回到位置“0”。 4.电源连接

高速公路自动栏杆机控制模块维修实例

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