基于BP神经网络的SCARA机器人故障诊断

以SCARA机器人为研究对象，在ADAMS软件中建立SCARA机器人模型，进行仿真。采集SCARA机器人大臂前后端、小臂前后端及底座等容易出现裂纹部位的加速度数据；在MATLAB中运用BP神经网络建立SCARA机器人故障诊断模型，实现利用BP神经网络对SCARA机器人故障进行智能识别与分类。结果表明：BP神经网络的计算结果与期望输出基本一致，验证了其准确性及可靠性。

Fault Diagnosis of SCARA Robot Based on BP Neural Network

Taking the SCARA robot as the research object, the SCARA robot model was established in ADAMS software, and the simulation was carried out.The acceleration data of the crack prone parts of the SCARA robot were collected, such as the front and rear end of the big arm, the front and rear end of the small arm and the base; the fault diagnosis model of SCARA robot was established by using BP neural network in MATLAB to realize the intelligent recognition and classification for SCARA robot fault by using BP neural network. The results show that the calculation results of BP neural network are basically consistent with the expected output, and the accuracy and reliability are verified.