YOLOv3-MSSA based hot spot defect detection for photovoltaic power stations

With the continuous development of the energy industry, photovoltaic power generation is gradually becoming one of the main power generation methods. However, detecting hot spot defects in photovoltaic power stations is challenging. Therefore, enhancing detection efficiency using information technology has become a crucial aspect. The study presents a defect detection model for PV power stations using the YOLOv3 (You Only Look Once v3) algorithm. The model incorporates coordinate attention module (CAM) and self-attention module (SAM) to improve feature extraction in low-resolution conditions. The Multi objective Sparrow is employed to achieve multiple objectives. It is very contributing in the detection of low-resolution features. It shows that the research method can reduce the loss value to 0.009 after 400 iterations of the loss curve test. The precision-recall (P-R) curve generated by the research method only starts to drop sharply when the Recall value reaches 0.96. The number of parameters generated by the research method is 3.46×106. The detection accuracy of the research method reaches 98.86 % when there are five defective fault types. The results indicate that the proposed research method offers improved detection speed and higher accuracy in identifying hot spot defects in PV power stations. This technology provides valuable support for hot spot defect detection and presents new opportunities for the field

Optimization of a commercial vehicle powertrain mounting system based on new rubber mounts

In order to improve the vibration isolation, environmental adaptability and development efficiency of rubber mounts, a novel rubber mount with adjustable parameters such as stiffness, support height and limit distance was proposed, and its structural composition and working principle were described. And then, a commercial vehicle was taken as the research object to conduct the calculation of mounts stiffness by employing the energy decoupling method and genetic algorithm. On the basis of the influence of cone angle, thickness and height on the ratio of axial-radial stiffness, the detailed structural design of the mounts was carried out, and the relationship between the preloading displacement and axial-radial stiffness was studied by the method of theoretical calculation and test, which made the process of the stiffness adjustment more specific and accurate. Finally, the vibration isolation performance test of the Powertrain Mounting System (PMS) before and after stiffness adjustment was completed. Results show that the adjusted PMS indicates better vibration isolation performance at idle speed and slow acceleration in place, and the new mounts can effectively improve the vibration performance of vehicle, environmental adaptability of mounts and product development efficiency

Comparison of optical 3D scanner and coordinate measurement system from the standpoint of macro-geometry measurement

The aim of the experiment described in the paper was to determine the possibility of using an optical 3D scanner to measure the macro-geometry of cutting tools. To verify this possibility, a precise component was measured, and the accuracy of optical 3D scanner was compared to a tactile coordinate measurement machine. A precise cemented carbide rod was used as a reference part and the measurement data were compared with the measurement result from the ZEISS Prismo coordinate measurement machine. The data obtained from the measurements were evaluated and compared. The experiment was carried out so that the use of an optical 3D scanner to measure cutting tools could be verified based on the desired requirements. Both dimensions and geometrical tolerancing – circularity were measured. The experiment has shown that an optical 3D scanner can achieve sufficient accuracy for the purpose of measuring macro-geometry of cutting tools

A simple harmonic quantum oscillator: fractionalization and solution

A quantum mechanical system that mimics the behavior of a classical harmonic oscillator in the quantum domain is called a simple harmonic quantum oscillator. The time-independent Schrödinger equation describes the quantum harmonic oscillator, and its eigenstates are quantized energy values that correspond to various energy levels. In this work, we first fractionalize the time-independent Schrödinger equation, and then we solve the generated problem with the use of the Adomian decomposition approach. It has been shown that fractional quantum harmonic oscillators can be handled effectively using the proposed approach, and their behavior can then be better understood. The effectiveness of the method is validated by a number of numerical comparisons

Lightweight steering equipment based on prestressed modal analysis

As the key component to control the driving direction of the vehicle, the steering device always bears large vibration and load. In order to improve structural performance and reduce costs, a multi-objective optimization method based on the results of prestressed modal analysis was proposed, which can achieve significant lightweight and cost-effectiveness improvement. Based on the principle and working characteristics of the steering device, the minimum value of mass, minimum value of maximum stress, maximum value of equivalent stiffness were set as optimization objectives. Through finite element analysis, the prestressed modal module was constructed, and the strength and modal characteristics of the steering device were obtained. In order to verify the accuracy of prestressed modal analysis, the vibration testing experimental platform was built in a non free state. The excitation and response signals can be obtained through sensors and data acquisition devices and used as input and output data. According to the comparative analysis of simulated vibration modes, it can be concluded that the coupling analysis of strength and mode is more in line with actual boundary conditions and has high reliability. The DOE (Design of Experience) method was adopted to construct discrete corresponding values between design variables and optimization objectives based on the results of prestressed modal analysis. In order to better evaluate the cost-effectiveness of lightweight, a comparative analysis was conducted on the results of primary and secondary lightweight. The results show that the prestressed modal analysis method can achieve good dynamic analysis accuracy. Without reducing strength and equivalent stiffness, the mass of the steering device can be reduced by 14 %, achieving high economic benefits

Optimizing mechanical properties of virgin and recycled PLA components using Anova and neural networks

The increasing demand for polymers in additive manufacturing (AM) has led to a significant increase in plastic waste, with over 300 million metric tons used in recent years. This research article explores the use of Poly Lactic Acid (PLA) as a biodegradable thermoplastic recycled material for 3D printed components, comparing its properties with virgin PLA and discussing solutions for variation and mechanical features improvement. Fused Deposition Modeling (FDM) is a widely used additive manufacturing process that allows for the creation of three-dimensional objects by depositing molten material layer by layer. This study investigates the impact of infill density, layer thickness, and raster angle for recycled 3D printing material, focusing on their dimensions and their influence on processing efficiency. This research paper aims to investigate the mechanical effects of recycled 3d printed components which are printed by using FDM with the combination of different process parameters compared with virgin PLA. From results optimal process parameters are found to enhancing quality and performance of recycled 3D printed components. Later results are compared by Analysis of Variance (ANOVA) as a statistical tool and also with ANN technique, which minimizes error deviation

Laser cladding powder flow field detection system based on ISR optimization algorithm

In coaxial powder feeding laser cladding, the morphology of the powder flow field is crucial for the forming quality. Therefore, this study utilizes high-speed imaging technology and an Image Super Resolution algorithm to create a laser cladding powder flow field detection system that is capable of detecting and tracking powder particles in the laser cladding environment. The experiment shows that the optimized algorithm has significant improvement in structural similarity indicators, with an improvement rate of nearly 11 %. For powder particle tracking, the distance accuracy of the optimized model is 1.5 lower than that of the unimproved model. In addition, by combining with the Kalman filtering algorithm, the tracking effect of powder particles has been further improved. This paper also found a relationship between powder transfer rate and powder utilization rate. In summary, the powder flow field analysis based on visual detection and image processing technology designed in this study can effectively reflect and predict the trend of changes in cladding quality

A gear fault diagnosis method based on variational mode decomposition and multi-scale discrete entropy

Aiming at monitoring of gearbox faults, a gear fault feature extraction method based on variational mode decomposition (VMD) and multi-scale discrete entropy (MDE) is proposed in this paper. Firstly, the gear fault signal is decomposed into a series of intrinsic modal function (IMF) by VMD with selected parameters; Secondly, the decomposed IMF are extracted by MDE feature extraction method to form a feature sample set; Finally, the least square support vector machine (LSSVM) is used to classify the data set after feature extraction. The experiment results show that the proposed method owns the higher fault diagnosis accuracy than the traditional multi-scale entropy methods

Effect of train traction on the wheel polygonal wear of high-speed trains

High-order polygonal wear of wheels is one of the most severe technical challenges for China's high-speed trains at present, and its formation mechanism has not been thoroughly understood. The effect of train traction on the wheel polygonal wear of high-speed trains was studied based on a wheel/rail rolling contact finite element model. The frequency domain characteristics of unstable vibration of the wheel/rail system under rolling/sliding contact were studied by using the finite element complex modal analysis method. We also examined wheel/rail contact forces and friction in the time domain. The cause of the high-order polygonal wear of Chinese high-speed train wheels was revealed. The effect of the vehicle speed and the wheel diameter on wheel polygonal wear were investigated. The results show: the friction-induced vibration of the wheel/rail system will be excited when the rolling/sliding contact between the wheel and rail. The radial zoom modal of the wheel is an unstable mode, which is the main cause of the 21-22 order polygonal wear of the high-speed train wheels in China. Additionally, vehicle speed has a linear relationship with the order of polygonal wear. Reducing the vehicle speed helps to control the polygonal wear of the wheels. Wheels of different diameters exhibit varying degrees of polygonal wear, with smaller wheels being more resistant to friction-induced vibrations

Gear error control and response of electric vehicle transmission gearing based on gear trimming

The lightweight development of electric vehicle motors is a prominent future trend, with the challenge of transmission vibration and noise acting as a key bottleneck that limits the enhancement of power and speed in electric vehicle drive systems. The noise generated by electric vehicle transmissions is primarily associated with the transmission system and gear structure. In line with this, the present study proposes an analysis of transmission error and response mechanisms through gear modifications. The research delves into the analysis of gear deformation and error generation characteristics. It further investigates methods for parametric equation modeling, tooth profile modification, deformation imprint analysis, and vibration response modeling to examine excitation response analysis and noise reduction techniques pertaining to transmission errors. The findings demonstrate that, under 40 % torque, the shaped gear exhibited a maximum reduction in transmission error of 34.2 %, resulting in an overall error improvement of over 5.7 %. Moreover, the maximum error difference after tooth profile and tooth direction shaping exceeded 2 %. The gear-shaping-based electric vehicle transmission showcased favorable economic and technical performance, while its excitation response mechanism provided valuable guidance for mass production. Overall, these results highlight the significance of analyzing transmission errors through gear modifications in achieving lightweight electric vehicle motors. By addressing transmission vibration and noise issues, this research contributes to overcoming limitations and promoting advancements in power and speed within electric vehicle drive systems