The data-driven fault diagnosis methods can improve the reliability of analog circuits by using the data generated from it. The data have some characteristics, such as randomness and incompleteness, which lead to the ...The data-driven fault diagnosis methods can improve the reliability of analog circuits by using the data generated from it. The data have some characteristics, such as randomness and incompleteness, which lead to the diagnostic results being sensitive to the specific values and random noise. This paper presents a data-driven fault diagnosis method for analog circuits based on the robust competitive agglomeration （RCA）, which can alleviate the incompleteness of the data by clustering with the competing process. And the robustness of the diagnostic results is enhanced by using the approach of robust statistics in RCA. A series of experiments are provided to demonstrate that RCA can classify the incomplete data with a high accuracy. The experimental results show that RCA is robust for the data needed to be classified as well as the parameters needed to be adjusted. The effectiveness of RCA in practical use is demonstrated by two analog circuits.展开更多
针对现场可编程门阵列(Field Programmable Gate Array,FPGA)电声测试数据采集电路的优化策略进行深入研究。在电声测试领域,数据采集精准性与效率极其关键,而FPGA凭借高性能属性得到广泛应用。在电声测试数据收集阶段,FPGA在采样率和...针对现场可编程门阵列(Field Programmable Gate Array,FPGA)电声测试数据采集电路的优化策略进行深入研究。在电声测试领域,数据采集精准性与效率极其关键,而FPGA凭借高性能属性得到广泛应用。在电声测试数据收集阶段,FPGA在采样率和多通道同步等方面面临难题。为化解这些困扰,制定一系列优化办法,包括高速模数转换器(Analog to Digital Converter,ADC)接口设计事项及多通道并行的架构体系,以增强电路性能,为电声测试给予更可靠且高效的数据收集支撑。展开更多
基金supported by the National Natural Science Foundation of China (61202078 61071139)the National High Technology Research and Development Program of China (863 Program)(SQ2011AA110101)
文摘The data-driven fault diagnosis methods can improve the reliability of analog circuits by using the data generated from it. The data have some characteristics, such as randomness and incompleteness, which lead to the diagnostic results being sensitive to the specific values and random noise. This paper presents a data-driven fault diagnosis method for analog circuits based on the robust competitive agglomeration （RCA）, which can alleviate the incompleteness of the data by clustering with the competing process. And the robustness of the diagnostic results is enhanced by using the approach of robust statistics in RCA. A series of experiments are provided to demonstrate that RCA can classify the incomplete data with a high accuracy. The experimental results show that RCA is robust for the data needed to be classified as well as the parameters needed to be adjusted. The effectiveness of RCA in practical use is demonstrated by two analog circuits.
文摘针对现场可编程门阵列(Field Programmable Gate Array,FPGA)电声测试数据采集电路的优化策略进行深入研究。在电声测试领域,数据采集精准性与效率极其关键,而FPGA凭借高性能属性得到广泛应用。在电声测试数据收集阶段,FPGA在采样率和多通道同步等方面面临难题。为化解这些困扰,制定一系列优化办法,包括高速模数转换器(Analog to Digital Converter,ADC)接口设计事项及多通道并行的架构体系,以增强电路性能,为电声测试给予更可靠且高效的数据收集支撑。
