Cable tension monitoring is vital for the health monitoring of cable-stayed bridges. During the service of bridges, cable tension fluctuates rather than monotonously changes. However, existing research works pay little attention to the influence of tension history. In this article, the influence of the tension history on the monitoring of cable tension was studied. To guide the experiment, the magnetization theory of ferromagnetic materials and the electromagnetic induction principle were combined to analyze the theory of the magnetoelastic inductance method. The magnetoelastic inductance method characterized cable tension by sensor inductance. Based on the theoretical analysis, tension monitoring experiments were carried out to figure out the influences of design tension and tension variation. Experimental results showed the design tension and the tension variation influenced the relationship between the inductance and the tension. To monitor the fluctuating tension, a secant method was proposed. When the tension changed less than 30% of the design tension, the tension can be ascertained by the secant method. The experimental results demonstrated that the influence of the tension history should be considered when the design tension was different or the tension variation was large. Besides, the influence of the tension history analyzed in this article is suitable for other tension monitoring methods based on the magnetic properties of ferromagnetic materials.

Cable tension monitoring is important to control the structural performance variation of cable-supported structures. Based on the elasto-magnetic effect and the self-induction phenomenon, a new non-destructive evaluation method was proposed for cable tension monitoring. The method was called the elasto-magnetic induction (EMI) method. By analyzing the working mechanism of the EMI method, a set of cable tension monitoring systems was presented. The primary coil and the induction unit of the traditional elasto-magnetic (EM) sensor were simplified into a self-induction coil. A numerical analysis was conducted to prove the validity of the EMI method. Experimental verification of the steel cable specimens was conducted to validate the feasibility of the EMI method. To process the tension monitoring, data processing and tension calculation methods were proposed. The results of the experimental verification indicated that different cables of the same batch can be calibrated by one proper equation. The results of the numerical analysis and the experimental verification demonstrated that the cable tension can be monitored both at the tension-applying stage and the tension-loss stage. The proposed EMI method and the given monitoring system are feasible to monitor the cable tension with high sensitivity, fast response, and easy installation.

In an actual structure, the arrangement of steel bars is complicated, there are many factors affecting the corrosion of steel bars, and these factors affect each other. However, accurately reflecting the corrosion of steel bars in actual engineering through theoretical calculations is difficult. Besides, it is impossible to detect and evaluate steel bars rust completely and accurately. This article is based on spontaneous magnetic leakage detection technology and adopts the method of stage corrosion and scanning along the reinforcing bar. Based on spontaneous magnetic flux leakage detection technology, the linear change rate of the tangential component curve of the magnetic flux leakage signal generated after the corrosion of a steel bar is studied, and a comparison is made between the steel bar coated concrete samples with different steel bar diameters. In this paper, the “origin of magnetic flux leakage signal” is defined as a reference point, which is convenient for effectively comparing the magnetic signal curves under all operating conditions. Besides, the “rust-magnetic fluctuation parameter” is proposed to accurately reflect the sudden change of leakage magnetic field caused by disconnection due to the corrosion of a steel bar. A new data processing method is provided for the non-destructive testing of steel corrosion using the spontaneous magnetic flux leakage effect, which can effectively reduce the influence of steel bar diameter on magnetic flux leakage signal and improve the precision of non-destructive testing technology of steel bar corrosion using the metal magnetic memory effect.

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.

The internal rebar corrosion of reinforced concrete (RC) structures harm the bearing capacity and durability of structures. Existing methods can measure rebar corrosion but are unsuitable for RC structures. Given this, the self-magnetic flux leakage (SMFL) field of V-shaped rebar corrosion damage was analyzed according to the magnetic dipole model, and the parameter K was proposed to characterize the corrosion degree. Using the naive Bayes algorithm, the SMFL method and the rust spot area analysis method were correlated to propose a rebar corrosion detection method. A corrosion detection experiment was conducted on RC specimens. The results showed that the parameter K was linearly correlated with the maximum cross-sectional rust loss rate η . Using the parameter K to evaluate the rust degree, the accuracy of rebar rust classification was 70%. After introducing the rust spot area ratio S as a supplementary parameter, the accuracy of rebar rust classification increased by 12.5% to 82.5%. This indicates that the proposed method could quantitatively detect the corrosion of the rebars within the concrete.