CN113313033A - Heat supply pipe network digital monitoring system based on sensor of Internet of things - Google Patents
Heat supply pipe network digital monitoring system based on sensor of Internet of things Download PDFInfo
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Abstract
The invention discloses a heat supply pipe network digital monitoring system based on an internet of things sensor, wherein the wireless transmission system comprises a pipeline section dividing and setting module, a data acquisition and uploading module and a data analysis and judgment module, the pipeline section dividing and setting module divides a heat supply pipeline into a plurality of pipeline sections with equal length in advance, each pipeline section is provided with a pressure sensor and a temperature sensor, the heat supply pipeline comprises a pipeline layer, a heat insulation layer and a protective layer, the pressure sensors are arranged on the pipeline layers of the pipeline sections, the temperature sensors are arranged on the heat insulation layers of the pipeline sections, the data acquisition and uploading module is used for acquiring state data of the pipeline sections and uploading the state data to a cloud platform, and the data analysis and judgment module is used for judging whether the heat supply pipeline leaks or not according to data detected by the pressure sensors and the temperature sensors.
Description
Technical Field
The invention relates to the technical field of heat supply pipe networks, in particular to a heat supply pipe network digital monitoring system based on an internet of things sensor.
Background
The heat supply pipeline is a pipeline for transmitting heat, and a plurality of heat supply pipelines are connected to form a heat supply pipe network. The heat supply pipeline generally has the pipeline layer, heat preservation and inoxidizing coating constitute, heating power circulates in the pipeline, the heat preservation is arranged in preventing the heat loss in the pipeline layer, the inoxidizing coating plays protective pipe's effect, reduce the external destruction corruption to the pipeline, among the prior art, generally all maintain after detecting heat supply pipeline existence leakage, but when maintaining again after leaking, can influence user's heat supply in service behavior, the life on pipeline layer is also relatively short.
Disclosure of Invention
The invention aims to provide a heat supply pipe network digital monitoring system based on an internet of things sensor, and aims to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a heat supply pipe network digital monitoring system based on an Internet of things sensor comprises a pipeline section dividing and setting module, a data acquisition and uploading module and a data analysis and judgment module, wherein the pipeline section dividing and setting module divides a heat supply pipeline into a plurality of pipeline sections with equal length in advance, each pipeline section is provided with a pressure sensor and a temperature sensor, the heat supply pipeline comprises a pipeline layer, a heat preservation layer and a protective layer, the pressure sensors are arranged on the pipeline layers of the pipeline sections, the temperature sensors are arranged on the heat preservation layers of the pipeline sections, the data acquisition and uploading module is used for acquiring state data of the pipeline sections and uploading the state data to a cloud platform, the data analysis and judgment module is used for judging whether the heat supply pipeline has leakage according to the data detected by the pressure sensors and the temperature sensors, and when the leakage exists, the corresponding pipeline sections are overhauled, when leakage does not exist, the corresponding pipeline section is selected as the section to be analyzed, image information of the section to be analyzed is collected, and whether maintenance repair needs to be carried out on the heat supply pipeline is analyzed and judged.
Further, the data analyzing and judging module comprises an in-doubt section selecting module, a temperature data analyzing module, a position reference index calculating module, a first similarity obtaining module, a second similarity obtaining module, a comprehensive evaluation parameter calculating module, a comprehensive evaluation parameter comparing module and a section to be analyzed analyzing module, wherein the in-doubt section selecting module collects data P detected by a temperature sensor of a pipeline section when detecting that data detected by the pressure sensor of the pipeline section is smaller than a pressure threshold value, and when the data P detected by the temperature sensor is larger than the temperature threshold value, the pipeline section is set as the in-doubt section, the temperature data analyzing module sequentially obtains detection data O1, O2, … and Om of the temperature sensors of m pipeline sections at the upstream of the in-doubt section and detection data R1, R2, … and Rn of the temperature sensors of n pipeline sections at the downstream of the in-doubt section, and calculates Ji as Oi-P, Kj-Rj-P, where i is 1 to m, J is 1 to n, the position reference index calculation module is configured to calculate a position reference index S1-U1/U2, U1 is a smaller one of J1 and K1, and U2 is a larger one of J1 and K1, the first similarity acquisition module obtains a first sequence from the upstream pipeline segments in a sequence from Ji to Ji, compares the first sequence with a sequence in a direction of upstream pipeline segments of a suspected segment to obtain a first similarity Sx, the second similarity acquisition module obtains a second sequence from the downstream pipeline segments in a sequence from Ki to Ki, compares the second sequence with a sequence in a direction of downstream pipeline segments of the suspected segment to obtain a second similarity Sy, and the comprehensive evaluation parameter calculation module obtains the second similarity Sy from the position reference index S1, and calculates a position reference index S1/U2, where U1 is a smaller one of J1 and K1, and U2 is a larger one of J1 and K1 And the comprehensive evaluation parameter comparison module compares the comprehensive evaluation parameter with a comprehensive evaluation threshold value, if the comprehensive evaluation parameter is greater than or equal to the comprehensive evaluation threshold value, the heat supply pipeline segment is judged to have leakage, the heat supply pipeline segment and the neighborhood thereof are overhauled by transmission information, if the comprehensive evaluation parameter is smaller than the comprehensive evaluation threshold value, the heat supply pipeline segment is judged not to have leakage, a segment to be analyzed with the suspected pipeline as the center and within a certain range is divided, and the segment to be analyzed analysis module analyzes and judges whether to perform maintenance repair on the corresponding pipeline segment.
Further, the analysis module of the section to be analyzed comprises an image acquisition processing module, a judgment module, a first processing module and a second processing module, wherein the image acquisition processing module acquires image information of the section to be analyzed and performs binarization processing on the image information to obtain a crack curve on the section to be analyzed, the judgment module is used for judging whether a certain crack curve is a closed curve or not, when the crack curve is judged to be the closed curve, the first processing module is used for performing analysis judgment, when the crack curve is judged not to be the closed curve, the second processing module is used for performing analysis judgment, the first processing module comprises an area acquisition module and an area comparison module, the area acquisition module is used for acquiring the area of the closed curve on the image of the section to be analyzed, and the area comparison module compares the acquired area of the area acquisition module with an area threshold value, and when the area is larger than or equal to the area threshold value, transmitting information to maintain and repair the pipeline section where the fracture curve is located.
Further, the second determination module includes a first reference line obtaining module, a second reference line obtaining module, an influence reference value calculating module and an influence reference value comparing module, the first reference line obtaining module obtains that a connection line between two end points of the fracture curve is a first reference line, the second reference line obtaining module obtains lengths of vertical lines from each point on the fracture curve to the first reference line, the lengths of the vertical lines are in descending order, a first vertical line is selected as a second reference line, the influence reference value calculating module calculates an influence reference value H of the fracture curve as Ls/Ws + Lr/Wr, wherein Ls and Lr are lengths of the first reference line and the second reference line of the fracture curve respectively, Ws and Wr are a first reference line threshold value and a second reference line threshold value respectively, and the influence reference value comparing module compares the influence reference value with the influence reference threshold value, and when the influence reference value is greater than or equal to the influence reference threshold value, transmitting information to maintain and repair the pipeline section where the fracture curve is located.
Further, the monitoring system further includes a monitoring method, and the monitoring method includes:
dividing a heat supply pipeline into a plurality of pipeline sections with equal length in advance, wherein each pipeline section is provided with a pressure sensor and a temperature sensor, the heat supply pipeline comprises a pipeline layer, a heat preservation layer and a protective layer, the pressure sensors are arranged on the pipeline layers of the pipeline sections, and the temperature sensors are arranged on the heat preservation layers of the pipeline sections;
collecting state data of each pipeline segment, uploading the state data to a cloud platform, analyzing the corresponding state data, judging whether the heat supply pipeline has leakage or not,
if there is a leak, the corresponding pipe section is serviced,
if no leakage exists, selecting the corresponding pipeline segment as the segment to be analyzed, collecting the image information of the segment to be analyzed, and analyzing and judging whether to maintain and repair the heat supply pipeline.
Further, the analyzing the corresponding state data includes:
if the data detected by the pressure sensor of a certain pipeline section is detected to be smaller than the pressure threshold value, the data P detected by the temperature sensor of the pipeline section is collected, when the data P detected by the temperature sensor is larger than the temperature threshold value, the pipeline section is set as a suspicious section,
sequentially acquiring detection data O1, O2, … and Om of temperature sensors of m pipeline sections at the upstream of the suspected section and detection data R1, R2, … and Rn of temperature sensors of n pipeline sections at the downstream, calculating Ji-Oi-P, Kj-Rj-P, wherein the value of i is 1 to m, and the value of J is 1 to n, and then a position reference index S1 is U1/U2, wherein U1 is the smaller one of J1 and K1, and U2 is the larger one of J1 and K1;
obtaining a first sequence of the upstream pipeline sections according to the sequence from small to large of Ji, comparing the first sequence with the sequence of the suspected section towards the upstream pipeline sections in the direction to obtain a first similarity Sx, obtaining a second sequence of the downstream pipeline sections according to the sequence from small to large of Ki, comparing the second sequence with the sequence of the suspected pipeline towards the downstream pipeline sections in the direction to obtain a second similarity Sy,
then the overall evaluation parameter Sz is 0.12S 1+ c Sx + d Sy, where c + d is 0.88, c, d are fractions between 0 and 1,
if the comprehensive evaluation parameter is more than or equal to the comprehensive evaluation threshold value, judging that the heat supply pipeline segment has leakage, and overhauling the suspected segment and the vicinity of the suspected segment;
and if the comprehensive evaluation parameter is smaller than the comprehensive evaluation threshold value, judging that the heat supply pipeline segment has no leakage, and dividing the pipeline segment to be analyzed within a certain range by taking the suspected pipeline as the center.
Further, the analyzing and determining whether to perform maintenance repair includes the following steps:
collecting the image information of the section to be analyzed, carrying out binarization processing on the image information to obtain a crack curve on the section to be analyzed,
judging whether a certain crack curve is a closed curve, if so, acquiring the area of the closed curve on the image of the section to be analyzed, and transmitting information to maintain and repair the pipeline section where the crack curve is located when the area is larger than or equal to an area threshold;
if the fracture curve is not a closed curve, acquiring a connecting line between two end points of the fracture curve as a first reference line, acquiring the length of a vertical line from each point on the fracture curve to the first reference line, selecting the first vertical line as a second reference line according to the length of the vertical line from big to small,
calculating an influence reference value H of the fracture curve, wherein Ls and Lr are the length of a first reference line and the length of a second reference line of the fracture curve respectively, and Ws and Wr are a first reference line threshold value and a second reference line threshold value respectively;
and when the influence reference value is greater than or equal to the influence reference threshold value, the transmission information carries out maintenance and repair on the pipeline section where the fracture curve is located.
Further, the analyzing the corresponding state data further includes:
sequentially acquiring detection data of the temperature sensors of the pipeline sections along the direction of each pipeline section upstream of the suspected pipeline, and when the a-th sensor is detected, if J (a +1) -Ja is smaller than or equal to a reference threshold value and Ja-J (a-1) is larger than the reference threshold value, then m is equal to a;
and sequentially acquiring detection data of the temperature sensors of the pipeline sections along the direction of each pipeline section downstream from the suspected pipeline, and when a b-th sensor is detected, if K (b +1) -Kb is less than or equal to a reference threshold value and Kb-K (b-1) is greater than the reference threshold value, n-b.
Further, the analyzing the corresponding state data further includes:
c＝m/(m+n)*0.88，d＝0.88-c。
compared with the prior art, the invention has the following beneficial effects: according to the invention, through analyzing the pressure data and the temperature data of the heat supply pipeline, when the heat supply pipeline is analyzed and judged to have leakage, the transmission information is used for overhauling the heat supply pipeline, when the heat supply pipeline is analyzed and judged to have no leakage, the heat supply pipeline is checked, whether maintenance and repair are needed to be carried out on the heat supply pipeline is judged, when the heat insulation layer and the protective layer of the heat supply pipeline have damage with large influence, the maintenance and repair are carried out in time, the working efficiency of the heat supply pipeline is improved, and the service life of the heat supply pipeline is prolonged.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic block diagram of a heat supply pipe network digital monitoring system based on an internet of things sensor.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides a technical solution: a heat supply pipe network digital monitoring system based on an Internet of things sensor comprises a pipeline section dividing and setting module, a data acquisition and uploading module and a data analysis and judgment module, wherein the pipeline section dividing and setting module divides a heat supply pipeline into a plurality of pipeline sections with equal length in advance, each pipeline section is provided with a pressure sensor and a temperature sensor, the heat supply pipeline comprises a pipeline layer, a heat preservation layer and a protective layer, the pressure sensors are arranged on the pipeline layers of the pipeline sections, the temperature sensors are arranged on the heat preservation layers of the pipeline sections, the data acquisition and uploading module is used for acquiring state data of the pipeline sections and uploading the state data to a cloud platform, the data analysis and judgment module is used for judging whether the heat supply pipeline has leakage according to the data detected by the pressure sensors and the temperature sensors, and when the leakage exists, the corresponding pipeline sections are overhauled, when leakage does not exist, the corresponding pipeline section is selected as the section to be analyzed, image information of the section to be analyzed is collected, and whether maintenance repair needs to be carried out on the heat supply pipeline is analyzed and judged.
The data analysis and judgment module comprises an in-doubt section selection module, a temperature data analysis module, a position reference index calculation module, a first similarity acquisition module, a second similarity acquisition module, a comprehensive evaluation parameter calculation module, a comprehensive evaluation parameter comparison module and a section to be analyzed analysis module, wherein the in-doubt section selection module acquires data P detected by a temperature sensor of a pipeline section when detecting that data detected by the pressure sensor of the pipeline section is smaller than a pressure threshold value, and when the data P detected by the temperature sensor is larger than the temperature threshold value, the pipeline section is set as an in-doubt section, the temperature data analysis module sequentially acquires detection data O1, O2, … and Om of the temperature sensors of m pipeline sections at the upstream of the in-doubt section and detection data R1, R2, … and Rn of the temperature sensors of n pipeline sections at the downstream of the in-doubt section, and calculates Ji-Oi-P, Kj-Rj-P, where i is 1 to m, J is 1 to n, the position reference index calculation module is configured to calculate a position reference index S1-U1/U2, U1 is a smaller one of J1 and K1, and U2 is a larger one of J1 and K1, the first similarity acquisition module obtains a first sequence from the upstream pipeline segments in a sequence from Ji to Ji, compares the first sequence with a sequence in a direction of upstream pipeline segments of a suspected segment to obtain a first similarity Sx, the second similarity acquisition module obtains a second sequence from the downstream pipeline segments in a sequence from Ki to Ki, compares the second sequence with a sequence in a direction of downstream pipeline segments of the suspected segment to obtain a second similarity Sy, and the comprehensive evaluation parameter calculation module obtains the second similarity Sy from the position reference index S1, and calculates a position reference index S1/U2, where U1 is a smaller one of J1 and K1, and U2 is a larger one of J1 and K1 And the comprehensive evaluation parameter comparison module compares the comprehensive evaluation parameter with a comprehensive evaluation threshold value, if the comprehensive evaluation parameter is greater than or equal to the comprehensive evaluation threshold value, the heat supply pipeline segment is judged to have leakage, the heat supply pipeline segment and the neighborhood thereof are overhauled by transmission information, if the comprehensive evaluation parameter is smaller than the comprehensive evaluation threshold value, the heat supply pipeline segment is judged not to have leakage, a segment to be analyzed with the suspected pipeline as the center and within a certain range is divided, and the segment to be analyzed analysis module analyzes and judges whether to perform maintenance repair on the corresponding pipeline segment.
The analysis module of the section to be analyzed comprises an image acquisition and processing module, a judgment module, a first processing module and a second processing module, wherein the image acquisition and processing module acquires image information of the section to be analyzed and performs binarization processing on the image information to obtain a crack curve on the section to be analyzed, the judgment module is used for judging whether a certain crack curve is a closed curve or not, when the crack curve is judged to be the closed curve, the first processing module is used for performing analysis and judgment, when the crack curve is judged not to be the closed curve, the second processing module is used for performing analysis and judgment, the first processing module comprises an area acquisition module and an area comparison module, the area acquisition module is used for acquiring the area of the closed curve on the image of the section to be analyzed, the area comparison module is used for comparing the acquired area of the area acquisition module with an area threshold value, and when the area is larger than or equal to the area threshold value, and transmitting information to maintain and repair the pipeline section where the fracture curve is located.
The second judging module comprises a first reference line obtaining module, a second reference line obtaining module, an influence reference value calculating module and an influence reference value comparing module, wherein the first reference line obtaining module obtains that a connecting line between two end points of the fracture curve is a first reference line, the second reference line obtaining module obtains the lengths of vertical lines from all the points on the fracture curve to the first reference line, the lengths of the vertical lines are selected and sequenced from large to small, the first vertical line is taken as a second reference line, the influence reference value calculating module calculates an influence reference value H of the fracture curve, which is Ls/Ws + Lr/Wr, wherein Ls and Lr are respectively the length of the first reference line and the length of the second reference line of the fracture curve, Ws and Wr are respectively a first reference line threshold value and a second reference line threshold value, and the influence reference value comparing module compares the influence reference value with the influence reference threshold value, and when the influence reference value is greater than or equal to the influence reference threshold value, transmitting information to maintain and repair the pipeline section where the fracture curve is located.
The monitoring system further comprises a monitoring method, and the monitoring method comprises the following steps:
the method comprises the following steps of dividing a heat supply pipeline into a plurality of pipeline sections with equal length in advance, wherein each pipeline section is provided with a pressure sensor and a temperature sensor, the heat supply pipeline comprises a pipeline layer, a heat preservation layer and a protective layer, the pressure sensors are arranged on the pipeline layers of the pipeline sections, and the temperature sensors are arranged on the heat preservation layers of the pipeline sections; the pressure sensor and the temperature sensor selected in the application need to meet the protection requirements of high-temperature, high-humidity and water-soaking environments, are powered by a battery with the service life of more than 5 years, and can realize wireless communication; the pressure sensor is used for measuring the pressure received by the pipeline layer, and the temperature sensor is used for measuring the temperature of the heat insulation layer;
collecting state data of each pipeline segment, uploading the state data to a cloud platform, analyzing the corresponding state data, judging whether the heat supply pipeline has leakage or not,
if there is a leak, the corresponding pipe section is serviced,
if no leakage exists, selecting the corresponding pipeline segment as the segment to be analyzed, collecting the image information of the segment to be analyzed, and analyzing and judging whether to maintain and repair the heat supply pipeline.
The analyzing the corresponding state data comprises:
if the data detected by the pressure sensor of a certain pipeline section is smaller than a pressure threshold value, collecting the data P detected by the temperature sensor of the pipeline section, when the data P detected by the temperature sensor is larger than the temperature threshold value, setting the pipeline section as a suspected section, and when a leakage point exists in the certain pipeline section, part of water flows out of the leakage point, so that the pressure on the pipeline section is reduced;
sequentially acquiring detection data O1, O2, … and Om of temperature sensors of m pipeline sections at the upstream of the suspected section and detection data R1, R2, … and Rn of temperature sensors of n pipeline sections at the downstream, calculating Ji-Oi-P, Kj-Rj-P, wherein the value of i is 1 to m, and the value of J is 1 to n, and then a position reference index S1 is U1/U2, wherein U1 is the smaller one of J1 and K1, and U2 is the larger one of J1 and K1;
in the present application, O1, O2, … and Om correspond to the data detected from the pipeline section in the upstream direction of the suspected section, R1, R2, … and Rn correspond to the data detected from the pipeline section in the downstream direction of the suspected section, that is, the detected data is the detected data diffused from the suspected section to both sides, so O1 is the detected data of the pipeline section closest to the suspected section in the upstream pipeline section of the suspected section, R1 is the detected data of the pipeline section closest to the suspected section in the downstream pipeline section of the suspected section, in the application, the plurality of pipeline sections with equal lengths, the temperature sensors are also arranged at fixed positions on the pipeline sections, and the distances between the temperature sensors are also equal, so that when leakage points exist on the suspected sections and water at the leakage points diffuses towards two sides, the temperatures detected by the two sensors are not greatly different; when J1 is larger than K1, S1 is equal to K1/J1, and when K1 is larger than or equal to J1, S1 is equal to J1/K1;
obtaining a first sequence of the upstream pipeline sections according to the sequence from small to large of Ji, comparing the first sequence with the sequence of the upstream pipeline sections from the suspected section to obtain a first similarity Sx, obtaining a second sequence of the downstream pipeline sections according to the sequence from small to large of Ki, comparing the second sequence with the sequence of the downstream pipeline sections from the suspected section to obtain a second similarity Sy, if the temperature sensor is farther from the suspected section when the leakage point exists on the suspected section and the water at the leakage point diffuses to both sides, the detected temperature is influenced by the leakage of the leakage point to be larger, the temperature sensor is closer to the suspected section, the detected temperature is influenced by the leakage of the leakage point to be larger, and based on the characteristic, therefore, whether the suspected section and the vicinity thereof have the leakage point can be judged according to the first similarity and the second similarity;
then the overall evaluation parameter Sz is 0.12S 1+ c Sx + d Sy, where c + d is 0.88, c and d are fractions between 0 and 1, c is m/(m + n) 0.88, d is 0.88-c; according to the method and the device, the number of the selected upstream pipeline sections and the number of the selected downstream pipeline sections are used as weight consideration factors of the comprehensive evaluation parameters, so that the calculation result of the comprehensive evaluation parameters is more accurate;
the analyzing the corresponding state data further comprises:
sequentially acquiring detection data of the temperature sensors of the pipeline sections along the direction of each pipeline section upstream of the suspected pipeline, and when the a-th sensor is detected, if J (a +1) -Ja is smaller than or equal to a reference threshold value and Ja-J (a-1) is larger than the reference threshold value, then m is equal to a; a is a natural number, a is more than or equal to 2,
sequentially acquiring detection data of the temperature sensors of the pipeline sections along the direction of each pipeline section from the suspected pipeline to the downstream, and when a b-th sensor is detected, if K (b +1) -Kb is smaller than or equal to a reference threshold value and Kb-K (b-1) is larger than the reference threshold value, n is equal to b; b is a natural number, b is greater than or equal to 2,
if the comprehensive evaluation parameter is more than or equal to the comprehensive evaluation threshold value, judging that the heat supply pipeline has leakage, and overhauling the suspected section and the vicinity of the suspected section; when the leakage is judged to exist, the cloud platform transmits a command to the Internet of things regulating valve on the heat supply pipeline to regulate the hot water distribution on the heat supply pipeline;
if the comprehensive evaluation parameter is smaller than the comprehensive evaluation threshold value, judging that the heat supply pipeline segment has no leakage, dividing out the segment to be analyzed of the pipeline segment within a certain range by taking the suspected pipeline as the center, directly setting the segment to be analyzed as the pipeline within a fixed distance range, determining according to selected m and n, rounding (m + n)/2, taking the obtained integer as the reference number, and combining the reference number of pipeline segments near the suspected pipeline as the segment to be analyzed by taking the suspected pipeline as the center;
the analyzing and judging whether to carry out maintenance and repair comprises the following steps:
collecting the image information of the section to be analyzed, carrying out binarization processing on the image information to obtain a crack curve on the section to be analyzed,
judging whether a certain crack curve is a closed curve, if so, acquiring the area of the closed curve on the image of the section to be analyzed, and transmitting information to maintain and repair the pipeline section where the crack curve is located when the area is larger than or equal to an area threshold;
if the fracture curve is not a closed curve, acquiring a connecting line between two end points of the fracture curve as a first reference line, acquiring the length of a vertical line from each point on the fracture curve to the first reference line, selecting the first vertical line as a second reference line according to the length of the vertical line from big to small,
calculating an influence reference value H of the fracture curve, wherein Ls and Lr are the length of a first reference line and the length of a second reference line of the fracture curve respectively, and Ws and Wr are a first reference line threshold value and a second reference line threshold value respectively;
and when the influence reference value is greater than or equal to the influence reference threshold value, the transmission information carries out maintenance and repair on the pipeline section where the fracture curve is located.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. A heat supply pipe network digital monitoring system based on an Internet of things sensor is characterized by comprising a pipeline section dividing and setting module, a data acquisition and uploading module and a data analysis and judgment module, wherein the pipeline section dividing and setting module divides a heat supply pipeline into a plurality of pipeline sections with equal length in advance, each pipeline section is provided with a pressure sensor and a temperature sensor, the heat supply pipeline comprises a pipeline layer, a heat preservation layer and a protective layer, the pressure sensors are arranged on the pipeline layers of the pipeline sections, the temperature sensors are arranged on the heat preservation layers of the pipeline sections, the data acquisition and uploading module is used for acquiring state data of the pipeline sections and uploading the state data to a cloud platform, the data analysis and judgment module is used for judging whether the heat supply pipeline has leakage according to the data detected by the pressure sensors and the temperature sensors, when the leakage exists, and (4) overhauling the corresponding pipeline segment, selecting the corresponding pipeline segment as the segment to be analyzed when leakage does not exist, acquiring the image information of the segment to be analyzed, and analyzing and judging whether to maintain and repair the heat supply pipeline.
2. The heat supply pipe network digital monitoring system based on the sensor of the internet of things according to claim 1, wherein: the data analysis and judgment module comprises an in-doubt section selection module, a temperature data analysis module, a position reference index calculation module, a first similarity acquisition module, a second similarity acquisition module, a comprehensive evaluation parameter calculation module, a comprehensive evaluation parameter comparison module and a section to be analyzed analysis module, wherein the in-doubt section selection module acquires data P detected by a temperature sensor of a pipeline section when detecting that data detected by the pressure sensor of the pipeline section is smaller than a pressure threshold value, and when the data P detected by the temperature sensor is larger than the temperature threshold value, the pipeline section is set as an in-doubt section, the temperature data analysis module sequentially acquires detection data O1, O2, … and Om of the temperature sensors of m pipeline sections at the upstream of the in-doubt section and detection data R1, R2, … and Rn of the temperature sensors of n pipeline sections at the downstream of the in-doubt section, and calculates Ji-Oi-P, Kj-Rj-P, where i is 1 to m, J is 1 to n, the position reference index calculation module is configured to calculate a position reference index S1-U1/U2, U1 is a smaller one of J1 and K1, and U2 is a larger one of J1 and K1, the first similarity acquisition module obtains a first sequence from the upstream pipeline segments in a sequence from Ji to Ji, compares the first sequence with a sequence in a direction of upstream pipeline segments of a suspected segment to obtain a first similarity Sx, the second similarity acquisition module obtains a second sequence from the downstream pipeline segments in a sequence from Ki to Ki, compares the second sequence with a sequence in a direction of downstream pipeline segments of the suspected segment to obtain a second similarity Sy, and the comprehensive evaluation parameter calculation module obtains the second similarity Sy from the position reference index S1, and calculates a position reference index S1/U2, where U1 is a smaller one of J1 and K1, and U2 is a larger one of J1 and K1 And the comprehensive evaluation parameter comparison module compares the comprehensive evaluation parameter with a comprehensive evaluation threshold value, if the comprehensive evaluation parameter is greater than or equal to the comprehensive evaluation threshold value, the heat supply pipeline segment is judged to have leakage, the heat supply pipeline segment and the neighborhood thereof are overhauled by transmission information, if the comprehensive evaluation parameter is smaller than the comprehensive evaluation threshold value, the heat supply pipeline segment is judged not to have leakage, a segment to be analyzed with the suspected pipeline as the center and within a certain range is divided, and the segment to be analyzed analysis module analyzes and judges whether to perform maintenance repair on the corresponding pipeline segment.
3. The heat supply pipe network digital monitoring system based on the sensor of the internet of things according to claim 2, wherein: the analysis module of the section to be analyzed comprises an image acquisition and processing module, a judgment module, a first processing module and a second processing module, wherein the image acquisition and processing module acquires image information of the section to be analyzed and performs binarization processing on the image information to obtain a crack curve on the section to be analyzed, the judgment module is used for judging whether a certain crack curve is a closed curve or not, when the crack curve is judged to be the closed curve, the first processing module is used for performing analysis and judgment, when the crack curve is judged not to be the closed curve, the second processing module is used for performing analysis and judgment, the first processing module comprises an area acquisition module and an area comparison module, the area acquisition module is used for acquiring the area of the closed curve on the image of the section to be analyzed, the area comparison module is used for comparing the acquired area of the area acquisition module with an area threshold value, and when the area is larger than or equal to the area threshold value, and transmitting information to maintain and repair the pipeline section where the fracture curve is located.
4. The heat supply pipe network digital monitoring system based on the sensor of the internet of things according to claim 3, wherein: the second judging module comprises a first reference line obtaining module, a second reference line obtaining module, an influence reference value calculating module and an influence reference value comparing module, wherein the first reference line obtaining module obtains that a connecting line between two end points of the fracture curve is a first reference line, the second reference line obtaining module obtains the lengths of vertical lines from all the points on the fracture curve to the first reference line, the lengths of the vertical lines are selected and sequenced from large to small, the first vertical line is taken as a second reference line, the influence reference value calculating module calculates an influence reference value H of the fracture curve, which is Ls/Ws + Lr/Wr, wherein Ls and Lr are respectively the length of the first reference line and the length of the second reference line of the fracture curve, Ws and Wr are respectively a first reference line threshold value and a second reference line threshold value, and the influence reference value comparing module compares the influence reference value with the influence reference threshold value, and when the influence reference value is greater than or equal to the influence reference threshold value, transmitting information to maintain and repair the pipeline section where the fracture curve is located.
5. The heat supply pipe network digital monitoring system based on the sensor of the internet of things according to claim 1, wherein: the monitoring system further comprises a monitoring method, and the monitoring method comprises the following steps:
dividing a heat supply pipeline into a plurality of pipeline sections with equal length in advance, wherein each pipeline section is provided with a pressure sensor and a temperature sensor, the heat supply pipeline comprises a pipeline layer, a heat preservation layer and a protective layer, the pressure sensors are arranged on the pipeline layers of the pipeline sections, and the temperature sensors are arranged on the heat preservation layers of the pipeline sections;
collecting state data of each pipeline segment, uploading the state data to a cloud platform, analyzing the corresponding state data, judging whether the heat supply pipeline has leakage or not,
if there is a leak, the corresponding pipe section is serviced,
if no leakage exists, selecting the corresponding pipeline segment as the segment to be analyzed, collecting the image information of the segment to be analyzed, and analyzing and judging whether to maintain and repair the heat supply pipeline.
6. The heat supply pipe network digital monitoring system based on the sensor of the internet of things according to claim 5, wherein: the analyzing the corresponding state data comprises:
if the data detected by the pressure sensor of a certain pipeline section is detected to be smaller than the pressure threshold value, the data P detected by the temperature sensor of the pipeline section is collected, when the data P detected by the temperature sensor is larger than the temperature threshold value, the pipeline section is set as a suspicious section,
sequentially acquiring detection data O1, O2, … and Om of temperature sensors of m pipeline sections at the upstream of the suspected section and detection data R1, R2, … and Rn of temperature sensors of n pipeline sections at the downstream, calculating Ji-Oi-P, Kj-Rj-P, wherein the value of i is 1 to m, and the value of J is 1 to n, and then a position reference index S1 is U1/U2, wherein U1 is the smaller one of J1 and K1, and U2 is the larger one of J1 and K1;
obtaining a first sequence of the upstream pipeline sections according to the sequence from small to large of Ji, comparing the first sequence with the sequence of the suspected section towards the upstream pipeline sections in the direction to obtain a first similarity Sx, obtaining a second sequence of the downstream pipeline sections according to the sequence from small to large of Ki, comparing the second sequence with the sequence of the suspected pipeline towards the downstream pipeline sections in the direction to obtain a second similarity Sy,
then the overall evaluation parameter Sz is 0.12S 1+ c Sx + d Sy, where c + d is 0.88, c, d are fractions between 0 and 1,
if the comprehensive evaluation parameter is more than or equal to the comprehensive evaluation threshold value, judging that the heat supply pipeline segment has leakage, and overhauling the suspected segment and the vicinity of the suspected segment;
and if the comprehensive evaluation parameter is smaller than the comprehensive evaluation threshold value, judging that the heat supply pipeline segment has no leakage, and dividing the pipeline segment to be analyzed within a certain range by taking the suspected pipeline as the center.
7. The heat supply pipe network digital monitoring system based on the sensor of the internet of things according to claim 6, wherein: the analyzing and judging whether to carry out maintenance and repair comprises the following steps:
collecting the image information of the section to be analyzed, carrying out binarization processing on the image information to obtain a crack curve on the section to be analyzed,
judging whether a certain crack curve is a closed curve, if so, acquiring the area of the closed curve on the image of the section to be analyzed, and transmitting information to maintain and repair the pipeline section where the crack curve is located when the area is larger than or equal to an area threshold;
if the fracture curve is not a closed curve, acquiring a connecting line between two end points of the fracture curve as a first reference line, acquiring the length of a vertical line from each point on the fracture curve to the first reference line, selecting the first vertical line as a second reference line according to the length of the vertical line from big to small,
calculating an influence reference value H of the fracture curve, wherein Ls and Lr are the length of a first reference line and the length of a second reference line of the fracture curve respectively, and Ws and Wr are a first reference line threshold value and a second reference line threshold value respectively;
and when the influence reference value is greater than or equal to the influence reference threshold value, the transmission information carries out maintenance and repair on the pipeline section where the fracture curve is located.
8. The heat supply pipe network digital monitoring system based on the sensor of the internet of things according to claim 6, wherein: the analyzing the corresponding state data further comprises:
sequentially acquiring detection data of the temperature sensors of the pipeline sections along the direction of each pipeline section upstream of the suspected pipeline, and when the a-th sensor is detected, if J (a +1) -Ja is smaller than or equal to a reference threshold value and Ja-J (a-1) is larger than the reference threshold value, then m is equal to a;
and sequentially acquiring detection data of the temperature sensors of the pipeline sections along the direction of each pipeline section downstream from the suspected pipeline, and when a b-th sensor is detected, if K (b +1) -Kb is less than or equal to a reference threshold value and Kb-K (b-1) is greater than the reference threshold value, n-b.
9. The heat supply pipe network digital monitoring system based on the sensor of the internet of things according to claim 6, wherein: the analyzing the corresponding state data further comprises:
c＝m/(m+n)*0.88，d＝0.88-c。
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