The increasing need for improvement of weld quality and productivity requires advanced welding monitoring and control technologies. In our research, a multi-optical sensing approach is utilized to maximize the effectiveness of reliable weld flaw detection and real-time adaptive feedback control of welding conditions to eliminate the formation of weld defects. Weld pool characteristics and strain-stress evolution in the heat affected zone, two factors that closely related to certain weld defects are monitored. The sensing system mainly consists of a digital camera synchronized with a laser-based illumination and filtering system to suppress the strong arc light so that the weld pool and the surrounding region can be clearly visualized to measure the weld pool surface dimension and estimate the penetration depth. The strain evolution and the weld distortion in the heat affected zone can also be monitored by digital image correlation (DIC) method with the assistance of the recently developed high-temperature speckle preparation method. In additional, a procedure has been developed to determine the stress evolution in real time.
A new online resistance spot weld non-destructive evaluation (NDE) technique based on infrared (IR) thermography has been developed. It is capable of both real-time online (during welding) and post-weld online/offline (after welding) inspections. The system mainly consists of an IR camera and a computer program with proprietary thermal imaging analysis algorithms integrated into existing production lines. For real-time inspection, the heat flow generated from the welding process (with temperature exceeding 1000°C) is monitored by the IR camera. For post-weld inspection, a novel auxiliary heating device is applied to locally heat the weld region, resulting in temperature changes on the order of 10°C, and the transmitted heat flow is monitored. Unlike the conventional IR NDE method that requires surface coating to reduce the influence of unknown emissivity, the new method can be applied on as-is bare metal surface thanks to the unique “thermal signatures” extracted from infrared thermal images, which positively correlates to weld quality with a high degree of confidence. The new method can be used to reliably detect weld size, surface indents and defects such as cold weld with sufficient accuracy for welds made from various combinations of materials, thickness, stack-up configuration, surface coating conditions and welding conditions.
Today’s auto industry primarily relies on destructive teardown evaluation to ensure the quality of the resistance spot welds (RSWs) due to their criticality in crash resistance and performance of vehicles. The destructive teardown evaluation is labor intensive and costly. The very nature of the destructive test means only a few selected welds will be sampled for quality. Most of the welds in a car are never checked. There are significant costs and risks associated with reworking and scrapping the defective welded parts made between the teardown tests.
IR thermography as a non-destructive testing (NDT) tool has its distinct advantage — its non-intrusive and non-contact nature. This makes the IR based NDT especially attractive for the highly automated assembly lines. IR for weld quality inspection has been explored in the past, mostly limited to the offline post-processing manner in a laboratory environment. No online real-time RSW inspection using IR thermography has been reported. Typically for postprocessing inspection, a short-pulse heating via xenon flash lamp light (in a few milliseconds) is applied to the surface of a spot weld. However, applications in the auto industry have been unsuccessful, largely due to a critical drawback that cannot be implemented in the high-volume production line – the prerequisite of painting the weld surface to eliminate surface reflection and other environmental interference. This is due to the low signal-to-noise ratio resulting from the low/unknown surface emissivity and the very small temperature changes (typically on the order of 0.1°C) induced by the flash lamp method.
An integrated approach consisting of innovations in both data analysis algorithms and hardware apparatus that effectively solved the key technical barriers for IR NDT. The system can be used for both real-time (during welding) and post-processing inspections (after welds have been made). First, we developed a special IR thermal image processing method that utilizes the relative IR intensity change, so that the influence of surface reflection and environment interference can be reduced. Second, for the post-processing inspection, a special induction heater is used to replace the flash lamp, resulting in temperature changes on the order of 10°C. As a result, the signal-to-noise ratio increased by several orders of magnitudes with no surface painting needed, and the inspection results are more accurate and reliable. For real-time inspection, the heat from welding (with temperature exceeding 1000°C) was utilized. Third, “thermal signatures” were identified to uniquely correlate to different weld quality attributes through computational modeling of heat transfer and extensive testing of specially designed ranges of welding conditions. Novel IR image analysis algorithms that automatically and intelligently identify the “thermal signatures” from the IR images and positively determine the weld quality in less than a second were developed.