Prediction method for damage of prestressed concrete cylinder pipe in complex environment

Abstract

The invention discloses a method for predicting the damage of a prestressed concrete cylinder pipe in a complex environment, and relates to the technical field of pipeline structure health monitoring, and the method comprises the steps: collecting multi-physical field data through deploying multiple types of sensors, transmitting the data to a central monitoring system in a wireless manner, carrying out the standardized preprocessing, and obtaining a multi-source fusion data set; a salt migration driving index dsa, a stress disturbance induction index yry and an electrochemical activity potential index che are constructed, a comprehensive corrosion risk index SCR is obtained, and corrosion behavior evaluation is carried out. And when the corrosion behavior is evaluated as a disturbance sign, a corrosion change prediction index CAR is further calculated according to time sequence evolution forming a corrosion risk index SCR, grading evaluation and transition identification of the corrosion state are realized, an evaluation result is stored in a database, and a corrosion risk evolution trend is presented through a visual chart. The method supports early warning and emergency response decision making, and has high adaptability and engineering practicability without adding hardware.

Description

Technical Field

[0001] The present invention relates to the technical field of pipeline structure health monitoring, and in particular to a damage prediction method for prestressed steel cylinder concrete pipes in complex environments. Background Art

[0002] Prestressed concrete-cylinder pipes (PCCs) are key structures widely used in urban water supply networks, large-scale industrial water supply, and long-distance water supply projects. Their internal core concrete, steel cylinder, and prestressed steel wire layer together form the main pressure-bearing system, characterized by strong pressure-bearing capacity, large pipe diameter, and good durability. However, during service, PSCs are often exposed to complex geological, hydrological, and environmental stress environments, making them susceptible to damage from a variety of factors, including salt penetration, electrochemical reactions, and stress disturbances. Traditional damage identification often relies on post-destruction assessments or fixed-period maintenance, which cannot promptly reflect the actual corrosion status and its development trends. Therefore, constructing a damage prediction method that is oriented to complex environments, has the ability to fuse multi-source data, and can dynamically predict the corrosion evolution process has become a core technical requirement for ensuring the safe operation of PSCs.

[0003] The current industry generally uses single-factor threshold judgment or regular manual inspections for corrosion analysis and risk assessment, lacking systematic modeling and dynamic linkage analysis methods for multiple coupled factors. Due to the high frequency and high uncertainty of environmental changes, existing methods often do not respond to initial corrosion perturbations or respond with lag, making it difficult to effectively identify microcrack-induced corrosion and its transition process. At the same time, most current methods ignore the nonlinear evolution characteristics of corrosion behavior, the multi-field driving mechanism of the environment, and the staged acceleration trend of the corrosion rate, resulting in the early warning accuracy and real-time performance of corrosion risks being difficult to meet engineering needs. Therefore, how to construct a corrosion analysis model driven by multi-dimensional parameters from the data layer and establish a corrosion evolution index that can be used for prediction is a key issue that urgently needs to be broken through. Summary of the Invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method for predicting damage of prestressed steel cylinder concrete pipes in complex environments, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A method for predicting damage of prestressed steel cylinder concrete pipes in complex environments comprises the following steps:

[0006] S1. Based on the sensor group installed in the prestressed steel cylinder concrete pipe, multi-physical field data is collected in real time, and a multi-source fusion data group is obtained after preprocessing;

[0007] S2. Calculate based on the multi-source fusion data set to obtain the salt migration driving index dsa, stress perturbation induced index yry, and electrochemical activity potential index che, respectively. Then, summarize and calculate to obtain the comprehensive corrosion risk index SCR, and evaluate the corrosion behavior with the set first corrosion behavior evolution threshold A and second corrosion behavior evolution threshold B;

[0008] S3. When the corrosion behavior assessment shows signs of disturbance, the corrosion change prediction index CAR is calculated based on the comprehensive corrosion risk index SCR, and the corrosion transition assessment is performed with the set corrosion acceleration transition threshold Z;

[0009] S4. Store the assessment results in a time series database and display the risk trend change process through a line chart.

[0010] 2. The damage prediction method for prestressed steel cylinder concrete pipes in complex environments according to claim 1, characterized in that: S1 includes S11;

[0011] S11, collecting multi-physical field data of the prestressed steel cylinder concrete pipe in real time based on the sensor group installed at various positions of the prestressed steel cylinder concrete pipe;

[0012] The sensor group includes conductivity sensor, thermocouple, capacitive relative humidity sensor, triaxial accelerometer, gyro and strain hybrid sensor array, ion electrode sensor, electrochemical microcurrent sensor and strain gauge pore pressure gauge.

[0013] Preferably, S1 further includes S12 and S13;

[0014] S12, establishing a communication connection between the sensor group and the central monitoring system via a wireless network, and transmitting the multi-physical field data collected by the sensor group to the central monitoring system in real time;

[0015] S13, pre-processing the multi-physics field data in real time through the central monitoring system to obtain a multi-source fusion data set;

[0016] Preprocessing includes dimensionless processing, denoising, time synchronization processing and filling missing values;

[0017] Dimensionless processing uses Z-Score standardization to perform standard transformation on multi-physics field data. Denoising uses multi-dimensional filtering technology to suppress noise on multi-physics field data and decompose and eliminate the noise effect in the data. Time synchronization uses linear interpolation algorithm to map multi-physics field data at different sampling time points to a unified time baseline. Missing value filling uses missing value interpolation technology to complete multi-physics field data caused by sampling interruption and communication packet loss.

[0018] The multi-source fusion data set includes pore water conductivity dd, prestressed steel wire surface temperature bw, pipe external relative humidity sd, pipe vibration peak vp, ground stress level angle change θ, prestressed steel wire surface chloride ion concentration cf, seepage current is and pore water pressure pg.

[0019] Preferably, S2 includes S21 and S22;

[0020] Based on the obtained multi-source fusion data set, the salt migration driving index dsa, stress perturbation induced index yry and electrochemical activity potential index che are obtained respectively;

[0021] S21. The influence trend of the external environment of the prestressed steel cylinder concrete pipe on the salt migration intensity is simulated by constructing the salt migration driving index DSA, which is used to describe the salt migration potential and driving capacity of the prestressed steel cylinder concrete pipe under the influence of the environment. The specific formula is as follows;

[0022]

[0023] Where ln represents the natural logarithm function, sin represents the sine function, 273.15 represents the constant for converting Celsius to Kelvin, π represents pi, and 200 represents the nonlinear mapping scale factor;

[0024] S22. The risk behavior pattern of abnormal stress disturbance-induced damage is simulated by constructing the stress disturbance induction index yry. The specific formula is as follows:

[0025]

[0026] Where tan represents the tangent function, e represents the exponential function, k1 represents the stress angle magnification adjustment coefficient, which is obtained through experiments by material manufacturers, and θ th It represents the critical angle threshold of principal stress deflection, which is set by the user according to the material structure design specification. K2 represents the smoothing adjustment factor, which is set by the user according to the actual situation.

[0027] Preferably, S2 further includes S23;

[0028] S23. The dynamic level of corrosion activity at the steel cylinder concrete interface is simulated by constructing the electrochemical activity potential index che. The specific formula is as follows:

[0029]

[0030] Where arctan represents the inverse tangent function.

[0031] Preferably, S2 further includes S24;

[0032] S24 is used to synthesize the obtained salt migration driving index dsa, stress perturbation induction index yry and electrochemical activity potential index che into a unified index to comprehensively judge the corrosion state, and to obtain the comprehensive corrosion risk index SCR by summarizing and calculating. The specific formula is as follows;

[0033]

[0034] Where ln represents the natural logarithm function.

[0035] Preferably, S24 further includes S241;

[0036] S241. Based on the comprehensive corrosion risk index (SCR) monitored for all prestressed steel cylinder concrete pipes over the past six months, the SCR is ranked from smallest to largest. Using the percentile statistical method, the historical SCR at 50% is set as the first corrosion behavior evolution threshold A, and the historical SCR at 80% is set as the second corrosion behavior evolution threshold B. These are then compared with the real-time SCR, and corrosion behavior is assessed based on the comparison results. The specific assessment plan is as follows:

[0037] When the comprehensive corrosion risk index SCR is less than the first corrosion behavior evolution threshold A, it means that the corrosion state is stable, there is no sign of structural disturbance, and normal monitoring is maintained;

[0038] When the first corrosion behavior evolution threshold A ≤ comprehensive corrosion risk index SCR ≤ second corrosion behavior evolution threshold B, it indicates that there are signs of disturbance in the prestressed steel cylinder concrete pipe. At this time, the corrosion prediction instruction is executed and the monitoring frequency is increased by 50%;

[0039] When the comprehensive corrosion risk index SCR is greater than the second corrosion behavior evolution threshold B, it indicates that the corrosion crack is in a state of expansion. At this time, risk information is generated and transmitted to relevant personnel through the wireless network, reminding them to activate avoidance signs for this section and initiate emergency measures, such as designing an emergency lining protective layer and a rapid pipe replacement plan.

[0040] Preferably, S3 includes S31;

[0041] S31. When the corrosion behavior assessment shows signs of disturbance, the current prestressed steel cylinder concrete pipe is analyzed for accelerated corrosion, and the corrosion change prediction index CAR is calculated using the current comprehensive corrosion risk index SCR as an indicator. The specific formula is as follows:

[0042]

[0043] Where ΔSCR(t) is the first-order difference term of the comprehensive corrosion risk index SCR, Δt represents the sampling time interval, Δ 2SCR(t) is the second-order difference term of the comprehensive corrosion risk index SCR, and ln represents the logarithmic function.

[0044] Preferably, S3 further includes S32;

[0045] S32. Based on the corrosion standards of the prestressed steel cylinder concrete pipe industry, a corrosion acceleration transition threshold Z is preset and compared with the obtained corrosion change prediction index CAR. Based on the comparison results, a corrosion transition assessment is performed. The specific assessment scheme is as follows;

[0046] When the corrosion change prediction index CAR ≤ the corrosion acceleration transition threshold Z, it indicates a normal corrosion rate and normal monitoring is maintained;

[0047] When the corrosion change prediction index CAR is greater than the corrosion acceleration transition threshold Z, it indicates that the corrosion rate is abnormal. At this time, abnormal information is generated and transmitted to relevant personnel through the wireless network, notifying them to intervene, such as plugging, section change, and flow pressure control.

[0048] Preferably, S4 includes S41 and S42;

[0049] S41. The results of the corrosion behavior assessment and the corrosion transition assessment are stored in a time series database, and are marked with a timestamp, a prestressed steel cylinder concrete pipe segment number, a change rate, and a risk level label, and then grouped and sorted according to the pipe segment number;

[0050] S42. Extract the sorted assessment results from the time series database and use a line graph to show the evolution of the corrosion risk value of the prestressed steel cylinder concrete pipe segment over time.

[0051] The horizontal X-axis of the line chart is set as the time dimension, and a solid line and a dotted line are drawn on the vertical Y-axis respectively. The solid line represents the comprehensive corrosion risk index SCR, and the dotted line represents the corrosion change prediction index CAR. Trend change points, such as inflection points and sudden increase segments, are marked, and interactive functions are set to support time window zooming and click-to-view of abnormal points.

[0052] The present invention provides a method for predicting damage of prestressed steel cylinder concrete pipes in complex environments. It has the following beneficial effects:

[0053] (1) This method successfully acquires comprehensive data on corrosion-inducing parameters of prestressed concrete cylinder pipes in saline, high-humidity, and high-stress environments by constructing a multi-physics real-time data acquisition system based on a sensor array. This method also establishes a closed data loop through a wireless network and a central monitoring system to ensure data continuity and timeliness. This data acquisition, preprocessing, and fusion system significantly enhances the spatiotemporal integrity of the model input and the realism of the environmental response.

[0054] (2) This method designs a complete set of multi-index coupling calculation models. Based on the obtained multi-source fusion data set, a summary calculation is performed to obtain the salt migration driving index dsa, the stress perturbation induced index yry, and the electrochemical activity potential index che. The synergy and driving relationship between the multi-source factors is simulated through complex nonlinear functions, and further integrated into the comprehensive corrosion risk index SCR to form a global quantitative representation of the corrosion state. The corrosion behavior is evaluated with the preset first corrosion behavior evolution threshold A and second corrosion behavior evolution threshold B. This modeling method avoids the problem of linear weighting masking the evolution of corrosion heterogeneity. It can also identify potential perturbation critical states through the time series distribution of the comprehensive corrosion risk index SCR. Assisted by percentile threshold analysis and corrosion behavior grade assessment mechanism, it can accurately identify the turning points and high-risk sections of the corrosion state, and realize integrated decision support for prediction and early warning.

[0055] (3) This method introduces the corrosion change prediction index CAR to dynamically calculate the growth trend of the comprehensive corrosion risk index SCR, and combines the transition threshold mechanism to judge the corrosion acceleration behavior, so that risk monitoring is extended from static indicators to dynamic evolution prediction. Combined with the trend chart visualization of the time series database, the intuitive communication and operation and maintenance reference of corrosion information are realized, providing real-time support for pipe section maintenance strategies. This method effectively solves the three major technical bottlenecks in traditional prestressed steel cylinder concrete pipe monitoring: "single data dimension, delayed response, and lack of prediction", and builds a closed-loop system for the entire process of "sensing, analysis, evaluation, prediction and display", which significantly improves the intelligence, dynamicity and foresight level of prestressed steel cylinder concrete pipe structure health monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 Schematic diagram of the steps of the damage prediction method for prestressed steel cylinder concrete pipe under complex environment of the present invention;

[0057] Figure 2 This is a flowchart of the implementation of the damage prediction method for prestressed steel cylinder concrete pipes in complex environments of the present invention. DETAILED DESCRIPTION

[0058] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0059] Example 1

[0060] See also Figure 1 and Figure 2The application provides a prestressed concrete cylinder pipe damage prediction method in a complex environment, and the above object is achieved by the following technical scheme: comprising the following steps:

[0061] S1, real-time acquisition of multi-physical field data according to a sensor group installed on the prestressed concrete cylinder pipe, and acquisition of a multi-source fusion data group after preprocessing;

[0062] S2, calculation according to the multi-source fusion data group, acquisition of a salt migration driving index dsa, a stress disturbance induced index yry and an electrochemical activity potential index che, respectively, and then acquisition of a comprehensive corrosion risk index SCR through summary calculation, and corrosion behavior evaluation with a first corrosion behavior evolution threshold A and a second corrosion behavior evolution threshold B;

[0063] S3, when the corrosion behavior evaluation is a disturbance sign, calculation of a corrosion change prediction index CAR according to the comprehensive corrosion risk index SCR as an index, and corrosion transition evaluation with a corrosion acceleration transition threshold Z;

[0064] S4, storage of the evaluation result into a time series database, and display of a trend change process of the risk through a line graph.

[0065] In this embodiment, multiple heterogeneous sensors are deployed in step S1 to collect multi-physics field data. After dimensionless processing, denoising, time synchronization processing, and filling in missing values, a multi-source fusion data set is obtained, achieving high-dimensional data fusion, ensuring comprehensive perception of corrosion inducements, overcoming the corrosion identification delay problem caused by single-factor observation in existing technologies, and improving the basic data quality and robustness of the monitoring system. In S2 and S3, this method innovatively constructs the salt migration driving index dsa, stress perturbation induced index yry, and electrochemical activity potential index che through the multi-source fusion data set, and performs nonlinear coupling to output the comprehensive corrosion risk index SCR. The corrosion behavior is then evaluated with the preset first corrosion behavior evolution threshold A and second corrosion behavior evolution threshold B. When the corrosion behavior is assessed as having signs of disturbance, the corrosion change prediction index CAR is further constructed to identify the trend of corrosion development rate changes. Compared to traditional linear weighted models, this index system better reflects the complex coupled behavior of the corrosion process, effectively avoids assessment distortion issues under extreme conditions, and can proactively detect signs of microscopic corrosion transitions, enabling a shift from "state identification" to "dynamic prediction" of corrosion. This provides more forward-looking technical support for the health assessment of prestressed steel cylinder concrete pipes. In the S4 phase, by dynamically storing corrosion assessment results and prediction indices in a time-series database and visualizing corrosion evolution trends in the form of interactive line graphs, structured management and intelligent analysis of segment-level risk trajectories are achieved. Compared with existing static detection or periodic manual inspections, this approach significantly improves data utilization efficiency, response timeliness, and transparency of pipeline network operations. It not only enables intelligent identification, risk prediction, and trend tracking of corrosion behavior in complex environments, but also achieves substantial improvements in corrosion warning accuracy, intervention timeliness, and scientific decision-making through the coordinated optimization of data fusion, algorithm modeling, and visual output.

[0066] Example 2

[0067] Please refer to Figure 1 and Figure 2 , specifically: S1 includes S11;

[0068] S11, collecting multi-physical field data of the prestressed steel cylinder concrete pipe in real time based on the sensor group installed at various positions of the prestressed steel cylinder concrete pipe;

[0069] The sensor group includes conductivity sensor, thermocouple, capacitive relative humidity sensor, triaxial accelerometer, gyro and strain hybrid sensor array, ion electrode sensor, electrochemical microcurrent sensor and strain gauge piezometer;

[0070] Conductivity sensors are used to collect pore water conductivity (dd), which reflects the salt ion concentration in groundwater and is the primary driver of corrosion.

[0071] Thermocouples are used to collect the surface temperature bw of the prestressed steel wire. The corrosion rate is related to the temperature index and is used to describe the corrosion chemical kinetics rate;

[0072] The capacitive relative humidity sensor is used to collect the relative humidity sd outside the tube body. The relative humidity determines the openness of the diffusion channel and describes the direct effect of relative humidity on ion migration.

[0073] The triaxial accelerometer is used to collect the peak vibration vp of the pipe body, which is used to describe sudden disturbances and traffic load impacts as a precursor signal of structural damage;

[0074] The gyro and strain hybrid sensor array is used to collect the change in the horizontal stress angle θ, which is used to describe the rotation of the principal stress direction of the soil around the pipe. Abnormal changes indicate displacement or lateral pressure changes in the underground environment, inducing structural deviation and crack opening.

[0075] The ion electrode sensor is used to collect the chloride ion concentration cf on the surface of the prestressed steel wire, which represents the corrosion accelerating ion and is a direct indicator for judging whether the prestressed steel wire has reached a critical corrosion state;

[0076] The electrochemical microcurrent sensor is used to collect the seepage current is, which is a direct physical quantity of the actual corrosion activity. It reflects the natural current intensity generated by the electrochemical potential difference inside the pipe and is the actual corrosion flow signal during the corrosion process.

[0077] The strain gauge piezometer is used to collect pore water pressure pg. High pore pressure tends to drive the water and salt mixture to migrate inward, describing the driving force of pore water and determining whether corrosive ions can penetrate the concrete cover under pressure.

[0078] S1 also includes S12 and S13;

[0079] S12, establishing a communication connection between the sensor group and the central monitoring system via a wireless network, and transmitting the multi-physical field data collected by the sensor group to the central monitoring system in real time;

[0080] S13, pre-processing the multi-physics field data in real time through the central monitoring system to obtain a multi-source fusion data set;

[0081] Preprocessing includes dimensionless processing, denoising, time synchronization processing and filling missing values;

[0082] Dimensionless processing uses Z-Score standardization to perform standard transformation on multi-physics field data. Denoising uses multi-dimensional filtering technology to suppress noise on multi-physics field data and decompose and eliminate the noise effect in the data. Time synchronization uses linear interpolation algorithm to map multi-physics field data at different sampling time points to a unified time baseline. Missing value filling uses missing value interpolation technology to complete multi-physics field data caused by sampling interruption and communication packet loss.

[0083] The multi-source fusion data set includes pore water conductivity dd, prestressed steel wire surface temperature bw, pipe external relative humidity sd, pipe vibration peak vp, ground stress level angle change θ, prestressed steel wire surface chloride ion concentration cf, seepage current is and pore water pressure pg.

[0084] In this embodiment, through the complete process of S11, S22, and S13 in stage S1, this method establishes a multi-dimensional, real-time, and intelligent data acquisition and fusion mechanism, significantly improving the comprehensive perception of corrosion factors in prestressed steel cylinder concrete pipes. By deploying a highly sensitive sensor array, in-situ acquisition of multi-physics field data for prestressed steel cylinder concrete pipes is achieved, breaking the previous limitation of relying on indirect indicators to infer corrosion status. Simultaneously, a wireless network establishes a communication connection between the sensor array and a central monitoring system. The central monitoring system's preprocessing mechanism for dimensionless processing, denoising, time synchronization, and missing value filling of multi-physics field data ensures high accuracy and reliability in terms of temporal consistency and numerical stability, laying a solid data foundation for subsequent corrosion mechanism modeling and dynamic evolution prediction. This solution not only enhances the depth and breadth of monitoring dimensions but also avoids the lag of manual inspections and the fragmentation of point-based sampling, enabling full coverage, high frequency, and intelligent evolution modeling of corrosion risk perception.

[0085] Example 3

[0086] Please refer to Figure 1 and Figure 2 , specifically: S2 includes S21 and S22;

[0087] Based on the obtained multi-source fusion data set, the salt migration driving index dsa, stress perturbation induced index yry and electrochemical activity potential index che are obtained respectively;

[0088] S21. Based on the fact that environmental salt migration capacity is not determined by a single concentration but is also modulated by the coupled effects of temperature and humidity, a salt migration driving index (DSA) is constructed to simulate the influence of the external environment of prestressed steel cylinder concrete pipes on the salt migration intensity. This index is used to describe the salt migration potential and driving capacity of prestressed steel cylinder concrete pipes under environmental influences. The specific formula is as follows:

[0089]

[0090] Where ln represents the natural logarithm function, sin represents the sine function, 273.15 represents the constant for converting degrees Celsius to Kelvin, π represents the circumference of a circle, and is used to map the relative humidity outside the pipe to the radian range. 200 represents the nonlinear mapping scale factor, which is used to control the humidity value within the range of [0,π / 2] as the input of the trigonometric function, ensuring that the effect of humidity on corrosion migration shows a reasonable nonlinear enhancement trend. Used to convert temperature into absolute temperature to meet the consistency of thermodynamic formula, indicating the activity of ions under temperature conditions. By introducing the natural logarithm to simulate the saturation effect of ion migration rate, we avoid the direct linear relationship and conform to the nonlinear trend of diffusion with concentration growth in practice. It is used to normalize the humidity to [0,π / 2] and then take the sine to obtain a mapping of [0,1]. The higher the relative humidity, the stronger the degree of wetting of the diffusion channel and the easier it is for ion diffusion to occur.

[0091] S22. Since corrosion damage is not entirely caused by chemical reactions, and there is also the problem of structural vibration-induced microcracks that exacerbate corrosion damage, a stress perturbation induction index yry is constructed to simulate the risk behavior pattern of damage induced by abnormal stress perturbations. The specific formula is as follows:

[0092]

[0093] Where tan represents the tangent function, e represents the exponential function, and k1 represents the stress angle magnification adjustment coefficient, which is used to adjust the sensitivity of the angle magnification in tan(k1*|θ|) and is obtained through experiments by material manufacturers. th It represents the critical angle threshold of principal stress deflection, which is used to define the principal stress deviation angle threshold of the critical point of structural instability risk. It is set by the user according to the material structure design specification. K2 represents the smoothing adjustment factor, which is used to control the response amplification of the stress disturbance induced index when the stress deflection angle approaches the threshold. It is set by the user according to the actual situation. It represents the response rate of the vibration energy amplitude and is related to the accumulation of structural fatigue. It simulates the cracking effect by introducing the square root energy. Tan(k1*|θ|) represents the amplification term of the abnormal deviation trend, reflecting the rate of deviation of the principal stress direction and nonlinear enhancement. It is used to capture the sudden change sensitive behavior of high-angle deflection. represents the Sigmoid modulation term, and introduces an exponential buffer mechanism. When θ does not reach the risk domain, the value is stable. When θ approaches the critical angle threshold of the principal stress deflection, the output rises rapidly but remains finitely controllable.

[0094] S2 also includes S23;

[0095] S23, the corrosion of the prestressed concrete cylinder pipe is determined by ions, current and interface environment, the dynamic level of the corrosion activity of the steel cylinder concrete interface is simulated by constructing an electrochemical activity potential index che, and the specific formula is as follows;

[0096]

[0097] In the formula, arctan represents the inverse tangent function, cf*is represents the corrosion reaction source term, the charge transfer reaction flux intensity caused by unit concentration of chloride ion, The equivalent synthesis resistance of interface migration resistance is represented by two terms, and the two terms represent the seepage resistance and interface wetting difficulty, The nonlinear coupling correction function is represented by two terms, which is used to express the directional deviation of the interface reaction.

[0098] S2 also includes S24;

[0099] S24, for synthesizing the unified index of the obtained salt migration driving index dsa, stress disturbance induction index yry and electrochemical activity potential index che to comprehensively judge the corrosion state, improve the early warning precision, and calculate the comprehensive corrosion risk index SCR, the specific formula is as follows;

[0100]

[0101] In the formula, ln represents the natural logarithm function, the damage of the prestressed concrete cylinder pipe is usually caused by microcracks, and external force disturbance is one of the important inducements, so ln(1+yry) is introduced to analyze the structural instability of the pipe body under abnormal disturbance and microseismicity, and the logarithmic function is introduced to maintain the nonlinear growth trend and alleviate the influence of high value explosion; The actual corrosion is not determined by the existence of ions itself, but by the activity control of ions participating in the reaction, so The square root is introduced to analyze the rate and capacity of the actual corrosion reaction of the steel and concrete interface, prevent the electrochemical activity potential index from dominating the overall output, and reflect the characteristics of the electrochemical activity potential index in the later corrosion enhancement term, and 1+dsa+yry is used for risk constraint and self-stabilizing adjustment to limit the non-rational amplification caused by local strong disturbance.

[0102] S24 also includes S241;

[0103] S241, according to the comprehensive corrosion risk index SCR of all prestressed concrete cylinder pipes monitored in the past six months, and sorting from small to large, through the percentile statistical method, the historical comprehensive corrosion risk index SCR at 50% is set as the first corrosion behavior evolution threshold A, and the historical comprehensive corrosion risk index SCR at 80% is set as the second corrosion behavior evolution threshold B, then compared with the real-time obtained comprehensive corrosion risk index SCR, and according to the comparison result, the corrosion behavior is evaluated, and the specific evaluation scheme is as follows;

[0104] When the comprehensive corrosion risk index SCR < the first corrosion behavior evolution threshold A, it indicates that the corrosion state is stable, there is no structural disturbance, and normal monitoring is maintained.

[0105] When the first corrosion behavior evolution threshold A ≤ the comprehensive corrosion risk index SCR ≤ the second corrosion behavior evolution threshold B, it indicates that there are signs of disturbance in the prestressed steel cylinder concrete pipe, at which time the corrosion prediction instruction is executed, and the monitoring frequency is increased by 50%.

[0106] When the comprehensive corrosion risk index SCR > the second corrosion behavior evolution threshold B, it indicates that it is in a corrosion crack propagation state, at which time risk information is generated, transmitted to relevant personnel through a wireless network, and relevant personnel are reminded to enable an avoidance sign for this section, and emergency measures such as designing an emergency lining protection layer and a rapid pipe replacement plan are started.

[0107] In this embodiment, by constructing the salt migration driving index dsa, the stress disturbance inducing index yry, and the electrochemical activity potential index che, three highly coupled physical and chemical behavior functions, a core analysis framework of the corrosion process of the prestressed steel cylinder concrete pipe under complex environment is formed, and finally the comprehensive corrosion risk index SCR is fused. The salt migration driving index dsa uses the natural logarithm function and the sine function to construct a nonlinear modulation mechanism of humidity and temperature, to express the combined effect of environmental humidity and temperature conditions on ion migration ability, to express the ion activity under thermodynamic conditions, reflecting the enhancement effect of temperature on ion migration, and through the natural logarithm to suppress linear expansion, to construct a nonlinear growth trend, to normalize humidity to [0, π / 2] and perform sine mapping, to depict the nonlinear enhancement effect of humidity on the wetness of the diffusion channel, and the two parts as a whole show a delicate simulation of the corrosion migration potential under the influence of environmental coupling factors; the stress disturbance inducing index yry simulates the structure disturbance amplification behavior and the buffer adjustment of risk response through the tangent function and the Sigmoid type index function, and expresses the structure vibration peak value vp and the ground stress deflection angle θ jointly, through the tangent function tan(k1*|θ|), to amplify the response sensitivity of the stress angle change, and then combined with the sigmoid modulation function to realize the response mutation feature control when the angle deflection approaches the threshold θ th , which accurately captures the dynamic chain of vibration, deflection, and crack-induced corrosion, and uses square enhancement to increase the driving weight of large-angle disturbance in the corrosion induction process; the electrochemical activity potential index che uses the arctangent function to represent the nonlinear response boundary of the steel cylinder corrosion interface electrochemical reaction, cf*is the active source term of the corrosion reaction, which is the chloride ion concentration and the seepage current, respectively, representing the ion flux per unit time per unit interface and the actual corrosion driving strength, and the denominator represents the interface reaction impedance term, taking into account the blocking effect of pore water pressure pg and conductivity dd, while is a nonlinear directional correction term, which indicates the directional deviation of the ion migration path under multiple resistance factors; the entire formula reflects the physical-electrochemical linkage mechanism of corrosion, emphasizing the actual dynamic response ability of interface corrosion; the SCR comprehensive corrosion risk index is formed by the fusion of the three, and the molecular part is composed of dsa, ln(1+yry) and They respectively reflect the environmental migration drive, disturbance risk perception and corrosion activity. Among them, ln(1+yry) handles the exponential explosion problem of disturbance response, making its output have controllable growth. The imbalance effect when electrochemistry dominates is suppressed; the denominator 1+dsa+yry implements a self-stabilizing constraint to prevent any one factor from dominating the overall judgment result. This formula constructs a non-weighted, cross-modulated fusion method between multi-dimensional corrosion factors, effectively avoiding the misjudgment problem caused by factor imbalance in the traditional linear weight model, and achieves the unified modeling goals of real-world perception of corrosion status, disturbance warning, and trend induction. Through a dual-threshold mechanism based on the percentile method, it realizes graded identification and classified warning of corrosion behavior. This method can jointly identify corrosion behavior under multi-source drive in complex environments. It is suitable for typical high-corrosion risk underground scenarios such as high salinity, high humidity, and multiple stress disturbances, greatly improving the sensitivity, stability, and response rationality of corrosion monitoring.

[0108] Example 4

[0109] Please refer to Figure 1 and Figure 2 , specifically: S3 includes S31;

[0110] S31. When the corrosion behavior assessment shows signs of disturbance, the current prestressed steel cylinder concrete pipe is analyzed for accelerated corrosion, and the corrosion change prediction index CAR is calculated using the current comprehensive corrosion risk index SCR as an indicator. The specific formula is as follows:

[0111]

[0112] Where ΔSCR(t) is the first-order difference term of the comprehensive corrosion risk index SCR, Δt represents the sampling time interval, Δ 2 SCR(t) is the second-order difference term of the comprehensive corrosion risk index SCR, ln represents the logarithmic function, It is the first-order derivative of the comprehensive corrosion risk index SCR, which represents the growth rate of the comprehensive corrosion risk index per unit time and is used to analyze whether the comprehensive corrosion risk index SCR is rising. is the second-order derivative of the comprehensive corrosion risk index SCR, which is used to analyze the rate of increase of the comprehensive corrosion risk index SCR. It is used to perform logarithmic compression on the second-order difference after adding the absolute value to avoid underestimation of small disturbances and suppress large values.

[0113] S3 also includes S32;

[0114] S32. Based on the corrosion standards of the prestressed steel cylinder concrete pipe industry, a corrosion acceleration transition threshold Z is preset and compared with the obtained corrosion change prediction index CAR. Based on the comparison results, a corrosion transition assessment is performed. The specific assessment scheme is as follows;

[0115] When the corrosion change prediction index CAR ≤ the corrosion acceleration transition threshold Z, it indicates a normal corrosion rate and normal monitoring is maintained;

[0116] When the corrosion change prediction index CAR is greater than the corrosion acceleration transition threshold Z, it indicates that the corrosion rate is abnormal. At this time, abnormal information is generated and transmitted to relevant personnel through the wireless network, notifying them to intervene, such as plugging, section change, and flow pressure control.

[0117] In this embodiment, by constructing the corrosion change prediction index CAR and setting the corrosion acceleration transition threshold Z in S3, the present invention introduces a dynamic judgment mechanism of acceleration evaluation and transition identification in corrosion monitoring, breaking through the limitation of traditional methods that can only evaluate the current corrosion situation and are not easy to predict sudden changes in corrosion trends. When the corrosion behavior is assessed as having signs of disturbance, this mechanism calculates the corrosion change prediction index CAR through time difference analysis of the comprehensive corrosion risk index SCR, capturing the real-time changes in corrosion rate and potential acceleration behavior. The formula consists of two parts multiplied together. The first part is Used to judge the basic growth trend of the comprehensive corrosion risk index SCR and whether there is a continuous increase in corrosion risk. Part II The rate of change in the growth trend of the Comprehensive Corrosion Risk Index (SCR) is assessed to detect whether the corrosion rate is accelerating. By combining these two factors, the Corrosion Change Prediction Index (CAR) not only reflects the current level of corrosion risk increase but also incorporates the changing trend of whether the risk increase is intensifying. This gives the CAR dual recognition capabilities for both trends and trend changes. The logarithmic compression mechanism avoids exponential explosion caused by unusually severe perturbations, ensuring the sensitivity, stability, and interpretability of the results. This design is particularly suitable for identifying the critical behavior of prestressed steel cylinder concrete pipes, where corrosion transitions from slow evolution to sudden changes. It forms the core mathematical foundation for identifying and predicting corrosion acceleration. By combining the threshold Z set according to industry standards for transition identification, this module not only provides accurate early warning of sudden corrosion development but also provides scientific triggering conditions for decision-making interventions. Especially in complex scenarios such as sudden seepage surges or drastic environmental changes, this module can proactively detect uncontrolled corrosion trends and automatically issue warnings, significantly improving the timeliness of corrosion prevention and control responses and the proactiveness of emergency management. This truly represents a significant leap from corrosion state identification to corrosion rate monitoring and trend transition warnings.

[0118] Example 5

[0119] Please refer to Figure 1 and Figure 2 , specifically: S4 includes S41 and S42;

[0120] S41. The results of the corrosion behavior assessment and the corrosion transition assessment are stored in a time series database, and are marked with a timestamp, a prestressed steel cylinder concrete pipe segment number, a change rate, and a risk level label, and then grouped and sorted according to the pipe segment number;

[0121] S42. Extract the sorted assessment results from the time series database and use a line graph to show the evolution of the corrosion risk value of the prestressed steel cylinder concrete pipe segment over time.

[0122] The horizontal X-axis of the line chart is set as the time dimension, and a solid line and a dotted line are drawn on the vertical Y-axis respectively. The solid line represents the comprehensive corrosion risk index SCR, and the dotted line represents the corrosion change prediction index CAR. Trend change points, such as inflection points and sudden increase segments, are marked, and interactive functions are set to support time window zooming and click-to-view of abnormal points.

[0123] In this embodiment, through the implementation of step S4, this method systematically stores the corrosion assessment and prediction results in a time series database and provides a high-dimensional visualization display method. This not only achieves the time series structured management of corrosion risk information, but also reveals the intrinsic relationship between corrosion development trends and accelerated transitions through the dynamic comparison of the comprehensive corrosion risk index SCR and the corrosion change prediction index CAR hyperbola in the line graph, facilitating the accurate identification of key risk points. In particular, the annotation of trend change points and the introduction of interactive functions significantly improve the interpretability and operability of the data, allowing pipeline network managers to intuitively track the corrosion evolution path of pipe sections, focus on sudden change sections, and respond quickly to avoid missing early weak abnormal signals. This visual analysis mechanism based on graph algebra and graph joint control is still rare in the existing prestressed steel cylinder concrete pipe operation and maintenance system, and provides a strong support means for achieving "intelligent identification, trend control and accurate early warning" closed-loop corrosion control.

[0124] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A damage prediction method for prestressed steel cylinder concrete pipes in complex environments, characterized by: The following steps are involved: S1. Based on the sensor group installed in the prestressed steel cylinder concrete pipe, multi-physical field data is collected in real time, and a multi-source fusion data group is obtained after preprocessing; S2. Calculate based on the multi-source fusion data set to obtain the salt migration driving index dsa, stress perturbation induced index yry, and electrochemical activity potential index che, respectively. Then, summarize and calculate to obtain the comprehensive corrosion risk index SCR, and evaluate the corrosion behavior with the first corrosion behavior evolution threshold A and the second corrosion behavior evolution threshold B. S3. When the corrosion behavior assessment shows signs of disturbance, the corrosion change prediction index CAR is calculated based on the comprehensive corrosion risk index SCR, and the corrosion transition assessment is performed with the corrosion acceleration transition threshold Z; S4. Store the assessment results in a time series database and display the risk trend change process through a line chart.

2. The damage prediction method for prestressed steel cylinder concrete pipes in complex environments according to claim 1 is characterized by: S1 includes S11; S11, collecting multi-physical field data of the prestressed steel cylinder concrete pipe in real time based on the sensor groups installed at various positions of the prestressed steel cylinder concrete pipe; The sensor group includes conductivity sensor, thermocouple, capacitive relative humidity sensor, triaxial accelerometer, gyro and strain hybrid sensor array, ion electrode sensor, electrochemical microcurrent sensor and strain gauge pore pressure gauge.

3. The damage prediction method for prestressed steel cylinder concrete pipes in complex environments according to claim 2 is characterized by: S1 also includes S12 and S13; S12, establishing a communication connection between the sensor group and the central monitoring system via a wireless network, and transmitting the multi-physical field data collected by the sensor group to the central monitoring system in real time; S13, pre-processing the multi-physics field data in real time through the central monitoring system to obtain a multi-source fusion data set; Preprocessing includes dimensionless processing, denoising, time synchronization processing and filling missing values; Dimensionless processing uses Z-Score standardization to perform standard transformation on multi-physics field data. Denoising uses multi-dimensional filtering technology to suppress noise on multi-physics field data and decompose and eliminate the noise effect in the data. Time synchronization uses linear interpolation algorithm to map multi-physics field data at different sampling time points to a unified time baseline. Missing value filling uses missing value interpolation technology to complete multi-physics field data caused by sampling interruption and communication packet loss. The multi-source fusion data set includes pore water conductivity dd, prestressed steel wire surface temperature bw, pipe external relative humidity sd, pipe vibration peak vp, ground stress level angle change θ, prestressed steel wire surface chloride ion concentration cf, seepage current is and pore water pressure pg.

4. The damage prediction method for prestressed steel cylinder concrete pipes in complex environments according to claim 3 is characterized by: S2 includes S21 and S22; Based on the obtained multi-source fusion data set, the salt migration driving index dsa, stress perturbation induced index yry and electrochemical activity potential index che are obtained respectively; S21. The influence trend of the external environment of the prestressed steel cylinder concrete pipe on the salt migration intensity is simulated by constructing the salt migration driving index DSA, which is used to describe the salt migration potential and driving capacity of the prestressed steel cylinder concrete pipe under the influence of the environment. The specific formula is as follows; Where ln represents the natural logarithm function, sin represents the sine function, 273.15 represents the constant for converting Celsius to Kelvin, π represents pi, and 200 represents the nonlinear mapping scale factor; S22. The risk behavior pattern of abnormal stress disturbance-induced damage is simulated by constructing the stress disturbance induction index yry. The specific formula is as follows: Where tan represents the tangent function, e represents the exponential function, k1 represents the stress angle magnification adjustment coefficient, which is obtained through experiments by material manufacturers, and θ th It represents the critical angle threshold of principal stress deflection, which is set by the user according to the material structure design specification. K2 represents the smoothing adjustment factor, which is set by the user according to the actual situation.

5. The damage prediction method for prestressed steel cylinder concrete pipes in complex environments according to claim 4 is characterized by: S2 also includes S23; S23. The dynamic level of corrosion activity at the steel cylinder concrete interface is simulated by constructing the electrochemical activity potential index che. The specific formula is as follows: Where arctan represents the inverse tangent function.

6. The damage prediction method for prestressed steel cylinder concrete pipes in complex environments according to claim 4 is characterized by: S2 also includes S24; S24 is used to synthesize the obtained salt migration driving index dsa, stress perturbation induction index yry and electrochemical activity potential index che into a unified index to comprehensively judge the corrosion state, and to obtain the comprehensive corrosion risk index SCR by summarizing and calculating. The specific formula is as follows; Where ln represents the natural logarithm function.

7. The damage prediction method for prestressed steel cylinder concrete pipes in complex environments according to claim 6 is characterized by: S24 also includes S241; S241. Based on the comprehensive corrosion risk index (SCR) monitored for all prestressed steel cylinder concrete pipes over the past six months, the SCR is ranked from smallest to largest. Using the percentile statistical method, the historical SCR at 50% is set as the first corrosion behavior evolution threshold A, and the historical SCR at 80% is set as the second corrosion behavior evolution threshold B. These are then compared with the real-time SCR, and corrosion behavior is assessed based on the comparison results. The specific assessment plan is as follows: When the comprehensive corrosion risk index SCR is less than the first corrosion behavior evolution threshold A, it means that the corrosion state is stable, there is no sign of structural disturbance, and normal monitoring is maintained; When the first corrosion behavior evolution threshold A ≤ comprehensive corrosion risk index SCR ≤ second corrosion behavior evolution threshold B, it indicates that there are signs of disturbance in the prestressed steel cylinder concrete pipe. At this time, the corrosion prediction instruction is executed and the monitoring frequency is increased by 50%; When the comprehensive corrosion risk index SCR is greater than the second corrosion behavior evolution threshold B, it indicates that the corrosion crack is in a state of expansion. At this time, risk information is generated and transmitted to relevant personnel through the wireless network, reminding them to activate avoidance signs for this section and initiate emergency measures, such as designing an emergency lining protective layer and a rapid pipe replacement plan.

8. The damage prediction method for prestressed steel cylinder concrete pipes in complex environments according to claim 7 is characterized by: S3 includes S31; S31. When the corrosion behavior assessment shows signs of disturbance, the current prestressed steel cylinder concrete pipe is analyzed for accelerated corrosion, and the corrosion change prediction index CAR is calculated using the current comprehensive corrosion risk index SCR as an indicator. The specific formula is as follows: Where ΔSCR(t) is the first-order difference term of the comprehensive corrosion risk index SCR, Δt represents the sampling time interval, Δ 2 SCR(t) is the second-order difference term of the comprehensive corrosion risk index SCR, and ln represents the logarithmic function.

9. The damage prediction method for prestressed steel cylinder concrete pipes in complex environments according to claim 8, characterized in that: S3 also includes S32; S32. Based on the corrosion standards of the prestressed steel cylinder concrete pipe industry, a corrosion acceleration transition threshold Z is preset and compared with the obtained corrosion change prediction index CAR. Based on the comparison results, a corrosion transition assessment is performed. The specific assessment scheme is as follows; When the corrosion change prediction index CAR ≤ the corrosion acceleration transition threshold Z, it indicates a normal corrosion rate and normal monitoring is maintained; When the corrosion change prediction index CAR is greater than the corrosion acceleration transition threshold Z, it indicates that the corrosion rate is abnormal. At this time, abnormal information is generated and transmitted to relevant personnel through the wireless network, notifying them to intervene, such as plugging, section change, and flow pressure control.

10. The damage prediction method for prestressed steel cylinder concrete pipes in complex environments according to claim 1, characterized in that: S4 includes S41 and S42; S41. The results of the corrosion behavior assessment and the corrosion transition assessment are stored in a time series database, and are marked with a timestamp, a prestressed steel cylinder concrete pipe segment number, a change rate, and a risk level label, and then grouped and sorted according to the pipe segment number; S42. Extract the sorted assessment results from the time series database and use a line graph to show the evolution of the corrosion risk value of the prestressed steel cylinder concrete pipe segment over time. The horizontal X-axis of the line chart is set as the time dimension, and a solid line and a dotted line are drawn on the vertical Y-axis respectively. The solid line represents the comprehensive corrosion risk index SCR, and the dotted line represents the corrosion change prediction index CAR. Trend change points, such as inflection points and sudden increase segments, are marked, and interactive functions are set to support time window zooming and click-to-view of abnormal points.

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