A method and system for dynamic early warning of expansion mold risk of a disassembly-free formwork cable well

Abstract

This invention discloses a dynamic early warning method and system for the risk of formwork bulging in cable wells without the need for formwork removal. The dynamic early warning method deploys a sensor array inside the formwork to collect real-time strain data, which is then processed using wavelet threshold denoising and temperature compensation. A multi-dimensional feature parameter set is constructed, including absolute stress value, stress change rate, and nonlinearity indices. Based on dynamic threshold logic, the working condition is categorized into normal pouring load state, local vibration impact state, or formwork bulging risk state. A graded early warning strategy is then implemented: a red warning is triggered and located for formwork bulging risk state; a yellow warning is triggered for local vibration impact state; and an orange warning is triggered for normal pouring load state when the load is approaching its limit. This invention requires no model training and utilizes physical characteristic formulas to effectively distinguish between vibration interference and actual deformation, significantly reducing the false alarm rate and achieving early warning and full-cycle monitoring of formwork bulging risk, thus realizing intelligent safety management and control during construction.

Description

Technical Field

[0001] This invention relates to the field of civil engineering construction monitoring and intelligent early warning technology, and in particular to a dynamic early warning method and system for the risk of formwork bulging in cable wells without the need for formwork removal. Background Technology

[0002] In the construction of underground structures such as cable wells, formwork that does not require removal is widely used due to its advantages such as convenient construction and no need for secondary dismantling. However, during the concrete pouring and solidification process, factors such as excessive lateral pressure, improper vibration operation, or defects in the formwork support system can easily lead to "formwork bulging" accidents, resulting in structural dimensional deviations or even collapse. Existing monitoring methods mainly suffer from two major problems: high false alarm rate and significant environmental interference.

[0003] On the one hand, traditional methods rely solely on monitoring the absolute value of stress, which cannot effectively distinguish between the instantaneous high-frequency impact caused by concrete vibration (which is a normal construction behavior) and the actual precursors of formwork deformation, leading to frequent false alarms and seriously interfering with the construction progress.

[0004] On the other hand, the temperature change caused by the heat of hydration of concrete will produce significant thermal strain. If there is no effective compensation mechanism, it will seriously interfere with the accurate measurement of mechanical strain and cause the monitoring data to be distorted.

[0005] Furthermore, existing technologies face the dilemma of lacking early warning and overlooking hidden damage. Traditional alarm logic often only triggers when stress exceeds the material's limit, by which time the structure may have already undergone irreversible plastic deformation, missing the optimal intervention window. Simultaneously, existing technologies lack effective assessment methods after the initial setting of concrete, making it difficult to detect hidden damage such as voids or microcracks at the formwork-concrete interface, leaving long-term quality risks. Therefore, there is an urgent need to develop a dynamic early warning method that can accurately distinguish between construction disturbances and actual risks, possess adaptive threshold adjustment capabilities, and assess hidden damage throughout the entire lifecycle, in order to improve the safety management level of cable well construction. Summary of the Invention

[0006] The purpose of this invention is to provide a dynamic early warning method and system for the risk of bulging in cable wells without dismantling the template, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a dynamic early warning method for the risk of formwork bulging in cable wells without dismantling the formwork, comprising the following steps:

[0008] S1, Sensor Network Deployment: Deploy a strain sensor array in the key stress area inside the non-removable template and establish a sensor network node model that includes spatial topology.

[0009] S2, Data Preprocessing: Real-time acquisition of strain time-series data from each node. A wavelet threshold denoising algorithm was used to adaptively remove high-frequency electrical noise to preserve stress abrupt change characteristics. Subsequently, a temperature compensation model based on the hydration heat mechanism was used to eliminate thermal strain interference caused by environmental temperature changes, thus decoupling and obtaining pure mechanical strain data that only reflects changes in mechanical load. To ensure subsequent feature indicators , , The calculation accuracy, among which, The absolute value of stress is the index. The stress change rate index It is a non-linearity index;

[0010] S3, Construction of Multidimensional Feature Parameter Set: Constructing a multidimensional feature parameter set using a sliding time window. Calculate three core feature indicators for each node, using [the unit] as the unit. , , Thus, a multidimensional feature parameter set is constructed;

[0011] S4, Dynamic State Judgment: Based on the preset dynamic threshold logic, the current working condition is identified by using a multi-dimensional feature parameter set. The current working condition is one of the following: normal pouring load state, local vibration impact state, and bulging risk state.

[0012] S5, Tiered Warning Execution: Execute tiered warning strategies based on the identified status.

[0013] Further optimization is achieved by employing the following strategy for deploying the strain sensor array in S1:

[0014] (1) The strain sensors are arranged in layers along the height of the cable well, and the spacing between the layers gradually increases with the height.

[0015] (2) Each layer of strain sensors is evenly distributed around the cable well wall, and the distribution is denser at the stress concentration points at the inside and outside corners;

[0016] (3) The strain sensor is waterproof and pre-embedded in the inner surface of the non-removable template, and the sensor lead wires converge to the wellhead protection box.

[0017] Further optimization involves using a serpentine buffer routing method for the sensor lead wires.

[0018] Further optimization is achieved by using the wavelet threshold denoising algorithm in S2 as follows:

[0019] A four-level discretization and soft-thresholding strategy based on the db4 wavelet basis is adopted. By utilizing the fourth-order vanishing moment and good regularity of the db4 wavelet, the pseudo-Gibbs phenomenon is avoided in the reconstructed signal while matching the smooth trend of concrete strain, thus ensuring the subsequent strain change rate. The accuracy of the calculation;

[0020] To address the non-stationary nature of construction noise, a fixed threshold is abandoned, and a noise estimator based on the absolute deviation of the median is used to adaptively calculate the threshold for each layer. Furthermore, a continuous soft thresholding function is applied to the detail coefficients; where, For the first The threshold of the layer, For the first Standard deviation of layer noise This represents the total length of the signal.

[0021] Further optimization is needed for the pure mechanical strain data in S2. The calculation formula is: ,

[0022] in, For the collected temperature data, The coefficient of thermal expansion of the template material. This is the initial temperature.

[0023] Further optimization is achieved by using the following logic to identify the working condition in step S4:

[0024] Setting dynamic thresholds: safety stress thresholds Vibration change rate threshold and nonlinear tolerance threshold ;

[0025] like < and < and This is determined to be a normal pouring load state;

[0026] like > and < It was determined to be a localized vibration and impact condition;

[0027] like > or[( ) ( [>0)], which is determined to be a risky state of mold expansion.

[0028] Further optimization involves an adaptive update mechanism for the dynamic threshold in S4, which includes:

[0029] The threshold of vibration change rate Take the current construction phase before Within a time The 95th percentile of the value multiplied by the magnification factor ;

[0030] The nonlinear tolerance threshold The system is dynamically adjusted according to the age of the concrete. Before the initial setting, the first threshold is set, and after the initial setting, it is automatically adjusted to a more stringent second threshold.

[0031] The safety stress threshold The yield strength of the template material was obtained by correcting the yield strength based on real-time monitored temperature data.

[0032] Further optimization includes the following tiered early warning strategy in S4:

[0033] When a situation is determined to be at risk of bulging, a Level 1 red alert is triggered, the coordinates of the high-risk area are locked, and it is recommended to immediately stop work and reinforce the area.

[0034] When the condition is determined to be local vibration impact, a level two yellow warning is triggered, the location of the impact source node is recorded and the abnormal vibration operation is indicated, but construction is not interrupted.

[0035] When the load condition is determined to be normal pouring load, but the absolute stress index Values ​​exceeding 0.9× At that time, a Level 3 orange alert was triggered, indicating that the load was approaching its limit and attention should be paid to controlling the pouring speed.

[0036] Further optimization includes a hidden damage assessment method, which involves continuously monitoring the stress fallback curve during the cooling stage after the initial setting of the concrete. If the stress does not fall back normally with the temperature decrease, but instead shows abnormal fluctuations or stagnation, it is determined that the interface between the formwork and the concrete has become detached or has micro-cracks, and a formwork detachment risk assessment report containing the location and severity of the detachment is generated.

[0037] This invention also provides a dynamic early warning system for the risk of formwork bulging in cable wells without the need for formwork removal, used to implement the aforementioned dynamic early warning method for the risk of formwork bulging in cable wells without the need for formwork removal, comprising:

[0038] The sensing layer consists of several pre-packaged embedded strain sensors and temperature control units, which are fixed inside the non-removable template.

[0039] A transmission layer, comprising shielded signal lines and a wellhead data collection box, is used to transmit data from the sensing layer to the processing layer.

[0040] The processing layer includes a microprocessor, which stores a dynamic discrimination logic program and a historical benchmark database for performing calculations and judgments in steps S3 to S5.

[0041] The interaction layer includes an audible and visual alarm device and a wireless transmission module, used to output graded early warning commands and remote data push.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] (1) The dynamic early warning method and system for the risk of formwork bulging in cable wells without dismantling formwork, based on multidimensional stress characteristic analysis, realizes accurate dynamic early warning of formwork bulging risk and has anti-interference characteristics. Specifically, it introduces the stress change rate index. and nonlinearity index Combined with dynamic threshold logic, it can effectively distinguish between normal vibration impact and real bulging risk, significantly reducing the false alarm rate;

[0044] (2) It realizes early warning of mold expansion risk. When the stress does not exceed the limit but the nonlinearity deteriorates significantly, the plastic yield instability trend can be identified, thus realizing early warning;

[0045] (3) The dynamic threshold has strong adaptability. The threshold can be automatically adjusted according to the construction stage and the age of concrete to adapt to complex on-site conditions.

[0046] (4) It realizes full-cycle monitoring of concrete pouring and solidification process, which not only covers the pouring process, but also assesses hidden damage after initial setting, filling the technical gap.

[0047] (5) The dynamic early warning method and system for the risk of bulging of the cable well without dismantling the formwork does not require model training. It can effectively distinguish between vibration interference and actual deformation by using physical characteristic formulas, which significantly reduces the false alarm rate and realizes intelligent safety management and control in the construction process. Attached Figure Description

[0048] Figure 1 This is a flowchart illustrating the dynamic early warning method for the risk of bulging in cable wells without the need for formwork removal, as disclosed in this invention.

[0049] Figure 2 This is the state discrimination logic diagram of the multidimensional feature parameter set disclosed in this invention. Detailed Implementation

[0050] The following are specific embodiments of the present invention, which are described in conjunction with the accompanying drawings. However, the present invention is not limited to these embodiments.

[0051] Example 1

[0052] like Figure 1 and Figure 2 As shown, this application discloses a dynamic early warning method for the risk of formwork bulging in cable wells without dismantling the formwork. The specific implementation steps are as follows:

[0053] S1, Sensor Network Deployment: A strain sensor array is deployed within the critical stress area inside the non-removable formwork of the cable well to be constructed. A sensor network node model containing spatial topology relationships is established, where the spatial topology relationships are the spatial coordinates and connection relationships of each node. The strain sensor array deployment strategy is as follows:

[0054] (1) The strain sensors are arranged in layers along the height of the cable well. Considering that the lateral pressure of the lower concrete is large, the spacing between the layers gradually increases with the height from bottom to top.

[0055] (2) Each layer of strain sensors is evenly distributed around the cable well wall, and the distribution is denser at the stress concentration points at the inside and outside corners;

[0056] (3) The strain sensor is waterproof and pre-embedded in the inner surface of the template to prevent damage during pouring. The sensor lead wires are connected to the wellhead protection box in a serpentine buffer routing method, which can absorb the small displacement during the concrete solidification process.

[0057] S2, Data Preprocessing: Real-time acquisition of strain time-series data from each node. The sampling frequency is 50Hz-100Hz. A wavelet threshold denoising algorithm is used to adaptively remove high-frequency electrical noise to retain stress change characteristics. Then, a temperature compensation model based on the hydration heat mechanism is used to eliminate thermal strain interference caused by environmental temperature changes. Decoupling yields pure mechanical strain data that only reflects changes in mechanical load. To ensure subsequent feature indicators , , The calculation accuracy, among which, The absolute value of stress is the index. The stress change rate index It is a non-linearity index;

[0058] S3, Construction of Multidimensional Feature Parameter Set: Constructing a multidimensional feature parameter set using a sliding time window. For each node, features are extracted, and three core feature indicators are calculated. , , Thus, a multidimensional feature parameter set is constructed;

[0059] Among them, the absolute value index of stress , calculated as This represents the current load level, and the maximum equivalent stress within the window is taken. To monitor the instantaneous stress at every moment within the monitoring window; stress change rate index , calculated as ,in For the derivative of strain with respect to time, This index, used for averaging operations, is sensitive to vibration operations, characterizes the dynamic response speed of the load, and calculates the average of the absolute values ​​of the strain derivative with respect to time; nonlinearity index... , calculated as The coefficient of determination residual, which characterizes the deviation of a material's constitutive relation, is defined as the difference between the measured stress-time curve and the ideal linear fitting curve. When the material enters the plastic stage or undergoes creep, the curve deviates from linearity. Significantly increased, among which, The coefficient of determination for linear fit. The higher the value, the higher the linearity. It is the correlation coefficient, which represents the strength and direction of the linear relationship between two variables in the beam.

[0060] S4, Dynamic State Judgment: Based on preset dynamic threshold logic, the current working condition is identified using a multi-dimensional feature parameter set. The current working condition is one of the following: normal pouring load state, local vibration impact state, and bulging risk state. The specific judgment logic is as follows:

[0061] Set dynamic threshold: (Safety stress threshold) (Threshold for vibration change rate) (Nonlinear tolerance threshold);

[0062] 1. Normal casting load condition: If < and < and This indicates that the load is within a safe range, changes smoothly, and conforms to the characteristics of linear elasticity.

[0063] 2. Local vibration and impact condition: If > and < This indicates that the stress change was drastic but did not exceed the limit, and was determined to be an instantaneous impact caused by the operation of the vibrator.

[0064] 3. Risk status of mold bulging: If > If the stress exceeds the limit, then [( ) ( Although the stress did not exceed the limit, the nonlinearity was significantly higher and showed an increasing trend, indicating that the material had entered plastic yielding or creep instability.

[0065] The dynamic threshold has an adaptive update mechanism, specifically:

[0066] Take the current construction phase before All within a time (e.g., 10 minutes) The 95th percentile of the value, multiplied by the magnification factor. To adapt to working conditions with different vibration intensities;

[0067] The system dynamically adjusts based on the age of the concrete. Before the initial setting, the concrete is highly fluid, so a relatively lenient first threshold is set. After the initial setting, the concrete begins to harden, and the system automatically adjusts to a more stringent second threshold to capture minute plastic deformations.

[0068] The yield strength of the template material is obtained by temperature correction based on real-time monitored temperature data to ensure that the threshold is not artificially high at high temperatures.

[0069] S5, Tiered Warning Execution: Execute tiered warning strategies based on the identified status. The specific strategies are as follows:

[0070] a. Level 1 Red Alert: When the system is determined to be in a "bursting risk state", it will immediately trigger a red alert, lock the specific coordinates of the high-risk area (i.e., the location of the corresponding sensor node), and suggest an immediate work stoppage and reinforcement through the interaction layer;

[0071] b. Level 2 Yellow Alert: When the condition is determined to be "local vibration impact state", a yellow alarm is triggered, the location of the impact source node is recorded, and the workers on site are notified that the vibration operation may be too violent or the location is inappropriate, but construction is not forcibly interrupted.

[0072] c. Level 3 Orange Alert: When the condition is determined to be "normal pouring load state" but... Values ​​exceeding 0.9× When this occurs, an orange alert is triggered, indicating that the current load is approaching its limit and that attention should be paid to controlling the subsequent pouring speed or height.

[0073] The dynamic early warning method for the risk of formwork bulging in cable wells without formwork in this application also includes hidden damage assessment. The specific assessment method is as follows: during the cooling stage after the initial setting of concrete, the system continuously monitors the stress fallback curve. Under normal circumstances, as the temperature decreases, the thermal strain disappears and the total stress should fall back steadily. If the stress is not detected to fall back normally with the temperature decrease, but instead shows abnormal fluctuations or stagnation, the system determines that the interface between the formwork and the concrete has become detached or micro-cracks have been generated inside, and automatically generates a formwork detachment risk assessment report including the location and severity of the detachment.

[0074] In one embodiment of the method of this application, the wavelet threshold denoising algorithm in step S2 is as follows:

[0075] Denoising is achieved using a four-level discretization based on the db4 wavelet basis and a soft thresholding strategy. Leveraging the fourth-order vanishing moment and good regularity of the db4 wavelet, the reconstructed signal avoids pseudo-Gibbs phenomena while matching the smooth strain trend of concrete, thus ensuring the subsequent strain change rate. The accuracy of the calculation;

[0076] To address the non-stationary nature of construction noise, a fixed threshold is abandoned, and a noise estimator based on the absolute deviation of the median is used to adaptively calculate the threshold for each layer. Furthermore, a continuous soft thresholding function is applied to the detail coefficients; where, For the first The threshold of the layer, For the first Standard deviation of layer noise This represents the total length of the signal.

[0077] In another embodiment of the method of this application, in step S2, a temperature compensation model based on the heat of hydration mechanism is used to eliminate interference. Since the hydration reaction of concrete releases a large amount of heat, it causes the formwork temperature to rise and generate thermal expansion. Therefore, this embodiment simultaneously collects temperature data. Pure mechanical strain data obtained through decoupling Compensation is performed using pure mechanical strain data. The calculation formula is: ,in, The coefficient of thermal expansion of the template material. This is the initial temperature.

[0078] Example 2

[0079] This invention also discloses a dynamic early warning system for the risk of formwork bulging in cable wells without formwork removal, used to realize a method for dynamic early warning of the risk of formwork bulging in cable wells without formwork removal, including:

[0080] The sensing layer consists of several pre-packaged embedded strain sensors and temperature control units, and is fixed inside the non-removable template in strict accordance with the strain sensor array layout strategy of Example 1.

[0081] The transmission layer, including shielded signal lines and wellhead data collection boxes, is responsible for converting analog signals collected by the sensing layer into digital signals and transmitting them to the processing layer. It has the ability to resist electromagnetic interference.

[0082] The processing layer contains a built-in microprocessor, which is an industrial-grade microprocessor. It stores a dynamic discrimination logic program (i.e., the S3-S5 method in Example 1) and a historical benchmark database, which are used to perform calculations and judgments in steps S3 to S5. The processing layer runs algorithms in real time to complete feature extraction, state determination and threshold update.

[0083] The interaction layer includes an audible and visual alarm device and a wireless transmission module, which are used to output graded early warning commands and remote data push. When an early warning is triggered, the on-site audible and visual alarm device responds immediately, and at the same time, the early warning information, high-risk coordinates and assessment reports are pushed to the remote monitoring center or the mobile terminal of the management personnel through the wireless transmission module.

[0084] The specific embodiments described herein are merely illustrative of the spirit of the invention. Those skilled in the art to which this invention pertains may make various modifications or additions to the described specific embodiments or use similar methods to substitute them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.

Claims

1. A dynamic early warning method for the risk of formwork bulging in cable wells without the need for formwork removal, characterized in that, Includes the following steps: S1, Sensor Network Deployment: Deploy a strain sensor array in the key stress area inside the non-removable template and establish a sensor network node model that includes spatial topology. S2, Data Preprocessing: Real-time acquisition of strain time-series data from each node. A wavelet threshold denoising algorithm was used to adaptively remove high-frequency electrical noise to preserve stress abrupt change characteristics. Subsequently, a temperature compensation model based on the hydration heat mechanism was used to eliminate thermal strain interference caused by environmental temperature changes, thus decoupling and obtaining pure mechanical strain data that only reflects changes in mechanical load. To ensure subsequent feature indicators , , The calculation accuracy, among which, The absolute value of stress is the index. The stress change rate index It is a non-linearity index; S3, Construction of Multidimensional Feature Parameter Set: Constructing a multidimensional feature parameter set using a sliding time window. Calculate three core feature indicators for each node, using [the unit] as the unit. , , Thus, a multidimensional feature parameter set is constructed; S4, Dynamic State Judgment: Based on the preset dynamic threshold logic, the current working condition is identified by using a multi-dimensional feature parameter set. The current working condition is one of the following: normal pouring load state, local vibration impact state, and bulging risk state. S5, Tiered Warning Execution: Execute tiered warning strategies based on the identified status.

2. The method for dynamic early warning of bulging risk in cable wells without dismantling the formwork as described in claim 1, characterized in that, The deployment strategy for the strain sensor array in S1 is as follows: (1) The strain sensors are arranged in layers along the height of the cable well, and the spacing between the layers gradually increases with the height. (2) Each layer of strain sensors is evenly distributed around the cable well wall, and the distribution is denser at the stress concentration points at the inside and outside corners; (3) The strain sensor is waterproof and pre-embedded in the inner surface of the non-removable template, and the sensor lead wires converge to the wellhead protection box.

3. The method for dynamic early warning of bulging risk in cable wells without dismantling the formwork as described in claim 2, characterized in that, The sensor leads are laid out using a serpentine buffer routing method.

4. The method for dynamic early warning of bulging risk in cable wells without dismantling the formwork as described in claim 1, characterized in that, The wavelet threshold denoising algorithm in S2 is as follows: A four-level discretization and soft-thresholding strategy based on the db4 wavelet basis is adopted. By utilizing the fourth-order vanishing moment and good regularity of the db4 wavelet, the pseudo-Gibbs phenomenon is avoided in the reconstructed signal while matching the smooth trend of concrete strain, thus ensuring the subsequent strain change rate. The accuracy of the calculation; To address the non-stationary nature of construction noise, a fixed threshold is abandoned, and a noise estimator based on the absolute deviation of the median is used to adaptively calculate the threshold for each layer. Furthermore, a continuous soft thresholding function is applied to the detail coefficients; where, For the first The threshold of the layer, For the first Standard deviation of layer noise This represents the total length of the signal.

5. The method for dynamic early warning of bulging risk in cable wells without dismantling the formwork as described in claim 1, characterized in that, Pure mechanical strain data in S2 The calculation formula is: , in, For the collected temperature data, The coefficient of thermal expansion of the template material. This is the initial temperature.

6. The method for dynamic early warning of bulging risk in cable wells without dismantling the formwork as described in claim 1, characterized in that, The discrimination logic for identifying the working condition in S4 is as follows: Setting dynamic thresholds: safety stress thresholds Vibration change rate threshold and nonlinear tolerance threshold ; like < and < and This is determined to be a normal pouring load state; like > and < It was determined to be a localized vibration and impact condition; like > or[( ) ( [>0)], which is determined to be a risky state of mold expansion.

7. The method for dynamic early warning of bulging risk in cable wells without dismantling the formwork as described in claim 6, characterized in that, The dynamic threshold in S4 has an adaptive update mechanism, which includes: The threshold of vibration change rate Take the current construction phase before Within a time The 95th percentile of the value multiplied by the magnification factor ; The nonlinear tolerance threshold The system is dynamically adjusted according to the age of the concrete. Before the initial setting, the first threshold is set, and after the initial setting, it is automatically adjusted to a more stringent second threshold. The safety stress threshold The yield strength of the template material was obtained by correcting the yield strength based on real-time monitored temperature data.

8. The method for dynamic early warning of bulging risk in cable wells without dismantling the formwork as described in claim 1, characterized in that, The graded early warning strategy in S4 includes: When a situation is determined to be at risk of bulging, a Level 1 red alert is triggered, the coordinates of the high-risk area are locked, and it is recommended to immediately stop work and reinforce the area. When the condition is determined to be local vibration impact, a level two yellow warning is triggered, the location of the impact source node is recorded and the abnormal vibration operation is indicated, but construction is not interrupted. When the load condition is determined to be normal pouring load, but the absolute stress index Values ​​exceeding 0.9× At that time, a Level 3 orange alert was triggered, indicating that the load was approaching its limit and attention should be paid to controlling the pouring speed.

9. The method for dynamic early warning of bulging risk in cable wells without dismantling the formwork as described in claim 1, characterized in that, The risk dynamic early warning method also includes hidden damage assessment, and the method for hidden damage assessment is: during the cooling stage after the initial setting of concrete, continuously monitor the stress fallback curve. If the stress does not fall back normally as the temperature decreases, but instead fluctuates abnormally or stagnates, it is determined that there is a gap or micro-crack at the interface between the formwork and the concrete, and a formwork gap risk assessment report is generated, which includes the location and severity of the gap.

10. A dynamic early warning system for the risk of formwork bulging in cable wells without the need for formwork removal, characterized in that, A method for implementing the dynamic early warning of bulging risk in cable wells without formwork removal as described in any one of claims 1 to 9 includes: The sensing layer consists of several pre-packaged embedded strain sensors and temperature control units, which are fixed inside the non-removable template. A transmission layer, comprising shielded signal lines and a wellhead data collection box, is used to transmit data from the sensing layer to the processing layer. The processing layer includes a microprocessor, which stores a dynamic discrimination logic program and a historical benchmark database for performing calculations and judgments in steps S3 to S5. The interaction layer includes an audible and visual alarm device and a wireless transmission module, used to output graded early warning commands and remote data push.

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