Abstract
This chapter presents the application of the last three steps (2, 3, and 4) of the Fault Diagnosis—Inverse Problem Methodology (FD-IPM), as described in Sect. 2.1, to the three benchmark problems that were presented in Sect. 2.4. Step 2 is to evaluate the faults for which only the detection is possible. The third step deals with the solution of an optimization problem with metaheuristics. The fourth step provides the conclusion on the diagnosis of the system, based on the results from the third step. The experiments with the DC Motor, Inverted Pendulum System and Two Tanks System are presented in Sects. 4.2, 4.3 and 4.4, respectively. The Inverted Pendulum System is affected by faults which cannot be diagnosed, only detected. For that reason, Step 2 was only applied to the The Inverted Pendulum System.
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References
Carlisle, A., Dozier, G.: An off-the-self PSO. In: Proceedings of the Particle Swarm Optimization Workshop, Indiana, pp. 1–6 (2001)
Chow, E.Y., Willsky, A.: Analytical redundancy and the design of robust failure detection systems. IEEE Trans. Autom. Control 29, 603–614 (1984)
Derrac, J., García, S., Molina, D., Herrera, F.: A practical tutorial on the use of nonparametric statistical test as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol. Comput. 1(1), 3–18 (2011)
Ding, S.X.: Model-Based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools. Springer, Berlin (2008)
Frank, P.M.: Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy – a survey and some new results. Automatica 26(3), 459–474 (1990)
García, S., Molina, D., Lozano, M., Herrera, F.: A study on the use of non-parametric tests for analyzing the evolutionary algorithms behaviour: a case study on the CEC 2005 Special Session on Real Parameter Optimization. J. Heuristics 15(6), 617–644 (2009)
Hoefling, T.: Detection of parameter variations by continuous-time parity equations. In: 12th IFACWorld-Congress, pp. 511–516 (1993)
Hoefling, T., Isermann, R.: Fault detection based on adaptive parity equations and single-parameter tracking. Control Eng. Pract. 4(10), 1361–1369 (1996)
Kameyama, K.: Particle swarm optimization – a survey. IEICE Trans. Inf. Syst. E92-D(7), 1354–1361 (2009)
Kennedy, J.: Chapter The behavior of particles. In: Evolutionary Programming VII: Proceeding of the Seventh Annual Conference on Evolutionary Programming (EP98). Lecture Notes in Computer Science, vol. 1447, pp. 581–590. Springer, New York (1998)
Silva Neto, A.J., Becceneri, J.C., Campos Velho, H.F. (eds.): Computational Intelligence Applied to Inverse Problems in Radiative Transfer. EdUERJ, Rio de Janeiro, Brazil (2016)
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Camps Echevarría, L., Llanes Santiago, O., Campos Velho, H.F.d., Silva Neto, A.J.d. (2019). Applications of the Fault Diagnosis: Inverse Problem Methodology to Benchmark Problems. In: Fault Diagnosis Inverse Problems: Solution with Metaheuristics. Studies in Computational Intelligence, vol 763. Springer, Cham. https://doi.org/10.1007/978-3-319-89978-7_4
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