Journal of Advanced Mechanical Design, Systems, and Manufacturing, Vol 17, Iss 4, Pp JAMDSM0045-JAMDSM0045 (2023)

Subjects

sensor, actuator, control, mechatronics, input/output equipments, audio/visual equipments, intelligent sensors, control systems, autonomous and decentralized/distributed systems, intelligent systems, Engineering machinery, tools, and implements, TA213-215, Mechanical engineering and machinery, and TJ1-1570

Abstract

The infrastructure built in the 1950s has deteriorated beyond its service life. However, replacing all infrastructure is very difficult and involves huge replacement costs. To address this problem, the optimization of maintenance operations and participation of various stakeholders in the maintenance is required; however, maintenance technology and social cognition in terms of infrastructure deterioration remains insufficient. In this study, we perform research and development simultaneously to improve maintenance technology and social cognition. However, technological issues exist, such as lack of high-reliability diagnoses and optimized scheduling of maintenance, and optimized repair methods. In particular, this study focuses on high-reliability diagnosis. Next, communication of information between stakeholders and infrastructure is required to improve social cognition in terms of infrastructure deterioration. Particularly, in this study, the infrastructure with communication function between the residents and infrastructure is referred to as “future intelligent infrastructure.” We prototype a vibration-sensing-actuation device for a future intelligent infrastructure. In particular, we focus on the detection of the water main deterioration and estimation of the ground soil internal state. Then, the operation of the minimum valuable function is verified. The concept and fundamental functions of the vibration-sensing-actuation device are proposed. Moreover, a prototype device that functionally limits the active and dynamic sensing and simplifies autonomous discrimination is implemented for deterioration detection of the water main. Consequently, the fundamental operation of pipe-thinning detection is confirmed. Furthermore, an application for ground soil internal state estimation was considered. Consequently, the fundamental operation of detecting change in soil stiffness was confirmed.

Mechanical Engineering Journal, Vol 10, Iss 1, Pp 22-00002-22-00002 (2023)

Subjects

random vibration, system identification, fokker-planck equation, vibration experiment, maximum likelihood estimation, Mechanical engineering and machinery, and TJ1-1570

Abstract

This paper discusses a new identification method for a linear single-degree-of-freedom system that uses a Gaussian random response and is based on the maximum likelihood estimation (MLE) method. The likelihood function of the proposed method consists of the analytical solution of the Fokker–Planck equation. We have already published a paper on theoretical and numerical considerations. However, in that study, the experimental verification of the proposed identification method was not performed. Therefore, in this study, we conduct an experimental verification of the proposed identification method. First, the identification algorithm is formulated in a spring-mass-damper system subjected to white noise excitation by a moving foundation to correspond to the actual experimental setup. A preliminary experiment in terms of the excitation source is conducted using a vibration speaker. In addition, the experimental modal analysis is performed to confirm the validity of the vibratory system. The fundamental operation test of the identification method is performed using the actual experimental random response data, and a dependency survey of the number of samples is conducted. From the results, the convergence behaviors of the estimation value are observed with an increasing number of samples in the spring constant and the ratio between the diffusion coefficient and the damping constant. In addition, benchmark tests are conducted using the half–power method (HPM) based on spectral analysis and the auto-regressive method (ARM) based on time–series analysis. In the case of spring constant estimation, the behaviors of the estimation value that converge to the true value are observed in all identification methods. In the ratio between the diffusion coefficient and damping constant, the behavior of the estimation value that converges to the true value is observed only in the proposed identification method.

system identification, random vibration, maximum likelihood estimation, Mechanical engineering and machinery, TJ1-1570, Engineering machinery, tools, and implements, and TA213-215

Abstract

This paper discusses the new identification method of a linear single-degree-of-freedom system using Gaussian random vibration response. The propose method is based on the method of Maximum Likelihood Estimation (MLE). The likelihood function of the proposed method is composed from the analytical solution of Fokker-Planck equation. The estimation formulas of unknown parameter are obtained by maximization of the original likelihood function. The obtained estimators represent the population variance estimation problem of multivariate Gaussian model. Furthermore, the numerical identifications are conducted using the random vibration response by calculation result of the 4th Runge-Kutta method. In the result, the estimation performance of the propose method is confirmed in terms of the dependency of sample number and dependency of the damping coefficient. Especially, the proposed method is implied the application to identification problem of the large damping system. Quantification of the large damping characteristic is the important problem, because it is the difficult problem in the conventional identification method. Moreover, the benchmark tests are conducted with Half-Power Method (HPM) based on the spectral analysis and Auto-Regressive Method (ARM) based on the time series analysis, respectively. The results of the benchmark test are shown in the accuracy of the propose method is higher than its of HPM and ARM, respectively. Finally, the expansion to the recursive estimation algorithm is conducted using MLE estimator of recurrence form. In addition, the operation of the recursive algorithm is confirmed.

system identification, nonlinear vibration, learning, kalman filter, diagnostics, modeling, Mechanical engineering and machinery, TJ1-1570, Engineering machinery, tools, and implements, and TA213-215

Abstract

The author proposed the identification method of symmetric nonlinear system based on the Auto-Regressive analysis and the method of averaging in a previous paper. However, there is a problem that conventional methods including the one in the previous paper cannot address the identification of asymmetric vibrating systems. In this paper, the system identification in asymmetric nonlinear system is investigated. At first, formulation of identification problem is conducted. The identification problem is described using the method of Krilov-Bogoliubov-Metropolsky is considered the two-order approximation. The description contains the amplitude dependency however coefficient of the sign cannot discriminate. Therefore, this paper proposes a new system identification method to solve these problems by identifying appropriate sign of nonlinear parameters based on movement of center-of-vibration. Identification experiment is conducted using numerical investigation, Runge-Kutta method. A nonlinear coefficient is considered in two cases: positive number and negative number. In both cases, the proposed method gives good estimated results which show good agreement with the true values. Moreover, identification experiment is conducted using the cantilever system subjected to the magnetic force. The proposed method gives estimated results which shows good agreement with the true experiment values.

diagnosis, pipe inspection, cylindrical shell, finite element method, vibration analysis, coupled vibration, Mechanical engineering and machinery, TJ1-1570, Engineering machinery, tools, and implements, and TA213-215

Abstract

In this paper, deterioration diagnosis for distribution main pipe was studied using the uniform cylindrical shell approximation and in-plane bending mode. The in-plane bending mode is expected to have high accuracy in detection of deterioration, because the eigen frecuency of the mode is proportional to pipe thickness. First, using the finite element method, the characteristics of in-plane bending mode are investigated. It is confirmed that in-plane bending mode has little small dependence on the pipe length and the boundary conditions at the pipe ends, it appears in the audio frequency bands, and it has linear dependence on the pipe thickness. In addition, formula with two dimensional ring approximation is derived. Moreover, the average thickness and the uniform-cylindrical shell approximation are introduced for deal with the deteriorated pipe. Using the thinning pipe thickness of previous study, validity of the average thickness and the uniform-cylindrical shell approximation were confirmed. On the other hand, actual pipeline has the sub-structure, for example, valve, hydrant, and so on. In order to deal with the coupled vibration between the cylindrical shell and the sub-structure, eigenvalue analysis are conducted using the Semi-Analytical Receptance Method (SARM). The experimental consideration were conducted in case of that the sub-structure non-attached case. The in-plane bending mode is observed experimentally on the actual pipe system and its resonant frequency shows good match with the theoretical values.