【摘要】 随着汽车保有量增多,立体车库得以迅速发展。立体车库通过使用垂直空间多层停放的立体解决方案,能够最大限度利用土地空间资源,它的研发与使用受到越来越多人的关注。电机对于立体车库运行非常重要,对其进行智能诊断对于实现无人值守立体车库十分必要。针对立体车库齿轮减速电机的故障诊断需求,设计数据采集装置采集电机信号,设计研发故障诊断算法对立体车库的齿轮减速电机进行故障诊断。通过对电机振动信号进行时域与频域分析,采用DBN提取振动信号时频域指标的深度特征,并根据电机样本数据的正负样本悬殊的特点,设计和实现了基于DBN-OCSVM的车库电机故障诊断模型,并实际运用到立体车库中。更多还原

【Abstract】 The stereo garage can maximize the use of land space resources by using the three-dimensional solution of vertical space multi-level parking.The motor is very important for the operation of the stereo garage,and the intelligent diagnosis of it is necessary to realize the unmanned stereo garage.In this paper,according to the fault diagnosis requirements of the three-dimensional garage gear reduction motor,a data acquisition device is designed to collect motor signals,and a fault diagnosis algorithm is designed and developed to diagnose the fault of the stereo garage gear reduction motor.Through time-domain and frequency-domain analysis of the motor vibration signal,DBN is used to extract the depth characteristics of the time-frequency domain indicators of the vibration signal,and according to the characteristics of the difference between the positive and negative samples of the motor sample data,the DBN-OCSVM-based garage motor is designed and implemented with actually applying to the stereo garage.更多还原