Fuzzy FMEA (Failure Mode and Effect Analysis) based system automatic fault diagnosis method
An automatic fault diagnosis and analysis system technology, applied in the direction of fuzzy logic-based systems, etc., can solve the problem of the frequency of fault occurrence, the degree of harm and the difficulty of detection, the degree of occurrence, severity and detection of fault modes are difficult to determine, the fault It is difficult to achieve breakthroughs in diagnostic research, so as to save manpower and ensure accuracy
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Embodiment 1
[0035] Embodiments of the present invention provide a system automatic fault diagnosis method based on fuzzy FMEA analysis, such as figure 1 shown, including:
[0036] 101. Obtain a diagnostic data source; the diagnostic data source includes one or more types of data; each type of data includes one or more items of information.
[0037] Among them, the diagnostic data source in this embodiment provides a judgment basis for fault diagnosis, and the diagnostic data source includes four types of data, including power consumption data, working condition data, channel monitoring data, and server monitoring data. Each type of data contains five items of information: numerical value, Boolean value, fixed constant, association relationship and phenomenon.
[0038] 102. Analyze and process the diagnostic data source, and input the processed diagnostic data source into a fuzzy FMEA analysis system.
[0039] Among them, the potential failure mode and effect analysis (Failure Mode and E...
Embodiment 2
[0045] Embodiments of the present invention provide a system automatic fault diagnosis method based on fuzzy FMEA analysis, such as figure 2 shown, including:
[0046] 201. Acquire a diagnostic data source; the diagnostic data source includes one or more types of data; each type of data includes one or more pieces of information.
[0047] Among them, the diagnostic data source includes four types of data: electricity consumption data, working condition data, channel monitoring data and server monitoring data, and each type of data includes five items of information: numerical value, Boolean value, fixed constant, correlation and phenomenon.
[0048] 202. Acquire the diagnostic data source file information.
[0049] Wherein, the archive information of the diagnostic data source includes archive data and log data of various diagnostic data sources.
[0050]203. Perform cluster analysis and data fusion processing on the diagnostic data source in combination with the archive in...
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