A method and system for identifying metal structure damage of large-scale loading and unloading machinery and equipment

Abstract

The present invention provides a method and system for identifying metal structure damage of large-scale loading and unloading mechanical equipment, belonging to the field of structural monitoring. The method includes: within a set period, collecting continuous strain changes on the surface of the metal structure through a distributed optical fiber strain sensor, and determining stress monitoring points according to the continuous strain changes; adopting the method of random excitation and multi-point response, tapping around all stress monitoring points in turn, and simultaneously collecting the strain at each stress monitoring point in real time through a three-axis fiber Bragg grating strain sensor and a long-gauge fiber Bragg grating strain sensor to obtain the time history strain data at each stress monitoring point; based on the time history strain data at each stress monitoring point, determining the strain modal parameters of each stress monitoring point by using the frequency domain decomposition method; and determining whether damage occurs and the degree of damage at each corresponding stress monitoring point according to the strain modal parameters of each stress monitoring point. The present invention improves the accuracy of metal structure damage identification.

Description

Technical Field

[0001] The present invention relates to the field of structural monitoring, and particularly to a method and system for identifying metal structure damage of large-scale loading and unloading machinery and equipment. Background Art

[0002] The main load-bearing structural members of large-scale loading and unloading machinery and equipment (such as cranes) are mainly made of profiled steel and plates as basic components, and are connected by welding, bolt connection and other connection methods according to certain rules to form a metal structure that can bear corresponding loads, which accounts for 60% - 80% of the total weight of the whole crane. For fatigue damage failures with time-accumulation characteristics, due to insufficient estimation of stress concentration, load stress spectrum, stress cycle times and characteristics, once serious defects occur in the metal structure leading to accidents, it will cause huge losses of personnel, property and adverse social impacts.

[0003] At present, the safety guarantee of large-scale loading and unloading machinery and equipment (such as cranes) mainly adopts three methods: (1) Regular inspections, special inspections and daily maintenance based on manual visual inspection and non-destructive testing methods, which require a large amount of time, materials and manpower, and there are time intervals for regular inspections and special inspections, lacking a warning mechanism for sudden accidents. (2) Static testing of structures, with poor accuracy, low efficiency and unable to realize real-time and long-term monitoring of the structural state. (3) Structural stress state monitoring using resistance strain gauges and fiber Bragg grating sensing technologies. Resistance strain gauges will have zero drift phenomena under the influence of structures, temperature or other uncertain factors during long-term stress monitoring, which will also cause incorrect measurement results.

[0004] In stress state monitoring, a point-type stress state monitoring method is adopted. The selection of monitoring points is mainly through simulation analysis and empirical screening, which has uncertainty. In addition, the point-type strain sensing technology is too local and has too large discreteness, making it difficult to characterize the damage change law of key areas of the structure. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and system for identifying metal structure damage of large-scale loading and unloading machinery and equipment, which can improve the accuracy of metal structure damage identification.

[0006] To achieve the above purpose, the present invention provides the following solution:

[0007] A method for identifying metal structure damage of large-scale loading and unloading machinery and equipment, comprising:

[0008] Within a set period, collect continuous strain changes on the surface of the metal structure through a distributed fiber optic strain sensor, and determine stress monitoring points according to the continuous strain changes;

[0009] Adopt the method of random excitation and multi-point response, tap around all stress monitoring points in turn to generate random excitation signals, and at the same time, collect the strain at each stress monitoring point in real time through three-direction fiber Bragg grating strain sensors and long-gauge fiber Bragg grating strain sensors to obtain the time-history strain data at each stress monitoring point; the long-gauge fiber Bragg grating strain sensors are arranged at the stress monitoring points in the linear area on the surface of the metal structure, and the three-direction fiber Bragg grating strain sensors are arranged at the stress monitoring points in the circular area or irregular area on the surface of the metal structure;

[0010] Based on the time-history strain data at each stress monitoring point, determine the strain modal parameters of each stress monitoring point based on the frequency domain decomposition method;

[0011] Determine whether damage occurs at each stress monitoring point according to the strain modal parameters of each stress monitoring point, and determine the degree of damage according to the strain modal parameters of the stress monitoring points where damage occurs.

[0012] Optionally, the distributed fiber optic strain sensor is fixed on the surface of the metal structure in a serpentine manner.

[0013] Optionally, based on the time-history strain data at each stress monitoring point, determine the strain modal parameters of each stress monitoring point based on the frequency domain decomposition method, specifically including:

[0014] For any stress monitoring point, perform Fourier transform on the time-history strain data at the stress monitoring point and add a Hanning window to obtain the spectrum data of the stress monitoring point;

[0015] According to the spectrum data of the stress monitoring point, determine the strain modal parameters of the stress monitoring point by using the strain frequency response function.

[0016] Optionally, the strain modal parameters include natural frequency, damping ratio and strain modal shape;

[0017] Determine whether damage occurs at each stress monitoring point according to the strain modal parameters of each stress monitoring point, and determine the degree of damage according to the strain modal parameters of the stress monitoring points where damage occurs, specifically including:

[0018] For any stress monitoring point, calculate the difference between the strain modal shape of the stress monitoring point and the strain modal shape of the healthy structure to obtain the modal shape difference of the stress monitoring point;

[0019] If the modal shape difference of the stress monitoring point is greater than the set threshold, damage occurs at the stress monitoring point, otherwise no damage occurs at the stress monitoring point;

[0020] When damage occurs at the stress monitoring point, determine the degree of damage at the stress monitoring point according to the modal shape difference of the stress monitoring point.

[0021] Optionally, the method for identifying metal structure damage of large-scale loading and unloading machinery and equipment further includes:

[0022] Real-time detecting the surface temperature of the metal structure through a fiber Bragg grating temperature sensor;

[0023] Compensating the strain at each stress monitoring point according to the surface temperature.

[0024] To achieve the above object, the present invention also provides the following solution:

[0025] A system for identifying metal structure damage of large-scale loading and unloading machinery and equipment, comprising:

[0026] A distributed fiber optic strain sensor, arranged on the surface of the metal structure, for collecting continuous strain changes on the surface of the metal structure;

[0027] A monitoring platform, connected to the distributed fiber optic strain sensor, for determining stress monitoring points according to continuous strain changes on the surface of the metal structure, and adopting the method of random excitation multi-point response to tap around all stress monitoring points in turn to generate random excitation signals;

[0028] A three-axis fiber Bragg grating strain sensor, arranged at stress monitoring points in the linear region on the surface of the metal structure, for real-time collecting the strain at each stress monitoring point in the linear region to obtain time history strain data at each stress monitoring point in the linear region;

[0029] A long gauge fiber Bragg grating strain sensor, arranged at stress monitoring points in the circular region or irregular region on the surface of the metal structure, for real-time collecting the strain at each stress monitoring point in the circular region or irregular region to obtain time history strain data at each stress monitoring point in the circular region or irregular region;

[0030] The monitoring platform is also connected to the three-axis fiber Bragg grating strain sensor and the long gauge fiber Bragg grating strain sensor. The monitoring platform is further used for determining strain modal parameters of each stress monitoring point based on the frequency domain decomposition method according to the time history strain data at each stress monitoring point, determining whether damage occurs at each corresponding stress monitoring point according to the strain modal parameters of each stress monitoring point, and determining the damage degree according to the strain modal parameters of the stress monitoring points where damage occurs.

[0031] Optionally, the distributed fiber optic strain sensor is fixed on the surface of the metal structure in a serpentine manner.

[0032] Optionally, the long-gauge fiber Bragg grating strain sensor is encapsulated with a chip-type carbon fiber substrate and is arranged at the stress monitoring point in the linear region on the surface of the metal structure by spot welding; the three-axis fiber Bragg grating strain sensor is encapsulated in a bridge form and is arranged at the stress monitoring point in the linear region on the surface of the metal structure by stud welding.

[0033] Optionally, the gauge length of the long-gauge fiber Bragg grating strain sensor is 60 mm.

[0034] Optionally, the metal structure damage identification system for large-scale loading and unloading machinery and equipment further includes:

[0035] a fiber Bragg grating temperature sensor, arranged on the surface of the metal structure for real-time detection of the surface temperature of the metal structure;

[0036] The monitoring platform is also connected to the fiber Bragg grating temperature sensor, and the monitoring platform is also used to compensate the strain at each stress monitoring point according to the surface temperature of the metal structure.

[0037] According to the specific embodiments provided by the present invention, the following technical effects are disclosed by the present invention:

[0038] The present invention uses a distributed fiber optic strain sensor to collect the continuous strain changes on the surface of the metal structure, determines the stress monitoring points according to the continuous strain changes, improves the accuracy of the stress monitoring points, and uses a combination of a three-axis fiber Bragg grating strain sensor and a long-gauge fiber Bragg grating strain sensor to collect the strain at each stress monitoring point to obtain the time history strain data at each stress monitoring point, and then determines the strain modal parameters of each stress monitoring point based on the frequency domain decomposition method, and further determines the damage location and damage degree of the metal structure, realizing the accurate real-time online monitoring of the stress of the metal structure during the operation of large-scale loading and unloading machinery and equipment, and improving the accuracy of metal structure damage identification. Description of the Drawings

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0040] Figure 1 is a flowchart of the method for identifying damage to the metal structure of large-scale loading and unloading machinery and equipment of the present invention;

[0041] Figure 2 is a schematic diagram of the third-order modal shape difference curve;

[0042] Figure 3Schematic diagram of the metal structure damage identification system for large-scale loading and unloading machinery and equipment of the present invention;

[0043] Figure 4 Schematic diagram of the positions of distributed fiber optic strain sensors.

[0044] Symbol description:

[0045] Distributed fiber optic strain sensor - 1, triaxial fiber Bragg grating strain sensor - 2, long gauge fiber Bragg grating strain sensor - 3, monitoring platform - 4, distributed fiber optic analyzer - 5, fiber optic jumper - 6. Specific implementation manners

[0046] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0047] The purpose of the present invention is to provide a method and system for identifying metal structure damage of large-scale loading and unloading machinery and equipment, which combines distributed fiber optic strain sensors, triaxial fiber Bragg grating strain sensors and long gauge fiber Bragg grating strain sensors to realize online real-time monitoring of metal structure damage of large-scale loading and unloading machinery and equipment (such as cranes), and solve the problems of inaccurate monitoring points and unreliable monitoring results.

[0048] To make the above objects, features and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0049] Embodiment 1

[0050] As Figure 1 shown, this embodiment provides a method for identifying metal structure damage of large-scale loading and unloading machinery and equipment, including:

[0051] S1: During a set period, collect continuous strain changes on the surface of the metal structure through a distributed fiber optic strain sensor, and determine stress monitoring points based on the continuous strain changes. Preferably, the distributed fiber optic strain sensor is fixed on the surface of the metal structure in a serpentine manner.

[0052] Specifically, a distributed fiber optic strain sensor is fixed on the surface of the dangerous parts of the metal structure of large loading and unloading machinery and equipment (such as cranes) in a serpentine manner, and the continuous strain changes on the surface of the metal structure during 6 cycle periods of test conditions including no-load and full-load are collected to determine the general location and scope of damage monitoring. The stress monitoring points are determined based on the positions where the parallel positions of the data collected in the serpentine distribution are relatively large to improve the accuracy of the stress monitoring points. Among them, the distributed fiber optic strain sensor is based on the Brillouin mechanism.

[0053] S2: In the way of random excitation and multi-point response, tap around all the stress monitoring points in turn to generate random excitation signals, and at the same time, collect the strain at each stress monitoring point in real time through the three-way fiber Bragg grating strain sensor and the long-gauge fiber Bragg grating strain sensor to obtain the time history strain data at each stress monitoring point.

[0054] Among them, the long-gauge fiber Bragg grating strain sensor is arranged at the stress monitoring points in the linear area on the surface of the metal structure, and the three-way fiber Bragg grating strain sensor is arranged at the stress monitoring points in the circular area or irregular area on the surface of the metal structure. That is, the long-gauge fiber Bragg grating strain sensor is arranged in the relatively spacious area on the surface of the metal structure, and the three-way fiber Bragg grating strain sensor is arranged in the irregular (narrow) position. The strain of the dangerous key area is obtained through the three-way fiber Bragg grating strain sensor and the long-gauge fiber Bragg grating strain sensor.

[0055] To adapt to long-term monitoring, the long-gauge fiber Bragg grating strain sensor and the three-way fiber Bragg grating strain sensor are fixed on the surface of the metal structure of large loading and unloading machinery and equipment by spot welding.

[0056] S3: According to the time history strain data at each stress monitoring point, determine the strain modal parameters at each stress monitoring point based on the frequency domain decomposition method. The strain modal parameters include natural frequency, damping ratio and strain modal vibration mode.

[0057] Specifically, for any stress monitoring point, perform Fourier transform on the time history strain data at the stress monitoring point and add a Hanning window to obtain the spectrum data of the stress monitoring point. According to the spectrum data of the stress monitoring point, determine the strain modal parameters of the stress monitoring point by using the strain frequency response function. Specifically, construct the strain frequency response function based on the spectrum data, and use the strain frequency response function to solve the natural frequency, damping ratio and strain modal vibration mode. Among them, the peak method is used to determine the natural frequency, the root mean square of the auto-power spectral density of the strain monitoring point (determined by Fourier transform) and the auto-power spectral density of the reference point (a determinable point selected next to the strain monitoring point) is used to determine the strain amplitude, and the phase is determined by the real part of the strain frequency response function.

[0058] The present invention performs strain modal parameter identification based on the frequency domain decomposition method. The maximum value of the strain amplitude of the stress monitoring points corresponding to each order of mode is used as the normalization factor value. The strain amplitude of each stress monitoring point is compared with the normalization factor value to obtain the strain modal shape. The positive and negative of the modal shape of each measuring point are determined by the phase angle (positive for 0° to 180°, negative for -180° to 0°).

[0059] S4: Determine whether damage occurs at each stress monitoring point according to the strain modal parameters of each stress monitoring point, and determine the degree of damage according to the strain modal parameters of the stress monitoring points where damage occurs.

[0060] Specifically, S4 includes: For any stress monitoring point, calculate the difference between the strain modal shape of the stress monitoring point and the strain modal shape of the healthy structure to obtain the modal shape difference of the stress monitoring point. If the modal shape difference of the stress monitoring point is greater than the set threshold, damage occurs at the stress monitoring point, otherwise no damage occurs at the stress monitoring point. When damage occurs at the stress monitoring point, determine the degree of damage at the stress monitoring point according to the modal shape difference of the stress monitoring point.

[0061] In this embodiment, the third-order modal shape is taken. When a significant mutation occurs in the strain modal shape difference of a certain order, it is considered that damage may occur at this position, and the magnitude of the mutation may be used to judge the degree of damage. Determine the possible position of structural damage according to the maximum absolute value of the difference between the strain modal shapes of the damaged and healthy structures, and judge the degree of damage according to the magnitude of the modal shape difference. The specific steps are as follows: Subtract the strain modal shape under the damaged condition from the strain modal shape under the undamaged condition. When the mutation amplitude of the third-order modal shape difference curve is greater than 80%, determine that this position is the possible position of damage. The degree of damage can be initially determined according to the mutation amplitude greater than 100% and 150%, as Figure 2 shown, the dotted line in the third-order modal shape difference curve represents the mutation, and the solid line represents normal.

[0062] In order to further improve the accuracy of damage identification, the method for identifying damage to the metal structure of large-scale loading and unloading machinery and equipment further includes: Real-time detecting the surface temperature of the metal structure through a fiber Bragg grating temperature sensor. Compensate the strain at each stress monitoring point according to the surface temperature.

[0063] The present invention arranges fiber Bragg grating temperature sensors within a set range around the three-axis fiber Bragg grating strain sensor and the long-gauge fiber Bragg grating strain sensor. On the one hand, it realizes temperature compensation for the three-axis fiber Bragg grating strain sensor and the long-gauge fiber Bragg grating strain sensor, and on the other hand, it provides a basis for analyzing the structural stress changes caused by temperature.

[0064] It should be noted that the numbers of the distributed optical fiber strain sensors, three - dimensional fiber Bragg grating strain sensors, long - gauge fiber Bragg grating strain sensors, and fiber Bragg grating temperature sensors provided on the surface of the metal structure of the present invention are all multiple.

[0065] Embodiment 2

[0066] In order to execute the method corresponding to the above - mentioned Embodiment 1 to achieve the corresponding functions and technical effects, a metal structure damage identification system for large - scale loading and unloading machinery and equipment is provided below.

[0067] As Figure 3 shown, the metal structure damage identification system for large - scale loading and unloading machinery and equipment provided in this embodiment includes: a distributed optical fiber strain sensor 1, a three - dimensional fiber Bragg grating strain sensor 2, a long - gauge fiber Bragg grating strain sensor 3, and a monitoring platform 4.

[0068] Among them, the distributed optical fiber strain sensor 1 is arranged on the surface of the metal structure and is used to collect the continuous strain changes on the surface of the metal structure.

[0069] Preferably, the distributed optical fiber strain sensor 1 is fixed on the surface of the dangerous area of the metal structure (such as the boom, guy derrick, turntable, cylinder, lower cross - beam, elephant trunk, main tie rod, secondary tie rod, and the connection between the machine room and the rotating column of a portal crane, etc.) in a serpentine manner. Among them, the connection between the machine room and the rotating column and the connection between the rotating column and the balance beam are arranged circumferentially along the rotating column, and the parts such as the elephant trunk, main tie rod, secondary tie rod, and main boom are arranged linearly. Both the circumferential arrangement and the linear arrangement are arranged in parallel again at an interval of 2 cm.

[0070] When monitoring the cumulative damage of the fillet welds of the main stressed structural members, the distributed optical fiber sensors are arranged in a serpentine manner at positions 1 cm above and below the edges of the fillet welds. When monitoring the cumulative damage at non - weld positions such as the rotating gear ring of the main stressed structural members, the distributed optical fiber strain sensor 1 is arranged circumferentially along the root of the gear ring.

[0071] The distributed optical fiber strain sensor 1 collects the global continuous strain of the dangerous area to determine the regional monitoring position. The distributed optical fiber strain sensor 1 is fixed on the surface of the metal structure in an adhesive form using ordinary optical fiber, and collects the continuous strain changes on the surface of the metal structure for 6 cycle periods under test conditions including no - load and full - load. Analyze the positions where mutations occur in adjacent two monitoring lines or nearby, and at the same time conduct statistical correlation analysis on the strain changes at adjacent positions in 6 cycles. The two are combined to determine the monitoring position and range of the sensor, so as to solve the problem of uncertainty brought by the finite - element analysis and empirical method used in the previous stress monitoring measurement points.

[0072] The three - dimensional fiber Bragg grating strain sensor 2 is arranged at the stress monitoring points in the linear region on the surface of the metal structure, and is used to collect the strain at each stress monitoring point in the linear region in real time, so as to obtain the time - history strain data at each stress monitoring point in the linear region.

[0073] The long - gauge fiber Bragg grating strain sensor 3 is arranged at the stress monitoring points in the circular region or irregular region on the surface of the metal structure, and is used to collect the strain at each stress monitoring point in the circular region or irregular region in real time, so as to obtain the time - history strain data at each stress monitoring point in the circular region or irregular region.

[0074] In this embodiment, the long - gauge fiber Bragg grating strain sensor 3 is encapsulated with a chip - type carbon fiber substrate and is arranged at the stress monitoring points in the linear region on the surface of the metal structure by spot welding. The gauge length of the long - gauge fiber Bragg grating strain sensor 3 is 60 mm. The three - dimensional fiber Bragg grating strain sensor 2 adopts a bridge - type packaging form and is arranged at the stress monitoring points in the linear region on the surface of the metal structure by stud welding. The three - dimensional fiber Bragg grating strain sensor 2 and the long - gauge fiber Bragg grating strain sensor 3 adopt a star - type topological structure. The three - dimensional fiber Bragg grating strain sensor 2 realizes the accurate monitoring of local stress and strain. The long - gauge fiber Bragg grating strain sensor 3 realizes the strain monitoring of key regions.

[0075] The monitoring platform 4 is connected to the distributed fiber optic strain sensor 1, the three - dimensional fiber Bragg grating strain sensor 2 and the long - gauge fiber Bragg grating strain sensor 3 respectively through a transmission network. The monitoring platform 4 is used to determine the stress monitoring points according to the continuous strain changes on the surface of the metal structure, and adopts the method of random excitation and multi - point response to tap around all stress monitoring points in turn to generate random excitation signals. According to the time - history strain data at each stress monitoring point, the strain modal parameters of each stress monitoring point are determined based on the frequency - domain decomposition method. Whether damage occurs at each stress monitoring point is determined according to the strain modal parameters of each stress monitoring point, and the damage degree is determined according to the strain modal parameters of the stress monitoring points where damage occurs.

[0076] In this embodiment, the monitoring platform 4 is a remote visual monitoring platform. The transmission network transmits the real - time strain data to the remote visual monitoring platform online through a DTU (Data Transfer Unit). The remote visual monitoring platform realizes the query, data storage, damage analysis and visual management of the monitoring data of the metal structure of large loading and unloading machinery and equipment, determines the location and damage degree of the damage of the machinery and equipment remotely, and grasps the operation status of the machinery and equipment in real time to ensure the operation safety of the machinery and equipment.

[0077] Furthermore, the metal structure damage identification system for large-scale loading and unloading machinery and equipment also includes an optical fiber signal demodulation subsystem. The optical fiber signal demodulation subsystem is used to demodulate the optical signals collected by the distributed optical fiber strain sensor 1, the three-way fiber Bragg grating strain sensor 2, and the long-gauge fiber Bragg grating strain sensor 3 into digital signals. The optical fiber signal demodulation subsystem includes a distributed optical fiber analyzer 5 and a fiber Bragg grating demodulator. The distributed optical fiber analyzer 5 is based on the Brillouin principle. After the strain monitoring points are determined, the distributed optical fiber analyzer 5 is removed to save costs.

[0078] The long-gauge fiber Bragg grating strain sensor 3 and the three-way fiber Bragg grating strain sensor 2 adopt a double-end form to avoid the problem that the entire chain signal cannot be collected due to the damage of one sensor. The two ends of the three-way fiber Bragg grating strain sensor 2 are respectively fusion-spliced to single-mode armored optical cables, and then connected to the optical fiber signal demodulation subsystem through the optical cables. After the fiber Bragg grating sensor is successfully connected to the optical fiber signal demodulation subsystem, it is calibrated and zeroed, and the demodulated digital signal is transmitted online to the remote visualization management platform through the DTU using the transmission network.

[0079] Furthermore, the metal structure damage identification system for large-scale loading and unloading machinery and equipment also includes a fiber Bragg grating temperature sensor. The fiber Bragg grating temperature sensor is arranged on the surface of the metal structure and is used to detect the surface temperature of the metal structure in real time. The monitoring platform 4 is also connected to the fiber Bragg grating temperature sensor, and the monitoring platform 4 is also used to compensate the strain at each stress monitoring point according to the surface temperature of the metal structure.

[0080] As a specific implementation method, slightly polish the area near the surface measurement points of the metal structure of the large-scale loading equipment. First, fix and bond one end of the optical fiber at the first position on the surface of the metal structure, and then tighten and fix the second position at an interval of 60 cm. Use a special bonding tool to fix the optical fiber on the surface of the metal structure, and bond the third position, ……, the nth position in the same operation sequence. After the layout is completed, connect it to the optical fiber jumper 6 (only in contact with the structure surface, without restraint). The optical fiber jumper 6 walks along the edge to the distributed optical fiber analyzer 5 in the machine room, as Figure 4 shown.

[0081] At the general position and range of the metal structure surface damage monitoring determined by the above method, fiber Bragg grating strain sensors are arranged. Among them, long-gauge fiber Bragg grating strain sensors 3 are arranged at linear parts such as the elephant trunk, large tie rod, small tie rod, and main boom, and three-way fiber Bragg grating strain sensors 2 are arranged at circular parts such as the connection between the machine room and the turntable column and the connection between the turntable column and the balance beam.

[0082] Collect the strain changes at the monitoring positions, and achieve accurate monitoring of the stress and strain at the dangerous parts of the metal structure of large-scale loading and unloading equipment. Based on the strains collected by the long-gauge fiber Bragg grating strain sensors 3 and the three-directional fiber Bragg grating strain sensors 2, the random excitation multi-point response method is adopted. Tap around all the strain monitoring points in turn to generate random excitation signals. Based on the frequency domain decomposition method, identify the strain modal parameters, and take the fourth-order modal shape. When there is an obvious mutation in the modal shape at a certain stage, it is considered that damage may occur at this position, and the magnitude of the mutation can judge the degree of damage.

[0083] The present invention adopts a combination of three-directional point-type fiber Bragg grating strain sensors and long-gauge fiber Bragg grating strain sensors to collect the strain and modal changes in the dangerous key areas. Based on the online monitoring data, analyze the damage position and degree of the metal structure, realize accurate real-time online monitoring of the stress of the metal structure during the operation of large-scale loading and unloading machinery and equipment, and timely alarm and display the abnormal state and abnormal area.

[0084] In this specification, each embodiment is described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. For the same and similar parts among the embodiments, reference can be made to each other.

[0085] In this article, specific examples are used to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A method for identifying metal structure damage of large-scale loading and unloading machinery and equipment, characterized in that, The method for identifying metal structure damage of large-scale loading and unloading machinery and equipment includes: Within a set period, continuously collect the strain changes on the surface of the metal structure through distributed fiber optic strain sensors, and determine stress monitoring points based on the continuous strain changes; fix the distributed fiber optic strain sensors on the surface of the dangerous parts of the metal structure of large-scale loading and unloading machinery and equipment in a serpentine manner, collect the continuous strain changes on the surface of the metal structure within 6 cycle periods of test conditions including no-load and full-load, and determine the general location and scope of damage monitoring; determine stress monitoring points based on the relatively large parallel positions of the data collected in the serpentine distribution. Adopt the method of random excitation and multi-point response, tap around all stress monitoring points in turn to generate random excitation signals, and at the same time collect the strain at each stress monitoring point in real time through three-axis fiber Bragg grating strain sensors and long-gauge fiber Bragg grating strain sensors to obtain the time history strain data at each stress monitoring point; the long-gauge fiber Bragg grating strain sensors are arranged at the stress monitoring points in the linear area on the surface of the metal structure, and the three-axis fiber Bragg grating strain sensors are arranged at the stress monitoring points in the circular area or irregular area on the surface of the metal structure. Based on the time history strain data at each stress monitoring point, determine the strain modal parameters of each stress monitoring point based on the frequency domain decomposition method. Determine whether damage occurs at each stress monitoring point according to the strain modal parameters of each stress monitoring point, and determine the degree of damage according to the strain modal parameters of the stress monitoring points where damage occurs.

2. The method for identifying metal structure damage of large-scale loading and unloading machinery and equipment according to claim 1, characterized in that, Based on the time history strain data at each stress monitoring point, determine the strain modal parameters of each stress monitoring point based on the frequency domain decomposition method, specifically including: For any stress monitoring point, perform Fourier transform on the time history strain data at the stress monitoring point and add a Hanning window to obtain the spectrum data of the stress monitoring point. According to the spectrum data of the stress monitoring point, determine the strain modal parameters of the stress monitoring point by using the strain frequency response function.

3. The method for identifying metal structure damage of large-scale loading and unloading machinery and equipment according to claim 1, characterized in that, The strain modal parameters include natural frequency, damping ratio and strain modal vibration mode. Determine whether damage occurs at each stress monitoring point according to the strain modal parameters of each stress monitoring point, and determine the degree of damage according to the strain modal parameters of the stress monitoring points where damage occurs, specifically including: For any stress monitoring point, calculate the difference between the strain modal vibration mode of the stress monitoring point and the strain modal vibration mode of the healthy structure to obtain the vibration mode difference of the stress monitoring point. If the vibration mode difference of the stress monitoring point is greater than the set threshold, damage occurs at the stress monitoring point, otherwise no damage occurs at the stress monitoring point. When damage occurs at the stress monitoring point, determine the degree of damage at the stress monitoring point according to the vibration mode difference of the stress monitoring point.

4. The method for identifying metal structure damage of large-scale loading and unloading machinery and equipment according to claim 1, characterized in that, The method for identifying metal structure damage of large-scale loading and unloading machinery and equipment further includes: Real-time detect the surface temperature of the metal structure through fiber Bragg grating temperature sensors. Compensate the strain at each stress monitoring point according to the surface temperature.

5. A system for identifying metal structure damage of large-scale loading and unloading machinery and equipment, characterized in that, The system for identifying metal structure damage of large-scale loading and unloading machinery and equipment includes: Distributed fiber optic strain sensors, arranged on the surface of the metal structure, used to collect continuous strain changes on the surface of the metal structure. Monitoring platform, connected to the distributed fiber optic strain sensor, is used to determine stress monitoring points according to the continuous strain changes on the surface of the metal structure, and adopts the method of random excitation multi-point response to tap around all stress monitoring points in turn to generate random excitation signals; among them, the distributed fiber optic strain sensor is fixed on the surface of the dangerous parts of the metal structure of large loading and unloading machinery and equipment in a snake shape, and the continuous strain changes on the surface of the metal structure within 6 cycle periods of test conditions including no-load and full-load are collected to determine the general location and scope of damage monitoring; the stress monitoring points are determined according to the positions with relatively large parallel positions of the data collected in the snake shape distribution. Three-axis fiber Bragg grating strain sensor, arranged at the stress monitoring points in the circular area or irregular area on the surface of the metal structure, is used to collect the strain at each stress monitoring point in the circular area or irregular area in real time to obtain the time history strain data at each stress monitoring point in the circular area or irregular area. Long gauge fiber Bragg grating strain sensor, arranged at the stress monitoring points in the linear area on the surface of the metal structure, is used to collect the strain at each stress monitoring point in the linear area in real time to obtain the time history strain data at each stress monitoring point in the linear area. The monitoring platform is also connected to the three-axis fiber Bragg grating strain sensor and the long gauge fiber Bragg grating strain sensor. The monitoring platform is also used to determine the strain modal parameters of each stress monitoring point based on the frequency domain decomposition method according to the time history strain data at each stress monitoring point, determine whether damage occurs at each stress monitoring point according to the strain modal parameters of each stress monitoring point, and determine the degree of damage according to the strain modal parameters of the stress monitoring points where damage occurs.

6. The system for identifying metal structure damage of large-scale loading and unloading machinery and equipment according to claim 5, characterized in that, The long gauge fiber Bragg grating strain sensor is encapsulated with a chip-type carbon fiber substrate and is arranged at the stress monitoring points in the linear area on the surface of the metal structure by spot welding; the three-axis fiber Bragg grating strain sensor adopts a bridge-type packaging form and is arranged at the stress monitoring points in the linear area on the surface of the metal structure by stud welding.

7. The system for identifying metal structure damage of large-scale loading and unloading machinery and equipment according to claim 5, characterized in that, The gauge length of the long gauge fiber Bragg grating strain sensor is 60 mm.

8. The system for identifying metal structure damage of large-scale loading and unloading machinery and equipment according to claim 5, characterized in that, The metal structure damage identification system of the large loading and unloading machinery and equipment further includes: Fiber Bragg grating temperature sensor, arranged on the surface of the metal structure, is used to detect the surface temperature of the metal structure in real time. The monitoring platform is also connected to the fiber Bragg grating temperature sensor. The monitoring platform is also used to compensate the strain at each stress monitoring point according to the surface temperature of the metal structure.

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