CN-121978206-A - Steel structure fatigue crack monitoring device and method based on distributed optical fiber acoustic wave sensing technology

Abstract

The invention discloses a device and a method for monitoring fatigue cracks of a steel structure based on a distributed optical fiber acoustic wave sensing technology, which belong to the technical field of monitoring the health state of the steel structure, wherein the device structure comprises N optical fiber stress wave sensing units, a signal transmission optical fiber, a distributed optical fiber acoustic wave demodulator and an upper computer; the optical fiber stress wave sensing unit comprises a cylindrical elastomer, spiral sensing optical fibers and a noise isolation shell, wherein the spiral sensing optical fibers are wound on the outer side surface of the cylindrical elastomer, the noise isolation shell is used for wrapping the cylindrical elastomer and the spiral sensing optical fibers, the signal transmission optical fibers are connected with the optical fiber stress wave sensing unit and the distributed optical fiber acoustic wave demodulator and enable the spiral sensing optical fibers in the N optical fiber stress wave sensing units to be connected in series, and the upper computer identifies crack initiation and expansion conditions based on Rayleigh scattering light phase change signals. The device and the method can realize distributed, real-time and high-sensitivity monitoring on the fatigue cracks of key parts such as main components of the steel structure, welding lines and the like.

Inventors

• LIU WEIKANG
• DONG SHUQIN
• SHEN YANBIN
• LUO YAOZHI

Assignees

• 浙江大学长三角智慧绿洲创新中心

Dates

Publication Date

20260505

Application Date

20251230

Claims (9)

1. 1. The device is characterized by comprising N optical fiber stress wave sensing units, signal transmission optical fibers, a distributed optical fiber acoustic wave demodulator and an upper computer; the optical fiber stress wave sensing unit comprises a cylindrical elastomer, a spiral sensing optical fiber and a noise isolation shell; the device comprises a cylindrical elastic body, a noise isolation shell, a spiral sensing optical fiber, a noise isolation shell, a sensor and a sensor, wherein the cylindrical elastic body is wound with the spiral sensing optical fiber on the outer side surface of the cylindrical elastic body; The signal transmission optical fiber is connected with the optical fiber stress wave sensing units and the distributed optical fiber acoustic wave demodulators, and the spiral sensing optical fibers in the N optical fiber stress wave sensing units are connected in series; The distributed optical fiber acoustic wave demodulator is used for acquiring Rayleigh scattered light phase change signals of the spiral sensing optical fibers in each optical fiber stress wave sensing unit in a measured time period, transmitting the Rayleigh scattered light phase change signals to the upper computer, and the upper computer utilizes the Rayleigh scattered light phase change signals to identify crack initiation and expansion conditions in a monitoring area of each optical fiber stress wave sensing unit in the measured time period.
2. 2. The distributed fiber acoustic wave sensing technology-based steel structure fatigue crack monitoring device according to claim 1, wherein the cylindrical elastic body is made of a high-elasticity low-damping material, and the high-elasticity low-damping material is selected from polyurethane, polyamide or a high-molecular composite material.
3. 3. The distributed fiber acoustic wave sensing technology-based steel structure fatigue crack monitoring device according to claim 1, wherein the noise isolation shell is of a three-layer composite material structure, the outer layer is an acoustic wave reflecting layer, the middle layer is a damping sound absorbing material, the inner layer is a thermosetting resin layer, the outer layer is any one of aluminum alloy, stainless steel or glass fiber reinforced composite material, and the middle layer is any one of polyurethane damping material, butyl rubber damping material or polymer composite damping material.
4. 4. The steel structure fatigue crack monitoring device based on the distributed optical fiber acoustic wave sensing technology according to claim 1, wherein a preformed hole is arranged on the noise isolation shell for the signal transmission optical fiber to pass through.
5. 5. The method for monitoring the fatigue crack of the steel structure based on the distributed optical fiber acoustic wave sensing technology is characterized by comprising the following steps of: And respectively pasting N optical fiber stress wave sensing units connected in series on the surface of a detected steel structure, acquiring Rayleigh scattering light phase change signals of the spiral sensing optical fibers in each optical fiber stress wave sensing unit in a detected time period by using a distributed optical fiber acoustic wave demodulator, and identifying crack initiation and propagation conditions in a monitoring area based on the Rayleigh scattering light phase change data.
6. 6. The method for monitoring fatigue cracks of steel structure based on distributed optical fiber acoustic wave sensing technology according to claim 5, wherein the phase change of Rayleigh scattered light is as follows Calculated by the following formula: ; Wherein L g is the length of the spiral sensing optical fiber, p e is the effective photoelastic coefficient of the spiral sensing optical fiber, lambda is the wavelength of light waves, R is the radius of the cylindrical elastomer, deltaR is the radius variation of the cylindrical elastomer, and alpha is the axial included angle between the spiral sensing optical fiber and the cylindrical elastomer.
7. 7. The method for monitoring fatigue cracks of the steel structure based on the distributed optical fiber acoustic wave sensing technology according to claim 5, wherein a deep learning classification model is adopted to classify Rayleigh scattered light phase change signals of the spiral sensing optical fibers in each optical fiber stress wave sensing unit in a measured time period, and crack initiation and propagation conditions in a monitoring area of each optical fiber stress wave sensing unit in the measured time period are identified.
8. 8. The method for monitoring fatigue cracks of the steel structure based on the distributed optical fiber acoustic wave sensing technology according to claim 7, wherein the input of the deep learning classification model is a multi-scale time-frequency characteristic constructed after time-frequency conversion of the Rayleigh scattered light phase change signal, the output is a crack state classification result, and the structure of the deep learning classification model is a convolutional neural network structure.
9. 9. The method for monitoring the fatigue crack of the steel structure based on the distributed optical fiber acoustic wave sensing technology according to claim 5, wherein the upper computer further performs spatial clustering and time evolution analysis on the identified crack initiation and propagation condition results, constructs a fatigue crack health index of the steel structure, and displays the crack development state of the monitoring area in a three-dimensional visual mode.

Description

Steel structure fatigue crack monitoring device and method based on distributed optical fiber acoustic wave sensing technology Technical Field The invention belongs to the technical field of steel structure health state monitoring, and particularly relates to a steel structure fatigue crack monitoring device and method based on a distributed optical fiber acoustic wave sensing technology. Background The steel structure is widely applied to the fields of bridges, venues, large-scale plants, ocean engineering, high-rise buildings and the like. With the continuous development of engineering structures in the large-span and light-weight directions, high-strength steel is widely used in various key bearing components due to high strength, good toughness and better welding performance. However, under long-term loading, fatigue loading and environmental factors (such as temperature changes, corrosion and wind vibration), fatigue cracks are still very likely to occur at stress concentration sites of structural members. For a high-strength steel structure, although the material has higher bearing capacity, the material has higher yield ratio, higher local brittleness sensitivity and higher fatigue crack growth rate, and the crack is difficult to detect in the initial stage of initiation, and often can be rapidly expanded in a short period, so that the bearing capacity of a component is obviously reduced, and even serious structural safety accidents are caused. Therefore, the method has important engineering significance for real-time, long-term and reliable online monitoring of the fatigue crack development of the steel structure, in particular to the high-strength steel structure. The existing fatigue crack monitoring means mainly comprise ultrasonic detection, magnetic powder detection, acoustic emission monitoring, resistance strain gauge detection and the like. The method has certain limitations, such as long period of manual nondestructive detection, incapability of realizing continuous monitoring depending on experience of operators, limited quantity of traditional acoustic emission sensors, complicated arrangement, difficulty in realizing large-scale coverage, poor durability of the resistance strain gauge, insufficient long-term stability, incapability of effectively capturing early-stage characteristic signals of microcracks and the like. Therefore, the method is difficult to meet engineering requirements in large steel structures, complex steel structures, hidden components or long-time online monitoring scenes. The Chinese patent document with the publication number of CN113899746A discloses a method for measuring the fatigue crack growth morphology of a steel structure based on DIC, which comprises the steps of collecting a group of digital image sequences for recording the variation process of the fatigue crack growth morphology of the steel structure, carrying out image processing on the digital image sequences to obtain a crack growth displacement field with a topological structure, carrying out crack growth morphology extraction on the crack growth displacement field, reducing the dynamic growth process of the fatigue crack of the steel structure, and realizing high-precision and intelligent real-time monitoring of the fatigue crack. The method depends on stable observation conditions, and is difficult to adapt to the field environment of complex engineering. The Chinese patent document with the publication number of CN116432475A discloses a multi-factor coupling collaborative early warning method for fatigue crack growth of a steel structure, which comprises the steps of obtaining multi-physical-field monitoring data of dangerous source distribution points of a steel structure project, obtaining a monitoring time sequence dataset, constructing an intuitive fuzzy matrix of the monitoring time sequence dataset, obtaining uncertainty of each index by utilizing gray correlation coefficients among monitoring indexes of each physical field, taking the obtained uncertainty as basic probability assignment of each evidence, preprocessing the evidence through weighted average, obtaining corrected basic probability assignment, obtaining basic probability assignment of the fatigue crack growth process of the steel structure at different development stages, and determining the fatigue crack growth grade of the dangerous source distribution points of the steel structure project by adopting the basic probability assignment. The method has complex algorithm and high dependence on the quality and the real-time performance of multi-source data. With the development of optical fiber sensing technology, distributed optical fiber acoustic wave sensing technology is focused in the field of structural health monitoring because of the advantages of continuous distribution, high sensitivity, strong electromagnetic interference resistance, suitability for long-distance monitoring and the like. The distributed optical fiber a