Data mining based technique for diagnosing the faults presenting on engine valves

For complex features of the vibration signals collected from engines often present in both the time and frequency domains, it is hard to distinguish the working condition of their valves. Particularly when many valves state are needed to identify, the work is difficult. In view of above reason, a smart data mining technique based on statistic rule is developed with the aid of genetic algorithm. After analyzing a large number of vibration signals collected from a diesel engine used for experiments, a few numbers of criteria that are really effective for diagnosing the valve states are found. Experimental results show that the proposed technique is intelligent and effective for solving the present problem. It paves a way for the comprehensive utilization of data mountain currently formed in production fields.