A Study On The Knowledge Engine System For Fault Diagnosis Of Shield Based On MAS

In the sudden boom of urban rail transportation in Shanghai and in many other metropolises of China, the shield has been playing an increasingly important role as the main apparatus for digging tunnels. The shield, to all intents and purposes, is an amalgam of new technologies in such fields as mechanics, hydraulic transmission, automatic control, testing and computer sciences. As China is ameliorating itself rapidly as an economy and updating its technologies for industrial control on a continual basis, the shield, like many other articles of field industrial equipment, has been endowed with more and more functions - accordingly, it is getting more and more advanced, complex and high-priced. Therefore, timely analyses of existent faults and accurate predictions of potential ones will temporally shorten break-downs and thus bring tangible profits not only to the process of production but also to the construction of China's modernism in general. In this context, the present author has set his research goal at discovering a solution to the integration of artificial intelligence into modernized production equipment, which is intended to be better technology-enabled, to operate more smoothly and to enjoy higher efficiency.Since the shield is a large complex continuously-operating mechanical device that features a multi-component structure, multi-level fault symptoms, an uncertainty of faults, etc., this paper chooses the knowledge engine system for fault diagnosis based on MAS to be its point of departure, from which to study the integrated reasoning mechanism of multiple reasoning agents and the structure of the integrated knowledge base and the knowledge-acquisition platform, both based upon the complementation of agents supported by multiple types of knowledge, with an eye to realizing a major break-through in the limited range for the specialized knowledge and reasoning ability of the single intelligent system for diagnosis.In order to meet the needs of the fuzzy reasoning proposition relevant to the uncertainty of shield faults and of the real-time fault diagnosis of the shield as an article of continuously-operating production equipment, the paper, in developing the reasoning agent of the knowledge engine system, presents its own designs of a fuzzy recognition method based upon the comprehensive static and dynamic membership computing to deal with the flizziness aspect of the object of research, of a probability and statistics method of recognition based upon the Bayesian principle to deal with the aspects of possibility and coupling, of a parallel computing method based upon neural networks and a machine learning platform based upon genetic neural networks to try to solve the "bottleneck" problem caused by the insufficient knowledge of a large number of state parameters and control signals of the shield and the problem of quick reasoning caused by this very "bottleneck."This paper also puts forward a proposition that the structural pattern of the knowledge engine system should be a multi-level alliance: after sub-agents and MAS communications modules and planners with different properties are developed, necessary agents can be organized into an alliance in accordance with the pre-fixed communications and planning mechanism, so that several sub-agents can each of them undertake some part of the intelligent task, as required by the scheme of the general task, which is capable of being divided and distributed, and that the integration of the completed sub-tasks is actually something beyond any single agent: to ascertain the operational state of or to diagnose the fault in the shield as an article of large complex equipment at a given moment or during a given span of time. Besides, in this process are met the needs for fault diagnoses that are relevant with the multi-component structure, the multi-level fault symptoms, the high fault frequency and the type variety of the shield.After conducting an in-depth study of the above-mentioned key topics, this paper goes on to create the knowledge engine system for the diagnosis of shied faults that has been developed for this research program. The Knowledge Engine System for the Diagnosis of Shield Faults, developed for different diagnosis purposes, boasts the functions of interactive, automatic and on-line diagnosis. Moreover, the flexible cooperation between the three functions, established by the communications and planning mechanism of the MAS, is reasonably expected to diagnose real faults with success. The system may also perform the functions not only of diagnosis simulation, information acquisition and optimized maintenance, but also of the sustainment and renewal of the knowledge base - in particular, through the re-use and re-construction of knowledge, the system can rapidly include information concerning the latest types of shields into its knowledge base and assist the reasoning agent in completing the diagnosis.The Knowledge Engine System for the Diagnosis of Shield Faults has got modified and improved in its constant trial operation. Applied and tested in several tunnel diggings, the System has received profuse praises from the Shield Engineering Company of the Shanghai Tunnel Engineering Co., Ltd. and from the experts in the fields of shield tunneling, mechanic and electrical equipment, control engineering and computer technology who attended the assessment conference for the Shield program.Last but not least, this paper outlines the future for further investigations into the research topic, discussing how the application of the knowledge engine system in the modernized production equipment can be further studied and improved from optimization.