State monitoring method and system based on multivariable state estimation

Abstract

The invention relates to the field of rotating equipment fault diagnosis, and discloses a state monitoring method and system based on multivariable state estimation, and the method comprises: A), collecting a working condition parameter signal and a vibration signal of equipment, and obtaining an m*n-dimensional feature parameter matrix; B) calculating the importance of each feature by adopting aGBDT method, and determining a feature selection number q according to the importance; C) calculating a state estimation value of the equipment by adopting a Mahalanobis distance method; and D) establishing an equipment exception judgment mechanism by adopting an exponential weighted average method, and judging the state condition of the equipment. According to the invention, the key parameters capable of reflecting the equipment state can be effectively selected, characteristic dimensions are reduced, state estimation time is shortened, interference of invalid characteristics is avoided, a Mahalanobis distance method is adopted to fuse multi-dimensional characteristic parameters into an estimated value, state estimation is carried out through an exponential weighted average method, fluctuation caused by random errors is reduced, instantaneous burst capacity can be absorbed, timeliness is high, and accuracy is high.

Description

technical field [0001] The invention relates to the field of fault diagnosis of rotating equipment, in particular to a state monitoring method and system based on multivariable state estimation. Background technique [0002] In recent years, domestic aerospace, rail transit, electric power and other industrial production have developed towards systematization, digitization and automation. The mechanical system has become increasingly complex, and the requirements for process parameters and equipment reliability have been increasing. Rotating equipment carries long-term running work, and is prone to abnormalities, which further affect production efficiency and equipment performance. Therefore, monitor the rotating machinery, detect the abnormality of the rotating equipment in time, realize the early judgment of the abnormality of the rotating equipment, avoid the direct economic loss caused by the unexpected shutdown of the factory automation production line due to failure an...

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Problems solved by technology

[0004] The purpose of the present invention is to solve the problem that the threshold value is fixed in the existing abnormal judgment method of rotating equipment, and the threshold value cannot be adjusted adaptively according to the working condition of the equipment, and the characteristic parameters are selected according to general experience, and no suitable characteristic parameters are selected for the equipment; the multi-variable characteristic parameters are not selected Fusion, the problem that comprehensive evaluation of the equipment state cannot be performed, and a state monitoring method based on multivariate state estimation is provided. The present invention can effectively select key parameters that can reflect the state of the equipment, reduce the feature dimension, reduce the state estimation time, and avoid invalidation The interference of features can improve the accuracy of state estimation, and the Mahalanobis distance method is used to fuse multi-dimensional feature parameters into an estimated value, and the state estimation is performed by the exponential weighted average method, which can reduce fluctuations caused by random errors and absorb Instant burst ability, strong timeliness

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