In order to effectively maintain and operate the smart substations, a data mining and analysing method for defects of secondary equipment based on the FP-Growth algorithm is proposed.The basic ideas of association rules and FP-Growth algorithm are introduced firstly, then the defect model and the system framework are proposed to mine and analyze the defect data. Through the analysis of the actual defect data of a substation using the proposed method, it shows that the proposed method can effectively find the relationship among secondary devices, manufactories, defect properties, defect causes and other factors. By data mining, it can provide valuable information for efficient maintaining and operation of the substations. Some auxiliary suggestions are given for operation of secondary device finally.
High-sensitivity sensing of multi-component gases has important applications in environmental monitoring, industrial process control, and biomedical analysis. Fiber-enhanced gas Raman spectroscopy based on node-less anti-resonant hollow-core fibers (AR-HCFs) has advantages for the detection of multi-component gases. AR-HCFs can significantly improve the collection efficiency of gas signals, but the diffusion rate of gas in AR-HCFs is slow under normal pressure, and the gas exchange in AR-HCFs requires the help of gas pressure control devices. In this work, a reflective fiber-enhanced gas Raman system is designed and only one end of the hollow-core fiber is coupled to the optical path, the other end is placed in free space which facilitates rapid gas exchange. Various gases such as CH4, H2, N2, NH3, etc. are injected into optical fibers for systematic research. It takes 70 s to fill the 0.5m-long AR-HCFs with hydrogen at 1.2 Bar, but only 8 s at 1.6 Bar. Due to the influence of the gas viscosity coefficient, the time required for CH4 to fulfill 1m-long AR-HCFs is about 1.4 times that of H2 under the same environment. It is proved that such an optical fiber-enhanced gas Raman system can realize fast gas filling and exchange, and has good detection ability for multi-component gas, which can be used in fields requiring the quick response of gas sensing.
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