| With good corrosion resistance, galvanized steel sheet has been widely used in the automotive manufacturing industry instead of the cold-rolled plate. However, the weld ability of galvanized steel sheet in resistance spot welding is poor because of the zinc coating which makes the contact area of the end of the electrode tip increase, and the current density reduce. Meanwhile, low melting point of zinc results in serious damage of the electrode tip. Therefore, the quality of the joint of spot welding is too unstable to control. Aiming at the quality control requirement of spot welding joints of galvanized steel sheet in the automotive manufacturing industry, we used the surface images of spot welding joints and the dynamic signal which we picked up real-time in the process of spot welding as the information source. In order to develop an online, non-destruction, low cost detection methods of quality evaluation, we carried out such researches as follows:1. Set up a platform to collect the surface images of welding joints. Under the same condition, surface images of welded joints are collected by using the digital imaging technology. The preprocessing of digital images shows that the surface image of joints can be used as the source of information.2. Analyze the feature of the surface images of a number of spot welding joints; determine the area of different characteristic region as characteristic parameter which can characterize the quality information of spot welding. According to the relevance analysis between the area of characteristic region and the shear strength of welding spot, select the characteristic parameter which has salient relativity as the input vector and the shearing strength of the joint as the output vector. Set up a BP neural network model which uses the shear strength as an indicator of quality evaluation. The test result of network model shows that it is successful to evaluate the quality of welding spot online by BP network model.3. Set up a platform which is a multi-channel real-time synchronous acquisition to collect the dynamic information such as Welding voltage, welding current, and the displacement of electrode without discrepancy in the process of resistance spot welding. Select dynamic resistance and electrode displacement as the signal source of online quality evaluation.4. By analyzing the signal of dynamic resistance and electrode replacement in welding process, abstract some characteristic parameters which are relevant with welding process. According to the correlation analysis between feature parameters and shear strength of joints, select these characteristic parameters which are closely related to shear strength of joints as the input vector of som network, and classify and analyze them. The result of som network shows that som network can realize the classification of the quality of joints of spot welded galvanized steel sheet. |