CN114637056A - Pipeline detection control method and system based on Internet of things - Google Patents
Pipeline detection control method and system based on Internet of things Download PDFInfo
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- CN114637056A CN114637056A CN202210243655.6A CN202210243655A CN114637056A CN 114637056 A CN114637056 A CN 114637056A CN 202210243655 A CN202210243655 A CN 202210243655A CN 114637056 A CN114637056 A CN 114637056A
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- G01S13/885—Radar or analogous systems specially adapted for specific applications for ground probing
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- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/887—Radar or analogous systems specially adapted for specific applications for detection of concealed objects, e.g. contraband or weapons
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Abstract
The application discloses a pipeline detection control method and system based on the Internet of things, and relates to the technical field of underground pipeline exploration, wherein the method comprises the following steps: acquiring pipeline information of a target pipeline; selecting a primary detection scheme and a secondary detection scheme from a plurality of preset detection schemes based on the pipeline information; detecting the target pipeline according to the primary detection scheme to obtain a first detection result; judging whether the first detection result is accurate or not based on an underground pipeline laying standard; if the first detection result is accurate, taking the first detection result as a final detection result; if the first detection result is inaccurate, detecting the target pipeline according to the secondary detection scheme to obtain a second detection result; and correcting the first detection result according to the second detection result to obtain the final detection result. The method and the device have the effects of selecting a proper detection scheme for detection and obtaining a relatively accurate detection result.
Description
Technical Field
The application relates to the technical field of underground pipeline exploration, in particular to a pipeline detection control method and system based on the Internet of things.
Background
Before the construction of some large projects, underground pipelines in a planned construction site need to be detected, and the detection task is to find the laying condition of various underground pipelines, the projection position and the depth on the ground, and set pipeline point marks on the ground so as to measure the coordinates and the elevation of pipeline points or carry out the mapping of underground pipeline diagrams. Its purpose is in order to protect existing underground pipeline, prevents to cause the destruction to the pipeline during the construction. In the actual detection process, a detector needs to perform initial on-site investigation, then selects a proper detection scheme for detection through experience, and finally draws an underground pipeline diagram according to the detection result.
With respect to the related art among the above, the inventors consider that the following drawbacks exist: if the environment of the construction site is complex, the detection scheme selected by the detector through experience may be inappropriate, so that the detection result is inaccurate easily.
Disclosure of Invention
In order to overcome the defect that detection results are inaccurate due to improper detection scheme selection, the application provides a pipeline detection control method and system based on the Internet of things.
In a first aspect, the application provides a pipeline detection control method based on the internet of things, which includes the following steps:
acquiring pipeline information of a target pipeline;
selecting a primary detection scheme and a secondary detection scheme from a plurality of preset detection schemes based on the pipeline information;
detecting the target pipeline according to the primary detection scheme to obtain a first detection result;
judging whether the first detection result is accurate or not based on an underground pipeline laying standard;
if the first detection result is accurate, taking the first detection result as a final detection result;
if the first detection result is inaccurate, detecting the target pipeline according to the secondary detection scheme to obtain a second detection result;
and correcting the first detection result according to the second detection result to obtain the final detection result.
By adopting the technical scheme, the pipeline information of the target pipeline is obtained firstly, two schemes, namely a proper primary detection scheme and a proper secondary detection scheme, are selected according to the pipeline information, then the primary detection scheme is utilized for carrying out primary detection to obtain a first detection result, whether the first detection result is accurate or not can be judged according to the laying standard of the underground pipeline, if so, the first detection result is directly used as a final detection result, and detection is not required again; if the first detection result is inaccurate, the secondary detection scheme can be adopted for detecting again, and the inaccurate first detection result is corrected through a second detection result obtained by the secondary detection scheme, so that a final detection result is obtained.
Optionally, the acquiring the pipeline information of the target pipeline includes the following steps:
defining a detection area of a target pipeline based on an underground pipeline laying standard;
randomly selecting a plurality of pre-detection points in the detection area;
pre-detecting the pre-detection point by using a detector, and acquiring a pre-detection result of the detector;
and obtaining the pipeline information of the target pipeline based on the pre-detection result.
By adopting the technical scheme, the design and the laying of the underground pipeline need to take the surrounding specific environment into consideration, so that a detection area with high probability of having the target pipeline can be defined according to the laying standard of the underground pipeline, then a plurality of detection points are randomly selected from the defined detection area to be used for the detection instrument to carry out the pre-detection, and the pipeline information of the target pipeline can be obtained through analysis according to the pre-detection result of the detection instrument, thereby being beneficial to selecting a proper detection scheme according to the pipeline information in the follow-up process.
Optionally, the randomly selecting a plurality of pre-probe points in the probe region includes the following steps:
judging whether an area graph formed by the detection area is circular or not;
if the region graph is circular, constructing a region polar coordinate system by taking the circle center of the region graph as an origin;
randomly generating a plurality of probe polar coordinates in the region polar coordinate system, and taking a point corresponding to the probe polar coordinate in the region polar coordinate system as a pre-probe point;
if the area graph is not circular, judging whether the area graph is rectangular or not;
if the region graph is rectangular, constructing a region rectangular coordinate system by taking any vertex of the region graph as an origin;
and randomly generating a plurality of probe point coordinates in the region rectangular coordinate system, and taking the corresponding point of the probe point coordinates in the region rectangular coordinate system as the pre-probe point.
By adopting the technical scheme, the detection area is usually defined as a circle or a rectangle, and different modes can be adopted for selection according to different area patterns formed by the detection area in order to ensure the randomness of the selection of the pre-detection points in the detection area. If the region graph is circular, a region polar coordinate system can be constructed, probe point polar coordinates in the region polar coordinate system are randomly generated, and points corresponding to the probe point polar coordinates are used as pre-probe points. If the region graph is rectangular, a region rectangular coordinate system can be constructed, probe point coordinates can be randomly generated, and then points corresponding to the probe point coordinates in the region rectangular coordinate system serve as pre-probe points.
Optionally, the method further comprises the following steps:
if the region graph is not a rectangle, generating a virtual rectangle which covers the region graph and has the smallest area;
constructing a virtual rectangular coordinate system by taking any vertex of the virtual rectangle as an origin;
randomly generating virtual coordinates in a plurality of virtual rectangular coordinate systems;
judging whether the virtual coordinate falls into the range of the region graph or not;
if the virtual coordinate falls into the range of the area graph, reserving the virtual coordinate;
if the virtual coordinate does not fall into the range of the area graph, deleting the virtual coordinate;
and taking the corresponding points of all the virtual coordinates in the virtual rectangular coordinate system as the pre-detection points.
By adopting the technical scheme, due to the fact that the complexity degree of the construction environment is high in a few cases, the detection region is difficult to be defined as a circle or a rectangle but other polygons or irregular figures, a virtual rectangle can be generated at the moment, the virtual rectangle is a rectangle which can contain the figures of the whole region and has the smallest area, and the smallest area is beneficial to shortening the calculation process of the following steps of random point selection, judgment and the like. After the virtual rectangle is generated, a virtual rectangular coordinate system is constructed by taking any vertex of the virtual rectangle as an origin, a plurality of virtual coordinates are generated, points corresponding to the generated virtual coordinates may fall outside the range of the regional graph, therefore, the virtual coordinates need to be judged, if the points are outside the range of the regional graph, the virtual coordinates are deleted, and finally, points corresponding to all the virtual coordinates which are not deleted are used as pre-probing points.
Optionally, the pipeline information includes a buried depth and a pipeline type, and the obtaining the pipeline information of the target pipeline based on the pre-detection result includes the following steps:
extracting the pre-detection depth and the pre-detection angle in the pre-detection result;
correcting the pre-exploration depth according to the pre-exploration angle to obtain the buried depth of the target pipeline;
acquiring the electromagnetic induction state of the target pipeline based on the pre-detection result;
and analyzing the electromagnetic induction state to obtain the pipeline type of the target pipeline.
By adopting the technical scheme, the detection pipe in the detector carries out deep pre-detection from the pre-detection point, and when the target pipeline is pre-detected, the detector can carry out electromagnetic induction detection and output a pre-detection result. The pre-detection result comprises a pre-detection angle when the target pipeline is detected deeply and a pre-detection depth when the target pipeline is detected deeply, the buried depth of the target pipeline can be calculated by combining the pre-detection depth and the pre-detection angle, and the pipeline type of the target pipeline can be analyzed according to the electromagnetic induction state of the target pipeline obtained by electromagnetic induction detection.
Optionally, the pipe types include a metal pipe and a non-metal pipe, and the selecting a primary detection scheme and a secondary detection scheme from a plurality of preset detection schemes based on the burial depth and the pipe type includes the following steps:
judging whether the pipeline type is the metal pipeline or the non-metal pipeline;
if the pipeline type is the non-metal pipeline, selecting a primary detection scheme and a secondary detection scheme from a plurality of preset detection schemes according to the burial depth;
if the pipeline type is the metal pipeline, selecting an electromagnetic induction detection scheme as a primary detection scheme;
judging whether the buried depth is greater than a preset first depth threshold value or not;
if the buried depth is greater than the first depth threshold value, selecting a geological radar detection scheme as a secondary detection scheme;
and if the buried depth is less than or equal to the first depth threshold value, selecting a high-density electric detection scheme as a secondary detection scheme.
By adopting the technical scheme, the preset detection scheme comprises the detection scheme of only detecting the metal pipeline or only detecting the nonmetal pipeline, so that the type of the pipeline of the target pipeline needs to be judged firstly, if the pipeline is the metal pipeline, the most applicable electromagnetic induction detection scheme can be directly selected as the primary detection scheme, and the secondary detection scheme needs to be selected by combining the burial depth of the target pipeline. The geological radar detection scheme is more beneficial to detecting deeper pipelines, so that when the burial depth is greater than a preset first depth threshold value, the geological radar detection scheme is selected as a secondary detection scheme; the high-density electric detection scheme needs to arrange electrodes and measuring lines underground, so that the high-density electric detection scheme is not suitable for underground pipelines with extremely deep buried depths, and when the buried depth is less than or equal to a first depth threshold value, the high-density electric detection scheme is selected as a secondary detection scheme.
Optionally, the selecting a primary detection scheme and a secondary detection scheme from a plurality of preset detection schemes according to the burial depth includes the following steps:
judging whether the buried depth is greater than the first depth threshold value;
if the burial depth is less than or equal to the first depth threshold value, selecting a drilling detection scheme as a primary detection scheme, and selecting the geological radar detection scheme as a secondary detection scheme;
if the buried depth is greater than the first depth threshold value, selecting the geological radar detection scheme as a primary detection scheme;
judging whether the buried depth is greater than a preset second depth threshold value, wherein the second depth threshold value is greater than the first depth threshold value;
if the buried depth is less than or equal to the second depth threshold value, selecting the drill rod detection scheme as a secondary detection scheme;
and if the buried depth is greater than the second depth threshold value, selecting the high-density electric detection scheme as a secondary detection scheme.
By adopting the technical scheme, when the target pipeline is a non-metal pipeline, the burial depth is graded according to a preset first depth threshold value and a preset second depth threshold value, if the burial depth is smaller than or equal to the first depth threshold value, the target pipeline is buried shallowly, a drill rod detection scheme can be directly selected as a primary detection scheme, and a geological radar detection scheme is selected as a secondary detection scheme; if the buried depth is greater than the first depth threshold value and less than or equal to the second depth threshold value, selecting a geological radar detection scheme as a primary detection scheme, and using a drilling detection scheme as a secondary detection scheme; and if the buried depth is greater than the second depth threshold value, selecting a geological radar detection scheme as a primary detection scheme, and taking a high-density electric detection scheme as a secondary detection scheme.
In a second aspect, the present application further provides an internet of things-based pipeline detection control system, which includes a memory, a processor, and a program stored in the memory and executable on the processor, where the program is capable of being loaded and executed by the processor to implement the internet of things-based pipeline detection control method as described in the first aspect.
By adopting the technical scheme, the pipeline information of the target pipeline is obtained firstly through calling of the program, two schemes, namely a proper primary detection scheme and a proper secondary detection scheme, are selected according to the pipeline information, then the primary detection scheme is utilized for carrying out primary detection to obtain a first detection result, whether the first detection result is accurate or not can be judged according to the laying standard of the underground pipeline, and if the first detection result is accurate, the first detection result is directly used as a final detection result without carrying out detection again; if the first detection result is inaccurate, the secondary detection scheme can be adopted for detecting again, and the inaccurate first detection result is corrected through a second detection result obtained by the secondary detection scheme, so that a final detection result is obtained.
In summary, the present application includes at least one of the following beneficial technical effects:
1. firstly, acquiring pipeline information of a target pipeline, selecting a proper primary detection scheme and a proper secondary detection scheme according to the pipeline information, then carrying out primary detection by using the primary detection scheme to obtain a first detection result, judging whether the first detection result is accurate according to the laying standard of the underground pipeline, and if so, directly taking the first detection result as a final detection result without carrying out detection again; and if the first detection result is inaccurate, the secondary detection scheme can be adopted for detecting again, and the inaccurate first detection result is corrected through a second detection result obtained by the secondary detection scheme, so that a final detection result is obtained.
2. In order to ensure the randomness of the selection of the pre-detection points in the detection area, the selection can be performed in different modes according to different area patterns formed by the detection area. If the region graph is circular, a region polar coordinate system can be constructed, probe point polar coordinates in the region polar coordinate system are randomly generated, and points corresponding to the probe point polar coordinates are used as pre-probe points. If the region graph is rectangular, a region rectangular coordinate system can be constructed, probe point coordinates can be randomly generated, and then points corresponding to the probe point coordinates in the region rectangular coordinate system serve as pre-probe points.
Drawings
Fig. 1 is a schematic flow chart of a pipeline detection control method based on the internet of things according to an embodiment of the present application.
Fig. 2 is a schematic flowchart of acquiring pipe information of a target pipe according to an embodiment of the present application.
Fig. 3 is a schematic flow chart of randomly selecting a plurality of pre-probing points according to an embodiment of the present application.
FIG. 4 is a schematic flow chart illustrating a process of generating a virtual rectangle and selecting a pre-probe point according to an embodiment of the present application.
Fig. 5 is a schematic flow chart of obtaining pipeline information based on a pre-probing result according to an embodiment of the present application.
FIG. 6 is a schematic flow chart illustrating a detection scheme based on the buried depth and the type of the pipeline according to an embodiment of the present application.
Fig. 7 is a flow chart illustrating a detection scheme according to a buried depth according to an embodiment of the present application.
Detailed Description
The present application is described in further detail below with reference to figures 1-7.
The embodiment of the application discloses a pipeline detection control method based on the Internet of things.
Referring to fig. 1, the pipeline detection control method based on the internet of things includes the following steps:
101, acquiring the pipeline information of the target pipeline.
The pipeline information can be obtained by obtaining a design drawing of a target pipeline, and the pipeline information can also be obtained by a pre-detection mode.
And 102, selecting a primary detection scheme and a secondary detection scheme from a plurality of preset detection schemes based on the pipeline information.
And 103, detecting the target pipeline according to the primary detection scheme to obtain a first detection result.
104, judging whether the first detection result is accurate or not based on the underground pipeline laying standard, and if so, executing a step 105; if not, go to step 106.
And 105, taking the first detection result as a final detection result.
And 106, detecting the target pipeline according to the secondary detection scheme to obtain a second detection result.
And 107, correcting the first detection result through the second detection result to obtain a final detection result.
And judging inaccurate data in the first detection result according to the underground pipeline laying standard, and replacing the inaccurate data by adopting corresponding data in the second detection result.
The implementation principle of the embodiment is as follows:
firstly, acquiring pipeline information of a target pipeline, selecting a proper primary detection scheme and a proper secondary detection scheme according to the pipeline information, then carrying out primary detection by using the primary detection scheme to obtain a first detection result, judging whether the first detection result is accurate according to the laying standard of the underground pipeline, and if so, directly taking the first detection result as a final detection result without carrying out detection again; and if the first detection result is inaccurate, the secondary detection scheme can be adopted for detecting again, and the inaccurate first detection result is corrected through a second detection result obtained by the secondary detection scheme, so that a final detection result is obtained.
In step 101 of the embodiment shown in fig. 1, pipeline information of a target pipeline is obtained by a pre-probing method, and before the pre-probing, a probing area needs to be defined and a pre-probing point needs to be randomly selected. This is illustrated in detail by the embodiment shown in fig. 2.
Referring to fig. 2, acquiring the pipe information of the target pipe includes the steps of:
and 201, defining a detection area of the target pipeline based on underground pipeline laying standards.
A plurality of pre-probe points are randomly selected 202 in the probe region.
And 203, pre-probing the pre-probing point by using a probe, and acquiring a pre-probing result of the probe.
And 204, obtaining the pipeline information of the target pipeline based on the pre-detection result.
The implementation principle of the embodiment is as follows:
the design and the laying of the underground pipeline need to consider the surrounding specific environment, so that a detection area with high probability of the existence of the target pipeline can be defined according to the laying standard of the underground pipeline, a plurality of detection points are randomly selected from the defined detection area for the pre-detection of the detection instrument, the pipeline information of the target pipeline can be obtained by analysis according to the pre-detection result pre-detected by the detection instrument, and the selection of a proper detection scheme according to the pipeline information is facilitated subsequently.
In step 202 of the embodiment shown in fig. 2, the area pattern formed by the detection area is generally circular or rectangular, and different coordinate systems can be established according to different area patterns, and then coordinates are randomly generated and a pre-detection point is selected according to the coordinates. This is explained in detail with reference to the embodiment shown in fig. 3.
Referring to fig. 3, the step of randomly selecting a plurality of pre-probing points includes the following steps:
301, determining whether the area pattern formed by the detection area is circular, if so, executing step 302; if not, go to step 304.
302, a region polar coordinate system is constructed with the center of the region graph as the origin.
303, randomly generating a plurality of probe polar coordinates in the region polar coordinate system, and taking the corresponding point of the probe polar coordinates in the region polar coordinate system as a pre-probe point.
The method comprises the steps of randomly generating a plurality of polar diameter values and a plurality of polar angle values by taking the edge of a region graph as a value upper limit, and randomly combining the plurality of polar diameter values and the plurality of polar angle values to obtain a plurality of probe polar coordinates.
304, determine whether the area graph is rectangular, if so, execute step 305.
A region rectangular coordinate system is constructed with any vertex of the region graph as an origin 305.
And 306, randomly generating probe point coordinates in a plurality of region rectangular coordinate systems, and taking the corresponding points of the probe point coordinates in the region rectangular coordinate systems as pre-probe points.
The method comprises the steps of randomly generating a plurality of X-axis values and a plurality of Y-axis values by taking the edge of an area graph as a value upper limit, and randomly combining the X-axis values and the Y-axis values to obtain a plurality of probe point coordinates.
The implementation principle of the embodiment is as follows:
in general, the detection area is defined as a circle or a rectangle, and in order to ensure the randomness of the selection of the pre-detection points in the detection area, the selection can be performed in different ways according to different area patterns formed by the detection area. If the region graph is circular, a region polar coordinate system can be constructed, probe point polar coordinates in the region polar coordinate system are randomly generated, and points corresponding to the probe point polar coordinates are used as pre-probe points. If the region graph is rectangular, a region rectangular coordinate system can be constructed, probe point coordinates can be randomly generated, and then points corresponding to the probe point coordinates in the region rectangular coordinate system serve as pre-probe points.
In step 304 of the embodiment shown in fig. 3, if the area pattern is not a rectangle and not a circle, but is another polygon or an irregular pattern, a virtual rectangle covering the whole area pattern may be generated, and then the pre-probing point is selected by combining the virtual rectangle. This is explained in detail with reference to the embodiment shown in fig. 4.
Referring to fig. 4, generating a virtual rectangle and selecting a pre-probe point includes the following steps:
when the region pattern is not a rectangle, a virtual rectangle having the smallest area and covering the region pattern is generated 401.
A virtual rectangular coordinate system is constructed with any vertex of the virtual rectangle as the origin 402.
At 403, virtual coordinates in a plurality of virtual rectangular coordinate systems are randomly generated.
The method comprises the steps of randomly generating a plurality of virtual X-axis values and a plurality of virtual Y-axis values by taking the edge of a regional graph as a value upper limit, and randomly combining the plurality of virtual X-axis values and the plurality of virtual Y-axis values to obtain a plurality of virtual coordinates.
404, judging whether the virtual coordinate falls into the range of the area graph, if so, executing a step 405; if not, go to step 406.
The virtual coordinates are retained 405.
406, the virtual coordinates are deleted.
And 407, taking the corresponding points of all the virtual coordinates in the virtual rectangular coordinate system as the pre-detection points.
The implementation principle of the embodiment is as follows:
in a few cases, due to the fact that the complexity of the construction environment is high, the detection region is difficult to be defined as a circle or a rectangle, but other polygons or irregular figures are adopted, a virtual rectangle can be generated at the moment, the virtual rectangle is a rectangle which can contain the figure of the whole region and has the smallest area, and the smallest area is beneficial to shortening the calculation process of the following steps of random point selection, judgment and the like. After the virtual rectangle is generated, a virtual rectangular coordinate system is constructed by taking any vertex of the virtual rectangle as an origin, a plurality of virtual coordinates are generated, points corresponding to the generated virtual coordinates may fall outside the range of the regional graph, therefore, the virtual coordinates need to be judged, if the points are outside the range of the regional graph, the virtual coordinates are deleted, and finally, points corresponding to all the virtual coordinates which are not deleted are used as pre-probing points.
In step 204 of the embodiment shown in fig. 2, the pipeline information includes a burial depth and a pipeline type, the burial depth of the target pipeline can be calculated through the pre-detection depth and the pre-detection angle in the pre-detection result, and the pipeline type of the target pipeline can be obtained through analysis of the electromagnetic induction state in the pre-detection result. This is explained in detail with reference to the embodiment shown in fig. 5.
Referring to fig. 5, obtaining the pipeline information based on the pre-probing result includes the following steps:
and 501, extracting the pre-detection depth and the pre-detection angle in the pre-detection result.
The pre-detection depth is the depth of a detection tube in the detector penetrating into the ground when the detection tube is pre-detected to a target pipeline, and the pre-detection angle is the angle formed by the detection tube and a plumb line when the detection tube is pre-detected to the target pipeline.
And 502, correcting the pre-exploration depth according to the pre-exploration angle to obtain the buried depth of the target pipeline.
And calculating the vertical distance between the target pipeline and the ground according to the trigonometric function, namely the burial depth of the target pipeline.
And 503, acquiring the electromagnetic induction state of the target pipeline based on the pre-detection result.
The electromagnetic induction detector at the head of the detection pipe is used for carrying out electromagnetic induction detection on the target pipeline, so that the electromagnetic induction state of the target pipeline, which is detected by the electromagnetic induction, is stored in a pre-detection result.
And 504, analyzing the electromagnetic induction state to obtain the pipeline type of the target pipeline.
The implementation principle of the embodiment is as follows:
and the detection tube in the detector is used for carrying out deep pre-detection from a pre-detection point, and when the target pipeline is pre-detected, the detector can carry out electromagnetic induction detection and output a pre-detection result. The pre-detection result comprises a pre-detection angle when the target pipeline is deep and a pre-detection depth when the target pipeline is pre-detected, the buried depth of the target pipeline can be calculated by combining the pre-detection depth and the pre-detection angle, and the pipeline type of the target pipeline can be analyzed according to the electromagnetic induction state of the target pipeline obtained by electromagnetic induction detection.
In step 102 of the embodiment shown in fig. 1, the pipe types include a metal pipe and a non-metal pipe, and the predetermined multiple detection schemes include a drill rod detection scheme, a geological radar detection scheme, a high-density electrical detection scheme, a high-density magnetic detection scheme, an electromagnetic induction detection scheme, an artificial earthquake detection scheme, and the like. And selecting a proper primary detection scheme and a proper secondary detection scheme according to the buried depth and the type of the pipeline. This is explained in detail with reference to the embodiment shown in fig. 6.
Referring to fig. 6, selecting a detection scheme based on the burial depth and the type of pipeline includes the steps of:
601, judging whether the pipeline type is a metal pipeline or a non-metal pipeline, and if the pipeline type is the non-metal pipeline, executing a step 602; if the metal pipe is a metal pipe, step 603 is executed.
And 602, selecting a primary detection scheme and a secondary detection scheme from a plurality of preset detection schemes according to the buried depth.
603, selecting an electromagnetic induction detection scheme as a primary detection scheme.
604, determining whether the buried depth is greater than a preset first depth threshold, if so, executing step 605; if not, go to step 606.
A geological radar detection scheme is selected 605 as a secondary detection scheme.
And 606, selecting a high-density electric detection scheme as a secondary detection scheme.
The implementation principle of the embodiment is as follows:
the preset detection scheme comprises a detection scheme for detecting only the metal pipeline or only the nonmetal pipeline, so that the type of the target pipeline needs to be judged firstly, if the target pipeline is the metal pipeline, the most applicable electromagnetic induction detection scheme can be directly selected as a primary detection scheme, and a secondary detection scheme needs to be selected by combining the burial depth of the target pipeline. The geological radar detection scheme is more beneficial to detecting deeper pipelines, so that when the buried depth is greater than a preset first depth threshold value, the geological radar detection scheme is selected as a secondary detection scheme; the high-density electric detection scheme needs to arrange electrodes and measuring lines underground, so that the high-density electric detection scheme is not suitable for underground pipelines with extremely deep buried depths, and when the buried depth is less than or equal to a first depth threshold value, the high-density electric detection scheme is selected as a secondary detection scheme.
In step 602 of the embodiment shown in fig. 6, when the pipe type is a non-metal pipe, a drilling detection scheme, a geological radar detection scheme and a high-density electrical detection scheme are more suitable, and further selection is performed in combination with the burial depth. This is explained in detail with reference to the embodiment shown in fig. 7.
Referring to fig. 7, selecting a detection scheme according to the buried depth includes the steps of:
701, judging whether the buried depth is larger than a first depth threshold value, if not, executing a step 702; if yes, go to step 703.
And 702, selecting a drill rod detection scheme as a primary detection scheme, and selecting a geological radar detection scheme as a secondary detection scheme.
703, selecting a geological radar detection scheme as a primary detection scheme.
704, determining whether the buried depth is greater than a preset second depth threshold, if not, executing step 705; if yes, go to step 706.
Wherein the second depth threshold is greater than the first depth threshold.
705, selecting a drill rod detection scheme as a secondary detection scheme.
And 706, selecting a high-density electric detection scheme as a secondary detection scheme.
The implementation principle of the embodiment is as follows:
when the target pipeline is a non-metal pipeline, the burial depth is graded according to a preset first depth threshold value and a preset second depth threshold value, if the burial depth is smaller than or equal to the first depth threshold value, the target pipeline is shallow in burial, a drilling detection scheme can be directly selected as a primary detection scheme, and a geological radar detection scheme is selected as a secondary detection scheme; if the buried depth is greater than the first depth threshold value and less than or equal to the second depth threshold value, selecting a geological radar detection scheme as a primary detection scheme, and using a drilling detection scheme as a secondary detection scheme; and if the buried depth is greater than the second depth threshold value, selecting a geological radar detection scheme as a primary detection scheme, and using a high-density electric detection scheme as a secondary detection scheme.
The embodiment of the application also discloses a pipeline detection control system based on the internet of things, which comprises a memory, a processor and a program stored on the memory and capable of running on the processor, wherein the program can be loaded and executed by the processor to realize the pipeline detection control method based on the internet of things as shown in fig. 1 to 7.
The implementation principle of the embodiment is as follows:
through calling of a program, firstly acquiring pipeline information of a target pipeline, selecting two schemes, namely a proper primary detection scheme and a proper secondary detection scheme, according to the pipeline information, and then carrying out primary detection by using the primary detection scheme to obtain a first detection result, judging whether the first detection result is accurate or not according to the laying standard of the underground pipeline, and if so, directly taking the first detection result as a final detection result without carrying out detection again; if the first detection result is inaccurate, the secondary detection scheme can be adopted for detecting again, and the inaccurate first detection result is corrected through a second detection result obtained by the secondary detection scheme, so that a final detection result is obtained.
The above are preferred embodiments of the present application, and the scope of protection of the present application is not limited thereto, so: equivalent changes in structure, shape and principle of the present application shall be covered by the protection scope of the present application.
Claims (8)
1. A pipeline detection control method based on the Internet of things is characterized by comprising the following steps:
acquiring pipeline information of a target pipeline;
selecting a primary detection scheme and a secondary detection scheme from a plurality of preset detection schemes based on the pipeline information;
detecting the target pipeline according to the primary detection scheme to obtain a first detection result;
judging whether the first detection result is accurate or not based on an underground pipeline laying standard;
if the first detection result is accurate, taking the first detection result as a final detection result;
if the first detection result is inaccurate, detecting the target pipeline according to the secondary detection scheme to obtain a second detection result;
and correcting the first detection result according to the second detection result to obtain the final detection result.
2. The pipeline detection control method and system based on the internet of things according to claim 1, wherein the step of obtaining the pipeline information of the target pipeline comprises the following steps:
defining a detection area of a target pipeline based on an underground pipeline laying standard;
randomly selecting a plurality of pre-detection points in the detection area;
pre-detecting the pre-detection point by using a detector, and acquiring a pre-detection result of the detector;
and obtaining the pipeline information of the target pipeline based on the pre-detection result.
3. The Internet of things-based pipeline detection control method according to claim 2, wherein the randomly selecting a plurality of pre-detection points in the detection area comprises the following steps:
judging whether the area graph formed by the detection area is circular or not;
if the region graph is circular, constructing a region polar coordinate system by taking the circle center of the region graph as an origin;
randomly generating a plurality of probe point polar coordinates in the region polar coordinate system, and taking a point corresponding to the probe point polar coordinates in the region polar coordinate system as a pre-probe point;
if the area graph is not circular, judging whether the area graph is rectangular or not;
if the region graph is rectangular, constructing a region rectangular coordinate system by taking any vertex of the region graph as an origin;
and randomly generating a plurality of probe point coordinates in the region rectangular coordinate system, and taking the corresponding point of the probe point coordinates in the region rectangular coordinate system as the pre-probe point.
4. The Internet of things-based pipeline detection control method according to claim 3, further comprising the following steps:
if the region graph is not a rectangle, generating a virtual rectangle which covers the region graph and has the smallest area;
constructing a virtual rectangular coordinate system by taking any vertex of the virtual rectangle as an origin;
randomly generating virtual coordinates in a plurality of virtual rectangular coordinate systems;
judging whether the virtual coordinate falls into the range of the region graph or not;
if the virtual coordinate falls into the range of the area graph, reserving the virtual coordinate;
if the virtual coordinate does not fall into the range of the area graph, deleting the virtual coordinate;
and taking the corresponding points of all the virtual coordinates in the virtual rectangular coordinate system as the pre-detection points.
5. The method for controlling pipeline exploration according to claim 2, wherein the pipeline information comprises a buried depth and a pipeline type, and the step of obtaining the pipeline information of the target pipeline based on the pre-exploration result comprises the following steps:
extracting the pre-detection depth and the pre-detection angle in the pre-detection result;
correcting the pre-exploration depth according to the pre-exploration angle to obtain the buried depth of the target pipeline;
acquiring the electromagnetic induction state of the target pipeline based on the pre-detection result;
and analyzing the electromagnetic induction state to obtain the pipeline type of the target pipeline.
6. The internet of things-based pipeline detection control method according to claim 5, wherein the pipeline types comprise metal pipelines and non-metal pipelines, and the selection of the primary detection scheme and the secondary detection scheme from the preset detection schemes based on the burial depth and the pipeline type comprises the following steps:
judging whether the pipeline type is the metal pipeline or the non-metal pipeline;
if the pipeline type is the non-metal pipeline, selecting a primary detection scheme and a secondary detection scheme from a plurality of preset detection schemes according to the burial depth;
if the pipeline type is the metal pipeline, selecting an electromagnetic induction detection scheme as a primary detection scheme;
judging whether the buried depth is greater than a preset first depth threshold value or not;
if the buried depth is greater than the first depth threshold value, selecting a geological radar detection scheme as a secondary detection scheme;
and if the buried depth is less than or equal to the first depth threshold value, selecting a high-density electric detection scheme as a secondary detection scheme.
7. The IOT-based pipeline exploration control method according to claim 5, wherein said selecting a primary exploration scheme and a secondary exploration scheme from a plurality of preset exploration schemes according to said burial depth comprises the steps of:
judging whether the buried depth is greater than the first depth threshold value;
if the buried depth is less than or equal to the first depth threshold value, selecting a drill rod detection scheme as a primary detection scheme, and selecting the high-density electric detection scheme as a secondary detection scheme;
if the buried depth is greater than the first depth threshold value, selecting the high-density electric detection scheme as a primary detection scheme;
judging whether the buried depth is greater than a preset second depth threshold value, wherein the second depth threshold value is greater than the first depth threshold value;
if the buried depth is less than or equal to the second depth threshold value, selecting the drill rod detection scheme as a secondary detection scheme;
and if the buried depth is greater than the second depth threshold value, selecting the geological radar detection scheme as a secondary detection scheme.
8. An internet of things-based pipeline detection control system, which comprises a memory, a processor and a program stored on the memory and capable of running on the processor, wherein the program can be loaded and executed by the processor to realize the internet of things-based pipeline detection control method according to any one of claims 1-7.
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