A method for monitoring the stability of a group of underground concrete structures of a sewage plant

Abstract

The present application relates to the technical field of concrete structure monitoring, and particularly relates to a sewage plant underground concrete structure group stability monitoring method. The present application can directly reflect the comprehensive response state of the underground structure under the water-soil coupling effect by synchronously collecting four types of physical quantities, i.e. concrete strain value, water-soil interface pressure value, interface shear displacement value and steel stress value, and laying monitoring points according to the differences in failure mechanism of different key positions, thereby improving the comprehensiveness and pertinence of monitoring. The present application further calculates a risk index by combining the abnormal occurrence frequency and the physical property change rate of the abnormal synergy zone, and outputs a graded early warning signal and a corresponding abnormal synergy zone spatial distribution map based on the risk index, thereby realizing visual early warning and helping the operation and maintenance personnel to quickly locate the risk and develop a response strategy.

Description

Technical Field

[0001] This invention relates to the field of concrete structure monitoring technology, specifically to a method for monitoring the stability of underground concrete structure groups in a sewage treatment plant. Background Technology

[0002] Underground concrete structures in wastewater treatment plants are typically buried at great depths and have complex structures. They operate under complex water-soil coupling environments and are susceptible to multiple coupled risks, such as foundation heave, sidewall cracking, joint leakage, and even overall instability, due to changes in groundwater buoyancy and lateral earth pressure, seepage, and disturbances from surrounding construction. Therefore, effective monitoring of the stability of underground concrete structures in wastewater treatment plants is necessary to ensure the safe and durable operation of the plant.

[0003] Existing technology, such as Chinese invention patent CN117871657A, describes a method for monitoring the stability of concrete structures based on piezomagnetic materials. This method indirectly reflects the stress state of the structure by incorporating piezomagnetic aggregates into the concrete and monitoring changes in their magnetic induction intensity.

[0004] In-depth analysis reveals the following problems with existing technologies: 1. They primarily monitor the stress state of upper structures such as load-bearing walls and columns, lacking direct monitoring capabilities for the coupling effects unique to underground structures, such as water-soil interface pressure and shear displacement caused by seepage; 2. Their early warning is based on static thresholds, making them insensitive to the co-evolution trend of multiple parameters and difficult to distinguish the dominant causes of risks; 3. They fail to conduct differentiated monitoring for specific failure mechanisms at different key locations, resulting in insufficient targeting of monitoring results and difficulty in guiding maintenance personnel to adopt targeted handling strategies. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and solve the problem that the prior art is unable to simultaneously obtain multi-dimensional physical quantities when facing complex water and soil coupling effects, cannot identify multi-parameter synergistic anomalies and their dominant causes, and thus cannot achieve targeted early warning and treatment.

[0006] The technical solution adopted by the present invention to solve its technical problem is: a method for monitoring the stability of underground concrete structure groups in sewage treatment plants, including the following steps: S1, setting up monitoring points at key locations of the concrete structure group, and acquiring concrete strain values, water-soil interface pressure values, interface shear displacement values ​​and steel stress values ​​at each monitoring point within the same monitoring period.

[0007] S2. Based on the current concrete strain value, soil-water interface pressure value, interface shear displacement value, and steel reinforcement stress value, calculate the rate of change of their physical properties relative to the previous monitoring value.

[0008] S3. Identify abnormal synergistic zones based on the rate of change of physical properties and determine the dominant abnormal physical quantity; classify the abnormal synergistic zones into buoyancy-dominated, lateral pressure-dominated, or seepage-dominated types according to the type of dominant abnormal physical quantity.

[0009] S4. Statistically count the frequency of anomalies in each classified anomaly coordination zone within a preset time window, and calculate the average rate of change of each monitoring point within it. Obtain the risk index based on the frequency of anomalies and the average rate of change, and output a graded early warning signal and the corresponding spatial distribution map of the anomaly coordination zone based on the risk index.

[0010] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention can directly reflect the comprehensive response state of underground structures under water-soil coupling by simultaneously collecting four types of physical quantities: concrete strain value, water-soil interface pressure value, interface shear displacement value and steel stress value, and by setting up monitoring points in a targeted manner according to the differences in failure mechanisms at different key locations, thereby improving the comprehensiveness and targeting of monitoring.

[0011] 2. This invention calculates the rate of change of the physical properties of each physical quantity relative to the previous monitoring period, and based on this, identifies spatially associated abnormal coordination zones, determines the dominant abnormal physical quantity, and classifies the abnormal coordination zones according to the dominant abnormal physical quantity. This not only effectively identifies real engineering risks and clarifies their dominant causes, providing a clear basis for subsequent differentiated handling, but also solves the problem of poor adaptability of static threshold early warning to dynamic working conditions.

[0012] 3. This invention calculates a risk index by combining the frequency of anomalies and the rate of change of physical properties in the abnormal coordination zone, and outputs a graded early warning signal and a corresponding spatial distribution map of the abnormal coordination zone based on this index; thus, it achieves visualized early warning, which helps maintenance personnel to quickly locate risks and formulate response strategies. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a schematic diagram of the monitoring method of the present invention;

[0015] Figure 2 This is a schematic diagram of the process for calculating the rate of change of physical properties according to the present invention;

[0016] Figure 3 This is a schematic diagram of the process for identifying abnormal collaborative regions in this invention;

[0017] Figure 4 This is a schematic diagram illustrating the process of obtaining the risk index according to the present invention. Detailed Implementation

[0018] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention. Furthermore, it should be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale.

[0019] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use. Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and apparatus should be considered part of the specification.

[0020] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0022] The following description, in conjunction with the accompanying drawings, details a specific scheme for a method for monitoring the stability of underground concrete structures in a wastewater treatment plant, as provided by this invention.

[0023] Please see Figure 1 The present invention provides a flowchart of a method for monitoring the stability of an underground concrete structure group in a sewage treatment plant, which includes the following steps: Step S1: Set up monitoring points at key locations of the concrete structure group, and within the same monitoring period, obtain the concrete strain value, water-soil interface pressure value, interface shear displacement value and steel stress value of each monitoring point.

[0024] Among them, the water-soil interface pressure value refers to the total normal pressure acting on the outer surface of the underground concrete structure, which is formed by the effective stress of the surrounding soil and the pore water pressure.

[0025] Interface shear displacement refers to the relative tangential displacement along the direction parallel to the structural joint or the contact surface between the structure and the soil.

[0026] Furthermore, in order to achieve efficient and accurate monitoring, this invention does not uniformly deploy all key locations, but instead adopts a scheme of first classifying key locations according to failure mechanisms, and then deploying monitoring points based on these classifications.

[0027] Specifically, considering that permanent joints and post-construction strips are structurally weak points, their connection stiffness is much lower than that of integrally cast concrete. Under the action of temperature stress, shrinkage stress, or uneven settlement, they are very likely to become the starting point for deformation concentration and crack initiation.

[0028] Therefore, the locations of all permanent joints and post-construction pouring strips between structural components as indicated in the structural design drawings are classified as critical locations. These structural components include, at a minimum, major load-bearing members such as the base slab, top slab, side walls, and beams.

[0029] For a certain type of critical location, the core of monitoring is to capture the relative movement of the interface. Therefore, by installing joint gauges or unidirectional displacement gauges on the structural surfaces on both sides of the joint or post-cast strip, with the axial direction of the joint gauges strictly parallel to the joint plane, the relative displacement of the structural components on both sides of the joint or interface along a direction parallel to the joint or interface can be directly measured, thereby obtaining the interface shear displacement value.

[0030] Considering that the section with the highest internal force is the region with the highest stress level in the structure under service conditions, it is often the starting point for crack initiation and steel reinforcement yielding. Therefore, the location of the component section with the highest calculated internal force value in the structural calculation report is listed as a Class II critical location.

[0031] The internal force calculations mainly include bending moment, shear force, and axial force. These are typically calculated using finite element structural analysis software such as MIDAS and ABAQUS based on the design load conditions. The specific calculation process is existing technology and will not be elaborated upon in this invention.

[0032] For the two key locations, the core of monitoring is to understand the stress state of the internal steel bars. Therefore, the stress value of the steel bars is obtained by using monitoring elements, such as vibrating wire steel bar stress gauges, which are installed on the main load-bearing steel bars.

[0033] The main reinforcing bars can be determined based on the reinforcement diagram in the structural calculation book, and are usually the longitudinal bars that bear the maximum bending moment or tensile force.

[0034] Considering that different soil layers exhibit significant differences in mechanical and hydrological properties such as elastic modulus, compressibility, and permeability, such as the boundary between clay and sand, and the transition zone between soft and hard soil, structures situated on the boundary lines of different soil layers are prone to uneven settlement.

[0035] When the elevation of the bottom / outer surface of the structural base slab or side wall is consistent with or very close to the highest historical groundwater level of the site, it means that it is subjected to the maximum water pressure for a long period or periodically, and is a sensitive area for buoyancy resistance and seepage prevention.

[0036] Therefore, based on the engineering geological profile, sections where the foundation slab or sidewalls of underground structures are situated at the boundary between different soil layers, or where their elevation corresponds to the historical highest groundwater level, are classified as three types of key locations. The historical highest groundwater level can be determined by the geological survey report.

[0037] For the three key locations, the core of the monitoring is to obtain the external water and soil load. Therefore, the water and soil interface pressure value is obtained by using monitoring elements that are deployed on the outer surface of the structure and whose sensing surface is flush with the outer surface of the structure, such as soil pressure cells pre-embedded on the inner surface of the formwork before concrete pouring.

[0038] Considering that long-term or temporary loads, such as newly constructed structures nearby, heavy loads, areas with frequent heavy vehicle traffic, and adjacent areas where excavation, piling, dewatering, or other activities are underway or may be carried out, can alter the distribution of soil pressure around the structure and generate additional squeezing or traction effects.

[0039] Therefore, based on the on-site survey records, the outer sidewalls and base slab sections adjacent to the work area with additional ground loads or soil disturbance were identified as four types of key locations.

[0040] For the four key locations, it is necessary to monitor both external loads and internal responses simultaneously. Therefore, it is necessary to pre-embed soil pressure cells on the outer surface of the structure to obtain the water-soil interface pressure value, and to install steel stress gauges on the corresponding main reinforcing bars to obtain the steel stress value.

[0041] In addition, to comprehensively assess the condition of the concrete itself, the concrete strain values ​​are obtained at all key locations using monitoring elements deployed in the concrete, such as vibrating wire concrete strain gauges.

[0042] The determination of the monitoring cycle needs to balance the timeliness of monitoring with the stability of data. Considering that the changes in the underground structure of a wastewater treatment plant due to environmental factors such as groundwater level and temperature are usually measured in days, this invention exemplarily uses 24 hours as a standard monitoring cycle.

[0043] If the structure is in a rapidly changing phase, such as during the later stages of construction or during dewatering operations, the monitoring cycle can be shortened to 12 hours or even less; if the structure has been in operation for many years and the surrounding hydrogeological environment is stable, the monitoring cycle can be appropriately extended to 48 hours.

[0044] It is important to note that after monitoring begins, at least one full monitoring cycle must be completed to obtain initial data.

[0045] Please see Figure 2 Step S2: Based on the current concrete strain value, soil-water interface pressure value, interface shear displacement value, and steel reinforcement stress value, calculate the rate of change of their physical properties relative to the previous monitoring value.

[0046] The specific process is as follows: First, the concrete strain value, water-soil interface pressure value, interface shear displacement value and steel stress value of each monitoring point in the current monitoring cycle and the previous monitoring cycle are paired to form the previous and next cycle data pairs of various physical quantities.

[0047] Next, based on the data pairs from previous and subsequent cycles, the difference between the current cycle monitoring value and the previous cycle monitoring value of each type of physical quantity at each monitoring point is calculated, and the difference is divided by the actual duration from the previous monitoring cycle to the current monitoring cycle to obtain the original rate of change of each type of physical quantity in the current monitoring cycle.

[0048] Then, the mean and standard deviation of the historical change rate of various physical quantities within the preset historical benchmark monitoring period are calculated.

[0049] Finally, the current original rate of change is subtracted from the corresponding historical rate of change mean, and then divided by the corresponding historical rate of change standard deviation to obtain the standardized rate of change of each type of physical quantity at each monitoring point in the current monitoring period, which is taken as the rate of change of physical properties.

[0050] The rate of change of physical properties is a quantitative indicator that characterizes the degree of drastic change of four types of monitored physical quantities over time: concrete strain, water-soil interface pressure, interface shear displacement, and steel reinforcement stress. The larger the absolute value, the more abnormal the change, and the sign indicates the direction of change.

[0051] As a preferred embodiment of the present invention, the historical baseline monitoring period can be determined and updated through the following process: In the initial monitoring stage, data from multiple consecutive monitoring periods in the previous period are used as the initial historical baseline monitoring period. However, it should be noted that the number of monitoring periods in the previous period should not be less than thirty. If it is less than thirty, all existing data can be used temporarily.

[0052] After stable monitoring, a sliding time window is dynamically maintained as the current historical baseline monitoring period, which includes multiple monitoring cycles that have recently been completed without triggering a tiered warning. Whenever a new monitoring cycle is completed without triggering a warning, it is included in the sliding time window and the oldest monitoring cycle is removed.

[0053] Step S3: Identify the abnormal synergistic zone based on the rate of change of physical properties and determine the dominant abnormal physical quantity; classify the abnormal synergistic zone into buoyancy-dominated, lateral pressure-dominated, or seepage-dominated types according to the type of dominant abnormal physical quantity.

[0054] Regions exhibiting spatial proximity and coordinated anomalies in multiple physical quantities are more likely to indicate real engineering risks stemming from common risk sources than single points. Therefore, this invention identifies anomalous coordinated regions after calculating the change rates of each physical property.

[0055] Please see Figure 3Step S31: Identify abnormal cooperative regions based on the rate of change of physical properties.

[0056] The specific process is as follows: First, based on the three-dimensional coordinates of each monitoring point, if the distance between any two monitoring points is less than the preset neighborhood radius, the two monitoring points are determined to be spatially adjacent points; otherwise, they are determined to be non-spatially adjacent points.

[0057] Considering that the size of a single pool or structure in a wastewater treatment plant is typically on the order of tens of meters, this invention exemplarily uses 20 meters as the neighborhood radius, which can effectively capture the interaction between the same structural unit or adjacent units. If the structure is very large or the monitoring points are sparse, it can be appropriately increased to 30 meters; if the structure is compact or requires precise risk positioning, it can be reduced to 10 meters.

[0058] Next, for two monitoring points that are spatially adjacent to each other, if both exceed the preset co-anomaly threshold in the rate of change of physical properties of at least two types of physical quantities, such as concrete strain and steel stress, or soil and water pressure and shear displacement being abnormal at the same time, then the two monitoring points are marked as anomaly correlation pairs; otherwise, no special marking is performed.

[0059] In this invention, the cooperative anomaly threshold can be set through historical data statistics. For example, based on statistical principles, the 95th percentile of the historical standardized rate of change can be used as the cooperative anomaly threshold.

[0060] In a preferred embodiment of the present invention, in order to further improve the accuracy of identifying abnormal cooperative regions, it is determined whether the abnormal association pairs conform to the preset physical mechanism of structural instability; if they conform, a mark indicating abnormal mechanism is added; otherwise, no mark is added.

[0061] The physical mechanisms of structural instability mainly include: (1) simultaneous abnormality of water-soil interface pressure and steel stress, which corresponds to the redistribution of internal forces due to rapid changes in external water and soil loads; (2) simultaneous abnormality of water-soil interface pressure and interface shear displacement, which corresponds to relative displacement of the structure caused by seepage or instability of the soil contact surface; (3) simultaneous abnormality of concrete strain and steel stress, which corresponds to coordinated deformation of the structural components under load.

[0062] Finally, all monitoring points connected by anomaly association pairs are grouped into a monitoring point group, and this monitoring point group and its corresponding spatial area are preliminarily identified as anomaly coordination zone.

[0063] Since the initially identified areas are based solely on monitoring point locations, their boundaries are relatively rough. Therefore, further boundary optimization and confirmation of the initially identified anomalous coordination areas are necessary.

[0064] Step S32: Optimization and confirmation of the boundary of the abnormal coordination zone. The specific process is as follows: Based on the three-dimensional coordinates of the monitoring points included in the initially identified abnormal coordination zone, the horizontal projection range is determined by calculating the minimum bounding rectangle of the X and Y coordinates of all monitoring points.

[0065] Next, based on the CAD-built 3D structural model, a spatial query algorithm is used to extract the outer surface contours of all components that intersect with the horizontal projection range, and these contours are connected as candidate structural boundaries. Here, components refer to the solid parts that make up the structure, such as base plates, side walls, beams, and columns.

[0066] Meanwhile, from the engineering geological profile map reflecting the distribution of strata along the depth, the boundary curves of all different soil layers that intersect with the candidate structure boundary in the vertical projection direction are extracted through graphic recognition or coordinate comparison; among them, different soil layers include clay, silt, sand, rock, etc.

[0067] Finally, considering that structural instability often occurs in the coupling zone between structural geometrical abrupt changes and strata abrupt changes, the candidate structural boundary and soil layer boundary curves are superimposed according to spatial coordinates, and the closed spatial area jointly enclosed by the two is taken as the finally confirmed abnormal synergistic zone.

[0068] In a preferred embodiment of the present invention, when the candidate structure boundary and the soil layer boundary curve cannot be enclosed together, the candidate structure boundary is preferentially used as the main boundary; if the main boundary itself cannot be closed, its endpoint is connected to the nearest soil layer boundary line that can form a closure, forming the smallest circumscribed closed area containing all abnormal monitoring points, which is the finally confirmed abnormal coordination area.

[0069] Step S33: Determine the dominant abnormal physical quantity and classify the abnormal coordination region according to the type of the dominant abnormal physical quantity, so as to formulate differentiated response strategies in the future.

[0070] Specifically, this involves calculating the arithmetic mean of the rates of change of various physical properties at all monitoring points within each finally confirmed anomaly coordination zone.

[0071] The type corresponding to the rate of change of the physical property with the largest absolute value of the arithmetic mean is identified as the dominant anomalous physical quantity.

[0072] According to the following rules: (1) When the dominant abnormal physical quantity is the water-soil interface pressure, if the corresponding abnormal coordination area is mainly distributed in the structural bottom plate area, it indicates that the upward water-soil load borne by the bottom plate area has increased abnormally. Its main risk is the anti-buoyancy stability problem caused by the increase of groundwater buoyancy, which can easily lead to the overall floating of the structure or the bottom plate bulging. Then, the abnormal coordination area is classified as the buoyancy-dominant type.

[0073] If the corresponding abnormal coordination zone is mainly distributed in the structural side wall area, it indicates that the lateral external soil and water load borne by the side wall area is abnormal. The main risk is an increase in external soil pressure or water pressure, which may lead to bending, cracking or even overturning of the wall. Therefore, the abnormal coordination zone is classified as lateral pressure-dominated.

[0074] Otherwise, auxiliary judgment is made based on the combination of the rate of change of physical properties of each monitoring point in the abnormal coordination zone: if the water-soil interface pressure and steel reinforcement stress are abnormally coordinated, it is classified as either buoyancy-dominated or lateral pressure-dominated based on the spatial relationship with the already classified adjacent areas; if the water-soil interface pressure and interface shear displacement are abnormally coordinated, it is classified as seepage-dominated; otherwise, it is marked as an anomaly to be verified, and the dominant abnormal physical quantity is indicated as water-soil interface pressure.

[0075] (2) When the dominant abnormal physical quantity is interfacial shear displacement or concrete strain, it indicates that the structure may have experienced significant relative displacement or material deformation. In the underground structural environment of sewage treatment plants, such anomalies are often caused or exacerbated by hydraulic action. Subsequently, the corresponding anomaly synergistic zone is classified as seepage-dominated.

[0076] (3) When the dominant abnormal physical quantity is the steel reinforcement stress, it indicates that the internal stress state of the structure has changed significantly. At this time, if the corresponding abnormal coordination zone is mainly distributed in the bottom plate area of ​​the structure, it is classified as the floating support type; if it is mainly distributed in the side wall area of ​​the structure, it is classified as the lateral pressure type; otherwise, based on the consideration that seepage will also cause internal force anomalies, it is classified as the seepage type.

[0077] It should be noted that "mainly distributed in" refers to the percentage of monitoring points within the abnormal coordination zone that are located in the corresponding structural area, thus avoiding misjudgment due to a small number of monitoring points. The corresponding percentage can be determined by calculating the number or area proportion of monitoring points located on the base slab and side walls within the projected area of ​​the abnormal coordination zone. For example, if more than 60% of the monitoring points or area belong to the base slab, it is judged to be mainly distributed in the structural base slab area.

[0078] However, for abnormal coordination areas with a small number of monitoring points, such as four or fewer monitoring points, classification is made directly based on the dominant abnormal physical quantity and with reference to the specific structural location of the monitoring point.

[0079] Step S4: Count the frequency of anomalies in each classified anomaly coordination zone within a preset time window, calculate the average rate of change of each monitoring point within it, obtain the risk index based on the frequency of anomalies and the average rate of change, and output a graded early warning signal and the corresponding spatial distribution map of the anomaly coordination zone based on the risk index.

[0080] Please see Figure 4 Step S41: Obtain the risk index based on the frequency of anomalies and the average rate of change.

[0081] Specifically, the total number of times each classified abnormal collaborative area is identified within a preset time window is used as the anomaly occurrence frequency.

[0082] In this invention, 30 days is exemplarily used as the preset time window length. This is because structural stability issues are often a cumulative development process, and 30 days can better reflect the activity level of short- to medium-term risks. If the structure is in a period of rapid change, such as during the rainy season or near deep foundation pit excavation, the time window can be shortened to 15 days; if used to assess the long-term, slow development trend of the structure, the time window can be extended to 60 days.

[0083] Next, within the same time window, for each identification result of the abnormal coordination zone, the average rate of change of physical properties of all monitoring points in the abnormal coordination zone is calculated as the average rate of change.

[0084] Then, the arithmetic mean of the absolute values ​​of all average rates of change within this time window is calculated as the historical average rate of change intensity. The historical average rate of change intensity reflects the average severity of anomalous changes.

[0085] Subsequently, the min-max normalization method can be used to normalize the frequency of anomalies and the intensity of historical average rates of change to the [0, 1] interval, respectively. This yields the normalized frequency of anomalies. Strength of historical average rate of change .

[0086] Simultaneously, the ratio of the number of anomalous association pairs with attached mechanistic anomalous labels to the total number of anomalous association pairs within the anomalous synergistic region is calculated as the mechanistic significance factor M.

[0087] In a preferred embodiment of the present invention, in order to reflect the synergistic amplification effect of multiple risk factors, the risk index R is calculated using the following weighted product formula, specifically: .

[0088] Here, α, β, and γ are weighting indices used to adjust the contribution of each factor to the total risk. They can be determined through multiple regression analysis or principal component analysis based on expert experience or historical data analysis. These are existing techniques and will not be elaborated on here. They usually satisfy α + β + γ = 1.

[0089] Considering that the intensity of the historical average rate of change directly quantifies the severity of the anomaly and best reflects the immediate harm of the risk, it is assigned the highest weighting index β, with an example value of 0.5.

[0090] The higher the value of the mechanism significance factor, the greater the possibility that the anomaly in the current abnormal synergistic area is caused by a clear engineering risk source such as a surge in soil and water load and seepage. Therefore, it can effectively improve the early warning sensitivity of risks that are highly concealed, in the early stage of development but with clear mechanisms. Therefore, it is assigned the second highest weight index α, with an example value of 0.3.

[0091] Step S42: Output graded early warning signals based on the risk index. Specifically: Determine the overall range of risk index values ​​based on the risk index R of all current abnormal coordination zones, i.e., [ ].

[0092] Based on the current risk index distribution of all abnormal collaborative zones, the overall value range is divided into multiple continuous risk level intervals. This is most common and practical in engineering risk management and emergency response, and is usually divided into three intervals: low risk, medium risk, and high risk.

[0093] As a preferred embodiment of the present invention, the quantile method is used for division. Specifically, all current risk indices are sorted in ascending order of value, and then divided into 3 equal parts. The range of values ​​before the 1 / 3 quantile is defined as the low-risk range, the range between the 1 / 3 quantile and the 2 / 3 quantile is defined as the medium-risk range, and the range after the 2 / 3 quantile is defined as the high-risk range.

[0094] Because monitoring data from different or even the same wastewater treatment plant may fluctuate at different times, using preset fixed thresholds for classification may lead to overly sensitive or insensitive early warnings in certain periods. This invention dynamically divides risk level intervals based on the current data distribution, adaptively matching the actual risk status of the current structure, ensuring that the early warning level is always associated with the most dangerous abnormal synergy zone, thereby improving the accuracy of early warnings.

[0095] Then, the risk index of each abnormal coordination zone is compared with the risk level range to determine its corresponding risk level. Finally, an early warning signal corresponding to the determined risk level is output. The early warning signal usually includes: text information, such as XX area, high risk, float-dominated type; color coding, such as red for high risk, yellow for medium risk, and green for low risk; and audible alarms. At the same time, it is pushed to the operation and maintenance personnel in real time through monitoring platforms, mobile apps, etc.

[0096] Step S43: Generate a spatial distribution map of the abnormal coordination zone. This enables risk visualization and assists in precise location.

[0097] Specifically, the design drawings of the underground concrete structure complex are used as the background map. The design drawings refer to CAD or BIM two-dimensional site plans that include all structural plan and section layouts.

[0098] The final confirmed boundary coordinates of each abnormal coordination zone are overlaid onto the corresponding spatial positions on the background map.

[0099] Then, based on the classification results of each abnormal coordination zone, on the background map with superimposed boundary coordinates, the closed areas under the jurisdiction of each abnormal coordination zone are filled with different filling patterns specifically used to represent the buoyancy-dominated, lateral pressure-dominated, and seepage-dominated types.

[0100] Fill patterns can be different colors, such as blue for buoyancy-dominant types, orange for lateral pressure-dominant types, and cyan for seepage-dominant types; they can also be different profile lines, such as diagonal lines, grids, dot matrix, or color blocks with different transparency. The specific fill pattern can be selected according to the actual situation.

[0101] Next, based on the risk level of each abnormal coordination zone, add labels containing risk values ​​to the closed areas of each filled abnormal coordination zone. These labels are typically text boxes that clearly display the risk index and risk level of the corresponding abnormal coordination zone.

[0102] Finally, the completed and labeled background map is output as the final spatial distribution map of the anomaly collaboration area. This map visually displays the location, type, level, and numerical value of risks, allowing operations personnel to quickly locate risks and formulate response strategies.

[0103] It should be noted that the spatial distribution map of the abnormal collaboration area should also use specific icons or colors to mark the anomalies to be verified.

[0104] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0105] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0106] In addition, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0107] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0108] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for monitoring the stability of underground concrete structure groups in a sewage treatment plant, characterized in that, Includes the following steps: S1. Set up monitoring points at key locations in the concrete structure group, and obtain the concrete strain value, water-soil interface pressure value, interface shear displacement value and steel stress value at each monitoring point within the same monitoring cycle. S2. Based on the current concrete strain value, water-soil interface pressure value, interface shear displacement value and steel stress value, calculate the rate of change of physical properties relative to the previous period's monitoring value. S3. Identify abnormal synergistic zones based on the rate of change of physical properties and determine the dominant abnormal physical quantity; classify the abnormal synergistic zones into buoyancy-dominated, lateral pressure-dominated, or seepage-dominated types according to the type of dominant abnormal physical quantity. The process of determining the dominant anomalous physical quantity is as follows: Calculate the arithmetic mean of the rates of change of various physical properties at all monitoring points within each finally confirmed anomaly coordination zone; The type corresponding to the rate of change of the physical property with the largest absolute value of the arithmetic mean is identified as the dominant anomalous physical quantity; The process of identifying abnormal cooperative regions based on the rate of change of the aforementioned physical properties is as follows: Based on the three-dimensional coordinates of each monitoring point, when the distance between any two monitoring points is less than the preset neighborhood radius, the two monitoring points are determined to be spatially adjacent points. For two monitoring points that are spatially adjacent to each other, if both exceed a preset collaborative anomaly threshold in the rate of change of physical properties of at least two types of physical quantities, they are marked as an abnormal correlation pair. All monitoring points connected by anomaly pairs are grouped into a monitoring point group, and the monitoring point group and its corresponding spatial area are initially identified as an anomaly coordination zone. The boundaries of the initially identified abnormal cooperation regions are optimized and confirmed, specifically as follows: Based on the three-dimensional coordinates of the monitoring points contained in the preliminarily identified abnormal coordination zone, its horizontal projection range is determined. Extract the outer surface contours of all components that intersect with the horizontal projection range from the 3D structural model, and use them as candidate structural boundaries; Extract the boundary curves of all different soil layers that intersect with the candidate structure boundary in the vertical projection direction from the engineering geological profile. The candidate structure boundary and soil layer boundary curve are superimposed according to spatial coordinates, and the closed spatial area jointly enclosed by the two is taken as the finally confirmed abnormal synergy area. At the same time, it determines whether the abnormal correlation pairs conform to the preset physical mechanism of structural instability; if they do, it adds a mark indicating that the mechanism is abnormal. Otherwise, no marker is added; S4. Count the total number of times each classified abnormal collaborative area is identified within a preset time window, and use this as the frequency of abnormal occurrence. Within the same time window, for each identification result of the abnormal coordination zone, the average rate of change of physical properties of all monitoring points in the abnormal coordination zone is calculated as the average rate of change. Calculate the arithmetic mean of the absolute values ​​of all average rates of change within the time window, and use it as the historical average rate of change intensity. Normalize the frequency of anomalies and the intensity of historical average rate of change, respectively, to obtain the normalized frequency of anomalies. Strength of historical average rate of change ; The ratio of the number of anomalous association pairs with attached mechanistic anomalous labels to the total number of anomalous association pairs within the anomalous synergistic region is calculated and used as the mechanistic significance factor M. The risk index is calculated using the following weighted product formula: ; Where α, β, and γ are weighting indices, α+β+γ=1, and R represents the risk index; The results calculated above are the risk index of the corresponding abnormal coordination zone. Based on the risk index, a graded early warning signal and the corresponding spatial distribution map of the abnormal coordination zone are output.

2. The method for monitoring the stability of underground concrete structures in a sewage treatment plant according to claim 1, characterized in that, The key locations include: All permanent joints between structural components and the location of post-construction pouring strips marked in the structural design drawings are classified as critical locations. The location of the component section with the largest internal force calculation value in the structural calculation book is listed as a Class II key location; Based on the engineering geological profile, the sections where the bottom slab or sidewall of the underground structure is located on the boundary line of different soil layers or where the elevation corresponds to the historical highest groundwater level are classified as three types of key locations. Based on the on-site survey records, the outer sidewalls and base slab sections adjacent to the work area with additional ground loads or soil disturbance were identified as four types of key locations.

3. The method for monitoring the stability of underground concrete structures in a sewage treatment plant according to claim 2, characterized in that, The process for obtaining the concrete strain value, soil-water interface pressure value, interface shear displacement value, and steel reinforcement stress value is as follows: Concrete strain values ​​were acquired at all critical locations using monitoring elements deployed within the concrete. At a critical location, the interface shear displacement value is obtained by measuring the relative displacement of the structures on both sides of the joint or interface along a direction parallel to the joint or interface. In two key locations, the stress value of the steel bars is obtained by monitoring elements installed on the main reinforcing bars. At key locations in categories three and four, the water-soil interface pressure value is obtained by using monitoring elements deployed on the outer surface of the structure with the sensing surface flush with the outer surface of the structure. Monitoring elements were also installed on the main reinforcing bars at four key locations to obtain the stress values ​​of the reinforcing bars.

4. The method for monitoring the stability of underground concrete structures in a sewage treatment plant according to claim 1, characterized in that, Step S2 specifically involves: Pair the concrete strain value, water-soil interface pressure value, interface shear displacement value and steel stress value of each monitoring point in the current monitoring cycle with the previous monitoring cycle to form the previous and next cycle data pairs of various physical quantities. Based on the data pairs from previous and subsequent cycles, the difference between the current cycle monitoring value and the previous cycle monitoring value of each type of physical quantity at each monitoring point is calculated, and the difference is divided by the actual duration from the previous monitoring cycle to the current monitoring cycle to obtain the original rate of change. Calculate the mean and standard deviation of the historical rate of change of various physical quantities within the preset historical benchmark monitoring period; Subtracting the mean of the corresponding historical rates of change from the current original rate of change, and then dividing by the standard deviation of the corresponding historical rates of change, yields the standardized rate of change of each type of physical quantity at each monitoring point in the current monitoring period, which is taken as the rate of change of physical properties.

5. The method for monitoring the stability of underground concrete structures in a sewage treatment plant according to claim 1, characterized in that, The process of classifying abnormal synergistic zones into buoyancy-dominated, lateral pressure-dominated, or seepage-dominated types is as follows: When the dominant abnormal physical quantity is the water-soil interface pressure, if the corresponding abnormal coordination zone is mainly distributed in the structural base plate area, it is classified as the buoyancy-dominated type; if the corresponding abnormal coordination zone is mainly distributed in the structural side wall area, it is classified as the lateral pressure-dominated type. When the dominant abnormal physical quantity is interfacial shear displacement or concrete strain, it is classified as seepage-dominated type. When the dominant abnormal physical quantity is steel reinforcement stress, if the corresponding abnormal coordination area is mainly distributed in the structural base plate area, it is classified as floating support dominant type; if the corresponding abnormal coordination area is mainly distributed in the structural side wall area, it is classified as lateral pressure dominant type.

6. The method for monitoring the stability of underground concrete structures in a sewage treatment plant according to claim 1, characterized in that, The process of outputting graded early warning signals based on the aforementioned risk index is as follows: Based on the risk indices of all current abnormal collaborative zones, determine the overall range of risk index values; Based on the current risk index value distribution of all abnormal collaborative zones, the overall value range is divided into multiple continuous risk level intervals; The risk index of each abnormal coordination zone is compared with the risk level range to determine its corresponding risk level. Output early warning signals corresponding to the determined risk level.

7. The method for monitoring the stability of underground concrete structure groups in a sewage treatment plant according to claim 6, characterized in that, The process of generating the spatial distribution map of the abnormal cooperation region is as follows: The design drawings of the underground concrete structure complex were used as the background map. The final confirmed boundary coordinates of each abnormal coordination zone are overlaid onto the corresponding spatial positions on the background map; Based on the classification results of each abnormal coordination zone, on the background map with superimposed boundary coordinates, the closed areas under the jurisdiction of each abnormal coordination zone are filled with different filling patterns specifically used to represent the buoyancy-dominated, lateral pressure-dominated, and seepage-dominated types. Based on the risk level of each abnormal coordination zone, add labels containing risk values ​​within the closed areas of each filled abnormal coordination zone. The completed and labeled background map will be output as the final spatial distribution map of the anomaly coordination area.

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