CN112712111A - Device state detection method, electronic device, and storage medium - Google Patents
Device state detection method, electronic device, and storage medium Download PDFInfo
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- 238000012549 training Methods 0.000 claims description 20
- 238000009432 framing Methods 0.000 claims description 6
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
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- G—PHYSICS
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Abstract
The invention discloses a device state detection method, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring a target image of equipment to be detected, and performing feature extraction on the target image to obtain a target feature image; carrying out similarity calculation on the target characteristic image and the basic characteristic image to obtain a similarity value; and if the similarity value is smaller than a preset threshold value, determining that the equipment to be detected is in an abnormal state. By applying the invention, the change of the equipment state can be effectively detected.
Description
Technical Field
The present invention relates to the field of image recognition technologies, and in particular, to a device status detection method, an electronic device, and a storage medium.
Background
In the power industry, the types of equipment are very many, and when the state judgment of the equipment is needed, the state of the equipment is stable, the change is small, and the state judgment of the equipment is difficult to train by obtaining enough materials, so the method of object identification is difficult to implement. Because the power equipment is in a special environment, each equipment has the special environment, the illumination difference is large, and the state identification of the equipment cannot be carried out through the traditional template matching.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides a device state detection method, an electronic device and a storage medium, which can effectively detect the change of the device state.
The device state detection method, the electronic device and the storage medium according to the embodiment of the first aspect of the invention comprise the following steps:
acquiring a target image of equipment to be detected, and performing feature extraction on the target image to obtain a target feature image;
carrying out similarity calculation on the target characteristic image and the basic characteristic image to obtain a similarity value;
and if the similarity value is smaller than a preset threshold value, determining that the equipment to be detected is in an abnormal state.
The equipment state detection method provided by the embodiment of the invention at least has the following beneficial effects: firstly, obtaining a target image of equipment to be detected, and performing feature extraction on the target image to obtain a target feature image; and then, carrying out similarity calculation on the target characteristic image and the basic characteristic image to obtain a similarity value, and if the similarity value is smaller than a preset threshold value, determining that the equipment to be detected is in an abnormal state. Since the state of the device is usually stable for a long period of time and does not change much, it is difficult to obtain enough material to train the neural network, and thus it is difficult to achieve the degree of autonomous recognition using the neural network. Through the steps, the similarity of the target characteristic image and the basic characteristic image is compared to obtain the similarity value, and then the similarity value is compared with the threshold value, so that whether the equipment state changes or not is judged, a large amount of training materials are not needed, and the change of the equipment state can be effectively detected.
According to some embodiments of the invention, further comprising:
acquiring an original image;
and performing framing and cutting on the part of the original image where the equipment is located according to a preset size through picture cutting to obtain the target image.
According to some embodiments of the invention, further comprising:
acquiring a basic image;
and performing feature extraction on the basic image to obtain the basic feature image.
According to some embodiments of the present invention, the calculating the similarity between the target feature image and the basic feature image to obtain a similarity value includes:
calculating the cosine similarity between the target characteristic image and the basic characteristic image to obtain the similarity value, wherein the cosine similarity calculation formula is as follows:
wherein x is1、y1Is the vector coordinate, x, of the target feature image2、y2The vector coordinates of the basic characteristic image.
According to some embodiments of the invention, feature extraction is performed on the target image by the VGG16 algorithm.
According to some embodiments of the invention, the VGG16 algorithm is trained.
According to some embodiments of the invention, the training of the VGG16 algorithm comprises:
acquiring an original image every 10 minutes, and acquiring for 24 hours to form a training image set;
performing framing and cutting on the part of the original image where the equipment is located according to a preset size through picture cutting to obtain a target training set;
and inputting the images of the target training set into the VGG16 algorithm, and training the VGG16 algorithm.
According to some embodiments of the present invention, if the similarity value is greater than or equal to a preset threshold, it is determined that the device corresponding to the target image is in a normal state.
An electronic device according to an embodiment of the second aspect of the present invention includes:
at least one processor, and,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the device status detection method described above.
A storage medium according to an embodiment of the second aspect of the present invention is a computer-readable storage medium, which stores computer-executable instructions for causing a computer to execute the above-mentioned device state detection method.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic diagram of an electronic device according to an embodiment of the invention;
FIG. 2 is a flow chart of a method for detecting device status according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of two states of a device to be tested according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, it should be understood that the orientation or positional relationship referred to in the description of the orientation, such as the upper, lower, front, rear, left, right, etc., is based on the orientation or positional relationship shown in the drawings, and is only for convenience of description and simplification of description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention.
In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and larger, smaller, larger, etc. are understood as excluding the number, and larger, smaller, inner, etc. are understood as including the number. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the present invention, unless otherwise explicitly limited, terms such as arrangement, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific contents of the technical solutions.
Referring to FIG. 1, the components of the electronic device 100 include, but are not limited to, a memory 110 and a processor 120. The processor 120 is coupled to the memory 110 via a bus 130 and the database 160 is used to store data.
The electronic device 100 also includes an access device 140, the access device 140 enabling the electronic device 100 to communicate via one or more networks 150. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the internet. The access device 1400 may include one or more of any type of network interface, e.g., a Network Interface Card (NIC), wired or wireless, such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.
In some embodiments of the invention, the above-mentioned components of the electronic device 100 and other components not shown in fig. 1 may be connected to each other, for example by a bus. It should be understood that the block diagram of the electronic device shown in fig. 1 is for exemplary purposes only and is not intended to limit the scope of the present invention. Those skilled in the art may add or replace other components as desired. The electronic device 100 may be any type of electronic device 100, such as a computer, a smart phone, a smart tablet, and the like.
Wherein the processor 120 may perform the steps of the device status detection method shown in fig. 2. Fig. 2 shows a flowchart of a device status detection method according to an embodiment of the present invention, and referring to fig. 2, includes steps S100 to S300.
Step S100: and acquiring a target image, and performing feature extraction on the target image to obtain a target feature image.
It can be understood that the target image can be obtained by obtaining the original image, and then performing framing and cropping on the part of the original image where the device is located according to the preset size through picture cutting. In the environment of the device, a camera may be generally disposed on one side of the device, and the relative position of the camera and the device is determined by determining the shooting angle of the device and the position of the key component, and adjusting the angle of the camera. If there are multiple devices within a camera range, the relative positions between the camera and the multiple devices are also fixed, and the position of each device in the original picture taken is also substantially fixed without changing the position of the camera. Therefore, according to the position relation of the equipment in the photo, after the original image is obtained, the equipment at the corresponding position in the original image can be cut by the preset size, and the target image is obtained.
It is understood that, the above-mentioned feature extraction of the target image is to perform feature extraction of the target image by the VGG16 algorithm. Training the VGG16 algorithm and training the VGG16 algorithm, wherein the training comprises the following steps:
acquiring an original image every 10 minutes, acquiring 24 hours, covering images of all time points, and forming a training image set;
performing framing and cutting on the part of the original image where the equipment is located according to a preset size through picture cutting to obtain a target training set;
and inputting the images of the target training set into the VGG16 algorithm, and training the VGG16 algorithm.
Step S200: and comparing the similarity of the target characteristic image with the similarity of the basic characteristic image to obtain a similarity value.
It can be understood that the basic feature image is obtained by first obtaining the basic image and then performing feature extraction on the basic image to obtain the basic feature image. The base image may be an original image captured at evening time, a cropped device image. The feature extraction may be performed by using the VGG16 algorithm. Comparing the similarity of the target characteristic image with the similarity of the basic characteristic image to obtain a similarity value, wherein the similarity value comprises the following steps: calculating the cosine similarity between the target characteristic image and the basic characteristic image to obtain a similarity value, wherein the cosine similarity calculation formula is as follows:
wherein (x)1,y1) (x) is the vector coordinate of the target feature image2,y2) The vector coordinates of the basic characteristic image.
Step S300: and if the similarity value is smaller than the preset threshold value, determining that the equipment corresponding to the target image is in an abnormal state.
Referring to fig. 3, it is understood that the device of the embodiment of the present application may be an electric device having two parts which are brought together in a normal state and separated in an abnormal state. And if the similarity value is greater than or equal to the preset threshold value, determining that the equipment corresponding to the target image is in a normal state. If the equipment is detected to be in an abnormal state, an alarm signal can be output, and a corresponding terminal is informed through a mail or a popup window.
According to the equipment state detection method, firstly, a target image is obtained, and feature extraction is carried out on the target image to obtain a target feature image; and then, comparing the similarity of the target characteristic image with the similarity of the basic characteristic image to obtain a similarity value, and if the similarity value is smaller than a preset threshold value, determining that the equipment corresponding to the target image is in an abnormal state. Since the state of the device is usually stable for a long period of time and does not change much, it is difficult to obtain enough material to train the neural network, and thus it is difficult to achieve the degree of autonomous recognition using the neural network. Through the steps, the similarity of the target characteristic image and the basic characteristic image is compared to obtain the similarity value, and then the similarity value is compared with the threshold value, so that whether the equipment state changes or not is judged, a large amount of training materials are not needed, and the change of the equipment state can be effectively detected.
The embodiment of the invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used for enabling a computer to execute the device state detection method.
It should be noted that the technical solution of the computer-readable storage medium and the technical solution of the above-mentioned device status detection method belong to the same concept, and details that are not described in detail in the technical solution of the computer-readable storage medium can be referred to the description of the technical solution of the above-mentioned device status detection method.
The above-described embodiments of the apparatus are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may also be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
One of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and alterations to these embodiments may be made without departing from the principles and spirit of the invention, which is encompassed in the scope of the present application.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.
Claims (10)
1. An equipment state detection method is characterized by comprising the following steps:
acquiring a target image of equipment to be detected, and performing feature extraction on the target image to obtain a target feature image;
carrying out similarity calculation on the target characteristic image and the basic characteristic image to obtain a similarity value;
and if the similarity value is smaller than a preset threshold value, determining that the equipment to be detected is in an abnormal state.
2. The device status detection method according to claim 1, further comprising:
acquiring an original image;
and performing framing and cutting on the part of the original image where the equipment is located according to a preset size through picture cutting to obtain the target image.
3. The device status detection method according to claim 1, further comprising:
acquiring a basic image;
and performing feature extraction on the basic image to obtain the basic feature image.
4. The device state detection method according to claim 3, wherein the calculating the similarity between the target feature image and the basic feature image to obtain a similarity value comprises:
calculating the cosine similarity between the target characteristic image and the basic characteristic image to obtain the similarity value, wherein the cosine similarity calculation formula is as follows:
wherein x is1、y1Is the vector coordinate, x, of the target feature image2、y2The vector coordinates of the basic characteristic image.
5. The device status detection method according to claim 1, characterized in that: and performing feature extraction on the target image through a VGG16 algorithm.
6. The device status detection method according to claim 5, further comprising: training the VGG16 algorithm.
7. The device state detection method of claim 6, wherein the training of the VGG16 algorithm comprises:
acquiring an original image every 10 minutes, and acquiring for 24 hours to form a training image set;
performing framing and cutting on the part of the original image where the equipment is located according to a preset size through picture cutting to obtain a target training set;
and inputting the images of the target training set into the VGG16 algorithm, and training the VGG16 algorithm.
8. The device status detection method according to claim 1, further comprising: and if the similarity value is greater than or equal to a preset threshold value, determining that the equipment corresponding to the target image is in a normal state.
9. An electronic device, comprising:
at least one processor, and,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the device status detection method of any one of claims 1 to 8.
10. A storage medium which is a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer-executable instructions for causing a computer to execute the device state detection method according to any one of claims 1 to 8.
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| CN202011535339.3A CN112712111A (en) | 2020-12-23 | 2020-12-23 | Device state detection method, electronic device, and storage medium |
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