The frictional resistance coefficient of ventilation of a roadway in a coal mine is a very important technical parameter in the design and renovation of mine ventilation. Calculations based on empirical formulae and field tests to calculate the resistance coefficient have limitations. An inversion method to calculate the mine ventilation resistance coefficient by using a few representative data of air flows and node pressures is proposed in this study. The mathematical model of the inversion method is developed based on the principle of least squares. The measured pressure and the calculated pressure deviation along with the measured flow and the calculated flow deviation are considered while defining the objective function, which also includes the node pressure, the air flow, and the ventilation resistance coefficient range constraints. The ventilation resistance coefficient inversion problem was converted to a nonlinear optimisation problem through the development of the model. A genetic algorithm (GA) was adopted to solve the ventilation resistance coefficient inversion problem. The GA was improved to enhance the global and the local search abilities of the algorithm for the ventilation resistance coefficient inversion problem.
Real-time monitoring of deformation of large structure parts is of great significance and the deformation of such structure parts is often accompanied with the change of curvature. The curvature can be obtained by measuring changes of strain, surface curve and modal displacement of the structure. However, many factors are faced with difficulty in measurement and low sensitivity at a small deformation level. In order to measure curvature in an effective way, a novel fibre Bragg grating (FBG) curvature sensor is proposed, which aims at removing the deficiencies of traditional methods in low precision and narrow adjusting. The sensor combines two FBGs with a specific structure of stainless steel elastomer. The elastomer can transfer the strain of the structure part to the FBG and then the FBG measures the strain to obtain the curvature. The performed simulation and experiment show that the sensor can effectively amplify the strain to the FBG through the unique structure of the elastomer, and the accuracy of the sensor used in the experiment is increased by 14% compared with that of the FBG used for direct measurement.