CN112734971A - Automatic inspection method, storage medium and inspection robot - Google Patents
Automatic inspection method, storage medium and inspection robot Download PDFInfo
- Publication number
- CN112734971A CN112734971A CN202011526074.0A CN202011526074A CN112734971A CN 112734971 A CN112734971 A CN 112734971A CN 202011526074 A CN202011526074 A CN 202011526074A CN 112734971 A CN112734971 A CN 112734971A
- Authority
- CN
- China
- Prior art keywords
- inspection
- information
- patrol
- fault
- routing inspection
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000007689 inspection Methods 0.000 title claims abstract description 215
- 238000000034 method Methods 0.000 title claims abstract description 69
- 238000005070 sampling Methods 0.000 claims description 14
- 230000033001 locomotion Effects 0.000 claims description 8
- 238000001514 detection method Methods 0.000 abstract description 7
- 238000004458 analytical method Methods 0.000 description 12
- 238000003745 diagnosis Methods 0.000 description 12
- 230000005540 biological transmission Effects 0.000 description 6
- 230000002159 abnormal effect Effects 0.000 description 3
- 239000002390 adhesive tape Substances 0.000 description 2
- 238000010835 comparative analysis Methods 0.000 description 2
- 238000010219 correlation analysis Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005065 mining Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 125000004122 cyclic group Chemical group 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000010191 image analysis Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000001151 other effect Effects 0.000 description 1
- 238000010223 real-time analysis Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C1/00—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people
- G07C1/20—Checking timed patrols, e.g. of watchman
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
- B25J19/02—Sensing devices
- B25J19/021—Optical sensing devices
- B25J19/023—Optical sensing devices including video camera means
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/67—Focus control based on electronic image sensor signals
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/695—Control of camera direction for changing a field of view, e.g. pan, tilt or based on tracking of objects
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
Abstract
The invention provides an automatic inspection method, a storage medium and an inspection robot, wherein the method comprises the following steps: responding to the polling starting signal, and determining the moving speed and the moving path in the polling process; acquiring patrol video information or patrol image information, and associating the patrol video information or the patrol image information with a patrol position; and if the monitored equipment is determined to have a fault according to the routing inspection video information or the routing inspection image information, taking the current routing inspection position as a fault point and reporting the routing inspection video information or the routing inspection image information corresponding to the fault point. According to the scheme, in the automatic inspection process, when the monitored equipment is determined to have a fault according to the inspection video information or the inspection image information, only the inspection video information or the inspection audio information related to the fault point needs to be reported, so that the inspection robot can complete the operation of fault detection and fault data reporting locally in the inspection process, the timeliness is higher, and the inspection efficiency can be improved.
Description
Technical Field
The invention belongs to the technical field of inspection robots for mines, and particularly relates to an automatic inspection method, a storage medium and an inspection robot.
Background
With the development of the intellectualization of mining, the inspection of key mining equipment is gradually advanced from manual inspection to robot inspection. The inspection robot acquires environmental parameters, sound and image information through sensing equipment carried by the inspection robot, and transmits the information to the ground through a network, so that the purpose of replacing manual underground inspection is achieved.
The inspection robot generally has two inspection modes, namely manual inspection mode and automatic inspection mode. In a manual inspection mode, the inspection robot receives a control instruction of a ground operator in real time and inspects according to a given speed and a given line; in the automatic inspection mode, the inspection robot inspects according to preset information such as time, speed and lines. When automatic inspection is carried out, an inspection robot usually runs at a constant speed, the robot can carry out non-differential information acquisition on an inspection line and report the acquired information to an upper computer in real time, although an upper computer analysis system can analyze the acquired data and find out suspected fault points, the data processing capacity is large and hysteresis exists, the dependence on network bandwidth is strong in the data transmission process, the real-time performance is not high, and the suspected fault points cannot be checked, confirmed and monitored in a key mode. Under the manual mode of patrolling and examining, control personnel can carry out real-time analysis according to patrolling and examining robot data collection to carry out key monitoring to suspected fault point, nevertheless need control personnel real-time duty, intensity of labour is great.
Therefore, there is a need for an inspection solution that avoids the problems of both manual and automatic inspection processes.
Disclosure of Invention
The invention aims to provide an automatic inspection method, a storage medium and an inspection robot, so that fault point information can be processed in time under the automatic inspection mode of the inspection robot, and the fault diagnosis accuracy and the inspection efficiency can be improved.
Therefore, some embodiments of the invention provide an automatic inspection method, which includes the following steps:
responding to the polling starting signal, and determining the moving speed and the moving path in the polling process;
acquiring patrol video information or patrol image information, and associating the patrol video information or the patrol image information with a patrol position;
and if the monitored equipment is determined to have a fault according to the routing inspection video information or the routing inspection image information, taking the current routing inspection position as a fault point and reporting the routing inspection video information or the routing inspection image information corresponding to the fault point.
Optionally, the automatic inspection method further includes the following steps:
acquiring polling audio information, and associating the polling audio information with a polling position;
and if the monitored equipment has faults according to the routing inspection audio information, taking the current routing inspection position as a fault point and reporting the routing inspection audio information corresponding to the fault point.
Optionally, the automatic inspection method further includes the following steps:
and if the feedback signal of successfully receiving the reported information is not received within the set time length, storing the routing inspection video information or the routing inspection image information corresponding to the fault point and the routing inspection audio information corresponding to the fault point.
Optionally, the automatic inspection method further includes the following steps:
if the monitored equipment is determined to have no fault according to the routing inspection video information or the routing inspection image information, and meanwhile, the running state of the monitored equipment is not a normal running state, the monitored equipment is judged to have a suspected fault, and the current routing inspection position is taken as a suspected fault point;
adjusting the moving speed and the moving path in the routing inspection process, taking the suspected fault point as a center, and reciprocating within a set distance around the suspected fault point after reducing the moving speed;
and the frequency of collecting inspection video information or inspection image information is improved in the reciprocating movement process.
Optionally, the automatic inspection method further includes the following steps, wherein the step of increasing the frequency of acquiring the inspection video information or the inspection image information in the reciprocating process includes:
and adjusting the moving speed, stopping moving at the sampling moment of acquiring the video information or the patrol image information, and adjusting the shooting angle and the focal length of the patrol video information or the patrol image information.
Optionally, the automatic inspection method further includes the following steps: if the monitored equipment is determined to have no fault according to the routing inspection audio information and the running state of the monitored equipment is not a normal running state, judging that the monitored equipment has a suspected fault, and taking the current routing inspection position as a suspected fault point;
adjusting the moving speed and the moving path in the routing inspection process, taking the suspected fault point as a center, and reciprocating within a set distance around the suspected fault point after reducing the moving speed;
the frequency of collecting the patrol inspection audio information in the reciprocating movement process is improved.
Optionally, the step of increasing the frequency of collecting polling audio information in the reciprocating process of the automatic polling method includes:
and adjusting the moving speed, stopping moving at the sampling moment of acquiring the patrol audio information, and adjusting the acquisition angle of the patrol audio information.
Optionally, in the automatic inspection method, the step of determining whether the monitored device has a fault according to the inspection audio information includes:
analyzing the frequency domain waveform and the sound intensity data in the patrol inspection audio information, and determining whether the monitored equipment has faults or not according to the comparison result of the frequency domain waveform and the standard frequency domain waveform and the comparison result of the sound intensity data and the standard sound intensity data.
Some embodiments of the present invention further provide a storage medium, wherein the storage medium stores program information, and the computer reads the program information and executes the automatic inspection method according to any one of the above items.
Some embodiments of the present invention further provide an inspection robot, including at least one processor and at least one memory, where at least one memory stores program information, and the at least one processor reads the program information and then executes any one of the above automatic inspection methods.
Compared with the prior art, the technical scheme provided by the invention at least has the following beneficial effects: in the automatic inspection process, when the monitored equipment is determined to have a fault according to the inspection video information or the inspection image information, only the inspection video information or the inspection audio information related to the fault point needs to be reported, so that the inspection robot can complete the operation of fault detection and fault data reporting locally in the inspection process, the timeliness is higher, and the inspection efficiency can be improved.
Drawings
Fig. 1 is a flowchart of an automatic inspection method according to an embodiment of the present invention;
fig. 2 is a flowchart of an automatic inspection method according to another embodiment of the present invention;
FIG. 3 is a flowchart illustrating a suspected fault point detection method according to an embodiment of the invention;
FIG. 4 is a flowchart illustrating a suspected point of failure detection method according to another embodiment of the invention;
fig. 5 is a block diagram of the inspection robot according to an embodiment of the present invention;
fig. 6 is a block diagram of an inspection robot according to another embodiment of the present invention.
Detailed Description
The embodiments of the present invention will be further described with reference to the accompanying drawings. In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description of the present invention, and do not indicate or imply that the device or assembly referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Wherein the terms "first position" and "second position" are two different positions.
Some embodiments of the present application provide an automatic inspection method, which can be applied to a control unit of an inspection robot, as shown in fig. 1, including the following steps:
s101: and responding to the polling starting signal, and determining the moving speed and the moving path in the polling process. The method can be carried out according to preset time, speed, routing inspection route and other self-information.
S102: acquiring patrol video information or patrol image information, and associating the patrol video information or the patrol image information with a patrol position. The position of the inspection robot can be obtained in real time in the inspection process of the inspection robot, and image information and video information of components such as the belt surface of a belt conveyor can be collected by a high-definition camera carried by the inspection robot.
S103: and if the monitored equipment is determined to have a fault according to the routing inspection video information or the routing inspection image information, taking the current routing inspection position as a fault point and reporting the routing inspection video information or the routing inspection image information corresponding to the fault point. The video information and the image information of each position on the routing inspection path when the monitored equipment works normally can be stored, and the routing inspection video information or the routing inspection image information received in real time is compared with the stored information in the normal working state in the automatic routing inspection process of the routing inspection robot to judge whether a fault occurs. The scheme can be realized by directly routing inspection robots in the realization process, and the video information or the image information related to the fault point information can be reported after the monitored equipment is locally judged to have a fault.
According to the scheme, in the automatic inspection process, when the monitored equipment is determined to have a fault according to the inspection video information or the inspection image information, only the inspection video information or the inspection audio information related to the fault point needs to be reported, so that the inspection robot can complete the operation of fault detection and fault data reporting locally in the inspection process, the timeliness is higher, and the inspection efficiency can be improved. And moreover, only the fault diagnosis result and the audio and video data related to the fault point are uploaded to the upper computer system, so that the bandwidth requirement on a transmission network is reduced.
Further, as shown in fig. 2, the method may further include the following steps:
s104: and acquiring patrol audio information, and associating the patrol audio information with a patrol position.
S105: and if the monitored equipment has faults according to the routing inspection audio information, taking the current routing inspection position as a fault point and reporting the routing inspection audio information corresponding to the fault point.
The audio information of each position department on the route of patrolling and examining when can be normally worked by supervisory equipment is saved, patrols and examines the automatic in-process of patrolling and examining of robot, compares the information under the normal operating condition who patrols and examines audio information and the storage that receives in real time, judges whether break down. In the scheme, the analysis server carried by the inspection robot is used for realizing audio and video analysis on site, and diagnosing the fault on line in real time.
Preferably, the above scheme may further include the following steps: and if the feedback signal of successfully receiving the reported information is not received within the set time length, storing the routing inspection video information or the routing inspection image information corresponding to the fault point and the routing inspection audio information corresponding to the fault point. That is, when the transmission network is abnormal, the diagnosis result is temporarily stored in the local analysis server, and is uploaded to the upper computer system after the network is unobstructed, so that the condition of losing the fault detection result can be avoided.
Further, as shown in fig. 3, the above method further includes the following steps:
s201: and if the monitored equipment is determined to have no fault according to the routing inspection video information or the routing inspection image information and the running state of the monitored equipment is not a normal running state, judging that the monitored equipment has a suspected fault, and taking the current routing inspection position as a suspected fault point. The video information and the image information which are used for indicating the fault and are normally arranged at each position on the routing inspection path of the monitored equipment can be stored, and in the automatic routing inspection process of the routing inspection robot, the routing inspection video information or the routing inspection image information which is received in real time is compared with the stored information under the fault working state, so that whether the fault occurs or not is judged. And if the inspection video and the inspection image are different from the normal state and the fault state, determining that the fault state is suspected.
And S202, adjusting the moving speed and the moving path in the routing inspection process, taking the suspected fault point as a center, and reciprocating within a set distance around the suspected fault point after reducing the moving speed.
And S203, increasing the frequency of collecting the inspection video information or the inspection image information in the reciprocating movement process. Preferably, the method further comprises the following steps: and adjusting the moving speed, stopping moving at the sampling moment of acquiring the video information or the patrol image information, and adjusting the shooting angle and the focal length of the patrol video information or the patrol image information.
S204: and judging whether the suspected fault point has a fault or not according to the plurality of routing inspection video information or routing inspection image information, if so, executing a step S205, and otherwise, executing a step S206.
S205: and taking the current inspection position as a fault point and reporting inspection audio information corresponding to the fault point.
S206: and continuing to inspect.
That is, when the inspection robot locally finds a suspected fault point, the inspection robot performs slow reciprocating inspection and multi-point stay sampling near the suspected fault point, and performs key acquisition and cyclic comparison analysis on video information and image information of the suspected fault point so as to improve the accuracy of fault diagnosis. For example, when suspected belt surface damage is found, the inspection robot performs low-speed reciprocating inspection near a suspected fault point and stops at multiple points for sampling, and image information is acquired at multiple angles; electric focusing is carried out at each stop point, so that the quality of the shot image is improved; finally, the accuracy of image analysis is improved through multipoint image contrast correlation analysis.
Further preferably, as shown in fig. 4, the following steps are further included between step S202 and step S204:
and S203', increasing the frequency of collecting the patrol inspection audio information in the reciprocating movement process. If the monitored equipment is determined to have no fault according to the routing inspection audio information and the running state of the monitored equipment is not a normal running state, judging that the monitored equipment has a suspected fault, and taking the current routing inspection position as a suspected fault point; the audio information which represents the fault and is normally located at each position on the routing inspection path of the monitored equipment can be stored, and in the automatic routing inspection process of the robot, the routing inspection audio information received in real time and the stored audio information under the fault working state are compared to judge whether the fault occurs. And if the polling audio information is different from the information in the normal state and the information in the fault state, judging that the fault state is suspected. Compared with the scheme that the condition different from the normal state is judged as the fault condition, the scheme is additionally provided with the method for detecting and judging the suspected fault point, so that the fault point can be judged more accurately.
Specifically, the moving speed can be adjusted, the moving is stopped at the sampling moment of the collected patrol audio information, and the collection angle of the patrol audio information is adjusted at the same time. Specifically, when a suspected audio fault is found, the inspection robot performs low-speed reciprocating inspection near the suspected point and stops sampling at multiple points, and data of each sampling point is contrasted and analyzed, so that the fault diagnosis accuracy is improved. Preferably, a fault or suspected fault may be determined by: analyzing the frequency domain waveform and the sound intensity data in the patrol inspection audio information, and determining whether the monitored equipment has faults or not according to the comparison result of the frequency domain waveform and the standard frequency domain waveform and the comparison result of the sound intensity data and the standard sound intensity data.
In the scheme, the suspected fault point can be monitored and checked in a key mode under the automatic inspection mode of the inspection robot, so that the fault diagnosis accuracy and the inspection efficiency are improved.
In some embodiments of the present invention, a storage medium is further provided, where the storage medium stores program information, and a computer reads the program information and executes the automatic inspection method according to any one of the above embodiments.
Some embodiments of the present invention further provide an inspection robot, as shown in fig. 5, including at least one processor 11 and at least one memory 12, where at least one memory 12 stores program instructions, and after executing the program instructions, at least one processor 11 executes any one of the automatic inspection methods applied to the control end. This robot of patrolling and examining can also include: an input device 13 and an output device 14. The processor 11, memory 12, input device 13 and output device 14 may be communicatively connected. Memory 12, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The processor 11 executes various functional applications and data processing by executing nonvolatile software programs, instructions, and modules stored in the memory 12, that is, implements the automatic polling method described above.
Further, as shown in fig. 6, the inspection robot further includes a camera 105 and a microphone 106, the camera 105 may be a high-definition camera, the microphone 106 may be a high-performance microphone, and the processor 11 may include an audio/video analysis server. The following description is made of an inspection process of the adhesive tape machine by using an example of inspection, and the inspection process comprises the following steps:
(1) the inspection robot can collect and analyze audio and video data of the rotating part, the belt surface and other parts of the adhesive tape machine by utilizing a self-carried high-definition camera, a high-performance pickup and an audio and video analysis server.
(2) When the inspection robot automatically inspects, the inspection robot drives at a constant speed on an inspection line according to the preset time, speed, inspection line and other information in an inspection task, acquires audio and video data in real time, and carries out online analysis by an audio and video analysis server carried by the inspection robot.
(3) And when a suspected fault point is found, performing key acquisition on the area data by adopting a low-speed reciprocating inspection and multi-point staying sampling mode.
(4) Aiming at suspected audio faults, the audio fault detection method performs low-speed reciprocating motion and multipoint staying sampling in an abnormal area, comprehensively collects fault audio information from different directions, judges the fault type through time-frequency domain waveform comparative analysis and a fault identification algorithm, and positions the fault part through sound intensity change.
(5) Aiming at suspected belt surface faults, the inspection robot reciprocates at a low speed in an abnormal area and stays at multiple points for sampling, the lens is adjusted to the optimal area by electrically focusing at each stay point so as to obtain multi-azimuth high-quality video image information, and the accuracy of video analysis is improved.
(6) And correlation and comparative analysis are carried out on the multipoint sampling data, so that the accuracy of fault diagnosis is improved.
(7) And sending the diagnosis result, the position information and the original data segment to an upper computer system.
The scheme in the embodiment of the invention can realize that the audio and video analysis is realized locally, the fault diagnosis analysis is not influenced by a transmission network, the real-time performance is high, and the network bandwidth occupation is small as long as the fault diagnosis result and a small amount of related audio and video data are uploaded; the system has the function of continuous transmission in a broken network, and normal routing inspection and fault diagnosis are not influenced when the transmission network is abnormally interrupted; the suspected fault point can be monitored repeatedly and intensively, the accuracy of fault diagnosis can be effectively improved, and the inspection efficiency and other effects can be improved.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. An automatic inspection method is characterized by comprising the following steps:
responding to the polling starting signal, and determining the moving speed and the moving path in the polling process;
acquiring patrol video information or patrol image information, and associating the patrol video information or the patrol image information with a patrol position;
and if the monitored equipment is determined to have a fault according to the routing inspection video information or the routing inspection image information, taking the current routing inspection position as a fault point and reporting the routing inspection video information or the routing inspection image information corresponding to the fault point.
2. The automatic inspection method according to claim 1, further comprising the steps of:
acquiring polling audio information, and associating the polling audio information with a polling position;
and if the monitored equipment has faults according to the routing inspection audio information, taking the current routing inspection position as a fault point and reporting the routing inspection audio information corresponding to the fault point.
3. The automatic inspection method according to claim 2, further comprising the steps of:
and if the feedback signal of successfully receiving the reported information is not received within the set time length, storing the routing inspection video information or the routing inspection image information corresponding to the fault point and the routing inspection audio information corresponding to the fault point.
4. The automatic inspection method according to claim 1, further comprising the steps of:
if the monitored equipment is determined to have no fault according to the routing inspection video information or the routing inspection image information, and meanwhile, the running state of the monitored equipment is not a normal running state, the monitored equipment is judged to have a suspected fault, and the current routing inspection position is taken as a suspected fault point;
adjusting the moving speed and the moving path in the routing inspection process, taking the suspected fault point as a center, and reciprocating within a set distance around the suspected fault point after reducing the moving speed;
and the frequency of collecting inspection video information or inspection image information is improved in the reciprocating movement process.
5. The automatic inspection method according to claim 4, further comprising the step of increasing the frequency of acquiring inspection video information or inspection image information during the reciprocating movement including:
and adjusting the moving speed, stopping moving at the sampling moment of acquiring the video information or the patrol image information, and adjusting the shooting angle and the focal length of the patrol video information or the patrol image information.
6. The automatic inspection method according to claim 1, further comprising the steps of:
if the monitored equipment is determined to have no fault according to the routing inspection audio information and the running state of the monitored equipment is not a normal running state, judging that the monitored equipment has a suspected fault, and taking the current routing inspection position as a suspected fault point;
adjusting the moving speed and the moving path in the routing inspection process, taking the suspected fault point as a center, and reciprocating within a set distance around the suspected fault point after reducing the moving speed;
the frequency of collecting the patrol inspection audio information in the reciprocating movement process is improved.
7. The automatic inspection method according to claim 6, wherein the step of increasing the frequency of the inspection audio information collected during the traverse includes:
and adjusting the moving speed, stopping moving at the sampling moment of acquiring the patrol audio information, and adjusting the acquisition angle of the patrol audio information.
8. The automatic inspection method according to any one of claims 2 to 7, including the step of determining whether the monitored equipment has a fault based on the inspection audio information includes:
analyzing the frequency domain waveform and the sound intensity data in the patrol inspection audio information, and determining whether the monitored equipment has faults or not according to the comparison result of the frequency domain waveform and the standard frequency domain waveform and the comparison result of the sound intensity data and the standard sound intensity data.
9. A storage medium having program information stored therein, wherein a computer reads the program information and executes the automatic inspection method according to any one of claims 1 to 8.
10. An inspection robot, comprising at least one processor and at least one memory, wherein at least one memory stores program information, and at least one processor reads the program information and executes the automatic inspection method according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011526074.0A CN112734971A (en) | 2020-12-22 | 2020-12-22 | Automatic inspection method, storage medium and inspection robot |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011526074.0A CN112734971A (en) | 2020-12-22 | 2020-12-22 | Automatic inspection method, storage medium and inspection robot |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112734971A true CN112734971A (en) | 2021-04-30 |
Family
ID=75605266
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011526074.0A Pending CN112734971A (en) | 2020-12-22 | 2020-12-22 | Automatic inspection method, storage medium and inspection robot |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112734971A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113739077A (en) * | 2021-08-20 | 2021-12-03 | 慧感(上海)物联网科技有限公司 | Intelligent automatic inspection method and device for industrial pipe gallery pipeline |
| CN114124677A (en) * | 2021-11-30 | 2022-03-01 | 上汽通用五菱汽车股份有限公司 | Method, device, equipment and storage medium for locating link fault of panoramic camera |
| CN114241620A (en) * | 2021-12-08 | 2022-03-25 | 思诺维特(北京)科技有限公司 | Data acquisition method and device, electronic equipment and storage medium |
| CN114265404A (en) * | 2021-12-16 | 2022-04-01 | 北京云迹科技股份有限公司 | Robot diagnosis method and device, electronic equipment and storage medium |
| CN114943408A (en) * | 2022-04-06 | 2022-08-26 | 深圳市弗赛特科技股份有限公司 | Intelligent monitoring method and system for potential safety hazards of hydrogenation station |
| CN116708506A (en) * | 2023-06-28 | 2023-09-05 | 广州豪特节能环保科技股份有限公司 | Intelligent monitoring method, system and storage medium for data center |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102941920A (en) * | 2012-12-05 | 2013-02-27 | 南京理工大学 | High-tension transmission line inspection robot based on multi-rotor aircraft and method using robot |
| CN103281515A (en) * | 2013-05-10 | 2013-09-04 | 山东华辉自动化设备有限公司 | Adjustable and controllable routing inspection type conveying belt wireless video monitoring system |
| CN105225288A (en) * | 2015-10-29 | 2016-01-06 | 锦瀚智慧管网技术有限公司 | A kind of pipe network cruising inspection system |
| CN106954042A (en) * | 2017-03-13 | 2017-07-14 | 兰州交通大学 | A kind of unmanned plane rail track inspection device, system and method |
| CN111508097A (en) * | 2020-04-26 | 2020-08-07 | 深圳市阡丘越科技有限公司 | Site inspection method, device, equipment and storage medium |
-
2020
- 2020-12-22 CN CN202011526074.0A patent/CN112734971A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102941920A (en) * | 2012-12-05 | 2013-02-27 | 南京理工大学 | High-tension transmission line inspection robot based on multi-rotor aircraft and method using robot |
| CN103281515A (en) * | 2013-05-10 | 2013-09-04 | 山东华辉自动化设备有限公司 | Adjustable and controllable routing inspection type conveying belt wireless video monitoring system |
| CN105225288A (en) * | 2015-10-29 | 2016-01-06 | 锦瀚智慧管网技术有限公司 | A kind of pipe network cruising inspection system |
| CN106954042A (en) * | 2017-03-13 | 2017-07-14 | 兰州交通大学 | A kind of unmanned plane rail track inspection device, system and method |
| CN111508097A (en) * | 2020-04-26 | 2020-08-07 | 深圳市阡丘越科技有限公司 | Site inspection method, device, equipment and storage medium |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113739077A (en) * | 2021-08-20 | 2021-12-03 | 慧感(上海)物联网科技有限公司 | Intelligent automatic inspection method and device for industrial pipe gallery pipeline |
| CN114124677A (en) * | 2021-11-30 | 2022-03-01 | 上汽通用五菱汽车股份有限公司 | Method, device, equipment and storage medium for locating link fault of panoramic camera |
| CN114124677B (en) * | 2021-11-30 | 2024-03-15 | 上汽通用五菱汽车股份有限公司 | Link fault positioning method, device and equipment of panoramic camera and storage medium |
| CN114241620A (en) * | 2021-12-08 | 2022-03-25 | 思诺维特(北京)科技有限公司 | Data acquisition method and device, electronic equipment and storage medium |
| CN114265404A (en) * | 2021-12-16 | 2022-04-01 | 北京云迹科技股份有限公司 | Robot diagnosis method and device, electronic equipment and storage medium |
| CN114265404B (en) * | 2021-12-16 | 2023-12-05 | 北京云迹科技股份有限公司 | Robot diagnosis method and device, electronic equipment and storage medium |
| CN114943408A (en) * | 2022-04-06 | 2022-08-26 | 深圳市弗赛特科技股份有限公司 | Intelligent monitoring method and system for potential safety hazards of hydrogenation station |
| CN114943408B (en) * | 2022-04-06 | 2022-11-29 | 深圳市弗赛特科技股份有限公司 | Intelligent monitoring method and system for potential safety hazards of hydrogen station |
| CN116708506A (en) * | 2023-06-28 | 2023-09-05 | 广州豪特节能环保科技股份有限公司 | Intelligent monitoring method, system and storage medium for data center |
| CN116708506B (en) * | 2023-06-28 | 2023-10-27 | 广州豪特节能环保科技股份有限公司 | Intelligent monitoring method, system and storage medium for data center |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112734971A (en) | Automatic inspection method, storage medium and inspection robot | |
| US20220259947A1 (en) | Monitoring system and method for wellsite equipment | |
| CN110996060A (en) | Industrial automation intelligent linkage system and method | |
| CN108663988B (en) | Intelligent monitoring system of numerical control machine tool based on Internet of things | |
| CN111080775A (en) | Server routing inspection method and system based on artificial intelligence | |
| CN110045679B (en) | Edge calculation-based machine tool multi-source data acquisition and data quality evaluation method | |
| CN110850881A (en) | Off-line inspection system and method for inspection robot of transformer substation | |
| CN111179457A (en) | Inspection system and inspection method for industrial equipment | |
| CN115184726B (en) | Smart power grid fault real-time monitoring and positioning system and method | |
| CN113726606B (en) | Abnormality detection method and apparatus, electronic device, and storage medium | |
| CN115091491B (en) | Power distribution room maintenance patrol robot and control method thereof | |
| CN110648319A (en) | Equipment image acquisition and diagnosis system and method based on double cameras | |
| CN111899211A (en) | Transformer oil leakage fault detection system and method based on images and smell | |
| CN114255784A (en) | Substation equipment fault diagnosis method based on voiceprint recognition and related device | |
| CN116243214A (en) | Online monitoring system and method for vibration data of power transformer | |
| CN116383633A (en) | Method and system for detecting faults of machine-made sand vibrating screen through multi-factor comprehensive analysis | |
| CN115169602A (en) | Maintenance method and device for power equipment, storage medium and computer equipment | |
| CN110049317A (en) | A kind of online fault detection method, system and the electronic equipment of video monitoring system | |
| CN113483815A (en) | Mechanical fault monitoring system based on industrial big data | |
| CN116168019B (en) | Power grid fault detection method and system based on machine vision technology | |
| CN110569990A (en) | Operation and maintenance system and operation and maintenance method suitable for marine nuclear power platform | |
| CN110888782A (en) | Device processing method, system, electronic device and computer readable storage medium | |
| CN117268759B (en) | Bearing balance test system, method and medium for textile mechanical equipment | |
| CN117254597B (en) | Method and system for business analysis and monitoring of power operation data | |
| KR20200099863A (en) | Method for analyzing of object |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210430 |