Dynamic and Wrench-Feasible Workspace Analysis of a Cable-Driven Parallel Robot Considering a Nonlinear Cable Tension Model

Cable-driven parallel robots (CDPRs) have several advantages and have been widely used in many industrial fields, especially industrial applications that require high dynamics, high payload capacity, and a large workspace. In this study, a design model for a CDPR system was proposed, and kinematic and dynamic modeling of the system was performed. Experiments were carried out to identify the dynamic modulus of elastic cables based on the dynamic mechanical analysis (DMA) method. A modified kinematic equation considering cable nonlinear tension was developed to determine the optimal cable tension at each position of the end-effector, and the wrench-feasible workspace was analyzed at various motion accelerations. The simulation results show that the proposed CDPR system obtains a large workspace, and the overall workspace is satisfactory and unrestricted for moving ranges in directions limited by the X-axis and the Y-axis from −0.3 to 0.3 m and by the Z-axis from 0.1 to 0.7 m. The overall workspace was found to depend on the condition of acceleration as well as the moving ranges limited by the end-effector. With an increase in external acceleration, the cable tension distribution increased and reached a maximum in the case of 100 m/s2.

Self-Localization of Tethered Drones without a Cable Force Sensor in GPS-Denied Environments

This paper considers the self-localization of a tethered drone without using a cable-tension force sensor in GPS-denied environments. The original problem is converted to a state-estimation problem, where the cable-tension force and the three-dimensional position of the drone with respect to a ground platform are estimated using an extended Kalman filter (EKF). The proposed approach uses the data reported by the onboard electric motors (i.e., the pulse width modulation (PWM) signals), accelerometers, gyroscopes, and altimeter, embedded in the commercial-of-the-shelf (COTS) inertial measurement units (IMU). A system-identification experiment was conducted to determine the model that computes the drone thrust force using the PWM signals. The proposed approach was compared with an existing work that assumes known cable-tension force. Simulation results show that the proposed approach produces estimates with less than 0.3-m errors when the actual cable-tension force is greater than 1 N.

Damage Identification in Hangers of Through-Arch Bridges Using Static Deflection Difference at the Anchorage Point

This study proposes a new damage identification method for hangers of arch bridges using the static deflection difference at the anchorage point of the hanger and the tie-beam. The relationship between the ratio of cable tension loss and the deflection difference at the anchorage point is studied. For the first time, the deflection difference influence matrix for hanger damage identification is defined. The static deflection change parameter is formulated as a function of the deflection difference influence matrix and the ratio of cable tension loss. The study shows that the percentage of cable tension loss can be obtained from the changes in static deflection at the anchorage point and the deflection difference influence matrix. Therefore, by observing a plot of the ratio of cable tension loss, the damage locations can be identified conveniently. Numerical and laboratory studies show that this method can accurately locate the damaged hanger of through-arch bridges under various scenarios. The proposed damage detection method has a clear theoretical base and is simple to operate, and it is suitable for practical engineering.

Stability sensitivity for a cable-based coal–gangue picking robot based on grey relational analysis

This article aims to establish the relationship between the position and cable tension influencing factors and the stability, and propose a method for quantitative stability sensitivity assessment for a cable-based coal–gangue picking robot. Firstly, a structural stability measure approach is proposed for the cable-based coal–gangue picking robot. Secondly, a stability sensitivity analysis model is developed to investigate the stability sensitivity on the selected influencing factors based on the grey relational degree, where the influencing degree of each factor on the stability for the cable-based coal–gangue picking robot is explored with grey relational analysis. At last, a numerical study is carried out to demonstrate the stability measure approach and stability sensitivity analysis model for the cable-based coal–gangue picking robot was scientific and reasonable, where the end-grab position set which the robot can meet the predetermined stability requirements is obtained. And meanwhile, the correlation of each influencing factor on the stability for the robot is calculated. And the stability sensitivity simulation results show that (1) the correlation of the seven influencing factors on the stability are, in a descending order, cable tension T 2 > cable tension T 4 > cable tension T 3 > cable tension T 1 > z-direction displacement of the end-grab > x-direction displacement > y-direction displacement; (2) among the influencing factors, the cable tensions have greater influence on the stability of coal–gangue picking robot, and it is followed by the z-direction displacement of the end-grab, while y-direction displacement is found to have the minimal influence. This article provides a guiding direction for robust design of the sorting trajectory planning and control of the coal–gangue picking robots.

Fully Automated and Robust Cable Tension Estimation of Wireless Sensor Networks System

Accurate estimation of cable tension is crucial for the structural health monitoring of cable-supported structures. Identifying the cable’s force from its vibration data is probably the most widely adopted method of cable tension estimation. According to string theory, the accuracy of estimated cable tension is highly related to identified modal parameters including natural frequencies and frequency order. To alleviate the factors that impact the accuracy of modal parameters when using the peak-picking method in wireless sensor networks, a fully automated and robust identifying method is proposed in this paper. This novel method was implemented on the Xnode wireless sensor system and validated with the data obtained from Jindo Bridge. The experiment results indicate that, through this method, the wireless sensor is able to distinguish the cognizable power spectrum, extract the peaks, eliminate false frequencies and determine frequency orders automatically to estimate cable tension force without any manual intervention or preprocessing. Meanwhile, the results of natural frequencies, corresponding orders and cable tension force obtained from the Xnode system show excellent agreement with the results obtained using the Matlab program method. This demonstrates the effectiveness and reliability of the Xnode estimation system. Furthermore, this method is also appropriate for other high-performance wireless sensor network systems to realize self-identification of cable in long-term monitoring.