Demonstration of an energy-optimized process control for metal ultrasonic welding based on process characteristic values

在转移项目“基于过程特征值的金属超声焊接能量优化过程控制演示”中，ISF与应用合作伙伴Schunk Sonosystems GmbH共同开发基于模型的过程控制原型。Schunk Sonosystems GmbH是全球公认的超声波金属焊接领域的专家。超声波金属焊接特别适用于连接电子技术部件，并且由于电子系统的日益复杂而日益成为工业关注的焦点。尽管超声波金属焊接在工业上广泛应用，但过程波动仍可能发生。这些波动通常无法解释，因为缺乏关于焊接过程中工具和待连接部件之间复杂相互作用的科学知识，因此，在大多数经验研究中几乎没有考虑到这些波动。在DFG前身项目“声发射超声波金属焊接过程分析”的框架内，我们自己的调查的基础上，已经表明，在连接区域内发生的热机械过程的信息可以从外部测量的整个机械系统的振动行为，包括焊接工具和连接部件。整个系统的振动行为与接缝形成相关。在该转移项目中，这些信息将被量化，转移到统计模型中并用于过程控制。通过优化每个关节部分的能量输入，可以实现单个关节的更高强度和整体更低质量的散射。为了实现这一点，在正在进行的焊接过程中根据实际的接头形成来确定最佳的过程结束，并相应地进行调整。合适的传感器和高频数据采集器用于记录结构声信号和其他信号源，例如穿透距离和系统的功耗。结合焊缝的质量数据，使用合适的统计方法在数据集中识别相关的传感器信号，并量化工艺参数。随后，在用于过程监测的原型系统中真实的实时地实现高频信号的处理，即，在正在进行的焊接过程中分析数据并将其转换成过程特征值。当基于过程特征值识别出过程的最佳结束时，该信息被传输到焊接系统，并且过程在适当的时间终止。

In the transfer project "Demonstration of an energy-optimized process control for metal ultrasonic welding based on process characteristic values", ISF is developing the prototype of a model-based process control together with the application partner Schunk Sonosystems GmbH. Schunk Sonosystems GmbH is recognized worldwide as a specialist in the field of ultrasonic metal welding.Ultrasonic metal welding is particularly suitable for joining electro technical components and is increasingly coming into industrial focus due to the growing complexity of electronic systems. Despite its industrial spread, process fluctuations can occur in ultrasonic metal welding. These fluctuations often cannot be explained, since there is a lack of scientifically sound knowledge about the complex interactions between tools and parts to be joined during the welding process and, as a result, they are hardly taken into account in the mostly empirical research. On the basis of our own investigations within the framework of the DFG predecessor project "Process analysis of ultrasonic metal welding by acoustic emission", it has already been shown that information on the thermomechanical processes taking place within the joining zone can be obtained from the externally measurable vibration behaviour of the overall mechanical system, consisting of welding tools and joining parts. The vibration behaviour of the overall system correlates with the joint formation.In this transfer project, this information will be quantified, transferred to a statistical model and used for process control. By optimizing the energy input for each joint part, it is possible to achieve higher strengths for the individual joint and lower quality scatter overall. To achieve this, the optimum process end is determined in the ongoing welding process as a function of the actual joint formation and adjusted accordingly. Suitable sensors and high-frequency data acquisition are used to record the structure-borne sound signals and other signal sources, such as the penetration distance and the power consumption of the system. In combination with the quality data of the welds, correlating sensor signals are identified in the data sets using suitable statistical methods and process parameters are quantified. Subsequently, the processing of the high-frequency signals is realized in real time in a prototype system for process monitoring, i.e. the data is analysed in the ongoing welding process and converted into the process characteristic values. When the optimum end of the process is identified on the basis of the process characteristic values, this information is transmitted to the welding system and the process is terminated at the appropriate time.