Bolted joints are widely used in various sectors due to the ease of connecting two or more parts, but the loss of torque in the bolts of this connection can cause catastrophic failures. This article presents a new piezoresistive sensor composed of a nanocomposite material with rubber, carbon black, and carbon nanotubes designed for monitoring structural health in bolted joints using a new approach for detecting tightening variation. The sensor combines rubber-like flexibility with enhanced conductivity thanks to incorporating carbon nanostructures. The properties of the rubber are thoroughly examined, and the sensor is tested in various scenarios. Its behavior and resistive response are first evaluated under cyclic loading to assess durability and functional reliability. The sensor is also analyzed for its response to environmental effects such as temperature and humidity, and their influence on measurements is evaluated. After that, the sensor is studied as an automatic and static indicator for detecting torque variation when coupled with bolted joints in a structure. This application leverages the sensor’s ability to detect variations in electrical resistance caused by changes in tightening torque, providing a method for identifying such issues. The study indicates the new sensor reliably responds to cyclic loading with resistance variation. Environmental conditions can introduce variations in influence depending on the material’s conductivity level. The sensor was applied to a bolted joint, and the variation in bolt torque can be related to the variation in electrical resistance. In addition, the percentage of nanomaterials makes the sensor more or less sensitive to the torque level, making it possible to produce a sensor for different torque ranges. For the most sensitive sensor, there was a variation of 60% in the measurements after varying by 2 Nm. At the same time, the second, with more nanomaterials, changed the resistance by another 40% for a range of 6 Nm. Furthermore, its application in identifying tightening variations has proven sensitive and effective, successfully detecting torque variations in bolts.
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