| 摘要 |
An opto-mechanical torque sensing device suitable for use with rotary machinery integrates a photoelastic polymer detector, a light source, a photoelastic image sensor and an artificial intelligence neural network and algorithm. The photoelastic polymer is formed into a hollow cylinder and bonded to metal collars located at each end of the cylinder. The collars serve to readily place the cylinder detector over a machine shaft and affix it to the shaft using a keyway, setscrew, or spring pin. Alternatively, split collars and a split sleeve can also be used to clamp the detector to the shaft. In the presence of polarized light, the photoelastic polymer detector generates an optical fringe pattern that varies as a function of torque applied to the shaft or other machine part on which the detector is mounted. The artificial intelligence neural network learns the mapping relationship between the observed optical fringe pattern and the applied torque using a training procedure. Once trained, the neural network generates a signal representative of torque in the shaft based on observed fringe pattern.
|
