Radar detection-based steel structure deformation dynamic monitoring device and use method

Abstract

The invention discloses a steel structure deformation dynamic monitoring device based on radar detection and a use method, and the device comprises a radar detection module which is used for transmitting and receiving a radar signal; the pyramid reflection module is arranged at a to-be-measured point of the steel structure and is used for enhancing reflection radar signals; the positioning module is arranged on the triangular pyramid reflection module and is used for determining the position of the triangular pyramid reflection module; the angle execution module is used for adjusting the emission angle of the radar detection module according to the position, fed back by the positioning module, of the triangular pyramid reflection module; and the processing module is used for processing the radar signal, judging whether the change of the previous position and the later position of the to-be-detected point in the time period exceeds a threshold value or not, and if yes, sending a filing instruction. The purpose of accurately monitoring local sudden change in a load test or hoisting and assembling process of a bridge and a building steel structure is achieved. Potential hazards in the later period are prevented, and construction safety is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of construction assistance, in particular to a steel structure deformation dynamic monitoring device based on radar detection and a use method thereof. BACKGROUND

[0002] Steel structure is a relatively important load-bearing raw material in building construction. In recent years, more and more buildings have begun to use large-span steel structures. Large-span steel structures are lighter in quality than traditional concrete, can be designed in various shapes, and have a shorter construction period. Steel structure engineering has a service life. After years of use, it needs to be evaluated whether the service life meets the requirements. If the steel member appears initial bending and deformation, it is difficult to find or detect by conventional methods.

[0003] In the construction or acceptance of steel structures, after the assembly of the steel structure is completed, the assembled steel structure needs to be hoisted by cooperating with a hoisting device. However, since the steel structure is more than one hundred tons, the steel columns are prone to deformation or relative displacement during hoisting, which poses a certain safety hazard. In addition, after the steel structure is installed, its installation quality needs to be detected, and whether it meets the design requirements also needs to be measured and checked. Currently, the hoisting of steel structures is usually observed and judged by skilled workers, which has poor precision and is prone to miss the slight deformation of the steel structure during hoisting, resulting in construction hazards in the later period.

[0004] The existing steel structure deformation monitoring method uses radar to monitor the deformation of the steel structure in a static state, but cannot provide targeted early warning according to the degree of deformation, and has poor flexibility in use. SUMMARY

[0005] The embodiments of the present application provide a steel structure deformation dynamic monitoring device based on radar detection and a use method thereof, which are used to solve the problem that the existing structure deformation monitoring method uses radar to monitor the deformation of the steel structure in a static state, and is a kind of foolproof monitoring method, which cannot provide targeted early warning according to the degree of deformation and has poor flexibility in use.

[0006] The technical scheme provided by the embodiments of the present application is as follows: In a first aspect, the embodiments of the present application provide a steel structure deformation dynamic monitoring device based on radar detection, which comprises: A multi-source perception unit comprising a radar detection module for transmitting and receiving radar signals, wherein the radar detection module comprises a continuous wave radar; A triangular pyramid reflection module arranged at a to-be-measured point of the steel structure for enhancing reflected radar signals, comprising an active target with an identity code; A positioning module arranged on the triangular pyramid reflection module for determining the position of the triangular pyramid reflection module; An angle executing module is configured to adjust the emission angle of the radar detection module according to the position of the triangular pyramid reflection module fed back by the positioning module. A processing module is configured to process the radar signal, judge whether the change of the preceding position and the subsequent position of the to-be-measured point in the time period exceeds a threshold value, and if so, issue a filing instruction, which includes: establishing a finite element analysis model of the steel structure as its digital twin; if the change of the preceding position and the subsequent position of the to-be-measured point in the time period exceeds the threshold value, a multi-level early warning is started, which includes: first attention, the deformation or predicted deformation reaches 80% of the threshold value, the system sends a prompt information to the monitoring screen; second warning, reaching 95% of the threshold value, the system issues an audible and light alarm to remind the on-site personnel to pay close attention; third alarm, exceeding the threshold value, the system issues the highest level of alarm and automatically sends a shutdown signal to the crane control system to force the hoisting operation to pause, thereby maximizing the safety.

[0007] Further, the multi-source perception unit further comprises a high-precision IMU attitude compensation module; the high-precision IMU attitude compensation module is configured to reduce the monitoring error caused by the deformation of the radar detection module itself, and filter the inertial displacement of the steel structure when the radar detection module acquires data, and only keep the elastic displacement data of the steel structure.

[0008] Further, the multi-source perception unit further comprises a visual recognition module, which is configured to identify the identity code of the to-be-measured point, provide visual positioning data, and if the radar detection module monitors the position anomaly of the to-be-measured point, judge whether the position anomaly is caused by foreign matter interference through the visual recognition module, the foreign matter including fallen leaves and flying birds.

[0009] Further, the multi-level early warning includes single-point multi-level early warning, which includes the following early warning formula: v(t)=Δtd(t)−d(t−Δt) Wherein, v(t): displacement change rate, unit mm / s; d(t): real-time displacement of the to-be-measured point at time t, unit mm; Δt: monitoring time interval, unit s; First attention: when |d(t)|≥0.8dthresh×C or |v(t)|≥0.8vthresh×C, trigger a prompt; second warning: when |d(t)|≥0.95dthresh×C or |v(t)|≥0.95vthresh×C, trigger an audible and light alarm; third alarm: when |d(t)|>dthresh×C or |v(t)|>vthresh×C, trigger a shutdown instruction; dthresh is the maximum displacement threshold value allowed by the structure safety; C is the confidence degree of multi-source data; vthresh is the rate threshold value.

[0010] Furthermore, the multi-level early warning includes multi-point collaborative early warning, which includes the following formula: δij(t)=∣di(t)−dj(t)∣ Where, di(t): the displacement of the i-th point to be measured; δij(t): The relative displacement difference between associated points i and j; Multi-point collaborative early warning triggering condition: When δij(t)>δthresh,ij×C, a level two early warning must be triggered even if a single point does not exceed the threshold; δthresh,ij refers to the allowable relative displacement threshold.

[0011] Furthermore, when an alarm is triggered, the system automatically records all sensor data, video recordings, and operating parameters for 30 seconds before and after the alarm, generating a complete event report.

[0012] Furthermore, the triangular cone reflection module is also equipped with an acceleration sensor for real-time detection of acceleration during the hoisting process of the steel structure.

[0013] Secondly, embodiments of this application provide a method for using a radar-based dynamic monitoring device for steel structure deformation, including: Arrange multiple triangular pyramid reflectors at appropriate locations within the measured space; The phased array continuous wave radar transmitting base station emits continuous radar waves. At the same time, under the action of the rotating base, the radar waves rotate and scan in the measurement space to form a measurement network. The displacement change from the initial position of the point to be measured to the position at the interval; Determine whether the changes in the earlier and later positions of the test point during the time period exceed the threshold. If so, issue a record instruction.

[0014] Furthermore, the determination of whether the changes in the prior and subsequent positions of the test point during the time period exceed a threshold, and if so, the issuance of a filing instruction includes: if the changes in the prior and subsequent positions of the test point during the time period exceed the threshold, then a multi-level early warning is initiated. The multi-level early warning includes: Level 1 attention, when the deformation or predicted deformation reaches 80% of the threshold; Level 2 early warning, when the deformation reaches 95% of the threshold, the system issues an audible and visual alarm to remind on-site personnel to pay close attention; Level 3 alarm, when the threshold is exceeded, the system issues the highest level alarm and automatically sends a stop signal to the crane control system, forcibly suspending the lifting operation to ensure safety to the greatest extent.

[0015] Furthermore, it also includes: establishing a finite element analysis model of the steel structure as its digital twin; if the changes in the earlier and later positions of the measured point exceed the threshold during the time period, a prompt message is sent to the monitoring screen.

[0016] The at least one technical solution adopted in this application embodiment can achieve the following beneficial effects: by feeding back the time taken for the position of the test point to change sequentially using radar waves, it can be determined whether the test point exceeds a threshold. This achieves the goal of accurately monitoring localized abrupt changes during load testing or hoisting and assembly of bridges and building steel structures, preventing potential hazards later and improving construction safety. Furthermore, it can provide different levels of early warning based on the degree of deformation, greatly improving monitoring accuracy and flexibility. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a schematic diagram of the principle structure provided for the embodiments of this specification.

[0018] Figure 2 This is a schematic diagram of the radar detection module structure provided in the embodiments of this specification.

[0019] Figure 3 This is a schematic diagram of the triangular cone reflection module structure provided in the embodiments of this specification. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0022] This specification provides an embodiment of a radar-based dynamic monitoring device for steel structure deformation. Please refer to [link to documentation]. Figure 1 As shown, it includes a multi-source sensing unit, which includes a radar detection module 1, a triangular cone reflection module 2, a positioning module 3, an angle execution module 4, and a processing module 5.

[0023] The radar detection module 1 is used to transmit and receive radar signals; in one possible implementation, the radar detection module includes a continuous wave radar.

[0024] The triangular cone reflector module 2 is installed at the test point on the steel structure to enhance the reflected radar signal, including active targets with identification codes. In one possible implementation, the triangular cone reflector module 2 includes a radar reflector 21, which is triangular cone in shape. The bottom of the radar reflector has a connection device for connecting to the test point on the steel structure, and a positioning module is disposed within the radar reflector. In yet another possible implementation, please refer to... Figure 3 As shown, the connecting device includes a U-shaped clamp 22 with elastic bends. A through-wire 23 penetrating the base plate is located at the top of the U-shaped clamp, with fastening nuts 24 at both ends. A positioning module 3 is mounted on the triangular pyramid reflector module to determine its position. In one possible implementation, the positioning module includes a GPS device, either embedded within the radar reflector or mounted on the U-shaped clamp. For example, the positioning module employs GPS-RTK or UWB high-precision positioning technology, providing coordinates not only for radar pointing but also for establishing the overall spatial attitude model of the hoisting system (crane, steel structure). The angle execution module, combined with visual-assisted positioning, enables faster and smoother radar beam tracking, supporting a "one-to-many" scanning monitoring mode. Another possibility is magnetic mounting.

[0025] Furthermore, the multi-source sensing unit also includes a high-precision IMU attitude compensation module and a visual recognition module. The high-precision IMU attitude compensation module is used to reduce monitoring errors caused by the deformation of the radar detection module itself, and to filter the inertial displacement of the steel structure when the radar detection module acquires data, retaining only the elastic displacement data of the steel structure. The visual recognition module is used to identify the identity code of the point to be measured, provide visual positioning data, and if the radar detection module detects an abnormal position of the point to be measured, the visual recognition module determines whether the abnormal position is caused by interference from foreign objects, including fallen leaves and birds.

[0026] For example, the "active target" at the point of measurement (such as the top of a steel structure) has a unique black and white QR code pattern on its surface and contains built-in LEDs powered by the system. The radar measures the target's distance and angle data [R_radar, θ_radar] per second. Simultaneously, the IMU measures the radar base's own pitch and roll angles [α_imu, β_imu] in real time. The fusion algorithm in the processing module performs the following calculations: The true displacement is calculated as R_radar - f(α_imu, β_imu) (where f is a geometrically based compensation algorithm). The vision system identifies the QR code on the target, providing independent two-dimensional image coordinates for cross-validation and assisted tracking, playing a crucial role, especially when radar signals are interfered with by heavy rain or other factors. This improves the accuracy of the system's absolute displacement measurement and effectively distinguishes between structural deformation and sensor sway, significantly reducing the false alarm rate.

[0027] Angle execution module 4 is used to adjust the emission angle of the radar detection module based on the position of the triangular cone reflector module fed back by the positioning module; in one possible implementation, please refer to... Figure 2 As shown, the angle execution module 4 includes, but is not limited to, the Huano Starry Sky HAWK-R6 slope stability monitoring radar system. It includes a rotating base 41 and an angle adjustment bracket 42 mounted on the rotating base 41, with the radar detection module mounted on the angle adjustment bracket. The processing module 5 processes the radar signal, determining whether the changes in the initial and subsequent positions of the measured point over a time period exceed a threshold. If so, a filing instruction is issued. In one possible implementation, the filing instruction includes an audible and visual alarm and an emergency braking operation instruction. In one possible implementation, the filing instruction includes: establishing a finite element analysis model of the steel structure as its digital twin; if the changes in the initial and subsequent positions of the measured point over a time period exceed a threshold, a three-level warning is activated. The three-level warning includes: Level 1: Attention – when the deformation or predicted deformation reaches 80% of the threshold, the system sends a prompt message to the monitoring screen. Level 2: When the threshold reaches 95%, the system issues an audible and visual alarm to remind on-site personnel to pay close attention. Level 3: When the threshold is exceeded, the system issues the highest-level alarm and automatically sends a stop signal to the crane control system, forcibly suspending the lifting operation to maximize safety.

[0028] In another possible implementation, the formula for single-point multi-level early warning is as follows: v(t)=Δtd(t)−d(t−Δt) v(t): rate of displacement change, in mm / s; d(t): The real-time displacement of the point to be measured at time t (relative to the initial position d0), in mm; Δt: Monitoring time interval (e.g., 1 second), unit: seconds; Level 1 Attention (80% threshold): A warning is triggered when |d(t)| ≥ 0.8dthresh × C or |v(t)| ≥ 0.8vthresh × C (vthresh is the rate threshold). Level 2 Warning (95% threshold): An audible and visual alarm is triggered when |d(t)| ≥ 0.95dthresh × C or |v(t)| ≥ 0.95vthresh × C. Level 3 Alarm (Over-threshold): A shutdown command is triggered when |d(t)| > dthresh × C or |v(t)| > vthresh × C; dthresh is the maximum permissible displacement threshold for structural safety (calibrated by design specifications or digital twin model), in mm. Further explanation: C is the confidence level of multi-source data (0~1, the reliability coefficient of data fused through IMU compensation, visual verification, etc., default 0.95).

[0029] The multi-point collaborative early warning formula is as follows. Large steel structures need to monitor multiple related points (such as truss nodes), and the collaborative risks caused by relative deformation need to be considered.

[0030] δij(t)=∣di(t)−dj(t)∣ di(t): The displacement of the i-th point to be measured; δij(t): The relative displacement difference between associated points i and j; Collaborative early warning trigger condition: When δij(t) > δthresh,ij × C, a secondary early warning must be triggered even if a single point does not exceed the threshold (due to the potential risk of connection failure). δthresh,ij refers to the allowable relative displacement threshold (determined by the structural connection stiffness).

[0031] Further optimization, to provide early warning of potential risks, uses Kalman filtering or LSTM neural networks to predict displacement trends in the near future, as shown in the following formula: Kalman filtering fuses radar measurements z(t) and system state predictions x^(t∣t−1) to output the optimal estimate x^(t) and predicts the displacement x^(t+n∣t) in the next n steps. State equation: x^(t∣t−1)=F⋅x^(t−1)+Bu(t) Observation equation: z(t) = H⋅x^(t∣t−1) + v(t) in: x(t)=[d(t),v(t),a(t)] ^T: State vector (displacement, velocity, acceleration); F: State transition matrix; B: Control input matrix; H: Observation matrix; v(t), u(t): process noise and observation noise (covariance matrices Q and R need to be calibrated).

[0032] Prediction and early warning logic: If the predicted displacement d^(t+ΔT)>dthresh×C within the future time interval ΔT, a level 3 alarm is triggered in advance (e.g., ΔT=5s, used for emergency braking in hoisting scenarios).

[0033] For nonlinear deformation scenarios (such as cumulative material fatigue deformation), LSTM can learn temporal features. It takes a historical displacement sequence [d(t−N),...,d(t−1)] as input and outputs predicted values ​​for the next M steps: d^(t+1),...,d^(t+M). Loss function (mean squared error): Loss=M1k=1∑M(d^(t+k)−d(t+k))2 Early warning optimization: When any point in the prediction sequence exceeds dthresh×C, the early warning level is related to the time point of the predicted exceedance (e.g., exceeding the limit 10 seconds in advance triggers level two, exceeding the limit 3 seconds in advance triggers level three), which greatly improves construction safety.

[0034] In operation, multiple triangular pyramid reflectors are positioned at appropriate locations within the measured space, including the location of the point to be measured. The radar transmitting base emits continuous radar waves, which, under the action of the rotating base, rotate and scan within the measurement space to form a measurement network. The displacement change from the initial location of the point to the location at an interval is measured. It is determined whether the change in the earlier and later locations of the point to be measured exceeds a threshold within the time period. If so, a record command is issued. During operation, based on the location information fed back by GPS, the angle of the rotating platform is adjusted by a stepper motor, thereby adjusting the transmission angle of the continuous wave radar. Preferably, a finite element analysis model of the steel structure is established as its digital twin. If the change in the earlier and later locations of the point to be measured exceeds the threshold within the time period, a prompt message is sent to the monitoring screen.

[0035] Furthermore, the triangular cone reflector module also includes an acceleration sensor 6 for real-time detection of acceleration during the hoisting process of the steel structure. For example: Step 1: Data Acquisition. Accelerometers are used to acquire acceleration data along the x, y, and z axes: ax, ay, and az, respectively. This data is compared and verified with displacement data obtained from radar monitoring. If the direction and data change in the same direction, monitoring continues.

[0036] Step 2: Filter the collected data, such as by using the Kalman filter algorithm, to fuse the data from the accelerometer, reduce noise interference, and improve data accuracy.

[0037] Step 3: Feature Extraction. Calculate the resultant acceleration. .

[0038] Step 4: Algorithm Determination. Set acceleration threshold. When the resultant acceleration a is greater than Initial assessment suggests that hoisting stall or instability may occur; further analysis of the rate of change of acceleration is performed, calculating the difference in acceleration between adjacent moments. ,like Exceeding the set rate of change threshold This increases the confidence value for judging hoisting stall and instability, further improving the accuracy of monitoring.

[0039] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0040] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A radar-based dynamic monitoring device for steel structure deformation, characterized in that, The device includes: A multi-source sensing unit includes a radar detection module for transmitting and receiving radar signals, wherein the radar detection module includes a continuous wave radar; The triangular cone reflector module, installed at the test point on the steel structure, is used to enhance the reflected radar signal, including active targets with identification codes; A positioning module, disposed on the triangular pyramid reflector module, is used to determine the position of the triangular pyramid reflector module; An angle execution module is used to adjust the emission angle of the radar detection module based on the position of the triangular cone reflector module fed back by the positioning module. The processing module processes radar signals and determines whether the changes in the initial and subsequent positions of the measured point over a time period exceed a threshold. If so, it issues a filing instruction, which includes: establishing a finite element analysis model of the steel structure as its digital twin; if the changes in the initial and subsequent positions of the measured point over a time period exceed the threshold, it initiates a multi-level early warning system, including: Level 1 alert: when the deformation or predicted deformation reaches 80% of the threshold, the system sends a prompt message to the monitoring screen; Level 2 early warning: when the deformation reaches 95% of the threshold, the system issues an audible and visual alarm to remind on-site personnel to pay close attention; Level 3 alarm: when the threshold is exceeded, the system issues the highest-level alarm and automatically sends a stop signal to the crane control system, forcing the hoisting operation to stop to maximize safety.

2. The radar-based dynamic monitoring device for steel structure deformation according to claim 1, characterized in that, The multi-source sensing unit also includes a high-precision IMU attitude compensation module; the high-precision IMU attitude compensation module is used to reduce the monitoring error caused by the deformation of the radar detection module itself, and to filter the inertial displacement of the steel structure when the radar detection module acquires data, retaining only the elastic displacement data of the steel structure.

3. The radar-based dynamic monitoring device for steel structure deformation according to claim 1, characterized in that, The multi-source sensing unit also includes a visual recognition module, which is used to identify the identity code of the point to be measured and provide visual positioning data. At the same time, if the radar detection module detects an abnormal position of the point to be measured, the visual recognition module determines whether the abnormal position is caused by interference from foreign objects, including fallen leaves and birds.

4. The radar-based dynamic monitoring device for steel structure deformation according to claim 1, characterized in that, The multi-level early warning system includes single-point multi-level early warning, and the single-point multi-level early warning includes the following early warning formula: v(t)=Δtd(t)−d(t−Δt) Where, v(t): rate of displacement change, in mm / s; d(t): Real-time displacement of the point to be measured at time t, in mm; Δt: Monitoring time interval, in seconds; Level 1 Warning: A prompt is triggered when |d(t)| ≥ 0.8dthresh×C or |v(t)| ≥ 0.8vthresh×C; Level 2 Warning: An audible and visual alarm is triggered when |d(t)| ≥ 0.95dthresh×C or |v(t)| ≥ 0.95vthresh×C; Level 3 Alarm: A shutdown command is triggered when |d(t)| > dthresh×C or |v(t)| > vthresh×C; dthresh is the maximum allowable displacement threshold for structural safety; C is the confidence level of multi-source data; vthresh is the rate threshold.

5. The radar-based dynamic monitoring device for steel structure deformation according to claim 4, characterized in that, The multi-level early warning system includes multi-point collaborative early warning, which includes the following formula: δij(t)=∣di(t)−dj(t)∣ Where, di(t): the displacement of the i-th point to be measured; δij(t): The relative displacement difference between associated points i and j; Multi-point collaborative early warning triggering condition: When δij(t)>δthresh,ij×C, a level two early warning must be triggered even if a single point does not exceed the threshold; δthresh,ij refers to the allowable relative displacement threshold.

6. The radar-based dynamic monitoring device for steel structure deformation according to claim 1, characterized in that, When an alarm is triggered, the system automatically records all sensor data, video recordings, and operating parameters for 30 seconds before and after the alarm, generating a complete event report.

7. The radar-based dynamic monitoring device for steel structure deformation according to claim 1, characterized in that, The triangular cone reflection module is also equipped with an acceleration sensor for real-time detection of acceleration during the hoisting process of the steel structure.

8. The method of using a radar-based dynamic monitoring device for steel structure deformation according to any one of claims 1-7, characterized in that, include: Arrange multiple triangular pyramid reflectors at appropriate locations within the measured space; The phased array continuous wave radar transmitting base station emits continuous radar waves. At the same time, under the action of the rotating base, the radar waves rotate and scan in the measurement space to form a measurement network. The displacement change from the initial position of the point to be measured to the position at the interval; Determine whether the changes in the earlier and later positions of the test point during the time period exceed the threshold. If so, issue a record instruction.

9. The method of using a radar-based dynamic monitoring device for steel structure deformation according to claim 8, characterized in that, The determination of whether the changes in the prior and subsequent positions of the test point within a time period exceed a threshold, and if so, the issuance of a filing instruction includes: if the changes in the prior and subsequent positions of the test point within a time period exceed the threshold, then a multi-level early warning is initiated. The multi-level early warning includes: Level 1 attention, when the deformation or predicted deformation reaches 80% of the threshold; Level 2 early warning, when the deformation reaches 95% of the threshold, the system issues an audible and visual alarm to remind on-site personnel to pay close attention; Level 3 alarm, when the threshold is exceeded, the system issues the highest level alarm and automatically sends a stop signal to the crane control system, forcibly suspending the lifting operation to ensure safety to the greatest extent.

10. The method of using a radar-based dynamic monitoring device for steel structure deformation according to claim 8, characterized in that, It also includes: establishing a finite element analysis model of the steel structure as its digital twin; if the changes in the earlier and later positions of the measured point exceed the threshold during the time period, a prompt message is sent to the monitoring screen.

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