为满足电机故障检测的需要,结合DSP精度高、数字信号处理能力强和ARM资源丰富、性能价格比高等特点,开发了一款基于TMS320F2812和S3C44B0X的双CPU结构的异步电动机故障检测装置。介绍了系统的主要功能并重点分析了系统采用的MCSA(Motor ...为满足电机故障检测的需要,结合DSP精度高、数字信号处理能力强和ARM资源丰富、性能价格比高等特点,开发了一款基于TMS320F2812和S3C44B0X的双CPU结构的异步电动机故障检测装置。介绍了系统的主要功能并重点分析了系统采用的MCSA(Motor Current Signature Analysis)技术、测量算法、快速傅里叶变换FFT和局部频谱的连续细化分析方法,给出了系统的硬件结构、软件框图和设计方案以及转子断条故障检测的实验结果。展开更多
This paper presents an approach for shunt faults detection and classification in transmission line using Support Vector Machine （SVM）. The paper compares between using three line post-fault current samples for one-h...This paper presents an approach for shunt faults detection and classification in transmission line using Support Vector Machine （SVM）. The paper compares between using three line post-fault current samples for one-half cycle and one-fourth cycle from the inception of the fault as inputs for SVM. Two SVMs are used, first SVMabc is used for faulty phase detection and second SVMg is used for ground detection. SVMs with polynomial kernel with different degrees are used to obtain the best classification score. The classification test results show that the proposed method is accurate and reliable.展开更多
文摘为满足电机故障检测的需要,结合DSP精度高、数字信号处理能力强和ARM资源丰富、性能价格比高等特点,开发了一款基于TMS320F2812和S3C44B0X的双CPU结构的异步电动机故障检测装置。介绍了系统的主要功能并重点分析了系统采用的MCSA(Motor Current Signature Analysis)技术、测量算法、快速傅里叶变换FFT和局部频谱的连续细化分析方法,给出了系统的硬件结构、软件框图和设计方案以及转子断条故障检测的实验结果。
文摘This paper presents an approach for shunt faults detection and classification in transmission line using Support Vector Machine （SVM）. The paper compares between using three line post-fault current samples for one-half cycle and one-fourth cycle from the inception of the fault as inputs for SVM. Two SVMs are used, first SVMabc is used for faulty phase detection and second SVMg is used for ground detection. SVMs with polynomial kernel with different degrees are used to obtain the best classification score. The classification test results show that the proposed method is accurate and reliable.
