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摘要: 应用振动监测技术, 对EQ6100-1型发动机连杆轴瓦与曲柄销间隙故障进行模拟, 分析振动响应与故障特征变化关系, 从振动信号中提取反映偶件故障的特征参数, 选择适当的数学模型描述特征参数随偶件状态的变化规律, 实现对发动机滑动轴承间隙故障的定量诊断。试验结果表明: 故障系数和连杆轴瓦与曲柄销间隙的关系是显著的, 相关曲线为多项式回归曲线, 其复相关系数接近1, 说明采用振动信号进行发动机滑动轴承间隙故障诊断在实践上是可行的。Abstract: In order to implement the quantitative diagnosis of engine sliding bearing failure, a simulation experiment on the relationship between the clearance of connecting rod bearings and their failures for EQ6100-1 model engine was conducted by using vibration monitoring technique, some characteristic parameters reflecting the failures of coupling parts were acquired from vibration signals, and a mathematic model was selected to properly describe the variation rules of the parameters with the change of coupling parts' conditions. Experiment result shows that the correlativity between failure coefficients and the clearance is prominent, their relative curves is polynomial regression curves, and their correlation coefficient approaches 1. It is obvious that the quantitative diagnosis method of engine sliding bearing failure by utilizing engine vibration signals is feasible.
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Key words:
- automobile engineering /
- engine /
- failure /
- diagnosis
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图 3 间隙正常状态下的振动响应功率谱
Figure 3. Vibration response power spectrums under normal clearance state
图 4 间隙异常状态下的振动响应功率谱
Figure 4. Vibration response power spectrums under abnormal clearance state
表 1 试验方案
Table 1. Test scheme
mm 故障原因 配合程度 技术状态 代表符号 数值 连杆轴瓦与曲柄销的磨损 δ1 0.091 正常间隙 δ2 0.200 中度间隙 δ3 0.320 严重磨损 
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表 2 不同状态下的功率谱值
Table 2. Values of power spectrums under different conditions
间隙状态 频带总功率/kHz 频带功率谱密度最大幅值/kHz 1.0~1.4 1.8~2.8 1.0~1.4 1.8~2.8 间隙正常 P0=1 490 P0=16 950 A0=28.74 A0=114.91 工作状态δ3 P1=4 917 P1=21 950 A1=63.51 A1=123.77 断火状态δ3 P2=2 199 P2=11 600 A2=20.34 A2=81.46
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表 3 异响诊断仪测试结果
Table 3. Measuring result of hetero-sound diagnostic instrument
频率/Hz 电压/mV 连杆轴承故障情况下 连杆轴承正常情况下 第6缸 第4缸 第6缸 第4缸 400 1.5 1.5 1.5 1.5 700 1.9 1.8 1.8 1.8 1 200 3.3 2.6 2.3 2.1 1 800 3.2 2.5 2.6 2.5 2 600 4.3 3.5 3.5 3.0
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表 4 测量结果
Table 4. Measure result
参数 间隙状态 δ1 δ2 δ3 1.00±0.08 1.43±0.07 2.22±0.10 1.00±0.06 2.01±0.08 3.32±0.10
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表 5 定量诊断阈值
Table 5. Threshold values of quantitative diagnosis
参数 状态 正常 中度故障 严重故障 SA < 1.12 1.12~1.64 > 1.64 SP < 1.36 1.36~2.25 > 2.25
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表 6 回归数据
Table 6. Regression data
参数 间隙状态 δ1 δ2 δ3 1 2 3 1 2 3 1 2 3 SA 0.91 0.99 1.10 1.32 1.45 1.48 2.12 2.21 2.33 SP 0.90 1.01 1.09 1.93 1.99 2.11 3.21 3.30 3.45
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