Motor abnormal noise detection method based on Hilbert-Huang transformation

A detection method and abnormal sound technology, applied in speech analysis, machine learning, instruments, etc., can solve problems such as the inability to realize automatic recognition, lack of self-adaptive ability, and influence threshold setting, so as to protect the health and coverage The effect that the accuracy of the expansion, discrimination increases

Active Publication Date: 2018-08-24
SHANDONG IND TECH RES INST OF ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

The disadvantages of this detection method for abnormal noise of the motor are: 1. The audio signal is a quasi-stable signal, that is, short-term stable; Carry out signal feature extraction; however, in abnormal noise faults of motors, there are a large number of fault samples of instantaneous unsteady signals; for these unsteady signals, Fourier transform is powerless
2. Judging the abnormal sound by judging whether there is a waveform beyond the specified maximum value, it does not have the ability to adapt, and the versatility is not high: because for different types of motor products, technicians need to reset the threshold; and through sensor collection For audio signals, the distance between the sensor and the sound source will also affect the threshold setting
3. Whether it is setting the maximum value or comparing waveforms, it requires professionals to judge, and automatic identification cannot be realized

Method used

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  • Motor abnormal noise detection method based on Hilbert-Huang transformation
  • Motor abnormal noise detection method based on Hilbert-Huang transformation
  • Motor abnormal noise detection method based on Hilbert-Huang transformation

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Embodiment Construction

[0028] The method for detecting abnormal sound of a motor includes the following steps:

[0029] Step 1. Set the sampling frequency and sampling time t, and collect the audio signal x(t) when the motor is in the no-load state;

[0030] Step 2. Carry out frame division and windowing processing on the audio signal, set the frame length as L and the overlapping length of two adjacent frames as M, and divide the audio signal into N frame signals; the frame length L can be regarded as the signal in each frame Steady-state signal is appropriate, so as to avoid the influence of unsteady state and time-varying of the entire audio signal; perform frame-based windowing processing on the audio signal, set the frame length L of each frame and the overlapping length of two adjacent frames (frame shift) M, the audio signal is divided into N frame signals; the frame length L is suitable for the signal in each frame to be regarded as a steady state signal, so as to avoid the unsteady state an...

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Abstract

The invention discloses a motor abnormal noise detection method based on Hilbert-Huang transformation, and the method comprises the six steps. The method can assist a worker to recognize the abnormalnoise of a motor, improves the detection efficiency, guarantees the delivery quality of a product, improves the overall production efficiency of an enterprise, reduces the manufacturing cost of the enterprise, and protects the health of the worker. The method can effectively solve a problem of an unsteady state of an audio signal of the motor, effectively detects the abnormal noise fault of an unsteady state motor, and is high in recognition accuracy.

Description

technical field [0001] The invention relates to the field of motor fault detection, in particular to a method for detecting abnormal noise of a motor. Background technique [0002] my country is the main producer of electric motors for various small household appliances such as washing machines, household air conditioners, refrigerators, and electric fans. The annual output of household air conditioner motors alone exceeds billions. [0003] In the production line of small motors, manual listening is generally used to distinguish good and defective products before the products go off-line, that is, workers listen to the sound of the motor in sequence with their ears in the soundproof room, and judge whether the motor is faulty based on the personal experience of the workers. . [0004] Due to the need for people to make subjective judgments, it has long been difficult to be replaced by automated devices. Moreover, it is impossible to establish a unified evaluation standard...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L25/51G10L21/0208G06N99/00
CPCG10L21/0208G10L25/51G06N20/00
Inventor 曹衍龙刘婷付伟男杨将新黄金娜
Owner SHANDONG IND TECH RES INST OF ZHEJIANG UNIV
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