Abstract
Safety of bolted joints in industrial machinery is of paramount importance. In this paper, fractional calculus-based predictive modeling has been investigated to control clamping force losses in bolted joints under service loads. Clamp load loss occurs in bolted joints due to application and subsequent removal of an externally applied separating service load on a fastener preloaded beyond its elastic limit. In this work, five different model structures were tried for system identification-based predictive modeling of joint clamp load loss. These structures were the first-order integer, second-order integer, first generation CRONE, fractional integral and fractional-order models. These models were validated by statistical parameters such as FIT, \(R^{2}\), mean squared error, mean absolute error, and maximum absolute error. The fractional-order model with three parameters provided most accurate estimate of the system performance. It also took minimum iterations to reach the optimum controller parameter settings. This model was controlled using PID and fractional PID controllers. Fractional PID controller was designed to minimize integral of squared error (ISE) and toward the convergence of gain/order parameters. The PID controller response exhibited better time domain characteristics as compared to the fractional PID, but suffered from a maximum overshoot as well. In a physical bolted joint, clamp load loss and external service load overshoots may lead to joint failures. Maximum overshoot was totally eliminated by fractional PID controller, proving its safe applicability to the bolted joint system. By choosing a realistic set point for clamp load loss, the maximum permissible external service loading conditions were predicted successfully.
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Shah, P., Sekhar, R. (2021). Predictive Modeling and Control of Clamp Load Loss in Bolted Joints Based on Fractional Calculus. In: Thampi, S.M., Gelenbe, E., Atiquzzaman, M., Chaudhary, V., Li, KC. (eds) Advances in Computing and Network Communications. Lecture Notes in Electrical Engineering, vol 735. Springer, Singapore. https://doi.org/10.1007/978-981-33-6977-1_2
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