A method for detecting the state of sewer pipe deposits

Abstract

The present application relates to the technical field of drainage system detection, and discloses a sewage pipeline deposit state detection method, which comprises the following steps: acquiring the transmission delay time of a target pipeline; calculating an evaluation index according to the transmission delay time; evaluating the deposit state of the target pipeline according to the flow delay index; and evaluating the type of the deposit of the target pipeline according to the flow delay index, the ammonia-nitrogen delay difference index and the water quality anomaly index. The sewage pipeline deposit state detection method can completely utilize the monitoring data of the flow meter, the COD sensor and the ammonia-nitrogen sensor that have been deployed in the drainage pipe network, analyze the transmission time delay difference of the three signals of flow, COD and ammonia-nitrogen, quantify the deposit accumulation degree and distinguish the deposit type, and avoid the increase of hardware cost.

Description

Technical Field

[0001] This invention relates to the technical field of drainage system testing, and in particular to a method for detecting the state of sediment in sewage pipes. Background Technology

[0002] Deposits accumulated in urban sewage pipe networks are a key factor leading to reduced pipe flow capacity, localized blockages, sewage overflows, and abnormal operating loads at treatment plants. Timely detection and assessment of deposit conditions are crucial for ensuring the safe operation of drainage systems and optimizing dredging and maintenance decisions.

[0003] However, existing mainstream technologies such as pipeline sonar detection, CCTV pipeline camera robots, and laser scanning all require the purchase of specialized equipment and the deployment of professional operators, resulting in high equipment purchase and maintenance costs and making large-scale, routine deployment in large pipeline networks difficult. Furthermore, most detection methods require water outages, dewatering operations, or entry into the pipeline, which not only affects the normal function of the drainage system but also poses operational safety risks, failing to achieve non-invasive online monitoring.

[0004] Furthermore, traditional detection methods are mostly periodic offline monitoring conducted annually or quarterly, which cannot capture the dynamic accumulation, scouring, and redistribution of sediments, making it difficult to detect sudden sedimentation risks in a timely manner. Usually, these risks are only detected when sediments accumulate to a point that severely affects flow capacity, causing abnormal rises in water levels or significant drops in flow velocity. By this time, dredging work is already in a reactive phase and costs have increased dramatically. Summary of the Invention

[0005] Therefore, the purpose of this invention is to provide early warning by analyzing changes in water quality and quantity before sediment accumulation affects flow capacity, without adding additional hardware detection equipment. This invention introduces a method for detecting sediment status in sewage pipelines, which avoids increasing hardware costs. It fully utilizes monitoring data from flow meters, COD sensors, and ammonia nitrogen sensors already deployed in the drainage network. By analyzing the differences in transmission time delays of the three signals (flow, COD, and ammonia nitrogen), it can quantify the degree of sediment accumulation and distinguish sediment types, thereby enabling early warning before sediment accumulation affects flow capacity. It also provides decision support for dredging scheduling and preventive maintenance of the pipeline network.

[0006] To address the aforementioned technical problems, this invention provides a method for detecting the state of sediment in sewage pipelines, comprising:

[0007] Obtain the transmission delay time of the target pipeline; the transmission delay time includes: flow transmission delay time, COD transmission delay time, and ammonia nitrogen transmission delay time;

[0008] An evaluation index is calculated based on the transmission delay time; the evaluation index includes a flow delay index, an ammonia nitrogen delay difference index, and a water quality anomaly index.

[0009] The deposition state of the target pipeline is assessed based on the flow delay index;

[0010] The type of sediment in the target pipeline is assessed based on the flow delay index, the ammonia nitrogen delay difference index, and the water quality anomaly index.

[0011] Compared with the prior art, the above-described technical solution of the present invention has the following advantages:

[0012] This invention provides a method for detecting sediment conditions in sewage pipelines. It fully utilizes monitoring data from flow meters, COD sensors, and ammonia nitrogen sensors already deployed in the drainage network to analyze the differences in transmission time delays of these three signals. This avoids increased hardware costs and the need for water outages or precipitation operations. Furthermore, based on flow delay indices, ammonia nitrogen delay difference indices, and water quality anomaly indices, it quantifies the degree of sediment accumulation and distinguishes sediment types. This facilitates early warning before sediment accumulation affects flow capacity, providing decision support for dredging scheduling and preventative maintenance of the pipeline network.

[0013] Specifically, the flow delay index, sensitive to sediment filling rates, can provide early warnings in the early stages of sediment accumulation, detecting problems 1 to 3 months earlier than traditional hydraulic methods, thus gaining valuable time for preventative maintenance. Furthermore, the flow delay index and water quality anomaly index can preliminarily distinguish between sandy and organic sediments, while the ammonia nitrogen delay difference index can further identify mixed sediments. Attached Figure Description

[0014] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0015] Figure 1 This is a schematic flowchart of a method for detecting the state of sediment in sewage pipelines in an embodiment of the present invention.

[0016] Figure 2 This is a schematic diagram of a process for verifying the deposition state of a target pipeline in an embodiment of the present invention. Detailed Implementation

[0017] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0018] To meet the needs of environmental supervision and operation scheduling, modern urban drainage networks have been widely equipped with a large number of online monitoring sensors, such as flow meters, COD sensors, ammonia nitrogen sensors, and monitoring well covers with water level monitoring functions.

[0019] The accumulation of sediment at the bottom of the pipe directly reduces the cross-sectional area of ​​the water flow, leading to a decrease in the average flow velocity at the same flow rate. Furthermore, sediment is not an inert medium; sediment layers rich in organic matter and microorganisms, in particular, create multiple obstacles to the transport of dissolved pollutants. The adsorption of organic molecules and ammonium ions on the surface of sediment particles causes pollutants to be temporarily retained and then slowly released, effectively increasing the migration path length. In addition, reactions such as hydrolysis and fermentation of organic matter, ammoniation of organic nitrogen, and nitrification / denitrification in the sediment alter the form and concentration of pollutants, and their kinetic processes are asynchronous with the water flow velocity, resulting in a slower transport velocity of the pollutant plume compared to the water flow. A slow exchange of substances occurs between the pore water in the porous structure of the sediment and the upper flowing water; the diffusion of dissolved pollutants into the pore water followed by slow release lags significantly behind the advection transport of the main water flow. Therefore, in pipes containing sediment, the flow rate signal, reflecting the overall movement of the water flow, is transmitted faster than the COD concentration signal and ammonia nitrogen concentration signal, reflecting the movement of dissolved pollutants; and the thicker and more active the sediment, the greater this difference in transmission velocity.

[0020] Therefore, in order to fully utilize the monitoring data from flow meters, COD sensors, and ammonia nitrogen sensors already deployed in the drainage network for sewage pipeline sediment status detection, in order to identify the degree of sediment accumulation and distinguish sediment types, the sewage pipeline sediment status detection method of the present invention includes: steps SS1 to SS4, as referenced. Figure 1 Furthermore, to reduce misjudgments, the sewage pipeline sediment state detection method of the present invention may further include: step SS5.

[0021] Step SS1: Obtain the transmission delay time of the target pipeline.

[0022] In application, the transmission delay time includes: traffic transmission delay time. COD transmission delay time and ammonia nitrogen transport delay time Furthermore, the transmission delay time may also include: water level transmission delay time. .

[0023] In practical applications, in pipes containing sediment, due to the obstruction effect, [the following will occur] > and > This phenomenon occurs in an ideally clean pipeline where dissolved contaminants flow with the water, theoretically... , as well as The three are similar. An ideal clean pipeline is one without any deposits in it. Generally, historical monitoring data from 30 to 60 days after pipeline dredging is selected as the baseline for its health status.

[0024] In some embodiments, step SS1 includes steps SS11 and SS12.

[0025] Step SS11: Obtain the timing monitoring data of the target pipeline.

[0026] In application, time-series monitoring data includes: flow rate time-series data, COD concentration time-series data, and ammonia nitrogen concentration time-series data. Furthermore, time-series monitoring data may also include: water level sequence data.

[0027] In practical applications, the flow time series data includes upstream and downstream flow sequences; the COD concentration time series data includes upstream and downstream COD concentration sequences; and the ammonia nitrogen concentration time series data includes upstream and downstream ammonia nitrogen concentration sequences. Since monitoring wells are generally only located downstream of the target pipeline, the water level sequence data includes the downstream water level sequence.

[0028] Step SS12: Calculate the transmission delay time based on the timing monitoring data.

[0029] In application, the flow transmission delay time is obtained based on the upstream flow sequence and the downstream flow sequence; the COD transmission delay time is obtained based on the upstream COD concentration sequence and the downstream COD concentration sequence; the ammonia nitrogen transmission delay time is obtained based on the upstream ammonia nitrogen concentration sequence and the downstream ammonia nitrogen concentration sequence; and the water level transmission delay time is obtained based on the upstream flow sequence and the downstream water level sequence.

[0030] In practical applications, the transmission delay time can be obtained based on cross-correlation analysis, using both the first and second sequences. For example, the transmission delay time can be obtained by calculating the cross-correlation function of the first and second sequences and taking the time offset corresponding to the maximum value of the cross-correlation function. Specifically: In the formula, This refers to the transmission delay time. } represents the maximum value of the cross-correlation function; It is the first sequence; It is the second sequence; The time offset is T; the interval is T. The mean of the first sequence; The mean of the second sequence; The standard deviation of the first sequence; is the standard deviation of the first sequence.

[0031] The flow transmission delay time is obtained when the first sequence is an upstream flow rate sequence and the second sequence is a downstream flow rate sequence. The COD transmission delay time is obtained when the first sequence is an upstream COD concentration sequence and the second sequence is a downstream COD concentration sequence. The ammonia nitrogen transmission delay time is obtained when the first sequence is an upstream ammonia nitrogen concentration sequence and the second sequence is a downstream ammonia nitrogen concentration sequence. The water level transmission delay time is obtained based on the upstream flow rate sequence and the downstream water level sequence.

[0032] In some embodiments, the flow transmission delay time can be obtained based on the upstream flow sequence and the downstream flow sequence using cross-correlation analysis. The COD transmission delay time can be obtained based on the upstream COD concentration sequence and the downstream COD concentration sequence using cross-correlation analysis. The ammonia nitrogen transmission delay time can be obtained based on the upstream ammonia nitrogen concentration sequence and the downstream ammonia nitrogen concentration sequence using cross-correlation analysis. The water level transmission delay time can be obtained based on the upstream flow sequence and the downstream water level sequence using cross-correlation analysis.

[0033] In actual implementation, when the cross-correlation function of the ammonia nitrogen concentration sequence meets the preset conditions, the waveform feature point matching method is used to calculate the ammonia nitrogen transmission delay time.

[0034] When the preset conditions are met, it indicates that the cross-correlation function has no obvious peak. Specifically, the preset conditions include any one of (1) to (3).

[0035] (1) The difference between the maximum value and the mean value of the cross-correlation function is less than 1.5 times the standard deviation. That is, the difference between the maximum value and the mean value of the cross-correlation function of ammonia nitrogen concentration is less than 1.5 times the standard deviation of the cross-correlation function.

[0036] (2) The second peak value of the cross-correlation function is greater than 0.9 times the highest peak value. That is, the second peak value of the cross-correlation function of ammonia nitrogen concentration is greater than 0.9 times the highest peak value of the cross-correlation function.

[0037] (3) The peak half-width of the cross-correlation function is greater than 6 sampling intervals. That is, the peak half-width of the cross-correlation function of ammonia nitrogen concentration is greater than 6 sampling intervals.

[0038] Furthermore, the ammonia nitrogen transport delay time is calculated using the waveform feature point matching method, including steps SS121 to SS127.

[0039] Step SS121: Obtain the downstream water level sequence.

[0040] Step SS122: Extract the first local maximum point from the upstream ammonia nitrogen concentration sequence and record the first occurrence time of each first local maximum point.

[0041] In application, a local maximum is a point where the value at that point is greater than the values ​​of the two adjacent points. Specifically, the first local maximum is a point where the ammonia nitrogen concentration is greater than the ammonia nitrogen concentrations of the two adjacent points. For example: ,and ;in, for The ammonia nitrogen concentration at the time of occurrence; for The ammonia nitrogen concentration at the time of occurrence; for The ammonia nitrogen concentration at the time of occurrence.

[0042] In practical applications, there can be multiple first local maxima. There are usually 2 to 3 first local maxima in a day, distributed in the morning, noon and evening.

[0043] Step SS123: Calculate the theoretical propagation time range based on the length of the target pipe and the historical flow velocity range.

[0044] In application, the historical flow rate range includes the maximum flow rate at full pipe flow and the minimum flow rate at low flow. The minimum theoretical propagation time is obtained by dividing the target pipe length L by the maximum flow rate; the maximum theoretical propagation time is obtained by dividing the target pipe length L by the minimum flow rate; and the theoretical propagation time range is determined based on the minimum and maximum theoretical propagation times.

[0045] Step SS124: Calculate the theoretical propagation time based on the length of the target pipe and the historical average flow velocity.

[0046] In application, the historical average velocity is calculated based on the historical velocity sequence. The theoretical propagation time is obtained by dividing the length L of the target pipe by the historical average velocity.

[0047] Step SS125: For each first local maximum point, determine the time search window for scanning the downstream water level sequence based on the first occurrence time and the theoretical propagation time range.

[0048] When applying this method, the minimum theoretical propagation time is added to the first occurrence time to determine the lower limit of the time search window; the maximum theoretical propagation time is added to the first occurrence time to determine the upper limit of the time search window; and the time search window is determined based on the lower and upper limits of the time search window.

[0049] Step SS126: Within the time search window, extract the second local maximum point of the downstream water level sequence, and record the second occurrence time of the second local maximum point whose occurrence time is closest to the theoretical propagation time.

[0050] In application, the number of time search windows is the same as the number of first occurrence moments. The downstream water level sequence is scanned sequentially within each time search window to obtain the second local maximum point.

[0051] In practical applications, the second local maximum point is the point where the water level is higher than the water levels of the two adjacent points. For example: ,and ;in, for The water level at the time of the incident; for The water level at the time of the incident; for The water level at the time of the incident.

[0052] In actual implementation, when there is one second local maximum point, the occurrence time corresponding to the second local maximum point is designated as the second occurrence time. When there are multiple second local maximum points, the occurrence time among these occurrence times that is closest to the theoretical propagation time is designated as the second occurrence time.

[0053] Step SS127: The median of the differences between the second occurrence time and each of the first occurrence times is taken as the ammonia nitrogen transport delay time.

[0054] In application, when the number of first occurrence moments is 1, the difference between the second occurrence moment and the first occurrence moment is taken as the ammonia nitrogen transmission delay time. When the number of first occurrence moments is multiple, each of the first occurrence moments is subtracted from the second occurrence moment to obtain multiple differences, and the median of these differences is taken as the ammonia nitrogen transmission delay time.

[0055] Step SS2: Calculate the evaluation index based on the transmission delay time.

[0056] In application, the evaluation indices include the flow delay index, the ammonia nitrogen delay difference index, and the water quality anomaly index. Furthermore, the evaluation indices also include the hydraulic anomaly index.

[0057] The traffic delay index is obtained by comparing the difference between the COD transmission delay time and the traffic transmission delay time with the traffic transmission delay time. Specifically, it includes the following formula:

[0058] ;

[0059] In the formula, FDI is the flow delay index; This refers to the data transmission delay time. This is the COD transmission delay time.

[0060] The ammonia nitrogen delay difference index is obtained by comparing the difference between the ammonia nitrogen transmission delay time and the flow transmission delay time with the flow transmission delay time. Specifically, it includes the following formula:

[0061] ;

[0062] In the formula, FNI is the ammonia nitrogen delay difference index; This refers to the ammonia nitrogen transport delay time. This refers to the latency of data transmission.

[0063] The water quality anomaly index is obtained by weighted summation of COD concentration changes and ammonia nitrogen concentration changes. Specifically, the COD concentration change is determined based on upstream and downstream COD concentration sequences; the ammonia nitrogen concentration change is determined based on upstream and downstream ammonia nitrogen concentration sequences. Further, the COD concentration change is determined based on the ratio of the difference between upstream and downstream COD concentrations to the average of upstream and downstream COD concentrations; the ammonia nitrogen concentration change is determined based on the ratio of the difference between upstream and downstream ammonia nitrogen concentrations to the average of upstream and downstream ammonia nitrogen concentrations. This specifically includes the following formula:

[0064] ;

[0065] In the formula, WQI is the water quality anomaly index; This represents the difference between upstream and downstream COD concentrations. This represents the average of the upstream and downstream COD concentrations. This represents the difference between the upstream and downstream ammonia nitrogen concentrations. This represents the average of the upstream and downstream ammonia nitrogen concentrations. The weighting coefficient for changes in COD concentration; The weighting coefficient for changes in ammonia nitrogen concentration; .

[0066] Furthermore, since the sensitivity of COD concentration changes and ammonia nitrogen concentration changes is similar under different sediment types, it is generally made Since both COD and ammonia nitrogen concentrations are highly sensitive to changes in organic environments, statistical analysis shows that ammonia nitrogen concentrations are relatively more stable in target pipes within concentrated septic tank areas. Therefore, [the following is likely a continuation of the previous sentence:] , In the target pipeline for domestic sewage, the COD concentration changes are relatively more stable, therefore... , Furthermore, the low temperatures in winter weaken nitrification, thus allowing... , This is to make the water quality anomaly index more accurately reflect sediment activity and improve the accuracy of subsequent judgments.

[0067] The hydraulic anomaly index is obtained by comparing the slope of the current water level and flow rate changes in the target pipeline with the slope of the water level and flow rate changes when there is no sediment. Specifically, the slope of the current water level and flow rate changes is the ratio of the current water level transmission delay time to the flow rate transmission delay time; the slope of the water level and flow rate changes when there is no sediment is the ratio of the water level transmission delay time to the flow rate transmission delay time in the target pipeline when there is no sediment. The specific formula includes the following:

[0068] ;

[0069] ;

[0070] ;

[0071] In the formula, HDI is the hydraulic anomaly index; The slope of the current water level and flow rate changes; The slope of the water level and flow rate changes when there is no sediment in the target pipeline; For traffic transmission delay time, in practical applications, ; This refers to the water level transmission delay time. The water level transport delay time when there is no sediment in the target pipeline; The flow transmission delay time is the time required when there are no deposits in the target pipeline. In practical applications, .

[0072] Step SS3: Evaluate the deposition status of the target pipeline based on the flow delay index.

[0073] When applying the method, a grading threshold is set; the flow delay index is compared with the grading threshold; and the deposition state of the target pipeline is evaluated based on the relationship between the flow delay index and the grading threshold. Furthermore, the deposition state of the target pipeline includes: healthy state, lightly deposited state, moderately deposited state, and heavily deposited state.

[0074] In practical applications, the grading thresholds include a first grading threshold, a second grading threshold, and a third grading threshold. Furthermore, based on historical data analysis, each grading threshold is determined according to the mean and standard deviation of the flow delay index when the target pipeline is free of sediment, and 0 < first grading threshold < second grading threshold < third grading threshold < 100%. For example: first grading threshold = +2· Second-level threshold = +3· ; and the third-level threshold +4· In the formula, The mean of the flow delay index when there are no deposits in the target pipeline; The standard deviation of the flow delay index when there are no deposits in the target pipeline.

[0075] In actual implementation, the deposition status of the target pipeline is evaluated based on the flow delay index, including: if the flow delay index is less than the first grading threshold, the target pipeline is determined to be in a healthy state; if the first grading threshold is less than or equal to the flow delay index and less than the second grading threshold, the target pipeline is determined to be in a lightly deposited state; if the second grading threshold is less than or equal to the flow delay index and less than the third grading threshold, the target pipeline is determined to be in a moderately deposited state; if the third grading threshold is less than or equal to the flow delay index, the target pipeline is determined to be in a heavily deposited state.

[0076] In some embodiments, when the target pipeline in the old urban area has a diameter of 300mm, a length of 400m, and an inclination angle of 0.0005°, =10%, =5%, the first level threshold is 20%, the second level threshold is 25%, and the third level threshold is 30%.

[0077] Step SS4: Assess the type of sediment in the target pipeline based on the flow delay index, the ammonia nitrogen delay difference index, and the water quality anomaly index.

[0078] When applied, the type of sediment in the target pipeline is assessed based on the flow delay index and the water quality anomaly index, including steps SS40 to SS42.

[0079] Step SS40: Set a first preset change threshold and a second preset change threshold to identify anomalies.

[0080] In application, based on historical data analysis, the first preset change threshold is determined by the mean and standard deviation of the flow delay index when the target pipeline is free of sediment. Based on historical data analysis, the second preset change threshold is determined by the mean and standard deviation of the water quality anomaly index when the target pipeline is free of sediment. For example: First preset change threshold = Second preset change threshold = In the formula, The mean value of the water quality anomaly index when there is no sediment in the target pipeline; The standard deviation of the water quality anomaly index when there is no sediment in the target pipeline.

[0081] In practical applications, when the target pipe diameter in an old urban area is 300mm, the length is 400m, and the inclination angle is 0.0005°, =10%, =5%, =12%, =6%, the first preset change threshold is 25%, and the second preset change threshold is 30%.

[0082] Step SS41: Compare the flow delay index with the first preset change threshold, and compare the water quality anomaly index with the second preset change threshold.

[0083] Step SS42: Assess the type of sediment in the target pipeline based on the relationship between the flow delay index and the first preset change threshold, and the relationship between the water quality anomaly index and the second preset change threshold.

[0084] If the flow delay index is less than or equal to the first preset change threshold and the water quality anomaly index is less than or equal to the second preset change threshold, then the target pipeline is determined to be free of sediment and in a healthy state.

[0085] If the flow delay index is less than or equal to the first preset change threshold and the water quality anomaly index is greater than the second preset change threshold, then the water quality in the target pipeline is determined to be abnormal, and an alarm is triggered.

[0086] If the flow delay index is greater than the first preset change threshold and the water quality anomaly index is greater than the second preset change threshold, then the sediment in the target pipeline is determined to be mainly organic matter or biofilm sediment.

[0087] If the flow delay index is greater than the first preset change threshold and the water quality anomaly index is less than or equal to the second preset change threshold, it is preliminarily determined that the sediment in the target pipeline is mainly sand or inorganic sediment.

[0088] Furthermore, when it is initially determined that the sediments in the target pipeline are mainly sandy or inorganic: calculate the ratio of the ammonia nitrogen delay difference index to the flow delay index, and based on the statistical analysis of historical data, determine whether the sediments in the target pipeline are of mixed sediment type or mainly sandy or inorganic sediment type.

[0089] For example, when the ammonia nitrogen delay difference index is divided by the flow delay index, if the ratio of the ammonia nitrogen delay difference index to the flow delay index is greater than 0.6, it means that the ammonia nitrogen delay difference index has reached more than 60% of the flow delay index, which indicates that there are a small amount of organic components in the sediment. In this case, the sediment of the target pipeline is judged to be a mixed sediment type. Otherwise, the sediment of the target pipeline is judged to be dominated by sand or inorganic sediment.

[0090] Step SS5: Calculate the comprehensive sedimentary state index by weighted summation of the evaluation indices, and verify the sedimentary state and the type of sediment based on the comprehensive sedimentary state index.

[0091] When applied, step SS5 includes steps SS51 to SS53.

[0092] Step SS51: Calculate the comprehensive sedimentation state index by weighted summation of the evaluation indices.

[0093] When calculating the comprehensive sedimentary state index by weighted summation of the assessment indices, the assessment indices may include the flow delay index (FDI), the water quality anomaly index (WQI), the hydraulic anomaly index (HDI), and the ammonia nitrogen delay difference index (FNI). Specifically, it includes the following formula:

[0094] SEI=w1×FDI+w2×WQI+w3×HDI+w4×FNI;

[0095] In the formula, SEI is the comprehensive sedimentation state index; w1 is the weighting coefficient of the flow delay index; w2 is the weighting coefficient of the water quality anomaly index; w3 is the weighting coefficient of the hydraulic anomaly index; w4 is the weighting coefficient of the ammonia nitrogen delay difference index, and w1+w2+w3+w4=1.

[0096] When the sediments in the target pipeline are predominantly sandy or inorganic, changes in the water quality anomaly index mainly reflect upstream water quality fluctuations rather than the sediments themselves. Increasing w2 can more sensitively capture subtle water quality changes caused by sand deposition, avoiding the underreporting of early deposition signals due to insufficient weighting. When the sediments in the target pipeline are predominantly sandy or inorganic, the initial impact of sand deposition on the hydraulic anomaly index is relatively small. Decreasing w3 can avoid noise interference from hydraulic fluctuations and prevent misjudgments caused by non-depositional factors such as rainfall and pump station start-up / shutdown. When the sediments in the target pipeline are predominantly sandy or inorganic, nitrification is weak, and the information content of the ammonia nitrogen delay difference index is limited. Decreasing w4 can effectively filter noise and avoid misjudging random fluctuations as organic deposition characteristics. Specifically: w1 is set to 0.3 to 0.4, w2 to 0.4 to 0.5, w3 to 0.1 to 0.2, and w4 to 0 to 0.1.

[0097] When the sediment in the target pipeline is of a mixed sediment type, it is necessary to highlight the importance of the flow delay index to fully reflect the water quality anomaly index and the hydraulic anomaly index, while appropriately retaining the ammonia nitrogen delay difference index as an auxiliary indicator. Specifically: w1 is set to 0.4 to 0.5, w2 to 0.2 to 0.3, w3 to 0.2 to 0.3, and w4 to 0 to 0.1.

[0098] When the sediment in the target pipeline is predominantly sandy or inorganic, the flow delay index can simultaneously reflect the sedimentation state and biochemical effects. Increasing w1 can improve the flow delay index's sensitivity to organic sediments. Conversely, when the sediment in the target pipeline is predominantly sandy or inorganic, it leads to an increase in the water quality anomaly index. However, the water quality anomaly index is easily affected by upstream discharges. Decreasing w2 can prevent the artificially inflated water quality anomaly index caused by sudden upstream pollution from interfering with sedimentation assessment. Specifically: w1 should be 0.5 to 0.6, w2 0.1 to 0.2, w3 0.2 to 0.3, and w4 0 to 0.1.

[0099] Step SS52: Verify the sedimentation state based on the comprehensive sedimentation state index.

[0100] When applying the application, a first verification threshold is set, which includes a first comprehensive threshold, a second comprehensive threshold, and a third comprehensive threshold. The comprehensive thresholds are determined based on the mean and standard deviation of the comprehensive deposition state index when the target pipeline is free of deposits, and 0 < first comprehensive threshold < second comprehensive threshold < third comprehensive threshold < 100%. For example: First comprehensive threshold = +2· Second comprehensive threshold == +3· ; and the third comprehensive threshold +4· In the formula, This represents the average comprehensive index of sedimentation state when the target pipeline is free of sediment. The standard deviation of the comprehensive index of sedimentation state when there are no sediments in the target pipeline.

[0101] In actual implementation, when comparing the deposition state, for example, when the target pipe in the old urban area has a diameter of 300mm, a length of 400m, and an inclination angle of 0.0005°, =15%, =6%, the first comprehensive threshold is 27%, the second comprehensive threshold is 33%, and the third comprehensive threshold is 39%.

[0102] The deposition state of the target pipeline is reassessed based on the magnitude of the comprehensive index and the comprehensive threshold, and the relationship between these two factors. If the assessment result based on the deposition state comprehensive index and comprehensive threshold is the same as the assessment result based on the flow delay index and classification threshold, the deposition state assessment of the target pipeline is considered accurate; otherwise, the assessment is considered inaccurate. (Reference) Figure 2 Specifically:

[0103] When a target pipeline is determined to be in a healthy state, if the comprehensive deposition state index is less than the first comprehensive threshold, the deposition state assessment of the target pipeline is considered accurate; otherwise, the assessment is considered inaccurate.

[0104] When the target pipeline is determined to be in a state of slight deposition, if the first comprehensive threshold ≤ the comprehensive index of deposition state < the second comprehensive threshold, then the deposition state assessment of the target pipeline is determined to be accurate; otherwise, the assessment is determined to be inaccurate.

[0105] When the target pipeline is determined to be in a moderate deposition state, if the second comprehensive threshold ≤ the deposition state comprehensive index < the third comprehensive threshold, then the deposition state assessment of the target pipeline is considered accurate; otherwise, the assessment is considered inaccurate.

[0106] When a target pipeline is determined to be in a state of heavy deposition, if the third comprehensive threshold is less than or equal to the comprehensive deposition state index, then the deposition state assessment of the target pipeline is considered accurate; otherwise, the assessment is considered inaccurate.

[0107] Step SS53: Verify the type of sediment based on the comprehensive sedimentary state index.

[0108] When applying the technology, verification is performed based on the type of sediment, specifically including three scenarios.

[0109] Scenario 1: When it is determined that the sediment in the target pipeline is mainly sand or inorganic sediment, the verification of the sediment type includes steps 5311 to 5312.

[0110] Step 5311: Calculate the first expected value based on the traffic delay index.

[0111] When applied, the first expected value = w1 × FDI; where FDI is the flow delay index.

[0112] Step 5312: Calculate the first relative error between the comprehensive sedimentation state index and the first expected value. If the first relative error is less than or equal to the first preset threshold, the sediment type assessment is determined to be accurate; otherwise, the assessment is determined to be inaccurate.

[0113] When applied, the first relative error = sedimentation state comprehensive index - first expected value.

[0114] In practical applications, historically accurate samples are selected, and the relative error distribution of various sediment types is statistically analyzed. The 90th percentile is then used as the preset threshold. Specifically, the first preset threshold is 15%.

[0115] Scenario 2: When it is determined that the deposits in the target pipeline are mainly organic matter or biofilm deposits, the verification of the deposit type includes steps 5321 to 5322.

[0116] Step 5321: Calculate the second expected value based on the flow delay index and the water quality anomaly index.

[0117] When applied, the second expected value = w1 × FDI + w2 × WQI; where FDI is the flow delay index and WQI is the water quality anomaly index.

[0118] Step 5322: Calculate the second relative error between the comprehensive sedimentation state index and the second expected value. If the second relative error is less than or equal to the second preset threshold, the sediment type assessment is determined to be accurate; otherwise, the assessment is determined to be inaccurate.

[0119] When applied, the second relative error = sedimentation state comprehensive index - second expected value.

[0120] In practical applications, the second preset threshold is 25%.

[0121] Scenario 3: When it is determined that the sediment in the target pipeline is of mixed sediment type, the verification of the sediment type includes steps 5331 to 5332.

[0122] Step 5331: Calculate the third expected value based on the flow delay index, the water quality anomaly index, and the ammonia nitrogen delay difference index.

[0123] When applied, the third expected value is w1×FDI+w2×WQI+w4×FNI; where FDI is the flow delay index; WQI is the water quality anomaly index; and FNI is an index including ammonia nitrogen delay difference.

[0124] Step 5332: Calculate the third relative error between the comprehensive sedimentation state index and the third expected value. If the third relative error is less than or equal to the third preset threshold, the sediment type assessment is determined to be accurate; otherwise, the assessment is determined to be inaccurate.

[0125] When applied, the third relative error = sedimentation state comprehensive index - third expected value.

[0126] In practical applications, the third preset threshold is 35%.

[0127] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0128] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0129] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0130] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0131] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for detecting the state of sediment in sewage pipes, characterized in that, include: Obtain the transmission delay time of the target pipeline; The transmission delay time includes: traffic transmission delay time, COD transmission delay time, and ammonia nitrogen transmission delay time; An evaluation index is calculated based on the transmission delay time; the evaluation index includes a flow delay index, an ammonia nitrogen delay difference index, and a water quality anomaly index. The deposition state of the target pipeline is assessed based on the flow delay index; The type of sediment in the target pipeline is assessed based on the flow delay index, the ammonia nitrogen delay difference index, and the water quality anomaly index. The acquisition of the transmission delay time of the target pipeline includes: The time-series monitoring data of the target pipeline is acquired, including: flow time-series data, COD concentration time-series data, and ammonia nitrogen concentration time-series data; wherein, the flow time-series data includes upstream flow sequence and downstream flow sequence; the COD concentration time-series data includes upstream COD concentration sequence and downstream COD concentration sequence; and the ammonia nitrogen concentration time-series data includes upstream ammonia nitrogen concentration sequence and downstream ammonia nitrogen concentration sequence. Calculate the transmission delay time based on the timing monitoring data: Based on the cross-correlation analysis method, the traffic transmission delay time is obtained according to the upstream traffic sequence and the downstream traffic sequence; Based on the cross-correlation analysis method, the COD transport delay time is obtained from the upstream COD concentration sequence and the downstream COD concentration sequence. The ammonia nitrogen transport delay time was obtained based on the upstream and downstream ammonia nitrogen concentration sequences. The calculation of the evaluation index based on the transmission delay time includes: The traffic delay index is obtained by comparing the difference between the COD transmission delay time and the traffic transmission delay time with the traffic transmission delay time. The ammonia nitrogen delay difference index is obtained by comparing the difference between the ammonia nitrogen transmission delay time and the flow transmission delay time with the flow transmission delay time. The water quality anomaly index is obtained by weighted summation of COD concentration changes and ammonia nitrogen concentration changes; wherein, the COD concentration change is determined based on the upstream COD concentration sequence and the downstream COD concentration sequence; the ammonia nitrogen concentration change is determined based on the upstream ammonia nitrogen concentration sequence and the downstream ammonia nitrogen concentration sequence.

2. The method for detecting the state of sediment in sewage pipelines according to claim 1, characterized in that, When the cross-correlation function of the ammonia nitrogen concentration sequence meets a preset condition, the ammonia nitrogen transport delay time is calculated using the waveform feature point matching method: Extract the first local maximum point from the upstream ammonia nitrogen concentration sequence and record the first occurrence time of each first local maximum point; For each first local maximum point, the time search window for scanning the downstream water level sequence is determined based on the first occurrence time and the theoretical propagation time range; Within the time search window, the second local maximum point of the downstream water level sequence is extracted, and the second occurrence time of the second local maximum point whose occurrence time is closest to the theoretical propagation time is recorded; The median of the differences between the second occurrence time and each of the first occurrence times is taken as the ammonia nitrogen transport delay time; The preset conditions include any of the following: The difference between the maximum value and the mean of the cross-correlation function is less than 1.5 times the standard deviation; The second peak value of the cross-correlation function is 0.9 times greater than the highest peak value; The peak half-width of the cross-correlation function is greater than 6 sampling intervals.

3. The method for detecting the state of sediment in sewage pipelines according to claim 1, characterized in that, The assessment of the deposition state of the target pipeline includes: If the traffic delay index is less than the first-level threshold, the target pipeline is determined to be in a healthy state. If the first-level threshold ≤ flow delay index < the second-level threshold, the target pipeline is determined to be in a state of slight deposition; If the second-level threshold is less than or equal to the flow delay index and less than the third-level threshold, the target pipeline is determined to be in a state of moderate deposition. If the third-level threshold is less than or equal to the flow delay index, the target pipeline is determined to be in a state of severe deposition. The grading threshold is determined based on the mean and standard deviation of the flow delay index when there is no sediment in the target pipeline, and 0 < first grading threshold < second grading threshold < third grading threshold < 100%.

4. The method for detecting the state of sediment in sewage pipelines according to claim 1, characterized in that, The assessment of the type of deposits in the target pipeline includes: Step SS41: Compare the flow delay index with a first preset change threshold, and compare the water quality anomaly index with a second preset change threshold; wherein, the first preset change threshold is determined based on the mean and standard deviation of the flow delay index when there is no sediment in the target pipeline; the second preset change threshold is determined based on the mean and standard deviation of the water quality anomaly index when there is no sediment in the target pipeline. Step SS42: Assess the type of sediment in the target pipeline based on the relationship between the flow delay index and the first preset change threshold, and the relationship between the water quality anomaly index and the second preset change threshold. If the flow delay index is greater than the first preset change threshold and the water quality anomaly index is greater than the second preset change threshold, then the sediment in the target pipe is determined to be mainly organic matter or biofilm sediment. If the flow delay index is less than or equal to the first preset change threshold and the water quality anomaly index is less than or equal to the second preset change threshold, then the target pipe is determined to be free of sediment and in a healthy state. If the flow delay index is greater than the first preset change threshold and the water quality anomaly index is less than or equal to the second preset change threshold, it is preliminarily determined that the sediment in the target pipeline is mainly sand or inorganic sediment. If the flow delay index is less than or equal to the first preset change threshold and the water quality anomaly index is greater than the second preset change threshold, then the water quality in the target pipeline is determined to be abnormal, and an alarm is triggered.

5. The method for detecting the state of sediment in sewage pipelines according to claim 4, characterized in that, When the initial assessment indicates that the sediment in the target pipeline is predominantly sandy or inorganic: Calculate the ratio of the ammonia nitrogen delay difference index to the flow delay index. Based on the ratio of the ammonia nitrogen delay difference index to the flow delay index, determine whether the sediment in the target pipeline is a mixed sediment type or a sediment type dominated by sand or inorganic matter.

6. The method for detecting the state of sediment in sewage pipelines according to claim 1, characterized in that, The method for detecting sediment conditions in sewage pipelines also includes: A comprehensive sedimentary state index is calculated by weighted summation of the evaluation indices, and the sedimentary state and the type of sediment are verified based on the comprehensive sedimentary state index. The evaluation index also includes a hydraulic anomaly index, which is obtained by comparing the slope of the current water level and flow rate change in the target pipeline with the slope of the water level and flow rate change when there is no sediment. The slope of the current water level and flow rate change is the ratio of the current water level transmission delay time to the flow rate transmission delay time. The slope of the water level and flow rate change when there is no sediment is the ratio of the water level transmission delay time to the flow rate transmission delay time when there is no sediment in the target pipeline.

7. The method for detecting the state of sediment in sewage pipelines according to claim 6, characterized in that, The depositional state is verified based on a comprehensive depositional state index, including: When the target pipeline is determined to be in a healthy state, if the comprehensive deposition state index is less than the first comprehensive threshold, the deposition state assessment of the target pipeline is determined to be accurate; otherwise, the assessment is determined to be inaccurate. When the target pipeline is determined to be in a state of light deposition, if the first comprehensive threshold ≤ the comprehensive index of deposition state < the second comprehensive threshold, then the deposition state assessment of the target pipeline is determined to be accurate; otherwise, the assessment is determined to be inaccurate. When the target pipeline is determined to be in a moderate deposition state, if the second comprehensive threshold ≤ the deposition state comprehensive index < the third comprehensive threshold, then the deposition state assessment of the target pipeline is accurate; otherwise, the assessment is inaccurate. When the target pipeline is determined to be in a state of heavy deposition, if the third comprehensive threshold is less than or equal to the comprehensive deposition state index, then the deposition state assessment of the target pipeline is considered accurate; otherwise, the assessment is considered inaccurate. The comprehensive threshold is determined based on the mean and standard deviation of the comprehensive index of sedimentation state when there is no sediment in the target pipeline, and 0 < first comprehensive threshold < second comprehensive threshold < third comprehensive threshold < 100%.

8. The method for detecting the state of sediment in sewage pipelines according to claim 6, characterized in that, Verification of the sediment type based on a comprehensive sedimentary state index includes: When the sediment in the target pipeline is determined to be predominantly sandy or inorganic: Calculate the first expected value based on the traffic delay index; Calculate the first relative error between the comprehensive sedimentation state index and the first expected value. If the first relative error is less than or equal to the first preset threshold, the sediment type assessment is determined to be accurate; otherwise, the assessment is determined to be inaccurate. When the sediment in the target channel is determined to be dominated by organic matter or biofilm deposition: Calculate the second expected value based on the flow delay index and the water quality anomaly index; Calculate the second relative error between the comprehensive sedimentation state index and the second expected value. If the second relative error is less than or equal to the second preset threshold, the sediment type assessment is determined to be accurate; otherwise, the assessment is determined to be inaccurate. When the sediment in the target pipe is determined to be of a mixed sediment type: The third expected value is calculated based on the flow delay index, the water quality anomaly index, and the ammonia nitrogen delay difference index. The third relative error between the comprehensive sedimentation state index and the third expected value is calculated. If the third relative error is less than or equal to the third preset threshold, the sediment type assessment is determined to be accurate; otherwise, the assessment is determined to be inaccurate.

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