CN113963363A - Detection method and device based on AR technology - Google Patents

Detection method and device based on AR technology Download PDF

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CN113963363A
CN113963363A CN202111200515.2A CN202111200515A CN113963363A CN 113963363 A CN113963363 A CN 113963363A CN 202111200515 A CN202111200515 A CN 202111200515A CN 113963363 A CN113963363 A CN 113963363A
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equipment
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CN113963363B (en
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王加辉
吕新伟
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Tmva Shanghai Network Technology Co ltd
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Tmva Shanghai Network Technology Co ltd
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Abstract

The application relates to a detection method and a device based on AR technology, which send out voice prompt when receiving a detection request; when acquiring a nameplate image, performing character recognition on the nameplate image to acquire an equipment label; searching for a corresponding equipment model according to the equipment label, and searching for a corresponding troubleshooting instruction in a preset instruction database according to the equipment model, wherein the troubleshooting instruction at least comprises the following steps: the first troubleshooting instruction, the second troubleshooting instruction and the third troubleshooting instruction are displayed; searching and displaying a corresponding fault confirmation template in a fault database according to the first fault troubleshooting instruction, and sending a voice request; and receiving a fault information value input by a user through the fault confirmation template, comparing the fault information value with the equipment standard value, if the fault information value is consistent with the equipment standard value, displaying a second fault troubleshooting instruction, otherwise, searching and displaying a corresponding overhaul instruction in the instruction database according to the first fault troubleshooting instruction.

Description

Detection method and device based on AR technology
Technical Field
The present application relates to the field of AR technologies, and in particular, to a detection method and apparatus based on an AR technology.
Background
After-sales service is the most important link after sales. After-market services have become a major component of businesses to maintain or expand market share. Especially for some high-precision equipment, whether the manufacturer has perfect after-sales service or not becomes one of the important selection criteria of the purchaser, but since the after-sales service needs to consume a large amount of human resources, the manufacturers with perfect after-sales service on the market still rarely use.
At present, when after-sale service is carried out, after a purchaser determines that equipment has a fault, the user contacts with a manufacturer, and the manufacturer dispatches a technician to a field to maintain the fault equipment within a period.
In the process of implementing the present application, the inventors found that the above-mentioned technology has at least the following problems:
the manufacturer needs to send technicians to the site for inspection and maintenance when performing after-sales service, which results in a long time period and affects the normal production of the purchaser.
Disclosure of Invention
In order to solve the problem that a factory needs to send technicians to a field for inspection and maintenance when after-sales service is carried out, and the time period is long, the application provides a detection method and a detection device based on an AR technology.
The detection method and device based on the AR technology adopt the following technical scheme:
in a first aspect, a detection method based on AR technology is provided, the method including:
sending out a voice prompt related to the request nameplate image when the detection request is received; when the nameplate image is obtained, character recognition is carried out on the nameplate image, and an equipment label is obtained; searching a corresponding equipment model in a preset nameplate database according to the equipment label, and searching a corresponding troubleshooting instruction in a preset instruction database according to the equipment model, wherein the troubleshooting instruction at least comprises: the method comprises the steps of displaying a first troubleshooting instruction, a second troubleshooting instruction and a third troubleshooting instruction; searching a corresponding fault confirmation template in a preset fault database according to the first fault troubleshooting instruction, displaying the fault confirmation template, and sending a voice request related to filling the fault confirmation template; and receiving a fault information value input by a user through the fault confirmation template, comparing the fault information value with a preset equipment standard value, if the fault information value is consistent with the equipment standard value, displaying the second fault troubleshooting instruction, if the fault information value is inconsistent with the equipment standard value, searching a corresponding overhaul instruction in the instruction database according to the first fault troubleshooting instruction, and displaying the overhaul instruction.
Through adopting above-mentioned technical scheme, check out test set acquires the equipment label that corresponds according to the data plate image, check out test set rethread equipment label looks for corresponding equipment model in the data plate database, look for corresponding all troubleshooting instructions in the database through equipment model after that, show the troubleshooting instruction in proper order, it is problematic until the troubleshooting result, thereby confirm the part that the faulty equipment needs to be overhauld, check out test set seeks and shows the maintenance instruction that corresponds according to the troubleshooting instruction, thereby be convenient for the user to overhaul faulty equipment fast, and then reduce the time that faulty equipment waited for the maintenance, so that faulty equipment resumes work fast.
Optionally, obtaining gray values of all pixel points according to the nameplate image; and comparing the gray value with a preset value, clearing the gray value smaller than the preset value, and adjusting the gray value larger than or equal to the preset value to be a preset standard value.
By adopting the technical scheme, the detection equipment adjusts the gray values of all pixel points on the nameplate image according to the preset value, so that the detection equipment performs graying processing on the nameplate image, characters are highlighted, the background is blurred, the data operation amount of the detection equipment during character recognition is reduced, and the character recognition rate is increased.
Optionally, a noise type in the nameplate image is analyzed according to a gray correlation analysis method, where the noise type at least includes: gaussian noise, salt and pepper noise; if the noise type is Gaussian noise, removing the Gaussian noise according to a Gaussian filtering method; and if the noise type is the salt and pepper noise, removing the salt and pepper noise according to a median filtering method.
By adopting the technical scheme, the detection equipment analyzes the noise type in the nameplate image according to the grey correlation analysis method, and performs noise reduction processing on different noise types by using different methods, so that the influence of image noise on character recognition is reduced, and the accuracy of character recognition is improved.
Optionally, if the equipment model corresponding to the equipment label is found in the nameplate database, finding the corresponding troubleshooting instruction according to the equipment model; if the equipment model corresponding to the equipment label is not found in the nameplate database, finding a communication address corresponding to the equipment label in a preset communication database, establishing a communication link with a corresponding terminal according to the communication address, and sending the nameplate picture to the terminal; and receiving a new equipment model from the terminal, and searching the corresponding troubleshooting instruction in the instruction database according to the new equipment model.
By adopting the technical scheme, the detection equipment searches for the corresponding equipment model in the nameplate database according to the equipment label, if the corresponding equipment model is found, the detection equipment searches for the corresponding troubleshooting instruction according to the equipment model, if the corresponding equipment model is not found, the detection equipment sends the nameplate picture to the corresponding terminal, and until the detection equipment receives the new equipment model from the terminal, the detection equipment searches for the corresponding troubleshooting instruction in the instruction database according to the new equipment model, so that the occurrence of the situation that the detection equipment cannot find the corresponding troubleshooting instruction is reduced, and the accuracy of troubleshooting of the detection equipment on the faulty equipment is improved.
Optionally, comparing the fault information value with the fault standard value, and calculating an error value; if the error value is not greater than a preset error standard value, confirming that the fault information value is consistent with the equipment standard value; and if the error value is larger than the error standard value, confirming that the fault information value is inconsistent with the equipment standard value.
By adopting the technical scheme, the error value can be obtained by subtracting the fault information numerical value from the fault standard value and taking the absolute value by the detection equipment, and the detection equipment compares the error value with the error standard value so as to judge whether the fault information numerical value is consistent with the equipment standard value, so that the flexibility of the judgment standard of the detection equipment on the fault is increased, and the occurrence of misjudgment is reduced.
Optionally, searching a corresponding overhaul result template in a preset overhaul database according to the overhaul instruction, and displaying the overhaul result template; receiving a maintenance information numerical value filled in by a user through the maintenance result template, and comparing the maintenance result template with a corresponding maintenance standard numerical value; if the overhaul information numerical value is consistent with the overhaul standard numerical value, sending out a prompt related to overhaul success; if the overhaul result template is inconsistent with the overhaul information template, searching a communication address corresponding to the equipment label in the communication database, establishing a communication link with a corresponding terminal according to the communication address, and sending the overhaul information value, the equipment model, the overhaul instruction and the corresponding third troubleshooting instruction to the terminal; and receiving the maintenance instruction corresponding to the third troubleshooting instruction from the terminal, and displaying the maintenance instruction.
Through adopting above-mentioned technical scheme, check out test set seeks and shows corresponding maintenance result template according to the maintenance instruction, the user fills in the numerical value of maintenance instruction detection into maintenance result template, check out test set receives maintenance result numerical value and contrasts with maintenance standard numerical value, thereby judge whether to overhaul successfully, if not successful, then will overhaul information numerical value, the equipment model, maintenance instruction and the third troubleshooting instruction that corresponds send to the terminal, when check out test set received the maintenance instruction that comes from the terminal, show the maintenance instruction, thereby reduce the possibility that the faulty equipment overhauld the failure.
Optionally, shooting a user according to a preset time interval to obtain an action image; identifying the motion image and extracting motion characteristics; comparing the action image with a preset standard image according to the action characteristics, and calculating the contact ratio; and comparing the contact ratio with a preset threshold value, and if the contact ratio is not less than the threshold value, sending an alarm signal related to the action error.
By adopting the technical scheme, the detection equipment corrects the overhauling action of the user in real time, so that the possibility of error in overhauling of the user is reduced, and the condition that the overhauling result is wrong due to improper action is reduced.
In a second aspect, a capture module configured to issue a voice prompt associated with a request for a nameplate image upon receiving a detection request; the identification module is used for carrying out character identification on the nameplate image when the nameplate image is obtained, and obtaining an equipment label; the troubleshooting module is used for searching a corresponding equipment model in a preset nameplate database according to the equipment label, searching a corresponding troubleshooting instruction in a preset instruction database according to the equipment model, wherein the troubleshooting instruction at least comprises: the system comprises a first troubleshooting instruction, a second troubleshooting instruction and a display module, wherein the first troubleshooting instruction and the second troubleshooting instruction are displayed; the fault confirmation module is used for searching a corresponding fault confirmation template in a preset fault database according to the first fault troubleshooting instruction, displaying the fault confirmation template and sending a voice request related to filling the fault confirmation template; and the maintenance module is used for receiving a fault information value input by a user through the fault confirmation template, comparing the fault information value with a preset equipment standard value, if the fault information value is consistent with the equipment standard value, displaying the second fault troubleshooting instruction, and if the fault information value is inconsistent with the equipment standard value, searching the corresponding maintenance instruction in the instruction database according to the first fault troubleshooting instruction, and displaying the maintenance instruction.
In a third aspect, the detection apparatus comprises a processor and a memory, in which at least one instruction, at least one program, a set of codes, or a set of instructions is stored, which is loaded and executed by the processor to implement the process of detecting the apparatus in an AR technology based detection method as claimed in any one of claims 1 to 7.
In a fourth aspect, a computer-readable storage medium is characterized in that at least one instruction, at least one program, a set of codes, or a set of instructions is stored in the storage medium, and the at least one instruction, the at least one program, the set of codes, or the set of instructions is loaded and executed by a processor to implement the process of detecting a device in an AR technology-based detection method according to any one of claims 1 to 7.
In summary, the present application includes at least one of the following beneficial technical effects:
the corresponding maintenance instruction is searched and displayed through the troubleshooting instruction, so that a user can conveniently and quickly maintain the faulty equipment, and the time for waiting for maintenance of the faulty equipment is shortened, so that the faulty equipment can be quickly recovered to work;
by comparing the error value with the error standard value, whether the fault information value is consistent with the equipment standard value or not is judged, so that the flexibility of the fault judgment standard of the detection equipment is increased, and the occurrence of misjudgment is reduced;
the noise type in the nameplate image is analyzed through a grey correlation analysis method, and different noise types are subjected to noise reduction processing through different methods, so that the influence of image noise on character recognition is reduced, and the accuracy of character recognition is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flowchart of a detection method based on AR technology according to an embodiment of the present application.
Fig. 2 is a schematic structural diagram of a detection apparatus based on AR technology according to an embodiment of the present application.
Fig. 3 is a schematic structural diagram of a detection apparatus provided in an embodiment of the present application.
Detailed Description
The present application is described in further detail below with reference to figures 1-3.
The embodiment of the application discloses a detection method based on AR technology, which can be applied to an after-sales service system, wherein an execution main body can be detection equipment with AR function, the AR technology is augmented reality technology, and the detection method is characterized in that the detection equipment is overlaid after simulation through scientific technologies such as computers and the like, virtual information is applied to the real world, so that real environment and virtual objects are overlaid to the same picture or space in real time to exist at the same time, and the detection method is convenient for being perceived by human beings. The detection equipment is provided with a camera, a loudspeaker, AR glasses and other parts, when the detection equipment is used, the detection equipment obtains an equipment label of the fault equipment by shooting a nameplate of the fault equipment, then basic information of the fault equipment is obtained through the equipment label, the detection equipment searches a fault troubleshooting method and a corresponding maintenance method of the equipment through the basic information, and then the fault troubleshooting method and the maintenance method are displayed in front of a user through an AR technology, so that the user can conveniently check and maintain the equipment.
The process flow shown in fig. 1 will be described in detail below with reference to specific embodiments, and the contents may be as follows:
and 101, sending out a voice prompt related to the request nameplate image when the detection request is received.
In the implementation, the user opens check out test set, clicks the maintenance request on the check out test set, and after check out test set received the maintenance request, check out test set sent voice prompt to the user through self speaker, and voice prompt can be: please shoot the nameplate of the faulty equipment. The user shoots the data plate of the fault equipment through the camera of the detection equipment under the voice prompt, so that the data plate image is obtained.
And 102, when acquiring the nameplate image, performing character recognition on the nameplate image to acquire an equipment label.
In implementation, when the detection equipment receives the nameplate image, the detection equipment performs graying processing on the nameplate image, and the detection equipment performs character recognition on the pictures subjected to the graying processing through a character recognition technology. The graying processing means that in an RGB model, if R = G = B, the color represents a grayscale color, wherein the value of R = G = B is called a grayscale value, therefore, each pixel of the grayscale image only needs one byte to store the grayscale value, the grayscale range is 0-255, and the processed grayscale image can reduce the possibility of banding distortion so as to increase the accuracy of character recognition. The character recognition technology is that the input characters are matched with a given character template in a relevant mode, the similarity degree between the input characters and each template is calculated, and the category with the maximum similarity degree is taken as a recognition result.
Further, if the detection device fails to recognize the device label on the nameplate image, the detection device may send a voice prompt, for example: please shoot the nameplate image again in alignment with the equipment label.
Optionally, the detecting device adjusts a pixel value of the nameplate image, and the corresponding processing may be as follows: acquiring gray values of all pixel points according to the nameplate image; and comparing the gray value with a preset value, clearing the gray value smaller than the preset value, and adjusting the gray value larger than or equal to the preset value to be a preset standard value.
In implementation, the detection device reads the gray values of all the pixel points, the detection device compares the gray values of all the pixel points with a preset value, wherein the preset value can be set to 125, if the gray values of the pixel points are smaller than the preset value, the gray values of the pixel points are cleared, if the gray values of the pixel points are larger than or equal to the preset value, the gray values of the pixel points are adjusted to a preset standard value, the standard value can be 255, the nameplate image is in black and white, characters needing to be identified are highlighted, then the pixel points needing to be identified are reduced, the data processing amount is reduced, and the character identification rate is greatly increased.
Optionally, the detecting device performs noise reduction processing on the nameplate image, and the corresponding processing is as follows:
analyzing the noise type in the nameplate image according to a grey correlation analysis method, wherein the noise type at least comprises the following steps: gaussian noise, salt and pepper noise; if the noise type is Gaussian noise, removing the Gaussian noise according to a Gaussian filtering method; and if the noise type is the salt and pepper noise, removing the salt and pepper noise according to a median filtering method.
In implementation, the detection device analyzes and identifies the noise type of the nameplate image according to a gray correlation analysis method, different noise reduction methods are used for different noise types, the gray correlation analysis method is used as a method for measuring the correlation degree between the factors according to the similarity or dissimilarity degree of development trends among the factors, namely the gray correlation degree, and the gray correlation degree is obtained according to the gray correlation analysis method, so that the image noise can be identified. When the noise type is Gaussian noise, the detection device removes the Gaussian noise by adopting a Gaussian filtering method, and when the noise type is salt and pepper noise, the detection device removes the salt and pepper noise by adopting a median filtering method. After the detection equipment makes an uproar to the image, can reduce the noise interference in the data plate image, improve the precision of character recognition.
103, searching a corresponding equipment model in a preset nameplate database according to the equipment label, and searching a corresponding troubleshooting instruction in a preset instruction database according to the equipment model, wherein the troubleshooting instruction at least comprises: the first troubleshooting instruction, the second troubleshooting instruction and the third troubleshooting instruction are used for displaying the first troubleshooting instruction.
The first troubleshooting instruction is any one of all troubleshooting instructions, and the second troubleshooting instruction is any one of all troubleshooting instructions except the first troubleshooting instruction.
In implementation, the detection equipment searches the equipment model in the nameplate database according to the equipment label, then searches all corresponding troubleshooting instructions in the instruction database according to the equipment model, and then selects a first troubleshooting instruction from all the troubleshooting instructions to display, so that a user can troubleshoot the faulty equipment according to the first troubleshooting instruction. Each troubleshooting instruction only detects a certain part of the faulty equipment, so that the damaged part of the faulty equipment can be determined according to the troubleshooting instruction, and the faulty equipment can be conveniently overhauled.
The troubleshooting instruction is a section of operation video, and the detection device displays the operation video in front of a user through an AR technology so that the user can conveniently and rapidly troubleshoot the troubleshooting device.
Further, the detection device searches a corresponding device warranty age in a preset warranty database according to the device label, compares the device warranty age with the current age, and searches a corresponding device model in the database according to the device label if the device warranty age is not less than the current age. If the warranty age of the equipment is less than the current age, the detection equipment sends out a voice prompt user, and the voice prompt can be as follows: your device warranty age has expired. And the detection equipment is provided with a recharging interface, when the user selects to continue charging the guarantee period, the detection equipment receives the information that the user successfully charges, and the detection equipment changes the equipment guarantee period corresponding to the equipment label in the database, so that the fault equipment is continuously overhauled. For example: the current age is 2021, if the equipment warranty age is 2020, the equipment warranty age is due, and if the equipment warranty age is 2022, the equipment warranty age is not due.
Optionally, if the equipment model corresponding to the equipment label is found in the nameplate database, finding a corresponding troubleshooting instruction according to the equipment model; if the equipment model corresponding to the equipment label is not found in the nameplate database, finding a communication address corresponding to the equipment label in a preset communication database, establishing a communication link with a corresponding terminal according to the communication address, and sending the nameplate picture to the terminal; and receiving a new equipment model from the terminal, and searching a corresponding troubleshooting instruction in an instruction database according to the new equipment model.
In implementation, the detection device searches the device model corresponding to the device label in the database, if the detection device can search the device model corresponding to the device label in the database, the detection device searches all corresponding troubleshooting instructions in the database through the device models, the corresponding troubleshooting instructions are sequentially displayed according to the priority order, and a user performs troubleshooting on the faulty device according to the troubleshooting instructions to obtain the damaged part of the faulty device. If the detection equipment does not find the equipment model corresponding to the equipment label in the database, the detection equipment sends the nameplate image to the terminal, the manufacturer manually identifies the nameplate image to obtain a new equipment model, the terminal sends the new equipment model to the detection equipment, the detection equipment searches all corresponding troubleshooting instructions in the database according to the new equipment model, and finally the detection equipment sequentially displays the troubleshooting instructions according to the priority sequence.
And step 104, searching a corresponding fault confirmation template in a preset fault database according to the first fault troubleshooting instruction, displaying the fault confirmation template, and sending a voice request related to filling the fault confirmation template.
In implementation, the detection device searches a corresponding fault confirmation template in a preset fault database according to the first troubleshooting instruction, displays the fault confirmation template on a display screen, and then sends a voice request: please fill in the test values. And detecting the value at the position detected by the troubleshooting instruction by a user, and filling the detected value into a specific position of the failure confirmation template by the user.
And 105, receiving a fault information value input by a user through a fault confirmation template, comparing the fault information value with a preset equipment standard value, displaying a second fault troubleshooting instruction if the fault information value is consistent with the equipment standard value, searching a corresponding overhaul instruction in an instruction database according to the first fault troubleshooting instruction if the fault information value is inconsistent with the equipment standard value, and displaying the overhaul instruction.
The fault information value is a value detected by a user according to a corresponding troubleshooting instruction, and the standard value is detected by a manufacturer according to normal operation of equipment when the equipment is standard.
When a user inputs a fault information value, the detection equipment receives the fault information value, compares the fault information value with a preset equipment standard value, if the fault information value is consistent with the equipment standard value, it indicates that a fault detection part of the fault equipment has no problem, and displays a second fault troubleshooting instruction. And if the fault information value is not consistent with the equipment standard value, the problem of the detection part of the fault equipment is shown, the detection equipment searches the corresponding maintenance instruction in the instruction database according to the first fault troubleshooting instruction, and the maintenance instruction is displayed in front of the user through AR glasses.
Optionally, the detection device compares the fault information value with the fault standard value, and the corresponding processing is as follows: comparing the fault information value with a fault standard value, and calculating an error value; if the error value is not greater than the preset error standard value, confirming that the fault information value is consistent with the equipment standard value; and if the error value is larger than the error standard value, confirming that the fault information value is inconsistent with the equipment standard value.
In implementation, the detection equipment subtracts the fault information value from the fault standard value to obtain a difference value, and then takes an absolute value of the difference value to obtain an error value, the detection equipment compares the error value with the error standard value, if the error value is not greater than a preset error standard value, the fault information value is in a normal fluctuation range, and the detection equipment considers that the fault information value is consistent with the fault standard value, so that the detection part has no fault; if the error value is larger than the error standard value, the fault information value is abnormal, the detection equipment considers that the fault information value is inconsistent with the fault standard value, and the detection part has a fault.
Optionally, searching a corresponding overhaul result template in a preset overhaul database according to the overhaul instruction, and displaying the overhaul result template; receiving a maintenance information numerical value filled in by a user through a maintenance result template, and comparing the maintenance result template with a corresponding maintenance standard numerical value; if the overhaul information numerical value is consistent with the overhaul standard numerical value, sending out a prompt related to overhaul completion; if the overhaul result template is inconsistent with the overhaul information template, searching a communication address corresponding to the equipment label in a communication database, establishing a communication link with a corresponding terminal according to the communication address, and sending the overhaul result template, the equipment model, an overhaul instruction and a corresponding third troubleshooting instruction to the terminal; and receiving a maintenance instruction corresponding to the third troubleshooting instruction from the terminal, and displaying the maintenance instruction.
In implementation, after the detection device displays the detection instruction, the detection device searches a corresponding overhaul result template in a preset overhaul database according to the overhaul instruction, and displays the overhaul result template through a display screen. The user maintains and detects the trouble part of faulty equipment according to the maintenance instruction, and the user fills the numerical value after detecting in the maintenance result template promptly maintenance information numerical value, and when check out test set received maintenance information numerical value, check out test set compared maintenance information numerical value and preset maintenance standard numerical value.
If the overhaul information numerical value is consistent with the overhaul standard numerical value, the overhaul success of the fault part is indicated, the detection equipment sends out a related prompt of finishing overhaul, and the prompt can be a voice prompt, for example: the overhaul is successful; if the overhaul information numerical value is not consistent with the overhaul standard numerical value, the overhaul failure of the fault part is indicated, the detection equipment searches a corresponding communication address in the communication database according to the equipment label, the detection equipment further has the communication address to establish a communication link with a corresponding terminal, and the detection equipment sends an overhaul result numerical value, an equipment model, an overhaul instruction and a third troubleshooting instruction to the terminal, wherein the third troubleshooting instruction is any one of all troubleshooting instructions. Technical staff analyzes the fault equipment, and the maintenance instruction is sent to the detection equipment through the terminal, and the detection equipment displays the maintenance instruction through the AR glasses.
Furthermore, the maintenance instruction sent by the detection equipment terminal is recorded in the instruction database, so that the maintenance instruction corresponding to the model of the target equipment is perfected, and the next use is facilitated.
Optionally, the detection device corrects the overhaul action of the user in real time, and the corresponding processing is as follows: shooting a user according to a preset time interval to obtain an action image; identifying the action image and extracting action characteristics; comparing the action image with a preset standard image according to the action characteristics, and calculating the contact ratio; and comparing the contact ratio with a preset threshold value, and if the contact ratio is not less than the threshold value, sending an alarm signal related to the action error.
In implementation, the detection device displays the overhaul instruction in front of the user through the AR, and when the user overhauls following the overhaul instruction, the detection device photographs the overhaul action of the user according to a preset time interval, where the preset time interval may be 1 second, and obtains an action image of the user, and the detection device obtains an action feature according to the action image, where the action feature may be a wrist, an arm, or the like. The detection equipment calculates the action image and compares the action image with the standard image according to the position of the action feature, namely, the position of the action feature in the action image is compared with the position of the action feature in the standard image, and the coincidence degree of the action feature is calculated. Check out test set compares contact ratio and threshold, and the threshold is that the producer presets, if contact ratio is not less than the threshold, then check out test set sends alarm signal, and alarm signal can be voice prompt, for example: if the action is wrong, please correct in time; and if the contact ratio is smaller than the threshold value, detecting that the equipment does not act.
The detection method and device based on the AR technology in the embodiment of the application have the implementation principle that: upon receiving a detection request from a user, the detection device issues a verbal prompt associated with the requested nameplate image. When the detection equipment acquires the nameplate image, the detection equipment performs graying processing on the nameplate image, so that the gray values of all pixel points in the nameplate image are adjusted, then the detection equipment performs noise reduction processing on the nameplate image, so that the influence of image noise on character recognition of the nameplate image is reduced, and the nameplate image after being processed by the detection equipment performs character recognition, so that an equipment label is acquired.
The detection equipment searches for a corresponding equipment model in the nameplate database according to the equipment label, so that a corresponding troubleshooting instruction is searched for in the instruction database according to the equipment model, the detection equipment displays a first troubleshooting instruction through the AR glasses, then the detection equipment searches for and displays a corresponding failure confirmation template in the failure database, and a user inputs a failure information value on the failure confirmation template according to a detection result of the first troubleshooting instruction.
The detection equipment subtracts the fault information value from the equipment standard value to obtain a difference value, obtains an absolute value of the difference value to obtain an error value, and compares the error value with the error standard value to judge whether the fault information value is consistent with the equipment standard value. If the first troubleshooting instruction is consistent with the second troubleshooting instruction, the detection equipment displays the second troubleshooting instruction, if the first troubleshooting instruction is inconsistent with the second troubleshooting instruction, the detection equipment searches the corresponding maintenance instruction in the instruction database according to the first troubleshooting instruction, and the maintenance instruction is displayed through the AR glasses, so that a technician does not need to be sent to go to the site for maintenance, the time for maintenance of the faulty equipment is reduced, and the faulty equipment can be rapidly recovered to production.
Based on the same technical concept, an embodiment of the present application further provides a detection apparatus based on AR technology, as shown in fig. 2, the apparatus includes:
the shooting module is used for sending out voice prompts related to the request nameplate images when the detection request is received;
the identification module is used for carrying out character identification on the nameplate image when the nameplate image is obtained, and obtaining an equipment label;
the troubleshooting module is used for searching a corresponding equipment model in a preset nameplate database according to the equipment label, searching a corresponding troubleshooting instruction in a preset instruction database according to the equipment model, wherein the troubleshooting instruction at least comprises: the method comprises the steps of displaying a first troubleshooting instruction, a second troubleshooting instruction and a third troubleshooting instruction;
the fault confirmation module is used for searching a corresponding fault confirmation template in a preset fault database according to the first fault troubleshooting instruction, displaying the fault confirmation template and sending a voice request related to filling the fault confirmation template;
and the maintenance module is used for receiving a fault information value input by a user through the fault confirmation template, comparing the fault information value with a preset equipment standard value, if the fault information value is consistent with the equipment standard value, displaying the second fault troubleshooting instruction, and if the fault information value is inconsistent with the equipment standard value, searching the corresponding maintenance instruction in the instruction database according to the first fault troubleshooting instruction, and displaying the maintenance instruction.
It should be noted that: in the detection apparatus based on the AR technology provided in the above embodiment, when the faulty device is overhauled, only the division of the above functional modules is taken as an example, and in practical application, the function distribution may be completed by different functional modules according to needs, that is, the internal structure of the server is divided into different functional modules, so as to complete all or part of the functions described above. In addition, the detection apparatus based on the AR technology and the detection method based on the AR technology provided by the above embodiments belong to the same concept, and specific implementation processes thereof are detailed in the method embodiments and are not described herein again.
Fig. 3 is a schematic structural diagram of a detection apparatus provided in an embodiment of the present application. The detection devices may vary widely in configuration or performance and may include one or more central processing units (e.g., one or more processors) and memory, one or more storage media (e.g., one or more mass storage devices) that store applications or data. The memory and storage medium may be, among other things, transient or persistent storage. The program stored on the storage medium may include one or more modules (not shown), each of which may include a series of instructions operating on the detection device. Still further, the central processor may be configured to communicate with the storage medium to perform a series of instruction operations in the storage medium on the detection device.
The detection apparatus may also include one or more power supplies, one or more wired or wireless network interfaces, one or more input-output interfaces, one or more keyboards, and/or one or more operating systems, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc.
The detection apparatus may comprise a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors to perform the one or more programs including processing for detecting the apparatus in performing one of the AR technology based detection methods described above.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above embodiments are preferred embodiments of the present application, and the protection scope of the present application is not limited by the above embodiments, so: all equivalent changes made according to the structure, shape and principle of the present application shall be covered by the protection scope of the present application.

Claims (10)

1. A detection method based on AR technology, characterized in that the method comprises:
sending out a voice prompt related to the request nameplate image when the detection request is received;
when the nameplate image is obtained, character recognition is carried out on the nameplate image, and an equipment label is obtained;
searching a corresponding equipment model in a preset nameplate database according to the equipment label, and searching a corresponding troubleshooting instruction in a preset instruction database according to the equipment model, wherein the troubleshooting instruction at least comprises: the method comprises the steps of displaying a first troubleshooting instruction, a second troubleshooting instruction and a third troubleshooting instruction;
searching a corresponding fault confirmation template in a preset fault database according to the first fault troubleshooting instruction, displaying the fault confirmation template, and sending a voice request related to filling the fault confirmation template;
and receiving a fault information value input by a user through the fault confirmation template, comparing the fault information value with a preset equipment standard value, if the fault information value is consistent with the equipment standard value, displaying the second fault troubleshooting instruction, if the fault information value is inconsistent with the equipment standard value, searching a corresponding overhaul instruction in the instruction database according to the first fault troubleshooting instruction, and displaying the overhaul instruction.
2. The detection method based on the AR technology as claimed in claim 1, further comprising, before said recognizing the characters of the nameplate image and obtaining the device label:
acquiring gray values of all pixel points according to the nameplate image;
and comparing the gray value with a preset value, clearing the gray value smaller than the preset value, and adjusting the gray value not smaller than the preset value to be a preset standard value.
3. The detection method based on the AR technology as claimed in claim 1, further comprising, before said recognizing the characters of the nameplate image and obtaining the device label:
analyzing a noise type in the nameplate image according to a grey correlation analysis method, wherein the noise type at least comprises the following steps: gaussian noise, salt and pepper noise;
if the noise type is Gaussian noise, removing the Gaussian noise according to a Gaussian filtering method;
and if the noise type is the salt and pepper noise, removing the salt and pepper noise according to a median filtering method.
4. The detection method based on the AR technology as claimed in claim 1, wherein the finding the corresponding troubleshooting instruction in a preset instruction database according to the device model includes:
if the equipment model corresponding to the equipment label is found in the nameplate database, finding the corresponding troubleshooting instruction according to the equipment model;
if the equipment model corresponding to the equipment label is not found in the nameplate database, finding a communication address corresponding to the equipment label in a preset communication database, establishing a communication link with a corresponding terminal according to the communication address, and sending the nameplate picture to the terminal;
and receiving a new equipment model from the terminal, and searching the corresponding troubleshooting instruction in the instruction database according to the new equipment model.
5. The detection method based on the AR technology as claimed in claim 1, further comprising, after comparing the fault information value with a preset device standard value:
comparing the fault information value with the fault standard value, and calculating an error value;
if the error value is not greater than a preset error standard value, confirming that the fault information value is consistent with the equipment standard value;
and if the error value is larger than the error standard value, confirming that the fault information value is inconsistent with the equipment standard value.
6. The detection method based on the AR technology as claimed in claim 1, wherein the step of searching the corresponding overhaul instruction in the instruction database according to the troubleshooting instruction and displaying the overhaul instruction comprises:
searching a corresponding overhaul result template in a preset overhaul database according to the overhaul instruction, and displaying the overhaul result template;
receiving a maintenance information numerical value filled in by a user through the maintenance result template, and comparing the maintenance result template with a corresponding maintenance standard numerical value;
if the overhaul information numerical value is consistent with the overhaul standard numerical value, sending out a prompt related to overhaul success;
if the overhaul result template is inconsistent with the overhaul information template, searching a communication address corresponding to the equipment label in a preset communication database, establishing a communication link with a corresponding terminal according to the communication address, and sending the overhaul information value, the equipment model, the overhaul instruction and the corresponding third troubleshooting instruction to the terminal;
and receiving the maintenance instruction corresponding to the third troubleshooting instruction from the terminal, and displaying the maintenance instruction.
7. The detection method based on the AR technology as claimed in claim 1, further comprising after said displaying and displaying the service instruction:
shooting a user according to a preset time interval to obtain an action image;
identifying the motion image and extracting motion characteristics;
comparing the action image with a preset standard image according to the action characteristics, and calculating the contact ratio;
comparing the contact ratio with a preset threshold value, and if the contact ratio is not less than the threshold value, sending an alarm signal related to an action error; and if the contact ratio is smaller than the threshold value, no action is performed.
8. An AR technology-based detection apparatus, the apparatus comprising:
the shooting module is used for sending out voice prompts related to the request nameplate images when the detection request is received;
the identification module is used for carrying out character identification on the nameplate image when the nameplate image is obtained, and obtaining an equipment label;
the troubleshooting module is used for searching a corresponding equipment model in a preset nameplate database according to the equipment label, searching a corresponding troubleshooting instruction in a preset instruction database according to the equipment model, wherein the troubleshooting instruction at least comprises: the method comprises the steps of displaying a first troubleshooting instruction, a second troubleshooting instruction and a third troubleshooting instruction;
the fault confirmation module is used for searching a corresponding fault confirmation template in a preset fault database according to the first fault troubleshooting instruction, displaying the fault confirmation template and sending a voice request related to filling the fault confirmation template;
and the maintenance module is used for receiving a fault information value input by a user through the fault confirmation template, comparing the fault information value with a preset equipment standard value, if the fault information value is consistent with the equipment standard value, displaying the second fault troubleshooting instruction, and if the fault information value is inconsistent with the equipment standard value, searching the corresponding maintenance instruction in the instruction database according to the first fault troubleshooting instruction, and displaying the maintenance instruction.
9. A detection device comprising a processor and a memory, said memory having stored therein at least one instruction, at least one program, set of codes or set of instructions, said at least one instruction, said at least one program, said set of codes or set of instructions being loaded and executed by said processor to implement a process of the detection device in an AR technology based detection method according to any of claims 1 to 7.
10. A computer readable storage medium having stored therein at least one instruction, at least one program, a set of codes, or a set of instructions, which is loaded and executed by a processor to implement a process of detecting a device in an AR technology based detection method according to any one of claims 1 to 7.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116308296A (en) * 2023-03-29 2023-06-23 华能海南昌江核电有限公司 Device management method and device, storage medium and electronic device
CN117726322A (en) * 2023-12-25 2024-03-19 深圳市正源翔工业智能有限公司 Intelligent management method and system for probe test equipment

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104318879A (en) * 2014-10-20 2015-01-28 京东方科技集团股份有限公司 Display device and display device failure analysis system and method
CN106863807A (en) * 2017-02-21 2017-06-20 珠海天威飞马打印耗材有限公司 A kind of fault cues method and device of 3D printer
CN111722714A (en) * 2020-06-17 2020-09-29 贵州电网有限责任公司 Digital substation metering operation inspection auxiliary method based on AR technology
CN112465793A (en) * 2020-12-04 2021-03-09 郑州捷安高科股份有限公司 Train fault detection method, device, equipment and storage medium
WO2021082644A1 (en) * 2019-10-29 2021-05-06 北京海益同展信息科技有限公司 Fault detection method and apparatus, and storage medium
CN112785008A (en) * 2020-10-30 2021-05-11 青岛经济技术开发区海尔热水器有限公司 Water heater fault processing method and water heater

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104318879A (en) * 2014-10-20 2015-01-28 京东方科技集团股份有限公司 Display device and display device failure analysis system and method
US20160112702A1 (en) * 2014-10-20 2016-04-21 Boe Technology Group Co., Ltd. Display apparatus, display apparatus fault analysis system and display apparatus fault analysis method
CN106863807A (en) * 2017-02-21 2017-06-20 珠海天威飞马打印耗材有限公司 A kind of fault cues method and device of 3D printer
WO2021082644A1 (en) * 2019-10-29 2021-05-06 北京海益同展信息科技有限公司 Fault detection method and apparatus, and storage medium
CN111722714A (en) * 2020-06-17 2020-09-29 贵州电网有限责任公司 Digital substation metering operation inspection auxiliary method based on AR technology
CN112785008A (en) * 2020-10-30 2021-05-11 青岛经济技术开发区海尔热水器有限公司 Water heater fault processing method and water heater
CN112465793A (en) * 2020-12-04 2021-03-09 郑州捷安高科股份有限公司 Train fault detection method, device, equipment and storage medium

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
孙唯: "查找电气故障方法探讨", 电工技术, no. 5, 31 December 2006 (2006-12-31) *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116308296A (en) * 2023-03-29 2023-06-23 华能海南昌江核电有限公司 Device management method and device, storage medium and electronic device
CN117726322A (en) * 2023-12-25 2024-03-19 深圳市正源翔工业智能有限公司 Intelligent management method and system for probe test equipment

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