Multiple sensor expert system for diagnostic reasoning, monitoring and control of mechanical systems (original) (raw)
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Mathematics, 2022
The workers operating and supervising machining tools are often in charge of monitoring a high number of parameters of the machining process, and they usually make use of, among others, cutting sound signals, for following-up and assessing that process. The interpretation of those signals is closely related to the operational conditions of the machine and to the work environment itself, because such signals are sensitive to changes in the process’ input parameters. Additionally, they could be considered as a valid indicator for detecting working conditions that either negatively affect the tools’ lifespan, or might even put the machine operators themselves at risk. In light of those circumstances, this work deals with the proposal and conceptual development of a new methodology for monitoring the work conditions of machining tools, based on expert systems that incorporate a reinforcement strategy into their knowledge base. By means of the combination of sound-processing techniques, ...
Real time expert system for predictive diagnostics and control of drilling operation
1990
The suitability and applicability of a real-time expert system for integrating multiple sensors for predictive diagnostics, monitoring, and supervisory control of a drilling operation in an automated manufacturing environment were investigated. The real-time IDES (influence diagram based expert system) performs probabilistic inference and expected-value decision-making in integrating dynamic but noisy sensory data and subjective expertise in symbolic and numerical data structures designed for real-time performance. An application using spindle motor current, feed motor current, and spindle-mounted strain-gauge sensors on a numerically controlled drilling machine is described. In this example, with relatively simple signal processing, IDES achieves effective prediction about the state of the drill and optimally controls the performance of the drilling machine. The real-time expert system performance is demonstrated over a wide range of machining conditions: two workpiece materials, two drill sizes, six speeds, and seven feed rates. With an MS-DOS personal computer, the system was able to predict tool failure in 1.7 to 2.1 ms, well within the desired response time of an industrial production line operation
Expert Systems in Engineering Applications
Springer, Berlin, 1993
This book provides a set of important contributions presenting a number of expert systems that deal with modern engineering applications. The book is divided in five parts. Part 1--General issues. Part 2--Expert systems in engineering domains. Pat 3--Expert systems in fault diagnosis. Part 4--Expert systems in robotics and manufacturing. Part 5--Expert systems catalogs ( AI and expert systems tools).
Effective Automatic Expert Systems for Dynamic Predictive Maintenance Applications
Volume 4: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation; Education; IGTI Scholar Award, 1997
As the need for specialist decision-making has increased with the volume of data produced by modern monitoring systems, and the current trend towards downsizing and external sourcing (for example, specialist consultant companies) has continued, the demand for computerbased expert systems for automatic machine condition (vibration and process) analysis and diagnosis has intensified Various levels of success have been achieved, but most expert systems available today do not reflect the actual reasoning process of a human expert; are inherently obsolete for the continuous learning capability required for dynamic applications; and/or require considerable skills in computer simulation or statistical methods to update the system. In this paper, new techniques and tools are presented that address the basic elements in the reasoning process of a human expert, and offer solutions to the practical implementation of effective and reliable automatic machine diagnosis. Essential tools for optimum automatic spectrum analysis are first introduced, and then a method presented that allows system results to be automatically qualified and improved upon to reflect actual machine conditions. The paper then introduces neuralnetwork technology as a means of implementing a workable, userdefined knowledge base that can be used to augment the expert system with the user's own knowledge and experience, and the idiosyncrasies of individual machines. NOMENCLATURE BD = Ball Diameter BPFO = Ball Passing Frequency (Outer Defect) PD = Pitch Diameter TMF Toothmeshing Frequency fc Centre frequency flu Rotational frequency fr Relative revs/sec between inner and outer races 13 Contact angle
An approach to integrating intelligentdiagnostics and supervision of machine tools
1998
Arguments are presented for the necessity of integrating diagnostics and supervision in technological machines. An example of integrated diagnostics and supervision of the machine tool main drive, based on an expert system and neural network, is shown. Problems of intelligent thermal displacement supervision and questions related to practical supervision of machining centres are presented.
A review of expert systems principles and their role in manufacturing systems
Robotica, 1985
SUMMARYThe objectives of this paper are twofold: The first is to briefly review for manufacturing engineers some of the early work undertaken by Artificial Intelligence researchers and the issues addressed which have culminated in today's “expert systems’ or ‘intelligent knowledge based systems’ (IKBS), as they are becoming known.The second is to indicate some early applications in manufacturing and to point out that any major success in this field requires long-term commitment, in depth familiarity with A.I. techniques and access to A.I. development tools, all of which are currently in short supply internationally.
Expert systems in the process industries
1992
This paper gives an overview of industrial applications of real-time knowledge based expert systems (KBES's) in the process industries. After a brief overview of the features of a KBES useful in process applications, the general roles of KBES's are covered. A particular focus is diagnostic applications, one of the major applications areas. Many applications are seen as an expansion of supervisory control. The lessons learned from numerous online applications are summarized.
An Intelligent Integrated System Scheme for Machine Tool Diagnostics
The International Journal of Advanced Manufacturing Technology, 2001
The technology of neural networks and expert systems are finding increasing applications in the field of machine tool diagnostics. In this paper, the advantages and disadvantages of these methods are analysed and compared. An intelligent integrated diagnosis system based on a combination of the two methods is presented. This scheme aims at exploiting the advantages and avoiding the disadvantages of neural networks and expert systems. The implementation of the intelligent integrated diagnosis system scheme is also presented. A diagnosis system based on the scheme is introduced, which was applied to the process diagnosis of an existing machining centre. The experimental results show that the integrated system scheme is feasible and effective for machine tool diagnosis tasks.