Influence of cable tension history on the monitoring of cable tension using magnetoelastic inductance method

Zhang, Senhua; Zhou, Jianting; Liao, Leng; Liu, Lei

doi:10.1177/1475921720987987

Cited by 15 publications

(8 citation statements)

References 32 publications

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“…The reason is that the receiving coil utilizes the tendon as the iron core to form an iron core inductor. The relationship between the coil inductance and the prestress could be expressed as Equation (6), 29 where L R ( σ ) is the inductance, σ is the prestress, l m is the length of the coil, N R is the coil turns, H R is the magnetic field inside the coil. In Equation (6), A air is the sectional area of the air gap between the coil and the tendon, μ 0 is the vacuum permeability, A iron is the sectional area of the tendon, μ ( σ ) is the magnetic permeability of the tendon, M ( σ ) is the magnetization of the tendon…”

Section: Theory Backgroundmentioning

confidence: 99%

Prestress monitoring for prestress tendons based on the resonance-enhanced magnetoelastic method considering the construction process

Zhang

Xia

Zhou

et al. 2023

Structural Health Monitoring

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Monitoring the prestress of prestressed concrete structures is hard but helpful. The resonance-enhanced magnetoelastic (REME) sensor could measure the stress of steel, but the measurement is influenced by the stress history. Thus, after analyzing the principle of the REME method according to the electric circuit theorem, the construction process and stress history of different prestress tendons were discussed. The prestress monitoring experiment showed that the induced voltage–prestress relationship was influenced by the stress history. To evaluate the prestress, a prestress evaluation method suitable for prestress steel strands was proposed. Using the precise calibration method, the monitoring errors in the construction stage and the prestress loss stage were less than 13.26% and 5.97%. The simplified calibration method reduced the workload of the calibration by 50% while the monitoring error increased by less than 4%. In addition, using the self-calibration method can avoid the influence of the differences in steel strands, leading to higher monitoring accuracy.

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Section: Theory Backgroundmentioning

confidence: 99%

Prestress monitoring for prestress tendons based on the resonance-enhanced magnetoelastic method considering the construction process

Zhang

Xia

Zhou

et al. 2023

Structural Health Monitoring

Self Cite

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“…According to the Joule effect and the magnetization theory of ferromagnetic material, there is a functional relationship between the stress of rebar and the change in magnetic permeability [30,31]. In Equation (1), µ is the permeability of rebar, µ 0 is the vacuum permeability, λ s is the axial deformation constant, M s is the saturation magnetization, K u is the uniaxial magnetic anisotropy constant, H R is the excitation magnetic field, and θ 0 is the angle between the magnetic field and the easy magnetization axis [32].…”

Section: Theorymentioning

confidence: 99%

Working Stress Measurement of Prestressed Rebars Using the Magnetic Resonance Method

et al. 2023

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Prestressed rebars are usually used to apply vertical prestress to concrete to prevent web cracking. The reduction of working stress will affect the durability of the structure. However, the existing working stress detection methods for prestressed rebars still need to be improved. To monitor the working stress of rebars, a magnetic resonance sensor was introduced to carry out experimental research. The correlation between rebar stress and the sensor’s induced voltage was theoretically analyzed using the magnetoelastic effect and magnetic resonance theory. A working stress monitoring method for prestressed rebars based on magnetic resonance was proposed. Working stress monitoring experiments were carried out for 16 mm, 18 mm, and 20 mm diameter rebars. The results showed that the induced voltage peak-to-peak value and the rebar prestress were nonlinearly correlated under different working conditions. Correlations between the characteristic indicators and the rebar working stress were obtained using nonlinear and linear fit. The cubic polynomial segmented fit outperformed the gradient overall linear fit, with the goodness of fit R2 greater than 0.96. The average relative error values of working stress monitoring were less than 5% under different working conditions. This provides a new method for working stress measurement of vertical prestressed rebars.

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“…Te efective feld H e , which has a stress-related term H σ , changes depending on the variation in the mechanical stress in the ferromagnetic material. Moreover, the parameters c, a, α, and others, which were examined in other studies by several researchers [25,29,30], change owing to the residual stress in the ferromagnetic material, making the total magnetization diferent. Terefore, if a steel rod as a ferromagnetic material is under tension, reversible and irreversible magnetization occurs, causing changes in the properties of magnetic hysteresis.…”

Section: Magnetization Of Ferromagnetic Materials Under Stressmentioning

confidence: 99%

Elastomagnetic Sensor-Based Long-Term Tension Monitoring of Prestressed Bridge Member with Temperature Compensation

Park,

Kim,

Jeon

et al. 2023

Structural Control and Health Monitoring

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Continuous monitoring of the prestressed members of a bridge under construction using the free cantilever method (FCM) is crucial for ensuring bridge safety. Temperature-sensitive sensors require special considerations as they may misinterpret the signal and tension. Moreover, the unnecessary and inappropriate use of features obtained from the sensor signal can deteriorate the efficiency of the signal and, therefore, tension analysis. This study proposes a tension estimation method using an embedded elastomagnetic (EM) sensor with a temperature-compensation technique. Changes in the signal due to the tension in the temporary steel rods were analyzed using a full-scale test, and the sensor data were acquired for 15 months via the field application. The temperature effect on the signal could be removed by subtracting the tension from the signal using the thermistor data, reducing the error by 91.99% when considering permeability. Additionally, linear regression (LR) and machine learning (ML) algorithms were adopted to predict the tension. Furthermore, the performances of both algorithms were compared using mean absolute error (MAE) and R2. For the prediction using each feature in magnetic hysteresis, LR surpassed ML and the permeability exhibited the highest prediction performance. Meanwhile, predictions using multiple features were attempted to investigate the applicability of ML. Two cases of prediction were performed using ML: on using all the features and the other using three features excluding coercivity, which showed poor relevance to tension. As a result, the performance of the tension prediction was improved significantly compared to the results obtained by LR. In summary, the obtained results have demonstrated that the utilization of selective features of data with temperature compensation techniques could enhance predictive power.

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Influence of cable tension history on the monitoring of cable tension using magnetoelastic inductance method

Cited by 15 publications

References 32 publications

Prestress monitoring for prestress tendons based on the resonance-enhanced magnetoelastic method considering the construction process

Prestress monitoring for prestress tendons based on the resonance-enhanced magnetoelastic method considering the construction process

Working Stress Measurement of Prestressed Rebars Using the Magnetic Resonance Method

Elastomagnetic Sensor-Based Long-Term Tension Monitoring of Prestressed Bridge Member with Temperature Compensation

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