{"title":"A Noncontact Method for Measuring the Charge of a Moving Object Based on Mutual Capacitance Matrix","authors":"Zhongzheng He;Sichao Qin;Juan Wu;Yu Qiao;Pengfei Li;Xi Chen","doi":"10.1109/JSEN.2024.3524277","DOIUrl":null,"url":null,"abstract":"The charge quantity is a fundamental physical parameter that reflects the electrical state of an object. Accurately estimating the charge of an object facilitates the assessment of electrostatic discharge risks and aids in preventing accidents. Measuring the charge of a moving object has long posed a technical challenge in this field. This article proposes a noncontact method for estimating the charge of a moving object by using the electrostatic signals generated by the object’s motion and its motion data. First, a noncontact charge measurement model based on a mutual capacitance matrix was developed using the image charge method in electrostatics. The accuracy of the model was verified through simulations of the charge on the sensing electrode. Next, a correction method for charge calculation was further proposed to reduce measurement errors caused by parasitic capacitance from the experimental setup. Finally, a verification experiment was conducted, wherein an electrometer measured the charge of the object in a stationary state, providing a reference to validate the proposed method. The experimental results demonstrated a strong correlation (<inline-formula> <tex-math>${r}~\\gt 0.96$ </tex-math></inline-formula>) and consistency (within the 95% confidence interval) between the measured and reference values across various conditions. The absolute error of the measurements was within ±1 nC (mean ± standard deviation: <inline-formula> <tex-math>$- 0.04~\\pm ~0.4$ </tex-math></inline-formula> nC), with a relative error of approximately ±10%. This study contributes to the prevention of electrostatic discharge accidents involving moving objects and presents novel insights and technological approaches for electrostatic detection.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6940-6951"},"PeriodicalIF":4.3000,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10832526/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
The charge quantity is a fundamental physical parameter that reflects the electrical state of an object. Accurately estimating the charge of an object facilitates the assessment of electrostatic discharge risks and aids in preventing accidents. Measuring the charge of a moving object has long posed a technical challenge in this field. This article proposes a noncontact method for estimating the charge of a moving object by using the electrostatic signals generated by the object’s motion and its motion data. First, a noncontact charge measurement model based on a mutual capacitance matrix was developed using the image charge method in electrostatics. The accuracy of the model was verified through simulations of the charge on the sensing electrode. Next, a correction method for charge calculation was further proposed to reduce measurement errors caused by parasitic capacitance from the experimental setup. Finally, a verification experiment was conducted, wherein an electrometer measured the charge of the object in a stationary state, providing a reference to validate the proposed method. The experimental results demonstrated a strong correlation (${r}~\gt 0.96$ ) and consistency (within the 95% confidence interval) between the measured and reference values across various conditions. The absolute error of the measurements was within ±1 nC (mean ± standard deviation: $- 0.04~\pm ~0.4$ nC), with a relative error of approximately ±10%. This study contributes to the prevention of electrostatic discharge accidents involving moving objects and presents novel insights and technological approaches for electrostatic detection.
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