汽车主减速器轴承失效征兆早期识别的评价法

Early Fault Recognition of Pinion Bearing in Main Reducer of Vehicle Using Information Fusion

对汽车主减速器主齿轴承进行寿命预估,开展了主齿轴承失效的试验研究。为了对轴承失效征兆早期识别进行评价和判断,提出了运用模糊理论和Dempster-Shafer证据理论相结合的信息融合的评估方法,以处理信息的不确定性。试验中模拟汽车的运行状态,使用振动加速度传感器、噪声传感器和红外温度传感器,对同一测试区内的多传感器进行分析融合。试验结果表明,从冗余的信息中可以得到轴承的运行状态隶属于单一的征兆之内,产生比单一信息源更精确、更完全的识别和判断,同时避免了未知先验概率的缺乏,又达到了失效征兆识别的目的。这说明证据理论与模糊推理相结合的信息融合方法在进行轴承失效试验时,对征兆早期识别具有更高的可信度和良好的早期故障识别能力。

A novel method of multi-sensor information fusion was presented for early fault recognition of the pinion bearing in the main reducer of vehicle diver axle. The pinion bearing is vulnerable to deteriorate in actual operation of the vehicle,which brings disadvantageous influence on the transmission system. The early fault recognition of pinion bearing was researched on a test rig in order to evaluate its service-life. In the experiment,various operating conditions of the vehicle were simulated and the information fusion was tested using the fuzzy theory and Dempster-Shafer (D-S) evidential theory. The signals were gathered by the acceleration sensors,the noise meters and the infrared temperature sensor. Experimental results demonstrate that bearing conditions can be identified within a single symptom from redundant information as compared with the methods using the single information source,which makes up for shortage of priori probability and meets the demands of recognition of fault symptoms. The study shows that the synthetic information fusion method based on fuzzy theory and D-S evidential theory has excellent reliability to early recognition of bearing failure.