Bridge status detection method based on fiber grating sensor and acoustic emission sensor

Abstract

The present invention discloses a bridge state detection method based on a fiber grating sensor and an acoustic emission sensor, which solves the problem of complex and inaccurate detection in the prior art, and includes: setting a detection threshold corresponding to the environmental noise energy; converting the steel cable acoustic emission signal data from the time domain into the steel cable acoustic emission signal data in the frequency domain, and performing energy integration to obtain the time domain energy value corresponding to the steel cable acoustic emission signal data and the frequency domain energy value corresponding to the steel cable acoustic emission signal data in the frequency domain; comparing the collected steel cable acoustic emission signal with the detection threshold; obtaining the sound intensity using the steel cable acoustic emission signal; obtaining the distance between the acoustic emission sensor and the abnormal position of the steel cable according to the sound intensity; obtaining the temperature change interference threshold of the fiber grating sensor; obtaining the grating signal mutation value, if the grating signal mutation value is greater than the temperature change interference threshold; and providing maintenance prompts according to the detection threshold comparison results. In summary, the method has high practical value and promotion value in the field of bridge detection technology.

Description

Technical Field

[0001] The invention relates to the technical field of bridge detection, in particular to a bridge state detection method based on a fiber grating sensor and an acoustic emission sensor. Background Art

[0002] The bridge status detection in this article is to monitor and evaluate the condition of the bridge structure, and issue early warning signals under special climate and traffic conditions or when the operating conditions are abnormally serious, so as to provide a basis and guidance for maintenance and management decisions. Among them, the cable (steel cable) is the main force-bearing component of the cable-stayed bridge, and it has been corroded by the outside world for a long time. Therefore, it is particularly important to timely detect the health status of the cable to ensure the structural safety and long-term stability of the bridge. At present, the main detection methods of the cable in the existing technology include acoustic emission detection, fiber grating detection, robot vision detection, etc. Among them, the naked eye or robot vision cannot perform long-term and real-time detection, and cannot handle the abnormal conditions of the bridge in time, and the visual detection image data processing is complicated. In addition, the acoustic emission detection technology mainly receives the elastic wave of the steel cable break or the pressure wave of the bridge deck deformation. If it is not effectively detected when the break or deformation occurs or there are external force majeure factors, it is easy to cause missed detection and missed reporting, such as the public technology of "publication number CN112986393A, named a method and system for detecting damage to bridge cables". Finally, fiber Bragg grating detection technology mainly detects bridge deck deformation and cable tension by changing the fiber Bragg grating coupling wavelength caused by temperature, strain or stress. Since it is sensitive to temperature, cross interference may occur.

[0003] Therefore, it is urgent to propose a bridge status detection method based on fiber grating sensors and acoustic emission sensors that is simple in logic, accurate and reliable. Summary of the invention

[0004] In view of the above problems, the purpose of the present invention is to provide a bridge state detection method based on a fiber grating sensor and an acoustic emission sensor. The technical solution adopted by the present invention is as follows:

[0005] The bridge state detection method based on fiber grating sensor and acoustic emission sensor comprises the following steps:

[0006] The acoustic emission sensor and the fiber grating sensor are respectively fixed on the surface of the steel cable of the bridge to be inspected;

[0007] The acoustic emission sensor is used to collect the acoustic emission signal, and the energy integration is used to obtain the time domain energy value E'0 (St i ), the frequency domain energy value E'0 (FSt i ), the time domain energy value E'1(St i) and the frequency domain energy value E'1(FSt i );

[0008] Preset false alarm probability P f , the detection threshold value TH is obtained according to the false alarm probability calculation formula in the binary hypothesis problem;

[0009] Combined with the time domain energy value E'0(St i ), the time domain energy value E'1(St i ), the frequency domain energy value E'0 (FSt i ) and the frequency domain energy value E'1(FSt i ), respectively obtain the time domain detection threshold TH1 under the first environmental condition, the time domain detection threshold TH2 under the second environmental condition, the frequency domain detection threshold TH3 under the first environmental condition, and the frequency domain detection threshold TH4 under the second environmental condition;

[0010] Collect the steel cable acoustic emission signal S of the acoustic emission sensor in real time and record the time from time T0 to time T i Wire rope acoustic emission signal data S ti , the cable acoustic emission signal data S ti FS, the steel cable acoustic emission signal data converted from time domain to frequency domain ti ;

[0011] The cable acoustic emission signal data S ti FS of steel cable acoustic emission signal in the frequency domain ti Perform energy integration to obtain the cable acoustic emission signal data S ti The corresponding time domain energy value E(S ti ) and frequency domain steel cable acoustic emission signal data FS ti The corresponding frequency domain energy value E(FS ti );

[0012] If the cable acoustic emission signal data S ti The corresponding time domain energy value E(S ti ) is greater than the time domain detection threshold TH1 under the first environmental condition, the first alarm signal M1 is triggered; if the cable acoustic emission signal data S ti The corresponding time domain energy value E(S ti ) is greater than the time domain detection threshold TH2 under the second environmental condition, the second alarm signal M2 is triggered; if the cable acoustic emission signal data FS in the frequency domain ti The corresponding frequency domain energy value E(FS ti ) is greater than the frequency domain detection threshold TH3 under the first environmental condition, the third alarm signal M3 is triggered; if the steel cable acoustic emission signal data FS in the frequency domain tiThe corresponding frequency domain energy value E(FS ti ) is greater than the frequency domain detection threshold TH4 under the second environmental condition, then a fourth alarm signal M4 is triggered;

[0013] The acoustic emission signal S of the steel cable is used to obtain the sound intensity I; the distance x between the acoustic emission sensor and the abnormal position of the steel cable is obtained according to the sound intensity I;

[0014] Applying simulated external temperature changes to the fiber Bragg grating sensor, obtaining optical wavelength signal data GT0 before applying the simulated external temperature changes and optical wavelength signal data GT1 after applying the simulated external temperature changes, and obtaining a temperature change interference threshold value K0 of the fiber Bragg grating sensor;

[0015] If one or more of the first alarm signal M1, the second alarm signal M2, the third alarm signal M3 and the fourth alarm signal M4 appear, the wavelength data difference and the change time ratio are calculated to obtain the grating signal mutation value K i ; If the grating signal suddenly changes to value K i If it is greater than the temperature change interference threshold K0, the fifth alarm signal M5 is triggered;

[0016] When the second alarm signal M2, the fourth alarm signal M4 and the fifth alarm signal M5 appear at the same time, a maintenance prompt is given.

[0017] Compared with the prior art, the present invention has the following beneficial effects:

[0018] (1) The present invention obtains the time domain energy value and frequency domain energy value under two working environments through energy integration, so as to obtain the environmental noise energy under good weather conditions (rated working conditions) and bad weather conditions (extreme working conditions), eliminate the influence of environmental noise on monitoring, and ensure the reliability of its detection.

[0019] (2) The present invention uses Fourier transform to convert the steel cable acoustic emission signal data from the time domain into the steel cable acoustic emission signal data in the frequency domain. The signal spectrum is relatively clean and white noise interference can be eliminated.

[0020] (3) The present invention obtains the sound intensity and the distance between the acoustic emission sensor and the abnormal position of the steel cable, thereby roughly determining the broken position of the steel cable, which is convenient for maintenance personnel to quickly confirm.

[0021] (4) The present invention applies simulated external temperature changes to obtain the temperature change interference threshold of the fiber Bragg grating sensor, thereby eliminating the interference of temperature changes on detection and ensuring the accuracy of detection.

[0022] (5) The present invention obtains the mutation value of the grating signal and compares it with the temperature change interference threshold to obtain the change in the health status of the cable, making the detection more accurate and reliable.

[0023] (6) The present invention performs multiple judgment detections through the distance between the acoustic emission sensor and the abnormal position of the steel cable, the sudden change value of the grating signal and the detection threshold, thereby eliminating interference from the environment and the sensor itself and ensuring the accuracy of the detection.

[0024] In summary, the present invention has the advantages of simple logic, accuracy and reliability, and has high practical value and promotion value in the field of bridge detection technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope of protection. For those skilled in the art, other related drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 It is a logic flow chart of the present invention.

[0027] Figure 2 This is a simulation analysis diagram of the stress change of broken wires inside the steel cable.

[0028] Figure 3 This is the acoustic emission signal analysis diagram. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical scheme and advantages of this application clearer, the present invention is further described below in conjunction with the accompanying drawings and embodiments, and the embodiments of the present invention include but are not limited to the following embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0030] In this embodiment, the term "and / or" is merely a term used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent three situations: A exists alone, A and B exist at the same time, and B exists alone.

[0031] The terms "first" and "second" in the description and claims of this embodiment are used to distinguish different objects rather than to describe a specific order of objects. For example, a first target object and a second target object are used to distinguish different target objects rather than to describe a specific order of target objects.

[0032] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0033] In the description of the embodiments of the present application, unless otherwise specified, the meaning of "multiple" refers to two or more than two. For example, multiple processing units refer to two or more processing units; multiple systems refer to two or more systems.

[0034] like Figures 1 to 3 As shown, this embodiment provides a bridge state detection method based on a fiber grating sensor and an acoustic emission sensor, which uses the fiber grating sensor and the acoustic emission sensor for joint detection; specifically, it includes the following steps:

[0035] In the first step, the acoustic emission sensor and the fiber grating sensor are respectively fixed on the surface of the steel cable of the bridge to be inspected.

[0036] The second step is to measure the environmental noise energy of the bridge cables under normal traffic operation, in good weather conditions and in bad weather conditions. It should be noted that the first environmental condition is the environmental condition of the acoustic emission sensor under good weather conditions. In addition, the second environmental condition is the environmental condition of the acoustic emission sensor under bad weather conditions. The bad weather refers to local weather conditions that are not conducive to human production and activities, or are destructive. For example, storms, sand (dust) storms, snowstorms, severe thunderstorms, hail, tornadoes, etc., are mature means of weather classification. The acoustic emission sensor is used to collect the acoustic emission signal, and the energy integration is used to obtain the time domain energy value E'0 (St i ), the frequency domain energy value E'0 (FSt i ), the time domain energy value E'1(St i ) and the frequency domain energy value E'1(FSt i Here, the time domain energy value E'0 (St i ), the frequency domain energy value E'0 (FSt i ), the time domain energy value E'1(St i ) and the frequency domain energy value E'1(FSt i ) is obtained using the following formula:

[0037]

[0038] Where E represents the time from T0 to time T i The energy value inside; S(t) represents the real-time sampling data value.

[0039] The third step is to preset the false alarm probability P f , and the detection threshold TH is obtained according to the false alarm probability calculation formula in the binary hypothesis problem, and its expression is:

[0040]

[0041] Among them, σ 2 Represents the total noise power of interference; P f represents the false alarm probability.

[0042] The fourth step is to combine the time domain energy value E'0 (St i ), the time domain energy value E'1(St i ), the frequency domain energy value E'0 (FSt i ) and the frequency domain energy value E'1(FSt i ), respectively obtain the time domain detection threshold TH1 under the first environmental condition, the time domain detection threshold TH2 under the second environmental condition, the frequency domain detection threshold TH3 under the first environmental condition, and the frequency domain detection threshold TH4 under the second environmental condition. It includes:

[0043] The time domain energy value E'0(St i ) Substitute the total noise power of the interference σ 2 , and use the calculation formula in the third step to obtain the time domain detection threshold TH1 under the first environmental condition. Similarly, the time domain energy value E'1 (St i ), the frequency domain energy value E'0 (FSt i ) and the frequency domain energy value E'1(FSt i ) respectively substitute the total noise power σ of the interference 2 , the time domain detection threshold TH2 under the second environmental condition, the frequency domain detection threshold TH3 under the first environmental condition, and the frequency domain detection threshold TH4 under the second environmental condition can be obtained in turn.

[0044] Step 5: Collect the steel cable acoustic emission signal S of the acoustic emission sensor in real time and record the time from time T0 to time T i Wire rope acoustic emission signal data S ti , Fourier transform is used to transform the cable acoustic emission signal data S ti FS, the steel cable acoustic emission signal data converted from time domain to frequency domain ti .

[0045] Step 6: Calculate the cable acoustic emission signal data S ti Perform energy integration to obtain the cable acoustic emission signal data S ti The corresponding time domain energy value E(S ti ); and the frequency domain cable acoustic emission signal data FS ti Perform energy integration to obtain the cable acoustic emission signal data FS in the sum frequency domain ti The corresponding frequency domain energy value E(FS ti ). Here, the energy integral adopts the energy integral calculation formula in the second step.

[0046] Step 7: Under the actual test environment, the collected steel cable acoustic emission signal is compared with the established threshold. ti The corresponding time domain energy value E(S ti ) is greater than the time domain detection threshold TH1 under the first environmental condition, the first alarm signal M1 is triggered; if the cable acoustic emission signal data S ti The corresponding time domain energy value E(S ti ) is greater than the time domain detection threshold TH2 under the second environmental condition, the second alarm signal M2 is triggered; if the cable acoustic emission signal data FS in the frequency domain ti The corresponding frequency domain energy value E(FS ti ) is greater than the frequency domain detection threshold TH3 under the first environmental condition, the third alarm signal M3 is triggered; if the steel cable acoustic emission signal data FS in the frequency domain ti The corresponding frequency domain energy value E(FS ti ) is greater than the frequency domain detection threshold TH4 under the second environmental condition, the fourth alarm signal M4 is triggered.

[0047] The eighth step is to use the steel cable acoustic emission signal S to obtain the sound intensity I, where the expression of the sound intensity is:

[0048]

[0049] Among them, ρ0 is the fluid density, ρ0c0 is the medium characteristic impedance, and p e Here, it is the received steel cable acoustic emission signal S. This paper only compares the sound intensity at the sound source and the detector, so the square of the acoustic emission signal S after collection is used to replace the sound intensity.

[0050] The distance x between the acoustic emission sensor and the abnormal position of the steel cable is obtained according to the sound intensity I, and its expression is:

[0051] I=I0e -ax

[0052] Where I0 represents the initial sound intensity; a represents the sound wave attenuation coefficient; and x represents the distance between the acoustic emission sensor and the abnormal position of the steel cable.

[0053] The ninth step is to avoid cross-interference of the fiber Bragg grating sensor caused by temperature, and eliminate the influence of temperature by comparing the intensity of the grating signal change. First, determine the temperature change interference threshold K0 of the fiber Bragg grating sensor. When the amplitude of the signal mutation is less than this threshold during the actual detection process, it is judged as a temperature influence, and no alarm signal is given. Set the time span T for applying simulated external temperature changes, and apply different temperatures to the fiber Bragg grating sensor to simulate external temperature changes. Among them, the expression of the temperature change interference threshold K0 of the fiber Bragg grating sensor is:

[0054]

[0055] Among them, GT1 represents the optical wavelength signal data after applying the simulated external temperature change; GT0 represents the optical wavelength signal data before applying the simulated external temperature change; T represents the time span of applying the simulated external temperature change.

[0056] Step 10: If one or more of the first alarm signal M1, the second alarm signal M2, the third alarm signal M3 and the fourth alarm signal M4 appear, calculate the wavelength data difference and the change time ratio and obtain the grating signal mutation value K. i , whose expression is:

[0057]

[0058] Here, the wavelength data difference is calculated and the grating signal mutation value K is obtained. i , including the following steps:

[0059] Real-time acquisition of the cable grating signal G to obtain the wavelength data G i ;

[0060] Preset counter N0 to obtain the next wavelength data G corresponding to wavelength data G0 i And record the counter value N i ;

[0061] According to the wavelength data G i , wavelength data G0, counter value N i And counter N0 to obtain the grating signal mutation value K i .

[0062] If the grating signal suddenly changes to K i If it is greater than the temperature change interference threshold K0, the fifth alarm signal M5 is triggered;

[0063] Step 11: When the second alarm signal M2, the fourth alarm signal M4 and the fifth alarm signal M5 appear at the same time, a maintenance prompt is given. The detection prompt contains information such as the distance between the acoustic emission sensor and the abnormal position of the steel cable.

[0064] This embodiment carries out simulation test, and its specific situation is as follows: Figure 2 As shown in the figure, a simulation analysis of the broken steel cable is carried out. When a wire breaks inside the steel cable, the strain of other steel wires is shown in the figure. There is an obvious change, and the fiber Bragg grating sensor can detect the strain. Figure 3 As shown in the figure, the acoustic emission signal of the steel cable is analyzed. Figure 3 In the figure, a, b, and c are the acoustic emission signals when the steel cable breaks. When the cable breaks, the acoustic emission signal is 20-30dB higher than the ambient noise. Compared with the normal working state, there is a significant change. The acoustic emission sensor can detect the cable break signal.

[0065] The above embodiments are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any changes that adopt the design principles of the present invention and are made through non-creative work on this basis should fall within the protection scope of the present invention.

Claims

1. A bridge status detection method based on fiber grating sensor and acoustic emission sensor, characterized in that: The following steps are involved: The acoustic emission sensor and the fiber grating sensor are respectively fixed on the surface of the steel cable of the bridge to be inspected; The acoustic emission sensor is used to collect the acoustic emission signal, and the energy integration is used to obtain the time domain energy value E'0 (St i ), the frequency domain energy value E'0 (FSt i ), the time domain energy value E'1(St i ) and the frequency domain energy value E'1(FSt i ); Preset false alarm probability P f , the detection threshold value TH is obtained according to the false alarm probability calculation formula in the binary hypothesis problem; Combined with the time domain energy value E'0(St i ), the time domain energy value E'1(St i ), the frequency domain energy value E'0 (FSt i ) and the frequency domain energy value E'1(FSt i ), respectively obtain the time domain detection threshold TH1 under the first environmental condition, the time domain detection threshold TH2 under the second environmental condition, the frequency domain detection threshold TH3 under the first environmental condition, and the frequency domain detection threshold TH4 under the second environmental condition; Collect the steel cable acoustic emission signal S of the acoustic emission sensor in real time and record the time from time T0 to time T i Wire rope acoustic emission signal data S ti , the cable acoustic emission signal data S ti FS, the steel cable acoustic emission signal data converted from time domain to frequency domain ti ; The cable acoustic emission signal data S ti FS of steel cable acoustic emission signal in the frequency domain ti Perform energy integration to obtain the cable acoustic emission signal data S ti The corresponding time domain energy value E(S ti ) and frequency domain steel cable acoustic emission signal data FS ti The corresponding frequency domain energy value E(FS ti ); If the cable acoustic emission signal data S ti The corresponding time domain energy value E(S ti ) is greater than the time domain detection threshold TH1 under the first environmental condition, the first alarm signal M1 is triggered; if the cable acoustic emission signal data S ti The corresponding time domain energy value E(S ti ) is greater than the time domain detection threshold TH2 under the second environmental condition, the second alarm signal M2 is triggered; if the steel cable acoustic emission signal data FS in the frequency domain ti The corresponding frequency domain energy value E(FS ti ) is greater than the frequency domain detection threshold TH3 under the first environmental condition, the third alarm signal M3 is triggered; if the steel cable acoustic emission signal data FS in the frequency domain ti The corresponding frequency domain energy value E(FS ti ) is greater than the frequency domain detection threshold TH4 under the second environmental condition, then a fourth alarm signal M4 is triggered; The acoustic emission signal S of the steel cable is used to obtain the sound intensity I; the distance x between the acoustic emission sensor and the abnormal position of the steel cable is obtained according to the sound intensity I; Applying simulated external temperature changes to the fiber Bragg grating sensor, obtaining optical wavelength signal data GT0 before applying the simulated external temperature changes and optical wavelength signal data GT1 after applying the simulated external temperature changes, and obtaining a temperature change interference threshold value K0 of the fiber Bragg grating sensor; If one or more of the first alarm signal M1, the second alarm signal M2, the third alarm signal M3 and the fourth alarm signal M4 appear, the wavelength data difference and the change time ratio are calculated to obtain the grating signal mutation value K i ; If the grating signal suddenly changes to value K i If it is greater than the temperature change interference threshold K0, the fifth alarm signal M5 is triggered; When the second alarm signal M2, the fourth alarm signal M4 and the fifth alarm signal M5 appear at the same time, a maintenance prompt is given.

2. The bridge state detection method based on fiber grating sensor and acoustic emission sensor according to claim 1 is characterized in that: Wire rope acoustic emission signal data S ti The corresponding time domain energy value E(S ti ) and frequency domain steel cable acoustic emission signal data FS ti The corresponding frequency domain energy value E(FS ti ) includes the following steps: Acoustic emission signal data of steel cable S ti Perform energy integration to obtain the cable acoustic emission signal data S ti The corresponding time domain energy value E(S ti ); FS of the steel cable acoustic emission signal data in the frequency domain ti Perform energy integration to obtain the steel cable acoustic emission signal data FS in the frequency domain ti The corresponding frequency domain energy value E(FS ti ).

3. The bridge state detection method based on fiber grating sensor and acoustic emission sensor according to claim 1 is characterized in that: Calculate the wavelength data difference and the ratio of the change time and obtain the grating signal mutation value K i , including the following steps: Real-time acquisition of the steel cable grating signal G, recording of the grating signal G0, counter N0, and the next grating signal G corresponding to the grating signal G0 i And the grating signal G i The corresponding counter N i ; According to the grating signal G i , grating signal G0, counter N i And counter N0 to obtain the grating signal mutation value K i , whose expression is:

4. The bridge state detection method based on fiber grating sensor and acoustic emission sensor according to claim 2 is characterized in that: The time domain energy value E'0 (St i ), the frequency domain energy value E'0 (FSt i ), the time domain energy value E'1(St i ) and the frequency domain energy value E'1(FSt i ) is obtained using the following formula: Where E represents the time from T0 to time T i The energy value inside; S(t) represents the real-time sampling data value.

5. The bridge state detection method based on fiber grating sensor and acoustic emission sensor according to claim 4 is characterized in that: According to the false alarm probability calculation formula in the binary hypothesis problem, the detection threshold value TH is obtained, and its expression is: Among them, σ 2 Represents the total noise power of interference; P f represents the false alarm probability.

6. The bridge state detection method based on fiber grating sensor and acoustic emission sensor according to claim 5 is characterized in that: Combined with the time domain energy value E'0(St i ), the time domain energy value E'1(St i ), the frequency domain energy value E'0 (FSt i ) and the frequency domain energy value E'1(FSt i ), respectively obtaining a time domain detection threshold TH1 under the first environmental condition, a time domain detection threshold TH2 under the second environmental condition, a frequency domain detection threshold TH3 under the first environmental condition, and a frequency domain detection threshold TH4 under the second environmental condition, comprising the following steps: The time domain energy value E'0(St i ) Substitute the total noise power of the interference σ 2 , and obtain the time domain detection threshold TH1 under the first environmental condition; The time domain energy value E'1(St i ) Substitute the total noise power of the interference σ 2 , and obtain the time domain detection threshold TH2 under the second environmental condition; The frequency domain energy value E'0(FSt i ) Substitute the total noise power of the interference σ 2 , and obtain the frequency domain detection threshold TH3 under the first environmental condition; The frequency domain energy value E'1(FSt i ) Substitute the total noise power of the interference σ 2 , and obtain the frequency domain detection threshold TH4 under the second environmental condition.

7. The bridge status detection method based on fiber grating sensor and acoustic emission sensor according to claim 1, 2 or 3, characterized in that: The sound intensity I is obtained by using the steel cable acoustic emission signal S. The expression of the sound intensity I is: Among them, ρ0 represents the fluid density; ρ0c0 represents the characteristic impedance of the medium; p e Represents the sound pressure, which is the steel cable acoustic emission signal S here.

8. The bridge status detection method based on fiber grating sensor and acoustic emission sensor according to claim 7 is characterized in that: The distance x between the acoustic emission sensor and the abnormal position of the steel cable is obtained according to the sound intensity I, and its expression is: I=I0e -ax Where I0 represents the initial sound intensity; a represents the sound wave attenuation coefficient; and x represents the distance between the acoustic emission sensor and the abnormal position of the steel cable.

9. The bridge status detection method based on fiber grating sensor and acoustic emission sensor according to claim 1, 2 or 3, characterized in that: Apply simulated external temperature changes to the fiber Bragg grating sensor, and obtain the temperature change interference threshold K0 of the fiber Bragg grating sensor, which is expressed as: Among them, GT1 represents the optical wavelength signal data after applying the simulated external temperature change; GT0 represents the optical wavelength signal data before applying the simulated external temperature change; T represents the time span of applying the simulated external temperature change.

10. The bridge status detection method based on fiber grating sensor and acoustic emission sensor according to claim 1, 2 or 3, characterized in that: The cable acoustic emission signal data S is converted into ti FS, the steel cable acoustic emission signal data converted from time domain to frequency domain ti .

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