The study combines WSN and smart bolt designs to complete an energy-efficient technology that uses a WSN to monitor bolt connections. Due to the random placement and use of bolts in the real world, we also considered the power consumption, battery life cycle and wireless monitoring mechanism to verify the feasibility of its actual system.  We will develop a smart bolt locking system and smart bolts. These include: Air Controllers, Bolt Sockets and Controller Wireless Connections, Caps, Gateways, and Sensing Bolts. In this system, the controller is connected to the air compressor to control the pressure and flow of the airflow. The bolt sleeve is coupled to the controller via the 2.4GHz RF signal to provide a lock message to the controller for control of airflow. The cap provides sufficient power to the induction bolt in conjunction with the battery. The induction bolt can sense the torque clamping force, looseness, sequence and so on.

The ARM451 Cortex®-M4 core with working voltage can be 2.5V ~ 5.5V, industrial temperature (-40 ℃ ~ 105 ℃), built-in 22.1184 MHz crystal oscillator, configurable Data Flash, strong anti-interference (ESD 8 kV), this series of products are built-in The core of the Digital Signal Processor (DSP) and Floating Point Unit (FPU), with high computing performance, system clock up to 72 MHz. And built-in 12-bit analog-to-digital converter (ADC) with up to 16 channels, and a 12-bit digital-to-analog converter (DAC), can directly handle the strain gauge in the sleeve (strain gauge) The torque analog data obtained by the sense can also be fed back to the front end through the built-in DAC after arithmetic processing to effectively control and correct some non-ideal effects.

This research can sense the state of torque clamping force, loosening, sequence, etc. through the screw sensor sleeve, and through the non-standard protocol radio frequency (proprietary) 2.4GHz RF and torque control gateway connection, so that the mechanical equipment has real-time monitoring, failure Intelligent functions such as prediction, precision compensation, automatic parameter setting, data accumulation, and big data analysis enable the information of each locked screw to be recorded in the cloud database in detail.