Power transformer fault prediction and diagnosis method and system based on audio characteristics
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A power transformer and audio feature technology, which is applied in the field of power transformer fault prediction and diagnosis based on audio features, can solve problems such as background noise cannot be ignored, power transformer structure is complex, and the operating environment is harsh
Pending Publication Date: 2021-02-23
TRINA SOLAR CO LTD
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[0007] (1) Most of the extraction of sound features of power transformers use frequency domain analysis methods, or use wavelet transform, Hilbert-Huang transform, etc. to extract some components of the reaction fault, instead of using cepstrum for reference to the sound recognition principle of human ear , Mel cepstrum angle for further analysis;
[0008] (2) The structure of the power transformer is complex, the operating environment is harsh, and the background noise cannot be ignored. Especially when the energy of the background no
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[0104] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.
[0105] Such as figure 2 As shown, a power transformer fault prediction and diagnosis method based on audio features, the specific steps include:
[0106] S1. Based on the chaotic oscillator to detect the effective signal of the audio data of the power transformer in the background of strong noise;
[0107] S2. for the effective audio signal extracted in the step S1, adopt the Mel Mel frequency cepstrum technology to calculate the logarithmic energy spectrum on the nonlinear Mel scale, as the feature quantity of the power transformer audio signal; in the extraction process Carry out Mel scale transformation, this nonlinear transformation makes the sound signal have higher anti-noise performance;
[0108] S3. Using the PCA principal component analysis method to calculate the principal component of the audio signal feature quantity of...
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Abstract
The invention provides a power transformer fault prediction and diagnosis method based on audio characteristics. The method specifically comprises the steps that S1, detecting effective signals of power transformer audio data under the noise background based on chaotic oscillators; S2, calculating a logarithm energy spectrum on the nonlinear Mel scale to serve as a characteristic quantity of the audio signal of a power transformer; S3, calculating a principal component of the audio signal characteristic quantity of the power transformer by adopting a principal component analysis method; S4, optimizing the optimal hyper-parameter training power transformer fault prediction model of the vector machine algorithm by adopting a quantum particle swarm optimization algorithm; and S5, if the powertransformer is in a fault state, adopting a 1/3 octave algorithm to extract the fault characteristic frequency range amplitude, comparing the fault characteristic frequency range amplitude with an expert experience rule base, and predicting/obtaining the fault type of the power transformer. According to the method, the identification precision of power transformer operation state fault predictioncan be improved, and the calculation amount is reduced; fault judgment can be carried out based on other measurement data or infrared images.
Description
technical field [0001] The invention belongs to the technical field of power transformer fault diagnosis, and in particular relates to a power transformer fault prediction and diagnosis method and system based on audio features. Background technique [0002] In the power system, power transformers play an important role in voltage conversion, power distribution, voltage regulation, isolation, etc., which are related to the safe, stable, reliable and economical operation of the power system. The power transformer has a complex structure, mainly composed of iron core, winding, oil tank, oil pillow, insulating bushing, tap, etc., and it is generally installed outdoors, and the working environment is harsh. As the running time increases, failures will inevitably occur. The failure involves Windings, main insulation, leads, tap changers, bushings, etc. According to DL / T573-95 "Guidelines for Maintenance of Power Transformers" and the operating environment of power transformers, ...
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