CN116781890A

CN116781890A - Fault detection method and device of image pickup device, electronic device and storage medium

Info

Publication number: CN116781890A
Application number: CN202310923913.XA
Authority: CN
Inventors: 陈康; 梁选勤; 余毅鹏
Original assignee: SHENZHEN TIANSHITONG TECHNOLOGY CO LTD
Current assignee: SHENZHEN TIANSHITONG TECHNOLOGY CO LTD
Priority date: 2023-07-25
Filing date: 2023-07-25
Publication date: 2023-09-19

Abstract

The embodiment of the application provides a fault detection method and device of image pickup equipment, electronic equipment and a storage medium, and belongs to the technical field of monitoring cameras. The method comprises the following steps: performing fault detection on the first camera equipment in a fault state to obtain preliminary fault data; extracting parameters of the first camera equipment to obtain target equipment parameters; performing fault voice synthesis according to the preliminary fault data and the target equipment parameters to obtain fault voice data; playing fault voice data to the second camera equipment according to a preset first time period; acquiring fault voice data through the second camera equipment, and analyzing the fault voice data to obtain preliminary fault data and target equipment parameters; and feeding back the analyzed primary fault data and target equipment parameters to the service platform through the second camera equipment. The embodiment of the application can realize the primary detection of the fault of the camera equipment and the acquisition of the equipment fault information, and improves the fault detection efficiency of the wireless network camera.

Description

Fault detection method and device of image pickup device, electronic device and storage medium

Technical Field

The present application relates to the field of monitoring cameras, and in particular, to a fault detection method and apparatus for an image capturing device, an electronic device, and a storage medium.

Background

The wireless network camera is mainly applied to the scene where a wired network cannot be arranged, such as traffic monitoring, factory monitoring, construction site monitoring, agricultural monitoring and the like. When the network or the equipment of the wireless network camera fails, the failure detection needs to be performed in time.

At present, two network fault detection methods of a network camera are mainly adopted, the first method is that the wireless network camera performs preliminary self-detection according to a self-detection scheme set in advance, then fault information is stored in a storage unit of the wireless network camera, and a technician obtains a fault information file from the storage unit for analysis and detection when arriving at a fault site; and the second is that a technician is connected with the wireless network camera in a communication way after arriving at a fault site, and logs in a system of the fault equipment to perform site detection and collect fault information. However, these methods all require technicians to reach the fault site, and the detection efficiency of the fault is low depending on the network environment and the equipment state of the site. Therefore, how to improve the failure detection efficiency of the wireless network camera is a technical problem to be solved.

Disclosure of Invention

The embodiment of the application mainly aims to provide a fault detection method and device of image pickup equipment, electronic equipment and a storage medium, and aims to improve the fault detection efficiency of a wireless network camera.

To achieve the above object, a first aspect of an embodiment of the present application proposes a fault detection method of an image capturing apparatus, the method including:

performing fault detection on the first camera equipment in a fault state to obtain preliminary fault data;

extracting parameters of the first camera equipment to obtain target equipment parameters;

performing fault voice synthesis according to the preliminary fault data and the target equipment parameters to obtain fault voice data;

playing the fault voice data to the second camera equipment according to a preset first time period;

acquiring the fault voice data through the second camera equipment, and analyzing the fault voice data to obtain the preliminary fault data and the target equipment parameters;

and feeding the analyzed primary fault data and the target equipment parameters back to a service platform through the second camera equipment.

In some embodiments, the performing fault detection on the first image capturing apparatus in the fault state to obtain preliminary fault data includes:

Performing network detection on the first camera equipment to obtain a network state;

determining a first image capturing apparatus in the failure state according to the network state;

and performing fault detection on the first image pickup equipment to obtain the preliminary fault data.

In some embodiments, the performing network detection on the first image capturing device to obtain a network state includes:

playing fault detection audio data to the first camera device through a mobile terminal; wherein the fault detection audio data comprises a fault information detection instruction;

acquiring the fault detection audio data through the first camera equipment, and analyzing the fault detection audio data to obtain the fault information detection instruction;

and carrying out network detection on the first image pickup equipment based on the fault information detection instruction to obtain the network state.

In some embodiments, the performing fault voice synthesis according to the preliminary fault data and the target device parameter to obtain fault voice data includes:

performing fault coding on the preliminary fault data and the target equipment parameters to obtain target fault coding data;

and performing audio synthesis on the target fault coding data to obtain the fault voice data.

In some embodiments, performing fault coding on the preliminary fault data and the target device parameter to obtain target fault coded data includes:

performing data splicing on the preliminary fault data and the target equipment parameters according to a preset fault coding format to obtain first fault data;

carrying out binary conversion on the first fault data to obtain second fault data;

determining the code compensation amount of the second fault data based on a preset fault code length;

performing coding compensation processing on the second fault data based on the coding compensation quantity to obtain third fault data;

and carrying out coding processing on the third fault data to obtain the target fault coded data.

In some embodiments, the audio synthesis of the target fault encoded data to obtain the fault voice data includes:

performing frequency domain calculation on the target fault coded data to obtain first spectrum information;

and performing audio analog signal conversion on the first frequency spectrum information to obtain the fault voice data.

In some embodiments, the obtaining the fault voice data by the second image capturing device and analyzing the fault voice data to obtain the preliminary fault data and the target device parameter includes:

Receiving the fault voice data;

performing fault information conversion on the fault voice data to obtain fault coding information;

decoding the fault coding information to obtain fault decoding data;

and extracting fault information from the fault decoding data to obtain the preliminary fault data and the target equipment parameters.

To achieve the above object, a second aspect of an embodiment of the present application proposes a failure detection apparatus of an image pickup apparatus, the apparatus comprising:

the fault detection module is used for carrying out fault detection on the first camera equipment in the fault state to obtain preliminary fault data;

the equipment parameter extraction module is used for extracting parameters of the first camera equipment to obtain target equipment parameters;

the voice synthesis module is used for carrying out fault voice synthesis according to the preliminary fault data and the target equipment parameters to obtain fault voice data;

the fault voice playing module is used for playing the fault voice data to the second camera equipment according to a preset first time period;

the fault audio analysis module is used for acquiring the fault voice data through the second camera equipment and analyzing the fault voice data to obtain the preliminary fault data and the target equipment parameters;

And the feedback module is used for feeding the analyzed primary fault data and the target equipment parameters back to a service platform through the second camera equipment.

To achieve the above object, a third aspect of the embodiments of the present application proposes an electronic device comprising a memory, a processor, a program stored on the memory and executable on the processor, and a data bus for enabling a connection communication between the processor and the memory, the program, when executed by the processor, implementing the method according to the first aspect.

To achieve the above object, a fourth aspect of the embodiments of the present application proposes a storage medium, which is a computer-readable storage medium, for computer-readable storage, the storage medium storing one or more programs executable by one or more processors to implement the method described in the first aspect.

The application provides a fault detection method, a fault detection device, electronic equipment and a storage medium of image pickup equipment, which are used for obtaining preliminary fault data by carrying out fault detection on first image pickup equipment in a fault state; extracting parameters of the first camera equipment to obtain target equipment parameters; performing fault voice synthesis according to the preliminary fault data and the target equipment parameters to obtain fault voice data; playing fault voice data to the second camera equipment according to a preset first time period; acquiring fault voice data through the second camera equipment, and analyzing the fault voice data to obtain fault information, namely preliminary fault data and target equipment parameters; and feeding back the analyzed primary fault data and target equipment parameters to the service platform through the second camera equipment. The embodiment of the application can realize the primary detection of the fault of the camera equipment and the acquisition of the equipment fault information, and improves the fault detection efficiency of the wireless network camera.

Drawings

Fig. 1 is a flowchart of a failure detection method of an image pickup apparatus provided by an embodiment of the present application;

fig. 2 is a flowchart of step S101 in fig. 1;

fig. 3 is a flowchart of step S201 in fig. 2;

fig. 4 is a flowchart of step S103 in fig. 1;

fig. 5 is a flowchart of step S401 in fig. 4;

fig. 6 is a flowchart of step S402 in fig. 4;

fig. 7 is a flowchart of step S105 in fig. 1;

fig. 8 is a schematic structural diagram of a failure detection device of an image pickup apparatus provided in an embodiment of the present application;

fig. 9 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application.

Detailed Description

The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

It should be noted that although functional block division is performed in a device diagram and a logic sequence is shown in a flowchart, in some cases, the steps shown or described may be performed in a different order than the block division in the device, or in the flowchart. The terms first, second and the like in the description and in the claims and in the above-described figures, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the application only and is not intended to be limiting of the application.

First, several nouns involved in the present application are parsed:

RS (Reed-Solomon) coding is a commonly used error correction coding technique in communication and storage systems, and performs an error correction function by adding redundant information before transmitting data, which can be used to detect and correct errors introduced during channel transmission. RS encoding calculates redundant information using an operation on a coefficient field so that original data can be restored by the redundant information even if there are a plurality of errors in the data. The RS code has a high error correction capability, can correct a plurality of errors, and is applicable to data blocks of different lengths. RS encoding is widely used in the fields of radio, satellite communication, optical fiber communication, etc. in digital communication, and in media such as magnetic disks and optical disks in data storage.

RS decoding is a process of decoding data encoded using an RS encoding technique. The RS decoding aims to restore the original data, and by performing an operation on the received encoded data using an algebraic operation method corresponding to the RS encoding, the position of the error can be detected and restored by an error correction algorithm.

The wireless network camera is mainly applied to the scene where a wired network cannot be arranged, such as traffic monitoring, factory monitoring, construction site monitoring, agricultural monitoring and the like. When the network or the equipment of the wireless network camera fails, the wireless network camera cannot communicate information and information with other equipment or servers, and the failure detection needs to be performed in time.

The wireless network cameras include, but are not limited to, 4G network cameras, 5G network cameras and WiFi cameras.

At present, two main network fault detection methods of network cameras are:

the first is that the wireless network camera performs preliminary self-checking according to a preset self-checking scheme, and after detecting the fault position, the fault information is stored in a storage unit of the wireless network camera, such as a storage card and a hard disk; and after the technician arrives at the fault site, acquiring a fault information file from the storage unit for analysis and detection.

And the second is that a technician is connected with the wireless network camera in a communication way after arriving at a fault site, and logs in a system of the fault equipment to perform site detection and collect fault information.

However, these methods all require technicians to reach the fault site, and the detection efficiency of the fault is low depending on the network environment and the equipment state of the site. Therefore, how to improve the failure detection efficiency of the wireless network camera is a technical problem to be solved.

Based on the above, the embodiment of the application provides a fault detection method and device of an image pickup device, an electronic device and a storage medium, aiming at improving the fault detection efficiency of a wireless network camera.

The method, the device, the electronic device and the storage medium for detecting the fault of the image capturing apparatus provided by the embodiment of the application are specifically described through the following embodiments, and the method for detecting the fault of the image capturing apparatus in the embodiment of the application is described first.

Fig. 1 is an optional flowchart of a fault detection method of an image capturing apparatus provided in an embodiment of the present application, where the method in fig. 1 may include, but is not limited to, steps S101 to S106.

Step S101, performing fault detection on first image pickup equipment in a fault state to obtain preliminary fault data;

step S102, extracting parameters of a first camera device to obtain target device parameters;

step S103, performing fault voice synthesis according to the preliminary fault data and the target equipment parameters to obtain fault voice data;

step S104, playing fault voice data to the second camera equipment according to a preset first time period;

step S105, obtaining fault voice data through the second camera equipment, and analyzing the fault voice data to obtain preliminary fault data and target equipment parameters;

And step S106, feeding back the analyzed primary fault data and target equipment parameters to the service platform through the second camera equipment.

Step S101 to step S106 shown in the embodiment of the present application, primary fault data is obtained by performing fault detection on the first image capturing device in the fault state; extracting parameters of the first camera equipment to obtain target equipment parameters; performing fault voice synthesis according to the preliminary fault data and the target equipment parameters to obtain fault voice data; playing fault voice data to the second camera equipment according to a preset first time period; acquiring fault voice data through the second camera equipment, and analyzing the fault voice data to obtain fault information, namely preliminary fault data and target equipment parameters; and feeding back the analyzed primary fault data and target equipment parameters to the service platform through the second camera equipment. The embodiment of the application can realize the primary detection of the fault of the camera equipment and the acquisition of the equipment fault information, and improves the fault detection efficiency of the wireless network camera.

The first camera device is a wireless network camera in fault, the second camera device is a wireless network camera in normal operation, and the second camera device is in communication connection with the service platform, wherein the number of the second camera devices is at least one.

It should be noted that, the distance between the first image capturing apparatus and the second image capturing apparatus is a sound receiving distance range that can be supported by the sound receiving device of the network camera, and the sound receiving device may be an internal microphone or an external pickup, which is not limited in this embodiment.

Referring to fig. 2, in some embodiments, step S101 may include, but is not limited to, steps S201 to S203:

step S201, network detection is carried out on the first camera equipment to obtain a network state;

step S202, determining a first image capturing apparatus in a failure state according to a network state;

step S203, performing fault detection on the first image capturing apparatus to obtain preliminary fault data.

In the steps S201 to S203 shown in the embodiment of the present application, by detecting the network state of the first image capturing device, it is determined that the first image capturing device is actually in a fault state, and then the first image capturing device is subjected to preliminary fault detection according to a preset self-detection scheme, so as to obtain preliminary fault data, and a technician does not need to go to a fault site to know the cause of the fault of the image capturing device, thereby improving the fault detection efficiency of the wireless network camera.

In step S201 of some embodiments, the first image capturing apparatus is periodically subjected to network detection for a preset second time period, so as to obtain a network state, for example, the first image capturing apparatus is periodically subjected to network detection at intervals of 30 minutes.

In some embodiments, the first image capturing apparatus is configured to perform network detection by sending a network request to a service platform or a website of a third party, including but not limited to sending a ping packet, an HTTP request, and the like.

In some embodiments, the system at the wireless network camera may send a ping packet to the service platform or the IP address of the website of the third party according to the preset second time period, so as to obtain a network state, and further determine whether the wireless network camera is automatically recovered or still in a fault state according to the network state. If a response returned by the service platform or the website of the third party according to the ping packet is received, the wireless network camera is characterized to be in an on-line state, namely, the wireless network camera is restored to a normal running state; and if the response returned by the service platform or the website of the third party according to the ping packet is not received, the wireless network camera is characterized as being in a fault state.

In some cases, for example, the surrounding network signals are bad, the wireless network camera is in a fault state due to disconnection, and when the network signals are recovered to be normal, the normal operation state is recovered again, and no alarm is needed again, so that a technician can see the fault information and the current state fed back by the wireless network camera on the service platform, and judge that the fault of the wireless network camera is solved, thereby improving the efficiency of fault detection and maintenance.

In some embodiments, multiple network detections are required for the first image capturing apparatus, and the first image capturing apparatus is determined to be in a failure state when the number of network states characterizing the first image capturing apparatus as being in a failure state exceeds a preset threshold. For example, the first image capturing apparatus continuously sends 5 ping instructions to the service platform, and if the response times returned by the service platform are less than 3 times, the first image capturing apparatus is in a fault state.

In step S203 of some embodiments, the first image capturing apparatus in the failure state performs self-inspection on the machine according to the set self-inspection scheme, and determines the cause of the failure.

In some embodiments, the self-checking scheme is a detection sequence defined by a technician, for example, detecting whether the wireless network card is normal, then detecting network configuration, then detecting network bandwidth, access rights, firewall, etc., and the specific self-checking scheme is not limited thereto.

It should be noted that, the preset second time period, the network detection mode, the network detection times and the self-checking scheme all need to be set according to the actual scene.

The preliminary fault data are fault codes of the image pickup device, and the fault codes are preset and used for assisting technicians in locating fault positions.

In some embodiments, the preliminary fault data may include, but is not limited to including:

1, the wireless module cannot be injected with a network;

2 indicates that the wireless network card cannot bind the IP;

3, the wireless network card can not be communicated with an external network;

4, the wireless network card can not be connected with the server;

5 indicates that the wireless network card cannot acquire the version number;

and 6, the communication failure between the master control and the wireless network card is indicated.

Referring to fig. 3, in some embodiments, step S201 may include, but is not limited to, steps S301 to S303:

step S301, playing, by the mobile terminal, the failure detection audio data to the first image capturing apparatus; wherein the fault detection audio data comprises a fault information detection instruction;

step S302, acquiring fault detection audio data through a first camera device, and analyzing the fault detection audio data to obtain a fault information detection instruction;

step S303, performing network detection on the first image capturing apparatus based on the fault information detection instruction, to obtain a network state.

In the steps S301 to S303 shown in the embodiment of the present application, by receiving the fault detection audio data sent by the mobile terminal, and analyzing the fault detection audio data to obtain a fault information detection instruction, the first camera device is subjected to network detection according to the fault information detection instruction to obtain a network state, so that the network state can be obtained without waiting for self-detection of the next period, and the network state detection method can be used for detecting the network condition of the wireless network camera by a technician in a scene of the scene, without performing communication connection with the wireless network camera one by one, only the mobile terminal, such as a mobile phone, a tablet computer, and other devices capable of playing the fault detection audio data are required, so that the wireless network camera can automatically detect, and if a fault exists, the network state can be fed back in time, thereby improving the fault detection efficiency of the wireless network camera.

It should be noted that, a technician uses the mobile terminal to directly play the fault detection audio data near the first image capturing device, so that the radio receiving device of the first image capturing device can receive the fault detection audio data, and further analyze the fault detection audio data.

In step S302 of some embodiments, the first image capturing apparatus analyzing the fault detection audio data to obtain the fault information detection instruction may be performing spectral conversion and decoding processing on the fault detection audio data to obtain the fault information detection instruction.

It should be noted that, step S301 and step S303 are manual parts of the method for realizing fault detection and fault information collection in a semi-automatic manner, that is, the fault detection audio data needs to be manually played, so that the first image capturing device detects to realize on-site fault detection.

In step S102 of some embodiments, the extracted target device parameter may be a unique identifier such as an international mobile equipment identity IMEI or a mobile equipment identity MEID, which is used to identify the identity information of the first image capturing device.

Referring to fig. 4, step S103 may include, but is not limited to, steps S401 to S402:

step S401, performing fault coding on the preliminary fault data and the target equipment parameters to obtain target fault coding data;

Step S402, audio synthesis is carried out on the target fault coding data to obtain fault voice data.

Referring to fig. 5, in some embodiments, step S401 may further include, but is not limited to, steps S501 to S505:

step S501, performing data splicing on the preliminary fault data and the target equipment parameters according to a preset fault coding format to obtain first fault data;

step S502, carrying out binary conversion on the first fault data to obtain second fault data;

step S503, determining the code compensation amount of the second fault data based on the preset fault code length;

step S504, performing code compensation processing on the second fault data based on the code compensation amount to obtain third fault data;

step S505, performing encoding processing on the third fault data to obtain target fault encoded data.

In the steps S501 to S505 shown in the embodiment of the present application, data splicing is performed on the preliminary fault data and the target device parameters to obtain first fault data, and then, the first fault data is subjected to binary conversion, code compensation processing and coding to obtain target fault coded data, so that reliability of data transmission can be improved, and error rate in the data transmission process can be reduced.

The technical scheme formed in step S501 to step S505 is the RS encoding process.

The preset fault coding format is a template and is used for determining the splicing sequence of the primary fault data and the target equipment parameters.

In some embodiments, the binary conversion is converting the decimal first fault data into a binary format, such as: the preliminary fault data is 2, and the target equipment parameter is 0101; the primary fault data and the target equipment parameters are subjected to data splicing to obtain first fault data, wherein the first fault data comprises the following steps: 01012; the first fault data is converted into binary data to obtain second fault data 1111110100.

And comparing the second fault data with a preset fault code length to determine the length of the data block to be compensated, and adding the data block behind the second fault data to obtain third fault data.

And finally, encoding the third fault data to obtain target fault encoded data.

Referring to fig. 6, in some embodiments, step S402 includes, but is not limited to, steps S601 to S602:

step S601, performing frequency domain calculation on target fault coding data to obtain first frequency spectrum information;

Step S602, performing audio analog signal conversion on the first frequency spectrum information to obtain fault voice data.

In the steps S601 to S602 shown in the embodiment of the present application, by performing frequency domain calculation and audio model signal conversion on the target fault coding data, fault voice data is obtained, and then the fault voice data is played to the second image capturing device, so that the fault information of the first image capturing device can be received and fed back, and timely feedback of the fault information is realized.

In some embodiments, step S601 may include, but is not limited to including the steps of:

performing fast Fourier transform processing on the target fault coded data to obtain fault time domain data;

performing window processing on the fault time domain data to obtain windowed fault data;

and performing discrete Fourier transform processing on the windowed fault data to obtain first frequency spectrum data.

In step S602 of some embodiments, the first spectral information is converted into faulty speech data using a vocoder.

In some embodiments, the fault voice data is a click, 1 is a click, 0 is a click, e.g., 01100101 the fault voice data is a click-click. Therefore, the second camera equipment can quickly identify fault voice data after receiving, and the accuracy and reliability of fault information transmission are improved.

In step S104 of some embodiments, the faulty voice data may be played to the technician' S mobile terminal in addition to the faulty voice data being played to the second image pickup apparatus.

It should be noted that, the time interval for playing the fault voice data may be set in combination with the actual scenario, for example, the time interval for allowing the fault voice data to be played is: 08:00-20:00, and reducing the disturbing degree.

When the mobile terminal receives the fault voice data, analyzing the fault voice data to obtain fault information of the first camera equipment, namely preliminary fault data and target equipment parameters; and then the fault information of the first camera equipment is fed back to the service platform, so that the automatic acquisition of the fault information is realized.

Referring to fig. 7, in some embodiments, step S105 may include, but is not limited to, steps S701 to S704:

step S701, receiving fault voice data;

step S702, performing fault information conversion on fault voice data to obtain fault coding information;

step S703, decoding the fault coding information to obtain fault decoding data;

and step S704, extracting fault information from the fault decoding data to obtain preliminary fault data and target equipment parameters.

In the steps S701 to S704 shown in the embodiment of the present application, the second image capturing device performs fault information conversion, decoding processing and fault information extraction on the fault voice data to obtain the fault information of the first image capturing device, that is, the preliminary fault data and the target device parameters, so that the fault information of the first image capturing device can be fed back to the service platform, timely feedback of the fault information is realized, and further automatic acquisition of the fault information is realized.

After the service platform receives the fault information of the first camera device, namely the preliminary fault data and the target device parameters, technicians can prepare equipment required for maintenance according to the preliminary fault data in a targeted manner, and maintenance efficiency can be improved.

In some embodiments, the fault information conversion of the fault voice data can be performed through framing, fourier transformation and other operations, so as to extract fault coded data. Performing RS decoding on the fault coded data, wherein the fault coded data is checked, and if the decoding check finds that errors exist, recovering the error data into correct data through operation and correction algorithm; preliminary fault data and target device parameters are then extracted. The RS encoding and the RS decoding are used for fault information, so that the accuracy and the reliability of fault information propagation can be improved, and information error propagation is avoided.

In one embodiment, a method for automatically completing fault detection and fault information collection of an image capturing device, without a technician arriving at a fault site for processing, can realize primary detection of a fault of the image capturing device and collection of device fault information, improves the fault detection efficiency of a wireless network camera, and comprises the following steps:

performing network detection on the first camera equipment according to a preset second time period to obtain a network state;

determining that the first camera device is in a fault state according to the network state;

performing fault detection on the first camera equipment to obtain preliminary fault data;

performing coding processing on the third fault data to obtain target fault coded data;

performing audio analog signal conversion on the first frequency spectrum information to obtain fault voice data;

playing fault voice data to the second camera equipment according to a preset first time period;

receiving the fault voice data through the second camera device;

decoding the fault coding information to obtain fault decoding data;

extracting fault information from the fault decoding data to obtain preliminary fault data and target equipment parameters;

and feeding back the analyzed primary fault data and target equipment parameters to the service platform through the second camera equipment.

In the automatic method, a technician does not need to reach a fault site in the whole process, and the first camera equipment in a fault state, the second camera equipment in a normal state and the server finish fault detection and fault information collection, so that the fault detection efficiency of the wireless network camera is improved.

In one embodiment, a method for semi-automatically completing fault detection and fault information collection of a camera device includes steps of, when a technician arrives at a site, determining whether a wireless network camera on the site has a fault, and if the wireless network camera has the fault, rapidly processing the fault, thereby improving the fault detection efficiency of the wireless network camera, including but not limited to:

Playing the fault detection audio data to the first camera device through the mobile terminal; wherein the fault detection audio data comprises a fault information detection instruction;

acquiring fault detection audio data through first camera equipment, and analyzing the fault detection audio data to obtain a fault information detection instruction;

network detection is carried out on the first camera equipment based on the fault information detection instruction, and a network state is obtained;

playing fault voice data to the mobile terminal;

receiving fault voice data through a mobile terminal;

decoding the fault coding information to obtain fault decoding data;

and feeding back the analyzed primary fault data and target equipment parameters to the service platform through the mobile terminal.

It should be noted that, when a technician plays the fault detection audio data through the mobile terminal on site, so that the first camera device performs self-checking to determine the fault voice data in the fault state and played, other second camera devices on site can also receive the fault information fed back from the second camera device, and the service platform also receives the fault information fed back by the mobile terminal and retains the latest received fault information.

The semi-automatic method is characterized in that a mobile terminal is not required to be in communication connection with the first camera equipment by a technician in the whole process, the mobile terminal is only required to be controlled to play sound, the detection of the wireless network camera on site can be completed, if faults exist, the detection operation of the technician is greatly simplified, the fault investigation and the fault information collection can be completed by one key, and the fault detection efficiency of the wireless network camera is improved.

In addition, the semi-automatic method can also be used for confirming whether the fault condition of the wireless network camera in the fault state changes again after a technician arrives at the fault site, whether the wireless network camera returns to normal, and the like.

In one embodiment, the automated method is to maintain the execution state in the whole process, while the semi-automated method can directly use the first fault device to perform self-checking, so that the fault detection result can be obtained without waiting for the next self-checking period even if the fault detection result is obtained, and the fault detection efficiency of the wireless network camera can be improved.

Referring to fig. 8, an embodiment of the present application further provides a fault detection device of an image capturing apparatus, which may implement the fault detection method of the image capturing apparatus, where the device includes:

a fault detection module 801, configured to perform fault detection on a first image capturing apparatus in a fault state, to obtain preliminary fault data;

the device parameter extraction module 802 is configured to perform parameter extraction on the first image capturing device to obtain a target device parameter;

the voice synthesis module 803 is configured to perform fault voice synthesis according to the preliminary fault data and the target device parameters, so as to obtain fault voice data;

The fault voice playing module 804 is configured to play fault voice data to the second image capturing device according to a preset first time period;

the fault audio analysis module 805 is configured to obtain fault voice data through the second image capturing device, and analyze the fault voice data to obtain preliminary fault data and target device parameters;

and a feedback module 806, configured to feed back the analyzed primary fault data and the target device parameters to the service platform through the second image capturing device.

The specific implementation of the fault detection device of the image capturing apparatus is basically the same as the specific embodiment of the fault detection method of the image capturing apparatus, and will not be described herein.

The embodiment of the application also provides electronic equipment, which comprises: the image pickup apparatus includes a memory, a processor, a program stored on the memory and executable on the processor, and a data bus for realizing connection communication between the processor and the memory, the program realizing the above-described failure detection method of the image pickup apparatus when executed by the processor. The electronic equipment can be any intelligent terminal including a tablet personal computer, a vehicle-mounted computer and the like.

Referring to fig. 9, fig. 9 illustrates a hardware structure of an electronic device according to another embodiment, the electronic device includes:

The processor 901 may be implemented by a general purpose CPU (central processing unit), a microprocessor, an application specific integrated circuit (ApplicationSpecificIntegratedCircuit, ASIC), or one or more integrated circuits, etc. for executing related programs to implement the technical solution provided by the embodiments of the present application;

the memory 902 may be implemented in the form of read-only memory (ReadOnlyMemory, ROM), static storage, dynamic storage, or random access memory (RandomAccessMemory, RAM). The memory 902 may store an operating system and other application programs, and when the technical solutions provided in the embodiments of the present specification are implemented by software or firmware, relevant program codes are stored in the memory 902, and the processor 901 invokes a fault detection method of the image capturing apparatus that executes the embodiments of the present application;

an input/output interface 903 for inputting and outputting information;

the communication interface 904 is configured to implement communication interaction between the device and other devices, and may implement communication in a wired manner (e.g. USB, network cable, etc.), or may implement communication in a wireless manner (e.g. mobile network, WIFI, bluetooth, etc.);

A bus 905 that transfers information between the various components of the device (e.g., the processor 901, the memory 902, the input/output interface 903, and the communication interface 904);

wherein the processor 901, the memory 902, the input/output interface 903 and the communication interface 904 are communicatively coupled to each other within the device via a bus 905.

The embodiment of the application also provides a storage medium, which is a computer readable storage medium and is used for computer readable storage, the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to realize the fault detection method of the image pickup device.

The memory, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory remotely located relative to the processor, the remote memory being connectable to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The embodiments described in the embodiments of the present application are for more clearly describing the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application, and those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

It will be appreciated by those skilled in the art that the solutions shown in fig. 1-7 are not limiting on the embodiments of the application and may include more or fewer steps than shown, or certain steps may be combined, or different steps.

The above described apparatus embodiments 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 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 this embodiment.

Those of ordinary skill in the art will appreciate that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof.

The terms "first," "second," "third," "fourth," and the like in the description of the application and in the above figures, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be understood that in the present application, "at least one (item)" means one or more, and "a plurality" means two or more. "and/or" for describing the association relationship of the association object, the representation may have three relationships, for example, "a and/or B" may represent: only a, only B and both a and B are present, wherein a, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b or c may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the above-described division of units is merely a logical function division, and there may be another division manner in actual implementation, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, including multiple instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present application. And the aforementioned storage medium includes: a U-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, or other various media capable of storing a program.

The preferred embodiments of the present application have been described above with reference to the accompanying drawings, and are not thereby limiting the scope of the claims of the embodiments of the present application. Any modifications, equivalent substitutions and improvements made by those skilled in the art without departing from the scope and spirit of the embodiments of the present application shall fall within the scope of the claims of the embodiments of the present application.

Claims

1. A fault detection method of an image pickup apparatus, characterized by comprising:

2. The method according to claim 1, wherein performing fault detection on the first image capturing apparatus in the fault state to obtain preliminary fault data includes:

3. The method according to claim 2, wherein the performing network detection on the first image capturing device to obtain a network state includes:

4. A method according to any one of claims 1 to 3, wherein said performing a fault speech synthesis based on said preliminary fault data and said target device parameters to obtain fault speech data comprises:

5. The method of claim 4, wherein performing fault encoding on the preliminary fault data and the target device parameter to obtain target fault encoded data comprises:

6. The method of claim 4, wherein said audio synthesizing said target fault coded data to obtain said fault speech data comprises:

7. The method according to claim 1, wherein the acquiring the faulty voice data by the second image capturing device and analyzing the faulty voice data to obtain the preliminary faulty data and the target device parameter, includes:

receiving the fault voice data;

decoding the fault coding information to obtain fault decoding data;

8. A failure detection apparatus of an image pickup device, characterized by comprising:

9. An electronic apparatus comprising a memory storing a computer program and a processor that when executing the computer program implements the fault detection method of the image pickup apparatus according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the fault detection method of the image pickup apparatus according to any one of claims 1 to 7.