CN110827435A - External damage monitoring method and system based on intelligent warning post and readable storage medium - Google Patents
External damage monitoring method and system based on intelligent warning post and readable storage medium Download PDFInfo
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- CN110827435A CN110827435A CN201911034541.5A CN201911034541A CN110827435A CN 110827435 A CN110827435 A CN 110827435A CN 201911034541 A CN201911034541 A CN 201911034541A CN 110827435 A CN110827435 A CN 110827435A
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- 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
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02G—INSTALLATION OF ELECTRIC CABLES OR LINES, OR OF COMBINED OPTICAL AND ELECTRIC CABLES OR LINES
- H02G1/00—Methods or apparatus specially adapted for installing, maintaining, repairing or dismantling electric cables or lines
- H02G1/02—Methods or apparatus specially adapted for installing, maintaining, repairing or dismantling electric cables or lines for overhead lines or cables
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- 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
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Abstract
The invention discloses an external damage monitoring method and system based on an intelligent warning post and a readable storage medium, and relates to the field of external damage identification and monitoring; the method comprises the following steps of 1: acquiring vibration data and distance data of the warning columns and then acquiring a primary recognition result; step 2: after video and image data are collected according to the primary recognition result, the data and the positioning data of the warning columns are sent to a cloud platform for secondary recognition, and a monitoring result is obtained; and step 3: sending the monitoring result to a patrol device, a monitoring platform and other field devices; and 4, step 4: and patrolling according to an external damage monitoring result, detecting and sending the distance between the patrolling device and the warning post and the data of the patrolling device to the cloud platform, and generating a patrolling path by the monitoring platform according to the distance and the data. The invention solves the problems that the existing external damage behaviors can not be monitored and prevented, and the patrol efficiency of external damage patrol personnel is low, and achieves the effects of carrying out manual intervention after intelligently identifying the external damage and improving the external damage monitoring efficiency.
Description
Technical Field
The invention relates to the field of outer broken identification and monitoring, in particular to an outer broken monitoring method and system based on an intelligent warning post and a readable storage medium.
Background
Along with urban economic development, the cable transformation rate of urban distribution networks is increased year by year, and meanwhile, the requirement on power supply reliability is higher and higher, but in the operation and maintenance process of urban cable networks, a traditional warning pile is only a pile with a warning mark, so that real warning and prevention effects cannot be realized, and the cable external damage fault rate is high.
On the other hand, the distribution network monitoring adopts manual inspection, which has low inspection efficiency, so that the external damage of pipelines or optical cables and the like based on the urban distribution network cannot be effectively prevented or prevented, thereby bringing various potential safety hazards caused by the external damage, bringing serious economic loss and seriously influencing the production and life of people; meanwhile, the inspection details of inspection personnel can not be obtained, the inspection quality can not be guaranteed, and the efficiency of monitoring the external broken network is low.
Therefore, an external damage monitoring method, system and readable storage medium based on an intelligent warning post are needed, which can overcome the above problems, monitor and prevent external damage behaviors, ensure the inspection quality and improve the monitoring quality and efficiency of the external damage behaviors.
Disclosure of Invention
The invention aims to: the invention provides an external damage monitoring method and system based on an intelligent warning post and a readable storage medium, and solves the problems that the existing external damage behavior cannot be monitored and prevented, and the patrol efficiency of external damage patrolmen is low.
The technical scheme adopted by the invention is as follows:
the outer broken monitoring method based on the intelligent warning post comprises the following steps:
step 1: acquiring vibration data and distance data of a warning post installed on an external damage site and then acquiring a primary recognition result;
step 2: triggering an acquisition device to acquire video data and image data according to the primary identification result, and sending the acquired video data, image data and positioning data of the warning columns to a cloud platform for secondary identification to obtain an external damage monitoring result;
and step 3: sending the external damage monitoring result to a patrol device, a monitoring platform and other field devices;
and 4, step 4: and patrolling according to an external damage monitoring result, detecting and sending the distance between the patrolling device and the warning post and the data of the patrolling device to the cloud platform, and generating a patrolling path by the monitoring platform according to the distance and the data.
Preferably, the step 1 comprises the steps of:
step 1.1: triggering and acquiring vibration data and distance data through a vibration sensor and a microwave radar sensor on an external broken field warning post;
step 1.2: judging whether the acquired vibration data and the distance data both meet a threshold value, if so, identifying the primary recognition result as an external broken state, and jumping to the step 2 after performing acousto-optic reminding; otherwise, the primary identification result is in a non-external-broken state, and the step 1.1 is skipped to continue the acquisition.
Preferably, the step 2 comprises the steps of:
step 2.1: the method comprises the steps that a collection device is triggered to collect image data and video data of an outer broken site, and the image data, the video data and positioning data corresponding to warning columns are sent to a cloud platform;
step 2.2: and the cloud platform inputs the image data and the video data into a trained recognition network, sequentially performs traversal, feature extraction and target classification to obtain recognition results, wherein the recognition results comprise an outer broken scene of the excavator and an outer broken scene of the crusher, and combines the recognition results with positioning data to generate an outer broken monitoring result.
Preferably, the recognition network training comprises the following steps:
step a: carrying out sample calibration after collecting training samples;
step b: classifying the calibrated samples into positive samples and negative samples;
step c: and performing feature extraction on the positive sample and the negative sample, and inputting the positive sample and the negative sample into a training classifier, wherein the training classifier adopts AdaBoost.
Preferably, the step 4 comprises the steps of:
step 4.1: inspecting the corresponding site according to the external damage monitoring result;
step 4.2: detecting the distance between the patrol device and a warning post on a patrol site;
step 4.3: and sending the positioning data of the inspection device and the distance to a monitoring platform, and generating an inspection path by the monitoring platform according to the distance and the positioning data.
An external broken monitoring system based on an intelligent warning post comprises
The warning post is used for acquiring the vibration data and the distance data of the outer breaking site to judge the outer breaking state, carrying out acousto-optic reminding and acquiring image data and video data according to the outer breaking state, then sending the outer breaking state and the positioning data to the cloud platform, and sending the distance between the outer breaking state and the inspection device to the monitoring platform;
the cloud platform is used for receiving the external damage state and the positioning data, carrying out secondary identification to obtain an external damage monitoring result, and sending the external damage monitoring result to the monitoring platform, the inspection device and other field devices;
the monitoring platform is used for receiving positioning data of the patrol device and generating or updating a patrol path according to the distance between the patrol site warning post and the patrol device, and receiving an external damage monitoring state;
and the patrol device is used for receiving the external damage monitoring result and sending patrol device positioning data to the monitoring platform.
Preferably, the warning post comprises a post body, a solar panel, a lithium battery, a sensor group, an acquisition device, a positioning module, a wireless module, an audible and visual alarm and a single chip microcomputer, wherein the solar panel is connected with the lithium battery, the lithium battery supplies power to the modules, the sensor group, the acquisition device, the positioning module and the audible and visual alarm are respectively and electrically connected with the single chip microcomputer, and the solar panel is arranged at the top of the main body;
the sensor group comprises a vibration sensor and a microwave radar ranging sensor; the vibration sensor and the microwave radar ranging sensor are respectively and electrically connected with the single chip microcomputer, and the acquisition device comprises a miniature camera; the wireless module comprises a 4G module.
Preferably, the patrol device comprises a safety helmet or a mobile terminal.
Preferably, the cloud platform comprises a secondary identification network comprising
The image preprocessing unit is used for traversing the input image;
the characteristic extraction unit is used for extracting the characteristics in the traversed image;
and the target classification unit is used for classifying the extracted features by utilizing an AdaBoost algorithm to obtain an identification result.
A readable storage medium, storing a computer program which, when executed by a processor, carries out the steps of the online monitoring method of a metering anomaly according to any one of claims 1 to 5.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
1. according to the invention, the intelligent warning post is used for collecting data and then recognizing the external broken behavior, the recognition result is shared to the patrol terminal, other operation terminals and the monitoring terminal through wireless transmission, so that patrol personnel can conveniently and rapidly perform manual prevention and inform hidden dangers according to the data of the patrol terminal, the monitoring efficiency and the patrol working efficiency of the external broken behavior are improved, other field devices update the recognition network according to the shared data, the recognition accuracy is further improved, and the monitoring terminal performs whole-course monitoring;
2. according to the invention, the vibration sensor and the laser radar are used for carrying out primary identification, then the camera is triggered to collect a field video, secondary identification is realized on the cloud platform through feature extraction and target classification, the identification accuracy rate is improved, the inspection and detection efficiency of the external breaking behavior is improved, and the external breaking behavior is prevented in advance; the recognition result is sent to other operation points, the data sample size is improved through shared data, the fault study and judgment time is shortened, the overall study and judgment accuracy and the working efficiency are comprehensively improved, and therefore the accuracy of scene recognition and external damage behavior recognition is improved;
3. according to the invention, the position information of the patrol device and the distance between the patrol device and the patrol site warning post are collected to generate a patrol path, so that the patrol quality is controlled, the problems of nonstandard patrol and no-arrival of patrol personnel are solved, and the monitoring quality is improved;
4. the warning post is triggered to work through vibration, and the solar panel supplies power to the warning post, so that low power consumption is realized.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a block diagram of the system of the present invention;
FIG. 3 is a first schematic diagram of an off-site acquisition of the present invention;
FIG. 4 is a second schematic diagram of an on-site outcropping of a collection of the present invention;
FIG. 5 is a monitoring flow diagram of the present invention;
FIG. 6 is a schematic diagram of the outer damage monitoring result of the present invention;
FIG. 7 is a flow chart of a cloud platform identification method of the present invention;
FIG. 8 is a schematic diagram of an inspection end external damage monitoring result according to the present invention;
FIG. 9 is a schematic diagram illustrating the transmission of the outbreak monitoring result according to the present invention;
FIG. 10 is a schematic diagram of the test of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It is noted that relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The features and properties of the present invention are described in further detail below with reference to examples.
Example 1
As shown in fig. 1, the external damage monitoring method based on the intelligent warning post comprises the following steps:
step 1: acquiring vibration data and distance data of a warning post installed on an external damage site and then acquiring a primary recognition result;
step 2: triggering an acquisition device to acquire video data and image data according to the primary identification result, and sending the acquired video data, image data and positioning data of the warning columns to a cloud platform for secondary identification to obtain an external damage monitoring result;
and step 3: sending the external damage monitoring result to a patrol device, a monitoring platform and other field devices, as shown in fig. 2 and 9;
and 4, step 4: and patrolling according to an external damage monitoring result, detecting and sending the distance between the patrolling device and the warning post and the data of the patrolling device to the cloud platform, and generating a patrolling path by the monitoring platform according to the distance and the data.
The step 1 comprises the following steps:
step 1.1: triggering and acquiring vibration data and distance data through a vibration sensor and a microwave radar sensor on an external broken field warning post;
step 1.2: judging whether the acquired vibration data and the distance data both meet a threshold value, if so, identifying the primary recognition result as an external broken state, and jumping to the step 2 after performing acousto-optic reminding; otherwise, the primary identification result is in a non-external-broken state, and the step 1.1 is skipped to continue the acquisition. The vibration data comprises vibration intensity and vibration frequency, and whether the vibration intensity is greater than 0.5g or not and the vibration frequency is greater than 10 times/second or not are judged; the distance data comprises a monitoring distance threshold value, and whether the monitoring distance threshold value is smaller than 5m is judged.
The step 2 comprises the following steps:
step 2.1: the method comprises the steps that a collection device is triggered to collect image data and video data of an outer broken site, and the image data, the video data and positioning data corresponding to warning columns are sent to a cloud platform;
step 2.2: and the cloud platform inputs the image data and the video data into a trained recognition network, sequentially performs traversal, feature extraction and target classification to obtain recognition results, wherein the recognition results comprise an outer broken scene of the excavator and an outer broken scene of the crusher, and combines the recognition results with positioning data to generate an outer broken monitoring result.
As shown in fig. 7, the recognition network training comprises the following steps:
step a: carrying out sample calibration after collecting training samples;
step b: classifying the calibrated samples into positive samples and negative samples;
step c: and performing feature extraction on the positive sample and the negative sample, and inputting the positive sample and the negative sample into a training classifier, wherein the training classifier adopts AdaBoost.
The classifier can be classified into a linear classification and a non-linear classification. A common linear classifier is a logistic regression classifier, which has high real-time performance but relatively low classification accuracy. Common nonlinear classifiers such as a support vector machine, AdaBoost and the like, wherein AdaBoost has excellent classification real-time performance and accuracy performance, and is one of the classifiers commonly used in the target detection technology. The reason why the real-time performance and the accuracy performance of Adaboost, namely Adaptive Boosting, are excellent is that the error rate of the weak learning algorithm can be adjusted in a self-Adaptive manner, and the error rate can reach a preset expected value after a plurality of iterations. On the other hand, accurate sample space distribution information is not needed, the distribution of the sample space is adjusted after each classification learning, namely, the weights of all training samples are updated, the correctly classified sample weight in the sample space is reduced, and the incorrectly classified sample weight is increased.
The Adaboost algorithm comprises the following steps:
inputting: contains N sets of labeled training samples { (1, y1), (N, y)N) Wherein 1, N represents the sequence number of the sample, yNClass labels (values are divided into 0 and 1) representing samples. The distribution space of the training samples is D,the number of iterations is T. The detailed steps of the algorithm are as follows:
firstly, initializing the weight: for yiSample of 0, set w1i1/2 m; for yiSet w for the sample of 11i＝1/2l。
Two, weight normalizationWherein T is the number of iterations of the training, and the value is 1, 2.
Thirdly, for each feature j, generating a corresponding if classifier hjCalculating the error e relative to the current weightj：
Fourthly, selecting the minimum error value epsilontIf classifier htAdding the obtained mixture into a strong classifier;
fifthly, updating the weight corresponding to each sample:
repeating the first to the fifth steps until T is more than T;
and finally obtaining a strong classifier:
the step 4 comprises the following steps:
step 4.1: inspecting the corresponding site according to the external damage monitoring result;
step 4.2: detecting the distance between the patrol device and a warning post on a patrol site;
step 4.3: and sending the positioning data of the inspection device and the distance to a monitoring platform, and generating an inspection path by the monitoring platform according to the distance and the positioning data.
As shown in fig. 8, for the schematic diagram of the information received by the patrol terminal, the patrol is performed with human intervention by patrol personnel corresponding to the site, the patrol personnel is required to wear a safety helmet, the patrol personnel is positioned by a positioning module on the safety helmet to see whether the patrol personnel reaches the outer broken site, meanwhile, a warning post detects the distance between the patrol personnel and the warning post, whether the patrol personnel arrives at the post is determined, and the corresponding data is sent to the monitoring platform to generate the patrol route by positioning data and distance data. Whether the patrol personnel arrive at the corresponding broken site or not can be determined, the positioning module of the safety helmet can also be a handheld movable terminal or a warning post of the patrol personnel to trigger a camera to collect and identify the work board of the patrol personnel, and specific judgment can be carried out according to specific conditions of the site or one-dimensional judgment or comprehensive judgment of multiple dimensions. The patrol route is examined in real time according to the data, so that the patrol quality is ensured, manual intervention is performed in advance, and potential safety hazards caused by external damage are avoided.
As shown in fig. 5, data collected by the warning post is wirelessly transmitted through 4G, the transmitted data includes image data, vibration data and the like, the image data, the vibration data and the like are transmitted to the cloud platform for identification, an identification result and data details are sent to the mobile terminal, and the mobile terminal includes a monitoring end or a patrol end; as shown in fig. 3 and 4, the scene photographs collected for the warning post; FIG. 10 is a schematic illustration of an embodiment of the present application; according to the invention, the intelligent warning post is used for collecting data and then recognizing the external broken behavior, the recognition result is shared to the patrol terminal, other operation terminals and the monitoring terminal through wireless transmission, so that patrol personnel can rapidly and manually prevent and inform hidden dangers according to the data of the patrol terminal, meanwhile, the monitoring terminal monitors the patrol work in the whole process, the patrol quality is ensured, the monitoring efficiency and the patrol work efficiency of the external broken behavior are improved, other field devices update the recognition network according to the shared data, and the recognition accuracy is further improved.
Example 2
Based on embodiment 1, this embodiment provides an outer broken monitoring system based on intelligence warning post, include
The warning post is used for acquiring the vibration data and the distance data of the outer breaking site to judge the outer breaking state, carrying out acousto-optic reminding and acquiring image data and video data according to the outer breaking state, then sending the outer breaking state and the positioning data to the cloud platform, and sending the distance between the outer breaking state and the inspection device to the monitoring platform;
the cloud platform is used for receiving the external damage state and the positioning data, carrying out secondary identification to obtain an external damage monitoring result, and sending the external damage monitoring result to the monitoring platform, the inspection device and other field devices;
the monitoring platform is used for receiving positioning data of the patrol device and generating or updating a patrol path according to the distance between the patrol site warning post and the patrol device, and receiving an external damage monitoring state;
and the patrol device is used for receiving the external damage monitoring result and sending patrol device positioning data to the monitoring platform.
The warning post includes cylinder, solar panel, lithium cell, sensor group, collection system, orientation module, wireless module, audible-visual annunciator and singlechip, solar panel is connected with the lithium cell, the lithium cell is each module power supply, sensor group, collection system, orientation module and audible-visual annunciator respectively with singlechip electric connection, solar panel sets up at the main part top.
The sensor group comprises a vibration sensor and a microwave radar ranging sensor; the vibration sensor and the microwave radar ranging sensor are respectively and electrically connected with the single chip microcomputer, and the acquisition device comprises a miniature camera; the wireless module comprises a 4G module.
The patrol device comprises a safety helmet or a movable terminal carried by patrol personnel.
The cloud platform comprises a secondary identification network, and the secondary identification network comprises
The image preprocessing unit is used for traversing the input image;
the characteristic extraction unit is used for extracting the characteristics in the traversed image;
and the target classification unit is used for classifying the extracted features by utilizing an AdaBoost algorithm to obtain an identification result.
The system comprises a processor, a memory and a computer program stored in the memory and executable on the processor, such as "step 1: acquiring vibration data and distance data of a warning post installed on an external damage site and then acquiring a primary recognition result; step 2: triggering an acquisition device to acquire video data and image data according to the primary identification result, and sending the acquired video data, image data and positioning data of the warning columns to a cloud platform for secondary identification to obtain an external damage monitoring result; and step 3: sending the external damage monitoring result to a patrol device, a monitoring platform and other field devices, as shown in fig. 2 and 9; and 4, step 4: and patrolling according to an external damage monitoring result, detecting and sending the distance between the patrolling device and the warning post and the data of the patrolling device to the cloud platform, and generating a patrolling path by the monitoring platform according to the distance and the data. "program, computer program may be divided into one or more modules/units, which are stored in the memory and executed by the processor to accomplish the present invention.
The memory includes high speed random access memory and may also include non-volatile memory such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
In conclusion, vibration data and distance data are collected through a vibration sensor of the warning post and a microwave radar ranging sensor, the vibration data comprise vibration intensity and vibration frequency, whether the vibration intensity is larger than 0.5g or not is judged, and the vibration frequency is larger than 10 times/second; the distance data comprises a monitoring distance threshold value, and whether the monitoring distance threshold value is smaller than 5m is judged. After the data are judged, if the data are met, triggering an audible and visual alarm and acquisition device to acquire field picture or video data, and sending an external damage state and positioning data to a cloud platform; the cloud platform carries out identification, the identification result is sent to each end, and the patrol end carries out patrol according to the received structure and carries out human intervention; the on-site warning post detects whether the patrol personnel arrive at the scene or not, and sends the arrival information to the monitoring platform, so that a patrol path can be generated, and the patrol quality can be controlled. The method and the device detect the outer damage in advance through intelligent acquisition and identification, and improve the efficiency and quality of outer damage monitoring on the basis of the quality of manual intervention of a controller.
Example 3
Based on embodiment 1, this embodiment provides a readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the steps of the external damage monitoring method according to embodiment 1 are implemented. The readable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as an exception prompting function) required by at least one function, and the like; the storage data area may store data (such as abnormal data, power data, etc.) created according to the use of the system, etc. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a flash memory Card (FlashCard), at least one magnetic disk storage device, a flash memory device, or other volatile solid state storage device.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. The outer broken monitoring method based on the intelligent warning post is characterized by comprising the following steps: the method comprises the following steps:
step 1: acquiring vibration data and distance data of a warning post installed on an external damage site and then acquiring a primary recognition result;
step 2: triggering an acquisition device to acquire video data and image data according to the primary identification result, and sending the acquired video data, image data and positioning data of the warning columns to a cloud platform for secondary identification to obtain an external damage monitoring result;
and step 3: sending the external damage monitoring result to a patrol device, a monitoring platform and other field devices;
and 4, step 4: and patrolling according to an external damage monitoring result, detecting and sending the distance between the patrolling device and the warning post and the data of the patrolling device to the cloud platform, and generating a patrolling path by the monitoring platform according to the distance and the data.
2. The intelligent warning post-based break-out monitoring method according to claim 1, wherein: the step 1 comprises the following steps:
step 1.1: triggering and acquiring vibration data and distance data through a vibration sensor and a microwave radar sensor on an external broken field warning post;
step 1.2: judging whether the acquired vibration data and the distance data both meet a threshold value, if so, identifying the primary recognition result as an external broken state, and jumping to the step 2 after performing acousto-optic reminding; otherwise, the primary identification result is in a non-external-broken state, and the step 1.1 is skipped to continue the acquisition.
3. The intelligent warning post-based break-out monitoring method according to claim 1, wherein: the step 2 comprises the following steps:
step 2.1: the method comprises the steps that a collection device is triggered to collect image data and video data of an outer broken site, and the image data, the video data and positioning data corresponding to warning columns are sent to a cloud platform;
step 2.2: and the cloud platform inputs the image data and the video data into a trained recognition network, sequentially performs traversal, feature extraction and target classification to obtain recognition results, wherein the recognition results comprise an outer broken scene of the excavator and an outer broken scene of the crusher, and combines the recognition results with positioning data to generate an outer broken monitoring result.
4. The intelligent warning post-based break-over monitoring method according to claim 3, wherein: the recognition network training comprises the following steps:
step a: carrying out sample calibration after collecting training samples;
step b: classifying the calibrated samples into positive samples and negative samples;
step c: and performing feature extraction on the positive sample and the negative sample, and inputting the positive sample and the negative sample into a training classifier, wherein the training classifier adopts AdaBoost.
5. The intelligent warning post-based break-over monitoring method according to claim 3, wherein: the step 4 comprises the following steps:
step 4.1: inspecting the corresponding site according to the external damage monitoring result;
step 4.2: detecting the distance between the patrol device and a warning post on a patrol site;
step 4.3: and sending the positioning data of the inspection device and the distance to a monitoring platform, and generating an inspection path by the monitoring platform according to the distance and the positioning data.
6. Outer broken monitoring system based on post is warned to intelligence, its characterized in that: comprises that
The warning post is used for acquiring the vibration data and the distance data of the outer breaking site to judge the outer breaking state, carrying out acousto-optic reminding and acquiring image data and video data according to the outer breaking state, then sending the outer breaking state and the positioning data to the cloud platform, and sending the distance between the outer breaking state and the inspection device to the monitoring platform;
the cloud platform is used for receiving the external damage state and the positioning data, carrying out secondary identification to obtain an external damage monitoring result, and sending the external damage monitoring result to the monitoring platform, the inspection device and other field devices;
the monitoring platform is used for receiving positioning data of the patrol device and generating or updating a patrol path according to the distance between the patrol site warning post and the patrol device, and receiving an external damage monitoring state;
and the patrol device is used for receiving the external damage monitoring result and sending patrol device positioning data to the monitoring platform.
7. The intelligent warning post-based break-over monitoring system according to claim 6, wherein: the alarm post comprises a post body, a solar panel, a lithium battery, a sensor group, an acquisition device, a positioning module, a wireless module, an audible and visual alarm and a single chip microcomputer, wherein the solar panel is connected with the lithium battery, the lithium battery supplies power to the modules, the sensor group, the acquisition device, the positioning module and the audible and visual alarm are respectively and electrically connected with the single chip microcomputer, and the solar panel is arranged at the top of the main body;
the sensor group comprises a vibration sensor and a microwave radar ranging sensor; the vibration sensor and the microwave radar ranging sensor are respectively and electrically connected with the single chip microcomputer, and the acquisition device comprises a miniature camera; the wireless module comprises a 4G module.
8. The intelligent warning post-based break-over monitoring system according to claim 6, wherein: the patrol device comprises a safety helmet or a movable terminal.
9. The intelligent warning post-based break-over monitoring system according to claim 6, wherein: the cloud platform comprises a secondary identification network, and the secondary identification network comprises
The image preprocessing unit is used for traversing the input image;
the characteristic extraction unit is used for extracting the characteristics in the traversed image;
and the target classification unit is used for classifying the extracted features by utilizing an AdaBoost algorithm to obtain an identification result.
10. A readable storage medium, characterized by: the readable storage medium stores a computer program which, when executed by a processor, performs the steps of the online monitoring method for metrology anomalies according to any one of claims 1 to 5.
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| CN111428610A (en) * | 2020-03-19 | 2020-07-17 | 中国联合网络通信集团有限公司 | Optical cable damage early warning method, device, system, electronic equipment and storage medium |
| CN112152208A (en) * | 2020-09-25 | 2020-12-29 | 国网四川省电力公司成都供电公司 | Method, system, terminal and medium for calculating open capacity of urban power distribution network |
| CN112584095A (en) * | 2020-11-25 | 2021-03-30 | 国家电网有限公司 | Intelligent pole tower external damage prevention monitoring method based on 3D convolution technology |
| CN113241671A (en) * | 2021-06-03 | 2021-08-10 | 广东电网有限责任公司 | Power transmission line monitoring device, system and method |
| CN113903133A (en) * | 2021-09-30 | 2022-01-07 | 中国工商银行股份有限公司 | Network point safety protection method, device and system |
| CN113920702A (en) * | 2021-11-19 | 2022-01-11 | 国网四川省电力公司德阳供电公司 | Station and house type equipment external damage monitoring and alarming method |
| CN113984195A (en) * | 2021-11-05 | 2022-01-28 | 上海能源建设集团有限公司 | Third-party activity sound vibration monitoring and alarming system for periphery of pipeline under municipal administration road |
| CN114155690A (en) * | 2021-11-29 | 2022-03-08 | 广东电网有限责任公司广州供电局 | Cable external-damage-prevention linkage early warning system and method |
| CN115102292A (en) * | 2022-08-25 | 2022-09-23 | 国网山西省电力公司太原供电公司 | Cable external-damage-prevention monitoring method and system |
| CN116626448A (en) * | 2023-04-18 | 2023-08-22 | 国网江西省电力有限公司南昌供电分公司 | Optical cable anti-external-damage monitoring system based on cloud platform |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111428610A (en) * | 2020-03-19 | 2020-07-17 | 中国联合网络通信集团有限公司 | Optical cable damage early warning method, device, system, electronic equipment and storage medium |
| CN112152208A (en) * | 2020-09-25 | 2020-12-29 | 国网四川省电力公司成都供电公司 | Method, system, terminal and medium for calculating open capacity of urban power distribution network |
| CN112584095A (en) * | 2020-11-25 | 2021-03-30 | 国家电网有限公司 | Intelligent pole tower external damage prevention monitoring method based on 3D convolution technology |
| CN113241671A (en) * | 2021-06-03 | 2021-08-10 | 广东电网有限责任公司 | Power transmission line monitoring device, system and method |
| CN113903133A (en) * | 2021-09-30 | 2022-01-07 | 中国工商银行股份有限公司 | Network point safety protection method, device and system |
| CN113984195A (en) * | 2021-11-05 | 2022-01-28 | 上海能源建设集团有限公司 | Third-party activity sound vibration monitoring and alarming system for periphery of pipeline under municipal administration road |
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| CN114155690A (en) * | 2021-11-29 | 2022-03-08 | 广东电网有限责任公司广州供电局 | Cable external-damage-prevention linkage early warning system and method |
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| CN115102292B (en) * | 2022-08-25 | 2022-12-27 | 国网山西省电力公司太原供电公司 | Cable external-damage-prevention monitoring method and system |
| CN116626448A (en) * | 2023-04-18 | 2023-08-22 | 国网江西省电力有限公司南昌供电分公司 | Optical cable anti-external-damage monitoring system based on cloud platform |
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