A New Method of Early Real-Time Fault Diagnosis for Technical Process

By taking the process of synthetic ammonia decarbonization as the research object, a new method of early real-time fault diagnosis based on the linear classifier-reforming neural network was proposed. The method, which need not establish accurate mathematical model, and has the advantages of its simple learning algorithm, accumulate knowledge from example automatically, learning and classification of parallel processing and fast response speed etc.. The results show that it can be applied to early real-time fault diagnosis in the process, and can provide techniques guarantee for safety production.