NL2032501B1

NL2032501B1 - A method and a system for identifying and positioning sewer clogging

Info

Publication number: NL2032501B1
Application number: NL2032501A
Authority: NL
Inventors: Liu Changqing; Ratnaweera Harsha; Wang Xiaodong; Li Zhichao; Li Ning; Zhao Fangchao
Original assignee: Univ Qingdao Technology
Priority date: 2022-03-16
Filing date: 2022-07-15
Publication date: 2024-03-01
Also published as: NL2032501A; CN114840571A

Abstract

The present disclosure relates to the technical field of underground sewer engineering, and provides a method and system for identifying and positioning clogging of a sewer. The method comprises the following steps: acquiring a wastewater level in the sewer by monitoring levels at key nodes of the sewer, acquiring level data from level gauges in real time and pre-processing the level data, and performing differential calculation on time series of changes in the pre-processed level data, thereby identifying and positioning the clogging. In addition to monitoring of sewer conditions, the present disclosure enables identification and positioning of water inlets from which groundwater permeates into the sewer due to damage of the sewer, and mixed connection points of rainwater and sewage and private connection points of industrial wastewater by means of flowmeters, which provides strong guarantee for the operation of the sewers. The present disclosure can help to identify and position clogging points correctly and efficiently, and can visually present position information of the clogging point in an intuitive and clear manner, which provides great convenience for sewer operation and maintenance personnel.

Description

A METHOD AND A SYSTEM FOR IDENTIFYING AND

POSITIONING SEWER CLOGGING

TECHNICAL FIELD

The present disclosure relates to the technical field of sewer engineering, and in particular, relates to a method and a system for identifying and positioning sewer clogging.

BACKGROUND

Sewer systems are municipal pipelines for wastewater transport, and therefore non-clogging operation of the systems is significantly important. However, the sewer system is quite often clogged by obstructions such as municipal garbage and sediment, which may be easily washed into sewers and lead to clogging and overflow of wastewater.

Consequently, environmental pollution as well as public hygienic problems may be caused.

Besides, unregulated sewer designing, such as faulty selection of sewer laying mode, sewer diameter, filling rate, laying slope and sewer material, may also lead to sewer clogging, siltation, or leakage. Conventionally, video surveillance by closed-circuit television (CCTV), laser profile analysis, sewer robots, and acoustic-based instruments (e.g., ultrasonic and sonar monitoring devices) have been used frequently to diagnose abnormalities in sewer system.

In recent years, machine learning-based methods, for example, qualitative trend analysis, random forests, support vector machines, have been employed coupled with monitoring devices, which represent progress in this field. Video surveillance by CCTV can clearly show the internal conditions of sewer, but identification results are usually subjective because this method highly depends on human judgement. Laser profile analysis identifies sewer clogging by constructing a three-dimensional model of the sewer, which is difficult to be achieved in the case of clogging and water accumulation in the sewer. A sewer robot can perform visual testing, non-destructive testing, sewer repair and other tasks, but the complexity of the sewer brings significant challenges to robot operation. The acoustic principle-based method is capable of obtaining acoustic characteristics of sewer conditions, butthe method is limited by a fault extraction approach of acoustic signals, and the accuracy of detecting abnormalities is too low. Thus, this method may not be applied in practice. Due to the above limitations, machine learning-based identification methods need to be further improved.

SUMMARY

To solve the technical problem in the background art, the present disclosure provides a method and system for identifying and positioning clogging of a sewer to monitor levels of inspection wells in real time with level gauges, and position clogging points and siltation sections of the sewer through analysis of change rules of level data. The present disclosure enables to quickly and accurately identify and position clogging and siltation points, and ensure stable operation of sewers. A method for identifying and positioning clogging of a sewer comprises the following steps:

S1: arranging a plurality of level gauges designated LG1, LG2 ... LGi ... LGn on a sewer to be detected in sections;

S2: acquiring level data from LG1-LGn in real time, and pre-processing the level data; and

S3: performing differential calculation on time series of changes in the pre- processed level data from LG1-LGn, and identifying, positioning and determining a clogging point based on a calculation result which comprises:

A. in the case that a differential value of the time series of the level data from

LGi is negative, and negative differential values of the time series of the level data from

LG(i+1)-LGn occur successively with time, determining that the clogging point/section is before LGi;

B. in the case that the differential value of the time series of the level data from

LGiis a great positive value, and negative differential values of the time series of the level data from LG(i+1)-LGn occur successively with time, determining that the clogging point/section is behind LG and close to LGi; and

C. in the case that the level data from LGi has no significant change, and negative differential values of the time series of the level data from LG(i+1)-LGn occur successively with time, determining that the clogging point/section is between LGi and

LG(i+1).

In step S3, the performing differential calculation on time series of changes in the pre-processed level data from LG1-LGn comprises: measuring a wastewater level value by the level gauge LGi at time T1 as h1, measuring a wastewater level value at time T2 after t seconds as h2 at a sampling frequency of t seconds, and calculating a differential value of the level data from the level gauge at T1 as (h2-h1)/t, which reflects a level change trend of the level gauge LGi after T1.

Further, in step S1, a spacing between two adjacent level gauges LGi and

LG(i+1) on the same sewer is less than 50 meters.

In step S2, the level data from the level gauges is pre-processed based on analysis of historical statistical data, and data of the level changes caused by normal wastewater fluctuation is eliminated.

A system for identifying and positioning clogging of a sewer, comprises. an online monitoring instrumentation and a programmable logic controller; wherein the online monitoring instrumentation comprises a plurality of level gauges and flowmeters arranged on the sewer; the programmable logic controller is provided with an analog signal input terminal, a signal input integrated unit, an I/O integration unit, a TCP/IP port, a signal output integration unit, a power master control switch, an AC/DC power adapter, a micro-computer, and an industrial router; wherein the input terminal is configured to acquire monitoring data transmitted by the level gauges and the flowmeters, and transmit the monitoring data to the micro-computer via the I/O integration unit and the TCP/IP port; and the micro-computer is provided with a clogging identification and positioning data processing program.

The micro-computer and the industrial router in the programmable logic controller constitute a remote transmission module, wherein the micro-computer is configured to process data and remotely transmit data, and the industrial router is configured to be connected to a network transmission medium.

The system for identifying and positioning clogging of a sewer further comprises: acloud service device, wherein the programmable logic controller is provided with a remote transmission module which is configured to upload the monitoring data and a determination result of clogging identification and positioning of the sewer to a cloud service system.

The cloud service system is provided with a mobile terminal via which a user connects the cloud service device to acquire the determination result of clogging identification and positioning.

The present disclosure achieves the following beneficial effects:

First, traditionally sewers are desilted and dredged only after wastewater overflows due to clogging, and such operation and maintenance management manner is hysteretic and may cause public health risk. However, the present disclosure enables timely detection of clogging points and siltation sections of the sewer, and automatic alarm to ensure stable operation of the sewer.

Second, the present disclosure mainly serves identification and positioning of clogging of the sewer, and can visually present position information of the clogging point in an intuitive and clear manner, which provides great convenience for sewer operation and maintenance personnel.

Third, in addition to monitoring of sewer conditions, the present disclosure enables identification and positioning of water inlets from which groundwater permeates into the sewer due to damage of the sewer, and mixed connection points of rainwater and sewage and private connection points of industrial wastewater by means of flowmeters, which provides strong guarantee for the operation of the sewers.

Fourth, the on-line monitoring instrumentations, the programmable logic controller and other hardware used in the present disclosure are mature products in the market, and are easy to install and have stable performance. Therefore, the hardware devices of the present disclosure have good reliability.

Fifth, the remote transmission module of the present disclosure can transmit operation data to the cloud system, and the staff can view the operation of the system in real time and an alarm is generated in case of any abnormality of the sewer, which improve operation reliability and enables system optimization.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart of a method for identifying and positioning clogging of a sewer of the present disclosure;

FIG. 2 is a detailed flowchart of a method for identifying and positioning clogging of a sewer of the present disclosure;

FIG. 3 is a diagram of a control cabinet device;

FIG. 4 is a diagram of a pilot experiment device for identifying clogging of a sewer;

FIG. 5 is a diagram illustrating level changes of an inspection well 1 with an obstruction placed into an inspection well 2;

FIG. 6 is a diagram illustrating level changes of an inspection well 4 with an obstruction placed into an inspection well 5;

FIG. 7 is a diagram illustrating level changes of the inspection well 2 with an obstruction placed into an inspection well 3;

FIG. 8 is a diagram illustrating level changes of the inspection well 4 and an inspection well 6 with an obstruction placed into the inspection well 2;

FIG. 9 is a diagram illustrating level changes of the inspection well 4 and the inspection well 6 with an obstruction placed into the inspection well 3;

FIG. 10 is a diagram illustrating level changes of the inspection well 5 and the inspection well 6 with an obstruction placed into the inspection well 4;

FIG. 11 is a diagram of a field experiment system;

FIG. 12 is a diagram illustrating level changes from a level gauge LG1 in FIG. 11; and

FIG. 13 is a diagram illustrating level changes from a level gauge LG2 in FIG. 11. 5

Reference numerals in the drawings: 1-0n-line monitoring instrumentation; 2-electric control cabinet; 3—control center; 4- reading of flowmeter; 5-reading of level gauge; 6—clogging identification and positioning program; 7—power supply module; 8—level gauge; 9—elevated water tank; 10-water tank switch; 11-signal transmission line; 12-sewer; 13-grille; 14—flowmeter, 15-sewage treatment facility; 16—sewage treatment station; and 17-inspection well.

DETAILED DESCRIPTION

In order to facilitate understanding of the present disclosure by those skilled in the art, specific embodiments of the present disclosure are described below in conjunction with the accompanying drawings.

Example 1:

Referring to FIG. 3 and FIG. 4, a system for identifying and positioning clogging of a sewer 12 is illustrated. The system comprises an online monitoring instrumentation 1 and a programmable logic controller; wherein the online monitoring instrumentation 1 comprises a plurality of level gauges 8 and flowmeters 14 arranged on the sewer 12; the programmable logic controller is provided with an analog signal input terminal, a signal input integration unit, an I/O integration unit, a TCP/IP port, a signal output integration unit, a power master control switch, an AC/DC power adapter, a micro-computer, and an industrial router; wherein the input terminal is configured to acquire monitoring data transmitted by the level gauges 8 and the flowmeters 14, and transmit the monitoring data to the micro-computer via the I/O integration unit and the TCP/IP port; and the micro-computer is provided with a clogging identification and positioning data processing program.

The micro-computer and the industrial router in the programmable logic controller constitute a remote transmission module, the micro-computer is configured to process data and remotely transmit data, and the industrial router is configured to be connected to a network transmission medium.

The system for identifying and positioning clogging of a sewer further comprises a cloud service device, the programmable logic controller comprises a remote transmission module, and the remote transmission module is configured to upload the monitoring data and a determination result of clogging identification and positioning of the sewer 12 to a cloud service system.

Example 2:

A method for identifying and positioning clogging of a sewer of the present disclosure comprises the following steps: step 1, acquiring wastewater levels in the sewer by monitoring levels at key nodes of the sewer; step 2, extracting and pre-processing wastewater level data, and eliminating data of level changes caused by normal water fluctuations of the sewer based on a qualitative trend analysis method; step 3, performing differential calculation on time series of changes in the pre- processed level data, if a level differential value is a large positive value, and a level differential value of a downstream adjacent level monitoring point thereof is negative, determining that a section between the two level monitoring points is clogged, such that the clogging is identified and positioned; and step 4, sending a serial number of the clogged section to a control center, such that the staff dredge the positioned section.

The method specifically comprises the following steps:

S3: performing differential calculation on time series of changes in the pre- processed level data from LG1-LGn, and identifying, positioning and determining a clogging point based on a calculation result.

Step S1 is performed by an on-line monitoring system composed of level gauges arranged in inspection wells of the underground sewer, and the identifying and positioning in steps S2 and S3 is performed by a computer program, which all together constitute a system for identifying and positioning clogging of a sewer, thus discharging the wastewater smoothly, and preventing such problems as wastewater overflow caused by clogging and siltation of the sewer.

Example 3:

A method for identifying and positioning clogging of a sewer 12 of the present disclosure is obtained by fluid mechanics pilot experiments.

In the experiments, a PVC pipe was used as a sewer 12, parameters of the pipe are shown in Table 1, inspection wells 17 (totally 7 inspection wells) were arranged at bends and reducers, and level gauges 8 (totally 3 level gauges) were movably mounted. LG1 monitored levels of three inspection wells 17, namely JC1, JC2, and JC3; LG2 monitored levels of two inspection wells 17, namely JC4 and JC5; LG3 monitored levels of two inspection wells 17, namely JC6 and JC7; and a spacing between adjacent inspection wells is listed in Table 2. An elevated water tank 9 supplied water to the sewer 12, and domestic wastewater from a sewage treatment plant was supplied to the elevated water tank. A flow was adjusted by adjusting degree of opening of a water tank switch 10, and the level was controlled unchanged to keep the flow stable. Real-time data from the level gauges 8 and the flowmeters 14 were displayed in real time on reading 5 of level gauge and reading 4 of flowmeter in an electric control cabinet 2 and powered by a power module 7.

Table 1: Parameters of sewer 12 “Sewer diametemm Laying slope io

DNO 12

DNO 7

DNB00 5

DNB00 B

Table 2: Spacings between inspection wells 17 “Serial number of inspection well ~~ Spacing/m -JetJgc2z

JC2J03 sz

JC3JC4 208 -Jc4-Jcs

JCBVCB 28

JCC o8&

The specific process comprises the following steps: 1. turning on a power switch and the water tank switch 10 of the elevated water tank 9, and adjusting a flow to 1 m?h; 2. sequentially placing obstructions into the second inspection well JC2 to the seventh inspection well JC7, and recording the time of placing the obstructions into the inspection wells; 3. taking out the obstructions 5 minutes after the obstructions are placed into the inspection wells, and recording the time of taking out the obstructions; 4. pre-processing experimental data, and analyzing changes in level data before and after the obstructions are placed; 5. sequentially adjusting the flow to 2 m?h, 3 mh, 4 m%h, 5 mh, 6 m¥h, 7 mh, 8 m3/h, 9 m*h, and 10 mh; 6. repeating steps 2 to 4; and

The data was processed according to level changes before and after the obstructions were placed at an hourly flow increment from 1 mh to 10 m%h, and processing results are as illustrated in FIGS. 5 to 10. FIG. 5 illustrates the level change of the inspection well JC1 after the obstruction is placed into the inspection well JC2, FIG. 6 illustrates the level change of the inspection well JC4 after the obstruction is placed into the inspection well JC5, and FIG. 7 illustrates the level change of the inspection well JC2 after the obstruction is placed into the inspection well JC3. By comparing the change rule of the level data, it may be found through analysis of the data in FIG. 5 and FIG. 6 that when a clogging point is behind the level gauge and is close to the level gauge, the reading 5 of the level gauge before the clogging point shows level increase within a period of time after the obstruction is placed. As illustrated in FIG. 7, when the clogging point is before the level gauge and the level gauge is far from the clogging point, no significant change occurs to the data. FIG. 8 illustrates the level change of the inspection wells JC4 and JC6 after the obstruction is placed into the inspection well JC2, FIG. 9 illustrates the level change of the inspection wells JC4 and JC6 after the obstruction is placed into the inspection well JC3, and FIG. 10 illustrates the level change of the inspection well JC5 and JC6 after the obstruction is placed into the inspection well JC4. According to analysis with reference to

FIG. 8, FIG. 9, and FIG. 10, the change rule of the level data from the level gauges behind the clogging point is as follows: the reading 5 of the liquid gauge close to the placement position of the obstruction decreases firstly, and then the data of the level gauge far from the placement position of the obstruction shows a level decrease. Accordingly, the following conclusions may be reached: 1. In the case that the level from LGi decreases, and the levels from LG(i+1)-

LGn decrease successively with time, it is determined that the clogging point/section is before LGi. 2. In the case that the level from LGi increases, and the levels from LG(i+1)-LGn decrease successively with time, it is determined that the clogging point/section is behind

LGi and close to LGi. 3. In the case that the level from LGi has no significant change, and the levels from LG(i+1)-LGn successively decrease with time, it is determined that the clogging point/section is between LGi and LG(i+1).

If the above-mentioned three cases occur, and the level gauge showing decreasing level returns to the original value over a period of time or some level gauges are repeatedly subject to the above-mentioned cases in different periods of time, it is determined that the sections corresponding to these levels are clogged and silted.

Further, in order to the change in wastewater level before and after clogging and siltation more obvious, in combination with the qualitative trend analysis method, the level data acquired by the level gauges was pre-processed and the data of the level changes caused by the normal flow fluctuation was eliminated, and the time series of the level data were subject to differential calculation. In combination with differential values of the time series of the level data, a final conclusion may be reached as follows:

LGi is negative, and negative differential values of the time series of the level data of

LG(i+1)-LGn occur successively with time, it is determined that a clogging point/section is before LGi;

LGi is a great positive value, and negative differential values of the time series of the level data from LG(i+1)-LGn a occur successively with time, it is determined that the clogging point/section is behind LG and close to LGi; and

C. in the case that level data from LGi has no significant change, and negative differential values of the time series of the level data from LG(i+1)-LGn occur successively with time, it is determined that the clogging point/section is between LGi and LG(i+1).

Example 4:

Based on the fluid mechanics pilot experiments of clogging identification, a productive verification experiment of clogging identification was carried out in a village of a city. Level gauges were mounted at an end of a municipal sewer and at the grille 13 to identify and position clogging points of a sewer 12, and monitor for clogging of the grille 13.

The domestic wastewater was collected by the sewer 12 and transferred to a sewage treatment facility 15 for treatment after passing through the grille. At the same time, the flowmeter 14 monitored the flow of the domestic wastewater entering a sewage treatment station 16 in real time to identify and position the clogging and siltation point and section of the sewer 12 so as to guarantee stable operation of the sewer 12. The monitoring devices comprised the level gauges and the flowmeters 14 which were arranged as shown in FIG. 11, and the monitoring data is as illustrated in FIG. 12 and FIG. 13.

By monitoring the level change of the wastewater using the level gauge LG1 in

FIG. 12, a significant level rise was found. As two upstream level gauges thereof had no significant level change before this period of time, it may be concluded that the section before a grille 13 in the downstream of the level gauge had clogging and siltation, which was confirmed through field observation.

By monitoring the level change of the wastewater using the level gauge LG2 in

FIG. 13, a significant level rise was found. As two upstream level gauges thereof had no significant level change before this period of time, it may be concluded that a section of the sewer 12 close to the level gauge LG2 (less than 5 m away from the level gauge LG2) in the downstream thereof had clogging and siltation, which was confirmed through field observation.

Described above are merely exemplary embodiments of the present disclosure, butare not intended to limit the protection scope of the present disclosure. Any modification, equivalent replacement and improvement made without departing from the spirit and principle of the present disclosure should fall within the protection scope of the present disclosure.

Claims

CONCLUSIONS

1. A method for detecting and locating blockages in a sewer, the method comprising the steps of: S1: setting up a large number of level sensors designated LG1, LG2, ..., LGi, ..., LGn on a sewer to be examined in sections; S2: obtaining level values from LG1-LGn in real time and preprocessing the level values; and S3: performing differential calculations on time series of changes in the pre-processed level values obtained from LG1-LGn, and identifying, locating and determining a blockage based on calculated results, which consist of:

A. in the situation that a differential value of the time series of the level values of LGi is negative, and negative differential values of the time series of the level values of LG(i+1)-LGn occur consecutively in time, determining that a blockage point/section is located in front of LGi;

B. in the case that the differential value of the time series of the level values of LGi is a larger positive value, and negative differential values of the time series of the level values of LG(i+1)-LGn occur consecutively with the time, determining that the obstruction point/section is located behind LG and close to LGi; and

C. in the case that the level values of LGi have no significant change, and negative differential values of the time series of the level values of LG(i+1)-LGn occur consecutively in time, determining that the blockage point /section is located between LGi and LG(i+1).

The method for detecting and locating blockages in a sewer according to claim 1, wherein in step S3 performing the differential calculation on time series of changes in the preprocessed level values obtained from LG1-LGn comprises: measuring as h1 of a waste water level value by the level sensor LGi at time T1, and measuring a waste water level value after t seconds as h2 at time T2 with a sampling frequency of t seconds, and measuring it at T1 as (h2-h1)/t calculating a difference value of the level

values of the level sensor LGi, which reflects a level change trend of the level sensor LGi after T1.

The method for detecting and locating blockages in a sewer according to claim 1, wherein in step S1 a distance between two adjacent level sensors LGi and LG(i+1) in the same sewer is less than 50 meters.

4. The method for detecting and locating blockages in a sewer according to claim 1, wherein in step S2 the level values of the level sensors are preprocessed on the basis of analysis of historical statistical data, and data of the level changes caused by normal fluctuations in the wastewater are eliminated.

5. A system for detecting and locating blockages in a sewer, comprising: an on-line monitoring instrument and a programmable logic controller; wherein the online monitoring instrument includes a plurality of level sensors and flow sensors disposed on a sewer; the programmable logic controller is equipped with an analog signal input terminal, a signal input integration unit, a |/O integration unit, a TCP/IP port, a signal output integration unit, a main power switch, an AC/DC -power adapter, a microcomputer and an industrial router; wherein the input terminal is arranged to obtain monitoring data output from the level sensors and the flow meters and to transmit the monitoring data to the microcomputer via the I/O integration unit and the TCP/IP port; and wherein the microcomputer is provided with a blockage identification and location determination data processing program.

6. The system for detecting and locating blockages in a sewer according to claim 5, wherein the microcomputer and the industrial router in the programmable logic controller form a remote transmission module, the microcomputer being adapted to process and respond to data transmit data remotely and the industrial router is designed to be connected to a network transmission medium.

7. The system for detecting and locating blockages in a sewer according to claim 5, further comprising: a cloud service device, wherein the programmable logic controller includes an external transfer module adapted to transmit the monitoring data and a blockage identification determination result and location of the sewer to a cloud service system.

The sewer blockage detection and location system according to claim 7, wherein the cloud service system includes a portable terminal through which a user connects the cloud service device to obtain the blockage identification and location determination result.