A method and system for dynamic assessment of the risk of blockage of a concrete delivery pipe

Abstract

The application provides a concrete delivery pipeline blockage risk dynamic evaluation method and system. First, the geometric characteristic information of the concrete delivery pipeline is obtained, and the pressure data and the flow rate data in the concrete delivery pipeline are collected in real time during the concrete delivery process. Then, based on the geometric characteristic information, the pressure data is dynamically compensated to generate compensated pressure data. Then, combined with the compensated pressure data and the flow rate data, the blockage risk evaluation value under the current concrete delivery state is calculated. Finally, according to the blockage risk evaluation value, a blockage risk evaluation report is output. The technical scheme provided by the application effectively eliminates structure interference false alarms, realizes accurate positioning and hierarchical response of the blockage risk position, and improves the blockage disposal efficiency and reliability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric digital data processing, and in particular to a concrete conveying pipeline blockage risk dynamic evaluation method and system. BACKGROUND

[0002] In the concrete pumping construction scene of super high-rise buildings, large-scale water conservancy projects and the like, the concrete conveying pipeline is prone to blockage accidents due to long distance, multi-bend pipe structure and complex concrete rheological properties.

[0003] The current mainstream scheme adopts a real-time monitoring system based on a pressure-flow rate dual-parameter threshold value. Specifically, real-time data is collected by pressure sensors and flowmeters arranged at key nodes of the pipeline. When it is detected that the pressure value continuously exceeds a preset static threshold value and is accompanied by a decrease in flow rate, a blockage alarm signal is triggered. The system relies on wireless transmission technology to realize multi-node data collection, and generates a pressure-flow rate trend curve on a central control platform to assist manual judgment.

[0004] Although this monitoring system can capture some blockage signs, it does not take into account the dynamic influence of structural parameters such as pipe bend angle and length on fluid resistance, resulting in distorted pressure data interpretation, especially frequent false alarms in the dense bend pipe area. At the same time, the fixed threshold value cannot adapt to changes in working conditions at different pumping stages (such as start, constant pressure and end), resulting in a high false alarm rate. More importantly, its alarm mechanism only marks the time dimension anomaly and cannot associate the spatial position of the pipeline to generate disposal guidance, making it difficult for operation and maintenance personnel to quickly locate the blockage section and develop a dredging strategy. SUMMARY

[0005] The present application provides a concrete conveying pipeline blockage risk dynamic evaluation method and system to solve the problems of high false alarm rate caused by decoupling of pressure data and pipeline physical structure, false triggering caused by fixed threshold value failing to respond to changes in pumping conditions, and low blockage point positioning efficiency caused by time-space separation of alarm signals in the prior art.

[0006] In a first aspect, the present application provides a concrete conveying pipeline blockage risk dynamic evaluation method, comprising:

[0007] obtaining geometric feature information of a concrete conveying pipeline, wherein the geometric feature information includes bend angle and length;

[0008] During the concrete conveying process, real-time collection of pressure data and flow rate data in the concrete conveying pipeline is performed;

[0009] based on the geometric feature information, performing dynamic compensation processing on the pressure data to generate compensated pressure data;

[0010] Combine the compensated pressure data and the flow rate data to calculate a blockage risk evaluation value under a current concrete conveying state;

[0011] According to the blockage risk evaluation value, output a blockage risk evaluation report.

[0012] Optionally, based on the geometric feature information, perform dynamic compensation processing on the pressure data to generate compensated pressure data, including:

[0013] Based on the bending angle, calculate a bending angle compensation value;

[0014] Based on the length, perform proportional adjustment processing on the bending angle compensation value to generate a comprehensive compensation parameter;

[0015] Apply the comprehensive compensation parameter to the pressure data to generate compensated pressure data.

[0016] Optionally, based on the length, perform proportional adjustment processing on the bending angle compensation value to generate a comprehensive compensation parameter, including:

[0017] Obtain a predefined pipe resistance reference parameter;

[0018] According to the mapping relationship between the bending angle compensation value and the pipe resistance reference parameter, calculate an influence factor of the bending angle on the unit length;

[0019] Combine the influence factor of the bending angle on the unit length with the length to generate a pipe comprehensive resistance correction value through continuous superposition calculation;

[0020] Take the pipe comprehensive resistance correction value as a comprehensive compensation parameter.

[0021] Optionally, apply the comprehensive compensation parameter to the pressure data to generate compensated pressure data, including:

[0022] Establish a dynamic balance model including a pressure balance unit and a resistance correction unit;

[0023] Input the pressure data into the pressure balance unit;

[0024] Input the comprehensive compensation parameter into the resistance correction unit to generate a dynamic correction component;

[0025] Perform a loop superposition operation on the pressure data and the dynamic correction component in the pressure balance unit;

[0026] When the loop superposition result meets a preset fluid dynamic balance condition, output compensated pressure data.

[0027] Optionally, in combination with the compensated pressure data and the flow rate data, a blockage risk evaluation value in the current concrete conveying state is calculated, including:

[0028] An abnormal pressure period feature value is extracted from the compensated pressure data;

[0029] A flow rate decay period feature value is extracted from the flow rate data;

[0030] An overlapping area of the abnormal pressure period feature value and the decay period feature value on a time axis is detected;

[0031] A blockage feature quantization value is generated based on a duration and an overlapping degree of the overlapping area;

[0032] The blockage feature quantization value is converted into a blockage risk evaluation value.

[0033] Optionally, the overlapping area of the abnormal pressure period feature value and the decay period feature value on the time axis is detected, including:

[0034] A pressure main action area of the abnormal pressure period feature value is defined, wherein the pressure main action area covers a pressure rising stage and a peak duration stage;

[0035] A decay effective area of the flow rate decay period feature value is defined, wherein the decay effective area lasts from a flow rate inflection point to a flow rate recovery threshold point;

[0036] A time sequence coincidence state of the pressure main action area and the decay effective area is captured through a sliding time window;

[0037] When a starting time of the pressure main action area is ahead of the decay effective area and a delay is less than a first set threshold, an effective overlapping event is recorded;

[0038] A duration and an occurrence interval of all effective overlapping events are aggregated to generate an overlapping area.

[0039] Optionally, according to the blockage risk evaluation value, a blockage risk assessment report is output, including:

[0040] A pumping pipeline risk distribution map is constructed, wherein the pumping pipeline risk distribution map is associated with geometric feature information of the concrete conveying pipeline;

[0041] Based on a numerical size of the blockage risk evaluation value, an emergency response event, a buffer processing event and a monitoring tracking event are divided;

[0042] mapping the emergency response event to a first priority area of the pumping pipeline risk distribution map, mapping the buffer handling event to a second priority area of the pumping pipeline risk distribution map, and mapping the monitoring tracking event to a third priority area of the pumping pipeline risk distribution map;

[0043] generating, by a risk level conversion device, multi-level treatment instructions corresponding to the first priority area, the second priority area, and the third priority area;

[0044] synthesizing, by a report generation device, the pumping pipeline risk distribution map and the multi-level treatment instructions to generate a blockage risk assessment report with a position marker.

[0045] In a second aspect, the present application provides a concrete delivery pipeline blockage risk dynamic assessment system, comprising:

[0046] an acquisition module configured to acquire geometric feature information of a concrete delivery pipeline, wherein the geometric feature information comprises a bending angle and a length;

[0047] a collection module configured to collect, in real time, pressure data and flow rate data in the concrete delivery pipeline during a concrete delivery process;

[0048] a processing module configured to perform dynamic compensation processing on the pressure data based on the geometric feature information to generate compensated pressure data;

[0049] a calculation module configured to calculate a blockage risk evaluation value in a current concrete delivery state in combination with the compensated pressure data and the flow rate data;

[0050] an output module configured to output a blockage risk assessment report according to the blockage risk evaluation value.

[0051] In a third aspect, the present application provides a computing device, comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a concrete delivery pipeline blockage risk dynamic assessment method as described in the first aspect.

[0052] In a fourth aspect, the present application provides a computer storage medium storing a computer program, wherein the computer program is executed by a computer to implement a concrete delivery pipeline blockage risk dynamic assessment method as described in the first aspect.

[0053] The application establishes a multi-dimensional perception framework of the concrete conveying state by synchronously acquiring pipeline geometric feature information and real-time pumping parameters, and realizes the transition of the blockage risk assessment from passive response to active prediction. The geometric feature information is processed cooperatively with the dynamically collected pressure and flow rate data as a structural constraint condition, forming the physical basis for pressure compensation and risk calculation, and fundamentally overcoming the defect of decoupling of structural parameters and flow state in traditional methods. The finally output risk assessment report runs through the whole process of pumping process monitoring, risk warning and disposal decision, and significantly improves the safety control ability of high-risk construction scenes.

[0054] Further, an innovative mechanism of generating a compensation value based on the pipe bending angle and fusing the pipe length proportion adjustment is constructed, and a pressure dynamic correction model adapting to the concrete rheological properties is constructed. The scheme converts the geometric features into comprehensive compensation parameters acting on the original pressure data in view of the difference between the local resistance mutation of the elbow pipe area and the cumulative resistance of the straight pipe section. This operation effectively eliminates the distortion of the pressure signal caused by the physical structure of the pipeline, so that the compensated pressure data truly reflects the actual resistance state of the concrete fluid, laying an accurate data foundation for subsequent risk assessment.

[0055] Further, by extracting the characteristic values of the abnormal pressure period and the flow rate decay period and detecting the overlapping area, a blockage event identification model coupled in time and space is constructed. This method breaks through the limitation of single parameter threshold, captures the precursor characteristics of pipe blockage by using the synchronous characteristics of pressure surge and flow rate decay. The blockage characteristic quantization value generated based on the overlapping area characteristics accurately represents the occurrence intensity and development trend of the blockage event, and is finally converted into a scientific and reliable risk evaluation value; the robustness of risk judgment under complex working conditions is improved, and misjudgment caused by intermittent fluctuations is avoided.

[0056] These aspects or other aspects of the application will be more apparent in the following description of the embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0058] Figure 1 A flow chart of a concrete conveying pipeline blockage risk dynamic assessment method provided by the application is shown;

[0059] Figure 2 A structural schematic diagram of a concrete conveying pipeline blockage risk dynamic assessment system provided by the application is shown;

[0060] Figure 3A structural schematic diagram of a computing device provided by the present application is shown. DETAILED DESCRIPTION

[0061] In order for those skilled in the art to better understand the scheme of the present application, the technical scheme in the present application will be clearly and completely described below in combination with the drawings in the present application.

[0062] In some of the processes described in the specification and the claims of the present application and the above drawings, a plurality of operations appearing in a specific order are included, but it should be clearly understood that these operations can be executed or in parallel without the order in which they appear in the text, and the serial numbers of the operations such as 101, 102, etc. are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes can include more or fewer operations, and the operations can be executed in sequence or in parallel. It should be noted that the "first", "second", etc. described herein are used to distinguish different messages, devices, modules, etc., and do not represent the order of precedence. Also, "first" and "second" are not of different types.

[0063] The technical scheme in the present application will be clearly and completely described below in combination with the drawings in the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0064] Figure 1 A flowchart of a method for dynamically evaluating the risk of blockage of a concrete delivery pipeline provided by the present application is shown in FIG. 1, which comprises the following steps: Figure 1

[0065] Step 101: Obtain the geometric feature information of the concrete delivery pipeline, wherein the geometric feature information includes the bending angle and the length.

[0066] In this step, the geometric feature information refers to a set of key parameters that describe the physical structure of the concrete delivery pipeline, mainly used to quantify the fluid flow resistance and spatial position influence; the bending angle specifically represents the bending degree of the pipe bending section (unit: degree), and its numerical value is directly related to the local resistance change when the fluid passes through the elbow; the length refers to the physical extension distance of the pipeline (unit: meter), representing the overall or segmented scale, used to evaluate the cumulative effect of the overall resistance. These parameters work together to provide a basis for subsequent dynamic compensation and risk calculation.

[0067] ​In this embodiment, first, the system calls the pre-constructed pipeline configuration database interface, extracts the stored bend angle data from the design stage digital drawing or laser scanning point cloud processing during installation using a database query algorithm (such as SQL retrieval technology); then, the length value is synchronously obtained using the same interface or an independent measurement module (such as an ultrasonic distance measuring sensor or a segmented cumulative algorithm); for segmented pipelines, the length calculation uses a cumulative strategy to ensure global consistency; then, these parameters are combined into a structured data set (JSON or XML format) and transmitted to the downstream module through the internal communication bus; the entire process is ensured by data verification logic (such as abnormal value filtering rules) to ensure information accuracy, and finally a geometric feature information package is generated that can be immediately used.

[0068] For example, in a certain high-rise building pumping scene, a delivery pipeline system containing a 120-meter straight pipe section and three 90-degree elbow pipes is pre-configured; during system initialization, the pipeline information management software is started, the design document is queried through the database API, the elbow bend angle data (each 90 degrees) is extracted, and the segmented length (40 meters each) is measured using an ultrasonic sensor and summed; based on these values, a geometric feature information data package is generated as the input reference for subsequent dynamic compensation processing.

[0069] Step 102, during the concrete conveying process, real-time acquisition of pressure data and flow rate data in the concrete conveying pipeline.

[0070] In this step, the pressure data refers to the internal fluid pressure value (usually in megapascals) obtained by the pressure sensor, which is used to represent the change in concrete flow resistance; the flow rate data refers to the movement speed of concrete in the pipeline measured by the flowmeter (usually in meters per second), which is used to reflect the continuity of the conveying state. Both types of data are time-stamped to achieve time synchronization, providing real-time input sources for core dynamic evaluation.

[0071] In this embodiment, it is realized through a multi-node sensor network and a real-time processing flow: first, piezoelectric pressure sensors and ultrasonic flowmeters are deployed at key positions in the pipeline (such as elbow sections and straight pipe section interfaces), and the original physical signals are converted into digital electrical signals by the sensor microprocessor; second, the LoRa wireless transmission protocol is used to aggregate node data packets (containing sensor ID, timestamp, and numerical value) to the edge computing gateway; then, the gateway runs data preprocessing algorithms (including median filter denoising and abnormal pulse suppression) to clean the original signals, and aligns the timestamps based on a unified clock source; finally, the cleaned data is time-sliced through a sliding window mechanism, and standardized pressure-flow rate data streams are output for downstream module calls.

[0072] In the continuation of the foregoing high-rise building project, the system deploys a set of pressure sensors (P1-P3) and ultrasonic flow meters (V1-V3) after each of the three 90-degree bends. After the concrete pumping starts, the P2 sensor detects a 1.5 MPa pressure fluctuation, and the V2 synchronously collects a flow rate of 0.8 m / s. After receiving the three sets of data through LoRa, the edge gateway eliminates mechanical vibration noise using median filtering and aligns the time sequence with 10 ms accuracy. Finally, it outputs a standardized dataset with the "Segment_2" location tag, providing a basic input source for the dynamic compensation of step 103.

[0073] Step 103, based on the geometric feature information, the pressure data is dynamically compensated to generate compensated pressure data.

[0074] In this step, the dynamic compensation processing specifically refers to the correction operation of real-time pressure data using pipe geometric features (bend angle and length). The purpose is to eliminate the inherent resistance interference caused by pipe structure, so that the pressure value only reflects the true state of concrete flow. The compensated pressure data is the correction result output by this correction operation, and its physical meaning is the net pressure value excluding the influence of pipe structure resistance, which is used to accurately identify the blockage anomaly.

[0075] In this embodiment, it is realized through multi-level calculation modules: first, call the bend angle compensation algorithm (such as the angle resistance mapping table based on experimental calibration data), combine the input bend angle to generate a bend angle compensation value; then execute the proportional adjustment algorithm, load the pre-set pipe resistance benchmark database, use the interpolation function to calculate the influence factor of bend angle on unit length, and generate the pipe comprehensive resistance correction value through cumulative integral operation of the influence factor and input length; then build a dynamic balance model, input the real-time pressure data stream into the pressure balance unit, and input the comprehensive resistance correction value into the resistance correction unit to generate a dynamic correction component sequence; in the pressure balance unit, perform loop iteration superposition (such as Newton-Raphson numerical approximation) on the original pressure data and dynamic correction component. When the pressure gradient change meets the convergence condition of the fluid continuity equation, the loop is terminated, and the compensated pressure data sequence is output, completing the structure resistance distortion correction.

[0076] Based on the geometric characteristics (three 90° bends, a single 40-meter section) obtained in the aforementioned high-rise building project and the 1.5 MPa pressure data collected at node P2, the system first calculates a 90° bend compensation value of 0.2 units through an angular resistance mapping table; retrieves the pipeline reference database to calculate an influence factor of 0.5 using cubic spline interpolation, and generates a comprehensive correction value of 0.8 by superimposing the 40-meter length after cumulative integration; the dynamic balance model iteratively calculates the original pressure 1.5 MPa and the correction component sequence for five rounds, and when the pressure fluctuation stabilizes within the ±0.05 MPa threshold, it outputs the compensated pressure 1.2 MPa, which eliminates the influence of inherent resistance in the bent pipe section and provides accurate input for the subsequent step 104 of blockage risk assessment.

[0077] Step 104, combining the compensated pressure data and the flow rate data, calculates the blockage risk evaluation value under the current concrete conveying state.

[0078] In this step, the blockage risk evaluation value specifically refers to a comprehensive evaluation index generated by quantitatively analyzing the time sequence correlation characteristics of the compensated pressure data and the flow rate data, which physically represents the probability and severity of blockage occurring in the current pipeline (usually output in percentage or risk level form) to drive the subsequent hierarchical response mechanism.

[0079] In this embodiment, the data analysis process is realized through multiple levels of linkage: first, time sequence feature extraction algorithms (such as local extreme value detection based on sliding windows) are used to identify abnormal pressure period feature values from the compensated pressure data, and derivative analysis methods are used to extract flow rate decay period feature values from the flow rate data; second, a time axis alignment engine is constructed to calculate the time sequence coincidence degree of the two feature values using the dynamic time warping algorithm (DTW), and when the "pressure main action area starting time precedes the decay effective area starting time and the delay is lower than the set threshold" condition is met, it is recorded as an effective overlap event; then, the duration and overlap area ratio of all effective overlap events are aggregated to generate a blockage feature quantization value; finally, the quantization value is converted to a blockage risk evaluation value in the range of 0-100 through a normalization mapping function (such as Sigmoid conversion), completing real-time risk assessment.

[0080] For example, continuing the high-rise building project case, based on the compensated pressure data 1.2 MPa and its abnormal fluctuation period (t=10s-30s) generated in step 103, combined with the decay period (t=11s-30s) extracted from the flow rate data, the time axis alignment engine detects that the starting time difference between the two is 1 second (<2 second threshold), determining an effective overlap event; the overlap duration of 19 seconds and the area ratio of 95% are calculated, and the Sigmoid function mapping generates a blockage risk evaluation value of 70%, indicating that the pipe section has a moderate blockage risk.

[0081] Step 105, according to the blockage risk evaluation value, outputs a blockage risk assessment report.

[0082] In this step, the blockage risk assessment report refers to a structured output document that integrates risk levels, pipeline locations, and disposal instructions. Its core function is to convert the blockage risk evaluation value into an executable disposal scheme with spatial coordinate identification, ultimately guiding precise unblocking operations on site.

[0083] In this embodiment, the risk space mapping engine is used to first analyze the pipeline geometric feature information and generate a pumping pipeline risk distribution map using a spatial coordinate system conversion algorithm (e.g., mapping the bending angle to spatial curvature). Then, the risk classification rule library is called, and when the blockage risk evaluation value exceeds the upper threshold, it is marked as an emergency response event, in the middle interval as a buffer processing event, and below the lower limit as a monitoring and tracking event. Next, the topological correlation algorithm is used to map the three-level events to the first, second, and third priority areas of the risk distribution map (e.g., using coordinate matching algorithm to bind the elbow number). Then, the risk level conversion device is triggered, and the multi-level disposal instruction library (including vibration unblocking parameters, reverse flow flushing scheme, etc.) is pre-stored according to the priority area index. Finally, the report generation device performs spatial data fusion to combine the vector layers of the risk distribution map with the disposal instruction text into a PDF format report, and marks the physical coordinates of the risk pipe segment with location markers (such as Segment_ID latitude and longitude encoding).

[0084] Continuing the previous high-rise building engineering case, the system defines the coordinates (x102, y205) of the No. 3 90° elbow pipe as the second priority area in the risk distribution map based on the 70% blockage risk evaluation value of Segment_2 pipe segment. The risk level conversion device calls the "buffer processing plan library" to generate the disposal instruction "enable low-frequency vibration device, amplitude parameter 3mm". Finally, the report generation device outputs a PDF report with geographic markers, the first page highlights the location of the No. 3 elbow pipe (coordinates x102, y205), and the second page provides vibration parameter operation guidelines to guide the precise implementation of unblocking operations by the operation and maintenance personnel.

[0085] To solve the problem of pressure distortion caused by the non-differential compensation of local resistance in the elbow area and the resistance along the straight pipe segment in the prior art, as an implementable embodiment, according to step 103, based on the geometric feature information, the pressure data is dynamically compensated to generate compensated pressure data, including:

[0086] Step 201, based on the bending angle, calculate the bending angle compensation value.

[0087] In this step, the bending angle compensation value refers to the bending pipe local resistance quantification parameter (unit: virtual resistance unit) calculated by the fluid mechanics model, which physically means the correction amount needed to eliminate the additional pressure loss caused by the bending angle.

[0088] In the embodiment, the angular resistance mapping calculation engine is implemented by first calling a preset angular resistance coefficient database (containing resistance benchmark values corresponding to different bending angles), and then using a nonlinear interpolation algorithm (such as cubic spline interpolation) to map the input bending angle to a corresponding bending angle compensation value.

[0089] Step 202, based on the length, the bending angle compensation value is proportionally adjusted to generate a comprehensive compensation parameter.

[0090] In this step, the comprehensive compensation parameter is a global correction factor (dimensionless coefficient) that integrates the length scale effect, which is used to expand the local bending resistance to an equivalent resistance compensation value of the whole pipe section.

[0091] In the embodiment, the pipeline resistance benchmark parameter (straight pipe unit length resistance standard value) is first loaded, and the unit length influence coefficient is obtained by querying the resistance influence factor mapping table according to the bending angle compensation value; then based on the length data, the unit influence coefficient is expanded along the pipeline length by continuous superposition calculation (such as segmented integration or accumulator algorithm) to generate a pipeline comprehensive resistance correction value as a comprehensive compensation parameter.

[0092] Step 203, applying the comprehensive compensation parameter to the pressure data to generate compensated pressure data.

[0093] In this step, the compensated pressure data is the purified pressure value (unit: MPa) obtained by eliminating the pipeline structure resistance distortion through the dynamic balance model, which directly reflects the real flow state.

[0094] In the embodiment, a closed-loop model containing a pressure balance unit (storing pressure data) and a resistance correction unit (receiving comprehensive compensation parameters) is first constructed; then the resistance correction unit is used to convert the comprehensive compensation parameters into a sequence of dynamic correction components (such as differential component pulses); then the iterative superposition algorithm (such as Newton iteration method) is used in the pressure balance unit to superimpose the components on the original pressure data in a loop until the fluid dynamic balance condition (such as the pressure gradient change rate < the set convergence threshold) is met; finally, the stable compensated pressure data is output.

[0095] In order to solve the problem that the resistance compensation mechanism in the prior art does not consider the nonlinear influence of the bending angle on the unit length resistance, as another embodiment, according to step 202, based on the length, the bending angle compensation value is proportionally adjusted to generate a comprehensive compensation parameter, including:

[0096] Step 301, obtaining a predefined pipeline resistance benchmark parameter.

[0097] In this step, the pipeline resistance benchmark parameter refers to the standard flat pipeline unit length fluid resistance constant calibrated by experiment (unit: resistance unit / meter), which has the physical meaning of the inherent resistance value per meter generated by the fluid flowing in the ideal straight pipe section, and is used to quantify the influence benchmark of other structural resistance.

[0098] In this embodiment, the system starts the resistance parameter loading module, accesses the "resistance benchmark library" stored in the SQLite database, and extracts the benchmark value matched with the current concrete rheological properties by using an index query algorithm such as B-tree index retrieval.

[0099] Step 302, according to the mapping relationship between the bending angle compensation value and the pipeline resistance benchmark parameter, the influence factor of bending angle on unit length is calculated.

[0100] In this step, the influence factor refers to the enhancement coefficient of bending angle compensation value on unit pipeline length resistance (dimensionless), and the quantitative formula is: influence factor=(bending angle compensation value / pipeline resistance benchmark parameter)×nonlinear correction coefficient, wherein the nonlinear correction coefficient is generated by the preset bending resistance mapping curve.

[0101] In this embodiment, first, the bending angle compensation value calculated in step 201 and the pipeline resistance benchmark parameter obtained in step 301 are received; a precompiled mapping function library (containing a segmented spline function set) is called to calculate the initial coefficient with the benchmark parameter as the denominator and the bending angle compensation value as the numerator; then the initial coefficient is nonlinearly adjusted through the correction coefficient table (storing the curvature correction weight of different bending angles), and finally the unit length influence factor is output.

[0102] Step 303, combine the bending angle influence factor on unit length with the length to generate the pipeline comprehensive resistance correction value through continuous superposition calculation.

[0103] In this step, continuous superposition calculation refers to the mathematical process of accumulating the unit influence factor along the length direction of the pipeline; and the pipeline comprehensive resistance correction value is the total correction amount output by the calculation (unit: resistance unit), which has the physical meaning of the resistance accumulation correction value caused by the bending of the entire pipe section.

[0104] In this embodiment, the influence factor (unit length resistance enhancement coefficient) generated in step 302 is called, combined with the input pipeline length data, and the segmented accumulation algorithm (such as the discrete integrator module) is used to perform continuous superposition operation. The specific process is as follows: after loading the influence factor value, the pipeline length is discretized into micro segments (such as virtual segment points), then the influence factor is applied to each micro segment for local resistance correction calculation, and then the local correction value is continuously summed by the accumulator, and the pipeline comprehensive resistance correction value is output when the integral covers the entire length.

[0105] Step 304, the pipeline comprehensive resistance correction value is taken as a comprehensive compensation parameter.

[0106] In this step, the comprehensive compensation parameter refers to a resistance compensation factor (unit: resistance unit) directly converted from the pipeline comprehensive resistance correction value, which is used to correct the original pressure data in the subsequent dynamic compensation model.

[0107] In this embodiment, the pipeline comprehensive resistance correction value generated by the receiving step 303 is directly assigned (without additional calculation) as the comprehensive compensation parameter and output to the downstream module.

[0108] In order to solve the problem of over-compensation caused by ignoring the dynamic balance characteristics of the fluid in the pressure compensation process in the prior art, as another embodiment, according to step 203, the comprehensive compensation parameter is applied to the pressure data to generate compensated pressure data, including:

[0109] Step 401, a dynamic balance model containing a pressure balance unit and a resistance correction unit is established.

[0110] In this step, the dynamic balance model refers to a digital simulation system constructed based on the Navier-Stokes equation of fluid mechanics, which is used to simulate the dynamic relationship between the pressure data and the structural resistance; the pressure balance unit is the calculation core, responsible for storing and iteratively processing the pressure data; the resistance correction unit is the correction module, dedicated to converting the comprehensive compensation parameter into a physical compensation amount, and the two form a closed-loop feedback mechanism through a data channel.

[0111] In this embodiment, first, a fluid dynamics simulation library (such as the OpenFOAM kernel) is called to initialize the model structure based on the geometric feature parameters of the pipeline, wherein the pressure balance unit is configured as a real-time pressure data container (stored using a double-precision floating-point array), and the resistance correction unit is designed as a compensation converter (with a built-in transfer function algorithm); second, a data exchange channel (such as a shared memory bus) between the two units is established, and an iterative control logic (with a gradient convergence threshold set) is configured; the core process is to allocate unit memory after loading the model kernel, then establish a bidirectional communication protocol, and finally complete the model initialization.

[0112] Step 402, the pressure data is input into the pressure balance unit.

[0113] In this embodiment, the system reads the pressure data stream (serialized data packet with timestamp) collected in real time by step 102, then checks the data integrity (CRC check), then unpacks the time sequence data, then sorts them by timestamp, and finally writes them to the specified memory address; when the last data packet is successfully written, the pending state identifier of the pressure balance unit is triggered.

[0114] Step 403, input the comprehensive compensation parameter into the resistance correction unit to generate a dynamic correction component.

[0115] In this step, the dynamic correction component refers to the instantaneous pressure correction sequence (unit: MPa) generated by the resistance correction unit, and the technical essence is the differential expression of the comprehensive compensation parameter in the fluid dynamics model, which is used to gradually eliminate the interference of structural resistance on the original pressure data.

[0116] In this embodiment, the resistance correction unit receives the comprehensive compensation parameter (scalar value), calls the internally preset differential equation solver (such as the Runge-Kutta method module), constructs the time-varying correction function based on the law of conservation of fluid momentum; and generates a dynamic correction component sequence (for example, outputs the component value at a millisecond level time step).

[0117] Step 404, performing a cyclic superposition operation on the pressure data and the dynamic correction component in the pressure balance unit.

[0118] In this step, the cyclic superposition operation refers to the iterative subtraction process of the time-stamped pressure data and the dynamic correction component, and the mathematical essence is to perform incremental compensation on the original pressure value sequence.

[0119] In this embodiment, the pressure balance unit loads the original pressure data sequence (with millisecond level time stamp), and performs clock synchronization matching (such as hash time stamp mapping) with the dynamic correction component sequence; then starts a loop counter, and performs a floating point subtraction operation (original pressure value minus correction component value at the corresponding time point) at each time point; updates the compensated pressure value in the storage area each time the loop is updated, and the result is used as the input of the next round.

[0120] Step 405, when the cyclic superposition result meets the preset fluid dynamic balance condition, output the compensated pressure data.

[0121] In this step, the fluid dynamic balance condition refers to the convergence criterion (based on the pressure gradient change rate) for judging whether the compensation is completed, and when the pressure gradient change value of continuous n iterations is less than the convergence threshold, it is determined that the system enters a stable state, and the balance condition is met.

[0122] In this embodiment, after each cyclic superposition, the gradient change amount of the current compensated pressure sequence (the absolute difference value of the results of the previous two iterations) is calculated; when the gradient change amount of continuous preset times (such as 3 times) is less than the convergence threshold (for example, 0.01 MPa / ms), a termination signal is triggered; finally, the current storage area data is frozen and the compensated pressure data is output.

[0123] To solve the problem that the single-parameter threshold method in the prior art cannot capture the precursor chain reaction of pipe blockage, as another embodiment, according to step 104, the blockage risk evaluation value in the current concrete conveying state is calculated in combination with the compensated pressure data and the flow rate data, including:

[0124] Step 501, extracting an abnormal pressure period characteristic value from the compensated pressure data.

[0125] In this step, the abnormal pressure period characteristic value refers to a set of non-continuous fluctuation characteristics in the compensated pressure data caused by blockage, including a pressure rise rate (unit: MPa / s) and a pressure fluctuation amplitude (unit: MPa), which are used to quantify the space-time characteristics of pressure mutation, and the technical essence is to exclude the real blockage signal expression after excluding the interference of the pipeline structure.

[0126] In this embodiment, first, wavelet denoising (Db4 wavelet basis function is selected) is performed on the compensated pressure data to eliminate environmental high-frequency noise; second, an adaptive sliding window (the window width is dynamically adjusted according to the concrete rheological characteristics) is used to scan the data stream, and if the pressure rise rate in the window exceeds the rate threshold value and the fluctuation amplitude continuously exceeds the amplitude tolerance, the abnormal period is marked; and finally, a period characteristic value structure (containing a start time stamp, a duration, a maximum rise rate, and a peak-to-peak value) is output.

[0127] Step 502, extracting a flow rate decay period characteristic value from the flow rate data.

[0128] In this step, the flow rate decay period characteristic value refers to a set of characteristic quantities of the continuous decrease of the concrete flow rate, including a flow rate inflection point time (time stamp), a decay slope (unit: m / s²), and a recovery threshold point (time when the flow rate rises to a preset ratio), and the physical meaning is to represent the dynamic process of flow obstruction.

[0129] In this embodiment, a first-order derivative operation is performed on the flow rate data to generate an acceleration sequence, and a zero-crossing detection algorithm is used to locate the flow rate inflection point (derivative changes from positive to negative); from the inflection point, the flow rate is tracked, and when the absolute value of the flow rate decline slope continuously exceeds the decay threshold value and continuously reaches the recovery threshold point (the point where the flow rate reaches 85% of the initial value), the decay period is marked; and finally, a characteristic value structure (inflection point time, decay slope, and recovery time) is output.

[0130] Step 503, detecting an overlap region of the abnormal pressure period characteristic value and the decay period characteristic value on the time axis.

[0131] In this step, the overlap region refers to the overlapping interval of the pressure main action area and the decay effective area on the time axis, and the technical essence is to confirm the physical reality of the blockage event through time sequence correlation to avoid false positives.

[0132] In this embodiment, the pressure main action area (pressure rise starting point to peak end point) extracted in step 501 and the attenuation effective area (flow rate inflection point to recovery point) extracted in step 502 are called; a time window is scanned with a step of 1 second, when the pressure main action area starting time is ahead of the attenuation effective area starting time and the time difference is less than or equal to a set threshold (such as 2 seconds), an effective overlap event is marked; the overlap duration and the overlap area ratio (overlap duration / pressure main action area duration) are calculated; and finally the overlap region object (starting time, ending time, duration, area ratio) is output.

[0133] Step 504, generating a blockage feature quantization value based on the duration and overlap degree of the overlap region.

[0134] In this step, the blockage feature quantization value is an intermediate value that converts the overlap space-time feature into a scalar risk indicator (range 0-1), and the calculation formula is: quantization value = duration weight x overlap duration + overlap weight x area ratio, and the weight coefficient is calibrated by experiment.

[0135] In this embodiment, a preset weight parameter library (such as duration weight 0.6, ratio weight 0.4) is loaded; the duration and area ratio of the overlap region object are called; and a weighted calculation is performed: quantization value = (0.6 x duration / max reference duration) + (0.4 x area ratio); wherein the maximum reference duration is dynamically adjusted according to the pipe length (such as 0.5 seconds per meter base); and finally the blockage feature quantization value is output.

[0136] Step 505, converting the blockage feature quantization value into a blockage risk evaluation value.

[0137] In this embodiment, the blockage feature quantization value is read; a Sigmoid function processor is called to calculate the conversion value: S(x) = 1 / (1+e^(-(10x-5))); and the result is multiplied by 100 to generate the blockage risk evaluation value.

[0138] In order to solve the problem of misidentification of overlap events caused by instantaneous pressure fluctuation and flow rate noise interference in the prior art, as another embodiment, according to step 503, detecting the overlap region of the abnormal pressure period feature value and the attenuation period feature value on the time axis, comprising:

[0139] Step 601, defining a pressure main action area of the abnormal pressure period feature value, wherein the pressure main action area covers the pressure rise stage and the peak duration stage.

[0140] In this step, the pressure main action zone refers to the core action period of abnormal pressure events, and its physical meaning is the core duration of blockage leading to pressure distortion, covering the pressure rising stage (the period when the pressure derivative is >0 and continuously increasing) and the peak duration stage (the period when the pressure is maintained at a threshold high position ≥80% of the peak value). This definition excludes the interference period of pressure drop and fluctuation noise.

[0141] In this embodiment, based on the compensated pressure data, the third derivative is first used to locate the pressure rising starting point (the position where the first derivative > the rising threshold appears for the first time); then the pressure peak point is locked through local extremum detection; and the peak point is scanned backward until the pressure value falls below 80% of the peak value for the first time to mark the end point.

[0142] Step 602, defining the decay effective zone of the flow rate decay period characteristic value, wherein the decay effective zone continues from the flow rate inflection point to the flow rate recovery threshold point.

[0143] In this step, the decay effective zone refers to the duration of substantial flow rate decline, which continues from the flow rate inflection point (the inflection point where the second derivative changes from positive to negative) to the flow rate recovery threshold point (the position where the flow rate rises to 85% of the baseline value before decay). This definition avoids the interference of normal flow rate fluctuations and temporary decline.

[0144] In this embodiment, the second derivative sequence of the flow rate is calculated, and the inflection point moment where the second derivative appears for the first time <0 is detected; the inflection point is tracked backward, and when the flow rate continuously falls below the baseline value before the inflection point, the recovery point is marked when it rises to 85% of the baseline value for the first time.

[0145] Step 603, capturing the time sequence coincidence state of the pressure main action zone and the decay effective zone through a sliding time window.

[0146] In this step, the sliding time window refers to a dynamic detection window that moves along the time axis (the window width can be configured), and its core function is to identify the spatiotemporal correlation between the two characteristic zones in continuous scanning; the time sequence coincidence state specifically refers to the partial or complete overlap phenomenon (i.e., the existence of a common time segment) between the pressure main action zone and the decay effective zone in the time dimension, which needs to meet the fluid dynamics causal relationship that the pressure fluctuation precedes the flow rate decay.

[0147] In this embodiment, the step is realized by a dynamic window scanning algorithm: the system first sets an initial sliding window based on the start time of the pressure main action area (the right boundary of the window is the start time plus a preset maximum delay tolerance), loads the pressure main action area time interval and the decay effective area time interval; during the window displacement process (the step size can be configured), when the start point of the pressure main action area is detected to be located within the current window, and the start point of the decay effective area is also present in the window, and the timing relationship that the start point of the pressure main action area precedes the start point of the decay effective area is satisfied, the overlapping length of the two intervals is calculated in real time (taking the minimum value of the two interval endpoints minus the maximum value of the start points); each window position that meets the condition is recorded as an effective event, and after the traversal is completed, the overlapping length and time difference of all events are aggregated as a timing coincidence state matrix output, forming a quantitative proof of the spatiotemporal correlation of the blockage event.

[0148] Step 604, when the start time of the pressure main action area precedes the decay effective area and the delay is less than a first set threshold, it is recorded as an effective overlapping event.

[0149] In this step, the effective overlapping event refers to a coincidence state recording unit that satisfies the strict fluid dynamics causal relationship (pressure fluctuation precedes flow rate decay) and excludes sensor errors, and its structure includes time difference (time difference between pressure start and flow rate decay) and overlapping segment core parameters (start point, duration, etc.). The first set threshold is a fault tolerance time difference upper limit set to eliminate sensor sampling delay or transmission jitter (usually the fluid transmission time + system error margin).

[0150] In this embodiment, the system first calls the pressure main action area start time stamp and the decay effective area start time stamp, and then calculates the time difference between the pressure main action area start time stamp and the decay effective area start time stamp; when both the time difference is greater than 0 (to ensure that the pressure fluctuation precedes) and the time difference is less than the first set threshold (to exclude non-causal delay), the event recorder is triggered to generate an effective overlapping event object (pressure start time, flow rate start time, time difference, overlapping period start and end points); the coincidence state that does not meet the condition is filtered and discarded, ensuring that only physically real blockage signals are retained in the event library.

[0151] Step 605, aggregate the duration and occurrence interval of all effective overlapping events to generate an overlapping region.

[0152] In this embodiment, the system first traverses the valid overlap event queue, extracts the time difference and duration parameters of each event; then calculates the dynamic weight based on the time difference (formula: weight = 1 / (1+Δt)), performs the duration weighted average calculation (∑(weight×duration) / ∑weight); at the same time, sort each event by timestamp, find the minimum value of the interval between adjacent event start times; finally, the first event start time, the last event end time, the weighted duration and the minimum interval value are integrated and output as a structured overlapping region.

[0153] In order to solve the problem that the pre-warning signal is disconnected with the space treatment in the prior art, resulting in a lag in the repair response, as another embodiment, according to step 105, a blockage risk assessment report is output according to the blockage risk evaluation value, including:

[0154] Step 701, constructing a pumping pipeline risk distribution map, wherein the pumping pipeline risk distribution map is associated with the geometric feature information of the concrete delivery pipeline.

[0155] In this step, the pumping pipeline risk distribution map is a visual digital model based on the spatial topology of the pipeline, the core of which is to map the pipeline geometric features (bend angle, length) into geometric structure elements (bend pipe is mapped into curvature radius, straight pipe is mapped into length vector) in the coordinate system, and mark the spatial position of the risk assessment result. The map realizes the accurate association of physical pipe sections and risk values through coordinate binding, solving the defect that the blockage section cannot be located in the background technology.

[0156] In this embodiment, the system calls the geometric feature information of the concrete delivery pipeline, converts the bend angle into a three-dimensional space curvature point array (90° bend pipe is mapped into a π / 2 radian arc) using a coordinate conversion algorithm (such as affine transformation), and converts the length data into a linear vector; a topology network graph based on the connection relationship of the pipeline (nodes are bend pipes / interfaces, edges are straight pipe sections) is constructed; the blockage risk evaluation value is injected into the corresponding pipe section topology node, and a dynamic and interactive risk distribution map is rendered by a color gradient algorithm (red = high risk, yellow = medium risk, blue = low risk).

[0157] Step 702, based on the numerical value of the blockage risk evaluation value, dividing emergency response events, buffer processing events and monitoring tracking events.

[0158] In this step, the emergency response event represents an extreme risk state that needs to be immediately interrupted and disposed, the buffer processing event refers to a critical risk state that allows short-term operation but requires intervention, and the monitoring tracking event represents a low risk state that only needs to be continuously observed; the three types of events are strictly divided by a dynamic threshold mechanism, and the threshold boundary is dynamically calibrated according to the concrete rheological characteristics.

[0159] In this embodiment, the step is realized by a complete flow of rheological property adaptive threshold segmentation engine: the system first calls the concrete property database (containing label, aggregate particle size parameters), matches the pre-set threshold rule library to activate the corresponding threshold group; then inputs the blockage risk evaluation value into the three-level judgment module, when the risk value exceeds the high-risk threshold, it is marked as an emergency response event (triggering immediate shutdown protocol), when it is between the moderate threshold and the high-risk threshold, it is marked as a buffer processing event (activating the buffer period intervention process), and when it is below the moderate threshold, it is marked as a monitoring tracking event (enabling low-priority monitoring).

[0160] Step 703, mapping the emergency response event to the first priority area of the pumping pipeline risk distribution map, mapping the buffer processing event to the second priority area of the pumping pipeline risk distribution map, and mapping the monitoring tracking event to the third priority area of the pumping pipeline risk distribution map.

[0161] In this step, the first priority area refers to the physical pipe segment coordinate set marked as the highest risk level in the risk distribution map (highlighted in red), which is used to locate the blockage point that needs to be disposed immediately; the second priority area is the medium-risk pipe segment coordinate set (yellow warning), which identifies the blockage area that allows buffer response; the third priority area is the low-risk pipe segment coordinate set (blue mark), which only needs to be continuously monitored. The three areas are accurately bound to specific pipeline positions through spatial coding, forming a closed-loop mapping from event level to spatial coordinates.

[0162] In this embodiment, the system first analyzes the three types of event objects divided in step 702, extracts their associated pipeline position identifiers (such as bend number or GPS coordinates); calls the pumping pipeline risk distribution map topology generated in step 701, and uses coordinate matching algorithm (such as K-D tree spatial index) to bind the emergency response event to the first priority area (write to the red alarm coordinate set), the buffer processing event to the second priority area (yellow warning coordinate set), and the monitoring tracking event to the third priority area (blue monitoring coordinate set); finally, update the visual rendering engine of the risk distribution map, so that the three color areas are dynamically superimposed on the pipeline geometric model, realizing real-time visual association of risk events and physical positions.

[0163] Step 704, generating multi-level disposal instructions corresponding to the first priority area, the second priority area and the third priority area through a risk level conversion device.

[0164] In this step, the risk level conversion device refers to an intelligent decision-making module with a built-in dredging strategy rule library, and its core function is to map priority areas to specific operation instructions; the multi-level disposal instruction is a set of dredging operation parameters customized according to the risk level.

[0165] In this embodiment, the preset multi-level treatment instruction library (including emergency response, buffer processing, and monitoring tracking three-level strategy templates) is loaded by the risk level conversion device, and a corresponding template is called according to an input area type; for a first priority area, a high-pressure backwashing template is matched and a position coordinate is injected to generate a specific parameter (such as performing 20 MPa backwashing at a coordinate (x305, y418)); for a second priority area, a low-frequency vibration template is activated to generate a vibration parameter (such as 2 Hz ± 0.5 amplitude); for a third priority area, a flow rate monitoring template is called to set a patrol frequency (such as 5 seconds / second sampling); and finally, multi-level treatment instructions with position binding are output.

[0166] In step 705, the pumping pipeline risk distribution map and the multi-level treatment instruction are synthesized by the report generation device to generate a blockage risk assessment report with position marking.

[0167] In this step, the report generation device refers to an automated system integrating spatial data fusion and document rendering engine.

[0168] In this embodiment, the system first calls the pumping pipeline risk distribution map (including spatial vector data of three-color priority areas) and the multi-level treatment instruction set; a coordinate alignment algorithm is used to accurately match the position parameters in the instruction with the spatial elements of the risk distribution map (such as K-D tree index association coordinates and instructions); then the risk distribution map is converted into an interactive vector layer through the document rendering engine, and operation labels are embedded at the corresponding coordinate positions of the multi-level treatment instructions (such as backwashing parameters marked beside the red area); finally, a report entity is generated through a PDF / HTML synthesizer, in which the position marking uses a two-dimensional code or a hyperlink to bind the coordinate navigation function, forming a blockage risk assessment report that can directly hit the blockage point.

[0169] Figure 2 A structural schematic diagram of a concrete delivery pipeline blockage risk dynamic evaluation system is provided for the present application, as shown in Figure 2 The system comprises:

[0170] An acquisition module 21 is configured to acquire geometric feature information of a concrete delivery pipeline, wherein the geometric feature information includes bending angles and lengths.

[0171] An acquisition module 22 is configured to acquire pressure data and flow rate data in the concrete delivery pipeline in real time during the concrete delivery process.

[0172] A processing module 23 is configured to perform dynamic compensation processing on the pressure data based on the geometric feature information to generate compensated pressure data.

[0173] A calculation module 24 is configured to calculate a blockage risk evaluation value in a current concrete delivery state in combination with the compensated pressure data and the flow rate data.

[0174] The output module 25 is configured to output a blockage risk assessment report according to the blockage risk evaluation value.

[0175] Figure 2 The concrete delivery pipeline blockage risk dynamic assessment system can perform Figure 1 The concrete delivery pipeline blockage risk dynamic assessment method of the embodiment can achieve the above technical effects. The specific implementation of the operation of each module and unit of the concrete delivery pipeline blockage risk dynamic assessment system in the above embodiment has been described in detail in the embodiment of the method, and will not be described in detail here.

[0176] In one possible design, Figure 2 The concrete delivery pipeline blockage risk dynamic assessment system of the embodiment can be implemented as a computing device, such as a computer. Figure 3 As shown in the figure, the computing device can include a storage component 31 and a processing component 32.

[0177] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32.

[0178] The processing component 32 is configured to perform the above Figure 1 The concrete delivery pipeline blockage risk dynamic assessment method of the embodiment.

[0179] The processing component 32 can include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component can also be one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components, for executing the above method.

[0180] The storage component 31 is configured to store various types of data to support the operation of the terminal. The storage component can be realized by any type of volatile or non-volatile storage device or their combination, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0181] Of course, the computing device can also include other components, such as input / output interface, display component, communication component, etc.

[0182] The input / output interface provides an interface between the processing component and peripheral interface modules, which can be output devices, input devices, and the like.

[0183] The communication component is configured to facilitate wired or wireless communication between the computing device and other devices, and the like.

[0184] The computing device can be a physical device or an elastic computing host provided by a cloud computing platform, and the processing component, the storage component, and the like can be basic server resources rented or purchased from the cloud computing platform.

[0185] The embodiment of the application further provides a computer storage medium storing a computer program, and the computer program can implement the above-mentioned method when executed by a computer. Figure 1 The embodiment shown in the figure is a concrete pipe blockage risk dynamic evaluation method.

[0186] Those skilled in the art can clearly understand the specific working process of the system, device and unit described above for the convenience and brevity of description, and the corresponding process in the foregoing method embodiments can be referred to, which will not be described here.

[0187] The device embodiments described above are only schematic, and the units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment scheme according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0188] From the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software and necessary general hardware platforms, and of course, can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of software products, and the computer software product can be stored in a computer readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including a plurality of instructions to make a computer device (which can be a personal computer, server, or network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0189] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present application, and are not intended to limit the same; although the present application has been described in detail with reference to the foregoing examples, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for dynamic assessment of blockage risk of concrete delivery pipeline, characterized in that: include: Acquiring geometric characteristic information of the concrete delivery pipeline, wherein the geometric characteristic information includes a bending angle and a length; During the concrete delivery process, real-time collection of pressure data and flow rate data in the concrete delivery pipeline; Based on the geometric feature information, dynamically compensating the pressure data to generate compensated pressure data; Calculating a blockage risk assessment value under a current concrete delivery state by combining the compensated pressure data and the flow rate data; Outputting a congestion risk assessment report according to the congestion risk evaluation value; The step of dynamically compensating the pressure data based on the geometric feature information to generate compensated pressure data includes: Calculating a bending angle compensation value based on the bending angle, wherein the bending angle compensation value refers to a quantitative parameter of the local resistance of the bend calculated by a fluid mechanics model, and the physical meaning of the bending angle compensation value is the correction amount required to eliminate the additional pressure loss caused by the bending angle; Based on the length, proportionally adjusting the bending angle compensation value to generate a comprehensive compensation parameter; applying the comprehensive compensation parameters to the pressure data to generate compensated pressure data; The step of proportionally adjusting the bending angle compensation value based on the length to generate a comprehensive compensation parameter includes: Obtain predefined pipeline resistance benchmark parameters; Calculating the influence factor of the bending angle on the unit length according to the mapping relationship between the bending angle compensation value and the pipeline resistance reference parameter, wherein the influence factor refers to the enhancement coefficient of the bending angle compensation value on the resistance per unit length of the pipeline; The influence factor of the bending angle on the unit length is combined with the length, and a correction value of the pipeline comprehensive resistance is generated by continuous superposition calculation; The pipeline comprehensive resistance correction value is used as a comprehensive compensation parameter.

2. The method according to claim 1, characterized in that Applying the comprehensive compensation parameter to the pressure data to generate compensated pressure data includes: Establish a dynamic balance model including a pressure balance unit and a resistance correction unit; inputting the pressure data into the pressure balancing unit; Inputting the comprehensive compensation parameter into the resistance correction unit to generate a dynamic correction component; performing a cyclic superposition operation on the pressure data and the dynamic correction component in the pressure balance unit; When the cyclic superposition result meets the preset fluid dynamic balance condition, the compensated pressure data is output.

3. The method according to claim 1, characterized in that Calculating a blockage risk assessment value under the current concrete delivery state by combining the compensated pressure data and the flow rate data includes: extracting abnormal pressure period characteristic values ​​from the compensated pressure data; extracting a flow velocity decay period characteristic value from the flow velocity data; Detecting an overlapping area on a time axis between the characteristic value of the abnormal pressure period and the characteristic value of the decay period; generating a blockage characteristic quantification value based on the duration and degree of overlap of the overlapping region; The blockage characteristic quantification value is converted into a blockage risk assessment value.

4. The method according to claim 3, characterized in that Detecting an overlapping area between the characteristic value of the abnormal pressure period and the characteristic value of the decay period on a time axis includes: Defining a main pressure action area of ​​the characteristic value of the abnormal pressure period, wherein the main pressure action area covers the pressure rising stage and the peak duration stage; Defining an effective attenuation region of the characteristic value of the flow velocity attenuation period, wherein the effective attenuation region extends from the flow velocity inflection point to the flow velocity recovery threshold point; Capturing the temporal overlap state of the pressure main action area and the attenuation effective area through a sliding time window; When the start time of the pressure main action area is ahead of the attenuation effective area and the delay is less than a first set threshold, it is recorded as a valid overlap event; Aggregate the duration and occurrence intervals of all valid overlapping events to generate the overlapping area.

5. The method according to claim 1, wherein Output a congestion risk assessment report based on the congestion risk evaluation value, including: Constructing a pumping pipeline risk distribution map, wherein the pumping pipeline risk distribution map is associated with geometric feature information of the concrete delivery pipeline; Based on the numerical value of the congestion risk assessment value, the emergency response events, the buffer processing events and the monitoring and tracking events are divided; Mapping the emergency response event to a first priority area of ​​the pumping pipeline risk distribution map, mapping the buffer processing event to a second priority area of ​​the pumping pipeline risk distribution map, and mapping the monitoring and tracking event to a third priority area of ​​the pumping pipeline risk distribution map; Generate multi-level handling instructions corresponding to the first priority area, the second priority area, and the third priority area through a risk level conversion device; The pumping pipeline risk distribution map and the multi-level disposal instructions are synthesized by using a report generating device to generate a blockage risk assessment report with position marks.

6. A concrete delivery pipeline blockage risk dynamic assessment system, applied to a concrete delivery pipeline blockage risk dynamic assessment method according to any one of claims 1 to 5, characterized in that: include: An acquisition module, configured to acquire geometric feature information of the concrete delivery pipe, wherein the geometric feature information includes a bending angle and a length; The acquisition module is used to collect the pressure data and flow rate data in the concrete delivery pipeline in real time during the concrete delivery process; a processing module, configured to perform dynamic compensation processing on the pressure data based on the geometric feature information to generate compensated pressure data; a calculation module, configured to calculate a blockage risk assessment value under a current concrete delivery state by combining the compensated pressure data and the flow rate data; The output module is used to output a congestion risk assessment report according to the congestion risk evaluation value.

7. A computing device, characterized in that The method comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a dynamic assessment method for blockage risk of a concrete delivery pipeline as described in any one of claims 1 to 5.

8. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, a dynamic assessment method for blockage risk of a concrete delivery pipeline according to any one of claims 1 to 5 is implemented.

Images