| Regarding to the after service system of traditional medical equipment, it is hard to keep balance between the effectiveness and the cost. However, with the development of information technology and internet, more and more medical equipments are used in non-traditional medical fields, such as primary care and families. It, on the on hand, expands the market; on the other hand, increase the requirement for after service. Recently, as the labor costs growing year by year, the company's running cost is greatly increased by simply through the expansion of the after service team to meet the requirements.Expert System is widely used in the field of fault diagnosis. Its working theory is to diagnose the fault through machine reasoning by using the knowledge base, which is widely applied to related computer area. Partially instead the human fault diagnosis by machine fault diagnosis; enterprises have lowered the running costs, and also developed the standardization of after service management.This thesis designs an expert system of fault diagnosis for remote ECG. Based on the knowledge, which was mined from the past records, system diagnosis fault through the integration reasoning. It diagnosis effectively and correctly, and also decrease the operating complexity for users. By using this system, companies could reduce the after service costs meanwhile increase the standardization of the service.Firstly, the thesis defines the necessity of the expert system of fault diagnosis, on the basis of analyzing the existing after service of medical equipment. Secondly, through the introduction of the related core technology, gaining the ECG's fault feature and customers chose the right technical scheme. Then after collecting materials, according to the demands, it divided the system into several modules based on different functions and designed them. The thesis mainly discusses the key sub modules:the inference machine and the data mining. At last this thesis includes the demo of partial function and prospect of this system. |