Abstract: Roof caving has been the main threat to the safety of underground mining, in which the caving of roof rock blocks is particularly concerning. The secondary structural planes of surrounding rocks around underground excavations, such as roadways and stopes, are developed. The rock mass is prone to break into several independent blocks, and these rock blocks may slide and fall under the action of static in-situ stress or external dynamic disturbances. Under quasistatic stress conditions, the instability and collapse of roof rock blocks are mainly caused by structural plane extensions and changes in the stress balance condition of the rock block system. However, under external dynamic disturbances, the sliding process and instability of roof rock blocks are associated with the development of fractures triggered by stress waves. Further, they are affected by the variation of stress balance conditions of the rock block system and the transmission of stress waves in the block system. This paper summarized the existing studies on roof rock block stability under quasistatic and dynamic disturbance conditions. Previous studies have proposed relatively mature theoretical systems for the stability analysis of roof rock blocks under static or quasistatic situations. However, a majority of the studies on rock block stability under an external dynamic disturbance condition examine stress wave propagation in a rock block system while overlooking the analysis of the crack development mechanism and dynamic variation in stress balance conditions. Therefore, further research is necessary to reveal the caving mechanism of roof rock blocks triggered by a dynamic disturbance. By summarizing relevant work, the difficulties encountered in the study of roof rock block caving under a dynamic disturbance are discussed. The key scientific problem is to uncover the fundamental mechanism behind roof rock block instability induced by a dynamic disturbance. Finally, a series of experimental and numerical simulations conducted on the sliding and instability of roof rock blocks under a dynamic disturbance revealed clear differences in the mechanism of the sliding instability of roof blocks due to dynamic disturbances in different directions. The reduction in friction between the blocks is the fundamental cause of the key block sliding under a lateral disturbance, while the sliding of the rock blocks under a vertical disturbance is mainly driven by the dynamic load. This finding can provide a theoretical reference for preventing and controlling roof caving in underground mines.
Abstract: With the in-depth deployment of China’s “Belt and Road Initiative” and other major strategies, major national strategic projects, such as the Sichuan–Tibet Railway, will be built in mountain valleys with complex terrain. Under the influence of continuous external factors (rainfall, earthquake, construction, etc.), rock masses of a high-steep rock slope in a stable state gradually transform to unstable rock, and then the unstable rock slides and destroys, which is a major hidden danger threatening the safety of project construction and operation. Unfortunately, the stability factor (SF) can only identify the occurrence of failure and cannot identify the transition of stable to unstable rock; thus, it cannot quantitatively identify unstable sliding rocks. Rock mass failures mostly evolve from unstable rocks. Therefore, how to establish a quantitative evaluation method to identify unstable sliding rock masses is a major problem in the field of early warning and prevention of rock collapse. In this study, the potential sliding surface cohesion and its slip resistance share are analyzed by introducing a cohesive stability factor (CSF) to achieve dynamic consideration of the stability, separation, and damage phases of slip-type rock masses. When the CSF is <1 and the ratio of cohesion to skid resistance (η) drops below the ratio of long-term strength to failure strength, the sliding rock masses become unstable. Among them, the CSF is the main control indicator, and η is the auxiliary indicator. The laboratory experimental results of sliding unstable rock mass show that a single SF cannot accurately identify the A8 unstable rock mass in the experimental group quantitatively because of the inconsistency of the standard, and a quantitative identification method of unstable rock masses based on the CSF and SF can scientifically realize the quantitative evaluation of unstable rock masses in terms of mechanics. The field case study shows that the improved method provides relatively objective judgment criteria for the quantitative identification of unstable sliding rock masses with an SF of ~1.2 in the Chongqing Three Gorges and other regions. Compared with the traditional mechanical identification methods of unstable rock masses, the new identification method proposed in this study can conduct a set of objective and unified identification criteria, which improves the accuracy and scientificalness of the traditional mechanical identification methods and provides an effective reference for better management of rockslides in high-risk areas.
Abstract: Iron ore pellets have several substantial advantages, such as high iron grade, low harmful elements, low smelting slag, and low pollution in the production process. Rapidly developing the pelleting process and improving the quality of pellet ores is crucial for achieving the goals of carbon peaking and carbon neutrality in the steel industry. Bentonite, a major binder in the pellet ore production process, can significantly improve the sphericity of raw materials and enhance the pellet quality; however, the higher SiO2 and Al2O3 content will cause an increase in the slag volume of ironmaking production. An organic binder has the advantages of low dosage and less harmful impurities, which can improve the pellet ore grade and the expansion rate of pellets. Thus, adding a small amount of organic binder to replace part of the bentonite is essential to improving the pellet performance. This study investigates the effect of organic binder P replacing part of bentonite on the high-temperature strength of pellets. The laser flash and thermogravimetric methods were employed to investigate the effects of organic binder on the internal structure, heat transfer, and mass transfer of pellets. The results indicated that bentonite was beneficial in reducing the porosity and high-temperature consolidation of pellets because it could promote the generation of a low-melting-point liquid phase. With increasing bentonite addition, the strength of preheated and roasted pellets increased, and the porosity decreased from 21.82% to 15.68% when bentonite addition increased from 1.1% to 2.0%. Thus, the composite binder could replace a part of the bentonite and significantly improve the strength of preheated and roasted pellets with increasing addition. Moreover, the organic binder P was pyrolyzed at a high temperature and formed pores inside the pellet, resulting in a lower thermal conductivity and a slower internal heating gradient. The thermal diffusivity reduced from 0.321 to 0.266 mm2·s?1, and the heat transfer coefficient decreased gradually from 0.551 to 0.454 J·g?1·K?1. Thus, the formation of a dense oxide layer on the surface of the pellets owing to rapid oxidation was avoided, and the oxidation of hematite inside the pellets was promoted, thus enhancing the pellet strength. Moreover, the tiny pores facilitated oxygen transfer to the interior of the pellets and promoted the oxidation of Fe3O4 to Fe2O3. The oxidation fraction $ f $TGA gradually increased from 90.80% to 92.17% with the addition of organic binder P.
Abstract: High-entropy alloy has become a research hotspot because of its unique microstructure and mechanical properties. The appearance of high-entropy alloy breaks the design concept of traditional alloy with one or two elements as the main element and other elements as the auxiliary element, providing a broader space for the development of new materials. Conventional alloys are generally optimized by four different strengthening methods, as are high-entropy alloys consisting of five or more elements. Appropriately doped interstitial atoms with small atomic sizes (such as C, B, O, and N) can dissolve into crystal interstice, combine with alloying elements to form a fine microstructure and dispersion-strengthened phase, and improve the properties of high-entropy alloy by reducing the layer fault energy and changing the dislocation motion mode. Therefore, exploring the effect of interstitial atom doping on the properties of high-entropy alloys is conducive to promoting the application of high-entropy alloys in different material fields. The effects of the interstitial atoms C, N, O, and B on the microstructures and properties of high-entropy alloys are analyzed. The contents of four kinds of interstitial atoms and their effects on the microstructures and properties of high-entropy alloys are summarized. Numerous studies have shown that doping interstitial atoms can not only regulate the structural composition of the phase (i.e., promote/inhibit the phase transformation and precipitate the second phase particles) in high-entropy alloy systems. The deformation mechanism, i.e., TWIP (Twinning induced plasticity) and TRIP（Transformation induced plasticity) effects, can also be changed to strengthen and toughen the material. Its effective utilization can not only broaden the design idea of high-entropy alloy but also effectively reduce the preparation cost of aviation materials. Finally, a new direction in microstructure design of high-strength, high-toughness, and high-entropy alloys containing interstitial atoms is proposed to (1) understand the doping mechanism of different types of high-entropy alloys and establish a solution-strengthening model more suitable for high-entropy alloy systems and (2) determine the appropriate interstitial atoms and doping amount to adjust the microstructures and mechanical properties of high-entropy alloys. The study and design of high-entropy alloys doped with different interstitial atoms are expected to reveal the effects of different interstitial atoms on the phase structure, deformation mechanism, and mechanical properties, which have important scientific and engineering practical significance.
Abstract: In recent years, with the gradual expansion of the global market for new energy vehicles, the supply and demand of lithium-ion batteries (LIBs) as a source of energy have been increasing, which directly promotes the significant increase in the number of used LIBs. Among them, ternary LIBs have been widely used because of their high specific capacity and excellent multiplying performance, which has aroused people’s concerns about their proper disposal. On the one hand, ternary LIBs contain rich nonferrous metals, such as lithium, nickel, cobalt, and manganese, with high recovery values. On the other hand, spent ternary LIBs contain a large number of toxic electrolytes and heavy metals, which will cause environmental pollution and damage human health if not handled properly. Therefore, research on the recycling and regeneration of spent ternary LIBs has been receiving considerable attention. Given the principles of low energy consumption, “green” recovery, and high recovery rate, this study briefly introduces the main failure causes of cathode materials for ternary LIBs and discusses the application scope and the advantages and disadvantages of traditional pyrometallurgy (such as chemical reduction and salinization roasting) and hydrometallurgical leaching processes (such as acid, alkali, and biological leaching). This review creatively summarizes the research progress on regeneration after hydrometallurgical leaching (such as coprecipitation and sol–gel methods) and direct regeneration (such as high-temperature solid-phase method, solvothermal treatment, and molten salt method) of spent ternary LIBs in recent years and analyzes the advantages and disadvantages of various regeneration technologies. Notably, compared with traditional pyrometallurgy and hydrometallurgy, the process of regeneration after hydrometallurgical leaching and direct regeneration considerably reduces the complexity of the process flow, maximizes the comprehensive utilization rate of nonferrous metals, and realizes the closed-loop recovery route of spent LIB cathode. Based on this, the innovative strategy of upgrading the cathode material of regenerated ternary LIBs through ion doping and surface coating modification, which effectively improved the poor thermal stability, short cycling, and low rate performance of ternary LIBs caused by high nickel content, was particularly discussed. Finally, from the perspective of recycling methods, multiple modification strategies, and mechanism research, the future development of recycling technology for spent ternary LIBs is proposed. This study aims to provide some references and suggestions for the improvement of the spent LIB recycling system and establish a closed-cycle recycling system for the production and recycling of spent LIBs.
Abstract: New energy vehicles can effectively alleviate the severe dependence of the conventional automobile industry on fossil fuels and the environmental problems worldwide. They are an inevitable requirement in the future development of vehicles. As the power core of new energy vehicles, the driving motors should demonstrate excellent magnetic properties to improve energy conversion efficiency and high strength to resist centrifugal forces during high-speed operation. However, the mechanical and magnetic properties of non-oriented silicon steels remain challenging to balance. Therefore, their coordinated control is a key scientific issue in developing driving motors used in new energy vehicles. This study reviews the regulation of the mechanical and magnetic properties of high-strength non-oriented silicon steels. Additionally, the influence of various strengthening methods on the magnetic properties of non-oriented silicon steels is analyzed. Furthermore, this review highlights the future development of coordinated control of the mechanical and magnetic properties of high-strength non-oriented silicon steels. In non-oriented silicon steels, the dislocation density is relatively low, and the grain size is rather large. Thus, the contribution of dislocation and fine-grain strengthening to the yield strength is minimal. Therefore, by combining fine-grain, dislocation, and solid solution strengthening, the best match in the mechanical and magnetic properties of high-strength nonoriented silicon steels can be obtained. Although the precipitation strengthening effect of alloying elements, such as Nb, Ti, V, and Zr, in nonoriented silicon steels is evident, the carbonitrides formed are coarse-sized and irregularly shaped, which considerably deteriorates the magnetic properties of nonoriented silicon steels. During the early stage of aging treatment, the dispersed Cu precipitates with a BCC structure and fairly small grain size, exhibiting a good strengthening effect. Moreover, these Cu precipitates are coherent with the matrix and exhibit little hindering force on the movement of magnetic domains such that they do not deteriorate the magnetic properties of nonoriented silicon steels. Therefore, employing various strengthening methods or finely dispersed nano-coherent precipitates, nonoriented silicon steels with high strength and excellent magnetic properties can be developed for application in driving motors of new energy vehicles, which is an essential requirement for the high-quality development of the new energy vehicle industry.
Abstract: Developing electrode materials for high-performance secondary batteries is one of the most effective approaches to alleviate energy and environmental crises. Nowadays, graphite anodes, which are widely used in commercial lithium-ion batteries, cannot satisfy the ever-growing energy needs of humans owing to their relatively low theoretical capacities and nearly no capacity in sodium-ion batteries. Therefore, developing new anodes with high capacity and energy density is necessary for next-generation large-scale energy systems. Red phosphorus has become an interesting topic in alkali-ion battery research and is expected to be commercially used as anode material in the next generation of secondary batteries owing to their intrinsic properties, such as their high activity, high theoretical specific capacity (2596 mA?h?g?1), suitable oxidation–reduction potential, highly abundant earth resources, and low cost of lithium/sodium-ion batteries. However, red phosphorus exhibits poor electrical conductivity and large volume expansion when used as electrode material, resulting in low utilization of active material, serious electrode pulverization, and poor electrode cycling stability, which seriously hindered their commercial application in next-generation rechargeable batteries. Recent studies have shown that the cycle stability and electronic conductivity of red phosphorus can be improved by rational structural design, which promotes the electrochemical performance of red phosphorus anodes. For example, reducing the material size to the nanoscale can effectively shorten the diffusion path, enhancing the ion diffusion rate while alleviating the volume expansion and pulverization of the active substance. Additionally, the size reduction changes the band energy of the red phosphorus, which can transform indirect into direct bandgap semiconductors. Besides, the external characteristics of the active materials affect the performance by reducing the internal stress generated by the phase transformation in charging and discharging cycles. By modifying the morphology and structure of red phosphorus to form porous, layer, hollow, or composite structures, the cyclability and chargeability of batteries could be optimized because the internal stress generated by the volume change of the active material can be effectively released, and the generation probability of cracks or fractures in the electrode is drastically reduced. Therefore, these strategies help alleviate electrode pulverization and promote the commercial application of red phosphorus in lithium/sodium-ion batteries. Herein, we review the recent research progress in controllable synthesis, structural design, and performance optimization mechanisms of red phosphorus-based nanocomposites. Finally, we summarize the challenges in current research on red phosphorus anode materials, propose potential solutions, and provide an outlook on the future development of red phosphorus-based anode materials in the energy storage system.
Abstract: Titanium alloys are extensively used in areas such as aerospace and biomedicine. However, inadequate mechanical qualities (e.g., low hardness and poor wear resistance) and poor machinability limit the scope of their application expansion. To directly manufacture near-net-shape titanium alloy components with complicated architectures and improved performances, titanium matrix composites (TMCs) were fabricated based on the Ti–N reaction by introducing nitrogen gas (N2) in the process of selective laser melting (SLM) of Ti6Al4V. The formation principle of this novel method is as follows: Laser-induced N2 decomposition near the melt pool of Ti6Al4V generates N atoms or ions, which react with Ti atoms in the melt pool to in-situ synthesize TiN-reinforcement particles. In turn, TiN-reinforced Ti6Al4V matrix composites are manufactured layer-by-layer. This approach has some important advantages, which are as follows: Above all, in-situ gas-liquid synthesized reinforcements are equally dispersed due to N2, good diffusivity and dispersibility. Furthermore, extremely small gas molecules have the potential to produce nanoscaled reinforcement. Moreover, the in-situ reaction mode produces a clean interface and strong interfacial bonding between the matrix and reinforcement. In this study, TMCs were prepared by SLM in three different N2 volume fractions of 3%, 10% and 30%, which were compared to the Ti6Al4V alloy fabricated in an argon atmosphere. The microstructures were observed by SEM. Interstitial solid solutions of N in the Ti lattices were confirmed by XRD patterns. The presence of TiN was verified by EDS. The high-resolution transmission electron microscope (HR-TEM) picture indicated that the matrix and reinforcement were TiN and Ti, respectively. Such in situ synthesized nitride reinforcements were uniformly distributed; in particular, numerous nanoscale reinforcements were uniformly dispersed in the composites manufactured in low volume fraction N2 atmospheres (3% and 10%). Additionally, the improved strength and plasticity were simultaneously achieved in a diluted N2 atmosphere (10%). The effect of varying N2 concentrations on the microstructure and mechanical characteristics of the TMCs was investigated. The content of the TiN particles increased with increasing N2 concentration due to the increased availability of N atoms and ions for nucleation and growth of the reinforcement. Nevertheless, the TMC produced in a high N2 atmosphere (30%) demonstrated degradation of the mechanical properties (particularly plasticity and ultimate strength) because of the presence of excessive N solid solutions and brittle TiN particles. The strengthening mechanisms were primarily grain refinement strengthening of the Ti matrix due to the "pinning" effect of TiN particles, the precipitation hardening and dispersion strengthening effects of uniformly distributed reinforcement particles, interstitial solid solution strengthening caused by the results from the portion of N in the Ti lattices, Orowan strengthening caused by the in-situ synthesis of nanoscaled reinforcements, and the load transfer effect from Ti matrix to TiN reinforcements because of the clean interface.
Abstract: Metallic glasses have received a lot of interest because of their excellent mechanical, physical, and chemical qualities. For example, they have a stronger resistivity than crystalline metals composed of the same elements and a lower viscosity coefficient. However, the difficulty in creating alloy compositions has been a concern for researchers. Traditional amorphous alloy systems design approaches, such as empirical trial-and-error methods and methods based on density functional theory (DFT), have assisted researchers in exploring numerous amorphous alloy systems during the growth of materials science over the last few decades. However, with the continuous development of materials science, these methods have been difficult to meet the needs of researchers due to their long development cycles and low efficiency. Additionally, the complex and long-range disordered structure of metallic glasses makes it difficult to understand their structure and nature in a comprehensive and clear way by conventional methods. Amorphous alloy composition design and property analysis are now often conducted using machine learning techniques because of their low experimental cost, short development cycle, strong data processing capability, and high predictive performance, among other advantages. They present new approaches and chances to address significant key bottlenecks in the field of metallic glass. In this study, the main processes of machine learning model building were introduced. Subsequently, the related studies on data pre-processing, model construction, and model validation were presented. For data pre-processing, data selection, feature engineering, and advanced data balancing methods were primarily described. In the feature engineering part, the model performance with various input features was examined, and it was shown that either employing physical properties or directly using the alloy compositions as the model input might result in high performance. Four machine learning algorithms were used to generate the machine learning model: artificial neural networks (ANN), support vector machines (SVM), random forest (RF), and extreme gradient boosting (XGBoost). A comparison indicates that SVM models work best with small data sets, whereas the performance of all other models tends to get better as the amount of training data increases. Generally, the XGBoost method outperforms several other methods and is, therefore, often used in machine learning competitions. Model validation approaches: K-fold cross-validation and leave-one-out cross-validation methods were presented. A good metallic glass performance prediction method needs to perform well in both validation methods. Finally, this study provides several possible future research directions on feature engineering, dataset construction, validation, and machine learning models.
Abstract: The brain–machine interface has been an integral component of the metaverse since the inception of the latter, in his classic science fiction novel “True Names,” Vernor Vinge, the American mathematician and computer science Professor, describes a virtual world that can be accessed and experienced via a brain–machine interface. Following the introduction of this idea, the science fiction novel “Avalanche” formally proposed the concept of a metaverse, where a virtual world constructed by humans using digital technology can be mapped onto and interact with the real world. Large companies such as Meta, Apple, Sony, Microsoft, and Samsung have launched new metaverse-related hardware and software products. Domestic giants such as Tencent, Alibaba, and Baidu have also integrated themselves into the metaverse, confirming its future development and commercial value. Goldman Sachs estimates that trillions of dollars will be invested in the development of the metaverse over the next few years. As the focus of metaverse research shifts toward content exchange and social interaction, the issue of addressing the current bottlenecks in audiovisual media interaction has become an urgent matter, and the brain–computer interface is one of its solutions. Brain–computer interfaces are becoming increasingly complex. As a physiological signal acquisition tool, it has demonstrated indispensable application potential in numerous fields of the metaverse. A non-invasive brain–computer interface possesses the advantages of being easy to obtain and having good performance and accuracy. It is the preferred method for detecting brain signals in brain–computer interfaces. The Electroencephalogram is a unique physiological signal conducive to reflecting people's psychological state. By reading and categorizing the relevant papers in the paper database, including Web of Science, CNKI, IEL, and ACM Digital Library; investigating the products and functional parameters of Neuralink, Synchron, OpenBCI, and Emotiv; studying three application scenarios, namely, the generative art in the metaverse art, the serious game of medicine and healthcare in the medical metaverse, and the application status of the brain–machine interface in virtual human expression synthesis in the social metaverse; and by investigating the existing commercial products and patents (MindWave Mobile, GVS, Galea), this paper discusses the challenges and potential problems that brain–computer interfaces may face with their widespread use by drawing parallels with the development process of network and neural security and bioethics. Furthermore, the possibility of in-depth and diverse applications of brain–computer interfaces in the future is explored, for instance, the use of sensory simulation technology to simulate olfactory sensation, gustatory sense, and tactile sensation, and the use of motor imagery to assist disabled people in participating in the metaverse.
Abstract: With the development and advancement of science and technology, the development and innovation of unmanned aerial vehicle (UAV) technology and products have brought great convenience to people in the fields of aerial photography, plant protection, electric cruise, and so on, but the development of UAVs also brings a series of management problems. Therefore, as a key part of the anti-UAV system, research into effective UAV detection is a pressing issue that must be addressed. In public environments such as parks, stadiums, and schools, the detection and tracking of UAV targets become more difficult due to their inherent characteristics and environmental factors. For example, under the occlusion of background interferences such as trees, buildings, and light, the target detection algorithm is unable to extract the effective features of the UAV target, resulting in target detection failure. It is of great significance to study the anti-occlusion target detection and tracking algorithm of anti-UAV systems for situations where UAVs cannot be successfully detected due to occlusion. This study proposes an improved anti-UAV system target detection algorithm YOLOX-drone based on YOLOX-S to solve the problem of the UAV being deformed and partially occluded in complex scenes, which makes it difficult to identify. First, in this study, numerous occluded drone images are collected in complex scenes, and the drone pictures are downloaded online for occlusion processing. The drone images were labeled to establish a UAV image dataset. Second, the YOLOX-S target detection network was constructed. On this premise, the coordinate attention mechanism is introduced to improve the saliency of the target image when the drone is obscured by highlighting useful features and suppressing useless ones. Then, the bottom-up path enhancement structure in the feature fusion layer is removed to reduce the network complexity, and an adaptive feature fusion network structure is designed to improve the expression ability of useful features, suppress interference, and improve detection accuracy. First, experiments were conducted on the Dalian University of Technology Anti-UAV dataset, and the experimental results show that YOLOX-drone improved average accuracy (IOU = 0.5) by 3.2%, 4.7%, and 10.1% compared to YOLOX-S, YOLOv5-S, and YOLOX-tiny, respectively. Then, experiments were conducted on the self-built UAV image dataset, and YOLOX-drone improved the average accuracy (IOU = 0.5) by 2.4%, 2.1%, and 6.4% in the cases of no occlusion, general occlusion, and severe occlusion, respectively, when compared with the original YOLOX-S target detection model. This demonstrates that the improved algorithm has good anti-occlusion detection ability.
Abstract: A differential robot is a typical mobile robot widely used in storage, agriculture, and other industries. The motion control of differential robots, including longitudinal and lateral control, is a current research hotspot. To date, researchers have not paid much attention to the interaction between longitudinal and lateral control of differential robots. However, the conflict between the ability to track the reference path and maintain the longitudinal speed at its maximum value is a critical issue that limits the operational efficiency of the differential robot. To solve this problem, a mapping relationship between the longitudinal speed and the turning curvature is analyzed. The mapping relationship is established when the maximum value of the longitudinal speed is known, i.e., the feasible upper limit of the longitudinal speed that can guarantee the steering ability of the differential robot is inversely proportional to the curvature of the trajectory. From this mapping relationship, a speed-adjusting method is proposed based on the preview information. This speed-adjusting method consists of two steps. First, the smaller value between the upper limit of the feasible longitudinal speed in a certain preview distance and the set value of the longitudinal speed are taken as the desired longitudinal speed. Second, a control law is established based on the deviation between this desired and current longitudinal speed. Additionally, a path-tracking method that cooperates with the above-mentioned speed-adjusting method is proposed. The theoretical basis of this path-tracking method is a nonlinear model predictive control. The prediction model used in this control method is derived from a kinematic model with longitudinal speed as a time-dependent parameter. Finally, a differential robot motion control system is formed based on speed adjusting and path tracking. The simulation and experimental results show that the proposed motion control system can actively adjust the longitudinal speed when the set value of the longitudinal speed of the differential robot is high and ensure high accuracy of path tracking control. Furthermore, the absolute value of the displacement and heading errors does not exceed 0.0499 m and 0.0726 rad, which are reduced by 97.57% and 45.04% compared with the motion control system without speed adjusting, respectively.
Abstract: Recently, planetary gearboxes have been widely used in helicopters, heavy trucks, ships, and other large and complex mechanical equipment because of their smooth transmission characteristics, small volume, and large reduction ratio. The planetary bearing, which plays a supporting role in the planetary gearbox, usually works in a worse environment but suffers from low speed and heavy load for a long time. Additionally, because of the strong noise generated by the interaction between gears during the operation of the planetary gearbox, the fault characteristics of planetary bearings are completely submerged in the background noise and are difficult to extract, which complicates classifying planetary-bearing faults accurately. Therefore, to effectively remove noise information from planetary-bearing signals, accurately extract fault information, and classify the fault types of planetary bearings, an adaptive dynamic mode decomposition (ADMD) and genetic algorithm and support vector machine (GA-SVM) with application to the fault classification of planetary bearing is proposed in this paper. The hard threshold selection of the traditional truncated rank cannot effectively process the time-domain vibration signals using the dynamic mode decomposition (DMD) method. Hence, this paper proposes improved grasshopper optimization algorithm (IGOA) to optimize the grasshopper optimization algorithm (GOA) by using dynamic weight and avoid the linear gradient mechanism, which cannot fully use the entire iterative process. Furthermore, IGOA can perform a global search to achieve the adaptive optimal parameter selection of the truncated rank. Besides, a new fitness function is defined that can effectively process the original time-domain signals. The traditional refined composite multiscale discrete entropy (RCMDE) is relatively dispersed, and it cannot characterize the features hidden in the signal better. Therefore, we normalize the RCMDE, forming the improved refined composite multiscale discrete entropy (IRCMDE). Then, the IRCMDE is calculated for the denoised signal, and a feature matrix is constructed to better mine the hidden features in the signal. Finally, GA is used to optimize the key parameters C and g of the SVM. The GA-SVM classification model is also constructed and applied to the bearing fault classification of the planetary gearbox, which can avoid the overfitting phenomenon in the training process and provide better generalization performance. Taking the planetary-bearing fault data in the planetary gearbox of Nanchang Hangkong University as the research object, the validity and practicability of the proposed method are verified, and the final classification result of the inner ring fault, outer ring fault, rolling body fault, and normal condition is 96.43%. In addition, this method can more accurately identify the fault types of planetary bearings and has better generalization ability than the empirical mode decomposition (EMD) signal processing method and the convolutional neural network (CNN) classification method.
Abstract: In this study, an embedded cement-based piezoelectric sensor based on a spherical piezoelectric ceramic shell was designed, fabricated, and characterized. Compared with the conventional piezoelectric acoustic emission sensor (PAES), which is based on sheet piezoelectric ceramics and can receive signals only in a specific direction, the novel embedded cement-based spherical piezoelectric sensor (CSPS) has the potential for omnidirectional signal reception. The frequency response range of the embedded CSPS, tested using the pencil-lead break test, is 70–600 kHz, which can meet the requirements of acoustic emission testing of concrete structures. Thus, the four-point bending test of the concrete beam was monitored using the acoustic emission technique. The concrete beams with two failure modes, bending and compression–shear failure, were created. During the four-point bending test, the CSPS embedded into the concrete beams and the commercial PAES externally placed on the surface of the concrete structure were used for acoustic emission monitoring. Data such as acoustic emission amplitude, b-value, and fractal dimension were measured using the embedded CSPS and analyzed and compared using the external commercial PAES. The results showed that the data measured using the embedded CSPS are highly consistent with those measured using the external PAES. Notably, at the late stage of the experiment, the number of low amplitude signals measured using the embedded CSPS was several times higher than that measured using the external PAES, which demonstrates that the sensitivity of the embedded CSPS is better than that of the external commercial PAES. Furthermore, the curve of the b-value and fractal dimension of the two kinds of sensors (the embedded CSPS and the external PAES) showed evident phased characteristics in different loading stages. In the bending failure test of the concrete beam, the trend of the curve of the fractal dimension can be divided into three stages, which correspond to the three stages of bending failure. Moreover, when the b-value keeps decreasing and becomes stable at a low level, it indicates that the concrete beam has entered the final yield failure stage. Furthermore, the transformation of each failure stage is accompanied by a sudden increase in energy. In the compression–shear failure test of the concrete beam, the steep drop in the b-value and fractal dimension indicates the development and connection of large fractures. Therefore, these indices dynamically reflect the evolution of structural damage and can be used as an early warning index for the final failure of the concrete beam. Compared with the acoustic emission location results calculated by the commercial PAES, the number of acoustic emission location results calculated using the embedded CSPS was greatly increased, which effectively improved the accuracy and sensitivity of damage location analysis.
Abstract: Coping with climate change is a common topic facing the world. The steel industry is an important basic industry of the national economy; however, it is also a resource-intensive and typical high-carbon-emission industry. Low-carbon green is the inevitable choice and the only way for its high-quality development. Under the background that the world has entered a new stage of low-carbon development, this study analyzes the historical trend that the transfer of steel industry centers in the world is accompanied by technological change. In the new stage that China has become a steel center and will continue for a long time, it is faced with the demand for a significant reduction in carbon emissions, intensity, energy consumption, green trade barriers (such as carbon border tax), green procurement pressure, and breakthrough technology research and development challenges. This study outlines the low-carbon development plan and path of the international and domestic steel industry and focuses on the analysis of the exploration and contribution made by China’s steel industry in low-carbon green development in recent years. This study also aims to analyze the transformation of the future steel industry to low-carbon development based on the continuation of the practical achievements of green manufacturing with practical cases and summarize four types of development paths, which provide practical cases for iron and steel enterprises to help achieve the national goal of “carbon peak, carbon neutral” . The first path is to transition from ultralow-emission-centered development to pollution and carbon reduction and promote sintering flue gas circulation and high-proportion pellet smelting, selective circulation purification of sintering flue gas and waste heat utilization, and other technologies. The second path is to reform the energy structure with hydrogen energy as the center in the energy field, research and develop low-cost, large-scale hydrogen production technology, build a network of hydrogen refueling stations, accelerate the construction of green logistics systems, and lead the industry development in the practice of exploring hydrogen metallurgy technology. The third path is to rely on the cycle sustainability of steel materials (starting from the entire industrial chain and upstream and downstream coordination), utilize a full life cycle assessment platform and products, create a low-carbon green industrial ecosystem, and comprehensively promote green manufacturing in combination with upstream and downstream key enterprises. The fourth path is to conduct cooperative research and development of breakthrough technologies (such as carbon capture utilization and storage and other cutting-edge technologies) to strengthen the cooperation between industry, university, and research and integrate global innovation resources. Finally, based on the current low-carbon development trend of the steel industry and the proposed low-carbon development paths, this study analyzes the impact of international situations (such as the EU carbon border regulation mechanism on China’s steel industry), promotes the full life cycle assessment of steel materials, encourages the construction of hydrogen energy development strategies and energy source systems, establishes a green industrial chain, and recommends collaborative carbon reduction.
Abstract: It is critical to discover a clean energy source to replace fossil fuels such as coal to meet the targets of “emission peak” and “carbon neutrality” in 2030 and 2060, respectively. Biomass is a kind of renewable energy that is rich in reserves and can be directly converted into fuel. Pyrolysis is a common way to maximize the value of biomass, and the composition and distribution of products can be adjusted by the addition of catalysts. Carbon-based catalysts have the advantages of low preparation costs and easy treatment after catalysis. However, they have the disadvantages of easy carbon deposition inactivation and low product selectivity. The competitiveness of carbon-based catalysts can be improved when combined with the microwave effect. Herein, the research status of microwave-assisted carbon-based catalysts for the pyrolysis of biomass is reviewed. This study primarily introduces the microwave heating theory principle as well as the microwave absorber and catalyst effect mechanisms on the microwave for pyrolysis. The limitations of metal catalysts and molecular sieve catalysts are analyzed, and the unique advantages of modified carbon-based catalysts in the field of microwave pyrolysis are proposed. Microwave heating uses microwave radiation to create heat in the internal particles of biomass; therefore, microwave pyrolysis has the advantages of a high heating rate, uniform heating, low energy loss, a high energy conversion rate, and instantaneous adjustment. The effects of different modification methods (metal loading method, chemical method, sulfonation, etc.) on the pore structure, oxygen-containing functional groups, and acidic groups of carbon-based catalysts and the characteristics of catalytic products are analyzed. Among them, the preparation method’s precipitation method is difficult to manage, and the repeatability is low. The impregnation method has the advantages of being an easy preparation process, being inexpensive, and having a large production capacity. The chemical process will remarkably alter the oxygen-containing groups and acidity of the biochar. Too much acidity causes carbon deposition and catalyst deactivation, whereas too few acidic oxygen-containing groups induce pyrolysis rate decreasing. Therefore, the raw materials used in sulfonation are not environmentally friendly. The application progress of microwave-assisted modified carbon-based catalysts in tar reforming and improving the properties of biomass pyrolysis products is summarized. Carbon-based catalysts combined with microwave heating can increase the yield of phenols and syngas and improve the quality of pyrolysis products. Herein, some suggestions on the problems existing in this research direction are put forward and prospected, which provides some reference for the selection and modification of carbon-based catalysts and the high-value utilization of biomass based on microwave catalytic pyrolysis.
Abstract: Nitrogen oxides (NOx) are the primary air pollutant in China. The iron and steel industries have become the primary industrial sources of NOx emissions in China. The NOx emissions from iron and steel industries account for 27.3% of all industrial NOx emissions from sources nationwide, surpassing thermal power generation and cement manufacturing. Over the past ten years, China’s iron and steel industry has achieved tremendous results in flue gas desulfurization, but a huge gap in denitrogenate (deNOx) still remains. In 2019, the Ministry of Ecology and Environment and other departments jointly issued “Opinions on Promoting the Implementation of Ultra-low Emission in the Iron and Steel Industry”, which promoted the retrofitting of ultra-low emission in the iron and steel industry. Sintering, pelleting, coking, and other processes are the focus of retrofitting for NOx emissions. Because their low-temperature flue gas contains several contaminants that differ from the flue gas of thermal power plants, they cannot completely copy the existing deNOx technology for the coal-fired boiler flue gas of thermal power plants. At present, selective catalytic reduction (SCR), activated carbon (AC) adsorption catalysis, ozone (O3) oxidation and absorption, and other technologies are used in sintering, pelleting, and coking processes. These technologies have achieved good results. Herein, we investigated the existing flue gas deNOx technologies for sintering, pelleting, and coking processes in iron and steel industries and analyzed the advantages and disadvantages of SCR technology, AC adsorption catalysis, and O3 oxidation and absorption technologies. The SCR technology has high efficiency and reliable performance, but the operation process requires heating of the flue gas, which uses large amounts of blast furnace gas or coking oven gas, and the service life of the catalyst is typically approximately three years. The waste SCR catalysts are recognized as HW50 hazardous waste. AC adsorption catalytic technology can simultaneously desulfurize and deNOx; its operating temperature is low without flue gas reheating. The by-product of H2SO4 can be utilized, and the waste AC produced can be directly used for sintering or coking, while its deNOx efficiency is low. O3 oxidation and absorption technologies have a low initial investment cost and require little floor space. However, their operating cost is relatively high, and the coabsorption of NOx and SO2 makes the desulfurization ash mixed with nitrate, which increases the difficulty of comprehensive utilization. Finally, we analyzed the application possibilities of SCR and other technologies, providing a reference for the development and selection of deNOx technologies for flue gas from the iron and steel industry.
Monthly, started in 1955 Supervising institution：Ministry of Education Sponsoring Institution：University of Science and Technology Beijing Editorial office：Editorial Department of Chinese Journal of Engineering Publisher：Science Press Chairperson：Ren-shu Yang Editor-in-Chief：Ai-xiang Wu ISSN 2095-9389CN 2095-9389
