Distributed intelligent monitoring system and method for strain of large steel structure beam

Abstract

The invention provides a large-scale steel structure beam strain distributed intelligent monitoring system and method, and relates to the technical field of large-scale steel structure monitoring. The system comprises a welding type strain gauge used for detecting the stress state of the bridge erecting machine, a data acquisition unit used for acquiring signals of the welding type strain gauge, and a protection module used for guaranteeing stable operation of equipment in an outdoor environment, the data transmission unit is used for transmitting the collected signals of the welding type strain gauge to the data analysis and diagnosis module through a 5G network; and the data analysis and diagnosis module is used for analyzing and processing the collected signals of the welding type strain gauge so as to monitor the working state of the bridge erecting machine. The welding type strain gauges are installed at key parts of the bridge girder erection machine, stress data are collected and analyzed in real time, comprehensive monitoring of the working state of the bridge girder erection machine is achieved, potential safety hazards are found in time, and the safety and efficiency of railway construction are improved.

Description

Technical Field

[0001] This invention relates to the field of large steel structure monitoring technology, and more particularly to a distributed intelligent monitoring system and method for strain monitoring of large steel structure beams. Background Technology

[0002] Large steel beams, such as those used in bridge erecting machines, are indispensable key structural components in modern engineering, widely used in infrastructure construction such as railways and highways. These structural components typically need to withstand enormous loads and complex stress environments, and their safety and stability directly affect the safe operation of the entire project. Therefore, real-time monitoring of the strain state of large steel beams is of great significance for preventing structural failures and ensuring construction safety.

[0003] Traditional strain monitoring of large steel beams relies primarily on periodic manual inspections. While this method can detect potential structural problems to some extent, it has several limitations. Manual inspections require regular on-site checks by professionals, resulting in low efficiency and high labor costs. Furthermore, manual inspections cannot provide real-time monitoring of the structure, making it difficult to promptly detect sudden structural issues. In extreme environmental conditions, such as high temperatures, low temperatures, and high vibrations, the accuracy and reliability of manual inspections are also questionable. In recent years, with the development of sensor and automation technologies, some online monitoring systems have begun to be applied to strain monitoring of large steel beams. However, these systems mostly suffer from high installation costs, susceptibility to signal interference, limited environmental limitations, and inconvenient maintenance.

[0004] Existing strain monitoring technologies for large steel structure beams suffer from the following drawbacks: First, low detection efficiency, failing to achieve real-time structural monitoring and hindering timely detection of sudden structural problems; second, high labor costs, relying on periodic manual inspections requiring significant manpower and time investment; third, insufficient reliability and adaptability of the monitoring system, making it difficult to guarantee stability and accuracy under complex environmental conditions such as extreme temperatures and high vibrations; and fourth, high installation and maintenance costs, with traditional online monitoring systems incurring high installation costs, signal susceptibility to interference, and inconvenient subsequent system maintenance when measurement points are geographically dispersed. These problems limit the widespread application of strain monitoring technologies for large steel structure beams. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a distributed intelligent monitoring system and method for strain monitoring of large steel structure beams. By installing welded strain gauges at key locations on the bridge erecting machine, this invention collects and analyzes stress data in real time, enabling comprehensive monitoring of the machine's operating status, timely detection of potential safety hazards, and improved safety and efficiency in railway construction.

[0006] The technical means employed in this invention are as follows:

[0007] A distributed intelligent monitoring system for strain of large steel structure beams, comprising:

[0008] Welded strain gauges are used to detect the stress state of bridge erecting machines;

[0009] The protection module is used to ensure the stable operation of the equipment in outdoor environments;

[0010] The data acquisition unit is used to acquire signals from the welded strain gauge.

[0011] The data transmission unit is used to transmit the acquired signals from the welded strain gauge to the data analysis and diagnostic module via a 5G network;

[0012] The data analysis and diagnostic module is used to analyze and process the signals collected by the welded strain gauges. It performs time-domain feature extraction, frequency-domain characteristic analysis, and fault mode identification on a large number of stress signals collected by the welded strain gauges in order to monitor the working status of the bridge erecting machine.

[0013] Furthermore, based on the structural characteristics and actual working conditions of the bridge erecting machine, the welded strain gauge is welded to the surface of the bridge erecting machine's steel structure, as follows:

[0014] After the bridge erecting machine's front trolley picks up the beam, the beam transport vehicle simultaneously carries the beam and moves to the center line of the span when the front trolley reaches the center line. The strain gauge is welded to the lower surface of the lower cover plate along the direction of the main beam. This position is the first test point.

[0015] When the beam is fed to the beam-taking position of the rear trolley, the rear trolley is located behind the middle support leg. After the hook is fully lifted, the strain gauge is welded to the side plate of the second column bend arm. Along the direction of the bend, this position is the second test point.

[0016] When the bridge erecting machine is in the span-crossing state, the front outrigger is retracted and the front end structure of the middle outrigger is in a suspended state. The strain gauge is welded to the top of the main web plate. This position is the third test point.

[0017] Strain gauges are welded to the upper cover plate at the mid-span of the main beam to monitor the stress state at the mid-span of the main beam. This position is the fourth test point.

[0018] Strain gauges are welded to the cover plate at the root of the cantilever to monitor the stress state at the root of the cantilever; this location is the fifth test point.

[0019] Strain gauges are welded at the curved arm of the middle support leg at the beam drop position to monitor the stress state at the beam drop position; this position is the sixth test point.

[0020] Furthermore, the stress state of the structure can be reflected by the deformation of the steel structure, as follows:

[0021] At the first test point, the lower cover plate was under tension during the beam removal and transportation process. Welded strain gauges were welded to the lower surface of the lower cover plate to directly reflect the tensile stress at that location.

[0022] At the second test point, the No. 2 column arm bears a large load when the rear trolley picks up the beam. It is under compression on the inside and tension on the outside. The welded strain gauge is welded directly above the side plate of the arm to reflect the stress concentration at this part.

[0023] At the third test point, the main web plate is subjected to a large bending moment in the through-hole state. A welded strain gauge is welded directly above the main web plate to reflect the tensile stress at this part.

[0024] At the fourth test point, the upper cover plate at the mid-span of the main beam is under compression when the main beam is under stress. Welded strain gauges are welded to the upper cover plate to reflect the compressive stress at this location.

[0025] At the fifth test point, the upper cover plate at the root of the cantilever is subjected to a large bending moment in the through-hole state. A welded strain gauge is welded to the upper cover plate to reflect the tensile stress at this part.

[0026] At the sixth test point, the middle outrigger arm bears a large load when the beam is lowered. Welded strain gauges are welded to the outrigger arm to reflect the stress concentration at this location.

[0027] Furthermore, the data acquisition unit includes multiple acquisition units and a controller. The acquisition units are used to acquire signals from the welded strain gauges, and the controller is used to manage and transmit the signals acquired by the acquisition units, wherein:

[0028] The data acquisition unit is a modular design, with each data acquisition unit supporting 4 signal inputs and each data acquisition unit controlling up to 4 of the welded strain gauges;

[0029] The controller supports 4 bus signal inputs, and a single bus can support up to 8 data acquisition devices.

[0030] Furthermore, the data collector and the controller communicate via an RS485 bus, and the distance between the controller and the data collector can be extended to 300 meters.

[0031] Furthermore, the protection module includes a cabinet, a metal cable protection pipe, and a temperature and humidity monitoring unit. The data acquisition unit, controller, and 5G communication unit are integrated in the cabinet. The shielded cable is run through the metal cable protection pipe. The temperature and humidity monitoring unit uses a digital sensor SHT35 connected to a microcontroller STM32F103ZET6 to display the collected temperature and humidity data in real time on the serial port.

[0032] Furthermore, the data analysis and diagnosis module includes:

[0033] The data receiving and processing module is used to receive strain data transmitted by the data acquisition unit and perform real-time analysis and processing of the strain data, including time-domain feature extraction and frequency-domain characteristic analysis.

[0034] The fault identification and early warning module is used to identify faults and issue early warning signals for stress states that exceed the preset stress thresholds.

[0035] The data storage module is used to store the processed data for subsequent analysis and querying.

[0036] This invention also provides a method for distributed intelligent monitoring of strain in large steel structure beams based on the aforementioned distributed intelligent monitoring system, comprising the following steps:

[0037] S1. Perform finite element stress simulation analysis on large steel structure beams, and determine the location distribution of strain monitoring points based on actual working conditions;

[0038] S2. Based on the determined location of the strain monitoring point, the welded strain gauge is welded to the corresponding position on the steel structure of the bridge erecting machine;

[0039] S3. Design a distributed data acquisition unit, including a modular acquisition unit and a controller. The acquisition unit and the controller communicate via an RS485 bus to acquire and transmit strain data from monitoring points in real time.

[0040] S4. The data analysis and diagnosis module receives strain data transmitted by the distributed data acquisition unit and performs time-domain feature extraction, frequency-domain characteristic analysis, and fault mode identification on the strain data to monitor the working status of the bridge erecting machine.

[0041] Furthermore, the distributed intelligent monitoring method for strain of large steel structure beams also includes:

[0042] The steps for conducting stress tests on large steel structure beams of different models and service lives, comparing and analyzing stress distribution under different working conditions, and optimizing the layout of monitoring points are as follows.

[0043] Compared with the prior art, the present invention has the following advantages:

[0044] 1. This invention provides a distributed intelligent monitoring system for strain in large steel structure beams. By installing welded strain gauges at key stress points of the bridge erecting machine, it can monitor the stress state of the machine under different working conditions in real time and transmit the collected data to the data analysis and diagnosis module for analysis and processing. The early warning module in the data analysis and diagnosis module can issue early warning signals for stress states exceeding preset stress thresholds, enabling technicians to promptly identify potential safety hazards and take corresponding measures to avoid accidents, thereby significantly improving the operational safety of the bridge erecting machine.

[0045] 2. The large-scale steel structure beam strain distributed intelligent monitoring system provided by this invention realizes real-time and automatic monitoring of the working status of the bridge erecting machine, eliminating the need for frequent manual intervention and greatly improving detection efficiency. At the same time, it reduces the equipment, manpower, and time costs required for manual inspection, lowering the overall inspection cost and demonstrating significant economic benefits.

[0046] 3. This invention provides a distributed intelligent strain monitoring system for large steel structure beams. Through finite element analysis of the structural characteristics and actual working conditions of the bridge erecting machine, and combined with the actual stress conditions, the system determines the location distribution of six strain monitoring points. This optimized layout of monitoring points can more comprehensively and accurately reflect the overall stress state of the bridge erecting machine, avoiding the blindness and incompleteness of monitoring point selection in traditional methods, improving the reliability and accuracy of monitoring results, and providing a more scientific basis for the safety assessment and maintenance of the bridge erecting machine.

[0047] 4. The large-scale steel structure beam strain distributed intelligent monitoring system provided by this invention utilizes welded strain gauges that are tightly bonded to the object surface, making them more suitable for long-term monitoring. Furthermore, its operating temperature range is -10℃ to +60℃, and its protection level reaches IP67, meeting the monitoring needs of bridge erecting machines in harsh environments. Simultaneously, the controller of the data acquisition unit uses the DH5971N from Donghua Testing, which has a high protection level (IP65) and stable performance, ensuring reliable operation of the entire monitoring system in harsh environments and improving the system's environmental adaptability.

[0048] 5. This invention provides a distributed intelligent monitoring system for strain in large steel structure beams. The data acquisition unit adopts a modular design, with each data acquisition unit constituting a module. When a module fails, only the data acquisition unit needs to be replaced, greatly improving system maintenance efficiency and reducing maintenance difficulty and cost. Furthermore, the controller and data acquisition unit communicate via an RS485 bus. Multiple controllers support synchronous expansion, and the expansion distance between the controller and the furthest data acquisition unit can reach 300 meters. This distributed online monitoring system design allows for convenient expansion and upgrades according to actual needs, exhibiting excellent scalability and flexibility. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a general block diagram of the system of the present invention.

[0051] Figure 2 This is a schematic diagram of a bridge erecting machine provided in an embodiment of the present invention.

[0052] Figure 3 This is a schematic diagram of the bridge erecting machine construction process provided in an embodiment of the present invention.

[0053] Figure 4 This invention provides a finite element analysis and monitoring point location for the bridge erecting machine after the trolley removes the beam, as provided in an embodiment of the invention.

[0054] Figure 5 This invention provides a finite element analysis and monitoring point location for the bridge erecting machine's rear trolley after beam removal, as provided in an embodiment of the invention.

[0055] Figure 6 This provides a finite element analysis and monitoring point location under the through-hole condition provided in an embodiment of the present invention.

[0056] Figure 7 This is a schematic diagram showing the distribution of strain monitoring points on a bridge erecting machine, as provided in an embodiment of the present invention. Detailed Implementation

[0057] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0058] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0059] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0060] like Figure 1 As shown, this invention provides a distributed intelligent monitoring system for strain of large steel structure beams, comprising:

[0061] Welded strain gauges are used to detect the stress state of bridge erecting machines. In this embodiment, the operating temperature of each welded strain sensor is -10℃ to 60℃, supporting "on-the-spot testing after welding".

[0062] The data acquisition unit is used to acquire signals from the welded strain gauge.

[0063] The protection module is used to ensure the stable operation of the equipment in outdoor environments;

[0064] The data transmission unit is used to transmit the acquired signals from the welded strain gauge to the data analysis and diagnostic module via a 5G network;

[0065] The data analysis and diagnostic module is used to extract time-domain features, analyze frequency-domain characteristics, and identify fault modes from the signals acquired by the welded strain gauges in order to monitor the working status of the bridge erecting machine.

[0066] In a specific implementation, as a preferred embodiment of the present invention, the welded strain gauge is welded to the surface of the steel structure of the bridge erecting machine, based on the structural characteristics and actual working conditions of the bridge erecting machine, as follows:

[0067] After the bridge erecting machine's front trolley picks up the beam, the beam transport vehicle simultaneously carries the beam and moves to the center line of the span when the front trolley reaches the center line. The strain gauge is welded to the lower surface of the lower cover plate along the direction of the main beam. This position is the first test point.

[0068] When the beam is fed to the beam-taking position of the rear trolley, the rear trolley is located behind the middle support leg. After the hook is fully lifted, the strain gauge is welded to the side plate of the second column bend arm. Along the direction of the bend, this position is the second test point.

[0069] When the bridge erecting machine is in the span-crossing state, the front outrigger is retracted and the front end structure of the middle outrigger is in a suspended state. The strain gauge is welded to the top of the main web plate. This position is the third test point.

[0070] Strain gauges are welded to the upper cover plate at the mid-span of the main beam to monitor the stress state at the mid-span of the main beam. This position is the fourth test point.

[0071] Strain gauges are welded to the cover plate at the root of the cantilever to monitor the stress state at the root of the cantilever; this location is the fifth test point.

[0072] Strain gauges are welded at the curved arm of the middle support leg at the beam drop position to monitor the stress state at the beam drop position; this position is the sixth test point.

[0073] In this embodiment, as Figure 2 As shown, the No. 1 trolley picks up the beam and moves forward synchronously with it, while the No. 2 trolley picks up the beam and feeds it synchronously. The beam is then lowered into place. Based on the structural characteristics of the bridge erecting machine and its actual working conditions, finite element analysis and stress analysis under actual working conditions are performed as follows:

[0074] After the bridge erecting machine's front trolley picks up the beam, the beam transport vehicle synchronously carries the beam to the center line of the span. At this point, the stress is greatest, with the upper cover plate under compression and the lower cover plate under tension. Since the tensile strength is lower than the compressive strength, strain gauges are welded to the lower surface of the lower cover plate, along the direction of the main beam. Finite element analysis and monitoring point locations after the bridge erecting machine's front trolley picks up the beam are shown below. Figure 3 As shown.

[0075] When the beam is fed to the rear trolley's beam-retrieving position, the rear trolley is located behind the middle support leg. After the hook-and-lift operation is complete, the second leg will bear a significant load. This will result in substantial stress concentration at the bend of the second column. The inner side of the bend of the second column is under compression, and the outer side is under tension. Stress test points are arranged directly above the side plate, along the direction of the bend. Finite element analysis and monitoring point locations after the bridge erecting machine's rear trolley retrieves the beam are shown below. Figure 4 As shown.

[0076] With the bridge erecting machine's front outrigger retracted and the front end of the middle outrigger suspended in mid-air, the upper cover plate at the front of the middle outrigger of the main beam is subjected to tensile stress. Stress testing points are located directly above the main web plate. Finite element analysis and monitoring point locations under the bridge erecting condition are as follows: Figure 5 As shown.

[0077] Based on the structural characteristics and actual working conditions of the bridge erecting machine, a stress analysis was conducted, and six strain monitoring points were established. The location distribution of the strain monitoring points of the bridge erecting machine is shown below. Figure 6 As shown.

[0078] In a specific implementation, as a preferred embodiment of the present invention, the stress state of the structure is reflected by the deformation of the steel structure, as follows:

[0079] At the first test point, the lower cover plate was under tension during the beam removal and transportation process. Welded strain gauges were welded to the lower surface of the lower cover plate to directly reflect the tensile stress at that location.

[0080] At the second test point, the No. 2 column arm bears a large load when the rear trolley picks up the beam. It is under compression on the inside and tension on the outside. The welded strain gauge is welded directly above the side plate of the arm to reflect the stress concentration at this part.

[0081] At the third test point, the main web plate is subjected to a large bending moment in the through-hole state. A welded strain gauge is welded directly above the main web plate to reflect the tensile stress at this part.

[0082] At the fourth test point, the upper cover plate at the mid-span of the main beam is under compression when the main beam is under stress. Welded strain gauges are welded to the upper cover plate to reflect the compressive stress at this location.

[0083] At the fifth test point, the upper cover plate at the root of the cantilever is subjected to a large bending moment in the through-hole state. A welded strain gauge is welded to the upper cover plate to reflect the tensile stress at this part.

[0084] At the sixth test point, the middle outrigger arm bears a large load when the beam is lowered. Welded strain gauges are welded to the outrigger arm to reflect the stress concentration at this location.

[0085] In specific implementation, as a preferred embodiment of the present invention, such as Figure 7 As shown, the data acquisition unit includes multiple acquisition units and a controller. The acquisition units are used to acquire signals from the welded strain gauges, and the controller is used to manage and transmit the signals acquired by the acquisition units.

[0086] The data acquisition unit is a modular design, with each data acquisition unit supporting 4 signal inputs and each data acquisition unit controlling up to 4 of the welded strain gauges;

[0087] The controller supports four bus signal inputs, and each bus can support up to eight data acquisition devices. In this embodiment, the controller parameters are shown in Table 1 below:

[0088] Table 1 Controller Parameters

[0089]

[0090] In a specific implementation, as a preferred embodiment of the present invention, the protection module includes a cabinet, a metal cable protection pipe, and a temperature and humidity monitoring unit. The data acquisition unit, controller, and 5G communication unit are integrated in the cabinet. The shielded cable is run through the metal cable protection pipe. The temperature and humidity monitoring unit uses a digital sensor SHT35 connected to a microcontroller STM32F103ZET6 to display the collected temperature and humidity data in real time in the serial port.

[0091] In a preferred embodiment of this invention, the data acquisition unit communicates with the controller via an RS485 bus, and the distance between the controller and the data acquisition unit can be extended to 300 meters. In this embodiment, the data acquisition unit can adapt to monitoring a series of physical quantities such as strain, stress, displacement, temperature, and vibration under harsh environments such as frequent thunderstorms, electromagnetic radiation, and large temperature variations. By monitoring stress parameters in real time, it achieves comprehensive monitoring of the bridge erecting machine's working status. Simultaneously, combined with data transmission and processing technology, the collected pressure data is transmitted in real time to the data analysis and diagnostic module for analysis and processing, so as to promptly detect potential safety hazards and fault risks.

[0092] In a specific implementation, as a preferred embodiment of the present invention, the data analysis and diagnosis module includes:

[0093] The data receiving module is used to receive strain data transmitted by the data acquisition unit;

[0094] The protection module is used to ensure the stable operation of the equipment in outdoor environments;

[0095] The data processing module is used to perform real-time analysis and processing of strain data, including data filtering, feature extraction and stress calculation. In this embodiment, by comparing real-time monitoring data with the fault information database, the automatic identification of faults such as stress concentration and abnormal deformation is realized, and it supports the import of 2D / 3D models to intuitively display the distribution of measuring points and strain status.

[0096] The data storage module is used to store the processed data for subsequent analysis and querying.

[0097] The early warning module is used to issue early warning signals for stress states exceeding preset stress thresholds. In this embodiment, two levels of early warning thresholds are configured to issue early warning signals based on analysis and diagnostic results. Specifically, a strain threshold is preset based on the structural beam material properties and design standards. A yellow warning is triggered when the monitored value reaches 80% of the threshold, and a red warning is triggered when it reaches 100%. On-site alarms are triggered via audible and visual devices, and early warning information is pushed remotely via SMS, email, and an app. Alarm records are automatically stored in the system log for easy traceability.

[0098] The communication module is used for data communication with external devices, such as sending analysis results to the monitoring terminal.

[0099] This invention also provides a method for distributed intelligent monitoring of strain in large steel structure beams based on the aforementioned distributed intelligent monitoring system for strain in large steel structure beams, comprising the following steps:

[0100] S1. Perform finite element stress simulation analysis on large steel structure beams, and determine the location distribution of strain monitoring points based on actual working conditions;

[0101] S2. Based on the determined location of the strain monitoring point, the welded strain gauge is welded to the corresponding position on the steel structure of the bridge erecting machine;

[0102] S3. Design a distributed data acquisition unit, including a modular acquisition unit and a controller. The acquisition unit and the controller communicate via an RS485 bus to acquire and transmit strain data from monitoring points in real time.

[0103] S4. The data analysis and diagnosis module receives strain data transmitted by the distributed data acquisition unit and performs time-domain feature extraction, frequency-domain characteristic analysis, and fault mode identification on the strain data to monitor the working status of the bridge erecting machine.

[0104] In this embodiment, the equilibrium state is obtained under the bridge erection machine's beam erection condition when unloaded. The front trolley picks up the beam and feeds it synchronously to the center line of the main beam's span, recording the real-time stress peak value. The rear trolley picks up the beam behind the middle support leg. When fully lifted, the middle support leg bears a large load, and the real-time stress peak value at the middle support leg's bend is recorded. The front and rear trolleys synchronously feed the beam to the beam placement position and simultaneously place it to the pier. The front and rear trolleys unload, and the real-time stress value at this time is recorded. Under the bridge erection machine's span-crossing condition, the equilibrium state is obtained when the bridge erection machine is unloaded. The entire machine moves longitudinally one span position, the front support leg is raised, and it is driven forward to the next pier position. At this time, the root of the cantilever bears the maximum bending moment, and the real-time stress peak value at this time is recorded. The real-time data recording is shown in Table 2.

[0105] Table 2 Real-time Data Recording Table

[0106]

[0107] Table 2 shows that during the entire operation of the bridge erecting machine, the maximum stress value occurs at the rear trolley lifting point, specifically at the bend of the middle outrigger. The measured value at this point is 171 MPa, and the calculated self-weight stress at this point is approximately 50 MPa. Therefore, the actual stress value generated at this point is approximately 221 MPa. The plate thickness at this point is 20 mm. Based on the Q345 standard plate thickness of 16-40 mm, the yield strength is 335 MPa. With a safety factor of 1.34, the stress is 250 MPa. The measured maximum stress value is within the allowable stress range.

[0108] According to the stress formula: Where δ is stress, measured in Pascals (Pa); F is the external force acting on the material, measured in Newtons (N); and A is the area of ​​the force, measured in square meters (m²). 2 Finite element analysis was performed on the bridge erecting machine under different working conditions, and the stress peak values ​​were compared with those measured in practice. The data are shown in Table 3.

[0109] Table 3 Comparison of Measured Data and Finite Element Analysis

[0110]

[0111] Stress testing at all test points of the bridge erecting machine under full operating conditions and throughout the entire process revealed that the locations of stress peaks and critical sections were largely consistent with the finite element analysis of the equipment. A comparison of the measured data and the finite element calculation data showed that the measured data generally matched the theoretical calculation results.

[0112] In a specific implementation, as a preferred embodiment of the present invention, the distributed intelligent monitoring method for strain of large steel structure beams further includes:

[0113] The steps for conducting stress tests on large steel structure beams of different models and service lives, comparing and analyzing stress distribution under different working conditions, and optimizing the layout of monitoring points are as follows.

[0114] In this embodiment, to avoid the randomness of the results and improve the accuracy of the comparative data, stress tests were conducted on box girder bridge erecting machines of different models and service lives, and the test data were compared and analyzed. Six machines of three different models (JQ900A, JQ900B, and TLJ900) were tested, and the data results are shown in Table 4.

[0115] Table 4 Comparison of experimental results

[0116]

[0117] Comparative experimental data reveals that the bend in the middle support arm or the junction of the lower crossbeam and the support experiences significant localized stress throughout the beam erection process. Furthermore, areas with uneven bend transitions exhibit relatively large stress concentrations, making these key areas for stress monitoring. Additionally, equipment with a high number of stress cycles shows relatively higher stress values ​​at the measured locations. Therefore, for equipment with a long manufacturing history and frequent use, stress monitoring at these points should be strengthened.

[0118] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A distributed intelligent monitoring system for strain of large steel structure beams, characterized in that, include: Welded strain gauges are used to detect the stress state of bridge erecting machines; The protection module is used to ensure the stable operation of the equipment in outdoor environments; The data acquisition unit is used to acquire signals from the welded strain gauge. The data transmission unit is used to transmit the acquired signals from the welded strain gauge to the data analysis and diagnostic module via a 5G network; The data analysis and diagnostic module is used to analyze and process the signals collected by the welded strain gauges. It performs time-domain feature extraction, frequency-domain characteristic analysis, and fault mode identification on a large number of stress signals collected by the welded strain gauges in order to monitor the working status of the bridge erecting machine.

2. The distributed intelligent monitoring system for strain of large steel structure beams according to claim 1, characterized in that, Based on the structural characteristics and actual working conditions of the bridge erecting machine, the welded strain gauge is welded to the surface of the steel structure of the bridge erecting machine, as follows: After the bridge erecting machine's front trolley picks up the beam, the beam transport vehicle simultaneously carries the beam and moves to the center line of the span when the front trolley reaches the center line. The strain gauge is welded to the lower surface of the lower cover plate along the direction of the main beam. This position is the first test point. When the beam is fed to the beam-taking position of the rear trolley, the rear trolley is located behind the middle support leg. After the hook is fully lifted, the strain gauge is welded to the side plate of the second column bend arm. Along the direction of the bend, this position is the second test point. When the bridge erecting machine is in the span-crossing state, the front outrigger is retracted and the front end structure of the middle outrigger is in a suspended state. The strain gauge is welded to the top of the main web plate. This position is the third test point. Strain gauges are welded to the upper cover plate at the mid-span of the main beam to monitor the stress state at the mid-span of the main beam. This position is the fourth test point. Strain gauges are welded to the cover plate at the root of the cantilever to monitor the stress state at the root of the cantilever; this location is the fifth test point. Strain gauges are welded at the curved arm of the middle support leg at the beam drop position to monitor the stress state at the beam drop position; this position is the sixth test point.

3. The distributed intelligent monitoring system for strain of large steel structure beams according to claim 2, characterized in that, The stress state of a steel structure can be reflected by its deformation, as follows: At the first test point, the lower cover plate was under tension during the beam removal and transportation process. Welded strain gauges were welded to the lower surface of the lower cover plate to directly reflect the tensile stress at that location. At the second test point, the No. 2 column arm bears a large load when the rear trolley picks up the beam. It is under compression on the inside and tension on the outside. The welded strain gauge is welded directly above the side plate of the arm to reflect the stress concentration at this part. At the third test point, the main web plate is subjected to a large bending moment in the through-hole state. A welded strain gauge is welded directly above the main web plate to reflect the tensile stress at this part. At the fourth test point, the upper cover plate at the mid-span of the main beam is under compression when the main beam is under stress. Welded strain gauges are welded to the upper cover plate to reflect the compressive stress at this location. At the fifth test point, the upper cover plate at the root of the cantilever is subjected to a large bending moment in the through-hole state. A welded strain gauge is welded to the upper cover plate to reflect the tensile stress at this part. At the sixth test point, the middle outrigger arm bears a large load when the beam is lowered. Welded strain gauges are welded to the outrigger arm to reflect the stress concentration at this location.

4. The distributed intelligent monitoring system for strain of large steel structure beams according to claim 1, characterized in that, The data acquisition unit includes multiple data acquisition units and a controller. The data acquisition units are used to acquire signals from the welded strain gauges, and the controller is used to manage and transmit the signals acquired by the data acquisition units. The data acquisition unit is a modular design, with each data acquisition unit supporting 4 signal inputs and each data acquisition unit controlling up to 4 of the welded strain gauges; The controller supports 4 bus signal inputs, and a single bus can support up to 8 data acquisition devices.

5. The distributed intelligent monitoring system for strain of large steel structure beams according to claim 1, characterized in that, The protection module includes a cabinet, a metal cable protection pipe, and a temperature and humidity monitoring unit. The data acquisition unit, controller, and 5G communication unit are integrated in the cabinet. The shielded cable is run through the metal cable protection pipe. The temperature and humidity monitoring unit uses a digital sensor SHT35 connected to a microcontroller STM32F103ZET6 to display the collected temperature and humidity data in real time on the serial port.

6. The distributed intelligent monitoring system for strain of large steel structure beams according to claim 4, characterized in that, The data collector and the controller communicate via an RS485 bus, and the distance between the controller and the data collector can be extended to 300 meters.

7. The distributed intelligent monitoring system for strain of large steel structure beams according to claim 1, characterized in that, The data analysis and diagnosis module includes: The data receiving and processing module is used to receive strain data transmitted by the data acquisition unit and perform real-time analysis and processing of the strain data, including time-domain feature extraction and frequency-domain characteristic analysis. The fault identification and early warning module is used to identify faults and issue early warning signals for stress states that exceed the preset stress thresholds. The data storage module is used to store the processed data for subsequent analysis and querying.

8. A method for distributed intelligent monitoring of strain in large steel structure beams based on the distributed intelligent monitoring system for strain in large steel structure beams according to any one of claims 1-7, characterized in that, Includes the following steps: S1. Perform finite element stress simulation analysis on large steel structure beams, and determine the location distribution of strain monitoring points based on actual working conditions; S2. Based on the determined location of the strain monitoring point, the welded strain gauge is welded to the corresponding position on the steel structure of the bridge erecting machine; S3. Design a distributed data acquisition unit, including a modular acquisition unit and a controller. The acquisition unit and the controller communicate via an RS485 bus to acquire and transmit strain data from monitoring points in real time. S4. The data analysis and diagnosis module receives strain data transmitted by the distributed data acquisition unit and performs time-domain feature extraction, frequency-domain characteristic analysis, and fault mode identification on the strain data to monitor the working status of the bridge erecting machine.

9. A distributed intelligent monitoring method for strain of large steel structure beams according to claim 8, characterized in that, Also includes: The steps for conducting stress tests on large steel structure beams of different models and service lives, comparing and analyzing stress distribution under different working conditions, and optimizing the layout of monitoring points are as follows.

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