Journal of Advanced Mechanical Design, Systems, and Manufacturing, Vol 18, Iss 1, Pp JAMDSM0005-JAMDSM0005 (2024)
sensor, actuator, control, mechatronics, input/output equipments, audio/visual equipments, intelligent sensors, control systems, intelligent systems, Engineering machinery, tools, and implements, TA213-215, Mechanical engineering and machinery, and TJ1-1570
Water pipes have exceeded their service life, and the number of leakage and burst accidents is increasing. These accidents cause economic losses due to the interruption of operations and supply. However, replacing all the deteriorated pipes is difficult, as this would involve a huge cost and long time. Therefore, the condition of water pipes must be quantified, and an efficient maintenance management is required. Current sensors for detecting water leakage have many problems because their measurement principle is a passive system, and thus they are susceptible to external noise. In our previous study, we proposed an active vibration sensing-actuation device to improve the measurement reliability for a water pipe deterioration diagnosis. The principle of deterioration diagnosis was based on the detection of the frequency change of the in-plane bending mode. In that study, the thresholds of discrimination were determined by the amplitude of the response based on empirical knowledge, which did not allow for theoretical or systematic discrimination. In this study, we focused on a simplified discrimination method of deterioration of a water pipe and its implementation with an IoT sensor module. The following three methods were considered in terms of implementation cost: an absolute threshold method based on theoretical random vibration analysis (based on a physical model), a linear discrimination method, and a support vector machine (based on a machine learning model), and the most appropriate discrimination method was determined. Furthermore, we considered the discrimination accuracy of models based on physics and machine learning. The results show that the support vector machine has the best accuracy, followed by the absolute threshold method, which has good accuracy. However, when compared in terms of computational complexity, the absolute threshold method is superior from both perspectives in terms of implementation. However, the application of the absolute threshold method is limited to the case where the physical characteristics of the sensing target are well known. In the case of unknown physical characteristics of the target, the method based on machine learning can be applied.
Journal of Advanced Mechanical Design, Systems, and Manufacturing, Vol 17, Iss 4, Pp JAMDSM0045-JAMDSM0045 (2023)
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
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.