Drainage pipeline blockage identification method and system based on distributed vibration optical fiber sensing

Abstract

This invention provides a method and system for identifying blockages in drainage pipes based on distributed vibration fiber optic sensing, belonging to the field of vibration signal processing technology. This invention deploys vibration fiber optic sensing points at equal intervals along the drainage pipe and manages them as monitoring point groups. Axial vibration signals of the pipe are collected within a set time period. Signal energy features are extracted by dividing the time window into multiple levels, and a dataset fitting curve is constructed. The slope of the fitting curve is compared with a set threshold to preliminarily determine whether a blockage exists. For the initially identified target blockage monitoring section, the blockage measurement points are screened by extracting the signal peak rise and fall time and half-width at half-maximum (WHM) features at the monitoring points. Combined with the upstream and downstream vibration energy ratio and energy gradient change law, the actual blockage location of the drainage pipe is determined. This method eliminates the need for full data acquisition and calculation, effectively reducing data transmission, computation, and storage pressure. It can suppress external instantaneous vibration interference and is suitable for online, efficient, and accurate monitoring of blockages in short-distance drainage pipes.

Description

Technical Field

[0001] This invention relates to the field of vibration signal processing technology, specifically to a method and system for identifying blockages in drainage pipes based on distributed vibration fiber optic sensing. Background Technology

[0002] Municipal drainage pipe networks can stretch for hundreds of kilometers. Currently, monitoring technologies for drainage pipe blockages are mainly divided into two categories: manual inspection monitoring technology and online real-time monitoring technology. The branch pipe sections at the end of the network, typically 10-50 meters in length, are the most prone to blockages due to their small total diameter and high volume of debris. For these branch pipe sections, contact monitoring technologies such as manual inspection and CCTV pipe endoscopy are widely used. These technologies provide direct and reliable information about the pipe's internal conditions, but are limited by operating costs and frequency, making continuous online monitoring impossible and resulting in low efficiency and difficulty in responding quickly to sudden blockages. Conventional online real-time monitoring technologies often employ a centralized, full-pipeline signal processing approach. This requires the collection, transmission, and calculation of raw vibration signals from all monitoring points along the entire length, leading to a significant data computation and storage burden. Furthermore, these technologies are susceptible to non-blockage anomalies such as instantaneous water flow impacts and external vibration interference, resulting in insufficient accuracy in blockage identification and low long-term operational reliability.

[0003] Therefore, there is a need for an online drainage pipe blockage identification technology that can reduce data computation and storage pressure and has noise interference suppression capabilities, so as to achieve a balance between cost and accuracy.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for identifying blockages in drainage pipes based on distributed vibration fiber optic sensing, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: The method for identifying blockages in drainage pipes based on distributed vibration fiber optic sensing includes the following steps: Step 1: For the target monitoring point group on the drainage pipeline, extract the features of the fiber optic signals of each time window in the current time period to construct its feature time series set and perform curve fitting. Extract the latest time window with a curve slope greater than a as the first time window, and proceed to step 2 when the curve slope is less than b at the latest time window. Step 2: Analyze the time difference between the first time window and the latest time window, and the slope of the curve of the monitoring point group adjacent to the target monitoring point group at the first time window to determine whether there is a suspected blockage. If so, proceed to step 3. Step 3: For any monitoring point in the target monitoring point group and its adjacent monitoring point groups, analyze its fiber optic signal for a predetermined time period before the latest time window to determine its peak rise time, peak fall time and half width at half maximum (WHM), and then determine the blocked target monitoring point and the reference monitoring point. Step 4 is executed only if there are consecutive blocked target monitoring points. Step 4: Based on continuous blockage target monitoring points, determine the target blockage monitoring section from within the drainage pipe, and determine the reference monitoring point as the upstream or downstream monitoring point based on it. Calculate the signal energy of each upstream / downstream monitoring point, and quotient and analyze the average signal energy of the upstream monitoring point and the average signal energy of the downstream monitoring point to determine the blockage monitoring point from the continuous blockage target monitoring points.

[0007] Furthermore, the method for setting up the monitoring point group is as follows: Vibration fiber optic sensors are arranged at equal intervals of 0.2m along the water flow direction of the drainage pipe, and the frequency of the vibration fiber optic sensors is not less than 100Hz. The locations where the vibration fiber optic sensors are arranged are used as monitoring points. Starting from the first monitoring point, every N monitoring points are divided into a monitoring point group. All the divided monitoring point groups are traversed. The remaining monitoring points with less than N points are not divided into monitoring point groups. The monitoring point groups are numbered in ascending order along the water flow direction of the drainage pipe. When analyzing each monitoring point group, it is used as the target monitoring point group.

[0008] Furthermore, the method for feature extraction of the fiber optic signals of the target monitoring point group within each time window of the current time period is as follows: Using the current moment as the endpoint, a predetermined time length is traced back to be used as the current time period. The preset time length is between 60 and 300 seconds. The time domain signal of the pipeline axial vibration, i.e. the fiber optic signal, is acquired in real time at each monitoring point. The current time period is divided into several time windows, and each time window is further divided into several sub-time windows. For any monitoring point in the target monitoring point group, obtain the sum of squares of the instantaneous amplitude of the time domain signal of the pipeline axial vibration in each sub-time window to obtain the signal energy of the monitoring point in each sub-time window. Extract the minimum signal energy of the monitoring point in each sub-time window in the same time window as the first feature value of the monitoring point in this time window. The mean of the first feature values ​​of all monitoring points in the target monitoring point group within the same time window is calculated as the feature value of the target monitoring point group in this time window. The feature values ​​of the target monitoring point group in each time window are summarized to construct its feature time series set, and then a curve is fitted with the time window as the horizontal axis and the feature value as the vertical axis.

[0009] Furthermore, the method for setting a and b is as follows: Under normal operating conditions with no blockages in the drainage pipe, a reference time interval is selected, and the time-domain signal of the axial vibration of the pipe at each monitoring point in the target monitoring point group within the reference time interval is continuously collected. The curve of the target monitoring point group within the reference time interval is then fitted, and the slope of the curve of the target monitoring point group in each time window within the reference time interval is extracted. The mean slope and standard deviation of the curve slope are then calculated. The value of the mean slope plus twice the standard deviation of the curve slope is taken as 'a', and the value of the mean slope minus twice the standard deviation of the curve slope is taken as 'b'.

[0010] Furthermore, the monitoring point group that is adjacent to the target monitoring point group and whose number is less than the target monitoring point group number is defined as the previous adjacent monitoring point group of the target monitoring point group, and the monitoring point group that is adjacent to the target monitoring point group and whose number is greater than the target monitoring point group number is defined as the next adjacent monitoring point group of the target monitoring point group. If the target monitoring point group's number is the minimum or maximum value, then it is defined as not having any suspected blockages; otherwise, the following judgment is made: If the time difference is not greater than the effective time threshold, and the slope of the curve of the previous adjacent monitoring point group of the target monitoring point group in the first time window is greater than a, and the slope of the subsequent adjacent monitoring point group of the target monitoring point group in the first time window is less than a, then it is determined that there is a suspected blockage in the target monitoring point group; otherwise, there is no suspected blockage. The effective time threshold is three times the duration of the current time period.

[0011] Furthermore, the method for determining the target monitoring point and the reference monitoring point for the blockage is as follows: Set the minimum effective half-width to 100ms; When the drainage pipe is unblocked, the time domain signal of the pipe axial vibration of each monitoring point within the reference time interval is continuously collected to extract all instantaneous amplitude values ​​of each monitoring point within the reference time interval. For any monitoring point, the mean value of all instantaneous amplitude values ​​within the reference time interval is calculated as the signal baseline value of that monitoring point. The target time interval is determined by tracing back a second predetermined time length from the end of the latest time window. The second predetermined time length is no more than 2 hours and no less than the difference between the end of the first time window of the target monitoring point group and the end of the latest time window. For any monitoring point within the target monitoring point group and its adjacent monitoring point groups, the maximum instantaneous amplitude is extracted from the time-domain signal of the pipeline axial vibration within the target time interval as its peak value within the target time interval, and the moment of the maximum instantaneous amplitude is extracted as its peak moment within the target time interval. Based on the peak moment, the moment when the instantaneous amplitude first falls below 20% of the difference between the signal baseline value and the peak value is located backward, and the time interval between this moment and the peak moment is taken as the peak rise time. The moment when the instantaneous amplitude first falls below 20% of the difference between the signal baseline value and the peak value is located backward, and the time interval between this moment and the peak moment is taken as the peak fall time. The moment when the instantaneous amplitude first falls below 50% of the difference between the peak value and the signal baseline value is located forward, and the moment when the instantaneous amplitude first falls below 50% of the difference between the peak value and the signal baseline value is located backward, and the time interval between the two moments is taken as the half-width at half-maximum (WHM). For any monitoring point in the target monitoring point group and adjacent monitoring point groups, if its peak rise time is greater than 40ms, peak fall time is greater than 100ms, and half-width is not less than 100ms, the monitoring point is determined to be a blockage target monitoring point; otherwise, it is used as a reference monitoring point.

[0012] Furthermore, the method for identifying the target blockage monitoring section within the drainage pipe and determining whether the reference monitoring point is an upstream or downstream monitoring point based on it is as follows: Analyze all monitoring points corresponding to the target monitoring point group and its adjacent monitoring point groups: integrate the continuously marked blockage target monitoring points into a target blockage monitoring section, take all reference monitoring points located before the target blockage monitoring section along the water flow direction of the drainage pipe as upstream monitoring points, and take all reference monitoring points located after the target blockage monitoring section along the water flow direction of the drainage pipe as downstream monitoring points.

[0013] Furthermore, the method for determining blockage monitoring points from a continuous set of blockage target monitoring points is as follows: Starting from the latest time window where the curve slope is less than b, trace back three time windows. Calculate the average signal energy of all upstream monitoring points within each time window, using this as the average signal energy of the upstream monitoring points within that time window. Similarly, calculate the average signal energy of all downstream monitoring points within each time window, using this as the average signal energy of the downstream monitoring points within that time window. Then, divide the average signal energy of the upstream and downstream monitoring points within the same time window, using this as the upstream-downstream energy ratio for that time window. When the upstream-downstream energy ratio is not less than 2.5 for three consecutive time windows, perform the following operations in the next time window to determine the blockage monitoring point from the continuous blockage target monitoring points: For continuous blockage monitoring points, the signal energy of each blockage monitoring point within this time window is calculated. Along the water flow direction of the drainage pipe, the signal energy of the next blockage monitoring point is subtracted from that of the previous blockage monitoring point within this time window. When the subtraction result is negative for the first time, the next blockage monitoring point is taken as the first blockage monitoring point. This process is repeated until the difference becomes positive for the first time. The previous blockage monitoring point when the difference becomes positive for the first time is taken as the last blockage monitoring point. All monitoring points between the first and last blockage monitoring points are output as blockage monitoring points.

[0014] Additionally, a drainage pipe blockage identification system based on distributed vibration fiber optic sensing is provided, characterized in that: the system is used to execute the aforementioned drainage pipe blockage identification method based on distributed vibration fiber optic sensing, including: The monitoring point group integration module is used to extract features of the fiber optic signals of the target monitoring point group on the drainage pipeline in each time window within the current time period, so as to construct its feature time series set and perform curve fitting. The latest time window with a curve slope greater than a is extracted as the first time window, and when the curve slope is less than b at the latest time window, it proceeds to step 2. The initial blockage location module is used to analyze the time difference between the first time window and the latest time window, the slope of the curve of the monitoring point group adjacent to the target monitoring point group at the first time window, and to determine whether there is a suspected blockage. If so, step 3 is executed. The blockage point location module is used to analyze the fiber optic signal of any monitoring point in the target monitoring point group and its adjacent monitoring point groups within a predetermined time period before the latest time window to determine its peak rise time, peak fall time and half width at half maximum (WHM), thereby determining the blockage target monitoring point and the reference monitoring point. Step 4 is executed only if there are consecutive blockage target monitoring points. The blockage monitoring point output module is used to determine the target blockage monitoring section from the drainage pipe based on continuous blockage target monitoring points, and to determine the reference monitoring point as the upstream or downstream monitoring point based on it. The module calculates the signal energy of each upstream / downstream monitoring point, and compares and analyzes the average signal energy of the upstream monitoring point and the average signal energy of the downstream monitoring point to determine the blockage monitoring point from the continuous blockage target monitoring points.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention sets up multiple monitoring point groups and extracts feature values ​​from the signals of the monitoring points within each group. When an abnormal slope is found in a monitoring point group within a certain time difference, the slope of the adjacent monitoring point groups before and after that monitoring point group is analyzed. A threshold triggering mechanism is used to determine whether the monitoring point group is a suspected blockage point. It does not require full collection and transmission of signals from all monitoring points in the entire section. Only after a suspected blockage point is determined, the signals of the target and all target monitoring points corresponding to the adjacent monitoring point groups are uploaded and processed. This invention also identifies suspected blockage points and, based on the characteristics of continuous water flow, high-speed jets, and strong turbulence caused by the contraction of the flow cross-section at the blockage location, processes the signals of all target monitoring points within the first two hours to obtain the peak rise time, peak fall time, and half-width at half-maximum (WHM) of each target monitoring point corresponding to these characteristics. This process determines the blockage target monitoring point, and then performs energy analysis on the target blockage monitoring section and the monitoring points before and after it to output the location of the blockage monitoring point. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 This is a flowchart for determining suspected blockages in this invention; Figure 3 This is a location map of the blockage monitoring points for this invention; Figure 4 This is a schematic diagram of the overall system structure of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0018] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0019] Example: Please see Figures 1 to 3 The present invention provides a technical solution: The method for identifying blockages in drainage pipes based on distributed vibration fiber optic sensing includes the following steps: Step 1: For the target monitoring point group on the drainage pipeline, extract the features of the fiber optic signals of each time window in the current time period to construct its feature time series set and perform curve fitting. Extract the latest time window with a curve slope greater than a as the first time window, and proceed to step 2 when the curve slope is less than b at the latest time window. For drainage pipes with a single section length of approximately 20m, the main form of blockage is localized short blockages. The blockage length of such pipes is mostly concentrated between 0.3m and 2m. Therefore, vibration fiber optic sensors are installed at equal intervals of 0.2m along the water flow direction of the drainage pipe. The axial vibration time-domain signal of the pipe is acquired in real time at each monitoring point to cover the typical blockage length and capture the characteristics of the blockage. The frequency of the vibration fiber optic sensors is not less than 100Hz, so that each monitoring point can collect 100 axial vibration amplitude data per second, avoiding the inability to monitor the frequency of water flow vibration, which would lead to signal distortion. The locations where vibration fiber optic sensors are deployed are used as monitoring points. Starting from the first monitoring point, every N monitoring points are divided into a monitoring point group. All the divided monitoring point groups are traversed. The remaining monitoring points with less than N points are not divided into monitoring point groups. The monitoring point groups are numbered in ascending order along the water flow direction of the drainage pipe. When analyzing each monitoring point group, it is used as the target monitoring point group. The value of N is between 3 and 10, which ensures that most of the blockage length is covered. At the same time, the preliminary determination of the blockage location can be completed based on a small amount of data within the monitoring point group. It is not necessary to upload the data of all monitoring points to the central processing unit in real time, thereby reducing the data transmission and centralized computing pressure. In such pipelines, the actual duration from the occurrence to maturity of a blockage generally ranges from 10 minutes to 2 hours. Especially when the blockage intensity increases from about 40% to 60%, it is a stage where the vibration energy tends to stabilize after a rapid increase. This change can be effectively identified through signal energy slope analysis over a short period of time. The trend change of vibration energy caused by the blockage can be captured within 5 minutes. Therefore, by tracing back a predetermined time length as the current time period, with the preset time length between 60 and 300 seconds, the trend change of the blockage energy can be fully captured, feature loss can be avoided, and a preliminary judgment can be made as to whether a blockage has occurred. However, the drainage pipeline environment is complex, with numerous random instantaneous vibration disturbances, such as heavy vehicles passing by on the ground and occasional vibrations from pumping stations. Based on practical engineering experience, these noises typically last no more than one second and do not form continuous, stable energy characteristics. Therefore, the current time period is divided into several equally spaced time windows, and each time window is further divided into equally spaced sub-time windows, with each sub-time window lasting no more than one second. For any monitoring point within the target monitoring point group, the sum of the squares of the instantaneous amplitudes of the pipeline axial vibration time-domain signal within each sub-time window is obtained to obtain the signal energy of each sub-time window. The minimum signal energy of each sub-time window is extracted as the first characteristic value of that time window. The duration of the sub-time window ranges from 50 to 200 ms. For example, the duration of a sub-time window can be set to 100 ms. In this case, after taking the minimum signal energy within the sub-time window, the mean of the first characteristic values ​​of all monitoring points within the target monitoring point group in the same time window is calculated and used as the characteristic value of the target monitoring point group in this time window. By extracting the minimum value and calculating the mean within the group, instantaneous spike noise can be effectively filtered out, the signal-to-noise ratio can be significantly improved, and the stable vibration energy caused by blockage can be accurately characterized. Finally, the feature values ​​of the target monitoring point group in each time window are summarized to construct its feature time series set, and then a curve is fitted with the time window as the horizontal axis and the feature value as the vertical axis. Under this curve, the slope of the curve corresponding to each time window can be known, providing a quantitative basis for subsequent blockage determination. During the mature stage of blockage, the energy variation amplitude of the vibration signal is more than three times that of normal operating conditions. To distinguish between normal operating conditions and blockage events, a reference time interval is selected under normal operating conditions of the drainage pipe without blockage. For example, this reference time interval can be selected as a continuous 24-hour period to continuously collect the time domain signal of the axial vibration of the pipe at each monitoring point in the target monitoring point group within the reference time interval. The curve of the target monitoring point group within the reference time interval is fitted with this signal, and the slope of the curve of the target monitoring point group in each time window within the reference time interval is extracted. The mean slope and standard deviation of the curve slope are calculated accordingly. Although the energy variation amplitude of the vibration signal is more than three times that of normal operating conditions, in order to improve the robustness of the operating condition judgment, this invention uses statistical thresholds for quantitative judgment. The value of the mean slope plus twice the standard deviation of the curve slope is taken as 'a', and the value of the mean slope minus twice the standard deviation of the curve slope is taken as 'b'. Slope 'a' is considered to be an abnormally high slope, belonging to the stage of rapid energy rise caused by blockage. Slope 'b' corresponds to an abnormally low slope, that is, the blockage has entered the dynamic equilibrium stage, thus initially distinguishing between normal fluctuations and blockage events. The core hydraulic characteristic of blockage is that when blockage occurs, the blockage point causes a reduction in the flow cross-section. Therefore, the pressure in front of the blockage point will increase significantly, causing the vibration energy to rise rapidly. When the downstream water flow recovers, the vibration energy does not change significantly. Therefore, based on this characteristic, the monitoring point group adjacent to the target monitoring point group and whose number is less than the target monitoring point group number is defined as the previous adjacent monitoring point group of the target monitoring point group, and the monitoring point group adjacent to the target monitoring point group and whose number is greater than the target monitoring point group number is defined as the next adjacent monitoring point group of the target monitoring point group. This establishes a clear upstream and downstream spatial judgment benchmark, and then analyzes the degree of energy change in the upstream and downstream and the blockage point. When the slope of the curve is less than b at the latest time window, proceed to step 2.

[0020] Step 2: Analyze the time difference between the first time window and the latest time window, and the slope of the curve of the monitoring point group adjacent to the target monitoring point group at the first time window to determine whether there is a suspected blockage. If so, proceed to step 3. If the target monitoring point group number is the minimum or maximum value, it is defined as having no suspected blockage. This is because over 90% of blockages occur in the middle section of the pipeline, with almost no blockages at the beginning and end. Furthermore, in actual engineering, blockage monitoring at the beginning and end of pipelines typically uses pressure characteristic sampling feedback, which has higher monitoring accuracy than vibration signals, eliminating the need for vibration signal judgment in this scheme. Therefore, if the target monitoring point group number is not the minimum or maximum value, the monitoring points are judged as follows: Analyze the time difference between the first time window and the latest time window. If the time difference is not greater than the effective time threshold, and the slope of the curve of the previous adjacent monitoring point group of the target monitoring point group in the first time window is greater than 'a', and the slope of the subsequent adjacent monitoring point group of the target monitoring point group in the first time window is less than 'a', then it is determined that there is a suspected blockage in the target monitoring point group. Otherwise, there is no suspected blockage. When blockage begins to accumulate in the pipe, the blockage will significantly hinder the water flow. Studies have shown that from the initial occurrence of pipe blockage to the maturity stage, that is, the complete stage of vibration energy from rapid rise to stabilization, it generally takes less than 2 hours. The first time window is the latest time window with a curve slope greater than 'a'. The time difference between the first time window and the latest time window is the duration from the end of the energy rise at the blockage location to the maturity of the blockage. Therefore, the effective time threshold is set to 3 times the duration of the current time period, corresponding to 3-15 minutes.

[0021] Meanwhile, blockage only causes upstream water flow to become congested and vibration energy to rise abnormally. Downstream areas do not experience the impact energy generated by the accumulation of blockage material; their energy changes remain stable or even decreasing. Therefore, when the time difference is not greater than the effective time threshold, and the slope of the curve of the preceding adjacent monitoring point group in the first time window is greater than 'a', and the slope of the following adjacent monitoring point group in the first time window is less than 'a', a blockage condition is determined, and step 3 is executed. Figure 2 As shown, when analyzing 40 sets of target monitoring point samples, if the value of a is 0.5 and the effective time threshold is 180 seconds, the existence of suspected blockage can be determined by analyzing the time difference between the first time window and the latest time window, and the slope of the curve of the monitoring point group adjacent to the target monitoring point group at the first time window, so as to decide whether to execute step 3.

[0022] Step 3: For any monitoring point in the target monitoring point group and its adjacent monitoring point groups, analyze its fiber optic signal for a predetermined time period before the latest time window to determine its peak rise time, peak fall time and half width at half maximum (WHM), and then determine the blocked target monitoring point and the reference monitoring point. Step 4 is executed only if there are consecutive blocked target monitoring points. The transient noises caused by on-site vehicle traffic, turbulent impacts, and occasional equipment vibrations are all narrow spike pulses with a half-width of less than 100ms. Therefore, the minimum effective half-width is set to 100ms to filter out non-blocking transient interferences. The signal baseline value is the average vibration amplitude of the monitoring point under normal operating conditions without blockage. When the drainage pipe is unblocked, the time domain signal of the pipe axial vibration of each monitoring point within the reference time interval is continuously collected to extract all instantaneous amplitudes of each monitoring point within the reference time interval. For any monitoring point, the average of all instantaneous amplitudes within the reference time interval is calculated as the signal baseline value of that monitoring point, which serves as the criterion for judging abnormal amplitudes and distinguishing between abnormal peak values ​​caused by blockage and normal water flow vibration amplitude. Related studies have shown that the entire process of a pipeline blockage from its initial occurrence to its maturity stage, i.e., the complete phase from rapid increase to stabilization of vibration energy, generally takes less than 2 hours. Therefore, the target time interval is determined by taking the end of the latest time window as the endpoint and tracing back to the second predetermined time length. The second predetermined time length is no more than 2 hours and no less than the difference between the end of the first time window and the end of the latest time window for the target monitoring point group, thus fully covering all vibration signals from the rapid development stage to the maturity stage of the blockage. For any monitoring point within the target monitoring point group and its adjacent monitoring point groups, the maximum instantaneous amplitude is extracted from the time-domain signal of the pipeline axial vibration within the target time interval as its peak value within the target time interval, and the moment of the maximum instantaneous amplitude is extracted as its peak moment within the target time interval. Based on the peak moment, the moment when the instantaneous amplitude first falls below 20% of the difference between the signal baseline value and the peak value is located backward, and the time interval between this moment and the peak moment is taken as the peak rise time. The moment when the instantaneous amplitude first falls below 20% of the difference between the signal baseline value and the peak value is located backward, and the time interval between this moment and the peak moment is taken as the peak fall time. The moment when the instantaneous amplitude first falls below 50% of the difference between the peak value and the signal baseline value is located forward, and the moment when the instantaneous amplitude first falls below 50% of the difference between the peak value and the signal baseline value is located backward, and the time interval between the two moments is taken as the half-width at half-maximum (WHM). Blockage is a continuous hydraulic impoundment caused by local cross-sectional contraction. The vibration waveform is characterized by a gentle rise and a slow fall, rather than a spike pulse of instantaneous noise. Based on engineering experience, it is believed that the peak rise time will be greater than 40ms and the peak fall time will be greater than 100ms. Therefore, for any monitoring point in the target monitoring point group and adjacent monitoring point groups, if the peak rise time is greater than 40ms, the peak fall time is greater than 100ms, and the half-width at half-height is not less than 100ms, the monitoring point is determined to be a blockage target monitoring point. Otherwise, it is used as a reference monitoring point and is considered to be the upstream or downstream position of the blockage point. Step 4 is only executed when there are consecutive blockage target monitoring points.

[0023] Step 4: Based on continuous blockage target monitoring points, determine the target blockage monitoring section from the drainage pipe, and determine the reference monitoring point as the upstream or downstream monitoring point based on it. Calculate the signal energy of each upstream / downstream monitoring point, and perform a quotient analysis on the average signal energy of the upstream monitoring point and the average signal energy of the downstream monitoring point to determine the blockage monitoring point from the continuous blockage target monitoring points. The drainage pipe blockages are mostly short, localized blockages of 0.3m-2m, corresponding to multiple consecutive monitoring points. The core hydraulic characteristic of the blockage is upstream stagnation followed by downstream recovery; that is, upstream water flow is obstructed by the blockage, resulting in a significant increase in vibration energy; downstream water flow quickly returns to normal operating conditions, and vibration energy remains stable. Analysis is performed on all monitoring points corresponding to the target monitoring point group and its adjacent monitoring point groups: The continuously marked target blockage monitoring points are integrated into a target blockage monitoring segment. This eliminates monitoring points with similar blockage characteristics, identifies the core section with abnormal vibration characteristics, and uses it as the boundary of the blockage. All reference monitoring points along the drainage pipe flow direction before the target blockage monitoring segment are designated as upstream monitoring points, and all reference monitoring points along the drainage pipe flow direction after the target blockage monitoring segment are designated as downstream monitoring points. Note that not all monitoring points within the target blockage monitoring segment coincide with the physical blockage location; the hydraulic impact of the blockage may extend beyond 5m. Therefore, spatial differential logic using energy gradients is needed to determine the actual location of the blockage monitoring point. Under normal operating conditions, there is no significant difference in vibration energy between the upstream and downstream of the pipeline, and the energy ratio between the upstream and downstream is close to 1. The latest time window with a curve slope less than b indicates that the blockage has entered a stable and mature stage, with localized blockage formation. Vibration energy no longer exhibits explosive fluctuations but remains at a stable level. Therefore, starting from the latest time window with a curve slope less than b, the average signal energy of all upstream monitoring points in each time window is calculated as the average signal energy of the upstream monitoring points in that time window. Similarly, the average signal energy of all downstream monitoring points in each time window is calculated as the average signal energy of the downstream monitoring points in that time window. The average signal energy within a time window is used, and the quotient of the average signal energy of upstream and downstream monitoring points within the same time window is taken as the upstream-downstream energy ratio for that time window. When local blockage occurs, the upstream stagnation causes vibration energy to be more than 2.5 times that of the downstream. Therefore, in the latest time window where the curve slope is less than b, three time windows are traced back until the upstream-downstream energy ratio is not less than 2.5 for three consecutive time windows. In the next time window, the following operation is performed to determine the blockage monitoring point from the continuous blockage target monitoring points, avoiding misjudgment due to a single accidental interference. The operation is as follows: For continuous blockage monitoring points, the signal energy of each monitoring point within a given time window is calculated. Along the water flow direction of the drainage pipe, the signal energy of each subsequent blockage monitoring point is subtracted from the signal energy of the preceding blockage monitoring point within that time window. The monitoring point corresponding to the first negative subtraction is designated as the first blockage monitoring point, and this process is repeated sequentially. The first blockage monitoring point is then subtracted from the signal energy of its immediately upstream monitoring point within the same time window. This continues until the difference first becomes positive. The preceding blockage monitoring point corresponding to the first positive difference is then designated as the last blockage monitoring point. All monitoring points between the first and last blockage monitoring points are then output as blockage monitoring points. Figure 3 As shown, for the analysis of 11 consecutive blockage target monitoring points, the difference in signal energy between the next blockage target monitoring point and the previous blockage target monitoring point in the time window is calculated in turn. In the 5th adjacent blockage target monitoring point, the difference is negative for the first time and the downward trend is significant. It can be concluded that the next blockage target monitoring point of this adjacent blockage target monitoring point is the blockage monitoring point, that is, the physical blockage location. This is because, based on experiments and the flow patterns and energy distribution of blockages, when water flows along the pipe towards the blockage point, the obstruction intensifies the water accumulation, and the vibration energy gradually increases. After passing the core blockage area, the flow cross-section recovers, the energy dissipates rapidly, and the energy slightly rebounds after the downstream flow stabilizes again. Therefore, when the energy ratio before and after the blockage point is consistently higher than 2.5, energy gradient analysis is performed on the target blockage monitoring section. The energy difference between adjacent monitoring points is calculated along the water flow direction. When the difference first turns from positive to negative, it indicates that the water flow has entered the blockage coverage area. Continuing to traverse backwards, when the difference first turns from negative to positive, it indicates that the water flow has left the blockage section and the energy begins to rebound. Through this spatial gradient differential logic, only monitoring points where actual blockages exist are retained, improving the accuracy of positioning.

[0024] Please see Figure 4 The present invention also provides a drainage pipe blockage identification system based on distributed vibration fiber optic sensing, for performing the above-described drainage pipe blockage identification method based on distributed vibration fiber optic sensing, including: The monitoring point group integration module is used to extract features of the fiber optic signals of the target monitoring point group on the drainage pipeline in each time window within the current time period, so as to construct its feature time series set and perform curve fitting. The latest time window with a curve slope greater than a is extracted as the first time window, and when the curve slope is less than b at the latest time window, it proceeds to step 2. The initial blockage location module is used to analyze the time difference between the first time window and the latest time window, the slope of the curve of the monitoring point group adjacent to the target monitoring point group at the first time window, and to determine whether there is a suspected blockage. If so, step 3 is executed. The blockage point location module is used to analyze the fiber optic signal of any monitoring point in the target monitoring point group and its adjacent monitoring point groups within a predetermined time period before the latest time window to determine its peak rise time, peak fall time and half width at half maximum (WHM), thereby determining the blockage target monitoring point and the reference monitoring point. Step 4 is executed only if there are consecutive blockage target monitoring points. The blockage monitoring point output module is used to determine the target blockage monitoring section from the drainage pipe based on continuous blockage target monitoring points, and to determine the reference monitoring point as the upstream or downstream monitoring point based on it. The module calculates the signal energy of each upstream / downstream monitoring point, and compares and analyzes the average signal energy of the upstream monitoring point and the average signal energy of the downstream monitoring point to determine the blockage monitoring point from the continuous blockage target monitoring points.

[0025] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0026] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the monitoring point groups and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0027] The monitoring point group described as a separate component may or may not be physically separated. The component shown as a monitoring point group may or may not be a physical monitoring point group; it may be located in one place or distributed across multiple network monitoring point groups. Some or all of the monitoring point groups can be selected to achieve the purpose of this embodiment according to actual needs.

[0028] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for identifying blockages in drainage pipes based on distributed vibration fiber optic sensing, characterized in that, The specific steps include: Step 1: For the target monitoring point group on the drainage pipeline, extract the features of the fiber optic signals of each time window in the current time period to construct its feature time series set and perform curve fitting. Extract the latest time window with a curve slope greater than a as the first time window, and proceed to step 2 when the curve slope is less than b at the latest time window. Step 2: Analyze the time difference between the first time window and the latest time window, and the slope of the curve of the monitoring point group adjacent to the target monitoring point group at the first time window to determine whether there is a suspected blockage. If so, proceed to step 3. Step 3: For any monitoring point in the target monitoring point group and its adjacent monitoring point groups, analyze its fiber optic signal for a predetermined time period before the latest time window to determine its peak rise time, peak fall time and half width at half maximum (WHM), and then determine the blocked target monitoring point and the reference monitoring point. Step 4 is executed only if there are consecutive blocked target monitoring points. Step 4: Based on continuous blockage target monitoring points, determine the target blockage monitoring section from within the drainage pipe, and determine the reference monitoring point as the upstream or downstream monitoring point based on it. Calculate the signal energy of each upstream / downstream monitoring point, and quotient and analyze the average signal energy of the upstream monitoring point and the average signal energy of the downstream monitoring point to determine the blockage monitoring point from the continuous blockage target monitoring points.

2. The drainage pipe blockage identification method based on distributed vibration fiber optic sensing according to claim 1, characterized in that: The method for setting up the monitoring point group is as follows: Vibration fiber optic sensors are arranged at equal intervals of 0.2m along the water flow direction of the drainage pipe, and the frequency of the vibration fiber optic sensors is not less than 100Hz. The locations where the vibration fiber optic sensors are arranged are used as monitoring points. Starting from the first monitoring point, every N monitoring points are divided into a monitoring point group. All the divided monitoring point groups are traversed. The remaining monitoring points with less than N points are not divided into monitoring point groups. The monitoring point groups are numbered in ascending order along the water flow direction of the drainage pipe. When analyzing each monitoring point group, it is used as the target monitoring point group.

3. The drainage pipe blockage identification method based on distributed vibration fiber optic sensing according to claim 2, characterized in that: The method for feature extraction of fiber optic signals from the target monitoring point group within each time window of the current time period is as follows: Using the current moment as the endpoint, a predetermined time length is traced back to be used as the current time period. The preset time length is between 60 and 300 seconds. The time domain signal of the pipeline axial vibration, i.e. the fiber optic signal, is acquired in real time at each monitoring point. The current time period is divided into several time windows, and each time window is further divided into several sub-time windows. For any monitoring point in the target monitoring point group, obtain the sum of squares of the instantaneous amplitude of the time domain signal of the pipeline axial vibration in each sub-time window to obtain the signal energy of the monitoring point in each sub-time window. Extract the minimum signal energy of the monitoring point in each sub-time window in the same time window as the first feature value of the monitoring point in this time window. The mean of the first feature values ​​of all monitoring points in the target monitoring point group within the same time window is calculated as the feature value of the target monitoring point group in this time window. The feature values ​​of the target monitoring point group in each time window are summarized to construct its feature time series set, and then a curve is fitted with the time window as the horizontal axis and the feature value as the vertical axis.

4. The drainage pipe blockage identification method based on distributed vibration fiber optic sensing according to claim 3, characterized in that: The method for setting a and b is as follows: Under normal operating conditions with no blockages in the drainage pipe, a reference time interval is selected, and the time-domain signal of the axial vibration of the pipe at each monitoring point in the target monitoring point group within the reference time interval is continuously collected. The curve of the target monitoring point group within the reference time interval is then fitted, and the slope of the curve of the target monitoring point group in each time window within the reference time interval is extracted. The mean slope and standard deviation of the curve slope are then calculated. The value of the mean slope plus twice the standard deviation of the curve slope is taken as 'a', and the value of the mean slope minus twice the standard deviation of the curve slope is taken as 'b'.

5. The drainage pipe blockage identification method based on distributed vibration fiber optic sensing according to claim 2, characterized in that: The monitoring point group that is adjacent to the target monitoring point group and whose number is less than the target monitoring point group number is defined as the previous adjacent monitoring point group of the target monitoring point group, and the monitoring point group that is adjacent to the target monitoring point group and whose number is greater than the target monitoring point group number is defined as the next adjacent monitoring point group of the target monitoring point group. If the target monitoring point group's number is the minimum or maximum value, then it is defined as not having any suspected blockages; otherwise, the following judgment is made: If the time difference is not greater than the effective time threshold, and the slope of the curve of the previous adjacent monitoring point group of the target monitoring point group in the first time window is greater than a, and the slope of the subsequent adjacent monitoring point group of the target monitoring point group in the first time window is less than a, then it is determined that there is a suspected blockage in the target monitoring point group; otherwise, there is no suspected blockage. The effective time threshold is three times the duration of the current time period.

6. The drainage pipe blockage identification method based on distributed vibration fiber optic sensing according to claim 5, characterized in that: The method for determining the target monitoring point and reference monitoring point for blockage is as follows: Set the minimum effective half-width to 100ms; When the drainage pipe is unblocked, the time domain signal of the pipe axial vibration of each monitoring point within the reference time interval is continuously collected to extract all instantaneous amplitude values ​​of each monitoring point within the reference time interval. For any monitoring point, the mean value of all instantaneous amplitude values ​​within the reference time interval is calculated as the signal baseline value of that monitoring point. The target time interval is determined by tracing back a second predetermined time length from the end of the latest time window. The second predetermined time length is no more than 2 hours and no less than the difference between the end of the first time window of the target monitoring point group and the end of the latest time window. For any monitoring point within the target monitoring point group and its adjacent monitoring point groups, the maximum instantaneous amplitude is extracted from the time-domain signal of the pipeline axial vibration within the target time interval as its peak value within the target time interval, and the moment of the maximum instantaneous amplitude is extracted as its peak moment within the target time interval. Based on the peak moment, the moment when the instantaneous amplitude first falls below 20% of the difference between the signal baseline value and the peak value is located backward, and the time interval between this moment and the peak moment is taken as the peak rise time. The moment when the instantaneous amplitude first falls below 20% of the difference between the signal baseline value and the peak value is located backward, and the time interval between this moment and the peak moment is taken as the peak fall time. The moment when the instantaneous amplitude first falls below 50% of the difference between the peak value and the signal baseline value is located forward, and the moment when the instantaneous amplitude first falls below 50% of the difference between the peak value and the signal baseline value is located backward, and the time interval between the two moments is taken as the half-width at half-maximum (WHM). For any monitoring point in the target monitoring point group and adjacent monitoring point groups, if its peak rise time is greater than 40ms, peak fall time is greater than 100ms, and half-width is not less than 100ms, the monitoring point is determined to be a blockage target monitoring point; otherwise, it is used as a reference monitoring point.

7. The drainage pipe blockage identification method based on distributed vibration fiber optic sensing according to claim 6, characterized in that: The method for identifying the target blockage monitoring section within the drainage pipe and determining whether a reference monitoring point is an upstream or downstream monitoring point based on it is as follows: Analyze all monitoring points corresponding to the target monitoring point group and its adjacent monitoring point groups: integrate the continuously marked blockage target monitoring points into a target blockage monitoring section, take all reference monitoring points located before the target blockage monitoring section along the water flow direction of the drainage pipe as upstream monitoring points, and take all reference monitoring points located after the target blockage monitoring section along the water flow direction of the drainage pipe as downstream monitoring points.

8. The drainage pipe blockage identification method based on distributed vibration fiber optic sensing according to claim 7, characterized in that: The method for determining blockage monitoring points from a continuous range of blockage target monitoring points is as follows: Starting from the latest time window where the curve slope is less than b, trace back three time windows. Calculate the average signal energy of all upstream monitoring points within each time window, using this as the average signal energy of the upstream monitoring points within that time window. Similarly, calculate the average signal energy of all downstream monitoring points within each time window, using this as the average signal energy of the downstream monitoring points within that time window. Then, divide the average signal energy of the upstream and downstream monitoring points within the same time window, using this as the upstream-downstream energy ratio for that time window. When the upstream-downstream energy ratio is not less than 2.5 for three consecutive time windows, perform the following operations in the next time window to determine the blockage monitoring point from the continuous blockage target monitoring points: For continuous blockage monitoring points, the signal energy of each blockage monitoring point within this time window is calculated. Along the water flow direction of the drainage pipe, the signal energy of the next blockage monitoring point is subtracted from that of the previous blockage monitoring point within this time window. When the subtraction result is negative for the first time, the next blockage monitoring point is taken as the first blockage monitoring point. This process is repeated until the difference becomes positive for the first time. The previous blockage monitoring point when the difference becomes positive for the first time is taken as the last blockage monitoring point. All monitoring points between the first and last blockage monitoring points are output as blockage monitoring points.

9. A drainage pipe blockage identification system based on distributed vibration fiber optic sensing, characterized in that: The system is used to perform the drainage pipe blockage identification method based on distributed vibration fiber optic sensing as described in any one of claims 1-8: The monitoring point group integration module is used to extract features of the fiber optic signals of the target monitoring point group on the drainage pipeline in each time window within the current time period, so as to construct its feature time series set and perform curve fitting. The latest time window with a curve slope greater than a is extracted as the first time window, and when the curve slope is less than b at the latest time window, it proceeds to step 2. The initial blockage location module is used to analyze the time difference between the first time window and the latest time window, the slope of the curve of the monitoring point group adjacent to the target monitoring point group at the first time window, and to determine whether there is a suspected blockage. If so, step 3 is executed. The blockage point location module is used to analyze the fiber optic signal of any monitoring point in the target monitoring point group and its adjacent monitoring point groups within a predetermined time period before the latest time window to determine its peak rise time, peak fall time and half width at half maximum (WHM), thereby determining the blockage target monitoring point and the reference monitoring point. Step 4 is executed only if there are consecutive blockage target monitoring points. The blockage monitoring point output module is used to determine the target blockage monitoring section from the drainage pipe based on continuous blockage target monitoring points, and to determine the reference monitoring point as the upstream or downstream monitoring point based on it. The module calculates the signal energy of each upstream / downstream monitoring point, and compares and analyzes the average signal energy of the upstream monitoring point and the average signal energy of the downstream monitoring point to determine the blockage monitoring point from the continuous blockage target monitoring points.

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