基于DRSN与电压幅值分析的航空HVDC系统逆变器故障诊断

Fault diagnosis of inverter of aviation HVDC sysytem based on DRSN and voltage amplitude analysis

机载270 V高压直流(HVDC)系统的故障诊断一直是航电领域中的一个难点问题,为此提出了基于深度残差收缩网络(DRSN)的故障模块识别算法与基于线电压幅值分析的故障器件定位算法。首先对系统总电流进行采集,并进行差值标准化处理获得特征数据;根据特征数据的特点,利用Flatten层对原有DRSN结构进行改进,来提高算法对故障模块的识别精度。在确定系统逆变模块故障之后,利用两相线电压之比确定出故障相,再利用线电压均值模型确定故障器件。相比于现有方法,所提方法仅使用1个电流传感器和2个电压传感器便实现了系统故障诊断,满足了飞机对重量的限制要求。实验证明:所提出的方法故障模块识别精度,以及故障器件定位精度可达97%以上,具有较好实用性。

The fault diagnosis of the airborne 270 V high-voltage direct current(HVDC)system has always been a dif⁃ficult problem in the field of avionics.Therefore,a fault module identification algorithm based on deep residual contrac⁃tion network(DRSN)and a fault component localization algorithm based on line voltage amplitude analysis have been proposed.Firstly,the total current of the system is collected,and the difference is standardized to obtain characteristic data.Based on the feature data,the Flatten layer is used to improve the original DRSN structure,so as to improve the algorithm recognition accuracy for fault modules.After determining the fault of the system inverter module,the fault phase is determined using the ratio of the two phase line-voltages,and then the fault device is determined using the average line-voltage model.Compared to existing methods,the proposed method only uses one current sensor and two voltage sensors to achieve system fault diagnosis,meeting the weight limitation requirements of aircraft.The ex⁃periment proves that the proposed method has good practicality in identifying fault modules and locating fault compo⁃nents with an accuracy of over 97%.