Elasto-magnetic Sensor Research Articles

Estimation of tension force in tension members using GRU algorithm based on yoke-type elasto-magnetic sensor data

Estimation of tension force in tension members using GRU algorithm based on yoke-type elasto-magnetic sensor data

Prestress Tension Measurement Using a Single Electromagnetic Sensor

Elasto-magnetic sensors are widely used to measure the tensile force of cable structures. Generally, the size of current elasto-magnetic sensors is designed to be large enough to measure the tensile force of the entire cable. Therefore, the tensile force of a single steel strand in cables cannot be measured, which causes some engineering problems, such as that the uniformity of prestress tension and forces within steel cables cannot be determined. In this study, a single-strand elasto-magnetic sensor, called the EM17 sensor, is proposed to detect and monitor the tensile force of single steel strands. EM17 is the smallest sensor developed to date, with an inner diameter of 17 mm. In addition, a series of experiments were conducted to investigate the effects of temperature, position, shielding environment, strand relaxation, strand fatigue and sensor sealing performance on sensor accuracy. The field tests show that the EM17 sensors can accurately measure the tensile force of steel strands. The results show that the uniformity of the prestressed steel strand and the error between measurement and target values are within the range of 5%, which is considered satisfactory.

Residual tensile force estimation method for earth anchor using elasto-magnetic sensing system.

The earth anchor method is used to prevent landslides, and repair and reinforce cut or steep slopes due to its benefits of ease of construction and economic feasibility. However, the loss of anchor force has become a problem, which may cause failure and collapse of slopes when the anchor force drops below the design anchor force. While numerous studies have been conducted to solve this problem, measuring the residual tensile force of existing earth anchors remains a challenge, as prior studies required sensors to be installed inside structural members at the time of construction. Therefore, to address this limitation, an experiment was performed in this study to develop an elasto-magnetic (EM) sensor for measuring tensile force based on the EM effect, which could be installed on externally exposed anchor heads. The commercial software ANSYS Maxwell was used to analyze the optimal sensor design for the experiment. Additionally, a series of tests to measure the tensile force was conducted by fabricating the sensor based on the numerical analysis results. The area of B-H curves measured by developed EM sensor was increased according to the decrease of tensile force. Also, The tensile force estimation equation was derived and verified using measured data. According to the results, the proposed method can be one of the solution for measuring residual tensile force of earth anchor.

Verification of Tensile Force Estimation Method for Temporary Steel Rods of FCM Bridges Based on Area of Magnetic Hysteresis Curve Using Embedded Elasto-Magnetic Sensor.

The free cantilever method (FCM) is a bridge construction method in which the left and right segments are joined in sequence from a pier without using a bottom strut. To support the imbalance of the left and right moments during construction, temporary steel rods, upon which tensile force is applied that cannot be managed after construction, are embedded in the pier. If there is an excessive loss of tensile force applied to the steel rods, the segments can collapse owing to the unbalanced moment, which may cause personal and property damage. Therefore, it is essential to monitor the tensile force in the temporary steel rods to prevent such accidents. In this study, a tensile force estimation method for the temporary steel rods of an FCM bridge using embedded Elasto-Magnetic (EM) sensors was proposed. After the tensile force was applied to the steel rods, the change in tensile force was monitored according to the changing area of a magnetic hysteresis curve, as measured by the embedded EM sensors. To verify the field applicability of the proposed method, the EM sensors were installed in an FCM bridge pier under construction. The three sensors were installed in conjunction with a sheath tube, and the magnetic hysteresis curve was measured over nine months. Temperature data from the measurement period were used to compensate for the error due to daily temperature fluctuations. The estimated tensile force was consistent with an error range of ±4% when compared with the reference value measured by the load cell. Based on the results of this experiment, the applicability of the proposed method was demonstrated.

Field applicability of a machine learning–based tensile force estimation for pre-stressed concrete bridges using an embedded elasto-magnetic sensor

It has been proposed that pre-stressed concrete bridges improve load performance by inducing axial pre-stress using pre-stress tendons. However, the tensile force of the pre-stress tendons could not be managed after construction, although it directly supports the load of the structure. Thus, the tensile force of the pre-stress tendon should be checked for structural health monitoring of pre-stressed concrete bridges. In this study, a machine learning–based tensile force estimation method for a pre-stressed concrete girder is proposed using an embedded elasto-magnetic sensor and machine learning method. The feedforward neural network and radial basis function network were applied to estimate the tensile force of the pre-stress tendon using the area ratio of the magnetic hysteresis curve measured by the embedded elasto-magnetic sensor. The feedforward neural network and radial basis function network were trained using 213 datasets obtained in laboratory experiments, and trained feedforward neural network and radial basis function network were applied to a 50-m real-scale pre-stressed concrete girder test for estimating tensile force. Nine embedded elasto-magnetic sensors were installed on the sheath, and the magnetic hysteresis curves of the pre-stress tendons were measured during tensioning. The area ratio was extracted and inputted to the trained feedforward neural network and radial basis function network to estimate the tensile force. The estimated tensile force was compared with the reference tensile force measured by the load cell. According to the result, the estimated tensile force can represent the actual tensile force of the pre-stress tendon without calibrating tensile force estimation algorithms at the site. In addition, it can measure the actual friction loss by estimating the tensile force at the maximum eccentric part. Based on the results, the proposed method might be a solution for the structural health monitoring of pre-stressed concrete bridges with field applicability.

Development of elasto-magnetic (EM) sensor for monitoring cable tension using an innovative ratio measurement method

The magnetic permeability changes of ferromagnetic materials under elastic stress offer the potential to measure tension based on the inverse magnetostrictive effect. The elasto-magnetic (EM) sensor is the most promising technology for monitoring tension in steel structures. Nevertheless, difference in the device channel or variation of the external wire resistance results in an inaccurate induced voltage variation of the EM sensor in tension measurement. In this paper, the EM sensor for monitoring cable tension using an innovative ratio measurement method was presented. An inductor-resistor model of the excitation system and a transformer model of the sensor system were established to obtain the explicit relationship between the ratio result and the external tension. The experimental results show that the ratio of the integral value of the induced voltage to the excitation current variation is proportional to the external tension, a finding that is consistent with the theoretical derivation. In addition, the simulation analysis and experiment result demonstrate that the ratio measurement method improves sensor performance with the comparison of the traditional induced voltage method. Finally, the EM sensor was applied in the Zhengzhou Olympic Stadium of China. The monitoring results show that the proposed ratio measurement method could accurately measure cable tension.

Development of Embedded EM Sensors for Estimating Tensile Forces of PSC Girder Bridges.

The tensile force of pre-stressed concrete (PSC) girders is the most important factor for managing the stability of PSC bridges. The tensile force is induced using pre-stressing (PS) tendons of a PSC girder. Because the PS tendons are located inside of the PSC girder, the tensile force cannot be measured after construction using conventional NDT (non-destructive testing) methods. To monitor the induced tensile force of a PSC girder, an embedded EM (elasto-magnetic) sensor was proposed in this study. The PS tendons are made of carbon steel, a ferromagnetic material. The magnetic properties of the ferromagnetic specimen are changed according to the induced magnetic field, temperature, and induced stress. Thus, the tensile force of PS tendons can be estimated by measuring their magnetic properties. The EM sensor can measure the magnetic properties of ferromagnetic materials in the form of a B (magnetic density)-H (magnetic force) loop. To measure the B-H loop of a PS tendon in a PSC girder, the EM sensor should be embedded into the PSC girder. The proposed embedded EM sensor can be embedded into a PSC girder as a sheath joint by designing screw threads to connect with the sheath. To confirm the proposed embedded EM sensors, the experimental study was performed using a down-scaled PSC girder model. Two specimens were constructed with embedded EM sensors, and three sensors were installed in each specimen. The embedded EM sensor could measure the B-H loop of PS tendons even if it was located inside concrete, and the area of the B-H loop was proportionally decreased according to the increase in tensile force. According to the results, the proposed method can be used to estimate the tensile force of unrevealed PS tendons.

Study on an innovative self-inductance tension eddy current sensor based on the inverse magnetostrictive effect

PurposeMagnetic permeability variations of ferromagnetic materials under elastic stress offer the potential to monitor tension based on the inverse magnetostrictive effect. The purpose of this paper is to propose an innovative self-inductance tension eddy current sensor to detect tension.Design/methodology/approachThe effectiveness of conventional elasto-magnetic (EM) sensor is limited during signal detection, due to its complex sensor structure, which includes excitation and induction coils. In this paper, a novel self-inductance tension eddy current sensor using a single coil is presented.FindingsThe output signal was analyzed through oscilloscope in the frequency domain and via self-developed data logger in the time domain. Experimental results show the existence of a linear relationship between voltage across the sensor and tension. The sensor sensitivity is dependent on operating conditions, such as current and frequency of the input signal.Practical implicationsThe self-inductance sensor has great potential for replacing conventional EM sensor due to its low cost, simple structure, high precision and good repeatability in tension detection.Originality/valueA spilt sleeve structure provides a higher permeability path to magnetic field lines than a non-sleeve structure, thus reducing the loss of magnetic field. The self-developed data logger improves sensitivity and signal-to-noise ratio of sensor. The novel sensor, as a replacement of the EM sensor, can easily and accurately monitor the tension force.

Improved Method for Elastomagnetic Effect Based Tension Measurement Using Harmonic Analysis Techniques

An improved method for elastomagnetic(EM) effect-based tension measurement is presented using harmonic analysis technique(HAT). The magnitudes of odd harmonics of EM signals are extracted to calculate the total harmonic distortion(THD), which is commonly used in electrical engineering area to represent the extent of the distortion of sinusoidal signals. The value of THD is applied for tension characterization. The EM signals are acquired by a EM sensor which is made of two coaxial solenoid coils, and then are alternatively processed in time and frequency domain. The advantages of the two signal processing methods are compared to find that the HAT is much more succinct. The determined characteristic parameters of calibration equation, such as linear regression and slope, tend to be stable as the number of orders for statistics increases. Moreover, the obtained calibration equation has better parameters, for example, the linear regression is larger than 0.996. The mentioned techniques are then applied for measuring the tension of high voltage transmission line, the experimental results testify that there is a significant linear relationship between THD and the applied tension. When the value of THD is equal to 1, the relative errors of estimated forces, which are calculated from calibration equations corresponding to various statistical harmonic orders, are less than 3%(a maximum of 2.4%for seven-wire steel strand and a maximum of 2.9% for high voltage transmission line). This study provides a new characterization and data processing method for EM-based tension measurement technology.

Smart elasto-magneto-electric (EME) sensors for stress monitoring of steel structures in railway infrastructures

Steel structures are widely used in railway infrastructures. Their stress state is the most important determinant of the safety of these structures. The elasto-magnetic (EM) sensor is the most promising for stress monitoring of in-service steel structures. Nevertheless, the necessity of magnetic excitation to saturation due to the use of a secondary coil for signal detection, keeps from its engineering application. In this paper, a smart elasto-magneto-electric (EME) sensor using magneto-electric (ME) sensing units to take the place of the secondary coil has been exploited for the first time. The ME sensing unit is made of ME laminated composites, which has an ultrahigh ME voltage coefficient and can measure the magnetic induction simply and precisely. Theoretical analysis and characterization experiments firstly conducted on the ME laminated composites showed that the ME sensing units can be applied in the EM sensor for improved performance in stress monitoring. A tension test of a steel bar was carried out to characterize our smart EME sensor and the results showed high accuracy and sensitivity. The present smart EME sensor is a promising tool for stress monitoring of steel structures in railway and other civil infrastructures.

Mechanical vibration sensor based on elastomagnetic composite

A mechanical vibration sensor based on a novel elastomagnetic composite made of magnetic microparticles uniformly dispersed in an elastic non-magnetic matrix is presented. A theoretical model predicting a linear behaviour of the sensor response with the vibration frequency and amplitude is reported. The obtained experimental results are in agreement with the model predictions for magnetic particle volume content lower than 15%. The ability of this kind of sensor to work at low frequencies, where other devices present a lack of reliability, is a very interesting characteristic of this elastomagnetic sensor.

Utilization of Neural Networks for Error Reduction of Elastomagnetic Sensors

This paper deals with an elastomagnetic sensor of a pressure output metrological parameter improving to achieve linear sensor output. The designed solution is based on using neural networks as a universal approximator that enables conversion from sensor output to measured force and suppresses error.

EMセンサを用いたPC鋼材の引張力モニタリング実験

Elasto-Magnetic (EM) actual-stress measurement method by utilizing the sensitivity of incremental magnetic permeability due to stressc hangeh as been beingd eveloped Previously, it has been proved that E M measurement method enable to measure actual-stress of steel wire, PC bar and PC strand contactlessly without destroyingt heir polyethylenec overing sheath. Furthermore monitoring tensile force of PC tendon is the most important issue in PC structure maintenance management. Therefore, in this paper, in order to grasp the reliability of EM sensor for field-application purpose, a test of tensile force monitoring on PC tendon of outercable PC beam by utilizing EM sensor was conducted As the result of the test, it is conformed that EM stress measurement technology can provide adequate accuracy and reliability to monitor tensile orce of PC tendon duringa life-cycle of PC structur