Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines

Study on Dynamic Monitoring of Wire Rope Tension Based on the Particle Damping Sensor

Real-time monitoring of wire rope tension is of great significance to the safe operation of mine hoist. Due to the longitudinal and lateral coupling vibration of wire ropes during the operation of hoist, there are high frequency components in measured tension signals of wire ropes, which cannot effectively characterize the actual lifting load. To overcome this problem, a particle damping sensor with a vibration dissipation function is designed in this paper. Multilayered steel balls are placed into the cylindrical cavity of the sensor. Damping vibration and energy dissipation will occur when the sensor is subjected to external excitation. Then, to obtain the optimal sensor characteristics, relevant parameters of the particles and the spoke structure are simulated. Finally, the sensor based on the optimized parameters is manufactured and tested in a coal mine. Compared with the general pressure sensor, the particle damping sensor can effectively eliminate the influence of wire ropes vibration on tension measurement and achieve accurate measurement results.

Hybrid Particle Swarm Optimization for Multi-Sensor Data Fusion

A hybrid particle swarm optimization (PSO), able to overcome the large-scale nonlinearity or heavily correlation in the data fusion model of multiple sensing information, is proposed in this paper. In recent smart convergence technology, multiple similar and/or dissimilar sensors are widely used to support precisely sensing information from different perspectives, and these are integrated with data fusion algorithms to get synergistic effects. However, the construction of the data fusion model is not trivial because of difficulties to meet under the restricted conditions of a multi-sensor system such as its limited options for deploying sensors and nonlinear characteristics, or correlation errors of multiple sensors. This paper presents a hybrid PSO to facilitate the construction of robust data fusion model based on neural network while ensuring the balance between exploration and exploitation. The performance of the proposed model was evaluated by benchmarks composed of representative datasets. The well-optimized data fusion model is expected to provide an enhancement in the synergistic accuracy.

Application of FRP Bolts in Monitoring the Internal Force of the Rocks Surrounding a Mine-Shield Tunnel

Monitoring the internal force of the rocks surrounding a mine-shield tunnel for the initial support of a mine-shield tunnel, in complex geological and hydrological environments, requires bolts with specific features such as high tensile strength, low shear strength, good insulation and resistance to corrosion. As such, internal force monitoring has become an important issue in safety monitoring for such tunneling projects. In this paper, the adaptability of a mine-shield tunnel project in a corrosive environment is investigated. A fiberglass reinforced plastic (FRP) bolt with high tensile strength, low shear strength, resistance to fatigue, non-conductivity and resistance to corrosion is used as a probe in tandem with an anchor-head dynamometer to monitor the internal force of the rocks surrounding a mine-shield tunnel for initial support. Additionally, solar energy collection technology is introduced to create a remote monitoring system. Using a 2.5 km long railway tunnel located in the northeast of the Pearl River Delta of China as a case study, the present study shows that, compared with a conventional steel bolt, the FRP bolt has advantages, such as avoidance of the risks associated with the shield machine, insulation and resistance to corrosion. As a probe, the response of the FRP bolt to events such as a blasting vibration and a construction disturbance that results in internal changes in the surrounding rock demonstrates a clear pattern that is appropriate for monitoring the internal force of the rocks surrounding a mine-shield tunnel in a corrosive environment. FRP bolt-based monitoring not only provides new technological support for controlling the risk involved in the initial support of a mine-shield tunnel but can also be widely deployed in projects with special requirements for disassembly, conductivity and corrosion.

The Video Collaborative Localization of a Miner's Lamp Based on Wireless Multimedia Sensor Networks for Underground Coal Mines

Based on wireless multimedia sensor networks (WMSNs) deployed in an underground coal mine, a miner's lamp video collaborative localization algorithm was proposed to locate miners in the scene of insufficient illumination and bifurcated structures of underground tunnels. In bifurcation area, several camera nodes are deployed along the longitudinal direction of tunnels, forming a collaborative cluster in wireless way to monitor and locate miners in underground tunnels. Cap-lamps are regarded as the feature of miners in the scene of insufficient illumination of underground tunnels, which means that miners can be identified by detecting their cap-lamps. A miner's lamp will project mapping points on the imaging plane of collaborative cameras and the coordinates of mapping points are calculated by collaborative cameras. Then, multiple straight lines between the positions of collaborative cameras and their corresponding mapping points are established. To find the three-dimension (3D) coordinate location of the miner's lamp a least square method is proposed to get the optimal intersection of the multiple straight lines. Tests were carried out both in a corridor and a realistic scenario of underground tunnel, which show that the proposed miner's lamp video collaborative localization algorithm has good effectiveness, robustness and localization accuracy in real world conditions of underground tunnels.