Abstract：Objective To solve the problems of low diagnostic accuracy and long time-consuming in the operation fault diagnosis
of existing pressure steam sterilization equipment, a method of operation fault diagnosis of pressure steam sterilization equipment
based on feature extraction is proposed. Methods The operation fault data of pressure steam sterilization equipment were collected
through Lab VIEW programming software and data acquisition card. Through AR model and sensitive IMF decomposition method,
the operation fault signal characteristics of pressure steam sterilization equipment were extracted, and the mapping was constructed
through nearest neighbor graph. The mapping matrix was obtained by Laplace operator, and the data was directly mapped to low
dimensional subspace to complete the reduction of equipment operation fault characteristics. The intelligent hybrid operation fault
diagnosis model was designed through the neural fuzzy inference adaptive system, and the reduced characteristic data was input into
the model to realize the operation fault diagnosis of pressure steam sterilization equipment. Results The design method was used to
diagnose the fault of pressure steam sterilization equipment in a hospital. The average diagnosis accuracy of the designed method was
89.2%, and the average diagnosis time of different fault types was within 640 ms. Conclusion The designed method can effectively
improve the operation fault diagnosis effect of pressure steam sterilization equipment, and has certain feasibility.
任希燕，周娟，胡霞，陈希希. 基于特征提取的压力蒸汽灭菌设备运行故障诊断方法研究[J]. 中国医疗设备, 2022, 37(10): 46-50.
REN Xiyan, ZHOU Juan, HU Xia, CHEN Xixi. Research on Fault Diagnosis Method of Pressure Steam Sterilization
Equipment Based on Feature Extraction. China Medical Devices, 2022, 37(10): 46-50.
