Industrial robots are an important way to realize the development of industrial industry intelligence and automation, an important driving force to accelerate the construction of Industry 4.0, and an important basic force to improve the professional level of industrial industry. The development of industrial robot technology has enhanced the requirements of its detection quality and the demand for data comprehensiveness. Most of the previous robots obtain the corresponding data through a single sensor system, which has a large error and a high limitation of the range of data obtained. The detection method of industrial robots has the problems of high cost and high professionalism. Therefore, this paper constructs a dual-angle sensor industrial robot detection system based on the fusion of multisource vibration signals and achieves the fusion of multisensor signals through Kalman filtering to provide reliable analysis data for the dual-angle sensor detection system. The experimental results show that Kalman filtering can effectively remove noise while preserving the original vibration signal characteristics and structure and improve the reliability and validity of the vibration signal. In addition, the dual-angle sensor detection system can realize the position detection of industrial robots according to the command standard and obtain the corresponding residual and standard values through system data analysis. The overall optimization of the system algorithm enhances the accuracy and reliability of the measurement.