基于声信号的带式输送机托辊故障特征分析

doi:10.16265/j.cnki.issn1003-3033.2023.S2.0036

中国安全科学学报 ›› 2023, Vol. 33 ›› Issue (S2): 13-17.doi: 10.16265/j.cnki.issn1003-3033.2023.S2.0036

基于声信号的带式输送机托辊故障特征分析

刘勇()

国家能源集团宝日希勒能源有限公司, 内蒙古呼伦贝尔 021008

收稿日期:2023-07-13 修回日期:2023-10-20 出版日期:2023-12-30
作者简介:
刘勇 (1968—),男,内蒙古鄂尔多斯人,本科,正高级工程师,主要从事煤炭智能开采技术工作。E-mail:10018225@chnenergy.com.cn。

Fault characteristic analysis of belt conveyor rollers based on sound signal

LIU Yong()

Baorixile Energy Co., Ltd., National Energy Group, Hulunbuir Inner Mongolia 021008, China

Received:2023-07-13 Revised:2023-10-20 Published:2023-12-30

摘要/Abstract

摘要：

针对带式输送机托辊数量众多且分布较散,而现有故障诊断方法准确率低、易受环境影响、监测成本高等问题,提出一种基于声信号的诊断方法。首先,通过伯恩斯全向麦克风采集带式输送机30组托辊工作状态下的声信号;然后,利用统计法分析采集的声信号的时域(TD)特征,实现故障特征初步挖掘;最后,分析声信号的频域(FD)以及时频域(TFD)中所包含的特征,以提高对故障特征的表达能力。结果表明:托辊声音的TD特征能够检测锈蚀故障,FD特征能够检测出严重故障,TFD域特征能够检测出各种典型的轴承损伤,在工业带式输送机托辊故障监测方面具有应用前景。

关键词: 声信号, 带式输送机, 托辊, 故障特征, 时域(TD)特征, 频域(TFD)特征, 时频域(TFD)特征

Abstract:

To address the problems of massive and dispersedly distributed rollers in belt conveyors, low accuracy, susceptibility to environmental impact, and high monitoring costs of existing fault diagnosis methods, a diagnosis method based on sound signals was proposed. Firstly, the sound signals of 30 sets of rollers of the belt conveyor under working conditions were collected through a BOURNS omnidirectional microphone. Then, statistical methods were used to analyze TD features of the collected sound signals, achieving preliminary fault feature mining. Finally, FD and TFD features of the sound signal were analyzed to improve the ability to express fault features. The results show that TD features of the roller sound can detect rust faults. FD features can detect serious faults, and TFD features can detect various typical bearing damages, having application prospects in the monitoring of roller faults in industrial belt conveyors.

Key words: sound signal, belt conveyor, roller, fault characteristic, time-domain (TD) feature, frequency-domain (FD) feature, time-frequency-domain (TFD) feature

中图分类号:

X924.2安全监测技术与设备

刘勇. 基于声信号的带式输送机托辊故障特征分析[J]. 中国安全科学学报, 2023, 33(S2): 13-17.

LIU Yong. Fault characteristic analysis of belt conveyor rollers based on sound signal[J]. China Safety Science Journal, 2023, 33(S2): 13-17.

图/表 5

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基于声信号的带式输送机托辊故障特征分析

Fault characteristic analysis of belt conveyor rollers based on sound signal

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