CN-122017182-A - Guided wave-magnetic leakage composite intelligent detection equipment and method for bridge cable damage detection

CN122017182ACN 122017182 ACN122017182 ACN 122017182ACN-122017182-A

Abstract

The invention relates to the field of bridge detection and structural health monitoring, and provides a guided wave-magnetic leakage composite intelligent detection device and method for bridge cable damage detection. The equipment adopts split modular design and consists of a climbing module, a data acquisition module and a calculation control module. The climbing module realizes stable climbing of the whole equipment on the surface of the cable, the data acquisition module integrates the magnetic leakage detection unit and the magnetostriction guided wave detection unit to form a composite detection device, and the calculation control module is embedded with a data acquisition card, an embedded processor and the like and is used for signal analysis and processing. The invention solves the problems of dead zone detection, insufficient detection precision, low data processing efficiency and the like of the anchoring zone, and can be widely applied to daily detection and maintenance of cable-supported bridges such as cable-stayed bridges, suspension bridges and the like.

Inventors

WANG JINGQUAN
LIU CHENGHAO
ZHANG FAN
Du Linpu
ZHANG ZHAOCHANG
LU KAIWEI

Assignees

江苏大学

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (10)

1. The guided wave-magnetic leakage composite intelligent detection device for bridge cable damage detection is characterized by comprising a data acquisition module, a calculation control module and a climbing module; The signal processing equipment and the signal generator are embedded in the calculation control module, and the signal processing equipment comprises a data acquisition card and an embedded processor which are electrically connected with the data acquisition module; The data acquisition module comprises a magnetic leakage detection unit, a magnetostriction guided wave detection unit and a pre-amplifying circuit fixed on the magnetic leakage detection unit, wherein the magnetic leakage detection unit comprises a permanent magnet, an armature and permalloy which form an excitation loop and a Hall element arranged between the excitation loop and a target cable; The climbing module comprises a pulley and a motor which are fixedly connected with the data acquisition module, and the climbing module is used for driving the guided wave-magnetic leakage composite intelligent detection equipment to axially climb on the surface of the target cable.
2. The guided wave-magnetic leakage composite intelligent detection device according to claim 1, wherein the armature is in a strip shape and is axially arranged on the target cable, permalloy is fixedly connected to two sides below the armature respectively, and a permanent magnet is arranged below the armature between the two permalloys.
3. The guided wave-magnetic leakage composite intelligent detection device according to claim 2, wherein the pulleys are respectively arranged at two ends of the armature, the pulleys are damping rubber-coated pulleys, one end of each pulley is fixedly connected with the armature through a damping spring, the other end of each pulley is fixedly connected with the armature through a damping connecting rod, and the pulleys are connected with the motor through damping belts.
4. The guided wave-magnetic leakage composite intelligent detection device of claim 1, further comprising a battery for providing operating power to each module.
5. The guided wave-magnetic leakage composite intelligent detection device according to claim 1, wherein a signal denoising filtering algorithm and a trained machine learning model are arranged in the embedded processor so as to process an input signal in real time and output a cable damage assessment result.
6. The guided wave-magnetic leakage composite intelligent detection device according to claim 1, wherein the number of the magnetic leakage detection units is determined according to the diameter of the target cable, and the larger the diameter is, the larger the number is.
7. The guided wave-magnetic leakage composite intelligent detection device according to claim 5 is characterized in that the embedded processor is an embedded development board based on a Linux system, the embedded development board is a raspberry group, a CPU (central processing unit), a memory, GPIO (general purpose input/output) pins and an Ethernet port are integrated and used for running the signal denoising filtering algorithm and the machine learning model, and the data acquisition card is a PXI-4496 integrated data acquisition card and used for converting amplified analog signals from a digital acquisition module into digital signals.
8. The guided wave-magnetic leakage composite intelligent detection device according to claim 7 is characterized in that the signal denoising filtering algorithm adopts a wavelet transformation algorithm and is used for denoising a non-stationary abrupt change signal generated by cable damage, the machine learning model is a deep neural network model and is used for automatically extracting cable damage characteristics and identifying damage types, sizes and positions, the input end of the calculation control module is connected with an output channel of a data acquisition card, and the output end of the calculation control module outputs damage assessment results.
9. The method for intelligently detecting damage of bridge cables based on the guided wave-magnetic leakage composite intelligent detection equipment as claimed in any one of claims 1 to 8 is characterized by comprising the following steps: s1, selecting a corresponding number of magnetic flux leakage detection units according to the diameter of a target cable, and combining the magnetic flux leakage detection units into an annular composite detection probe array through a module connecting device, wherein the annular composite detection probe array is circumferentially arranged on the periphery of the target cable; s2, starting a climbing module, climbing the whole intelligent detection equipment along the axial direction of the target cable, and synchronously working a data acquisition module; S3, uniformly saturated magnetization is carried out on the target cable by an excitation loop of the magnetic leakage detection unit, and a Hall element collects leakage magnetic flux signals; s4, amplifying the original leakage magnetic flux signal and the guided wave signal by a pre-amplifying circuit, transmitting the amplified signals to a data acquisition card through a shielding cable, and converting the amplified signals into digital signals; s5, embedding a signal denoising filtering algorithm and a trained machine learning model into the embedded processor, performing wavelet transformation denoising filtering processing on the digital signal by a calculation control module, and extracting damage characteristics; S6, inputting the signals subjected to denoising and filtering treatment into a machine learning model after training is completed so as to automatically identify the type, size and position of the damage; And S7, displaying the cable damage evaluation result in real time at the output end of the calculation control module to finish detection.
10. The method of claim 9, wherein the signal denoising filtering algorithm is implemented by a wavelet transform library in LabVIEW, and denoising the non-stationary abrupt signal generated by cable damage by retaining time resolution and frequency resolution; The training method of the machine learning model comprises the steps of constructing a cable sample database containing different types of damage with different degrees, extracting magnetic leakage and guided wave signal characteristics of samples, and performing supervised learning training to enable the model to learn the mapping relation between the damage characteristics and the damage types, sizes and positions.

Description

Guided wave-magnetic leakage composite intelligent detection equipment and method for bridge cable damage detection Technical Field The invention relates to the technical field of bridge engineering and structural health monitoring, in particular to a damage detection device suitable for cable bearing structures of cable stayed bridges, suspension bridges and the like, and particularly relates to composite detection equipment combining two nondestructive detection technologies of guided wave and magnetic leakage and an intelligent evaluation method thereof. Background With the rapid development of the construction of the traffic infrastructure in China, the number of the large-span bridges is increased. The cable is used as a core stress member of the bridge, and the health condition of the cable is directly related to the overall safety of the bridge. The cable is in a high-stress state for a long time, bears multiple actions such as wind vibration, vehicle load, environmental corrosion and the like, and is easy to generate damage such as rust, broken wire and the like. If the medical instrument can not be found and treated in time, sudden fracture accidents can be caused, and serious casualties and economic losses are caused. At present, the bridge cable detection mainly adopts methods such as manual visual inspection, ultrasonic detection, magnetostriction guided wave detection, magnetic leakage detection and the like. However, the prior art has the obvious defects that (1) the detection means is single, the coverage range is limited, although the magnetic leakage detection technology has higher detection precision and can accurately position local defects, the hidden parts such as an anchoring area and the like cannot be effectively detected due to the limitation of the working principle, and the magnetostriction guided wave detection technology can realize the detection of the anchoring area and is sensitive to corrosion damage, but the detection precision and the defect positioning capability of the magnetostriction guided wave detection technology are required to be improved. At present, the two technologies are applied to the field of cable detection, but the two technologies are organically combined, so that the composite detection research for exerting the respective advantages is less. (2) The signal quality is greatly affected by the field environment, namely, the lifting height of the sensor is large during cable detection, so that magnetic leakage and guided wave signals are weak, the signal is easy to submerge in field noise and clutter signals, and high-quality data are difficult to collect. (3) The data processing efficiency is low, the original data acquired by the existing detection technology is large in volume, manual interpretation is time-consuming and labor-consuming, an effective algorithm is lacking to convert the original signals into visual damage images and evaluation results, and the detection efficiency is difficult to meet the large-scale bridge management and maintenance requirements. Therefore, a new cable detection technical solution capable of overcoming the above-mentioned drawbacks is highly desired. Disclosure of Invention The invention provides a guided wave-magnetic leakage composite intelligent detection device and a method for bridge cable damage detection, which combine the technical advantages of guided wave detection and magnetic leakage detection, realize automatic climbing detection through a modularized robot detection platform, and introduce a machine learning algorithm to carry out intelligent processing on detection signals, thereby effectively solving the problems of limited application range, poor signal quality, low data processing efficiency and the like of a single detection method and having the advantages of high detection precision, wide coverage range, high intelligent degree. The invention provides guided wave-magnetic leakage composite intelligent detection equipment for bridge cable damage detection. The device comprises a climbing module, a data acquisition module and a calculation control module, wherein the calculation control module is embedded with signal processing equipment and a signal generator, the signal processing equipment comprises a data acquisition card and an embedded processor, the data processing equipment is electrically connected with the data acquisition module through a connecting wire, the data acquisition module comprises a magnetic leakage detection unit, a magnetostriction guided wave detection unit and a pre-amplifying circuit fixed on the magnetic leakage detection unit, the magnetic leakage detection unit comprises a permanent magnet, an armature, permalloy and a Hall element arranged between the excitation loop and a target cable, the permanent magnet, the armature and permalloy form an excitation loop, the Hall element is arranged between the excitation loop and the target cable, the plurality of magnetic leakage