[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123246-en":3,"doc-seo-123246-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123246,1099514067438,"River Wang","https://ap-avatar.wpscdn.com/avatar/100002539ee87300030?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780474512215547542",8,"Research & Report","Machine Learning Based Probe Skew Correction for High-frequency BH Loop Measurements","Experimental characterization of magnetic components is essential for modeling behavior in high-frequency PWM converters, where the BH loop measurement is a key electrical method to separate core loss. However, the measurement is sensitive to probe phase skew, which distorts the BH loop and introduces large core-loss errors. This work presents a machine-learning approach that identifies skew using correlations between skew and the measured loop’s shape/trajectory. Augmented training data are generated from measured waveforms, and a CNN pipeline predicts skew to compensate and output corrected core-loss and BH-loop results with strong accuracy and generalizability.","Wang, Y. , Liu, S. , Wang, J. , Cui, B. , & Yang, J. (2025) . Machine Learning Based Probe Skew Correction for High-frequency BH Loop Measurements. IEEE Transactions on Power Electronics. Advance online publication. [https://doi.org/10.1109/TPEL.2025.3564663](https://doi.org/10.1109/TPEL.2025.3564663)  \nPeer reviewed version  \nLicense (if available): CC BY  \nLink to published version (if available):  \n10.1109/TPEL.2025.3564663  \nLink to publication record on the Bristol Research Portal  \nPDF-document  \nThis is the accepted author manuscript (AAM) of the article which has been made Open Access under the University of Bristol's Scholarly Works Policy. The final published version (Version of Record) can be found on the publisher's website. The copyright of any third-party content, such as images, remains with the copyright holder.  \nUniversity of Bristol – Bristol Research Portal  \nGeneral rights  \nThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: [http://www.bristol.ac.uk/red/research-policy/pure/user-guides/brp-terms/](http://www.bristol.ac.uk/red/research-policy/pure/user-guides/brp-terms/)  \nMachine Learning Based Probe Skew Correction for High-frequency BH Loop Measurements  \nYakun Wang, Song Liu, Jun Wang, Member, IEEE, Binyu Cui, Student Member, IEEE, and Jingrong Yang, Student Member, IEEE  \nAbstract—Experimental characterization of magnetic components has grown to be increasingly important to understand and model their behaviours in high-frequency PWM converters. The BH loop measurement is the only available approach to separate the core loss as an electrical method, which, however, issusceptive to the probe phase skew. As an alternative to the regular de-skew approaches based on hardware, this work proposes a novel machine-learning-based method to identify and correct the probeskew, which builds on the newly discovered correlation between the skew and the shape/trajectory of the measured BH loop. A special technique is proposed to artificially generate skewed images from measured waveforms as augmented training sets. A machine learning pipeline is developed with the Convolutional Neural Network (CNN) to treat the problem as an image-based prediction task. The trained model has demonstrated a high accuracy and generalizability in identifying the skew value from a BH loop unseen by the model, which enables the compensation of the skew to yield the corrected core loss value and BH loop.  \nKeywords—machine learning, BH loop measurement, power magnetics, instrumentation, probe skew  \nI. INTRODUCTION  \nThe characterization of core loss for high-frequency magnetic components (e.g. Fig. 1(a)) used in power conversion applications has been increasingly important to inform the design and virtual prototyping of power converters. The most common method for measuring high-frequency core loss is the twowinding BH loop measurement approach shown in Fig. 1(b), due to its capability of separating the core loss (i.e. excluding the copper loss) and suitability for rapid testing under highfrequency excitations without the need for reaching a thermal equilibrium, compared to the calorimetric approaches.  \n(a) (b)  \nFig. 1. (a) magnetic component for high-frequency power electronics applications (b) Two-winding BH loop measurement  \nHowever, the most challenging aspect of the two-winding method is the phase discrepancy error caused by the different propagation delays between the voltage and current probes, known as the skew-the probe skew can lead to a distorted BH loop resulting in up to ±200% of error in the measured core loss [1] . Conventionally, probe skew can only be calibrated through  \nThis project has been supported by the Jean Golding Institute (JGI) for data science and data-intensive research at the University of Bristol. (Corresponding author: Jun Wang)  \ndeskew tools, such as Keysight U1880A or Lecroy DCS025, ","cbCais0vLaVwffBm","https://ap.wps.com/l/cbCais0vLaVwffBm","pdf",1333896,1,7,"English","en",105,"# Abstract\n# I. INTRODUCTION","[{\"question\":\"Why is probe phase skew a problem in BH loop measurements?\",\"answer\":\"Probe phase skew causes a phase discrepancy between voltage and current probes, distorting the measured BH loop and leading to substantial errors in the inferred core loss.\"},{\"question\":\"How does the proposed method correct probe skew?\",\"answer\":\"It learns a mapping between irregularities in the measured BH loop shape/trajectory and the skew value, then compensates the measurement to recover corrected core-loss and BH-loop outputs.\"},{\"question\":\"What role does machine learning and the CNN play in the pipeline?\",\"answer\":\"A supervised learning pipeline using a convolutional neural network treats skew identification as an image-based prediction task, enabling the model to estimate skew from an unseen BH loop.\"}]","Machine Learning Based Probe Skew Correction for High-frequency BH Loop Measurements | PDF",1785815436,18,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-based-probe-skew-correction-for-high-frequency-bh-loop-measurements","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-based-probe-skew-correction-for-high-frequency-bh-loop-measurements/123246/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is probe phase skew a problem in BH loop measurements?","Question",{"text":75,"@type":76},"Probe phase skew causes a phase discrepancy between voltage and current probes, distorting the measured BH loop and leading to substantial errors in the inferred core loss.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the proposed method correct probe skew?",{"text":80,"@type":76},"It learns a mapping between irregularities in the measured BH loop shape/trajectory and the skew value, then compensates the measurement to recover corrected core-loss and BH-loop outputs.",{"name":82,"@type":73,"acceptedAnswer":83},"What role does machine learning and the CNN play in the pipeline?",{"text":84,"@type":76},"A supervised learning pipeline using a convolutional neural network treats skew identification as an image-based prediction task, enabling the model to estimate skew from an unseen BH loop.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]