Stable and continuous visual posture measurement data is of great significance for improving the work efficiency of coal-mine tunneling equipment. Currently, posture measurement methods for tunneling equipment based on visual information face issues such as cumbersome calibration process of cooperative target during station transfer and inability to perform automatic continuous measurements. Aiming at this problem, an automatic calibration method for station transfer based on binocular vision is proposed. Firstly, the HSV (hue, saturation, value) color segmentation and point-line feature extraction technology were employed to process the red features of the cooperative target, so as to obtain the image information of the cooperative target. Then, a calibration solution model for station transfer was designed, and the binocular vision measurement method was used to obtain the spatial parameters of the cooperative target. Finally, based on the characteristic that the relative position between the camera and the cooperative target was unchanged during the calibration process, the L-M (Levenberg-Marquardt) algorithm was used to optimize the spatial parameters of the cooperative target, and the optimization results were applied to the visual positioning system to complete the calibration for station transfer. The experimental results showed that the position measurement error of the tunneling equipment body after the calibration for station transfer was within 50 mm, and the attitude angle measurement error was within 0.6°. The proposed automatic calibration method for station transfer based on binocular vision meets the accuracy requirements of the visual positioning system for coal-mine tunneling equipment, which can provide theoretical support for the research of rapid tunneling technology.

At present, the 3D printed concrete field is still hampered by numerous issues that impede its large-scale industrial production and application. Among these, pores stand out as the most prevalent defect. Consequently, there is an urgent imperative to develop pertinent detection technologies for enhancing the printing quality of concrete. Aiming at the existing 3D printed concrete interface pore detection methods that mainly rely on subjective experience of individuals, and have disadvantages such as long-time consumption, high cost and large computational resource consumption, a lightweight intelligent pore detection method is proposed by introducing a deep learning-based object detection algorithm. Firstly, the traditional image processing algorithms were employed to preprocess the 3D printed concrete interface pore images, and the pore image dataset suitable for the target detection algorithm was constructed. At the same time, based on the characteristics of the constructed dataset, the anchor-box calculation method was optimized to acquire anchor boxes that were better suited to the interface pore targets, so as to improve the detection accuracy. Then, within the backbone network of the detection method, the ShuffleNetv2 network was utilized for multi-scale feature extraction, and part of the network was removed to reduce the network depth and the number of calculation parameters, thereby enhancing the pore detection efficiency. Finally, in order to improve detection precision, the polarized self-attention mechanism module was incorporated into the feature extraction network to enhance the attention to the pore target while maintaining high resolution. Experimental results demonstrated that the proposed method could effectively complete the intelligent detection of 3D printed concrete interface pores. Through comparing with various detection algorithms, it was found that multiple performance indicators of the method were improved, and the detection efficiency was significantly boosted. The research results can provide some data support for the subsequent quality control and performance evaluation of concrete.

As the exploration center of oil and gas resources in China moves towards deep and ultra-deep layers, the difficulty of oil and gas exploration has been increasing, which can be recognized poor drilling capacity and low rate of penetration resulted from high strength and strong abrasion of deep hard formation rocks. In order to improve the rock-breaking performance of deep hard rock bits, conical cutters are widely used in the design of hybrid-cutters PDC (polycrystalline diamond compact) bits. However, the rock-breaking volume of conical cutter is small, and its cutter arrangement method needs more comprehensive theoretical support. Therefore, taking the rock-breaking specific energy as the objective function, a rock-breaking specific energy evaluation model for the PDC cutter based on the fractal characteristics of rock cutting morphology was established by quantifying the physical parameters such as cutting force and cutting energy consumption of different types of PDC cutters during the rock-breaking process and using the maximum particle size of rock cuttings and fractal dimension of rock cutting particle size. Meanwhile, the rock-breaking performance of conical PDC cutter was investigated by comparing with the conventional planar PDC cutter, and the effects of cutting depth, cutting angle and cutting speed on the rock-breaking performance were analyzed. The results showed that the conical PDC cutter was suitable for rock breaking with large cutting depth and low energy consumption, while the conventional PDC cutter was suitable for rock breaking with high speed and small cutting depth. The cutting angle of two kinds of PDC cutters was recommended to be about 20°. Conical PDC cutters were suitable for arrangement at the central vertex and crown area of the hybrid-cutters PDC bit, while conventional PDC cutters were suitable for encrypted arrangement from the nose to shoulder area of the bit. The research results can provide theoretical basis for revealing the particle size distribution law of rock cuttings generated by PDC cutter breaking rock and the design of hybrid-cutters PDC bits.

Aiming at the difficulty of wall-climbing robot in wall sensing and automated detection of large petrochemical equipment, an improved RTAB-Map (real-time appearance-based mapping) algorithm was proposed to realize the wall-climbing robot's localization, mapping and navigation by fusing multiple sensor data. Firstly, a robot motion chassis with wall adsorption ability was built to ensure the flexible and stable movement of the wall-climbing robot on the wall surface. Secondly, to address the cumulative error of the odometer resulting from the wall-climbing robot's slippage on the wall surface, the extended Kalman filter was utilized to fuse the data of encoder and inertial measurement unit to provide accurate odometer information for mapping and navigation. Thirdly, based on the RTAB-Map algorithm, the data of depth camera, LiDAR and odometer were fused to generate 2D grid and 3D point cloud map to realize a complete description of the equipment wall, and the navigation algorithm framework of the wall-climbing robot was constructed based on the fusion data. Finally, the experimental validation was carried out on the equipment wall. The results showed that the yaw angle error could be significantly reduced by using fusion mileage method, the average error of yaw angle was reduced by 88.94% compared with that under wheel odometer planning with an average error of 0.78°. The improved RTAB-Map algorithm improved the wall-climbing robot's mapping and sensing ability in the wall environment, and realized the autonomous navigation combined with the path planning algorithm. The research results have a certain reference significance for the research and application of automated detection technology of wall-climbing robots.

Aiming at the problem of poor formation stability of environmental sanitation robots during cluster operations, an innovative formation control method combining the leader-follower strategy and artificial potential field algorithm is proposed. Firstly, according to the structural characteristics of the environmental sanitation robot, its kinematics model was constructed based on the leader-follower strategy. Then, in view of the complex operation environment of environmental sanitation robots, the artificial potential field algorithm was employed for formation obstacle avoidance, and a novel formation transformation strategy was proposed to enable robots to smoothly pass through the working scenarios such as back streets and alleys, so as to realize the cooperative operation of multi-robots. Finally, the simulation experiments were conducted by MATLAB software and the experimental test was carried out in the actual operation scenario. The results showed that the proposed method could effectively facilitate the formation of environmental sanitation robots to avoid obstacles and pass through narrow passage in complex operation scenarios, while achieving stable formation maintenance and flexible transformation. The tracking error of the following robot remained below 0.1 m when the formation was stable, and the experimental results verified the effectiveness of the formation control method. The research results provide reference for the formation control of environmental sanitation robots in different operation scenarios.

In order to solve the problems of low success rate, easy damage to fruits and unreasonable picking methods in the process of mechanical picking of clustered crabapple, a rigid-flexible coupling end-effector for picking clustered crabapple was designed. The soft fingers made of silica gel were used to wrap the crabapple, and the crabapple stalks were cut using the method of cutting. The effects of shear air pressure, blade thickness and driving air pressure on the picking success rate and their value range were determined through single factor test. On this basis, the response surface analysis of three factors and three levels was conducted to study the interactive effects of each factor on the picking success rate. The quadratic regression model was established with the success rate of picking four- and five-fruits as the response value, and the picking success rate was used as the evaluation index to optimize each factor. The results showed that the influence on the picking success rate was shear air pressure, blade thickness and driving air pressure in order from large to small. When the shear air pressure was 0.260 MPa, the blade thickness was 0.4 mm, and the driving air gas pressure was 0.09 MPa, the end-effector had the highest picking success rate, and the success rate of picking three-, four- and five-fruits could reach 100%, 100% and 91.29%, respectively. The results of parameter optimization were verified by experiment, and showed that the picking end-effector could complete the picking task, and the success rate of picking three-, four- and five-fruits could reach 100%, 100% and 91%, respectively, meeting the expected picking requirement. The use of the end-effector can reduce the labor force of picking crabapple and provide a new idea for the picking of other clustered fruit.

Aiming at the problems of insufficient passing ability and flexibility of existing mobile robots in complex and narrow environment, a modular reconfigurable tracked robot is proposed inspired by the recombination deformation mechanism of amoebas. By simulating the rigid-flexible transition characteristics of amoeba cytoplasmic particles, a lockable track module based on the latching structure was designed by fusing the pitch and yaw joints. Multiple track modules were connected in series to form a closed-loop single chain to form the external structure of the robot. Under the drive of the internal flexible body, the track chain could realize continuous rolling. By successively adjusting the yaw joint angle of front track modules and locking them by the body head, while unlocking the rear track modules in turn by the body tail, the robot could actively change its geometric morphology during the forward process. Then, based on the position relationship between adjacent track modules described by the joint angles, the morphological matrix of the robot was obtained, and the kinematics model of the robot was established by the iterative analysis of the joint angle sequence. Finally, the morphological variation range of the robot was simulated and analyzed to accurately evaluate its motion flexibility, and its motion performance was verified by making a robot prototype and carrying out a series of test experiments. The results showed that the minimum turning radius of the robot was 17.7 cm, and the robot could flexibly avoid obstacles in narrow confined space by continuously changing the yaw direction. With the passive adaptation of pitch joints, the robot could traverse all kinds of rough terrain, thus verifying the flexibility and passing ability of the robot. The research results can provide new ideas for the bionic structure design of mobile robots.

Aiming at the limitations of traditional rigid pipeline robots such as large volume and poor adaptability to unstructured environments, a soft pipeline robot based on Kresling origami structure is designed. Inspired by peristaltic crawling mode, the soft pipeline robot employed a tower spring-Kresling origami structure as the telescopic structure and silicone friction belts as the friction structure. The robot achieved a maximum payload of 5.9 times its own mass, a horizontal crawling speed of 25.14 mm/s and a crawling speed of 9.96 mm/s in vertical pipelines. Then, the effects of the telescopic structure type, the shrinkage length, material and angle parameters of Kresling origami structure, and the friction force on the robot's crawling speed were analyzed. Finally, the robot prototype was fabricated and the feasibility of the robot crawling in pipelines with different inner diameters, inclination angles and shapes was demonstrated through experiments. The results showed that the designed robot had good adaptability and flexibility, and could use the compliance of Kresling origami structure to adapt to the complex pipeline environment, which provided a novel way for pipeline detection, maintenance and other applications.

In order to solve the problem that the traditional piezoelectric-driven tip-tilt stage cannot adapt to many millimeter-level large-stroke application scenarios due to its small stroke, a three-degree-of-freedom large-stroke flexible tip-tilt stage driven by voice coil motor is designed, and its compliance modeling and performance testing are carried out. Firstly, the structural configuration of the three-degree-of-freedom large-stroke flexible tip-tilt stage was introduced, which included three sets of 120° uniformly arranged vertical driving chains, and the motion decoupling of each driving chain and the linear guidance of the motor rotor were achieved by using flexible spherical hinges and parallelogram mechanisms. At the same time, the kinematics equation of the dynamic platform of the tip-tilt stage was established according to the geometric relationship of each driving chain. Then, the compliance matrix method was used to derive the compliance analytical models for the flexible spherical hinge, the driving chain and the overall tip-tilt stage. Subsequently, the accuracy of the derived compliance analytical model was verified through the statics finite element simulation analysis for the tip-tilt stage. Finally, a tip-tilt stage testing system was built to measure its maximum stroke, as well as the translational compliance along the Z-axis and the rotational compliance around the X and Y axes, so as to verify the effectiveness and rationality of the structural design of the tip-tilt stage and the derived compliance analytical model. The results showed that the relative error between the calculation results of the compliance analytical model and the finite element simulation results, as well as the experimental results, was within 10%. The maximum stroke range of the tip-tilt stage was ±0.054 3 rad×±0.047 2 rad×±4.45 mm, which had the advantages of large-stroke and compact structure. The designed tip-tilt stage can be used in various situations that require large-stroke spatial positioning, demonstrating broad application prospects.

The rotary platform of the roadheader bears eccentric load and strong impact when cutting coal and rock, and its performance affects the working efficiency and safety of the roadheader. To explore the influencing factors of fatigue life of the rotary platform and identify the optimal service parameters of the roadheader, a fatigue life prediction method for the rotary platform based on the Kriging surrogate model and DEM-MFBD (discrete element method-multi flexible body dynamics) bidirectional coupling technology was proposed. Firstly, the spatial force models for the cutting part and rotary platform of the roadheader were established, and the force law of the cutting part and rotary platform was clarified. Then, the bidirectional rigid-flexible coupling dynamics simulation analysis for the rotary platform was conducted by combining RecurDyn and EDEM software to obtain the stress distribution of the rotary platform under the working condition. Finally, 15 groups of service parameters of roadheader were selected by Latin hypercube sampling method as input, and the corresponding Kriging surrogate model was established with the fatigue life of the rotary platform as the response. The surrogate model was optimized by particle swarm optimization algorithm to obtain the fatigue life of the rotary platform under the optimal service parameters. The results showed that the fatigue life of the rotary platform was maximum when the cutting head speed of the roadheader was 54 r/min, the lateral swing speed of rotary platform was 1.003 m/min, and the vertical swing angle of cutting arm was 7°. Combining DEM-MFBD bidirectional coupling technology, Kriging surrogate model and particle swarm optimization algorithm to explore the optimal service parameters of the roadheader can provide new ideas for the optimization design of rotary components.

Vibrator baseplate is the key medium for coupling shear wave vibroseis vibrator with earth, while the welding part of baseplate teeth and baseplate is prone to fatigue failure due to complex force under the condition of seismic wave excitation, which leads to low service life of baseplate. In view of the problem that the welding residual stress was not considered in the traditional structure fatigue life analysis method, the stress coupling criterion was established by using the equal strain principle, and the coupling calculation of welding residual stress and working load stress was carried out for the dangerous parts of the baseplate welding seam. Then, based on the modified S-N curve and coupled stress spectrum, the Miner criterion was used to analyze the fatigue life of baseplate under the coupling of welding residual stress and working load stress. The results showed that the fatigue failure life of the baseplate under the coupling of welding residual stress and working load stress was 8.69 a, and the relative error with the actual working life of 8 a was 8.6%. The fatigue life prediction method of vibrator baseplate coupled with welding residual stress has high accuracy and stability, which can provide a new idea and method for the maintenance and optimization of shear wave vibroseis.

In the traditional rolling bearing fault modeling, half-sine function is used to describe the displacement excitation, and the stiffness weakening effect at the fault edge is ignored, which leads to the deviation between the model and the reality. Taking NU306 bearing with local faults as the research object, a new piecewise displacement excitation function was proposed considering the elastic deformation of raceway before and after a fault. The coefficients of the function were determined by finite element analysis method and incorporated into the dynamic model of rolling bearing. The vibration characteristics of bearing under different fault widths using piecewise displacement excitation function and traditional half-sine displacement excitation function were compared and analyzed. The results showed that the piecewise displacement excitation function was more in line with the actual situation, and the obtained vibration signals were more consistent with the experimental results. Additionally, the bearing vibration response curve based on the piecewise displacement excitation function was smoother than that based on the traditional displacement excitation function. The research results provide a certain reference for in-depth study of vibration characteristics of rolling bearings with local faults.

In order to investigate the heat transfer performance of heating pipeline of a heavy-duty diesel engine's lubricant tank during the preheating stage under extremely cold conditions, a test platform for heat transfer performance of the heating pipeline of lubricant tank was constructed. The temperature variation law of the lubricant in the tank during the preheating process was studied, the working parameters such as coolant inlet temperature, volume flow rate and lubricant initial temperature were adjusted, and the effects of different working conditions on the lubricant temperature variation were analyzed. The test results showed that when the lubricant initial temperature was -50 ℃, its high viscosity led to a very uneven temperature distribution inside the tank during preheating with only a few temperature measuring points showing a significant increase. Increasing the inlet temperature and volume flow rate of the coolant both increased the average heat transfer power, especially the increase of coolant inlet temperature had a more significant effect on the increase of average heat transfer power. When the lubricant initial temperature to -40, -30 and -20 °C respectively, the average heat transfer power increased first and then decreased, and when the lubricant initial temperature was -40 ℃, the average heat transfer power was maximum. The research results provide a reference for optimizing the lubricant preheating strategy and improving the structure of heating pipeline of the lubricant tank.

The distributions of pressure field, temperature field and velocity field of gas in cylinder of the piston expander are difficult to obtain by traditional analytical methods. Therefore, the dynamic performance of the double inlet/exhaust piston expander was studied based on the dynamic grid technology of CFD (computational fluid dynamics). Firstly, the unsteady flow of gas in the cylinder of the double inlet/exhaust piston expander was simulated numerically, and the transient distributions of the pressure field, temperature field and velocity field were obtained. Secondly, the output power test platform of the expander was built, and the simulation values and test values of the output power under multiple working conditions were compared. The error between the two was less than 5.5%, which verified the correctness of the simulation method. Finally, the influences of inlet pressure and inlet temperature on the dynamic performance of expander were analyzed through orthogonal experiment. The results showed that after the compressed air entered the expansion cylinder, the temperature of gas increased rapidly at first, and then decreased continuously after the crankshaft angle was 15°. After opening the exhaust valve, the pressure of gas in the cylinder was higher than the ambient pressure and the residual pressure energy could be recovered. Increasing the inlet temperature could effectively improve the dynamic performance of the expander. When the inlet pressure was 0.5 MPa and the inlet temperature increased from 273 K to 333 K, the output power of the expander increased by 19.8% and the gas energy utilization rate increased by 18.3%. Increasing the inlet pressure, the output power of the expander gradually increased, and the gas energy utilization rate gradually decreased. When the inlet temperature was 273 K, and the inlet pressure increased from 0.5 MPa to 2 MPa, the output power of the expander increased from 0.81 kW to 3.76 kW, and the gas energy utilization rate decreased by 15.3%. The research results provide a theoretical basis for the performance optimization of piston expander.