The track line suffers from track irregularity, subgrade settlement, rail surface defects and gauge distortion. Measuring the track geometry quality plays an important role for rail administrations to safe operation and track maintenance. In order to meet the requirements of track daily inspection, this paper describes a comprehensive detection system for the track geometry, which is designed by four cameras, an inclinometer and inertial measurement unit. Moreover, the detection system has the characteristics of simple structure, automatic detection and multiple measurement parameters. Firstly, to measure track alignment and irregularity, a multi-sensing calibration method is established to fuse visual sensors and inertial sensors. An accelerometer and a Kalman filter are used to eliminate accumulated unrealistic drifts of accelerometer and gyroscope. Secondly, to measure the rail surface defects and gauge, the model of laser and machine vision is deduced to obtain coordinate values in a unified coordinate system and an improved iterative closest point method is developed to improve the matching accuracy. Finally, a series of experiments are carried out to validate the measuring performance. The results indicate that the proposed method can accurately measure the track geometry, with the maximum deviations of track alignment, track irregularity, rail defects and gauge are less than 0.5mm, 0.4mm, 0.3mm and 0.1mm, respectively. The detection system is not only simple in structure but also has multiple detection parameters, which is especially suitable for track daily maintenance.

Permanent magnet wall-climbing robots are widely used in the maintenance of tanks in the petrochemical industry and the overhaul of large-pressure pipelines in the hydropower industry. One of the difficulties is to achieve the safe and reliable adsorption of wall-climbing robots. Based on the Halbach array, a double-layer superposition magnetic circuit magnetization method is designed in this paper. Under the same constraints, the adsorption force of the permanent magnetic chuck is increased by at least $8\%$ compared with the traditional magnetic circuit design method. Under the working air gap of 1∼9 mm, the average magnetic energy utilization rate is increased by at least $16.46\%$. This approach not only improves the magnetic energy utilization of the permanent magnetic chuck but also improves the adsorption safety of the wall-climbing robot.

This paper establishes a matrix displacement model and an improved dynamic model for the static and dynamic performances analysis for a kind of bridge-type displacement amplification mechanism with distributed-compliance, which has better performances than traditional lumped-compliance bridge-type mechanisms. In the matrix displacement model, the stiffness matrix for two rigid bodies connected by flexures is first obtained by regarding the displacements and the forces on two mass centers of the rigid bodies as the node displacements and node forces. By extending and superimposing each elemental stiffness matrix, the global stiffness matrix for the flexure mechanism can be obtained to calculate the displacement amplification ratio and input stiffness of the bridge-type mechanism. In the improved dynamic model, in order to establish the Lagrangian dynamic model more accurately, the deflectional, axial, and rotational velocities of any point on the beam flexure are calculated by solving the derivatives of the deformation curves of beam flexures versus time to obtain the expression of the kinetic energy in the vibrating beams. On this basis, the three-degree-of-freedom vibration differential equation for the bridge-type mechanism is established by using the Lagrange method, and the natural frequency in the working direction is obtained accurately. The presented models are compared with the finite element analysis, and experiments for two case studies of the bridge-type distributed-compliance mechanism are presented. The comparisons results demonstrate the high prediction accuracy of the improved dynamic model.

This paper introduces a two-tier feedback control law for the path tracking of a mobile robot equipped with N on-axle trailers. Initially, through a recursive design process, the curvature-tracking challenge is converted into stabilizing the joint angles at predefined reference values. This design approach is straightforward and can be easily extended to configurations with multiple trailers. Using input-to-state stability analysis, we demonstrate the asymptotic stability of the closed-loop system, which is structured in cascade form. Furthermore, we reformulate the path-tracking problem as a curvature-planning challenge and propose an algorithm to determine the desired curvature for the tail trailer. The simulation results validate the effectiveness of this novel algorithm in truck-trailer systems.

As an important transmission component of industrial robots, the harmonic reducer determines the positioning accuracy, bearing capacity and service life of the robot end-effector. Predicting the performance can grasp the working status in advance and avoid major losses caused by uncertain factors such as component damage. The current paper focuses on a harmonic reducer performance prediction algorithm based on Multivariate State Estimation Technique (MSET) and LargeVis dimensionality reduction. Firstly, an accelerated life test platform is designed to collect multi-dimensional parameters that can characterize the operating state of the harmonic reducer throughout the life cycle. Afterwards, as far as the MSET method is concerned, the fault warning threshold is set according to the residual between the constructed memory matrix of the health state data and the actual observed value. Finally, utilizing LargeVis to reduce the dimensionality of multi-dimensional features, combining with Mahalanobis distance to construct a health index degradation model, and then selecting Long Short-Term Memory (LSTM) network to predict the downward trend of the harmonic reducer. The analysis of the accelerated life test data of the harmonic reducer demonstrates that the proposed method can send out the fault warning signal 18 minutes in advance in the sample with a life of 5.7 hours, and has a strong ability to predict the degradation trend of the harmonic reducer.

In this paper, a long-stroke parallel compliant tip-tilt-piston micropositioning stage driven by voice coil motors (VCMs) is proposed. The stage is equipped with three sets of driving arms, which include a spherical hinge, VCM, and parallelogram guide mechanism, evenly spaced at 120° intervals. The spherical hinge is composed of orthogonal leaf-spring beams, and the VCM is embedded into the parallelogram mechanism to form a compact design. The compliance matrix method and the geometric method facilitated the determination of compliance in all six degree-of-freedom directions of the spherical hinge and the derivation of kinematic equations for decoupling the motion of the stage. In addition, finite element analysis was utilized to determine the maximum stroke and stress of the stage. To validate the proposed design, a stage prototype was constructed and subjected to experimental testing. Furthermore, a feedback controller was designed, integrating proportional integral controller, notch filter, and sliding mode controller feedforward. The experimental results indicate that the stage can achieve a long stroke of ±50.75 mrad × ±44.2 mrad × ±4.425 mm, with the natural frequencies in the three-axis direction of 22.3 × 25.5 × 25.5 Hz3. In addition, the maximum relative tracking error was maintained below 5.25%, highlighting the effectiveness of the control technique in achieving a high tracking performance.