This paper presents a control method for the problem of trajectory jitter and poor tracking performance of the end of a three-joint rigid manipulator. The control is based on a high-order particle swarm optimization algorithm with an improved sliding mode control neural network. Although the sliding mode variable structure control has a certain degree of robustness, because of its own switching characteristics, chattering can occur in the later stage of the trajectory tracking of the manipulator end. Hence, on the basis of the high-order sliding mode control, the homogeneous continuous control law and super-twisting adaptive algorithm were added to further improve the robustness of the system. The radial basis function neural network was used to compensate the errors in the modeling process, and an adaptive law was designed to update the weights of the middle layer of the neural network. Furthermore, an improved particle swarm optimization algorithm was established and applied to optimize the parameters of the neural network, which improved the trajectory tracking of the manipulator end. Finally, MATLAB simulation results indicated the validity and superiority of the proposed control method compared with other sliding mode control algorithms.

The study introduced a finite element model of DQ75t-28m bridge crane metal structure and made finite element static analysis to obtain the stress response of the dangerous point of metal structure in the most extreme condition. The simulated samples of the random variable and the stress of the dangerous point were successfully obtained through the orthogonal design. Then, we utilized BP neural network nonlinear mapping function trains to get the explicit expression of stress in response to the random variable. Combined with random perturbation theory and first-order second-moment (FOSM) method, the study analyzed the reliability and its sensitivity of metal structure. In conclusion, we established a novel method for accurately quantitative analysis and design of bridge crane metal structure.

Aiming at addressing the problem of dust generated when grab is unloaded, the flow field characteristics of fugitive dust in an open space were studied and reflected its unstable and complex nonlinear dynamic process. Using coal, sand, and flour as research objects, an experimental model and measurement system for grab unloading were built, and the dust diffusion range, diffusion speed and direction, settling time, dust concentration, and induced wind velocity at different measurement points were compared. The computational fluid dynamics–discrete element method (CFD-DEM) coupling method was adopted, the discrete phase model (DPM) of dust was established, the interaction of the particle, dust, and airflow fields during the unloading process of the grab was further studied, and the distribution and diffusion laws of the induced airflow and dust were obtained. The acquisition of flow field characteristics is of great significance for controlling and guiding the orderly deposition of dust.

With the application of wireless sensor networks become widespread, supply energy for these wireless sensors proves to be a significant issue. Moreover, for the ambient vibration lies everywhere, the vibration can supply energy for the wireless sensor via energy harvester. The piezoelectric energy harvester becomes the research focus for the simple structure and higher energy conversion efficiency. Due to the transcendental equation in distributed parameter model, the numerical method is become powerful complement for theoretical and experimental method. This paper uses ANSYS to analyze the single piezoelectric cantilever in static analysis, model analysis, harmonic response analysis and mechanical-electrical coupling analysis. It analyzes the natural frequency and voltage effect from four aspects which are length to thickness ratio, length to width ratio, the substrate thickness to piezoelectric thickness ratio and seismic mass. Test and measurement for piezoelectric energy harvester is conduct on the testing platform. Macro cantilever beam piezoelectric energy harvester are tested and measured

Minimizing the power consumption of the belt conveyor is the common wish of all enterprises and even countries. Among all the resistances generated by the belt conveyor during the operation, the indentation rolling resistance accounts for the largest proportion and the power consumed is the largest. Therefore, accurately predicting and reducing the rolling resistance of indentation is the focus of current research. Firstly, based on the three‐element Maxwell solid model, the dynamic loading experiments of cylindrical rubber made of conveyor belt cover material were carried out at different temperatures. The identification models of elastic moduli E₂ and E₃ and viscosity coefficient η₂ in the three‐element Maxwell model were obtained, and then the fitting functions of the three parameters were gotten, which can intuitively reflect the influence of temperature. Secondly, the mathematical model of the indentation rolling resistance was derived. The mathematical model is characterized by the direct parameters such as belt speed v, thickness of backing material h, the idler radius R, and the rubber viscoelastic parameters E₂, E₃, and η₂ and the indirect parameters such as normal force P and temperature T. Afterwards, the effects of belt speed, normal force, temperature, idler radius, and thickness of underlay on the indentation rolling resistance were studied under different working conditions. After that, experimental testing and analysis were fulfilled using test equipment and compared with theoretical analysis results. The results prove that the theoretical results are basically consistent with the experimental results, in line with the actual engineering rules. Finally, the application of the results in practical engineering was analyzed superficially.