Search Results (33)

As a key component in the hydraulic brake system of automobiles, the brake joint directly affects the braking performance and driving safety of the vehicle. Therefore, improving the quality of brake joints is crucial. During the processing, due to the complexity of the welding material and welding process, the weld seam is prone to various defects such as cracks, pores, undercutting, and incomplete fusion, which can weaken the joint and even lead to product failure. Traditional weld seam detection methods include destructive testing and non-destructive testing; however, destructive testing has high costs and long cycles, and non-destructive testing, such as radiographic testing and ultrasonic testing, also have problems such as high consumable costs, slow detection speed, or high requirements for operator experience. In response to these challenges, this article proposes a defect detection and classification method for laser welding seams of automotive brake joints based on machine vision inspection technology. Laser-welded automotive brake joints are subjected to weld defect detection and classification, and image processing algorithms are optimized to improve the accuracy of detection and failure analysis by utilizing the high efficiency, low cost, flexibility, and automation advantages of machine vision technology. This article first analyzes the common types of weld defects in laser welding of automotive brake joints, including craters, holes, and nibbling, and explores the causes and characteristics of these defects. Then, an image processing algorithm suitable for laser welding of automotive brake joints was studied, including pre-processing steps such as image smoothing, image enhancement, threshold segmentation, and morphological processing, to extract feature parameters of weld defects. On this basis, a welding seam defect detection and classification system based on the cascade classifier and AdaBoost algorithm was designed, and efficient recognition and classification of welding seam defects were achieved by training the cascade classifier. The results show that the system can accurately identify and distinguish pits, holes, and undercutting defects in welds, with an average classification accuracy of over 90%. The detection and recognition rate of pit defects reaches 100%, and the detection accuracy of undercutting defects is 92.6%. And the overall missed detection rate is less than 3%, with both the missed detection rate and false detection rate for pit defects being 0%. The average detection time for each image is 0.24 s, meeting the real-time requirements of industrial automation. Compared with infrared and ultrasonic detection methods, the proposed machine-vision-based detection system has significant advantages in detection speed, surface defect recognition accuracy, and industrial adaptability. This provides an efficient and accurate solution for laser welding defect detection of automotive brake joints. Full article

This study determined the hydro-chemical properties of groundwater in a typical mining area and its associated human health risks, focusing on the Guangwang mining area. Groundwater samples were analyzed for toxic metals, after which analysis of principal components, the entropy-weighted water quality index, and Spearman analysis of correlation were applied to the collected data. The Environmental Protection Agency of the United States’s health hazard appraisal was utilized to assess the hazards of toxic metals in the local water supply to the health of both grownups and juveniles. HCO₃-Na and SO₄⋅Cl-Ca⋅Mg were found to be the predominant groundwater hydro-chemical types. The eastern section of the area of study showed the greatest average total dissolved solids (16,347.00 mg/L) and SO₄²⁻ (8980.00 mg/L) levels. It was determined that the groundwater hydro-chemical type was Ca-HCO₃ and that limestone leeching and the evaporative level in the coal seam aquifer were the predominant factors regulating groundwater hydrochemistry. Six of the ten assessed metals exceeded the World Health Organization’s safe water for drinking standards, with particularly high Al (66.97 mg/L) and Cd (194.53 μg/L). Spearman correlation analysis showed significant correlations between Mn, Al, Cu, and Zn, which could be attributed to bauxite minerals associated with the coal mine. Release of metal ions was attributed to the oxidation of metal sulfide minerals, which is driven by mining-induced water–rock interaction. The intake of water for drinking was shown to be the predominant route of hazard to human health. The hazard index decreased from east to west due to the level of abandoned coal mines in the eastern region, along with well-developed fissures. The total carcinogenic hazard for grownups exceeded that of juveniles due to the greater quantity of water for drinking consumed and higher surface area of skin amongst grownups. The results can guide groundwater pollution regulation activities in mining areas to minimize potential hazards of groundwater quality to the health of humans. Full article

Welding is an important process in the production of aluminum reservoirs for motor vehicles. The welding quality affects product performance. However, rapid and accurate detection of weld surface defects remains a huge challenge in the field of industrial automation. To address this problem, we proposed a 3D vision-based aluminum reservoir welding surface defect detection method. First of all, a scanning system based on laser line scanning camera was constructed to acquire the point cloud data of weld seams on the aluminum reservoir surface. Next, a planar correction algorithm was used to adjust the slope of the contour line according to the slope of the contour line in order to minimize the effect of systematic disturbances when acquiring weld data. Then, the surface features of the weld, including curvature and normal vector direction, were extracted to extract holes, craters, and undercut defects. For better extraction of the defect, a double-aligned template matching method was used to ensure comprehensive extraction and measurement of defect areas. Finally, the detected defects were categorized according to their morphology. Experimental results show that the proposed method using 3D laser scanning data can detect and classify typical welding defects with an accuracy of more than 97.1%. Furthermore, different types of defects, including holes, undercuts, and craters, can also be accurately detected with precision 98.9%. Full article

In order to disintegrate nuclear fuel rods in the grid connection structure, a 10 kW fiber laser was used to cut a stainless steel simulation component with four layers of 3 mm thick plates and 12 mm gaps. The slit width is regarded as an important indicator to evaluate the cutting quality of the four-layer stainless steel plate. The results showed that good laser cutting quality can be successfully achieved under the proper process parameters. The widths of the cut seams of the four layers of grating after cutting were 1.25, 1.65, 1.80, and 1.92 mm. As the auxiliary gas pressure decreased layer by layer, the metal melting pool for the first two plates was mainly destroyed by the auxiliary gas. The cutting quality was good, and the slit area was mainly austenite with the presence of some ferrite. The third- and fourth-layer plates almost had no gas flow to assist blowing off, so the cut surface was an uneven melting pit, the cutting quality was poor, and the cut seam area ferrite content was higher than the upper plate cut seam area. At the same time, due to the lack of airflow cooling of the bottom plate, high laser energy, and long heating time, grain coarsening occurred, while grain deformation and a large number of dislocations existed. It can provide process support and technical guidance for the disintegration of nuclear fuel rods. Full article

Deep coalbed methane (CBM) resources are abundant in China, and in the last few years, the country’s search for and extraction of CBM have intensified, progressively moving from shallow to deep strata and from high-rank coal to medium- and low-rank coal. On the other hand, little is known about the gas content features of deep coal reservoirs in the eastern Junggar Basin, especially with regard to the gas content and the factors that affect it. Based on data from CBM drilling, logging, and seismic surveys, this study focuses on the gas content of Baijiahai Uplift’s primary Jurassic coal seams through experiments on the microscopic components of coal, industrial analysis, isothermal adsorption, low-temperature CO₂, low-temperature N₂, and high-pressure mercury injection. A systematic investigation of the controlling factors, including the depth, thickness, and quality of the coal seam and pore structure; tectonics; and lithology and thickness of the roof, was conducted. The results indicate that the Xishanyao Formation in the Baijiahai Uplift usually has a larger gas content than that in the Badaowan Formation, with the Xishanyao Formation showing that free gas and adsorbed gas coexist, while the Badaowan Formation primarily consists of adsorbed gas. The coal seams in the Baijiahai Uplift are generally deep and thick, and the coal samples from the Xishanyao and Badawan formations have a high vitrinite content, which contributes to their strong gas generation capacity. Additionally, low moisture and ash contents enhance the adsorption capacity of the coal seams, facilitating the storage of CBM. The pore-specific surface area of the coal samples is primarily provided by micropores, which is beneficial for CBM adsorption. Furthermore, a fault connecting the Carboniferous and Permian systems (C-P) developed in the northeastern part of the Baijiahai Uplift allows gas to migrate into the Xishanyao and Badaowan formations, resulting in a higher gas content in the coal seams. The roof lithology is predominantly mudstone with significant thickness, effectively reducing the dissipation of coalbed methane and promoting its accumulation. Full article

With the rapid development of the construction machinery industry, thick plate welds are increasingly needing efficient, accurate, and intelligent processing. This study proposes an intelligent grinding system using 3D line laser measurement and deep learning algorithms to solve the problems of inefficiency and inaccuracy existing in traditional weld grinding methods. This study makes use of 3D line laser measurement technology and deep learning algorithms in tandem, which perform automated 3D measurement and analysis to extract key parameters of the weld seam, in conjunction with deep learning algorithms applied on image data of the weld seam for the automatic classification, positioning, and segmentation of the weld seam. The entire work is divided into the following: image acquisition, motion control, and image processing. Based on various weld seam detection algorithms, the selected model was MNet-based DeepLab-V3. An intelligent trimming system for welding seams based on deep learning was constructed. Experiments were conducted to verify the feasibility and accuracy of the 3D line laser measurement technology for weld seam inspections, and that the deep learning algorithm can effectively identify the type and location of the weld seam, thus predicting the trimming strategy. With an accuracy far superior to conventionally based methods in accurate detection and regrinding of weld surface defects, the system proves advantageous for improved weld regrinding productivity and quality. It was determined that the system presents significant advantages in reinforcing weld regrinding when it comes to efficiency and quality, thus initiating a paradigm of using intelligent treatments for medium/thick plate welds in the construction machinery industry. Full article

Strip steel surface defect detection has become a crucial step in ensuring the quality of strip steel production. To address the issues of low detection accuracy and long detection times in strip steel surface defect detection algorithms caused by varying defect sizes and blurred images during acquisition, this paper proposes a lightweight strip steel surface defect detection network, YOLO-SDS, based on an improved YOLOv8. Firstly, StarNet is utilized to replace the backbone network of YOLOv8, achieving lightweight optimization while maintaining accuracy. Secondly, a lightweight module DWR is introduced into the neck and combined with the C2f feature extraction module to enhance the model’s multi-scale feature extraction capability. Finally, an occlusion-aware attention mechanism SEAM is incorporated into the detection head, enabling the model to better capture and process features of occluded objects, thus improving performance in complex scenarios. Experimental results on the open-source NEU-DET dataset show that the improved model reduces parameters by 34.4% compared with the original YOLOv8 algorithm while increasing average detection accuracy by 1.5%. And it shows good generalization performance on the deepPCB dataset. Compared with other defect detection models, YOLO-SDS offers significant advantages in terms of parameter count and detection speed. Additionally, ablation experiments validate the effectiveness of each module. Full article

The use of coal-derived activated carbon (AC) for water treatment applications demands more sustainable production methods, with chemical activation emerging as a promising alternative to thermal activation due to its higher AC quality, lower carbon burn-off, and higher yield. The study explored the effect of surface area, particle size and acid washing on the quality of AC derived from three seams of lower-rank Collie coal under the same activation conditions with potassium hydroxide (KOH). The quality of AC was determined by surface area and iodine number. The study demonstrates that Collie coal, suitable for AC production via KOH activation, yielded iodine numbers of 640 and 900 mg/g, with yields of 53 and 57 wt.%. Particle size influenced AC yield, with finer particle sizes yielding AC at 57–59 wt.%, whereas coarser ones yielded around 58–65 wt.%. SEM analysis shows the well-developed porous structure in Collie coal-derived activated carbons, with cleaner particles after acid washing. A positive correlation exists between coal surface area and AC iodine numbers, with higher values in coal samples correlating to increased iodine numbers in resulting AC. The regression model’s predicted values yield a coefficient of determination (R²) of 0.99. Full article

With the application of modern coal mining technology and the fact that there are fewer and fewer high-quality coal seams, the quality enhancement and utilization of low-rank coal are gaining more and more attention. To solve the problems of high consumption of chemicals and low recovery of refined coal in the flotation separation process of low-rank coal, the long-flame coal from the Inner Mongolia Autonomous Region of China was selected as the research object, and the factors affecting the flotation process were analyzed and optimized by adopting the response surface method and establishing a regression model with high precision and reliability. The test results showed that the primary and secondary relationships of the factors on the fine coal yield were as follows: slurry concentration > frother dosage > collector dosage; and the primary and secondary relationships of the factors on the flotation refinement index were as follows: slurry concentration > collector dosage > frother dosage. The optimal conditions for flotation were 2453.09 g/t of collector, 795.84 g/t of frother, and 50.04 g/L of slurry concentration. Under these conditions, the fine coal yield was 51.51%, and the relative error of 53.71% was 4.27%. The flotation refinement index was 21.34%, and the relative error with the predicted value of 21.58% was 1.12%. The relative error of the experimental results was within a reasonable range, which indicated that the regression model obtained by the response surface method was highly reliable. The research results are of great significance to strengthen the comprehensive utilization of long-flame coal in full particle size and improve the economic benefits of coal enterprises. Full article

This study advances the vibration-assisted welding (VAW) technique for joining medium-carbon, low-alloy steels, which are typically challenging to weld. Traditional welding methods suggest low linear energy and mandatory pre- and post-heating due to these steels’ poor weldability. However, VAW employs a vibrating table to maintain part vibration throughout the automatic MIG/MAG welding process. This study tested the VAW technique on 42CrMo4 steel samples, achieving satisfactory weld quality without the need for pre- and post-heating treatments. This research revealed that while vibration frequencies between 550 Hz and 9.5 kHz minimally affect the appearance of the weld joint, the oscillation acceleration has a significant impact. The acceleration along the weld axis (a_x), combined with the welding speed and vibration frequency, affects the weld surface’s appearance, particularly its scaly texture and size. Lateral acceleration (a_y) alters the seam width, whereas vertical acceleration (a_z) affects penetration depth at the root. Notably, if the effective acceleration (a_ef) surpasses 40 m/s², there is a risk of molten metal expulsion from the weld pool or piercing at the joint’s base. The quality of the joints was assessed through macroscopic and microscopic structural analyses, micro-hardness tests in the weld zone, and bending trials. The mechanical properties of the VAW samples were found to be acceptable, with hardness slightly exceeding that of the samples subjected to pre- and post-heating. Moreover, the VAW process significantly reduced energy consumption and operational time. The employed vibration system, with a power rating of 100 W, operates for just a few minutes, resulting in substantially lower energy usage compared to the traditional pre- and post-heating method, which typically requires a 5 kW electric furnace. Full article

The escalation of mining activities in the karst regions of Guizhou Province has heightened the occurrence of water-inrush incidents in deep coal mines. This study focused on water-inrush phenomena within the Xinhua mining area of Jinsha County, Guizhou Province, aiming to investigate the sources of these incidents. The findings indicated that the overlying limestone of the Changxing Formation in the coal seam served as a vulnerable aquifer under certain conditions, leading to water inrushes. The analysis of the spatiotemporal distribution patterns of water-inrush incidents at the working face indicated that previous mining operations damaged the shallow Changxing Formation limestone, resulting in the accumulation of goaf water and the formation of numerous mining-induced fractures. These fractures served as rapid conduits for water inrushes from both atmospheric precipitation and underground sources at the deep working face. The examination of surface water and mine water quality demonstrated that both exhibited similar characteristics, predominantly featuring bicarbonate, sulfate, and sodium compositions. Investigation into the relationship between mine water inflow and atmospheric precipitation established that atmospheric precipitation influenced the mine water supply cycle, with a replenishment period of ~10 months during the operational phase of the Jinyuan Coal Mine and about one month post-closure. The fractures induced by mining activities within the Changxing Formation limestone facilitated water flow, with atmospheric precipitation serving as the primary water source for the mine. This study offered a valuable scientific foundation for addressing water-related damage resulting from atmospheric precipitation in mines susceptible to water inrushes under analogous hydrogeological conditions. Full article

In existing highlight removal methods, research on highlights on metal surfaces is relatively limited. Therefore, this paper proposes a new, simple, effective method for removing highlights from metal surfaces, which can better restore image details. Additionally, the approach presented in this paper is highly effective for highlight removal in everyday real-world highlight scenarios. Specifically, we first separate the image’s illumination space based on the Retinex model and generate a highlight mask using the mean plus standard deviation method. Then, based on the mask, we transform the original image and the image at the corresponding mask position to the V channel of the HSV space, achieving the effective elimination of highlights. To enhance the details of the restored image, this paper introduces a method involving adaptive Laplacian sharpening operators and gradient fusion for detail enhancement at highlight removal positions. Finally, a highlight-free image with well-preserved details is obtained. In the experimental phase, we validate the proposed method using real welding seam highlight datasets and real-world highlight datasets. Compared with the existing methods, the proposed method achieves high-quality qualitative and quantitative evaluation. Full article

Hot-dip galvanized components offer a great potential for corrosion protection of up to 100 years, while laser beam welding in vacuum (LaVa) has the advantage of high penetration depths Combined, this process chain can be economically used in steel construction of bridges, wind turbines, or other steel constructions. Therefore, investigations of butt joint welding of galvanized 20 mm thick S355M steel plates using LaVa were carried out. The butt joints were prepared under different cutting edges such as flame-cut, sawn, and milled edges, and they were studied with and without the zinc layer in the joint gap. For this purpose, the laser parameters such as the beam power, welding speed, focus position, and working pressure all varied, as did the oscillation parameters. The welds performed using an infinity oscillation with an amplitude of 5 mm represented a pore-free weld up to a zinc layer thickness of 400 µm in the joint gap. The seam undercut increased with increasing the zinc layer thickness in the joint gap, which can be explained by the evaporating zinc and consequently the missing material, since no filler material was used. The joint welds with zinc only on the sheet surface achieved a sufficient weld quality without pores. Full article

Fusion welding causes joint deterioration when joining aluminum alloys, which limits the use of aluminum alloy components in high-end equipment. This paper focuses on an overview of how to achieve high-strength aluminum alloy welded joints using welding/plastic deformation composite forming technology. The current technology is summarized into two categories: plastic deformation welding and plastic deformation strengthening. Plastic deformation welding includes friction stir welding, friction welding, diffusion welding, superplastic solid-state welding, explosive welding, and electromagnetic pulse welding. Plastic deformation strengthening refers to the application of plastic deformation to the weld seam or heat-affected zone, or even the whole joint, after welding or during welding, including physical surface modification and large-scale plastic deformation technology. Important processing parameters of plastic deformation welding and their effects on weld quality are discussed, and the microstructure is described. The effect of plastic deformation strengthening technology on the microstructure and performance evolution, including the hardness, tensile strength, fatigue property, residual stress, and hot cracking of aluminum alloy welded joints, and its evolution mechanism are systematically analyzed. Finally, this paper discusses the future development of plastic deformation strengthening technology and anticipates growing interest in this research area. Full article

Smooth surface blasting control technology is aimed at blasting the rock body until it is left with a smooth surface and to protect it from damage; the current air spaced axial uncoupled charge and air spaced radial uncoupled continuous charge are effective charging structures for smooth surface blasting. Reserved air spacing can effectively reduce the blast wave and the peak pressure of the explosive gas, improving the quasi-static pressure of the explosive gas under the action of rock surface blasting with fracture seam quality. In order to ensure the effect of surface blasting, small-diameter light surface holes are more often used; with the development of drilling machinery, the use of large-diameter light blast holes with an oversized uncoupled coefficient of loading structure effectively improves the efficiency of the construction and at the same time achieves better blasting results. However, according to the bursting assumption of obtaining the theory of light surface blasting in the application of large uncoupling coefficient loading, light surface blasting has certain limitations. In this regard, the bursting theory explores the air spacing uncoupling charge in line with the multi-faceted exponential expansion of the critical uncoupling coefficient and is in accordance with the following: the requirements of light surface blasting and the field loading structure; the derivation of the quasi-static pressure on the wall of the gunhole under the action of large uncoupling, uncoupling coefficient, and the parameters of the spacing between the gunholes; the establishment of the axial uncoupling coefficient and the radial uncoupling coefficient-equivalent relationship between the uncoupling coefficient and the theoretical relationship between the selection of the spacing between the holes; the uncoupling coefficient and the selection of the theoretical relationship between the spacing between the holes. This study reveals the mechanism by which different parameters of surface blasting can achieve good results in engineering practices. A slope in Guizhou is an example of sample calculations and the application of two different charging structures applied to field loading, which have achieved good surface blasting results. Full article