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In order to reduce the natural frequency of the piezoelectric vibration energy harvester, improve the output power of the piezoelectric vibration energy harvester, and meet the demand of power supply for the low-power wireless switch in the low-frequency vibration environment, an asymmetric hybrid supported beam piezoelectric vibration energy harvester is proposed. The theoretical model of the hybrid support beam was established. The correlation factors affecting the open-circuit voltage and the total output power of the hybrid braced beam were analyzed. The dimensional parameters of the hybrid supported beam piezoelectric energy harvester were optimized by using the optimization method of orthogonal experiments. Different coincidence degrees experiments were used to further optimize the structural design of the hybrid support beam. The test results show that the maximum output power is 770 μW, when the external excitation frequency is 1.0 g and the external resistance is 50 kΩ. Finally, a wireless switch test system was established, and the piezoelectric vibration energy harvester was experimentally verified to be capable of powering the wireless switch.

This study proposes a new approach to gait recognition using LoRa signals, taking into account the challenging conditions found in underground coal mines, such as low illumination, high temperature and humidity, high dust concentrations, and limited space. The aim is to address the limitations of existing gait recognition research, which relies on sensors or other wireless signals that are sensitive to environmental factors, costly to deploy, invasive, and require close sensing distances. The proposed method analyzes the received signal waveform and utilizes the amplitude data for gait recognition. To ensure data reliability, outlier removal and signal smoothing are performed using Hampel and S-G filters, respectively. Additionally, high-frequency noise is eliminated through the application of Butterworth filters. To enhance the discriminative power of gait features, the pre-processed data are reconstructed using an autoencoder, which effectively extracts the underlying gait behavior. The trained autoencoder generates encoder features that serve as the input matrix. The Softmax method is then employed to associate these features with individual identities, enabling LoRa-based single-target gait recognition. Experimental results demonstrate significant performance improvements. In indoor environments, the recognition accuracy for groups of 2 to 8 individuals ranges from 99.7% to 96.6%. Notably, in an underground coal mine where the target is located 20 m away from the transceiver, the recognition accuracy for eight individuals reaches 93.3%.

In order to solve the problems of nonlinearity, uncertainty and coupling of multi-hydraulic cylinder group platform of a digging-anchor-support robot, as well as the lack of synchronization control accuracy of hydraulic synchronous motors, an improved Automatic Disturbance Rejection Controller-Improved Particle Swarm Optimization (ADRC-IPSO) position synchronization control method is proposed. The mathematical model of a multi-hydraulic cylinder group platform of a digging-anchor-support robot is established, the compression factor is used to replace the inertia weight, and the traditional Particle Swarm Optimization (PSO) algorithm is improved by using the genetic algorithm theory to improve the optimization range and convergence rate of the algorithm, and the parameters of the Active Disturbance Rejection Controller (ADRC) were adjusted online. The simulation results verify the effectiveness of the improved ADRC-IPSO control method. The experimental results show that, compared with the traditional ADRC, ADRC-PSO and PID controller, the improved ADRC-IPSO has better position tracking performance and shorter adjusting time, and its step signal synchronization error is controlled within 5.0 mm, and the adjusting time is less than 2.55 s, indicating that the designed controller has better synchronization control effect.

At present, SLAM is widely used in all kinds of dynamic scenes. It is difficult to distinguish dynamic targets in scenes using traditional visual SLAM. In the matching process, dynamic points are incorrectly added to the pose calculation with the camera, resulting in low precision and poor robustness in the pose estimation. This paper proposes a new dynamic scene visual SLAM algorithm based on adaptive threshold homogenized feature extraction and YOLOv5 object detection, named AHY-SLAM. This new method adds three new modules based on ORB-SLAM2: a keyframe selection module, a threshold calculation module, and an object detection module. The optical flow method is used to screen keyframes for each frame input in AHY-SLAM. An adaptive threshold is used to extract feature points for keyframes, and dynamic points are eliminated with YOLOv5. Compared with ORB-SLAM2, AHY-SLAM has significantly improved pose estimation accuracy over multiple dynamic scene sequences in the TUM open dataset, and the absolute pose estimation accuracy can be increased by up to 97%. Compared with other dynamic scene SLAM algorithms, the speed of AHY-SLAM is also significantly improved under a guarantee of acceptable accuracy.

As an important equipment for deep well hoisting, the safe and stable operation of the Blair mine hoist is vital for the development and utilization of deep mineral resources. However, it is always a challenging task to keep consistent wire rope tension in the event of an actuator fault. In this study, an adaptive dynamic surface technology-based actuator fault-tolerant scheme is proposed. A fault observer with a neural network adaptation term is designed to estimate the loss of actuator efficiency caused by faults. Considering the redundant characteristic of the two actuators, a novel dynamic surface technology-based controller with a fuzzy assignment and state constraints is developed to eliminate the impact of fault. The stability of the closed-loop system under the proposed strategy is theoretically proved by rigorous Lyapunov analysis. Comparative experiments under various conditions are carried out on a xPC based mine hoist platform, and the results show the applicability together with the superiority of the proposed scheme.

To overcome high periodic maintenance requirements, difficult replacement, and large application limitations of wireless sensor nodes powered by chemical batteries during the vibration control process of stiffened plates, a two-degree-of-freedom diagonal beam piezoelectric vibration energy harvester was proposed. Multidimensional energy harvesting and broadband work are integrated into one structure through the combined action of oblique angle, mass blocks, and piezoelectric beam. The mechanical model of the beam is established for theoretical analysis; the output characteristics of the structure are analyzed by finite element simulation; a piezoelectric energy harvesting experimental bench is built. The results show that: The structure has a wider harvesting band, multi-order resonant frequency, multi-dimensional energy harvesting, and higher output voltage and power than the traditional cantilever structures. The output performance of the specimens with 45° oblique angle, 5 g:5 g mass ratio, and 0.2 mm thickness of piezoelectric substrate is good in the frequency band of 10~40 Hz. When the excitation frequency is 28 Hz, the output voltage of the sextuple array structure reaches 19.20 V and the output power reaches 7.37 mW. The field experiments show that the harvester array can meet the requirements of providing auxiliary energy for wireless sensor nodes in the process of active vibration control of stiffened plates.

In order to reduce the natural frequency of the piezoelectric vibration energy harvester, improve performance of the piezoelectric vibration energy harvester, and meet the requirements of energy acquisition in the low-frequency vibration environment, a variable-section circular piezoelectric vibration energy harvester is presented. The dynamic model and electromechanical coupling model of variable-section circular piezoelectric vibration energy harvester are established. The main factors affecting the output performance of piezoelectric vibration energy harvester are analyzed. The structure parameters of piezoelectric vibration energy harvester are optimized by orthogonal experiment. An experimental platform is built to test output voltage and output power of piezoelectric vibration energy harvester. The experimental results show that when the number of energy harvester is 4 and the external load is 180KΩ, the parallel output power can reach 0.213mW, which can meet the requirements of micro-power device power supply.

In order to realize 3-dimensional, wide-band vibration energy harvesting in low-frequency and low-amplitude environments, a multi-layer Z-type beam piezoelectric harvester structure is proposed. Nonlinear mass and instabilities of horizontal and longitudinal are introduced by the multi-layer Z-type beam structure. Simulation and experiment results show that when the number of beam layer is 7 and excitation intensity is 0.8 g, there are more than 4 voltage peaks within 5–40 Hz, the maximum voltage is above 16 V, the maximum output power can reach 180 μW, which greatly widens harvesting frequency band. When exciting in horizontal and vertical directions, the maximum voltages peaks are all above 10 V, the number of voltage peaks are all above 5, maximum output powers can reach 108 μW and 53 μW respectively, by which 3-dimensional energy harvesting is verified. Next, the performances of arrays are studied. When the arrays number is 12, excitation intensity reduces to 0.2 g, nearly 90% of the voltage response amplitudes for parallel arrays within 15–40 Hz are above 4 V, almost all the voltage response amplitudes for series arrays are above 5 V within 17–40 Hz, even response amplitudes are all above 10 V within 23–33 Hz. The maximum output power generated by parallel arrays is up to 864.5 μW. So, wide-band 3-dimensional vibration energy harvesting for low amplitude environment is realized by multi-layer Z-type vibration energy harvester. Finally, the feasibility that wireless switch could be powered by the multi-layer Z-type vibration energy harvester parallel arrays from low-frequency and low-amplitude environment is verified. [ABSTRACT FROM AUTHOR]