Model-based real-time dynamic power factor measurement in AC resistance spot welding with an embedded ANN

Today, real-time measurement of dynamic power factor in resistance spot welding (RSW) is of increasing importance. On the basis of the welding transformer circuit model, a new method is proposed to measure the peak angle of the welding current and then calculate the dynamic power factor in each half-wave. The tailored sensing and computing system ensures that the measuring method possesses a real-time computational capacity with satisfying accuracy. Since the power factor cannot be represented via an explicit function with respect to measurable parameters, the traditional method(s) has to approximate the power factor angle with a constant phase lag angle and fails to detect its dynamic characteristics. An offline-trained embedded artificial neural network (ANN) successfully realizes the realtime implicit function calculation or estimation. A digital-signal-processor-based RSW monitoring system is developed to perform ANN computation. Experimental results indicate that the proposed method is applicable for measuring the dynamic power factor in single-phase half-wave controlled rectifier circuits.