多传感器信息融合在焊接质量控制中的应用

Multi-sensor Information Fusion Technology in the Measurement of Weld Penetration

利用BP神经网络,将电弧传感器和超声波传感器所获观测信息以及焊接电流、焊接速度、焊缝坡口等焊接参数信息进行有效融合,得到焊缝熔深预测模型.为了对焊缝熔深进行精确控制,结合传统PID控制器与模糊控制器的优点,设计了参数自调整模糊PID控制器,仿真结果表明:建立的焊缝熔深预测模型能够实时、快速、准确地测量得到焊缝熔深信息,在系统性能各方面参数自调整模糊PID控制器相比于传统PID控制器有着显著优势.

BP neural network for effectively fusioning the information obtained by arc sensor and ultrasonic sensor and information of welding parameters such as welding current,welding speed,welding groove and so on was used to obtain the prediction model of weld penetration depth. Simulation results showed that： the prediction model of weld penetration depth could measure the weld penetration quickly,accurately and in real time. For the precise control of weld penetration,parameters self-tuning fuzzy PID controller was desing,which combined with the advantages of traditional PID controller and fuzzy controller. Smulation results showed that compared with traditional PID controller,parameters self-tuning fuzzy PID controller had a significant advantage in the performance of the system.