Municipal pipeline deformation monitoring and grading early warning system based on distributed sensor array

Abstract

The application discloses a municipal pipeline deformation monitoring grading early warning system based on a distributed sensing array, and mainly relates to the field of municipal pipeline safety monitoring. The system is characterized in that a three-dimensional characteristic coordinate system is constructed, a traditional single-index monitoring is upgraded to a complete state description in a three-dimensional space, and the evaluation one-sidedness of the traditional technology is overcome. Meanwhile, a multi-stage early warning envelope surface is constructed in a step-by-step manner from inside to outside. Through judging the process of a state point crossing the envelope surfaces at different stages, grading response is realized, and the problem of frequent false alarms or omissions in the critical area in the traditional binary threshold early warning is avoided. After triggering the early warning, a double-tracing mechanism of an exogenous discrimination condition and an endogenous discrimination condition is constructed, the cause type of deformation is automatically identified, and the blindness of adopting a unified response scheme for different types of deformation is avoided.

Description

Technical Field

[0001] This invention relates to the field of municipal pipeline safety monitoring, and in particular to a graded early warning system for municipal pipeline deformation monitoring based on a distributed sensor array. Background Technology

[0002] As an important part of urban infrastructure, municipal pipelines undertake key functions such as water supply and drainage, gas transmission, and heat supply. During long-term service, pipelines are inevitably affected by multiple factors such as ground consolidation and settlement, disturbance from surrounding construction, repeated traffic loads, and material aging and creep. When the deformation exceeds the allowable limits of the pipeline structure or joints, it will cause safety accidents such as leakage, rupture, or even overall instability, resulting in serious economic losses and social impact.

[0003] Currently, municipal pipeline deformation monitoring mainly relies on regular manual inspections, displacement point measurements, or single-threshold early warnings, which still have the following shortcomings: First, the monitoring dimensions are singular, usually only focusing on the magnitude of the deformation, without simultaneously considering key parameters that characterize the dynamic development trend, and thus failing to comprehensively reflect the real-time safety status of the pipeline; Second, early warning methods are mostly fixed threshold binary judgments, lacking a graded and progressive early warning space, making it difficult to distinguish different levels of danger, and easily generating frequent false alarms or missed alarms at critical states. Moreover, after triggering an early warning, there is a lack of automatic identification capability for the type of deformation inducing factors, making it impossible to distinguish between sudden deformation caused by external disturbances and internal gradual deformations such as ground subsidence and material creep, resulting in a lack of targeted response measures.

[0004] Therefore, there is an urgent need for a municipal pipeline monitoring and early warning system that can achieve multi-dimensional state representation, multi-level progressive early warning, and automatic traceability of deformation types to solve the above-mentioned technical defects. Summary of the Invention

[0005] The purpose of this invention is to provide a municipal pipeline deformation monitoring and early warning system based on a distributed sensor array, so as to solve the problems of single monitoring dimensions, lack of early warning classification, and inability to automatically identify deformation types in the existing technology.

[0006] The objective of this invention can be achieved through the following technical solution: a municipal pipeline deformation monitoring and early warning system based on a distributed sensor array, comprising: The acquisition-processing status module collects real-time deformation raw data of municipal pipelines through the deployed monitoring points, and obtains a standardized time-series deformation dataset after outlier removal and time-series noise reduction, and calculates the basic deformation parameters. The envelope graph construction module obtains the real-time state point P(t) based on the basic deformation parameters, constructs the three-dimensional feature coordinate system of pipeline deformation of Sva in combination with the real-time state point P(t), sets three extreme failure benchmark points, and presets a multi-level early warning envelope surface in combination with the three extreme failure benchmark points. The variable-level module is used to project the acquired state points P(t) onto a preset multi-level warning envelope in chronological order to obtain state trajectory lines, perform matching and judgment on the state trajectory lines, and output yellow / orange / red warning commands. The deformation-identification and tracing module is used to respond to yellow / orange / red warning commands, obtain the state sequence T, perform tracing matching by combining the set exogenous and endogenous discrimination conditions, output the deformation type, and construct a warning information sheet; The pipeline management backend is used to respond to yellow / orange / red warning commands and warning information sheets, and immediately perform corresponding preset warning operations or displays.

[0007] Preferably, the real-time deformation raw data includes pipeline deformation and sampling timestamp, and the basic deformation parameters include single-cycle cumulative deformation, real-time deformation rate, and deformation acceleration; Single-cycle cumulative deformation represents the deformation accumulated within a preset fixed monitoring period; real-time deformation rate represents the difference / time interval between adjacent time-series deformations; deformation acceleration represents the difference / time interval between adjacent time-series deformation rates.

[0008] Preferably, the state point P(t) = {S(t), v(t), a(t)}, where t represents the sampling time, S represents the single-cycle cumulative deformation, v represents the deformation rate, and a represents the deformation acceleration. A three-dimensional feature coordinate system for pipeline deformation is constructed with the cumulative deformation S as the X-axis, the deformation rate v as the Y-axis, and the deformation acceleration a as the Z-axis. Based on the limit failure benchmarks of three key dimensions, the multi-level warning envelope maps corresponding to the same limit failure benchmarks of the three key dimensions in the database are matched. Based on the multi-level warning envelope maps, yellow warning envelopes, orange warning envelopes, and red warning envelopes are preset in the three-dimensional feature coordinate system of pipeline deformation to obtain the multi-level warning envelopes.

[0009] Preferably, the three ultimate failure reference points include the ultimate cumulative deformation reference point Smax, the ultimate deformation rate reference point vmax, and the ultimate deformation acceleration reference point amax, and the ultimate failure reference points of the three key dimensions are used as anchor points for the construction of the envelope surface.

[0010] Preferably, the matching and analysis process for the state trajectory line is as follows: When the current state point P(t) of the state trajectory line is located inside the yellow warning envelope, monitoring continues. When the current state point P(t) of the state trajectory line first crosses from the inside of the yellow warning envelope to its outside without touching the orange warning envelope, a yellow warning command is generated. When the current state point P(t) of the state trajectory line continues to develop outward, crosses the orange warning envelope without touching the red warning envelope, an orange warning command is generated. When the current state point P(t) of the state trajectory line breaks through and crosses the red warning envelope, a red warning command is generated.

[0011] Preferably, the analysis process of the state sequence T is as follows: Yellow warning instructions, orange warning instructions, and red warning instructions are collectively referred to as deformation recognition instructions. When a deformation recognition instruction is generated, the current state point P(t) and the state sequence T of W consecutive historical sampling points are obtained: T = {P(t-W+1), P(t-W+2), ..., P(t)}.

[0012] Preferably, the analysis process of the early warning information sheet is as follows: Based on the state sequence T, calculate the average deformation rate and average deformation acceleration of the sliding window, and extract the acceleration values ​​a of NL points, including the current and previous points, from the state sequence T. Retrieve the preset external acceleration threshold stored in the database, compare the acceleration value 'a' of NL points with the preset external acceleration threshold one by one, and determine whether there is an acceleration jump flag. If yes, the acceleration jump flag is set to 1; otherwise, the acceleration jump flag is set to 0. Extract the deformation rate from the current state point P(t), obtain the absolute value of the deformation rate, and simultaneously retrieve the preset external rate threshold stored in the database. Compare the absolute value of the deformation rate with the preset deformation rate threshold to determine whether there is a deformation rate surge flag. If yes, the deformation rate surge flag = 1; otherwise, the deformation rate surge flag = 0. The discrimination matching is determined by combining the exogenous type discrimination condition and the endogenous type discrimination condition, and the deformation type is output. The deformation type includes exogenous type deformation, endogenous type deformation, or uncertain type. Simultaneously, based on deformation recognition instructions, an early warning information sheet is generated by combining the instruction with deformation type, collection timestamp, and monitoring point coordinate information.

[0013] The beneficial effects of this invention are as follows: This invention improves the traditional single-index monitoring into a complete state description in three-dimensional space by constructing a three-dimensional feature coordinate system with cumulative deformation S, deformation rate v, and deformation acceleration a as the three axes. This overcomes the one-sidedness of traditional technology, which relies solely on a single deformation threshold for judgment.

[0014] This invention also sets three key anchor points in a three-dimensional feature coordinate system and constructs a multi-level early warning envelope surface that progresses from the inside out, forming a continuous gradient space from the stable zone to the danger zone. By judging the process of the state point crossing each level of the envelope surface, a graded response from "strengthening attention" to "human intervention" and then to "emergency handling" is realized. This avoids the problem of frequent false alarms or missed alarms in the critical zone of traditional binary threshold early warning, improves the rationality and operability of the early warning, and automatically identifies the type of deformation cause by constructing a dual traceability mechanism of exogenous and endogenous discrimination conditions after the early warning is triggered. This provides a key basis for the selection of subsequent disposal measures and avoids the blindness of using a uniform response scheme for different types of deformation. Attached Figure Description

[0015] The invention will now be further described with reference to the accompanying drawings; Figure 1 This is a flowchart of the overall system framework of the present invention; Figure 2 This is a schematic diagram of the basic deformation parameter analysis of this invention. Detailed Implementation

[0016] 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. 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.

[0017] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments; Example 1: Please refer to Figures 1 to 2 As shown, the present invention is a municipal pipeline deformation monitoring and hierarchical early warning system based on a distributed sensor array, including a data acquisition and processing status module, an envelope graph construction module, a deformation classification module, a deformation identification and tracing module, and a pipeline management backend; The data acquisition and processing status module is connected to the envelope graph construction module, which provides a standardized time-series deformation dataset and basic deformation parameters. The envelope graph construction module is connected to the deformation grading module, which provides a preset multi-level early warning envelope. The deformation grading module is connected to the pipeline management backend and the deformation identification and tracing module, respectively, and outputs graded early warning instructions. The deformation identification and tracing module is connected to the pipeline management backend and outputs an early warning information sheet containing the deformation type. The data acquisition and processing module collects real-time deformation data of municipal pipelines from deployed monitoring points. After outlier removal and time-series noise reduction, a standardized time-series deformation dataset is obtained. Basic deformation parameters are then calculated, including: By uniformly deploying monitoring points along the axial and circumferential directions of the municipal pipeline using distributed fiber optic sensors and strain sensor arrays, the raw data of real-time deformation at each monitoring point can be obtained in real time. The raw data for real-time deformations includes: pipeline deformations, sampling timestamps, etc. The collected raw deformation data is preprocessed, including outlier removal, temperature drift compensation, temporal noise reduction, and spatial interpolation to eliminate false deformation data caused by environmental interference and equipment errors. After preprocessing, a standardized temporal deformation dataset is obtained, which includes real-time deformation at each time point, acquisition timestamps, monitoring point coordinates, etc. Based on a standardized time-series deformation dataset, the basic deformation parameters are initially calculated, including single-cycle cumulative deformation, real-time deformation rate, and deformation acceleration. Single-cycle cumulative deformation: The deformation of each monitoring point is accumulated in time intervals based on a preset fixed monitoring cycle, which characterizes the static cumulative damage degree of pipeline deformation and reflects the superposition effect of ultra-long cycle micro deformation. Real-time deformation rate: Calculated by the ratio of the difference between adjacent time-series deformation values ​​to the time interval, it characterizes the real-time development speed of pipeline deformation and captures the dynamic changes in short-term deformation. Deformation acceleration: Calculated by the ratio of the difference in deformation rate between adjacent time series to the time interval, it characterizes the changing trend of deformation development and is a core parameter for identifying deformation stagnation, trend reversal, and precursors of sudden changes. Envelope diagram - The basic deformation parameters of the construction module are obtained from the real-time state point P(t). A three-dimensional characteristic coordinate system of pipeline deformation for Sva is constructed using the real-time state point P(t), and three ultimate failure benchmark points are set. A multi-level early warning envelope surface is preset based on these three ultimate failure benchmark points, specifically including: Obtain the real-time state point P(t) = {S(t), v(t), a(t)}, where t represents the sampling time, S represents the single-cycle cumulative deformation, v represents the deformation rate, and a represents the deformation acceleration. A three-dimensional feature coordinate system for pipeline deformation is constructed with the cumulative deformation S as the X-axis, the deformation rate v as the Y-axis, and the deformation acceleration a as the Z-axis. Any state point P in the three-dimensional characteristic coordinate system of this pipeline deformation represents the complete deformation state of the monitoring point at a certain moment. Within this space, the origin and the surrounding area represent the absolutely stable state. In the three-dimensional feature coordinate system of pipeline deformation, the ultimate failure reference points of the pipeline in three key dimensions are set: the ultimate cumulative deformation reference point Smax, the ultimate deformation rate reference point vmax, and the ultimate deformation acceleration reference point amax. The ultimate failure reference points of the three key dimensions are used as anchor points for the construction of the envelope surface. For example, under extremely low-speed quasi-static loading conditions, i.e., when the deformation rate v≈0 and the deformation acceleration a≈0, the maximum allowable cumulative deformation that the pipeline can withstand without losing its function is the limit cumulative deformation reference point Smax. This point is located at the farthest point of the cumulative deformation X-axis in the three-dimensional characteristic coordinate system of pipeline deformation. The maximum allowable deformation rate at which a pipe joint or pipe body will not buckle or break under instantaneous dynamic disturbances where the cumulative deformation is very small and the acceleration approaches zero is the ultimate deformation rate reference point vmax, which is located at the farthest end of the deformation rate Y-axis. When the cumulative deformation and deformation rate are still low, the maximum allowable deformation acceleration caused by impact or sudden load that does not lead to instantaneous instability of the pipeline structure is the ultimate deformation acceleration reference point amax. This point is located at the ultimate deformation acceleration reference point amax, and this point is located at the farthest end of the deformation acceleration Z-axis. Based on the ultimate failure benchmark points of three key dimensions, the multi-level early warning envelope surface map corresponding to the same ultimate failure benchmark points of the three key dimensions in the database is matched. Based on the multi-level early warning envelope surface map, yellow early warning envelope surface, orange early warning envelope surface and red early warning envelope surface are preset in the three-dimensional feature coordinate system of pipeline deformation to obtain the multi-level early warning envelope surface. For example, the orange warning envelope is obtained by expanding the yellow warning envelope based on the preset ratio coefficient k1, and the red warning envelope is obtained by expanding the orange warning envelope based on the preset ratio coefficient k2. k1 and k2 are manually set and are both greater than zero.

[0018] Example 2: The deformation grading module projects the acquired state points P(t) onto a preset multi-level warning envelope in chronological order to obtain state trajectory lines. It then performs matching and judgment on the state trajectory lines and outputs yellow / orange / red warning commands, specifically including: The discrete state points P(t) = {S(t), v(t), a(t)} acquired in real time are projected into the three-dimensional state space in chronological order to form a continuous state trajectory line that reflects the deformation evolution process. Matching analysis between the state trajectory line and the multi-level early warning envelope: When the current state point P(t) of the state trajectory line is located inside the yellow warning envelope, it is determined to be a stable inertial creep state or a stationary state, and monitoring continues. When the current state point P(t) of the state trajectory line crosses from the inside of the yellow warning envelope to the outside of it for the first time, and has not yet touched the orange warning envelope, it is determined that the pipeline deformation has deviated from the normal range, and a yellow warning instruction is generated. When the current state point P(t) of the state trajectory line continues to develop outward, crosses the orange warning envelope but has not yet touched the red warning envelope, it is determined that the pipeline deformation state has entered the warning stage, and an orange warning command is generated. When the current state point P(t) of the state trajectory line breaks through and crosses the red warning envelope, regardless of the specific numerical combination of the current point P(t), the pipeline structure is immediately determined to be in an extremely dangerous state, and a red warning instruction is generated. The pipeline management backend is used to respond to yellow, orange, or red warning instructions and immediately take the preset warning actions corresponding to the yellow, orange, or red warning instructions. For example, yellow warning instruction: display the text "Intensify Attention"; orange warning instruction: display human intervention; red warning instruction: display emergency handling. The deformation identification and tracing module is used to respond to yellow / orange / red warning commands, obtain the state sequence T, perform tracing matching based on the set exogenous and endogenous discrimination conditions, output the deformation type, and construct a warning information sheet, specifically including: Yellow, orange, and red warning commands are collectively referred to as deformation recognition commands; When generating deformation recognition instructions, obtain the current state point P(t) and the state sequence T of W (W>0) consecutive historical sampling points: T={P(t-W+1), P(t-W+2), ..., P(t)}; Based on the state sequence T, calculate the average deformation rate and average deformation acceleration of the sliding window; Extract the acceleration values ​​'a' from the current and previous NL points in the state sequence T; Retrieve the preset external acceleration threshold stored in the database, and compare the acceleration values ​​'a' of NL points one by one with the preset external acceleration threshold to determine whether there is an acceleration jump flag. If the acceleration values ​​of all NL points are greater than the preset external acceleration threshold, it is determined that a valid acceleration jump has been detected, and the acceleration jump flag is set to 1. If the acceleration values ​​of all NL points are not greater than the preset external acceleration threshold, it is determined that no valid acceleration jump has been detected, and the acceleration jump flag is set to 0. Extract the deformation rate from the current state point P(t), obtain the absolute value of the deformation rate, and simultaneously retrieve the preset external rate threshold stored in the database. Compare the absolute value of the deformation rate with the preset deformation rate threshold to determine whether there is a deformation rate surge flag. If the absolute value of the deformation rate is greater than the preset deformation rate threshold, it is determined that the current sampling point has detected a deformation rate surge, and the deformation rate surge flag is set to 1. If the absolute value of the deformation rate is less than or equal to the preset deformation rate threshold, it is determined that the current sampling point has not detected a deformation rate surge, and the deformation rate surge flag is set to 0. Set the external and internal discrimination conditions. External discrimination condition: If the acceleration jump flag is 1 and S(t) in the current state point P(t) is less than the preset cumulative deformation low ratio (e.g., 0.3) × Smax, or the deformation rate increase flag is 1 and S(t) in the current state point P(t) is less than the preset cumulative deformation low ratio × Smax, then it is determined to be an external deformation. That is, when the cumulative deformation is still low, but there is a sustained high acceleration or instantaneous high speed, it indicates that the pipeline is suddenly subjected to external energy input under low damage conditions, which is a typical characteristic of external disturbance. Endogenous deformation discrimination criteria: If the average deformation rate of the sliding window is less than the preset low-order ratio of deformation rate (e.g., 0.1) × vmax, and the average deformation acceleration of the sliding window is less than the preset average deformation acceleration threshold of the sliding window, and S(t) in the current state point P(t) is less than the preset high-order ratio of cumulative deformation (e.g., 0.7) × Smax, then it is determined to be an endogenous deformation. That is, within a long time window, both the deformation rate and acceleration are at extremely low levels, with no dynamic impact characteristics; however, the cumulative deformation is approaching the limit, which is a typical manifestation of endogenous gradual processes such as material creep and formation consolidation and settlement. If the deformation type is satisfied with both exogenous and endogenous deformation types, but a deformation recognition command is triggered, it is determined to be an uncertain type. The discrimination matching is determined by combining the exogenous type discrimination condition and the endogenous type discrimination condition, and the deformation type is output. The deformation type includes exogenous type deformation, endogenous type deformation, or uncertain type. Simultaneously, based on deformation recognition instructions, early warning information sheets are generated by combining instructions with deformation type, collection timestamp, monitoring point coordinates, and other data. For example, instructions + type: yellow warning instructions + external deformation, yellow warning instructions + internal deformation, orange warning instructions + external deformation, etc. The pipeline management backend is used to respond to and immediately display early warning information, so as to provide a basis for selecting subsequent response measures in a timely manner. For example, a yellow alert plus exogenous deformation indicates that a short-term external disturbance signal has been detected. Please check whether there are any construction activities in the vicinity. A yellow alert plus endogenous deformation indicates that the monitored section shows long-term slow deformation characteristics, which may be due to ground subsidence or pipe creep. Please continue to monitor the situation. An orange alert plus exogenous deformation indicates that external impact deformation has intensified. Immediate human intervention is required to investigate the source of damage and assess the damage. In summary, by constructing a three-dimensional feature coordinate system with cumulative deformation S, deformation rate v, and deformation acceleration a as the three axes, the traditional single-index monitoring is elevated to a complete state description in three-dimensional space. This overcomes the one-sidedness of traditional technologies that rely solely on single deformation threshold judgments. Furthermore, by setting three key anchor points in the three-dimensional feature coordinate system, a multi-level early warning envelope is constructed from the inside out, forming a continuous gradient space from the stable zone to the danger zone. By judging the process of the state point P(t) traversing each level of the envelope, a graded response from "intensified attention" to "human intervention" and then to "emergency handling" is achieved. This avoids the problem of frequent false alarms or missed alarms in the critical zone of traditional binary threshold early warning, improving the rationality and operability of the early warning. Moreover, after triggering an early warning, a dual tracing mechanism of exogenous and endogenous discrimination conditions is constructed to automatically identify the type of deformation trigger, providing a key basis for the selection of subsequent response measures and avoiding the blind application of a uniform response scheme to different types of deformation.

[0019] The threshold is set for result comparison and analysis to determine whether it is good or bad. The value of the threshold is determined by a combination of large-scale model analysis of the sample data and human experience, and can also be adjusted appropriately based on seasonal or common-sense influencing factors. The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A municipal pipeline deformation monitoring and hierarchical early warning system based on a distributed sensor array, characterized in that, include: The system includes a data acquisition and processing status module, an envelope graph construction module, a deformation grading module, a deformation identification and traceability module, and a pipeline management backend. The acquisition-processing status module collects real-time deformation raw data of municipal pipelines through the deployed monitoring points, and obtains a standardized time-series deformation dataset after outlier removal and time-series noise reduction, and calculates the basic deformation parameters. The envelope graph construction module obtains real-time state points P(t) = {S(t), v(t), a(t)} based on basic deformation parameters, where t represents the sampling time, S represents the single-cycle cumulative deformation, v represents the deformation rate, and a represents the deformation acceleration. With the cumulative deformation S as the X-axis, the deformation rate v as the Y-axis, and the deformation acceleration a as the Z-axis, a three-dimensional feature coordinate system for pipeline deformation is constructed, and three ultimate failure benchmark points are set. Multi-level early warning envelope surfaces are preset in combination with the three ultimate failure benchmark points. The variable-level module is used to project the acquired state points P(t) onto a preset multi-level warning envelope in chronological order to obtain state trajectory lines, perform matching and judgment on the state trajectory lines, and output yellow / orange / red warning commands. The deformation-identification and tracing module is used to respond to yellow / orange / red warning commands, obtain the state sequence T, perform tracing matching by combining the set exogenous and endogenous discrimination conditions, output the deformation type, and construct a warning information sheet; The pipeline management backend is used to respond to yellow / orange / red warning commands and warning information sheets, and immediately perform corresponding preset warning operations or displays; The analysis process of the state sequence T is as follows: Yellow warning instructions, orange warning instructions, and red warning instructions are collectively referred to as deformation recognition instructions. When a deformation recognition instruction is generated, the current state point P(t) and the state sequence T of W consecutive historical sampling points are obtained: T = {P(t-W+1), P(t-W+2), ..., P(t)}; The analysis process of the warning information sheet is as follows: Based on the state sequence T, calculate the average deformation rate and average deformation acceleration of the sliding window, and extract the acceleration values ​​a of NL points, including the current and previous points, from the state sequence T. Retrieve the preset external acceleration threshold stored in the database, compare the acceleration value 'a' of NL points with the preset external acceleration threshold one by one, and determine whether there is an acceleration jump flag. If yes, the acceleration jump flag is set to 1; otherwise, the acceleration jump flag is set to 0. Extract the deformation rate from the current state point P(t), obtain the absolute value of the deformation rate, and simultaneously retrieve the preset external rate threshold stored in the database. Compare the absolute value of the deformation rate with the preset deformation rate threshold to determine whether there is a deformation rate surge flag. If yes, the deformation rate surge flag = 1; otherwise, the deformation rate surge flag = 0. The discrimination matching is determined by combining the exogenous type discrimination condition and the endogenous type discrimination condition, and the deformation type is output. The deformation type includes exogenous type deformation, endogenous type deformation, or uncertain type. Simultaneously, based on deformation recognition instructions, an early warning information sheet is generated by combining the instruction with deformation type, collection timestamp, and monitoring point coordinate information.

2. The municipal pipeline deformation monitoring and hierarchical early warning system based on a distributed sensor array according to claim 1, characterized in that, The real-time deformation raw data includes pipeline deformation and sampling timestamp, and the basic deformation parameters include single-cycle cumulative deformation, real-time deformation rate and deformation acceleration. Single-cycle cumulative deformation represents the deformation accumulated within a preset fixed monitoring period; real-time deformation rate represents the difference / time interval between adjacent time-series deformations. Deformation acceleration represents the difference / time interval between adjacent time-series deformation rates.

3. The municipal pipeline deformation monitoring and hierarchical early warning system based on a distributed sensor array according to claim 2, characterized in that, Based on the limit failure benchmarks of three key dimensions, the multi-level warning envelope maps corresponding to the same limit failure benchmarks of the three key dimensions in the database are matched. Based on the multi-level warning envelope maps, yellow warning envelopes, orange warning envelopes, and red warning envelopes are preset in the three-dimensional feature coordinate system of pipeline deformation to obtain the multi-level warning envelopes.

4. The municipal pipeline deformation monitoring and hierarchical early warning system based on a distributed sensor array according to claim 3, characterized in that, The three ultimate failure reference points include the ultimate cumulative deformation reference point Smax, the ultimate deformation rate reference point vmax, and the ultimate deformation acceleration reference point amax. The ultimate failure reference points of the three key dimensions are used as anchor points for the construction of the envelope surface.

5. The municipal pipeline deformation monitoring and hierarchical early warning system based on a distributed sensor array according to claim 1, characterized in that, The matching and analysis process for the state trajectory line is as follows: When the current state point P(t) of the state trajectory line is located inside the yellow warning envelope, monitoring continues. When the current state point P(t) of the state trajectory line first crosses from the inside of the yellow warning envelope to its outside without touching the orange warning envelope, a yellow warning command is generated. When the current state point P(t) of the state trajectory line continues to develop outward, crosses the orange warning envelope without touching the red warning envelope, an orange warning command is generated. When the current state point P(t) of the state trajectory line breaks through and crosses the red warning envelope, a red warning command is generated.

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