[{"main_file_link":[{"url":"https://ieeexplore.ieee.org/document/9954484"}],"conference":{"end_date":"2022-09-29","location":"Miltenberg, Germany","name":"2022 Kleinheubach Conference","start_date":"2022-09-27"},"title":"AI Assisted Interference Classification to Improve EMC Troubleshooting in Electronic System Development","author":[{"last_name":"Maalouly","full_name":"Maalouly, Jad","first_name":"Jad"},{"first_name":"Dennis","last_name":"Hemker","full_name":"Hemker, Dennis"},{"first_name":"Christian","last_name":"Hedayat","full_name":"Hedayat, Christian"},{"full_name":"Rückert, Christian","last_name":"Rückert","first_name":"Christian"},{"full_name":"Kaufmann, Ivan","last_name":"Kaufmann","first_name":"Ivan"},{"full_name":"Olbrich, Marcel","last_name":"Olbrich","first_name":"Marcel"},{"last_name":"Lange","full_name":"Lange, Sven","id":"38240","first_name":"Sven"},{"first_name":"Harald","last_name":"Mathis","full_name":"Mathis, Harald"}],"date_created":"2022-11-24T14:21:17Z","publisher":"IEEE","date_updated":"2022-11-24T14:21:34Z","citation":{"apa":"Maalouly, J., Hemker, D., Hedayat, C., Rückert, C., Kaufmann, I., Olbrich, M., Lange, S., &#38; Mathis, H. (2022). AI Assisted Interference Classification to Improve EMC Troubleshooting in Electronic System Development. <i>2022 Kleinheubach Conference</i>. 2022 Kleinheubach Conference, Miltenberg, Germany.","mla":"Maalouly, Jad, et al. “AI Assisted Interference Classification to Improve EMC Troubleshooting in Electronic System Development.” <i>2022 Kleinheubach Conference</i>, IEEE, 2022.","bibtex":"@inproceedings{Maalouly_Hemker_Hedayat_Rückert_Kaufmann_Olbrich_Lange_Mathis_2022, place={Miltenberg, Germany}, title={AI Assisted Interference Classification to Improve EMC Troubleshooting in Electronic System Development}, booktitle={2022 Kleinheubach Conference}, publisher={IEEE}, author={Maalouly, Jad and Hemker, Dennis and Hedayat, Christian and Rückert, Christian and Kaufmann, Ivan and Olbrich, Marcel and Lange, Sven and Mathis, Harald}, year={2022} }","short":"J. Maalouly, D. Hemker, C. Hedayat, C. Rückert, I. Kaufmann, M. Olbrich, S. Lange, H. Mathis, in: 2022 Kleinheubach Conference, IEEE, Miltenberg, Germany, 2022.","chicago":"Maalouly, Jad, Dennis Hemker, Christian Hedayat, Christian Rückert, Ivan Kaufmann, Marcel Olbrich, Sven Lange, and Harald Mathis. “AI Assisted Interference Classification to Improve EMC Troubleshooting in Electronic System Development.” In <i>2022 Kleinheubach Conference</i>. Miltenberg, Germany: IEEE, 2022.","ieee":"J. Maalouly <i>et al.</i>, “AI Assisted Interference Classification to Improve EMC Troubleshooting in Electronic System Development,” presented at the 2022 Kleinheubach Conference, Miltenberg, Germany, 2022.","ama":"Maalouly J, Hemker D, Hedayat C, et al. AI Assisted Interference Classification to Improve EMC Troubleshooting in Electronic System Development. In: <i>2022 Kleinheubach Conference</i>. IEEE; 2022."},"place":"Miltenberg, Germany","year":"2022","publication_status":"published","publication_identifier":{"eisbn":["978-3-948571-07-8"]},"language":[{"iso":"eng"}],"keyword":["emc","pcb","electronic system development","machine learning","neural network"],"user_id":"38240","department":[{"_id":"59"},{"_id":"485"}],"project":[{"_id":"52","name":"PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing"}],"_id":"34140","status":"public","abstract":[{"text":"In this paper, machine learning techniques will be used to classify different PCB layouts given their electromagnetic frequency spectra. These spectra result from a simulated near-field measurement of electric field strengths at different locations. Measured values consist of real and imaginary parts (amplitude and phase) in X, Y and Z directions. Training data was obtained in the time domain by varying transmission line geometries (size, distance and signaling). It was then transformed into the frequency domain and used as deep neural network input. Principal component analysis was applied to reduce the sample dimension. The results show that classifying different designs is possible with high accuracy based on synthetic data. Future work comprises measurements of real, custom-made PCB with varying parameters to adapt the simulation model and also test the neural network. Finally, the trained model could be used to give hints about the error’s cause when overshooting EMC limits.","lang":"eng"}],"type":"conference","publication":"2022 Kleinheubach Conference"},{"title":"Far-field prediction combining simulations with near-field measurements for EMI assessment of PCBs","publisher":" The Institution of Engineering and Technology (IET)","date_created":"2021-03-18T13:49:49Z","year":"2020","edition":"1","keyword":["Huygens' box","NF-to-FF transformation","efficient FF radiation model","FF behaviour","EMI assessment","PCB","near-field measurements","efficient radiation model","far-field behaviour","RF design process","far-field prediction","Huygens'box principle","fullwave simulation","electronic system radiation","equivalent radiation source","electromagnetic simulation tool","near-field scan data","EM compatibility failure reduction"],"language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"Using near-field (NF) scan data to predict the far-field (FF) behaviour of radiating electronic systems represents a novel method to accompany the whole RF design process. This approach involves so-called Huygens' box as an efficient radiation model inside an electromagnetic (EM) simulation tool and then transforms the scanned NF measured data into the FF. For this, the basic idea of the Huygens'box principle and the NF-to-FF transformation are briefly presented. The NF is measured on the Huygens' box around a device under test using anNF scanner, recording the magnitude and phase of the site-related magnetic and electric components. A comparison between a fullwave simulation and the measurement results shows a good similarity in both the NF and the simulated and transformed FF.Thus, this method is applicable to predict the FF behaviour of any electronic system by measuring the NF. With this knowledge, the RF design can be improved due to allowing a significant reduction of EM compatibility failure at the end of the development flow. In addition, the very efficient FF radiation model can be used for detailed investigations in various environments and the impact of such an equivalent radiation source on other electronic systems can be assessed."}],"publication":"Tensorial Analysis of Networks (TAN) Modelling for PCB Signal Integrity and EMC Analysis","main_file_link":[{"url":"https://digital-library.theiet.org/content/books/10.1049/pbcs072e_ch14"}],"doi":"10.1049/pbcs072e_ch14","date_updated":"2022-01-06T06:55:03Z","author":[{"full_name":"Schröder, Dominik","last_name":"Schröder","first_name":"Dominik"},{"id":"38240","full_name":"Lange, Sven","last_name":"Lange","first_name":"Sven"},{"full_name":"Hangmann, Christian","last_name":"Hangmann","first_name":"Christian"},{"first_name":"Christian","last_name":"Hedayat","full_name":"Hedayat, Christian"}],"place":"Croyton, UK","citation":{"ama":"Schröder D, Lange S, Hangmann C, Hedayat C. Far-field prediction combining simulations with near-field measurements for EMI assessment of PCBs. In: <i>Tensorial Analysis of Networks (TAN) Modelling for PCB Signal Integrity and EMC Analysis</i>. 1st ed. Croyton, UK:  The Institution of Engineering and Technology (IET); 2020:315-346 (32). doi:<a href=\"https://doi.org/10.1049/pbcs072e_ch14\">10.1049/pbcs072e_ch14</a>","chicago":"Schröder, Dominik, Sven Lange, Christian Hangmann, and Christian Hedayat. “Far-Field Prediction Combining Simulations with near-Field Measurements for EMI Assessment of PCBs.” In <i>Tensorial Analysis of Networks (TAN) Modelling for PCB Signal Integrity and EMC Analysis</i>, 1st ed., 315-346 (32). Croyton, UK:  The Institution of Engineering and Technology (IET), 2020. <a href=\"https://doi.org/10.1049/pbcs072e_ch14\">https://doi.org/10.1049/pbcs072e_ch14</a>.","ieee":"D. Schröder, S. Lange, C. Hangmann, and C. Hedayat, “Far-field prediction combining simulations with near-field measurements for EMI assessment of PCBs,” in <i>Tensorial Analysis of Networks (TAN) Modelling for PCB Signal Integrity and EMC Analysis</i>, 1st ed., Croyton, UK:  The Institution of Engineering and Technology (IET), 2020, pp. 315-346 (32).","mla":"Schröder, Dominik, et al. “Far-Field Prediction Combining Simulations with near-Field Measurements for EMI Assessment of PCBs.” <i>Tensorial Analysis of Networks (TAN) Modelling for PCB Signal Integrity and EMC Analysis</i>, 1st ed.,  The Institution of Engineering and Technology (IET), 2020, pp. 315-346 (32), doi:<a href=\"https://doi.org/10.1049/pbcs072e_ch14\">10.1049/pbcs072e_ch14</a>.","bibtex":"@inbook{Schröder_Lange_Hangmann_Hedayat_2020, place={Croyton, UK}, edition={1}, title={Far-field prediction combining simulations with near-field measurements for EMI assessment of PCBs}, DOI={<a href=\"https://doi.org/10.1049/pbcs072e_ch14\">10.1049/pbcs072e_ch14</a>}, booktitle={Tensorial Analysis of Networks (TAN) Modelling for PCB Signal Integrity and EMC Analysis}, publisher={ The Institution of Engineering and Technology (IET)}, author={Schröder, Dominik and Lange, Sven and Hangmann, Christian and Hedayat, Christian}, year={2020}, pages={315-346 (32)} }","short":"D. Schröder, S. Lange, C. Hangmann, C. Hedayat, in: Tensorial Analysis of Networks (TAN) Modelling for PCB Signal Integrity and EMC Analysis, 1st ed.,  The Institution of Engineering and Technology (IET), Croyton, UK, 2020, pp. 315-346 (32).","apa":"Schröder, D., Lange, S., Hangmann, C., &#38; Hedayat, C. (2020). Far-field prediction combining simulations with near-field measurements for EMI assessment of PCBs. In <i>Tensorial Analysis of Networks (TAN) Modelling for PCB Signal Integrity and EMC Analysis</i> (1st ed., pp. 315-346 (32)). Croyton, UK:  The Institution of Engineering and Technology (IET). <a href=\"https://doi.org/10.1049/pbcs072e_ch14\">https://doi.org/10.1049/pbcs072e_ch14</a>"},"page":"315-346 (32)","publication_status":"published","publication_identifier":{"isbn":["9781839530494","9781839530500"]},"related_material":{"record":[{"id":"21542","relation":"other","status":"public"}]},"project":[{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"_id":"21542","user_id":"38240","department":[{"_id":"485"}],"status":"public","type":"book_chapter"}]