Research of fault diagnosis of lubricating oil in coal mining equipment
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摘要: 针对传统润滑油分析方法存在测试及分析周期较长、成本较高、不能系统地反映润滑油状态及煤矿设备运行状况的问题，提出了一种多参数融合诊断方法。该方法通过采集煤矿设备在用润滑油的黏度、密度、介电常数和温度来构造润滑油多参数模式向量，对待检状态的模式向量与标准模式向量进行分析来判断设备所属状态；对比润滑油的铁谱分析结果，发掘润滑油污染状态参数的内在关联和变化规律。实验结果表明，该方法可实现润滑油污染状态及煤矿设备运行状况的准确、快速诊断。Abstract: In view of problems that traditional lubricating oil analysis method exists long test and analysis period and high cost, and cannot reflect lubricating oil state and running state of coal mining equipment systematically, a multi-parameter fusion diagnosis method was proposed. The method constructs multi-parameter pattern vector of lubricating oil by collecting viscosity, density, dielectric constant and temperature of the lubricating oil used in coal mining equipment, and judges equipment state through analysis on pattern vector of state to be detected and standard pattern vector. It discovers internal correlation and variation law of pollution state parameters of the lubricating oil by comparing with ferrography analysis result of the lubricating oil. The experimental result shows that the method can realize accurate and rapid diagnosis of pollution state of lubricating oil and running state of coal mining equipment.
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Keywords:
- coal mining equipment /
- lubricating oil /
- fault diagnosis /
- multi-parameter fusion /
- pattern vector
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