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Machine condition monitoring with inventive system TRIZ1

Cempel C.

Vibrations in Physical Systems

2012

Vol. 25

97--102

The machine condition monitoring has not been approached by TRIZ2 practitioners, as yet, so the knowledge of TRIZ methodology has not been applied there. But it seems to be a need to make such an approach in order to see if some new knowledge and new technology will emerge from this study. In doing this we need at first to define the ideal final result (IFR). As a next we need to describe the problem of system condition monitoring (CM) in terms of TRIZ problem (engineering) parameters and to look for respective inventive principles. This means we should present the machine CM problem by the main tool of TRIZ, it means the contradiction matrix. When specifying the problem parameters and inventive principles, one should use analogy and metaphorical thinking, which by definition is not exact but fuzzy, and leads sometimes to unexpected results and outcomes, especially when doing it first time. The paper undertakes this important application problem and brings some fresh insight into system and machine CM problems. This may mean for example the minimal dimensionality of TRIZ engineering parameter set for the description of machine CM problems, and of course the ideal final result of TRIZ methodology.

Multi symptom condition monitoring of a critical mechanical systems as a first approach to design condition inference agent (CIA)

Cempel C.

Diagnostyka

2004

Vol. 30, T. 1

91--96

The paper presents the introductory results in application to multi fault condition monitoring of mechanical systems in operation, in particular internal combustion engines. This generalization to multi dimensionality and multi fault condition monitoring is possible by utilizing transformed symptom observation matrix, and by successive application of singular value decomposition (SVD) and based on it principal component analysis (PCA). On this basis one can make full ex-traction of fault related information taken from symptom observation matrix, which can be created by traditional monitoring technology. Moreover, by SVD/PCA we can create some independent fault measures and indices, and of overall system condition. In another words, full utilization of SVD/PCA enable us to pass from multi dimensional - non orthogonal symptom space, to or-thogonal generalized fault space, of much reduced dimension. This seems to be important, as it can increase the scope and the reliability of condition monitoring of critical system in operation. It enables also to maximize the amount of condition related information, and to redesign the tradi-tional condition monitoring system. At the end of the paper some introductory consideration are presented leading to a design of Condition Inference Agent (CIA), which will enable to infer in real time on condition of critical objects in operation.