Cable Tension Estimation Research Articles

Remote estimation of cable tension using catenary theory and point clouds obtained by terrestrial laser scanning

This study addressed the structural health monitoring of civil engineering cable structures, in which single cable tension is the key parameter influencing safe and intended behaviour. Traditional methods for monitoring the tension force in a cable are labour-intensive and require direct interaction with the cable. In contrast, the proposed approach provides a remote and rapid assessment of the tension force in the cables of engineering structures using only the shape of the cable. First, a terrestrial laser scanner was used to acquire a point cloud of the cable geometry from a distance. Catenary theory was subsequently applied to the point cloud data to calculate the theoretical tensile force in the observed cable. When the results were compared with those obtained through conventional direct measurements using a dynamometer, the differences were negligible. The proposed approach was subsequently demonstrated on the actual in-service overhead contact lines of a tram system. The results indicated that the precision of the proposed approach is highly dependent on the accuracy of the data describing the physical properties of the cable (cable linear mass). Thus, the proposed approach was proven to be precise, reliable, and rapid, and directions for future research were discussed accordingly.

A Tension Sensor Array for Cable-Driven Surgical Robots.

Tendon-sheath structures are commonly utilized to drive surgical robots due to their compact size, flexibility, and straightforward controllability. However, long-distance cable tension estimation poses a significant challenge due to its frictional characteristics affected by complicated factors. This paper proposes a miniature tension sensor array for an endoscopic cable-driven parallel robot, aiming to integrate sensors into the distal end of long and flexible surgical instruments to sense cable tension and alleviate friction between the tendon and sheath. The sensor array, mounted at the distal end of the robot, boasts the advantages of a small size (16 mm outer diameter) and reduced frictional impact. A force compensation strategy was presented and verified on a platform with a single cable and subsequently implemented on the robot. The robot demonstrated good performance in a series of palpation tests, exhibiting a 0.173 N average error in force estimation and a 0.213 N root-mean-square error. In blind tests, all ten participants were able to differentiate between silicone pads with varying hardness through force feedback provided by a haptic device.

Bridge cable tension estimation using the vibration method

Accurate cable tension assessment is essential for cable-stayed bridges in the construction and health monitoring phases. Accordingly, several approaches, have been presented over the last decades. The vibration method has become one of the most relevant methods. Throughout the years, several practical formulas, and approaches for cable tension estimation from measured natural frequencies have been presented. The paper demonstrates in-situ measurements of natural frequencies of cables and subsequent cable tension calculation, on a cable-stayed bridge. Problem of unknown bending stiffness was solved by using multiple frequencies. On the other hand, problem of unknown boundary stiffness is much more difficult to solve. Therefore, fixed and hinged ends were considered as two boundary situations. Moreover, the design of the bridge allows to measure the tension of each individual rope. This allows the unique comparison of the Cable tensions and individual rope tensions. Cable tension was also estimated as a sum of rope tensions what allows to verify the cable tension results. The measurement of individual ropes allowed the authors to highlight the most stressed ropes. The paper also provides a unique insight to the distribution and variation in the rope tension within the cables. Possible causes of tension differences in ropes and differences between the rope and cable tensions are discussed.

Cable tension estimation of cable-stayed bridge using vision-based modal identification

In this study, it is aimed to estimate the cable tensions of the Komurhan Cable-Stayed Bridge using vision-based modal identification and to verify the vision-based modal identification by comparing cable tensions with the existing monitoring system. First, cable tensions were determined by a lift-off testing and estimated using the vibration response under seismic events recorded by existing acceleration sensors on the bridge. In these methods, only 8 of 42 cables are continuously monitored with the existing monitoring system. Then, all cable tensions were estimated by vision-based modal identification using video recordings. These cable tensions gave consistent results compared to the 8 cables in the existing monitoring system. Thus, vision-based modal identification has been verified. With this method, multiple cable tensions can be simultaneously estimated from a single video recording without requiring access to the structure.

Noncontact cable tension estimation using edge recognition technology based on convolutional network

The cable is the main load-bearing component of cable-stayed, suspension, and tied-arch bridges. The tension of the cable is crucial to the bridge's overall safety. Therefore, achieving an accurate and rapidcable tension estimation is of great practical importance. Currently, the method of estimating cable tension based on image processing technology avoids the disadvantages of conventional estimation methods, such as high cost, difficult sensor installation, and potential structural damage. However, for estimating cable tension based on image processing technology, a complex optical background may reduce the accuracy and stability of cable tension estimation. A method for estimating cable tension based on a deep convolutional network is proposed to solve the problem. The convolutional network is initially used to identify cable edges. Second, analyzing the edge pixels' motion identifies the cable's fundamental frequency. Finally, the cable tension is estimated using the correlation between fundamental frequency and cable tension. A field experiment was conducted on cable-stayed and tied-arch bridges in Chengdu to validate the proposed method's applicability and accuracy. The results of the experiments indicate that the edge detection effect of the proposed method is demonstrably superior to that of the Canny algorithm under various optical backgrounds and that the cable tension relative difference between the proposed method and the conventional method based on accelerometer is within 5%.

Extensive Field Validations and Corresponding Numerical Investigations for a Cable Tension Estimation Method Based on Local Vibration Measurements

To assess the applicability of the tension estimation method using local vibration measurements in a thorough manner, this research work is devoted to systematically investigate the appropriate covering ranges of measurements for different cables. Four cables of three cable-stayed bridges are deliberately chosen to cover a wide range of the cable slenderness parameter. Numerical analyses with finite element models and field validations with real measurements are conducted for these stay cables to demonstrate that the covering range of local measurements can be undoubtedly reduced with the increase of cable slenderness. For a relatively short cable with the slenderness parameter at the order of 4000, the adoption of 1/3 coverage is sufficient to keep a high-level accuracy with at most 1% of error. Besides, 1/4, 1/6, and 1/7 coverages are found adequate to maintain the same level of accuracy for longer cables with the slenderness parameter at the orders of 30000, 55000, and 80000, respectively. With the solid validations presented in the current study, the covering range of the cable for this simplified method employing local vibration measurements can be confidently reduced to greatly alleviate the expense and hard work of sensor installation near the high end.

Cable Tension Estimation For The Cable-stayed Bridge With Hysteresis Damping

Damping materials are popular applications for almost vibration structures; however, they have rarely been investigated in different practical experiments. That is why new approaches would be necessary to assess these problems. In this study, the mathematical model of cable is remarkable in assessing the cable tension of the cable-stayed bridge. A differential vibration equation is used to derive the cable tension considering material damping as the hysteresis phenomenon. The experimental measurements of cable vibration at Phu My Bridge are calculated to find approximate damping ratio and tension values. The selected damping model with experimental data has been collected to derive an efficient method for evaluating structure status. These values are used to assess damping efficiently in the cable-stayed bridge structures. The results presented in this paper shall help elucidate experimental procedures for characterizing damping materials. The proposed procedures are used not only for the cable-stayed bridge but also for generally cable-stayed structures.

A Novel Approach for Cable Tension Monitoring Based on Mode Shape Identification

Estimation and monitoring of cable tension is of great significance in the structural assessment of cable-supported bridges. For short cables, the traditional cable tension identification method via frequency measurement has large errors due to the influence of complex boundaries, which affect the accuracy of estimation. A new cable tension estimation method based on mode shape identification with a multiple sensor arrangement on the cable can take the influence of boundary conditions into account and its accuracy has been verified. However, it requires more sensors compared to the traditional frequency-based method, which will significantly increase the cost of long-term monitoring in practice. Therefore, a novel approach for cable tension monitoring considering both cost and accuracy is further proposed in this study. The approach adopts multiple sensors to measure the influence of boundary conditions. Then, only a single sensor is required for long-term monitoring of the cable. In this paper, an analytical model of the cable is firstly established. The influence of boundary conditions is calculated, which ensures the accuracy of mode shape identification. Furthermore, a field experiment is carried out to verify the effectiveness of the new approach. The results have demonstrated the effectiveness and accurateness of the proposed method in long-term short cable tension monitoring.

A convenient cable tension estimation method simply based on local vibration measurements to fit partial mode shapes

To apply the tension estimation method based on effective vibration lengths, it has been clarified that the installation of at least one sensor near the high end of a stay cable or a suspender of arch bridge is necessary for attaining good accuracy. Efforts are made in this research to release such an undesirable requirement that may greatly hinder popular applications of this method. re-examination of formulations first reveals that the half-wavelength, rather than the whole effective vibration length, of each considered mode is actually needed in the mode shape based method. Therefore, cable tension estimation simply using local vibration measurements to fit partial mode shapes is a viable alternative as long as the accuracy in determining the half-wavelengths of all the chosen modes can be ensured. Numerical analyses with the finite element models for two stay cables are then conducted to investigate the appropriate covering range of local measurements and the preferred choice of modes. Following those guidelines, the experimental results with a pre-stressed strand are further analyzed to demonstrate that excellent accuracy in tension estimation for the experimental strand with slenderness similar to a short stay cable can be achieved when 1/2 and 1/3 covering ranges are adopted. Finally, by taking vibration measurements on a real stay cable with a length of 100 m, the accuracy for the tension value estimated from 1/4 covering range is persuasively validated with a difference less than 1 % compared to that estimated from full coverage.

Stay cable tension estimation of cable‐stayed bridge under limited information on cable properties using artificial neural networks

Stay cable tension estimation of cable‐stayed bridge under limited information on cable properties using artificial neural networks

Instantaneous identification of tension in bridge cables using synchrosqueezing wave-packet transform of acceleration responses

Real-time monitoring of cable tension is essential in detecting damage and assessing the service performance of bridges. Vibration frequency-based methods for cable tension identification have been increasingly investigated in bridge engineering over the last decade. However, cable tension estimation using vibration frequency-based methods can only obtain the average cable tension over a specified time interval. Therefore, identification of instantaneous variation of cable tension still remains to be a pending issue. To tackle this problem, this study proposes an algorithm defined as Synchrosqueezing Wave-packet-based Instantaneous Frequency Tracking (SWIFT) to identify the instantaneous change of cable tension by monitoring its acceleration responses. The proposed algorithm can extract the time-varying instantaneous frequency of the tested cable and further identify the variation of instantaneous cable tension by time-frequency analysis of the transversal motion. Moreover, the identification accuracy and noise robustness are numerically verified using a synthetic time-varying multi-frequencies signal. Finally, experimental validation is conducted on a prototype cable and an actual cable of the Sutong Yangtze River bridge, respectively. The theoretical, numerical, and experimental results show that the proposed method can precisely identify instantaneous cable tension under noisy conditions.

Computer vision‐based real‐time cable tension estimation algorithm using complexity pursuit from video and its application in Fred‐Hartman cable‐stayed bridge

Computer vision‐based real‐time cable tension estimation algorithm using complexity pursuit from video and its application in Fred‐Hartman cable‐stayed bridge

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.

Real-time cable tension estimation from acceleration measurements using wireless sensors with packet data losses: analytics with compressive sensing and sparse component analysis

Real-time cable tension estimation from acceleration measurements using wireless sensors with packet data losses: analytics with compressive sensing and sparse component analysis

Computer vision‐based real‐time cable tension estimation in Dubrovnik cable‐stayed bridge using moving handheld video camera

Cables are essential components of the cable-stayed bridges as they serve as the main load-bearing component. Hence, continuous monitoring of such cables becomes necessary as they are vulnerable to the fatigue damage induced by dynamic loads. Sensors are attached to the cables to examine the health of the cables; however, these contact-based sensors can malfunction in harsh weather condition, which makes impossible to estimate the cable health in such unfavorable condition. Therefore, in this paper, we propose a completely noncontact video-based stay-cable tension measurement technique where the video is recorded using a moving handheld camera at a significant distance from the structure itself. Here, the cable tension is determined from vibration-based measurement, but the vibration of the cable recorded in the video includes the true vibration of the cable along with the camera motion. Hence, we amalgamated a series of image processing techniques to nullify the camera movement. First, we detect the camera movement based on the movement of the bridge deck and pylon, which are fixed objects, using Kanade–Lucas–Tomasi (KLT) feature tracking algorithm. Then we nullify the camera movement by using the affine transformation matrix obtained by random sample consensus (RANSAC) algorithm. Subsequently from the steady video, the cable motions are estimated using the phase-based motion estimation technique. From the time history of the cable vibration, real-time frequency variations are estimated using Short-Time Fourier Transform (STFT). Finally, the real-time tension is determined from this dominant frequency variation history using the taut-string theory. This paper shows the significant potential of camera-based sensing techniques in structural health monitoring as the mean estimated tension and the design cable tension are found to be comparable.

Dynamic Modeling and State Estimation of Cable-Conduit Actuation During Interaction With Nonpassive Environments

Remote actuation solutions such as cable-conduit transmissions are beneficial in wearable robotics to reduce dynamic loading on distal joints. However, these systems often introduce high reflected impedance or require rigid sensors for force control that hinder their integration in wearables. Low impedance and ease of integration could be both obtained by combining distributed cable strain sensing with dynamic modeling to estimate output force and position. In this article, we present a new computational model to analyze the dynamics of cable-conduit systems. The model features bidirectional propagation of motion within the transmission, which allows for simulation of human-interacting systems, where either or both the human and the robot can be force or position sources. Moreover, we present a new method for rapidly solving for the system of equations based on iterative linearization of the system of nonlinear equations. The model and the solution method are validated in a physical prototype through experiments involving physical interaction with a human subject. Finally, we develop methods for model-based estimation of cable tension given measurements from multiple noisy strain sensors embedded in the transmission, and quantify the accuracy achievable via different methods as a function of the number and location of sensors. Results demonstrate that the model accurately predicts behavior observed in the prototype. Moreover, the newly developed iterative linearization solution method allows a 100-fold increase of computation speed compared to a standard solver. Finally, we demonstrate that cable tension can be estimated with increasing accuracy when increasing the number of sensors, but accuracy decreases if the output portion of the transmission is not instrumented.

Mode shape–aided cable force determination using digital image correlation

Assuming the distance between two nodal points of a specific cable vibration mode as the effective length of a pinned–pinned cable, mode shape–aided cable tension estimation methods are employed to estimate the cable force. This article proposes a framework based on digital image correlation technique for remote measurement of the dynamic displacement time history of cables in cable structures. Frequency domain decomposition technique is then used to extract the cable natural frequencies and mode shapes. Identified cable mode shapes are used along with a tensioned pinned–pinned cable model to estimate the cable force. Accuracy of the proposed methodology is investigated using the experimental data coming from a laboratory-scale test setup and hanger cables of a real-world arch bridge.

Development of Artificial Neural Network Model for Estimation of Cable Tension of Cable-Stayed Bridge

Development of Artificial Neural Network Model for Estimation of Cable Tension of Cable-Stayed Bridge

Cable Tension Estimation for Suspen-Dome Structures Based on Numerical Method

Suspen-dome structures have been widely adopted due to their superiority over traditional structures. Cable condition is crucial to the safety of suspen-dome structures, especially the magnitude of cable force. However, thus far, investigations on estimating the tension in this type of structure remain lacking. In this study, double-element method was initially developed to simulate cables, and its accuracy was validated. Tension compensation method was adopted to ensure that the cable force is equal to the designed value. Then, transient analysis was conducted based on an actual suspen-dome structure. The dynamic responses derived based on the overall structures and the simplified models were compared, and the reliability of the simplified models was validated. Finally, parametrical analysis was conducted to investigate the influence of support stiffness and cable-bending stiffness on the fundamental frequency of cables. A cable tension estimation program, which was suitable for suspen-dome structures, was updated. Results indicate that vibration method can maintain good accuracy when used in suspen-dome structures.

Vibration-based cable condition assessment: A novel application of neural networks

Vibration-based cable tension estimation methods demand complex computations especially when usage of comprehensive cable models is required. Avoiding mathematical calculations, this paper proposes a simple novel framework to estimate the cable tension based on Artificial Neural Networks (ANNs). Employing a comprehensive cable model, a set of data including cable length, cable mass per unit length, cable axial stiffness, cable bending stiffness, cable tension and the corresponding cable natural frequencies is generated for training, validation, and testing of the ANNs. The acquired ANNs are then used to estimate the cable tensions in new Ironton-Russell Bridge and the results are compared against the cable tensions directly measured by lift-off test. It will be shown that for new Ironton-Russell Bridge, using cable length, cable mass per unit length, cable axial stiffness, and first two cable natural frequencies as input features to ANNs, the cable tensions can be accurately estimated.