Ore dressing equipment fault abnormity audio analyzing and identifying method based on HMM

Abstract

The invention provides an ore dressing equipment fault abnormity audio analyzing and identifying method based on an HMM (Hidden Markov Model), and relates to the digital audio processing technical field. The method includes the steps: inputting an ore dressing equipment audio signal in a WAV format, pre-processing a collected audio sample, extracting a linear prediction cepstrum coefficient (LPCC), a Mel frequency cepstrum coefficient (MFCC) and other characteristics and taking the characteristics as characteristic parameters, carry out training by a Baum-Welch algorithm, obtaining a state transfer probability matrix through training, conducting identification by means of a Viterbi algorithm, and realizing identification by calculating the maximum probability of an unknown audio signal during a transfer process as well as by a model corresponding to the maximum probability. The method can effectively detect abnormal sound in an audio signal so as to effectively identify fault abnormities of ore dressing equipment.

Description

technical field [0001] The invention relates to a method for analyzing and identifying an abnormal audio frequency of a mineral processing equipment failure based on a hidden Markov model (Hidden Markov Model, HMM), and belongs to the technical field of digital audio processing. Background technique [0002] Mineral processing equipment is widely used in various fields such as mineral processing and resource recovery, and has a wide range of uses. The massive development and utilization of mineral resources, the continuous reduction of available resources, and the increasing awareness of environmental protection of human beings have put forward higher and higher requirements for mineral processing equipment, which promotes the continuous development of mineral processing equipment in the direction of larger, better and more efficient and energy-saving. [0003] With the rapid development of science and technology and the continuous improvement of factory automation, the dail...

AI Technical Summary

Problems solved by technology

[0006] However, in the actual production workshop, the low-frequency noise generated by the fault may be covered by the high-frequency part of the industrial noise (industrial noise, usually refers to the noise generated by mechanical equipment friction, impact, vibration and other related reasons in the normal production of the factory)

At the same time, industrial noise has a great impact on the hearing of the staff. Working in this environment for a long time will cause irreversible damage to hearing and physical health.

Images