Application of advanced data-driven parametric models to load reconstruction in mechanical structures and systems

Abstract

This paper considers a method for reconstructing sine-wave excitation using an inverse, parametric data-driven model developed to monitor the magnitude and frequency of the load to which a structure is exposed. The main goal of the paper is to discuss, and experimentally verify, the applicability of different SISO and MIMO structures of parametric models, such as the ARX, ARARX, OE, BJ, and PEM models described by the linear system identification theory. Experimental validation tests were conducted on a set-up consisting of a metal frame equipped with two electrodynamic exciters, several acceleration transducers and a data-acquisition system. The fidelity and adequacy of various model structures was judged in time and frequency domains based on stability diagrams, FPE and AIC criteria, as well as on the magnitude of the relative error between the measured and reconstructed load. The experimental test results showed that, in the case of measurement data moderately corrupted by noise, the ARX and OE models provide better accuracy of inversion than advanced models, such as ARARAX, BJ or PEM. This leads to the conclusion that increasing the complexity of a model structure does not result in better reconstruction of the load. Therefore, less complicated structures are acceptable for practical applications and, in fact, should be favored.

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“…Finally, an example, in the form of a numerical simulation, is supplied to demonstrate the effectiveness of the control methodology, which is shown to rapidly and efficiently control nonlinear multi-variable systems. Czop (2011) discussed a method for reconstructing sine-wave excitation. Czop developed an inverse, parametric data-driven model to monitor the magnitude and frequency of the load to which a structure is exposed.…”

“…Besides the above successful applications in structural systems, soft computing and artificial intelligence have been successfully applied to the nonlinear system, such as robot manipulation, engineering application and construction managements. With globalisation and the spread of the internet, soft computing and its application are springing up for communications, biology, medicine, the humanities, management sciences, and similar fields (Hsiao et al, 2005a,b,c,d,e;Chen et al, 2004Chen et al, , 2005Chen et al, , 2006a2007a,b,c,d,e,f, 2008a,b,c,d,e, 2009a,b,c,d,e,f, 2010a,b,c,d,e,f,g,h, 2011a,b,c,d,e,f,g,h, 2012aChen, 2006Chen, , 2009aChen, ,b, 2010aChen, ,b, 2011aChen, ,b,c,d,e,f,g,h,i, 2012aHsieh et al, 2006;Tsai et al, 2008;Yang et al, 2008a,b;Yeh et al, 2008Yeh et al, , 2012Lin et al, 2009aLin et al, ,b, 2011aLin et al, ,b, 2012aChen and Chen, 2010a,b;Chen and Saif, 2010;Chiang et al, 2010Chiang et al, , 2011Lee, 2010;Lee et al, 2010aLee et al, ,b 2011aLi et al, 2010;Lin and Chen, 2010, 2011Liu et al, 2010Liu et al, , 2011aLiu et al, ,b, 2012aShih et al, 2010aShih et al, ,b,c, 2011aSolihin et al, 2010;…”

Application of inverse data-driven parametric models in the reconstruction of passenger vehicle wheel vertical movement under ride conditions

“…Nonetheless, the technique (model inversion) is applicable to the problems of load reconstruction in mechanical systems in order to modify the dynamics of a structure or a system and to achieve better performance, e.g. to lower the level of loading forces (Czop, 2010;Mendrok and Uhl, 2004;Uhl, 2007;Giergiel and Uhl, 1989). Load prediction in systems for which the force signal cannot be directly measured due to constructional constraints, as in the case of forces being exchanged by a wheel and the road or rail, is considered to be one of the most practical applications of the inverse approach (Bracciali and Cascini, 1998;Raath and van Waveren, 1998;Torfs et al, 1991).…”

Force localization and reconstruction using a two-step iterative approach

“…For impact monitoring tasks, we do not normally know the impact location in advance, and for contact force measurements between the vehicle and road, there is no appropriate mounting location. This is why inverse force reconstruction techniques (Law et al., 1997; Wang and Chiu, 2003; Czop, 2010; Mendrok and Uhl, 2010; Zhang and Sharf, 2010; Wentzel, 2013; Bernal and Ussia, 2015), which mean that we measure the responses of structures with accelerometers or strain gauges at feasible locations and inversely calculate the forces, need to be developed. However, this inverse-calculation problem is usually mathematically ill-posed.…”