CN117227551B - New energy equipment safety monitoring method, device, equipment and readable storage medium - Google Patents
New energy equipment safety monitoring method, device, equipment and readable storage medium Download PDFInfo
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02T10/00—Road transport of goods or passengers
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- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/12—Electric charging stations
Abstract
The invention provides a new energy equipment safety monitoring method, a device, equipment and a readable storage medium, wherein the method comprises the following steps: acquiring first data, second data and third data; identifying the position information of the charging pile at each historical acquisition moment according to the charging pile historical image set, and carrying out outlier identification correction operation on all the position information to obtain a processed position information set; and identifying whether the current position information of the charging pile is abnormal or not according to the processed position information set and the current image of the charging pile, obtaining a judging result, obtaining control information of the charging pile according to the judging result and the current environment information of the charging pile, and carrying out safety control on the charging pile according to the control information. By utilizing the method provided by the invention, the accurate state information of the charging pile can be obtained, so that the charging pile can be accurately checked and maintained, and the normal operation of the charging pile is ensured.
Description
Technical Field
The invention relates to the technical field of new energy, in particular to a new energy equipment safety monitoring method, a device, equipment and a readable storage medium.
Background
At present, as the traditional energy is increasingly exhausted, new energy equipment gradually appears in the life of people, such as new energy automobiles, which not only can reduce the pollution to the environment, but also can save energy, so that the new energy automobiles are increasingly favored by people; meanwhile, along with the slow popularization of the new energy automobile, corresponding supporting facilities are gradually matched with the new energy automobile, such as a charging pile, and the normal operation of the charging pile can ensure the safe supply of energy, that is to say, the charging pile is a key factor for ensuring the normal running of the new energy automobile; in addition, when an extreme event occurs, the extreme event may affect the position of the charging pile, so that the charging pile may not work normally, and therefore, a method for monitoring the charging pile in real time is needed to ensure safe operation of the charging pile and further ensure normal supply of energy.
Disclosure of Invention
The invention aims to provide a new energy equipment safety monitoring method, a device, equipment and a readable storage medium, so as to solve the problem that the new energy charging pile in the related technology cannot normally or safely operate and the normal energy supply cannot be guaranteed.
In order to achieve the above purpose, the embodiment of the present application provides the following technical solutions:
in one aspect, an embodiment of the present application provides a new energy device security monitoring method, where the method includes:
acquiring first data, second data and third data, wherein the first data comprises a charging pile history image set in a preset history time period, the second data comprises a current image of a charging pile, and the third data comprises environment information of the current charging pile;
identifying the position information of the charging pile at each historical acquisition moment according to the charging pile historical image set, and carrying out outlier identification correction operation on all the position information to obtain a processed position information set;
and identifying whether the current position information of the charging pile is abnormal or not according to the processed position information set and the current image of the charging pile, obtaining a judging result, obtaining control information of the charging pile according to the judging result and the current environment information of the charging pile, and carrying out safety control on the charging pile according to the control information.
In a second aspect, an embodiment of the present application provides a new energy device safety monitoring apparatus, where the apparatus includes an acquisition module, an identification module, and a control module.
The charging pile management system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring first data, second data and third data, the first data comprises a charging pile history image set in a preset history time period, the second data comprises a current image of a charging pile, and the third data comprises environment information of the current charging pile;
the identification module is used for identifying the position information of the charging pile at each historical acquisition moment according to the charging pile historical image set, and carrying out abnormal value identification correction operation on all the position information to obtain a processed position information set;
and the control module is used for identifying whether the current position information of the charging pile is abnormal or not according to the processed position information set and the current image of the charging pile, obtaining a judging result, obtaining control information of the charging pile according to the judging result and the current environment information of the charging pile, and carrying out safety control on the charging pile according to the control information.
In a third aspect, embodiments of the present application provide a new energy device security monitoring device, where the device includes a memory and a processor. The memory is used for storing a computer program; the processor is used for realizing the steps of the new energy equipment safety monitoring method when executing the computer program.
In a fourth aspect, embodiments of the present application provide a readable storage medium having a computer program stored thereon, where the computer program when executed by a processor implements the steps of the new energy device security monitoring method described above.
The beneficial effects of the invention are as follows:
in the invention, the image of the charging pile is acquired in consideration of the convenience of data acquisition, the position information of the charging pile is acquired by analyzing the image, and whether the current position information is abnormal or not is judged according to the position information of the historical period; and then merging the current environmental information, comprehensively analyzing the state of the charging pile according to the position information and the environmental information, and finally carrying out early warning of different grades according to the state.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a new energy device safety monitoring method according to an embodiment of the invention;
FIG. 2 is a schematic structural diagram of a new energy device safety monitoring apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a new energy device safety monitoring device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the 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 invention, as 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 made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that: like reference numerals or letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.
Example 1
As shown in fig. 1, the present embodiment provides a new energy device security monitoring method, which includes step S1, step S2, and step S3.
Step S1, acquiring first data, second data and third data, wherein the first data comprises a charging pile history image set in a preset history time period, the second data comprises a current image of a charging pile, and the third data comprises environment information of the current charging pile;
in this step, the preset historical time period may be understood as a period of historical time taking the current time as an end point, and the specific duration may be set in a user-defined manner according to the user requirement, for example, the current time is 12 pm, and then the preset historical time period may be from 12 pm in yesterday to 12 pm today, or from 12 pm in the previous day to 12 pm today; in the step, the situation that if some external force factors possibly influence the position of the charging pile, such as the situation that the charging pile is impacted to topple over, is considered, so that the image of the charging pile is collected, the position information of the charging pile is analyzed through the image, in the step, the image of the charging pile is directly collected and analyzed, and the collecting method is simple, so that the applicability of the method can be improved; meanwhile, the fact that factors such as strong wind, heavy rain and earthquake influence the charging pile is considered, so that current environmental factors are collected, the current safety of the charging pile is analyzed through several factors, and compared with one factor, the method in the step can more comprehensively reflect the current state information of the charging pile, and further accuracy of a final safety maintenance method is improved;
S2, identifying the position information of the charging pile at each historical acquisition moment according to the charging pile historical image set, and carrying out outlier identification correction operation on all the position information to obtain a processed position information set; the specific implementation steps of the step comprise a step S21 and a step S22;
step S21, sequentially marking the charging pile historical images acquired at every two adjacent historical acquisition moments as a first image and a second image respectively, carrying out gray processing on the first image and the second image respectively after the acquisition moments of the second image to obtain a third image and a fourth image, and subtracting the gray value of each pixel of the third image from the gray value of each pixel of the fourth image to obtain a fifth image;
illustratively, subtracting the gray value of each pixel of the third image from the gray value of each pixel of the fourth image may be subtracting the gray value of each pixel of the fourth image corresponding to the third image from the gray value of each pixel of the fourth image, to obtain the fifth image. In this step, for example, the time of acquiring the first image is 11 minutes at noon, and then the time of acquiring the second image may be 12 minutes at noon; in the step, gray processing is carried out on the first image and the second image, and the three primary color values can be filtered, so that only gray values are reserved in the images, and the step of subtracting the gray value of each pixel of the third image from the gray value of each pixel of the fourth image is simpler and more convenient to operate;
In some embodiments, the number of fifth images is plural, and because the number of adjacent historical acquisition moments is plural, image processing is sequentially performed on every two adjacent historical acquisition moments to obtain a corresponding plurality of fifth images. Step S22, sequentially performing binarization processing, corrosion filtering processing and expansion processing on the fifth image to obtain a sixth image, determining first position information of the charging pile in the sixth image, wherein the first position information comprises the length and the width of the charging pile, obtaining the position information of the charging pile at each historical acquisition time according to the first position information, and performing outlier identification correction operation on all the position information to obtain a processed position information set.
For example, the adjacent historical acquisition time may be sequentially referred to as a first time, a second time, a third time, etc., the sixth image M1 calculated using the history image of the charging pile corresponding to the first time and the second time, and the position information of the charging pile obtained using the M1 image may be referred to as position information corresponding to the first time, where the first time is a certain historical acquisition time; and sequentially calculating the position information corresponding to the subsequent multiple adjacent historical acquisition moments according to the method.
In this step, the object represented in the sixth image is typically an outline of the object, through which the length and width of the charging pile can be determined, and through which the position information of the minimum target frame in the sixth image can be determined, where the minimum target frame is a target frame that can just frame the charging pile; meanwhile, the specific implementation steps of the step comprise a step S221 and a step S222;
step S221, determining a minimum target frame in a sixth image according to the position information, and determining the position information of the charging pile in each second image according to the coordinate information of the minimum target frame; performing set analysis on the position information of the charging piles in each second image to obtain the top vertical distances of the charging piles corresponding to each history acquisition moment, collecting all the top vertical distances to obtain a top vertical distance set, and clustering the data in the top vertical distance set by using a clustering algorithm to obtain a plurality of clustering categories;
in the step, after the position information of the minimum target frame is determined, the coordinates of the charging pile in the sixth image and the coordinates of the charging pile in the second image are unchanged because the sizes of the sixth image and the second image are consistent, so that the coordinate information of the minimum target frame can be used as the coordinate information of the minimum target frame in the second image, the vertical distance between the top of the charging pile and the place can be calculated according to the coordinate information of the minimum target frame, then the vertical distance between the top of the charging pile and the place at each acquisition moment can be calculated by the method, and the position change of the charging pile can be reflected by the vertical distance between the top of the charging pile and the place; generally, under normal conditions, the position information of the charging pile will not change, if the position of the charging pile changes, the charging pile may be abnormal, such as foundation settlement, and if the charging pile is not handled in time, serious loss may be caused. Therefore, in the step, after all the top vertical distances are collected, whether the current position of the charging pile has an abnormal condition or not is judged by analyzing the top vertical distances for a period of time;
Step S222, processing the top vertical distance set based on each cluster category to obtain a processed position information set.
In this step, since whether the position of the current charging pile is abnormal is determined and analyzed according to the top vertical distance set, in order to accurately determine whether the position of the current charging pile is abnormal, the accuracy of data in the top vertical distance set needs to be improved, and if a missing value exists in the set, the accuracy of a final result is affected, so in this step, the top vertical distance set is processed by using a clustering algorithm; the specific processing method comprises a step S2221 and a step S2222;
step S2221, calculating the similarity between any two data by adopting a Euclidean distance algorithm in each cluster category to obtain a similarity calculation result, comparing the similarity calculation result with a preset first threshold value, and if the similarity calculation result is smaller than the preset threshold value, respectively combining the any two data into a data set;
in this step, in addition to the euclidean distance algorithm, the cosine distance algorithm and the pearson correlation coefficient may be used to calculate the similarity;
Step S2222, for each cluster category, dividing the number of data sets corresponding to each cluster category by the number of data pairs in each cluster category, comparing the calculated result with a preset second threshold, deleting the data contained in the corresponding cluster category when the calculated result is greater than the second preset threshold, and performing the deletion value supplementing operation after deleting to obtain a processed top vertical distance set, and recording the processed top vertical distance set as a processed position information set.
In the step, the second preset threshold value is in direct proportion to the number of each clustering category, namely, each clustering category corresponds to one second preset threshold value, and the specific numerical value can be set in a self-defined mode according to the user requirement; meanwhile, in the step, when the missing value is supplemented, the average value of the two values before and after the missing value can be used as the missing value to supplement;
and S3, identifying whether the current position information of the charging pile is abnormal or not according to the processed position information set and the current image of the charging pile, obtaining a judging result, obtaining control information of the charging pile according to the judging result and the current environment information of the charging pile, and performing safety control on the charging pile according to the control information.
In the step, whether the current position information of the charging pile is abnormal or not is identified according to the processed position information set and the current image of the charging pile, and the specific implementation steps for obtaining the judgment result comprise the step S31 and the step S32;
step S31, adding the top vertical distance of the charging pile at the current moment into the processed position information set to obtain a first set, performing fitting operation on data in the first set by adopting an autoregressive moving average model to obtain fitting data corresponding to each acquisition moment, and performing difference calculation on each fitting data and corresponding real data to obtain a difference calculation result;
in this step, the vertical distance of the top of the charging pile at the current moment can be calculated according to the calculation method; meanwhile, the fitting data in this step can be regarded as prediction data;
step S32, carrying out mean value and variance calculation on all the difference calculation results, adding the mean value and the variance to obtain a first calculation result, adding fitting data corresponding to each acquisition time to the first calculation result to obtain a second calculation result, and subtracting the fitting data corresponding to each acquisition time from the first calculation result to obtain a third calculation result; and if the top vertical distance corresponding to the current moment is larger than the second calculation result or smaller than the third calculation result, judging that the current position information of the charging pile is abnormal.
The fitting data corresponding to each acquisition time is added with the first calculation result to obtain a plurality of second calculation results, and the fitting data corresponding to each acquisition time is subtracted from the first calculation result to obtain a plurality of third calculation results; comparing the top vertical distance corresponding to the current moment with the second calculation result or the third calculation result, wherein the top vertical distance corresponding to the current moment can be compared with the maximum value in the plurality of second calculation results or the top vertical distance corresponding to the current moment can be compared with the maximum value in the plurality of third calculation results; for example, the target second calculation result and the target third calculation result may be determined from the plurality of second calculation results and the plurality of third calculation results, respectively, and then the top vertical distance corresponding to the current moment may be compared with the target second calculation result or the target third calculation result, respectively.
In the step, the second calculation result and the third calculation result can be regarded as two boundary values corresponding to each data point, and the result of whether the top vertical distance at the current moment is abnormal can be obtained through the setting of the two boundary values;
In the step, control information of the charging pile is obtained according to the judging result and the current environmental information of the charging pile, and the specific implementation step of carrying out safety control on the charging pile according to the control information comprises the step S33;
step S33, analyzing the judgment result, if the judgment result is that the current position information of the charging pile is abnormal, carrying out abnormal labeling on the charging pile, meanwhile, analyzing the current environment information of the charging pile, judging whether the current environment information is an extreme environment event or not, and if the current environment information is an extreme environment event and the charging pile is in an abnormal state, sending first-level early warning information; if the charging pile is in an abnormal state at the same time of not belonging to the extreme environmental event, sending secondary early warning information; if the charging pile is not in an abnormal state at the same time of the extreme environmental event, sending three-level early warning information; if the charging pile is not in an abnormal state at the same time of not belonging to the extreme environmental event, no processing is carried out, and all levels of early warning information are used for prompting a user to check and maintain the charging pile.
In this step, the specific implementation step of determining whether the current environmental information is an extreme environmental event includes step S331, step S332, and step S333;
Step S331, obtaining current geological information and current weather information, combining the current geological information and the current weather information, recording the combined current geological information and the combined current weather information as environment information of the current environment, obtaining historical environment information, marking the historical environment information, and obtaining marked historical environment information if the marked information belongs to an extreme environment event;
in the step, the geological information and the weather information can be recorded in a text form, and the geological information and the weather information are marked after being combined;
step S332, inputting the marked historical environment information into a VGG (Visual Geometry Group ) network, and calculating the cross entropy loss corresponding to the marked historical environment information according to the prediction result output by the VGG network; inputting the marked historical environment information into a denoising self-encoder to obtain a coding result, and performing supervised training on the denoising self-encoder according to the absolute value of the difference between the marked historical environment information and the coding result to obtain a trained denoising self-encoder;
in this step, models such as a depth residual network and the like can be used in addition to the VGG network; the denoising self-encoder can also be replaced by a sparse self-encoder or a stacked self-encoder;
And step 333, constructing an environmental event classification model based on the trained denoising self-encoder and the cross entropy loss corresponding to the marked historical environmental information, and inputting the current environmental information into the environmental event classification model to obtain a result of whether the current environmental information is an extreme environmental event. The specific implementation steps of the step comprise a step S3331;
s3331, inputting marked historical environment information into a trained denoising self-encoder, and marking the absolute value of the difference between the output of the trained denoising self-encoder and the marked historical environment information as a fourth calculation result; and aiming at a fourth calculation result and cross entropy loss corresponding to each marked historical environment information, adding the fourth calculation result and the cross entropy loss according to weights corresponding to the fourth calculation result and the cross entropy loss respectively to obtain a fifth calculation result, sequencing the marked historical environment information corresponding to each fifth calculation result according to the sequence of the fifth calculation result from small to large, and training the VGG network by taking the previous N marked historical environment information after sequencing to obtain an environment event classification model, wherein N is a positive integer.
In the step, the fourth calculation result can be regarded as a reconstruction error corresponding to the marked historical environment information, and the step sorts each sample data according to the fourth calculation result and the cross entropy loss.
In the above steps, in this embodiment, the convenience of data acquisition is considered, so that the image of the charging pile is acquired, the position information of the charging pile is acquired by performing analysis processing on the image, and whether the current position information is abnormal or not is determined according to the position information of the history period; then the current environment information is merged, the state of the charging pile is comprehensively analyzed according to the position information and the environment information, and finally, early warning of different grades is carried out according to the state.
Example 2
As shown in fig. 2, the present embodiment provides a new energy device safety monitoring apparatus, which includes an acquisition module 701, an identification module 702, and a control module 703.
An obtaining module 701, configured to obtain first data, second data and third data, where the first data includes a history image set of a charging pile in a preset history period, the second data includes a current image of the charging pile, and the third data includes environmental information in which the charging pile is currently located;
the identifying module 702 is configured to identify, according to the charging pile history image set, position information of the charging pile at each history collection time, and perform an outlier identification correction operation on all the position information, so as to obtain a processed position information set;
and the control module 703 is configured to identify whether the current position information of the charging pile is abnormal according to the processed position information set and the current image of the charging pile, obtain a judgment result, obtain control information of the charging pile according to the judgment result and the current environment information of the charging pile, and perform safety control on the charging pile according to the control information.
In a specific embodiment of the disclosure, the identification module 702 further includes a first calculating unit 7021 and a modifying unit 7022.
The first calculating unit 7021 is configured to sequentially record, as a first image and a second image, the charging pile history images acquired at each two adjacent history acquisition moments, where the second image acquisition moment is later, respectively perform gray processing on the first image and the second image pair to obtain a third image and a fourth image, and subtract a gray value of each pixel of the fourth image from a gray value of each pixel of the third image to obtain a fifth image;
and the correction unit 7022 is configured to sequentially perform binarization processing, corrosion filtering processing and expansion processing on the fifth image to obtain a sixth image, determine first position information of the charging pile in the sixth image, where the first position information includes a length and a width of the charging pile, obtain position information of the charging pile at each historical acquisition time according to the first position information, and perform outlier identification correction operation on all the position information to obtain a processed position information set.
In a specific embodiment of the disclosure, the modifying unit 7022 further includes a clustering unit 70221 and a processing unit 70222.
A clustering unit 70221, configured to determine a minimum target frame in a sixth image according to the position information, and determine position information of the charging pile in each second image according to coordinate information of the minimum target frame; performing set analysis on the position information of the charging piles in each second image to obtain the top vertical distances of the charging piles corresponding to each history acquisition moment, collecting all the top vertical distances to obtain a top vertical distance set, and clustering the data in the top vertical distance set by using a clustering algorithm to obtain a plurality of clustering categories;
The processing unit 70222 is configured to process the top vertical distance set based on each cluster category, to obtain a processed position information set.
In a specific embodiment of the disclosure, the processing unit 70222 further includes a second computing unit 702221 and a third computing unit 702222.
The second calculating unit 702221 is configured to calculate, in each cluster category, a similarity between any two data by using a euclidean distance algorithm, obtain a similarity calculation result, compare the similarity calculation result with a preset first threshold, and if the similarity calculation result is smaller than the preset threshold, respectively combine the any two data into a data set;
and a third computing unit 702222, configured to divide, for each cluster type, the number of data sets corresponding to each cluster type by the number of data pairs in each cluster type, compare the computed result with a preset second threshold, delete data included in the corresponding cluster type when the computed result is greater than the second preset threshold, perform a deletion value supplementing operation after deletion, obtain a processed top vertical distance set, and record the processed top vertical distance set as a processed position information set.
In a specific embodiment of the disclosure, the control module 703 further includes a joining unit 7031 and a fourth computing unit 7032.
The adding unit 7031 is configured to add the top vertical distance of the charging pile at the current moment to the processed position information set to obtain a first set, perform fitting operation on data in the first set by using an autoregressive moving average model to obtain fitting data corresponding to each acquisition moment, and perform difference calculation on each fitting data and corresponding real data to obtain a difference calculation result;
a fourth calculating unit 7032, configured to perform mean and variance calculation on all the difference calculation results, add the mean and the variance to obtain a first calculation result, add fitting data corresponding to each acquisition time to the first calculation result to obtain a second calculation result, and subtract fitting data corresponding to each acquisition time to the first calculation result to obtain a third calculation result; and when the top vertical distance corresponding to the current moment is larger than the second calculation result or smaller than the third calculation result, judging that the current position information of the charging pile is abnormal.
In a specific embodiment of the disclosure, the control module 703 further includes an analysis unit 7033.
The analysis unit 7033 is configured to analyze the determination result, if the determination result is that the current position information of the charging pile is abnormal, perform abnormal labeling on the charging pile, analyze the environmental information, determine whether the current environmental information is an extreme environmental event, and if the current environmental information is an extreme environmental event and the charging pile is in an abnormal state, send first-level early warning information; if the charging pile is in an abnormal state at the same time of not belonging to the extreme environmental event, sending secondary early warning information; if the charging pile is not in an abnormal state at the same time of the extreme environmental event, sending three-level early warning information; if the charging pile is not in an abnormal state at the same time of not belonging to the extreme environmental event, no processing is carried out, and all levels of early warning information are used for prompting a user to check and maintain the charging pile.
In a specific embodiment of the present disclosure, the analysis unit 7033 further includes an acquisition unit 70331, an input unit 70332, and a construction unit 70333.
The acquiring unit 70331 is configured to acquire current geological information and current weather information, combine the current geological information and the current weather information, record the combined current geological information and the combined current weather information as current environmental information, acquire historical environmental information, label the historical environmental information, and acquire labeled historical environmental information if the labeled information belongs to an extreme environmental event;
An input unit 70332, configured to input the labeled historical environmental information into a VGG network, and calculate a cross entropy loss corresponding to the labeled historical environmental information according to a prediction result output by the VGG network; inputting the marked historical environment information into a denoising self-encoder to obtain a coding result, and performing supervised training on the denoising self-encoder according to the absolute value of the difference between the marked historical environment information and the coding result to obtain a trained denoising self-encoder;
the construction unit 70333 is configured to construct an environmental event classification model based on the trained denoising self-encoder and the cross entropy loss corresponding to the marked historical environmental information, and input the current environmental information into the environmental event classification model to obtain a result of whether the current environmental information is an extreme environmental event.
In one embodiment of the present disclosure, the construction unit 70333 further comprises a training unit 703331.
The training unit 703331 is configured to input the marked historical environmental information into a trained denoising self-encoder, and record an absolute value of a difference between an output of the trained denoising self-encoder and the marked historical environmental information as a fourth calculation result; and aiming at a fourth calculation result and cross entropy loss corresponding to each marked historical environment information, adding the fourth calculation result and the cross entropy loss according to weights corresponding to the fourth calculation result and the cross entropy loss respectively to obtain a fifth calculation result, sequencing the marked historical environment information corresponding to each fifth calculation result according to the sequence of the fifth calculation result from small to large, and training the VGG network by taking the previous N marked historical environment information after sequencing to obtain an environment event classification model, wherein N is a positive integer.
It should be noted that, regarding the apparatus in the above embodiments, the specific manner in which the respective modules perform the operations has been described in detail in the embodiments regarding the method, and will not be described in detail herein.
Example 3
Corresponding to the above method embodiments, the embodiments of the present disclosure further provide a new energy device security monitoring device, where the new energy device security monitoring device described below and the new energy device security monitoring method described above may be referred to correspondingly with each other.
Fig. 3 is a block diagram illustrating a new energy device security monitoring device 800 according to an exemplary embodiment. As shown in fig. 3, the new energy device security monitoring device 800 may include: a processor 801, a memory 802. The new energy device security monitoring device 800 may also include one or more of a multimedia component 803, an i/O interface 804, and a communication component 805.
The processor 801 is configured to control the overall operation of the new energy device security monitoring apparatus 800, so as to complete all or part of the steps in the new energy device security monitoring method. The memory 802 is used to store various types of data to support operation at the new energy device security monitoring device 800, which may include, for example, instructions for any application or method operating on the new energy device security monitoring device 800, as well as application-related data, such as contact data, messages, pictures, audio, video, and the like. The Memory 802 may be implemented by any type or combination of volatile or non-volatile Memory devices, such as static random access Memory (Static Random Access Memory, SRAM for short), electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM for short), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM for short), programmable Read-Only Memory (Programmable Read-Only Memory, PROM for short), read-Only Memory (ROM for short), magnetic Memory, flash Memory, magnetic disk, or optical disk. The multimedia component 803 may include a screen and an audio component. Wherein the screen may be, for example, a touch screen, the audio component being for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in the memory 802 or transmitted through the communication component 805. The audio assembly further comprises at least one speaker for outputting audio signals. The I/O interface 804 provides an interface between the processor 801 and other interface modules, which may be a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 805 is configured to perform wired or wireless communication between the new energy device security monitoring device 800 and other devices. Wireless communication, such as Wi-Fi, bluetooth, near field communication (Near FieldCommunication, NFC for short), 2G, 3G or 4G, or a combination of one or more thereof, the respective communication component 805 may thus comprise: wi-Fi module, bluetooth module, NFC module.
In an exemplary embodiment, the new energy device security monitoring device 800 may be implemented by one or more application specific integrated circuits (Application Specific Integrated Circuit, abbreviated as ASIC), digital signal processor (DigitalSignal Processor, abbreviated as DSP), digital signal processing device (Digital Signal Processing Device, abbreviated as DSPD), programmable logic device (Programmable Logic Device, abbreviated as PLD), field programmable gate array (Field Programmable Gate Array, abbreviated as FPGA), controller, microcontroller, microprocessor, or other electronic component for performing the new energy device security monitoring method described above.
In another exemplary embodiment, a computer readable storage medium is also provided, comprising program instructions which, when executed by a processor, implement the steps of the new energy device security monitoring method described above. For example, the computer readable storage medium may be the memory 802 described above including program instructions executable by the processor 801 of the new energy device security monitoring device 800 to perform the new energy device security monitoring method described above.
Example 4
Corresponding to the above method embodiments, the present disclosure further provides a readable storage medium, where a readable storage medium described below and the above described new energy device security monitoring method may be referred to correspondingly.
A readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the new energy device security monitoring method of the above method embodiment.
The readable storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, and the like.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The new energy equipment safety monitoring method is characterized by comprising the following steps:
acquiring first data, second data and third data, wherein the first data comprises a charging pile history image set in a preset history time period, the second data comprises a current image of a charging pile, and the third data comprises environment information of the current charging pile;
Identifying the position information of the charging pile at each historical acquisition moment according to the charging pile historical image set, and carrying out outlier identification correction operation on all the position information to obtain a processed position information set;
the step of identifying the position information of the charging pile at each historical collection time according to the charging pile historical image set, and carrying out outlier identification correction operation on all the position information to obtain a processed position information set, wherein the step of obtaining the processed position information set comprises the following steps:
sequentially marking the charging pile historical images acquired at every two adjacent historical acquisition moments as a first image and a second image respectively, carrying out gray processing on the first image and the second image respectively after the acquisition moments of the second image to obtain a third image and a fourth image, and subtracting the gray value of each pixel of the third image from the gray value of each pixel of the fourth image to obtain a fifth image;
sequentially performing binarization processing, corrosion filtering processing and expansion processing on the fifth image to obtain a sixth image, determining first position information of a charging pile in the sixth image, wherein the first position information comprises the length and the width of the charging pile, obtaining the position information of the charging pile at each historical acquisition moment according to the first position information, and performing outlier identification correction operation on all the position information to obtain a processed position information set;
Identifying whether the current position information of the charging pile is abnormal or not according to the processed position information set and the current image of the charging pile, obtaining a judging result, obtaining control information of the charging pile according to the judging result and the current environment information of the charging pile, and performing safety control on the charging pile according to the control information;
obtaining control information of the charging pile according to the judging result and the current environmental information of the charging pile, and performing safety control on the charging pile according to the control information, wherein the safety control comprises the following steps:
analyzing the judging result, if the judging result is that the current position information of the charging pile is abnormal, carrying out abnormal labeling on the charging pile, meanwhile, analyzing the current environment information of the charging pile, judging whether the current environment information is an extreme environment event, and if the current environment information is an extreme environment event and the charging pile is in an abnormal state, sending first-level early warning information; if the charging pile is in an abnormal state at the same time of not belonging to the extreme environmental event, sending secondary early warning information; if the charging pile is not in an abnormal state at the same time of the extreme environmental event, sending three-level early warning information; if the charging pile is not in an abnormal state at the same time of not belonging to the extreme environmental event, no processing is carried out, and all levels of early warning information are used for prompting a user to check and maintain the charging pile.
2. The new energy equipment safety monitoring method according to claim 1, wherein obtaining the position information of the charging pile at each historical collection time according to the first position information, performing outlier identification correction operation on all the position information, and obtaining a processed position information set, including:
determining a minimum target frame in the sixth image according to the position information, and determining the position information of the charging pile in each second image according to the coordinate information of the minimum target frame; performing set analysis on the position information of the charging piles in each second image to obtain the top vertical distances of the charging piles corresponding to each history acquisition moment, collecting all the top vertical distances to obtain a top vertical distance set, and clustering the data in the top vertical distance set by using a clustering algorithm to obtain a plurality of clustering categories;
and processing the top vertical distance set based on each cluster category to obtain a processed position information set.
3. The method for monitoring safety of new energy equipment according to claim 2, wherein the processing of the top vertical distance set based on each cluster category to obtain a processed position information set comprises:
In each cluster category, calculating the similarity between any two data by adopting a Euclidean distance algorithm to obtain a similarity calculation result, comparing the similarity calculation result with a preset first threshold value, and if the similarity calculation result is smaller than the preset threshold value, respectively combining the any two data into a data set;
for each clustering category, dividing the number of data groups corresponding to each clustering category by the number of data pairs in each clustering category, comparing the calculated result with a preset second threshold value, deleting the data contained in the corresponding clustering category when the calculated result is larger than the second preset threshold value, performing deletion value supplementing operation after deleting to obtain a processed top vertical distance set, and recording the processed top vertical distance set as a processed position information set.
4. The new energy device security monitoring method according to claim 1, wherein identifying whether the current position information of the charging pile is abnormal according to the processed position information set and the current image of the charging pile, to obtain a determination result, comprises:
adding the top vertical distance of the charging pile at the current moment into the processed position information set to obtain a first set, performing fitting operation on data in the first set by adopting an autoregressive moving average model to obtain fitting data corresponding to each acquisition moment, and performing difference calculation on each fitting data and corresponding real data to obtain a difference calculation result;
Calculating the mean value and the variance of all the difference calculation results, adding the mean value and the variance to obtain a first calculation result, adding fitting data corresponding to each acquisition time to the first calculation result to obtain a second calculation result, and subtracting the fitting data corresponding to each acquisition time from the first calculation result to obtain a third calculation result; and if the top vertical distance corresponding to the current moment is larger than the second calculation result or smaller than the third calculation result, judging that the current position information of the charging pile is abnormal.
5. The method for monitoring safety of new energy equipment according to claim 4, wherein determining whether the environmental information currently located is an extreme environmental event comprises:
acquiring current geological information and current weather information, combining the current geological information and the current weather information, marking the combined current geological information and the combined current weather information as environment information of the current environment, acquiring historical environment information, marking the historical environment information, and obtaining marked historical environment information if the marked information belongs to an extreme environment event;
inputting the marked historical environment information into a VGG network, and calculating cross entropy loss corresponding to the marked historical environment information according to a prediction result output by the VGG network; inputting the marked historical environment information into a denoising self-encoder to obtain a coding result, and performing supervised training on the denoising self-encoder according to the absolute value of the difference between the marked historical environment information and the coding result to obtain a trained denoising self-encoder;
And constructing an environmental event classification model based on the trained denoising self-encoder and the cross entropy loss corresponding to the marked historical environmental information, and inputting the current environmental information into the environmental event classification model to obtain a result of whether the current environmental information is an extreme environmental event.
6. New energy equipment safety monitoring device, its characterized in that includes:
the charging pile management system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring first data, second data and third data, the first data comprises a charging pile history image set in a preset history time period, the second data comprises a current image of a charging pile, and the third data comprises environment information of the current charging pile;
the identification module is used for identifying the position information of the charging pile at each historical acquisition moment according to the charging pile historical image set, and carrying out abnormal value identification correction operation on all the position information to obtain a processed position information set;
the identification module is further used for sequentially marking the charging pile historical images acquired at every two adjacent historical acquisition moments as a first image and a second image respectively, carrying out gray processing on the first image and the second image respectively after the acquisition moments of the second image to obtain a third image and a fourth image, and subtracting the gray value of each pixel of the third image from the gray value of each pixel of the fourth image to obtain a fifth image; sequentially performing binarization processing, corrosion filtering processing and expansion processing on the fifth image to obtain a sixth image, determining first position information of a charging pile in the sixth image, wherein the first position information comprises the length and the width of the charging pile, obtaining the position information of the charging pile at each historical acquisition moment according to the first position information, and performing outlier identification correction operation on all the position information to obtain a processed position information set;
The control module is used for identifying whether the current position information of the charging pile is abnormal or not according to the processed position information set and the current image of the charging pile, obtaining a judging result, obtaining control information of the charging pile according to the judging result and the current environment information of the charging pile, and carrying out safety control on the charging pile according to the control information;
the control module is further used for analyzing the judgment result, if the judgment result is that the current position information of the charging pile is abnormal, the charging pile is marked abnormally, meanwhile, the environment information of the charging pile is analyzed, whether the current environment information is an extreme environment event or not is judged, and if the current environment information is an extreme environment event, and meanwhile, the charging pile is in an abnormal state, first-level early warning information is sent; if the charging pile is in an abnormal state at the same time of not belonging to the extreme environmental event, sending secondary early warning information; if the charging pile is not in an abnormal state at the same time of the extreme environmental event, sending three-level early warning information; if the charging pile is not in an abnormal state at the same time of not belonging to the extreme environmental event, no processing is carried out, and all levels of early warning information are used for prompting a user to check and maintain the charging pile.
7. New energy equipment safety monitoring equipment, its characterized in that includes:
a memory for storing a computer program;
a processor for implementing the steps of the new energy device security monitoring method according to any one of claims 1 to 5 when executing the computer program.
8. A readable storage medium, characterized by: the readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the new energy device security monitoring method according to any one of claims 1 to 5.
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