CN112348303A - Wisdom water affairs information processing system - Google Patents

Wisdom water affairs information processing system Download PDF

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CN112348303A
CN112348303A CN202010774313.8A CN202010774313A CN112348303A CN 112348303 A CN112348303 A CN 112348303A CN 202010774313 A CN202010774313 A CN 202010774313A CN 112348303 A CN112348303 A CN 112348303A
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李素媛
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Abstract

The utility model provides a wisdom water affairs information processing system, includes sensor group array, infiltration monitoring positioning unit, sensor group array includes a plurality of sensor groups that arrange at urban water supply pipe for the status data of each monitoring point of real-time supervision water supply pipe, infiltration monitoring positioning unit is through the analysis the status data of each monitoring point of water supply pipe that sensor group array provided judges water supply pipe infiltration state. The water supply pipe permeate status includes a qualitative indication of whether or not permeate is present and a quantitative indication of the permeate location.

Description

Wisdom water affairs information processing system
Technical Field
The invention belongs to the field of information analysis, and particularly relates to an intelligent water affair information processing system.
Background
The direct drinking water is generally delivered to the household by adopting a quality-based water supply mode, domestic water and direct drinking water in tap water are separated according to different requirements of people on water in life, a pipe network is additionally arranged, the tap water is deeply processed into purified water capable of being directly drunk by adopting a special process, and then the purified water is delivered to the household by a pipeline of food sanitation level.
The direct drinking water system mainly includes: the system comprises an equipment system, a pipe network system, a master control system and a cloud system. The equipment system comprises an equipment control system, a linkage control system of equipment rooms (a water production host and other equipment), an equipment and pipe network dynamic system, an equipment function and maintenance detection system, a sterilization system, an equipment room water quality and air detection system and an equipment room security system. The pipe network system comprises a main pipe control system, a branch and tail end linkage system, a pipe network valve and a maintenance linkage system. The master control system comprises a master control system among pipe network data feedback devices, a master control device control pipe network system and a tail end and master control device linkage system. The cloud system comprises a device and pipe network and cloud data sharing system, a master control platform and device and cloud data sharing system, a device and wireless device and master control platform data linkage sharing system, and a wireless device and master control platform data linkage system.
With the increasing construction speed of cities, water safety accidents of urban underground pipe networks occur continuously in recent years, the water affair information processing cost is continuously increased, and enterprises and other organizations widely apply IT technology and establish innovative management modes of intelligent water affairs to help the enterprises to effectively process increasingly complex water affair operation information processing. Along with the increasingly wide distribution of the water supply network and the continuous expansion of the pipeline area span, the research and design of the remote monitoring system of the water supply network become more important. The water supply network remote monitoring system can not only strengthen the centralized management of water supply network equipment and improve the automation level of water supply information processing, but also can strengthen the protection of water resources in the water delivery link. Therefore, the system has very important environmental protection significance and social significance for the research of the water supply pipeline monitoring system.
The above information is merely presented as background information to assist the reader in understanding the present invention. No determination or assertion is made by the applicant as to whether any of the above is applicable as prior art with respect to the present application.
Disclosure of Invention
Based on the above, in order to solve the above problems, effectively realize the monitoring of the water supply pipeline, reduce the waste of water resources, and solve the technical problem of automatic intelligent early warning, the invention provides a smart water service information processing system, which comprises a sensor group array and an osmosis monitoring and positioning unit, wherein the sensor group array comprises a plurality of sensor groups arranged in the urban water supply pipeline and is used for monitoring the state data of each monitoring point of the water supply pipeline in real time.
Further optionally, the water supply pipe permeate status includes a qualitative indication of whether or not permeate is present and a quantitative indication of permeate location.
Further optionally, the infiltration monitoring and positioning unit gives a qualitative indication of whether the water supply pipeline is infiltrated by analyzing the status data of each monitoring point of the water supply pipeline provided by the sensor group array, and comprises:
the flow time sequence collected by the kth sensor group is collected as follows:
Figure 936409DEST_PATH_IMAGE001
，
the flow time sequence collected by the (k + 1) th sensor group is as follows:
Figure 118778DEST_PATH_IMAGE002
，
wherein N is the time length of the interception, and the judgment is calculated
Figure 770340DEST_PATH_IMAGE003
A difference of (a) if
Figure 596082DEST_PATH_IMAGE004
Wherein
Figure 991291DEST_PATH_IMAGE005
In order to set the flow rate threshold value,
Figure 540084DEST_PATH_IMAGE006
and
Figure 866941DEST_PATH_IMAGE007
and respectively judging that the water supply pipeline between the kth sensor group and the (k + 1) th sensor group is permeated, and giving out early warning indication of permeation.
Further optionally, the infiltration monitor locating unit gives a quantitative indication of the infiltration site of the water supply pipeline by analyzing status data of each monitored point of the water supply pipeline provided by the sensor array, and comprises:
the pressure time sequence collected by the kth sensor group is collected as follows:
Figure 133975DEST_PATH_IMAGE008
，
the pressure time sequence collected by the (k + 1) th sensor group is collected as follows:
Figure 67296DEST_PATH_IMAGE009
，
wherein N is the length of time of the truncation,
respectively translating the pressure time sequence acquired by the kth sensor group and the k +1 th sensor group
Figure 271132DEST_PATH_IMAGE010
And obtaining the pressure time sequence collected by the k sensor group after translation according to the pressure data of the time unit as follows:
Figure 530075DEST_PATH_IMAGE011
，
the pressure time sequence collected by the (k + 1) th sensor group after translation is as follows:
Figure 18825DEST_PATH_IMAGE012
，
wherein
Figure 536263DEST_PATH_IMAGE013
In order to be the time difference between the two,
Figure 59648DEST_PATH_IMAGE014
,
Figure 722449DEST_PATH_IMAGE015
and M is the length of the truncated time sequence,
Figure 964074DEST_PATH_IMAGE016
and summing the translated upstream and downstream pressures to obtain:
Figure 504777DEST_PATH_IMAGE017
，
calculate its mean and variance:
mean value
Figure 652642DEST_PATH_IMAGE018
，
Variance (variance)
Figure 253388DEST_PATH_IMAGE019
，
Traversal computation
Figure 716730DEST_PATH_IMAGE020
OfDifference (D)
Figure 294080DEST_PATH_IMAGE021
When the value is minimized
Figure 792057DEST_PATH_IMAGE010
，
Time difference of arrival of osmotic pressure signal at kth and (k + 1) th sensor group
Figure 786208DEST_PATH_IMAGE022
Is composed of
Figure 2426DEST_PATH_IMAGE023
Corresponding when the value is minimized
Figure 884931DEST_PATH_IMAGE013
A value of (d);
calculating the position indication x from the water supply pipeline penetration point to the k sensor group:
Figure 17841DEST_PATH_IMAGE024
，
wherein k is the number of the sensor group of the positive integer type, L is the distance between the kth and k +1 sensor groups,
Figure 694810DEST_PATH_IMAGE022
the time difference between the arrival of the osmolarity pressure signal at the kth and (k + 1) th sensor groups,
Figure 132745DEST_PATH_IMAGE025
is the propagation speed of the osmotic pressure signal in the pipeline;
and displaying k and x as quantitative indications of permeation positions through the intelligent water service system.
Further optionally, after the permeation monitoring and positioning unit gives the permeation early warning indication, analyzing and calculating a permeation position quantitative indication; wherein a set flow threshold value
Figure 545839DEST_PATH_IMAGE005
The method is obtained by constructing a deep learning network for training; the sensor group comprises one or more of a pressure sensor, a flow sensor, a temperature sensor and a viscosity sensor.
Further optionally, the intelligent water affair information processing system further comprises a big data visualization unit for human-computer interaction.
Further optionally, the intelligent water affair information processing system comprises a communication network for data transmission; the system also comprises a maintenance and repair unit which is used for receiving the state data given by the penetration monitoring and positioning unit and responding according to the penetration state data when penetration indication occurs.
The intelligent water affair system provided by the invention has the advantages of higher response speed and higher positioning precision, the safe operation of a water supply network can be effectively ensured, and the automatic early warning capability and efficiency of the system are improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is an exemplary schematic diagram of an intelligent water information processing system according to the present invention;
FIG. 2 is another exemplary schematic diagram of an intelligent water information processing system according to the present invention;
FIG. 3 is an exemplary flow chart of a qualitative analysis of the intelligent water information processing system according to the present invention; FIG. 4 is an exemplary flow chart of quantitative calculations for an intelligent water information processing system according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further optionally described in detail with reference to the accompanying drawings. This description is made by way of example and not limitation to specific embodiments consistent with the principles of the invention, the description being in sufficient detail to enable those skilled in the art to practice the invention, other embodiments may be utilized and the structure of various elements may be changed and/or substituted without departing from the scope and spirit of the invention. The following detailed description is, therefore, not to be taken in a limiting sense. In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further explained below by combining the specific drawings.
The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. Furthermore, the various embodiments described herein are not necessarily mutually exclusive, as some embodiments may be combined with one or more other embodiments to form new embodiments. The term "or" as used herein refers to a non-exclusive or, unless otherwise specified. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
The intelligent water affair system is a novel technical platform which takes water sources, water supplies, pipe networks, treatment plants and received water bodies as an integral system and depends on the development of instrumentation, automatic control, data analysis, artificial intelligence, the Internet and the like, and aims to promote the reasonable utilization of water resources and the effective protection of water ecological environment under the optimized condition by using intelligent means based on the information flow and the data flow of the water system.
Fig. 1 is an exemplary schematic diagram of an intelligent water information processing system according to the present invention, and as shown in fig. 1, the intelligent water information processing system according to the present invention includes a sensor array and an infiltration monitoring and positioning unit. In some embodiments, the intelligent water information processing system may or may not include some other units and components. Not shown in fig. 1.
In some embodiments, the sensor group array comprises a plurality of sensor groups arranged in a municipal water supply pipeline and used for monitoring the state data of each monitoring point of the water supply pipeline in real time, and the infiltration monitoring and positioning unit judges the infiltration state of the water supply pipeline by analyzing the state data of each monitoring point of the water supply pipeline provided by the sensor group array.
In some embodiments, the sensor group includes one or more of a pressure sensor, a flow sensor, a temperature sensor, a viscosity sensor. Further, all the sensing devices necessary for the required data may be included in the sensor group.
In some embodiments, the water supply pipe permeate status includes a qualitative indication of whether or not permeate is present and a quantitative indication of permeate location. The indication can be presented in a manner available in the prior art, such as display or text warning.
For example, in some embodiments, intelligent water utilities are based on information flow and data flow of the water system, and intelligent means are used to promote reasonable utilization of water resources and effective protection of water ecological environment under optimized conditions. The intelligent water affair sharing technical platform is formed by four plates of drinking water safety operation, optimized operation of a sewage treatment plant, operation information processing of a drainage pipe network and ecological safety of a storage water body, and resource sharing of common advanced technology in the water affair field is achieved through a user-friendly network platform. The sharing technology in the field of drinking water safety operation comprises rapid detection of trace pollutants and automatic monitoring of biotoxicity, provides real-time safety early warning for water source water and drinking water through data analysis, and guarantees drinking water safety in cities and rural areas. The sharing technology in the field of optimized operation of the sewage treatment plant comprises real-time monitoring of the quality and the quantity of inlet water and the breathing rate of the sewage treatment plant, can provide a basis for stable standard reaching of the outlet water of the sewage treatment system, improves the optimized marshalling operation technology of a pump station, the simulation optimization technology of a sewage treatment process, the accurate aeration technology of aerobic biological treatment, the intelligent dosing control technology and the operation performance evaluation management method, and realizes energy saving, consumption reduction and stable standard reaching of the sewage treatment plant. The real-time monitoring of the drainage pipe network and the pump station provides early warning for the impact of rainstorm and industrial wastewater to a sewage treatment plant, and the safe operation and information processing of the drainage pipe network are improved based on the simulation analysis technology of inflow infiltration of the pipe network model. The high-density water quality monitoring and automatic monitoring technology of trace pollutants makes up for the short board of monitoring data sparseness and water ecological safety parameter loss. The micro automatic monitoring station and the shipborne mobile monitoring system can provide continuous high-density monitoring data in time and space, and the frequency can reach one group of data per minute. And finally, big data analysis and decision management of receiving water body safety can be formed.
For example, in some embodiments, the intelligent water affair information processing system may include an independent industrial-chain-wide integration system, an aerodynamic water body separation technology, a multi-layer regeneration separation technology, a real-time online intelligent monitoring technology, a matrix stainless steel pipe network system and bump loose joint technology, a fresh-keeping technology of running water, a terminal constant-pressure water supply technology, and a water purification system technology.
FIG. 2 is another exemplary diagram of an intelligent water information processing system according to the present invention. As shown in fig. 2, in some embodiments, the intelligent water affair information processing system further includes a big data visualization unit for human-computer interaction. Effective data analysis is provided for governments through collection, mining and analysis of resident water consumption information; the intelligent Internet of things water meter developed by a company has the advantages that data are uploaded, the running condition of the water meter is used as an intelligent water service platform, and a user can inquire the book using condition at any time.
In some embodiments, the intelligent water information processing system further comprises a communication network for data transmission. In the prior art, various wired or wireless communication modes can be used in the present invention to realize data transmission, such as 2G, 3G, 4G, 5G mobile networks, etc.
In some embodiments, the intelligent water information processing system further comprises a maintenance and repair unit for receiving the state data from the penetration monitoring and positioning unit and responding according to the penetration state data when a penetration indication occurs. To realize 24-hour emergency response of 24-hour standby maintenance service of a maintenance team.
FIG. 3 is an exemplary flow chart of a qualitative analysis of the intelligent water information processing system according to the present invention. As shown in fig. 3, the infiltration monitor positioning unit gives a qualitative indication of whether the water supply pipeline is infiltrated by analyzing the state data of each monitoring point of the water supply pipeline provided by the sensor group array, and comprises:
the flow time sequence collected by the kth sensor group is as follows:
Figure 267676DEST_PATH_IMAGE001
，
the flow time sequence collected by the (k + 1) th sensor group is as follows:
Figure 381126DEST_PATH_IMAGE002
wherein N is the time length of the interception,
computing a judgment
Figure 306356DEST_PATH_IMAGE003
A difference of (a) if
Figure 29200DEST_PATH_IMAGE004
Judging that the water supply pipeline between the kth sensor group and the (k + 1) th sensor group is permeated, and giving out a permeation early warning indication, wherein
Figure 356276DEST_PATH_IMAGE005
In order to set the flow rate threshold value,
Figure 410600DEST_PATH_IMAGE006
and
Figure 557548DEST_PATH_IMAGE007
respectively, water flow temperature and viscosity influencing factors.
This is because the flow rate of the supplied water is also affected by changes in other physical quantities, such as pressure, temperature, viscosity, etc. at the inlet and outlet of the pipe, which causes a slight difference in the flow rate of the supplied water at the inlet and outlet, resulting in poor delivery. On the premise of considering the influence of various physical changes, the instantaneous flow of the inlet and the outlet of the pipeline has a normal difference value change range. When the pipeline normally runs, the variation range of the inlet and outlet flow difference value is relatively stable and cannot exceed the variation range of the difference value; if the pipeline leaks, the difference value will be obviously increased and exceeds the normal variation range of the difference value. According to the principle, a threshold value can be set by combining the actual operation condition of a pipe network, and when the transmission difference exceeds the threshold value, the leakage accident of the pipeline can be judged. This can roughly determine whether the pipe has penetrated and the size of the penetration, but cannot infer the position of the pipe penetration point, so a new detection technique is introduced.
In some embodiments, the set flow threshold
Figure 585547DEST_PATH_IMAGE005
The method is obtained by constructing deep learning network training.
FIG. 4 is an exemplary flow chart of quantitative calculations for an intelligent water information processing system according to the present invention. As shown in fig. 3, the infiltration monitor positioning unit gives quantitative indication of infiltration location of the water supply pipeline by analyzing status data of each monitoring point of the water supply pipeline provided by the sensor group array, comprising:
the pressure time sequence collected by the kth sensor group is collected as follows:
Figure 85DEST_PATH_IMAGE008
，
the pressure time sequence collected by the (k + 1) th sensor group is collected as follows:
Figure 455337DEST_PATH_IMAGE009
，
wherein N is the length of time of the truncation,
respectively translate the kth part,Pressure time series collected by k +1 sensor group
Figure 355160DEST_PATH_IMAGE010
And in time unit, obtaining the pressure time sequence collected by the k sensor group after translation as follows:
Figure 409354DEST_PATH_IMAGE026
，
the pressure time sequence collected by the (k + 1) th sensor group after translation is as follows:
Figure 445443DEST_PATH_IMAGE027
，
wherein
Figure 852022DEST_PATH_IMAGE013
In order to be the time difference between the two,
Figure 973562DEST_PATH_IMAGE014
，
Figure 343364DEST_PATH_IMAGE015
and M is the length of the truncated time sequence,
Figure 738354DEST_PATH_IMAGE016
and summing the translated upstream and downstream pressures to obtain:
Figure 535408DEST_PATH_IMAGE017
，
computing
Figure 144244DEST_PATH_IMAGE028
Mean and variance of (c):
mean value
Figure 493365DEST_PATH_IMAGE018
，
Variance (variance)
Figure 504047DEST_PATH_IMAGE019
，
Traversal computation
Figure 472003DEST_PATH_IMAGE020
Variance of (2)
Figure 82981DEST_PATH_IMAGE021
When the value is minimized
Figure 794585DEST_PATH_IMAGE010
，
Time difference of arrival of osmotic pressure signal at kth and (k + 1) th sensor group
Figure 423888DEST_PATH_IMAGE022
Is composed of
Figure 562745DEST_PATH_IMAGE023
Corresponding when the value is minimized
Figure 880594DEST_PATH_IMAGE013
A value of (d);
calculating the position indication x from the water supply pipeline penetration point to the k sensor group:
Figure 165863DEST_PATH_IMAGE024
，
wherein k is the number of the sensor group of the positive integer type, L is the distance between the kth and k +1 sensor groups,
Figure 151136DEST_PATH_IMAGE022
the time difference between the arrival of the osmolarity pressure signal at the kth and (k + 1) th sensor groups,
Figure 460895DEST_PATH_IMAGE025
is the propagation speed of the leakage signal in the pipeline;
and displaying k and x as quantitative indications of permeation positions through the intelligent water service system.
In some embodiments, a quantitative indication of the permeation location is analyzed and calculated after the permeation monitoring and positioning unit gives the permeation early warning indication. The implementation method can reduce the operation amount and improve the overall operation efficiency of the system.
In order to ensure the continuous, stable and safe operation of a water supply network of the system, the real-time monitoring and the information processing of the water supply network become important. The water supply network remote monitoring system can not only strengthen the centralized management of water supply network equipment and improve the automation level of water supply information processing, but also can strengthen the protection of water resources in the water delivery link. The monitoring of the water supply pipeline is effectively realized, the waste of water resources is reduced, and the technical problem of automatic intelligent early warning is solved.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims.
Moreover, other implementations of the invention will be apparent to those skilled in the art from consideration of the specification of the invention disclosed herein. The embodiments and/or aspects of the embodiments can be used in the systems and methods of the present invention alone or in any combination. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.

Claims (10)

1. The utility model provides a wisdom water affairs information processing system, its characterized in that, includes sensor group array, infiltration monitoring positioning unit, sensor group array includes a plurality of sensor groups that arrange at city water supply pipe for the status data of each monitoring point of real-time supervision water supply pipe, infiltration monitoring positioning unit is through the analysis the status data of each monitoring point of water supply pipe that sensor group array provided judges the infiltration state of water supply pipe.
2. The intelligent water information processing system according to claim 1, wherein the water supply pipe permeation status includes a qualitative indication of whether or not permeation occurred and a quantitative indication of permeation location.
3. The intelligent water information processing system according to claim 2, wherein the infiltration monitor locating unit provides a qualitative indication of whether the water supply pipeline is infiltrated by analyzing the status data of each monitoring point of the water supply pipeline provided by the sensor array, comprising:
the flow time sequence collected by the kth sensor group is as follows:
Figure 713194DEST_PATH_IMAGE001
，
the flow time sequence collected by the (k + 1) th sensor group is as follows:
Figure 125720DEST_PATH_IMAGE002
，
wherein N is the length of time of the truncation,
computing a judgment
Figure 402987DEST_PATH_IMAGE003
A difference of (a) if
Figure 584569DEST_PATH_IMAGE004
Judging that the water supply pipeline between the kth sensor group and the (k + 1) th sensor group is permeated, and giving out a permeation early warning indication, wherein
Figure 538357DEST_PATH_IMAGE005
In order to set the flow rate threshold value,
Figure 438180DEST_PATH_IMAGE006
and
Figure 4290DEST_PATH_IMAGE007
respectively, water flow temperature and viscosity influencing factors.
4. The intelligent water information processing system according to claim 2, wherein the infiltration monitor positioning unit gives a quantitative indication of infiltration location of the water supply pipeline by analyzing status data of each monitoring point of the water supply pipeline provided by the sensor array, comprising:
the pressure time sequence collected by the kth sensor group is collected as follows:
Figure 810353DEST_PATH_IMAGE008
，
the pressure time sequence collected by the (k + 1) th sensor group is collected as follows:
Figure 436506DEST_PATH_IMAGE009
，
wherein N is the length of time of the truncation,
respectively translating the pressure time sequence acquired by the kth sensor group and the k +1 th sensor group
Figure 56581DEST_PATH_IMAGE010
And in time unit, obtaining the pressure time sequence collected by the k sensor group after translation as follows:
Figure 160804DEST_PATH_IMAGE011
，
the pressure time sequence collected by the (k + 1) th sensor group after translation is as follows:
Figure 805061DEST_PATH_IMAGE012
，
wherein
Figure 602116DEST_PATH_IMAGE013
In order to be the time difference between the two,
Figure 991378DEST_PATH_IMAGE014
，
Figure 164870DEST_PATH_IMAGE015
and M is the length of the truncated time sequence,
Figure 414367DEST_PATH_IMAGE016
and summing the translated upstream and downstream pressures to obtain:
Figure 382323DEST_PATH_IMAGE017
，
computing
Figure 966538DEST_PATH_IMAGE018
Mean and variance of (c):
mean value
Figure 412563DEST_PATH_IMAGE019
，
Variance (variance)
Figure 543330DEST_PATH_IMAGE020
，
Traversal computation
Figure 197034DEST_PATH_IMAGE021
Variance of (2)
Figure 780462DEST_PATH_IMAGE022
When the value is minimized
Figure 528713DEST_PATH_IMAGE010
，
Time difference of arrival of osmotic pressure signal at kth and (k + 1) th sensor group
Figure 513986DEST_PATH_IMAGE023
Is composed of
Figure 823745DEST_PATH_IMAGE024
Corresponding when the value is minimized
Figure 664443DEST_PATH_IMAGE013
A value of (d);
calculating the position indication x from the water supply pipeline penetration point to the k sensor group:
Figure 717849DEST_PATH_IMAGE025
，
wherein k is the number of the sensor group of the positive integer type, L is the distance between the kth and k +1 sensor groups,
Figure 557630DEST_PATH_IMAGE023
the time difference between the arrival of the osmolarity pressure signal at the kth and (k + 1) th sensor groups,
Figure 271245DEST_PATH_IMAGE026
is the propagation speed of the osmotic pressure signal in the pipeline;
and displaying k and x as quantitative indications of permeation positions through the intelligent water service system.
5. The intelligent water information processing system according to claim 4, wherein a quantitative indication of permeation location is analyzed and calculated after the permeation monitoring and positioning unit gives the permeation pre-warning indication.
6. The intelligent water information processing system according to claim 3, wherein the set flow threshold value
Figure 563686DEST_PATH_IMAGE005
The method is obtained by constructing deep learning network training.
7. The intelligent water information processing system according to any one of claims 1-6, wherein the sensor set comprises one or more of a pressure sensor, a flow sensor, a temperature sensor, and a viscosity sensor.
8. The intelligent water affair information processing system according to any one of claims 1-6, further comprising a big data visualization unit for human-computer interaction.
9. The intelligent water information processing system according to any one of claims 1-6, further comprising a communication network for data transmission.
10. The intelligent water information processing system according to any one of claims 1-6, further comprising a maintenance repair unit for receiving the status data from the penetration monitoring and locating unit and responding to the penetration status data when a penetration indication occurs.
CN202010774313.8A 2020-08-05 2020-08-05 Wisdom water affairs information processing system Pending CN112348303A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113111471A (en) * 2021-04-14 2021-07-13 武汉行健道信息技术有限公司 Urban intelligent water affair digital intelligent management system based on artificial intelligence and Internet of things
CN113610369A (en) * 2021-07-26 2021-11-05 广州园林建筑规划设计研究总院有限公司 Evaluation method of water ecological service efficacy and urban waterfront landscape construction method
CN115218962A (en) * 2022-07-29 2022-10-21 安徽省阜阳市大洋消防器材有限公司 Data collection and detection system based on big data intelligent urban water supply

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113111471A (en) * 2021-04-14 2021-07-13 武汉行健道信息技术有限公司 Urban intelligent water affair digital intelligent management system based on artificial intelligence and Internet of things
CN113111471B (en) * 2021-04-14 2022-02-22 湖南华埔信息产业有限公司 Urban intelligent water affair digital management system based on artificial intelligence and Internet of things
CN113610369A (en) * 2021-07-26 2021-11-05 广州园林建筑规划设计研究总院有限公司 Evaluation method of water ecological service efficacy and urban waterfront landscape construction method
CN115218962A (en) * 2022-07-29 2022-10-21 安徽省阜阳市大洋消防器材有限公司 Data collection and detection system based on big data intelligent urban water supply

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