Abstract: Provided is an intelligent analysis system for inner detecting magnetic flux leakage (MFL) data in pipelines, including a complete data set building module, a discovery module, a quantization module and a solution module, wherein: a complete data set building method is adopted in the complete data set building module to obtain a complete magnetic flux leakage data set; a pipeline connecting component discovery method is adopted in the discovery module to obtain the precise position of a weld; an anomaly candidate region search and identification method is adopted in the discovery model to find out magnetic flux leakage signals with defects; a defect quantization method based on a random forest is adopted in the quantization module to obtain a defect size; and a pipeline solution based on an improved ASME B31G standard is adopted in the solution module to output an evaluation result.

Abstract: Provided is an intelligent analysis system for inner detecting magnetic flux leakage (MFL) data in pipelines, including a complete data set building module, a discovery module, a quantization module and a solution module, wherein: a complete data set building method is adopted in the complete data set building module to obtain a complete magnetic flux leakage data set; a pipeline connecting component discovery method is adopted in the discovery module to obtain the precise position of a weld; an anomaly candidate region search and identification method is adopted in the discovery model to find out magnetic flux leakage signals with defects; a defect quantization method based on a random forest is adopted in the quantization module to obtain a defect size; and a pipeline solution based on an improved ASME B31G standard is adopted in the solution module to output an evaluation result.

Abstract: A load fuzzy modeling device for the power system based on the causality diagram, the composite cloud generator and the improved T-S fuzzy model, comprising: a hardware device, including: the sensors, a signal conditioning and filter module, an A/D conversion module, a causality conversion module, a DSP module, a memory module, a display and keyboard module connected with the DSP module, respectively and a communication module connected with the PC.

Abstract: A load fuzzy modeling device for the power system based on the causality diagram, the composite cloud generator and the improved T-S fuzzy model, comprising: a hardware device, including: the sensors, a signal conditioning and filter module, an A/D conversion module, a causality conversion module, a DSP module, a memory module, a display and keyboard module connected with the DSP module, respectively and a communication module connected with the PC.