Condition monitoring of high power CO(2) laser welder systems for preventive maintenance
Abstract
The purpose of this research was to develop condition monitoring techniques that could be used to characterize the nominal condition of an industrial CO$\sb2$ laser and observe any changes that might occur over time for use with preventive maintenance. In this research, both a static and dynamic model have been developed to characterize the power distribution of a high power transverse-flow DC-excited CO$\sb2$ laser. Both models linked the input discharge power of the laser to the output power, as well as, the heat losses in the system. The dynamic model is an extension of the static power distribution model to account for dynamic effects such as continuously ramping up and down the laser output power and the cyclic nature of the laser's chiller. The models were used to characterize the nominal laser behavior during production and observe any changes that occurred over time. A method called the parametric diagnostic technique based on the dynamic laser power distribution model was used to monitor the condition of several components on an industrial laser used in actual production. The results showed that this technique can be used to monitor the laser's condition and isolate fault signatures caused by contamination successfully. Control charts were also successfully generated that showed the deterioration of the laser's condition between maintenance intervals. It is believed that the models and the monitoring techniques developed in this research can be practically implemented and used to help reduce machine down-time and to improve the quality of parts produced with the device. With the results obtained in this research, an on-line user-friendly monitoring system that indicates the condition of the laser and warns the user of any abnormalities can be developed. Such a monitoring system can also be used to determine when and what maintenance is required to keep the laser functioning properly.
Degree
Ph.D.
Advisors
Tu, Purdue University.
Subject Area
Industrial engineering
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