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The health status of the planetary gears in the cutting section of shearer's rocker arm directly affects the cutting efficiency. The strong noise interference caused by multiple impacts during the cutting of coal and rock by the shearer, the complex gear structure, and the variable transmission path make it difficult to extract fault features. In order to solve the above problems, a fault diagnosis method for planetary gears in shearer based on spectral average denoising and correlation spectrum is proposed. Based on the distribution features of signal spectrum and the random features of noise, the spectrum average denoising method is adopted to suppress the interference of noise on the signal spectrum and obtain the signal denoising spectrum. The method constructs relevant spectra to establish the intrinsic relationship between few sample denoising spectra and multi sample denoising spectra, and reduce the demand for sample size for average spectrum denoising. The method uses a one-dimensional convolutional neural network (1D CNN) to establish an accurate mapping relationship between correlation spectra and fault categories, with correlation spectra as input and fault categories as output, to achieve planetary gear fault classification and recognition. The experimental verification of the fault diagnosis method for planetary gears in shearer based on spectral average denoising and correlation spectrum is carried out on the drivetrain diagnostics simulator transmission system fault diagnosis experimental platform. The results show that the method can enhance the key frequency that characterizes the fault features. The overall recognition rate for five types of health status signals of planetary gears, including normal, broken teeth, wear, missing teeth, and cracks, reaches 96%. Gear fault diagnosis can be effectively and accurately achieved when the signal-to-noise ratio is not less than 15 dB.

Coal and gangue sorting methods based on heavy-medium coal selection technology, jigging technology, flotation technology, dry coal selection technology and γ-ray detection method have high investment costs, low sorting efficiency and serious environmental pollution. The accuracy of the coal gangue sorting method based on CCD cameras is not high, and the X-ray based coal gangue sorting technology can harm the health of personnel. Infrared thermal imaging technology has the advantage of being unaffected by light and dust, and will not cause harm to the human body. A coal gangue recognition method based on infrared thermal imaging has been proposed. Firstly, coal and gangue pass through the heating area under the conveyor belt, and the temperature of the center point of coal and gangue is monitred through an infrared thermal imager to obtain the temperature of the heated coal and gangue. The infrared thermal imager is used to capture the uniformly heated coal and gangue in the heating area, obtaining infrared grayscale and color images of the coal and gangue. Secondly, Gaussian filtering is used to preprocess and extract features from the infrared grayscale images and infrared color images of coal and gangue. The grayscale mean of the infrared grayscale image, the grayscale value feature corresponding to the maximum frequency, and the G-channel first-order moment and G-channel second-order moment features of the infrared color image are used as sorting features. The above four features are used as inputs for the classification model. Finally, support vector machine (SVM) is used for classification and recognition to achieve the goal of recognizing coal and gangue. The experimental results show that the coal gangue recognition method based on infrared thermal imaging has achieved an accuracy rate of over 98% for the sorting of bituminous coal, anthracite, and lignite, and has a good classification effect.

The addition of trace Mo and Nb elements to the Fe-Cr-Al ferrite alloy of the accident tolerant fuel (ATF) cladding can play a role in solid solution strengthening and precipitation. The precipitated Laves phase distributes at the grain boundary and subgrain boundary, which can fix the grain boundary and hinder grain growth, improving the thermal stability of the alloy. According to another view, the pinning effect of the Laves phase is smaller than the solute drag effect (SDE) and does not contribute significantly. The phase field method was used to quantitatively simulate the hindrance of Mo and Nb solute elements to grain boundary migration in order to study SDE on grain boundary migration during grain growth. To model the effect of the solute elements on grain boundary migration, a polycrystalline phase field model and a solute drag additional term were introduced to the existing phase field model, and the specific expressions of these models were derived for simulation. The simulation results show that the phase field method can observe the unsteady solute separation process, in comparison to the classical steady-state SDE model. In addition, the distribution of solute at grain boundaries with different migration rates and the corresponding SDE dissipation energy at those rates are also obtained, and the action range of Nb and Mo element SDE is determined. The degree of solute segregation at the grain boundary is negatively related to the grain boundary migration rate. When the grain boundary migration rate is greater than 1×10-5 m/s, the segregation of Mo and Nb at the grain boundary tends to zero. The relationship between SDE dissipation energy and interface migration rate is parabolic, with a peak value of 69.7 J/mol at a rate of 1.124×10-6 m/s. When the interface migration rate is less than 1.124×10-6 m/s, the concentration distribution deviates from the equilibrium state and the dominant SDE dissipation energy increases. When the interface migration rate is greater than 1.124×10-6 m/s, the solute separates and the degree of segregation decreases, while the dominant SDE dissipation energy decreases. During the early stage of grain growth, the solute at the grain boundary is not in a saturated state and the interface migration rate is too high, resulting in no obvious SDE. At the same time, the high interface migration rate causes solute retention. The results of the study show that the model is suitable for simulating the SDE in the polycrystalline growth process, and can provide valuable information for a deeper understanding of the solute dragging process of Mo and Nb in materials and for material design and performance prediction.

Regarding the poor visible light response and the difficulty in synchronously driving photocatalytic reduction and oxidation reactions of MOFs, In2S3/UiO-67 composites (IM-1, IM-3, and IM-5) were prepared by deposition of in situ generated In2S3 species on the surface of UiO-67(Zr-MOF), and the formation of heterostructure was confirmed by PXRD, FT-IR and XPS characterization. Under the irradiation of 500 W xenon lamp, the reduction efficiency of IM-3 for Cr(Ⅵ) reached 92.4% within 60 min, providing the reduction rate of 2.3 and 20 times that of pure In2S3 and Zr-MOF, respectively. The degradation efficiency for RhB was 78% within 180 min, with the degradation rate of 1.75 and 2.3 times of that of pure In2S3 and Zr-MOF. Moreover, the migration direction of photogenerated carriers were elucidated by XPS, and the photocatalytic reaction mechanism was further revealed in combination with free radical trapping experiments.

Abstract Chinese cordyceps was one of most valuable traditional Chinese medicine fungi. To elucidate the molecular mechanisms related to energy supply mechanism involved in the initiation and formation of primordium in Chinese cordyceps, we performed the integrated metabolomic and transcriptomic analyses of it at pre-primordium period, primordium germination period and after-primordium period, respectively. Transcriptome analysis showed that many genes related to ‘starch and sucrose metabolism’, ‘fructose and mannose metabolism’, ‘linoleic acid metabolism’, ‘fatty acids degradation’ and ‘glycerophospholipid metabolism’ were highly up-regulated at primordium germination period. Metabolomic analysis showed many metabolites regulated by these genes in these metabolism pathways were also markedly accumulated at this period. Consequently, we inferred that carbohydrate metabolism and β-oxidation pathway of palmitic acid and linoleic acid worked cooperatively to generate enough acyl-CoA, and then entered TCA cycle to provide energy for fruiting body initiation. Overall, our finding provided important information for further exploring the energy metabolic mechanisms of realizing the industrialization of Chinese cordyceps artificial cultivation.

Due to the complex working conditions of high noise, low illumination, and blurred movement in coal mines underground, as well as the phenomenon of coal gangue easily gathering, it is difficult to extract features from coal gangue object detection models. The classification and positioning of coal gangue are inaccurate. In order to solve the above problems, a coal gangue recognition method based on the CED-YOLOv5s model is proposed. Firstly, the coordinate attention (CA) mechanism is introduced into the YOLOv5s backbone network, which encodes feature maps by embedding coordinate information into channel relationships and long-range dependencies. The method fully utilizes channel attention information and spatial attention information to make the model focus more on important features and suppress irrelevant information. Secondly, the EIoU regression loss function is introduced in the detection head of YOLOv5s to minimize the width and height difference between the object box and anchor box. It enhances the position and boundary information of the object, improves the positioning precision and convergence speed of the model in dense objects. Finally, a lightweight decoupling head is introduced in the detection head of YOLOv5s, decoupling separate feature channels for classification and regression tasks. It solves the interference problem between the coupling head part of the class task and the regression task in the original model, further improving the parallel operation efficiency and detection precision of the model. The experimental results show that the CED-YOLOv5s model has the best overall performance compared to other YOLO series object detection models. It has an average detection precision of 94.8%, an improvement of 3.1% compared to the YOLOv5s model, and a detection speed of 84.8 frames/s. The results can fully meet the real-time detection requirements of coal gangue in coal mines.

The coal gangue recognition method based on visible light images has low accuracy and slow recognition speed. The coal gangue recognition method based on high-energy ray transmission has significant radiation, resulting in limited application. The infrared thermal imaging has advantages such as strong penetration and no influence from light. But the surface temperature of coal and gangue is relatively close at room temperature, resulting in no significant difference between coal and gangue in infrared thermal images, making it difficult to achieve good recognition results. In order to solve the above problems, a coal gangue recognition method based on water heat transfer and infrared thermal imaging is proposed. The method conducts infrared thermal imaging experiments on coal and gangue under different water temperatures (18, 21, 24, 27, 30 ℃). The method distinguishes between coal and gangue based on the differences in infrared thermal images and temperature changes. The experimental results show that the infrared thermal images of coal and gangue are different at different water temperatures. When the water temperature is lower than the ambient temperature, there is a significant difference between the infrared thermal images of coal and gangue. Under the same water temperature conditions, the difference between the infrared thermal images of coal and gangue gradually increases with time. The surface temperature changes of coal and gangue both show an increasing trend with the increase of water temperature and time. But the surface temperature changes of gangue are greater than those of coal. When the water temperature is 18℃ and the time is 180 s, the difference and temperature difference between the infrared thermal images of coal and gangue reach their maximum. This indicates that low-temperature water can serve as a heat transfer medium, which is more conducive to creating a large temperature difference between coal and gangue. The accurate and rapid recognition of coal and gangue infrared thermal images can be achieved.

Blockchain technology, with its decentralization, traceability, and immutability, offers promising solutions across various sectors, including education. This study explores the application of blockchain in enhancing the security and personalization of educational resource sharing within university physical education (PE). We ensure secure resource sharing by developing a blockchain-based model for PE resource distribution and refining the consensus algorithm. Our research involved a 10-week experiment with 80 university students, measuring changes in psychological factors (e.g., anxiety, depression) and physiological parameters (e.g., lung capacity). Results indicated a notable improvement in students’ psychological well-being, with anxiety and depression levels dropping by an average of 15%, and a significant enhancement in physiological health, evidenced by an average increase in lung capacity of 2.11±1.00 ml/kg. These findings underscore the potential of blockchain technology to elevate university PE teaching practices and positively impact student health, highlighting its significant applicability and future potential in educational contexts.

The climate is an important factor influencing residents’ travel behavior. Many studies have focused on travel in areas with gentle terrain, with high-altitude regions receiving increased research attention due to their unique climatic conditions. Pilgrimage is a daily travel activity for many residents, and studying pilgrim flow patterns helps enrich the theory of travel behavior in high-altitude regions. In the context of population aging, it is crucial to help policymakers and transportation planners recognize the travel mobility needs of elderly pilgrims. This paper comprehensively analyzes the socio-demographic, travel and personal health attributes related to the mobility of elderly pilgrims and establishes plateau climate as an important factor influencing the travel behavior of this group. This study considers the actual situation of the Tibetan Plateau to fit the theoretical gap related to the travel behavior of urban residents in the plateau. Using travel diary data from selected cities on the Tibetan Plateau, a Random Coefficient Multinomial Logit Model is used to analyze the mobility patterns of elderly pilgrims. Considering the realities of China and based on specific research findings, policies developed by transportation practitioners and urban planners need to encourage older adults to use active transportation modes with lower carbon emissions and public transportation.

Reasonable design of inorganic nano-base materials to promote the anticorrosion performance of waterborne epoxy resin (EP) coating remains a great challenge. Herein, we describe the preparation method and anticorrosion properties of zeolitic imidazolate framework (ZIF-67) composite coatings. ZIF-67 could be used as both anticorrosion filler and pigment for the coatings. The addition of ZIF-67 improved the impermeability of the coating, thus slowing down the chemical reaction on the surface of the substrate. The long-term corrosion-resistant performance of composite coatings (ZIF-67@EP) in 3.5% NaCl solution was evaluated comparatively. Before immersion, the low-frequency impedance of 1% ZIF-67@EP coating was 2.5 times of 0% ZIF-67@EP coating, and after 14 days of immersion, the low-frequency impedance of 1% ZIF-67@EP coating was still 1.8 times of 0% ZIF-67@EP coating. The corrosion rate of 1% ZIF-67@EP coating was decreased by 177 times.

Lung cancer is the malignant tumor with the highest incidence and mortality in China, and is prone to brain metastasis in the process of disease development, which seriously affects the quality of life and survival of patients. The treatment methods for brain metastasis of lung cancer include surgery, chemotherapy, whole brain radiotherapy, stereotactic radiosurgery, molecular targeted therapy, immunotherapy, anti-angiogenesis therapy, etc. It's one of the research hotspots to choose reasonable and effective treatment schemes for different patients. This paper reviews the research progress in the treatment of brain metastasis from lung cancer, to provide reference for selecting more reasonable clinical treatment for the patients.

Objective To evaluate the osteogenic effect of concentrated growth factor (CGF) combined with deproteinated bovine bone mineral (DBBM) in site preservation using clinical and histomorphometric observations. Methods A total of 26 patients who needed extraction of affected teeth and received staged implantation after site preservation were selected. The patients were randomly divided into the DBBM group (Bio-Oss was implanted simultaneously after extraction) and CGF+DBBM group (CGF+Bio-Oss was implanted simultaneously after extraction), with 13 patients in each group, and both groups were covered with Bio-Gide collagen membrane. Cone beam computed tomography (CBCT) was performed preoperatively and 6 months later to measure the changes in alveolar bone height and width, and the bone specimens were drilled 6 months after site preservation during implant surgery for histological analyses. Results CBCT showed that the height and width of alveolar bone were absorbed 6 months after site preservation in the CGF+DBBM and DBBM groups, and the reduction in alveolar ridge width in the CGF+DBBM group was statistically less than the DBBM group (P

Objective The clinical characteristics and imaging information of insular glioma patients were collected to predict mutation status of isocitrate dehydrogenase 1 (IDH1). Methods A total of 596 patients with gliomas confirmed by postoperative pathology in The First Affiliated Hospital with Nanjing Medical University from January 2011 to June 2021 were enrolled, including 72 insular gliomas, 213 frontal gliomas, 165 temporal gliomas, 76 parietal gliomas, 28 and 29 midline gliomas. All patients were examined by MRI, fifteen glioma⁃related features were selected from the visually accessible rembrandt images (VASARI), including enhancement quality, enhancement proportion, non⁃enhancement proportion, necrosis proportion, edema proportion, cyst, thickness of enhanced margin, definition of the enhanced margin, hemorrhage, diffusion, deep white matter involvement, deep ventricle involvement, midline cross, T2⁃FLAIR mismatch, maximum diameter of tumor. Univariate and multivariate Logistic regression analysis were used to screen the predictive factors related to IDH1⁃mutant in insular glioma. The receiver operating characteristic (ROC) curve was plotted and area under the curve (AUC), sensitivity and specificity were calculated to evaluate the predictive power of MRI features for IDH1⁃mutant glioma. Results IDH1 mutation rate was higher in insular and frontal gliomas (P＜0.01, for all). WHO grade Ⅱ had the highest IDH1 mutation rate (P=0.008, 0.000), and grade Ⅳ had the lowest mutation rate (P=0.000). The IDH1 mutation rate in low⁃expression Ki⁃67 gliomas was higher than that in high⁃expression gliomas (P=0.000). Logistic regression analysis showed that weak enhancement (OR=35.671, 95%CI: 2.805-453.600; P=0.006), non⁃enhancement (OR=75.453, 95%CI: 2.881-1872.759; P=0.009), unlimited diffusion (OR=10.573, 95%CI: 1.043-107.175; P=0.046), no deep ventricle involvement (OR=187.601, 95%CI: 2.269-15507.607; P=0.020), T2⁃FLAIR mismatch (OR=47.536, 95%CI: 2.838-796.097; P=0.007) were independent predictive factors for IDH1 mutation in insular glioma. The AUC of enhancement degree, diffusion, deep ventricle involvement and T2⁃FLAIR mismatch for the diagnosis of IDH1⁃mutant glioma were 0.846 (95%CI: 0.748-0.944, P=0.000), 0.730 (95%CI: 0.609-0.850, P=0.001), 0.708 (95%CI: 0.584-0.833, P=0.003) and 0.745 (95%CI: 0.627-0.864, P=0.000). The combination of the 4 groups had the highest diagnostic efficacy, and the AUC was 0.961 (95%CI: 0.923-0.999, P=0.000). Conclusions Low grade insular glioma has a high IDH1 mutation rate. MRI features of weak enhancement and non⁃enhancement, unlimited diffusion, non deep ventricle involvement and T2⁃FLAIR mismatch contribute to noninvasive prediction of IDH1⁃mutant insular glioma.

This study examined the potential mechanism of zoledronate on interleukin (IL)-1β-induced temporomandibular joint osteoarthritis (TMJOA) chondrocytes, using IL-1β-induced rabbit immortalized mandibular condylar chondrocytes cultured with zoledronate. Cell viability, apoptosis, mRNA, and protein expression of relevant genes involved in extracellular matrix (ECM) degradation, apoptosis, and Wnt/β-catenin signaling were examined. The involvement of the Wnt/β-catenin signaling was examined using Wnt/β-catenin inhibitor (2-(4-(trifluoromethyl)phenyl)-7,8-dihydro-5H-thiopyrano[4,3-d]pyrimidin-4-ol (XAV-939)) and activator lithium chloride (LiCl). Aggrecan and type II collagen were downregulated by zoledronate, especially with 100 nM for 48 h (p < 0.01), consistently with the upregulation of A disintegrin and metalloproteinase with thrombospondin motifs-4 (ADAMTS-4) (p < 0.001), matrix metalloprotease-9 (MMP-9) (p < 0.01), caspase-3 (p < 0.001) and downregulation of proliferating cell nuclear antigen (PCNA) (p < 0.01). The apoptotic rate increased from 34.1% to 45.7% with 100 nM zoledronate for 48 h (p < 0.01). The effects of zoledronate on ADAMTs4 (p < 0.001), MMP-9 (p < 0.001), caspase-3 (p < 0.001), and PCNA (p < 0.01) were reversed by XAV-939, while LiCl increased caspase-3 expression (p < 0.01). In conclusion, zoledronate enhances IL-1β-induced ECM degradation and cell apoptosis in TMJOA chondrocytes. Wnt/β-catenin signaling might be involved in this process, but additional studies are necessary to determine the exact involvement of Wnt/β-catenin signaling in chondrocytes after zoledronate treatment.

Conveyor belt deviation and coal stacking are common faults of belt conveyor in the coal mine. The traditional contact conveyor belt deviation or coal stacking detection methods can not meet the requirements of coal mine safety production in terms of durability, sensitivity and reliability. However, the detection effect based on the image processing method is greatly affected by image color information, which is prone to false identification. The belt conveyor deviation and coal stacking monitoring method based on 3D point cloud is proposed. The 3D point cloud data of the conveyor belt surface is collected by line laser binocular camera. The real-time monitoring of belt deviation and coal stacking is carried out by analyzing and processing the point cloud data. In terms of conveyor belt deviation monitoring, Euclidean clustering and random sampling consistency algorithm are used to filter redundant point cloud data, and extract edge data points of the conveyor belt. The mean central characterization value is used to characterize the degree of conveyor belt deviation, so as to reduce the influence of the shape change in the width direction of the conveyor belt on the monitoring. In terms of coal stacking monitoring, the equivalent height of coal flow is obtained by processing point cloud data. The height and width information of coal flow is characterized by the equivalent height, so that the coal stacking degree is evaluated in real-time. The test bed of the belt conveyor deviation and coal stacking monitoring system is built. The test results show the following points. When the speed of the conveyor belt is 0.5-3.0 m/s, the detection error of the edge point of the conveyor belt is − 2.84-1.26 mm, and the maximum error is only 2.84 mm. It shows that the system can reliably realize the function of deviation fault monitoring and accurately predict the deviation trend. Coal samples (14-41 kg, in increments of 1 kg) are stacked on the conveyor belt. When the coal mass is within the range of 14-24 kg and 28-41 kg, the coal stacking detection results are correct. There are detection errors in the range of 25-27 kg. The reason is that the coal sample quality in this range is close to the critical value of 27.6 kg for triggering the coal stacking alarm.

As a typical spinel ferrite, NiFe2O4 is suitable for use in gas sensors. Herein, we report the fabrication of porous, tremella-like NiFe2O4 assembled using porous, ultrathin nanosheets via the coordination of Ni2+ and Fe2+ with 1,4-phenylenediboronic acid. The optical band gap of the NiFe2O4 is estimated to be about 1.7 eV. Furthermore, the NiFe2O4 sensor annealed at 400 °C exhibits a low detection limit of 50 ppb, a fast response/recovery time (11.6 s/41.9 s to 10 ppm toluene), good reproducibility, and long-term stability at 220 °C. The suitable sensing performances can be attributed to the good catalytic activity of NiFe2O4 to toluene oxidation. Moreover, the ultrathin nanosheets with porous structures provide a large number of active sites to significantly favor the diffusion and adsorption/desorption of toluene molecules. This current work provides an insight into fabricating NiFe2O4 using 1,4-phenylenediboronic acid, which is promising for ppb-level toluene detection.

Drilling operation is widely used in modern coal mine operation.Carbon monoxide gas (CO) is produced in coal seam during drilling operation, which leads to fire and CO exceeding accident.In this paper, an experimental platform for monitoring CO in coal borehole is built and Fourier infrared spectroscopy is carried out to analyze the law of production CO in coal seam during drilling from macroscopic and microscopic perspectives.The experimental results show that there is a certain amount of CO generated in the coal seam drilling operation, and the production of CO is proportional to the speed and temperature of the drill bit.In the coal sample cuttings after drilling, the contents of aliphatic group and oxygen-containing functional group are higher than the raw coal, indicating that the production rate of CO is higher than the consumption rate.Analysis shows that the CO produced during drilling operation is a mixture of oxidized carbon monoxide (O-CO) and carbon monoxide (S-CO) produced by the cracking of coal macromolecules.Among them, the O-CO generated during drilling operation mainly comes from oxygen-containing functional groups formed by oxidation of aliphatic functional groups such as -CH2 and -CH3, and pyrolysis occurs under the action of internal energy.S-CO is caused by coal's macromolecular fracture and the conversion of mechanical energy to thermal energy, leading to the pyrolysis of oxygen-containing functional groups in raw coal.

Wi-Fi6 standard will be major Wi-Fi technology dominated for deployment after 2020. But to support increasing bandwidth requirements and number of access devices per year, Wi-Fi technology and throughput still need to be further developed and improved. This paper will introduce the key technology involved for latest IEEE802.11be standard discussion, describing the major changes on physical and MAC layer, particularly providing the analysis for multi-access point coordination, hybrid automatic repeat request and Wi-Fi full duplex mode. Finally, this paper will introduce the granted progress of latest 6 GHz applied by both new 802.11ax version and 802.11be with related Wi-Fi function impact.

Objective. To investigate the association between gender and gastrointestinal (GI) dysfunctions, as well as gender and other motor symptoms/nonmotor symptoms, in a sample of PD patients. Methods. 186 patients with PD were recruited into this study and divided into male PD group (M-PD) and female PD group (FM-PD). Demographic and PD-related clinical information of the participants were collected by the same neurologist. PD patients were objectively assessed by a spectrum of rating scales of motor symptoms and nonmotor symptoms (including GI dysfunctions). The data were analyzed by SPSS 20 statistical software. Results. Totally 95 cases (51.08%) were in the M-PD group and 91 cases (48.92%) in the FM-PD group. There were no significant differences in age, BMI, and lifestyles between the two groups (P > 0.05). Males had higher educational level (P = 0.002). Females were more likely to have early satiety and loss of appetite (P = 0.025, P = 0.001). There were no significant differences in LED disease duration, age of motor symptoms onset, types of motor symptoms onset, location of motor symptoms onset, and phenotype of motor symptoms between the two groups (P > 0.05). Females had significantly higher UPDRS-III and HAMD scores than males (P = 0.037, P = 0.034). There were no significant differences in PQSI, ESS, RLS, RBD, HAMA, HAMD, and MoCA scores between the two groups. Gender was associated with HAMD (OR = 0.682, P = 0.019). Conclusions. Gender is a risk factor for depression, but not for GI dysfunctions in patients with PD.

In view of problem that global optimal path was difficult to determine due to disturbance of obstacle interval in process of path planning for coal mine search and rescue robot, optimal path planning algorithm for coal mine search and rescue robot based on gradient-coordinate rotation method was proposed. The robot first moves according to gradient-coordinate rotation method, then performs local path optimization according to existing motion path, and makes feasibility judgment on the planned local optimal path until there is no obstacle interval in the path. The simulation results show that the algorithm can make the coal mine search and rescue robot accurately plan the global optimal path from starting point to target point under the premise of avoiding obstacles, so as to improve rationality and efficiency of robot motion path planning.

A 3D model of suspension support system of permanent magnetic suspension belt conveyor was established. Stability of permanent magnetic suspension support system under different magnetic conveyor belt shape, permanent magnet arrangement, permanent magnet shape and partial load condition were simulated. The results show that stability of groove-type magnetic conveyor belt is better than that of flat-type and V-type magnetic conveyor belts with stable bearing capacity. Stability and bearing capacity of conveyor belt are better when permanent magnet has groove-type structure. Partial load will increase deviation of magnetic conveyor belt. In order to effectively solve deviation problem of magnetic conveyor belt, an anti-deviation device for groove-type magnetic conveyor belt was designed. By installing auxiliary rollers on both sides of the groove-type magnetic conveyor belt, stability of the suspension support system of permanent magnetic suspension belt conveyor can be further improved.

In order to analyze the dynamics characteristic of the hip joint simulator which taking the 3HUS+ S spatial parallel mechanism as the core module,starting from the kinematics of parallel mechanism,the relationship between the velocity,acceleration of moving platform and the linear module slider and active branched- chains are established. By the forces and torques of the centroid of the moving platform,active branched- chains and linear module,the dynamics model is established based on the principle of virtual power. The driving torques and powers of the linear module are obtained by simulating on the dynamics model,a reference for the simulator in the analysis of dynamics characteristics and research of control strategy is provided.

In order to overcome the defects of traditional serial hip joint testing machine on high speed,complex motion simulation and large dynamic loading,aparallel hip joint testing machine with a3SPS+1PS spatial parallel manipulator as the core module is developed.The complicated forward position solution and the singularity are significant difficulties of its application.An analytical model of forward position analysis is built with the coordinates of hinge points on the moving platform and a univariate polynomial equation of higher degree is obtained,proving that there exist 8forward solution for a single input at most.The singular status of the testing machine under required motions is investigated according to the Jacobian matrix.The two singular points are proved to be the forward singularities caused by the overlaps of the forward position solution.Then the corresponding avoidance strategy is given.

Taking two-stage planetary gear of the cutting part of MG900 /2215-GWD shearer as study object,the dynamics analysis simulation of it is carried out by using virtual prototype technology.By comparing the meshing force curves in time domain and frequency domain of the health and several broken tooth fault of varying degrees,the dynamic response of two-stage planetary gear system under fault condition is analyzed.It can be found that under fault condition,the mesh force side bands of energy become intensive,and the intensity increases with the extent of the damage increase.The research results can provide a theoretical basis for two-stage planetary gear fault diagnosis and testing.