Thermal power plant fan equipment fault diagnosis method based on multi-sensor feature fusion
A feature fusion, equipment failure technology, applied in the direction of instruments, computer parts, character and pattern recognition, etc., can solve the problems of unreliable diagnosis results, single vibration signal, unstable diagnosis system, etc., to improve the efficiency and reliability of fault diagnosis. The effect of enhancing the ability of sexual, dynamic information
Pending Publication Date: 2022-04-15
SOUTHEAST UNIV
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Problems solved by technology
At present, the evaluation of fault diagnosis of fan equipment mostly relies on a single vibration signal, which may easily cause problems such as unstable diagnosis system and unreliable diagnosis results.
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[0065] The technical solution of the invention will be described in detail below in conjunction with the accompanying drawings. Apparently, the described examples are only some examples of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention.
[0066] It is worth mentioning that, unless otherwise specified, the technical terms used in the application of the present invention shall have the usual meanings understood by those skilled in the art to which the present invention belongs.
[0067] Such as figure 1 As shown, the fault diagnosis method flow of thermal power plant fan equipment based on multi-sensor feature fusion includes the following steps:
[0068] S1: Acquisition of sound signals, vibration signals and temperature signals generated when the equipment is running;
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The invention discloses a thermal power plant fan equipment fault diagnosis method based on multi-sensor feature fusion. The method comprises the following steps: S1, collecting a sound signal, a vibration signal and a temperature signal generated during equipment operation; s2, preprocessing the sound signals acquired in the step S1; s3, feature extraction is carried out on the preprocessed sound signal segments, the vibration signals and the temperature signals, and a signal-enhanced Mel-frequency cepstral coefficient method is adopted for the sound signals; and S4, performing feature fusion on the feature vectors obtained through the multiple sensors in the step S3, and substituting the fused final vector into the constructed SVM model to obtain the fault condition of the mechanical equipment. According to the method, a multi-sensor feature fusion mode is selected, feature fusion is carried out on sound signals, vibration signals, temperature signals and the like, the dynamic signal capturing capacity of the system is enhanced, the state of equipment is more accurately obtained, and the detection rate of the abnormal information detection system is increased.
Description
technical field [0001] The invention relates to the field of fault diagnosis methods for fan equipment in thermal power plants, in particular to a fault diagnosis method for fan equipment in thermal power plants based on multi-sensor feature fusion. Background technique [0002] The thermal power plant contains many complicated mechanical equipment. As one of the important auxiliary machines in the thermal power plant, the fan equipment is directly related to the long-term stable power generation of the thermal power plant. Once one of the equipment fails, it may cause the entire The efficiency of power plants is reduced or even safety accidents occur, so it is very important to ensure the safe and stable operation of fans in thermal power plants. The efficiency of traditional equipment detection methods is low, and the remedy for sudden failures will not be timely; in addition, most of them lack accurate technical data for reference and reference, and the reliability of fau...
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IPC IPC(8): G06K9/00G06K9/62G06Q10/00G06Q50/06
Inventor 陈从颜林施旗刘浩丁兰飒
Owner SOUTHEAST UNIV