CN-122015020-A - Method and system for early warning health state of long-distance heat supply pipeline

CN122015020ACN 122015020 ACN122015020 ACN 122015020ACN-122015020-A

Abstract

The invention belongs to the technical field of pipeline state monitoring, in particular to a method and a system for early warning the health state of a long-distance heat supply pipeline, which are used for acquiring and storing distributed optical fiber temperature measurement data, point type sensor monitoring data and environmental air temperature data along the pipeline to form a historical data chain with a time stamp and a position index; dividing monitoring subareas by using adjacent point sensors as boundaries, comparing actual temperature drop with design allowable temperature drop, judging the subareas as abnormal subareas if deviation exceeds standard, subdividing the abnormal subareas into monitoring points by using optical fiber resolution, searching a historical similar optical fiber temperature data set S by taking a current working condition as a condition, calculating a temperature difference delta T between the current optical fiber temperature and an S mean value, grading health states according to at least two preset temperature difference thresholds, and outputting early warning. The problems of large monitoring blind area and inaccurate positioning in the prior art are solved, and accurate identification and grading early warning of local failure points of the pipeline heat preservation layer are realized.

Inventors

NI FENGYAO
KONG DEBIN
DONG PING
DU HUANFENG
YANG CUIWEI

Assignees

山东东宏管业股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260305

Claims (10)

1. The method for early warning the health state of the long-distance heat supply pipeline is characterized by comprising the following steps of: Acquiring and storing distributed optical fiber temperature measurement data, point sensor monitoring data and environmental air temperature data along the pipeline, and adding a time stamp and a position coordinate index to each piece of data to form a data chain containing historical working conditions, wherein the point sensor monitoring data at least comprises medium temperature data and medium flow data; Dividing a pipeline into N monitoring subareas by using adjacent point type temperature sensors as boundaries, calculating actual temperature drop according to medium temperatures of point type sensors on the upstream and downstream of each subarea, and comparing the actual temperature drop with design allowable temperature drop; In the temperature drop abnormal partition, subdividing the partition into M monitoring points by utilizing the resolution of distributed optical fiber temperature measurement data, and aiming at any abnormal point in the partition, taking the current medium temperature in the pipe, the environment temperature and the flow as matching conditions, and retrieving an optical fiber monitoring temperature data set S under the history similar working condition from a database; and calculating the temperature difference delta T between the current optical fiber monitoring temperature of the abnormal point location and the average value of the optical fiber monitoring temperatures in the historical similar data set S, classifying the health state of the abnormal point location according to the preset at least two-stage temperature difference threshold value, and outputting corresponding early warning information.
2. The method for early warning the health state of a long-distance heat supply pipeline according to claim 1, wherein during the formation of a data chain, protocol conversion and acquisition of the distributed optical fiber temperature measurement system, the point sensor and the weather table data are carried out through a unified data standardization switching interface, and the GPS/Beidou time service and pipeline length punctuation are used as double indexes to carry out time-space alignment on the distributed optical fiber temperature measurement data, the point sensor monitoring data and the environmental air temperature data, so that clock deviation among multiple source data is eliminated.
3. The method for early warning the health state of a long-distance heat supply pipeline according to claim 2, wherein the clock bias is eliminated, specifically: Selecting weather station data with GPS/Beidou time service as a UTC reference source, calculating the acquisition time difference between each sensor and the weather data, and establishing a synchronous model; Performing time offset compensation on the high-frequency sensor data by adopting a sliding window averaging method, and matching the low-frequency data to a unified time axis by adopting linear interpolation; a clock drift monitoring threshold is set, and resynchronization is automatically triggered when the deviation exceeds a set value.
4. The method for early warning the health state of a long-distance heat supply pipeline according to claim 1, wherein in the process of comparing the actual temperature drop with the design allowable temperature drop, extreme deviation correction is carried out on the actual temperature drop through the monitoring precision of the sensor, and deviation calculation is carried out on the corrected numerical value and the design allowable temperature drop; The design permission temperature drop is calculated according to the pipeline length, the medium temperature and the heat preservation layer structure parameter and the thermodynamic model.
5. The method for early warning the health state of a long-distance heat supply pipeline according to claim 1, wherein the current medium temperature in the pipeline, the environment temperature and the flow are used as matching conditions, and the optical fiber monitoring temperature data set S under the history similar working condition is retrieved from a database, specifically: Retrieving a historical data chain meeting set conditions, and extracting corresponding optical fiber monitoring temperature data to form a data set S; The setting conditions are as follows: The current medium temperature and the historical medium temperature are less than or equal to a first temperature threshold value; the current environmental temperature and the historical environmental temperature are less than or equal to a second temperature threshold value; The current flow and the historical flow are less than or equal to the flow threshold.
6. The method for early warning of health status of a long-distance heat supply pipeline according to claim 1, wherein the preset at least two-stage temperature difference threshold comprises a first temperature difference threshold value θ1, a second temperature difference threshold value θ2 and a third temperature difference threshold value θ3, and θ1< θ2< θ3; the abnormal point positions are classified in health state according to the temperature difference delta T and corresponding early warning information is output, and the method specifically comprises the following steps: if the theta 1 is less than or equal to delta T < theta 2, judging that the system is slightly abnormal, recording and recording a record and prompting important detection in the next monitoring period; if theta 2 is less than or equal to delta T < theta 3, judging that the system is moderate abnormal, pushing visual alarm information and connecting the visual alarm information with a video monitoring confirmation state; if the delta T is more than or equal to theta 3, judging that the temperature is seriously abnormal or the thermal insulation function is suspected to be invalid, and triggering a high-priority inspection plan.
7. The method for early warning the health state of a long-distance heat supply pipeline according to claim 1, wherein the first temperature difference threshold value theta 1 is set according to the monitoring sensitivity of the point sensor, the third temperature difference threshold value theta 3 is set according to the medium temperature in the pipeline, and the insulation structure is judged to be basically invalid when the monitoring temperature of the optical fiber approaches to the medium temperature within +/-5 ℃ in the pipeline.
8. The method for early warning the health state of a long-distance heat supply pipeline according to claim 1, wherein the health state classification further introduces a annual aging rate alpha of a pipeline heat insulation material to dynamically correct a temperature difference threshold value, and the annual aging rate alpha is predicted based on a annual relative increment rate of heat dissipation loss according to the following formula: Δqt=q(t)-q(t-1)≈q 0 ·(1+α)^(t-1)·α; Wherein q (t) is steady-state heat dissipation loss of the pipeline in the t-th year, q 0 is initial heat dissipation loss, t is the operation year number of the pipeline, and alpha is the aging rate of the heat conductivity coefficient of the heat insulation material.
9. The method for early warning the health state of a long-distance heat supply pipeline according to claim 1 is characterized by further acquiring vibration data monitored by a distributed optical fiber, and when abnormal increase of the vibration amplitude is monitored, superposing and judging the risk of external mechanical damage by combining with a health state grading result, and triggering corresponding early warning.
10. The long-distance heat supply pipeline health state early warning system is used for realizing the long-distance heat supply pipeline health state early warning method as claimed in claim 1, and is characterized by comprising the following steps: the multi-source data acquisition module is configured to acquire distributed optical fiber temperature measurement data, point sensor monitoring data and environmental air temperature data along the pipeline; The database module is configured to add a time stamp and a position coordinate index to each piece of received data and store the time stamp and the position coordinate index to form a data chain containing history working conditions; Dividing a pipeline into N monitoring subareas by taking adjacent point type temperature sensors as boundaries, calculating actual temperature drop according to medium temperatures of point type sensors on the upstream and downstream of each subarea, and comparing the actual temperature drop with design allowable temperature drop; The abnormal point location and retrieval module is configured to subdivide a temperature drop abnormal partition into M monitoring points by utilizing the resolution of distributed optical fiber temperature measurement data; aiming at any abnormal point in the optical fiber monitoring temperature data set S under the similar historical working condition is retrieved from the database module by taking the current medium temperature in the pipe, the environment temperature and the flow as matching conditions; The grading early warning module is configured to calculate the temperature difference delta T between the current optical fiber monitoring temperature of the abnormal point and the optical fiber monitoring temperature average value in the historical similar data set S, grade the health state of the abnormal point according to the preset at least two-stage temperature difference threshold value, and output corresponding early warning information.

Description

Method and system for early warning health state of long-distance heat supply pipeline Technical Field The invention belongs to the technical field of pipeline state monitoring, and particularly relates to a method and a system for early warning of the health state of a long-distance transmission heat supply pipeline. Background The statements in this section merely mention background of the present disclosure and do not necessarily constitute prior art. The long-distance heat supply pipeline is the aorta of the urban central heating system, and the safe and stable operation is important. The prefabricated directly buried polyurethane heat-insulating pipeline is widely applied to long-distance heat supply engineering due to good heat-insulating performance and mechanical strength. However, in a long-term service environment with high temperature, high humidity and complex load, the polyurethane heat-insulating layer is easy to age, carbonize and even fall off, so that the heat-insulating effect is reduced, huge heat loss is caused, and safety accidents are also caused by local overheating or stress concentration of the working steel pipe in severe cases. Therefore, on-line monitoring and early warning of the health state of the pipeline heat preservation layer become key requirements for guaranteeing the safety of a heat supply pipe network and realizing intelligent operation and maintenance. At present, monitoring of long-distance heat supply pipelines mainly depends on point sensors installed on heat exchange stations, relay pump stations and key nodes, and abnormal conditions of the pipelines are determined by monitoring parameters such as temperature, pressure and flow of media. The tubing anomaly may also be determined by continuously monitoring the temperature and strain along the tubing through a distributed optical fiber. However, the arrangement of the point sensors has a spacing distance, and a large number of monitoring blind areas exist only by relying on sparse point sensors. Even if the optical fiber data are combined, an effective linkage analysis mechanism is lacking, and a specific microscopic damage point cannot be accurately positioned after the macroscopic temperature drop abnormality is found. Disclosure of Invention The invention provides a method and a system for early warning the health state of a long-distance heat supply pipeline, which solve the problem that in the prior art, accurate identification and positioning of local heat preservation failure points of the pipeline cannot be performed due to sparse sensor arrangement and data fracture. The first aspect of the invention discloses a long-distance heat supply pipeline health state early warning method, which comprises the following steps: Acquiring and storing distributed optical fiber temperature measurement data, point sensor monitoring data and environmental air temperature data along the pipeline, and adding a time stamp and a position coordinate index to each piece of data to form a data chain containing historical working conditions, wherein the point sensor monitoring data at least comprises medium temperature data and medium flow data; Dividing a pipeline into N monitoring subareas by using adjacent point type temperature sensors as boundaries, calculating actual temperature drop according to medium temperatures of point type sensors on the upstream and downstream of each subarea, and comparing the actual temperature drop with design allowable temperature drop; In the temperature drop abnormal partition, subdividing the partition into M monitoring points by utilizing the resolution of distributed optical fiber temperature measurement data, and aiming at any abnormal point in the partition, taking the current medium temperature in the pipe, the environment temperature and the flow as matching conditions, and retrieving an optical fiber monitoring temperature data set S under the history similar working condition from a database; and calculating the temperature difference delta T between the current optical fiber monitoring temperature of the abnormal point location and the average value of the optical fiber monitoring temperatures in the historical similar data set S, classifying the health state of the abnormal point location according to the preset at least two-stage temperature difference threshold value, and outputting corresponding early warning information. Furthermore, during the formation of a data chain, protocol conversion and acquisition are carried out on the distributed optical fiber temperature measurement system, the point type sensor and the weather table data through a unified data standardization switching interface, and the GPS/Beidou time service and pipeline length punctuation are used as double indexes to carry out time-space alignment on the distributed optical fiber temperature measurement data, the point type sensor monitoring data and the environmental air temperature data, so that clock deviat