Similar to human joints, various types of bearings (such as joint bearings, sliding bearings, rolling bearings and various articulations) are also joints of mechanical equipment. It is a device that connects two or more rotating pairs, and is widely used in various structures, mechanisms and equipment. For thousands of years, people have used them for its working state, therefore they can only be maintained regularly or installed sensors far away from the monitored connection pair were used. This method can neither detect the failure of the connection pair in time nor detect the early fault signals causing a machine failure. FATRI has successfully developed a joint neuron module using MEMS micro-sensors, wireless communications, and AI technology. The neuron module can sense the temperature, temperature gradient, vibration and vibration gradient of all kinds of connection pairs, and can sense all kinds of early fault signals and other physical parameters of connection pairs through the self-learning mechanism of artificial intelligence.
This system is used to detect faults and dynamics parameters in all types of machines and mechanisms.The module has the characteristics of self-supply, extreme high sensitivity, excellent signal-to-noise ratio, a self-learning function, software embedded expert system, small module size and a good physical embedded package.
Maximum tolerance in centrifugation
The equipotential diagram describes the selection of the sensor according to the rotation and the axial distance of the installation position. The calculation formula is g=1/900R(pi N), R is the axial distance (m) of the installation position, N is the rotational speed (r/min), and the three equipotential lines are 200g, 800g and 2000g, respectively.