Damage detection of structural members using internet of things (IoT) paradigm

Abstract

Abstract Structural Health Monitoring (SHM) has gained a lot of importance in today’s scenario. Significant reduction in the cost of sensors and connectivity, made remote data collection possible to monitor the structures and perform critical analysis so that actions can be taken to assess and enhance the residual life of the structures. Internet of Things (IoT) is the system of smart sensors that combines sensing and transmission of various responses of the structures to distant servers which continuously processes and monitors these responses. The present paper proposes an integrated platform of IoT for damage detection using a Wi-Fi module, Raspberry Pi, (Piezoelectric) PZT sensors along with Digital to Analog (DAC) and Analog to Digital converters (ADC). Responses from the host structure are extracted by the PZT sensors and a mathematical model is proposed to identify and quantify the damage compared with responses of the healthy structural member. The algorithm is executed using Python in Raspberry Pi. The present work includes testing of simply supported aluminium beam surface bonded with PZT transducers where one is an actuator and the other is a sensor. The beam is excited by a sinusoidal wave through an actuator. The digital wave sent from Raspberry Pi is converted to analog using DAC and excites the beam through the actuator. The responses received from the sensor is converted to digital form using ADC. The responses are initially taken for healthy beam and for the same beam, a sequential increase in crack widths is induced. Responses of the healthy and damaged beam are compared using Cross-Correlation (CC) damage index to identify the extent of the damage. The CC values are analyzed and sent to the cloud where an alert message is sent to mobile if the CC value exceeds the threshold limit.