| Resistance spot welding (RSW) is a major sheet-metal joining means for auto body assembly in automotive industry. The advantage of RSW is its inherently properties of the high productivity and the efficient robotization. Aluminum alloys is one of the valuable lightweight materials in the research of the weight reduction. With natures of multivariate, complication and less weldability, experts have been focusing their efforts on monitoring and control in order to improve spot weld quality over the years. In my dissertation, three parts of the work are studied in aluminum alloys spot welding of monitoring and control. First. Physical model of currentless contact resistance (CCR) has been established and CCR is calculated. The probability density function(PDF) of CCR has been put forward to investigate implicit contact resistance properties. It is well-know that CCR is determined by pressure of the electrode, especially in low pressure case, PDF of CCR has skewness and kurtosis. So the stable distribution has been employed firstly to capture the PDF of CCR in different pressure of electrode and the test shows that stable distribution can constitute a class of CCR distribution. The stable distribution developed in this study is primarily targeted to offer a new method studying contact resistance.Second. Research on monitoring and control parameters of weld quality in aluminum alloys spot welding.Research on wavelet packet decomposition and its energy spectrum using voltage signals. Wavelet packet decomposition and its energy spectrum deals with the signal of voltage and its relationship with weld quality. The result demonstrates that wavelet packet energy spectrum is a desirable approach of monitoring and control parameters in aluminum alloys spot welding. Research on the sound signals. The research is based on the fact that spot welding quality has correlation with sound energy from nugget growth in the time-frequency domain. In particular, the difference in sound emission of big nugget size and small nugget size is distinguishable from the time-frequency distribution.Time -frequency analysis has been used to diagnose the sound signals. As aresult, some details, which are not discovered before, now show themselves in probability distribution. These details enhance the understanding of physical process of the nugget growth during spot welding.In order to extracted information from signals collected in the process, Renyi entropy is selected as feature extraction variables from the process of spot welding. Discussion of the relationship between Renyi entropy and nugget area has been presented. At the same time, the experiment shows that Renyi entropy can characterize the nugget growth.Research on electrode displace signals. The signals of electrode displace can show the nugget growth. The designed experiment demonstrates that there is considerable relationship between the mode parameters of electrode vibration and nugget growth. AR(n) autoregressive model has been applied to compute damp ratio, vibration frequency and power spectrum of electrode displace. And research on the relationship between these parameters and nugget quality are studied systematically. Thus the condition has been reached that the first peak in the energy spectrum of vibration signal can be used as the feature parameter for monitoring and control nugget growth. Third, Research on monitoring and control method.RSW is a complex process in which many electrical, mechanical and thermal process variables are involved, so weld quality depends on many variables. Due to the complex nature of RSW, information provided by one or two variables might be insufficient. Monitoring and control of high weld quality must be required, including not only multiple sensors data fusion but also combination of several control methods. A new monitoring and control means, based on genetic algorithm, data fusion and neural network, is presented through comparison with other methods in our research. In addition, feature-based process mo...
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