CN115277362A - Fault diagnosis method, fault diagnosis device, electronic equipment and computer readable medium - Google Patents
Fault diagnosis method, fault diagnosis device, electronic equipment and computer readable medium Download PDFInfo
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Abstract
The embodiment of the application discloses a fault diagnosis method and device, electronic equipment and a computer readable medium. An embodiment of the method comprises: acquiring an identification, an Internet Protocol (IP) address and a port number of intelligent equipment to be detected; querying the intelligent device from the first system based on the identification; determining distribution network information of the intelligent device based on the IP address and the port number, and inquiring network data associated with the distribution network information from the second system; summarizing the equipment data and the network data to generate comprehensive data; and carrying out fault diagnosis on the intelligent equipment based on the comprehensive data to obtain a fault diagnosis result. The embodiment improves the fault diagnosis efficiency and the fault diagnosis accuracy.
Description
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to a fault diagnosis method, a fault diagnosis device, electronic equipment and a computer readable medium.
Background
With the development of internet technology, in more and more scenes such as families, business and the like, intelligent equipment (for example, a camera device capable of being networked) can be deployed, and functions such as remote control and scene linkage can be realized by accessing the intelligent equipment to a network. When a smart device fails, it is usually necessary to perform fault diagnosis on the smart device and a network accessed by the smart device at the same time.
In the prior art, network data of a network to which an intelligent device is connected is usually stored in an independent system and cannot be directly acquired, so that maintenance personnel is usually required to go to the door to detect the intelligent device and the network to which the intelligent device is connected, and fault diagnosis is performed according to experience by observing fault phenomena. The method has the problems of complex fault diagnosis process, higher requirement on the skills of maintenance personnel, low fault diagnosis efficiency and lower accuracy.
Disclosure of Invention
The embodiment of the application provides a fault diagnosis method, a fault diagnosis device, electronic equipment and a computer readable medium, so as to solve the technical problems of low fault diagnosis efficiency and low accuracy in the prior art.
In a first aspect, an embodiment of the present application provides a fault diagnosis method, where the method includes: acquiring an identifier, an Internet Protocol (IP) address and a port number of intelligent equipment to be detected; querying the intelligent device for device data from a first system based on the identification; determining distribution network information of the intelligent equipment based on the IP address and the port number, and inquiring network data associated with the distribution network information from a second system; summarizing the equipment data and the network data to generate comprehensive data; and carrying out fault diagnosis on the intelligent equipment based on the comprehensive data to obtain a fault diagnosis result.
In a second aspect, an embodiment of the present application provides a fault diagnosis apparatus, including: the device comprises an acquisition unit, a detection unit and a control unit, wherein the acquisition unit is used for acquiring the identification, the Internet protocol IP address and the port number of the intelligent device to be detected; the first query unit is used for querying the device data of the intelligent device from a first system based on the identification; the second query unit is used for determining the distribution network information of the intelligent equipment based on the IP address and the port number, and querying network data associated with the distribution network information from a second system; the generating unit is used for summarizing the equipment data and the network data to generate comprehensive data; and the first fault diagnosis unit is used for carrying out fault diagnosis on the intelligent equipment based on the comprehensive data to obtain a fault diagnosis result.
In a third aspect, an embodiment of the present application provides an electronic device, including: one or more processors; storage means having one or more programs stored thereon which, when executed by the one or more processors, cause the one or more processors to carry out the method according to any one of the preceding first aspects.
In a fourth aspect, the present application provides a computer-readable medium, on which a computer program is stored, which when executed by a processor implements the method according to any one of the first aspect.
According to the fault diagnosis method, the fault diagnosis device, the electronic equipment and the computer readable medium, the equipment data of the intelligent equipment are inquired from the first system through the acquired identification of the intelligent equipment to be detected, the network data associated with the distribution network information is inquired from the second system through the acquired IP address and the port number of the intelligent equipment, further, the equipment data and the network data from different systems can be summarized to obtain the comprehensive data, the comprehensive data can be made to be comprehensive, and a perfect data basis can be provided for fault diagnosis. The intelligent equipment is subjected to fault diagnosis based on the comprehensive data, and maintenance personnel do not need to go to the door to detect the intelligent equipment and a network accessed by the intelligent equipment, so that a fault diagnosis process is simplified, and the fault diagnosis efficiency is improved. Meanwhile, the process does not depend on manual experience, and the influence of subjective factors can be eliminated, so that the accuracy of fault diagnosis is improved.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings:
FIG. 1 is an exemplary system architecture diagram to which embodiments of the present application may be applied;
FIG. 2 is a flow diagram of one embodiment of a fault diagnosis method of the present application;
FIG. 3 is a flow chart of an application scenario of the fault diagnosis method of the present application;
FIG. 4 is a flow chart of yet another embodiment of a fault diagnosis method of the present application;
fig. 5 is a schematic structural diagram of an embodiment of the failure diagnosis apparatus of the present application;
fig. 6 is a schematic structural diagram of a computer system for implementing 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. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not to be construed as limiting the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that, in the present application, the embodiments and features of the embodiments may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
It should be noted that all actions of acquiring signals, information or data in the present application are performed under the premise of complying with the corresponding data protection regulation policy of the country of the location and obtaining the authorization given by the owner of the corresponding device.
Fig. 1 shows an exemplary system architecture diagram to which the fault diagnosis method or the fault diagnosis apparatus of the present application can be applied.
As shown in fig. 1, the system architecture may include a fault diagnosis device, and the fault diagnosis device may interact with the first system and the second system respectively to query and obtain data. In some examples, the fault diagnosis device may be a server for performing fault diagnosis. The first system and the second system may be maintained by different servers, respectively, and the fault diagnosis device may communicate with the servers for maintaining the first system and the second system through a wired communication link, a wireless communication link, an optical fiber cable, or the like. The servers may be implemented as a distributed server cluster composed of a plurality of servers, or may be implemented as a single server. And is not particularly limited herein.
The first system may be used to manage and maintain device data of smart devices in the internet of things, for example, and may include, but is not limited to, at least one of: an internet of things management system, a smart device background management system, an application background management system (e.g., a background management system for controlling applications of a smart device), and so on. The smart device may include, but is not limited to, a camera (e.g., a webcam).
The second system may be used to manage and maintain network data, for example, and may include, but is not limited to, at least one of: a PON (Passive Optical Network ) management system, a Network resource management system, an internet authentication system, and the like.
It should be noted that the fault diagnosis method provided by the embodiment of the present application is generally executed by a fault diagnosis device, and accordingly, the fault diagnosis apparatus is generally disposed in the fault diagnosis device.
Referring to FIG. 2, a flow diagram of one embodiment of a fault diagnosis method according to the present application is shown. The fault diagnosis method comprises the following steps:
In this embodiment, the smart device to be detected may include, but is not limited to, an electronic device with a networking function, for example, a camera (e.g., a camera) in an environment of the internet of things. An executing body of the fault diagnosis method (e.g., the fault diagnosis device in fig. 1) may acquire an identification, an internet protocol IP address, and a port number of the smart device to be detected. The identifier of the smart device may be a serial number of the smart device, or may also be information such as a Media Access Control Address (MAC Address) of the smart device, which is not limited herein.
In practice, the execution main body may receive a fault diagnosis request carrying an identifier of the intelligent device, and obtain the identifier of the intelligent device by analyzing the request. And then, whether the intelligent equipment is online or not can be detected based on the intelligent equipment background management system, and the IP address and the port number of the intelligent equipment are inquired from the intelligent equipment background management system based on the identification under the condition that the intelligent equipment is online. The intelligent device background management system can store network information of the intelligent device, and the network information can include an IP address and a port number.
In some alternative implementations, the above steps may be performed while the smart device is online. If the IP address and the port number are failed to be obtained, or if the intelligent device is offline, a historical log of the intelligent device can be obtained, and fault diagnosis is carried out on the intelligent device based on the historical log to obtain a fault diagnosis result. Wherein, the history log may include but is not limited to at least one of the following: historical fault diagnosis results (including timing automatic diagnosis results and manual diagnosis results), historical online records, historical online broadband information and historical online equipment information. Further, at this time, the prompt information of "the intelligent device information query fails, please try to restart the intelligent device and diagnose again" may be output, and the last fault diagnosis result in the history log may be output at the same time for reference.
And step 202, inquiring the device data of the intelligent device from the first system based on the identification.
In this embodiment, the execution subject may query the device data of the smart device from the first system based on the identifier of the smart device. The first system may be used to manage and maintain device data of the smart device in the internet of things, and for example, may include, but is not limited to, at least one of the following: the system comprises an internet of things management system, a smart device background management system, a background management system of a target application (for example, an application for controlling a smart device), and the like.
The device data may include, but is not limited to, at least one of: the network connection mode information (which may be used to indicate a connection mode of the smart device, for example, wired connection or wireless connection), wireless network signal strength information, network connection rate and negotiation times of the wired connection, connection quality (for example, delay, whether packet is lost, whether jitter is generated, etc.) of the camera to the gateway, device basic information (for example, user account, device identifier, device serial number, etc.), bound mobile phone number information, online condition information, online and offline records, alarm information, work order, use condition information, etc.
And step 203, determining the distribution network information of the intelligent device based on the IP address and the port number, and inquiring network data associated with the distribution network information from the second system.
In this embodiment, the distribution network information may include, but is not limited to, a broadband account. The execution main body can be in communication connection with an internet authentication system for managing the distribution network information, and the distribution network information of the intelligent device is inquired by taking the IP address and the port number as keywords. After the distribution network information is obtained, network data associated with the distribution network information can be inquired from the second system. Wherein the second system may be independent of the first system.
The network data may include, but is not limited to, at least one of: the network access information includes basic network access information (e.g., a broadband account, broadband line resource information, a broadband rate, a broadband installation address, etc.), optical modem related information (e.g., a bound optical modem situation, an operating state situation, the number of terminals hanging down, etc.), broadband quality information (e.g., a broadband online situation, an online and offline situation, traffic information, line optical attenuation, etc.), and upstream PON device information (e.g., a PON port error code, an optical line terminal relay traffic situation, etc.).
And step 204, summarizing the equipment data and the network data to generate comprehensive data.
In this embodiment, the execution subject may summarize device data and network data. For example, each item of data in the device data and each item of data in the network data may be format converted to obtain data in a target format (e.g., a key-value pair format). Then, the obtained data are summarized in the forms of lists, sets and the like to generate comprehensive data.
In some alternative implementations, the executing agent may first query a target data table in a target database based on the identification of the smart device. If there is no target data table, the target data table may be created based on the identifier as the table name. After the target data table is queried, each piece of data in the device data and each piece of data in the network data can be used as records and added to the target data table to obtain comprehensive data. If the target data table has data stored therein, the data in the target data table may be updated based on the integrated data.
And step 205, performing fault diagnosis on the intelligent equipment based on the comprehensive data to obtain a fault diagnosis result.
In this embodiment, the execution subject may implement fault diagnosis on the intelligent device by analyzing the comprehensive data, so as to obtain a fault diagnosis result. For example, a fault diagnosis model may be trained in advance by a machine learning method (e.g., a supervised learning method), and the integrated data is input to the model to obtain a fault diagnosis result. For another example, a correspondence table for representing the correspondence between the data and the fault diagnosis result may be preset, and the fault diagnosis result may be obtained by looking up the table.
In some optional implementations, the fault diagnosis may also be performed by: first, a preset fault diagnosis rule is obtained. The fault diagnosis rule may include at least one diagnosis conclusion and a fault condition corresponding to each diagnosis conclusion. And then, detecting whether the comprehensive data meets all fault conditions, taking the fault conditions met by the comprehensive data as target fault conditions, and summarizing diagnosis conclusions corresponding to the target fault conditions to obtain fault diagnosis results.
Optionally, the fault diagnosis rule may include: and if the connection mode of the intelligent equipment is wireless connection, network delay from the intelligent equipment to the gateway is abnormal, the wireless signal intensity of the intelligent equipment is abnormal and other data are normal, determining that the wireless signal of the position where the intelligent equipment is located is weak.
Optionally, the fault diagnosis rule may include: if the connection mode is wired connection, the online and offline frequency of the intelligent device is abnormal, the optical power of a network line of the intelligent device is abnormal, the online and offline frequency of a broadband account in the distribution network information is abnormal, the broadband account is online, and other data is normal, the broadband line accessed by the intelligent device is determined to be abnormal.
Optionally, the fault diagnosis rule may include: and if the connection mode is wired connection, the online and offline frequency of the intelligent equipment is abnormal, the network rate of the intelligent equipment is abnormal, the broadband account is online and other data is normal, determining the network cable fault of the intelligent equipment.
Optionally, the fault diagnosis rule may include: if the connection mode is wired connection, the broadband account in the distribution network information is on line, the ratio of the uplink network traffic and the bandwidth of the intelligent equipment is abnormal, the number of the intelligent equipment using the broadband account is larger than a preset value, and other data are normal, it is determined that the uplink network bandwidth of the intelligent equipment is insufficient.
The failure diagnosis rule may be set as needed, and is not limited to the above.
In some optional implementations, after obtaining the fault diagnosis result, the execution main body may further add the fault diagnosis result to the history log to update the history log. Thus, real-time updates of the history log can be maintained.
Referring to fig. 3, a schematic diagram of an application scenario of the fault diagnosis method of the present application is shown. In this scenario, the smart device may be a home-mounted camera. The user can input the identification of the camera on the warranty page of the terminal equipment or the front-end equipment and initiate a fault diagnosis request. After receiving the request, the server may extract the identifier from the request, and further query the IP address and the port number based on the identifier. Then, based on the identifier, the device data of the camera may be queried from the first system, and based on the IP address and the port number, the distribution network information of the camera may be determined, and the network data associated with the distribution network information may be queried from the second system. Then, the device data and the network data may be summarized to generate integrated data. Finally, fault diagnosis can be performed on the camera based on the comprehensive data to obtain a fault diagnosis result, for example, "the network fault of the camera network, please check the network from the broadband device to the camera". After the fault result is obtained, the fault result can be displayed in the terminal equipment or the front-end equipment, therefore, a user can interact with the background through the terminal equipment or the front-end equipment, when the user inputs information in the terminal equipment or the front-end equipment, the data processing process runs in the background, the user can browse the fault diagnosis result directly from the terminal equipment or the front-end equipment, and the usability degree is high.
According to the method provided by the embodiment of the application, the device data of the intelligent device is inquired from the first system through the acquired identification of the intelligent device to be detected, the network data associated with the distribution network information is inquired from the second system through the acquired IP address and the port number of the intelligent device, further, the device data and the network data from different systems can be summarized to obtain the comprehensive data, the obtained comprehensive data can be comprehensive, and a perfect data base can be provided for fault diagnosis. The intelligent equipment is subjected to fault diagnosis based on the comprehensive data, and maintenance personnel do not need to go to the door to detect the intelligent equipment and a network accessed by the intelligent equipment, so that a fault diagnosis process is simplified, and the fault diagnosis efficiency is improved. Meanwhile, the process does not depend on manual experience, and the influence of subjective factors can be eliminated, so that the accuracy of fault diagnosis is improved.
With further reference to fig. 4, a flow chart of yet another embodiment of a fault diagnosis method is shown. The flow of the fault diagnosis method comprises the following steps:
Step 401 in this embodiment can refer to step 201 in the corresponding embodiment of fig. 2, and is not described herein again.
In some optional implementation manners, if the IP address and the port number are not obtained successfully, or if the intelligent device is offline, a history log of the intelligent device may be obtained, and fault diagnosis may be performed on the intelligent device based on the history log to obtain a fault diagnosis result. Further, at this time, the prompt information of "the intelligent device information query fails, please try to restart the intelligent device and diagnose again" may be output, and the last fault diagnosis result in the history log may be output at the same time for reference.
Based on the identification, device data of the smart device is queried from the first system, step 402.
Step 402 in this embodiment can refer to step 202 in the corresponding embodiment of fig. 2, and is not described herein again.
And step 403, determining the distribution network information of the intelligent device based on the IP address and the port number, and querying network data associated with the distribution network information from the second system.
Step 403 in this embodiment can refer to step 203 in the corresponding embodiment of fig. 2, which is not described herein again.
Step 404 in this embodiment can refer to step 204 in the corresponding embodiment of fig. 2, and is not described herein again.
In some alternative implementations, the executing agent may first query a target data table in a target database based on the identification of the smart device. If there is no target data table, the target data table may be created based on the identifier as a table name. After the target data table is queried, each piece of data in the device data and each piece of data in the network data can be used as records and added to the target data table to obtain comprehensive data. If the target data table has data stored therein, the data in the target data table may be updated based on the integrated data.
And 405, performing fault diagnosis on the intelligent equipment based on the comprehensive data to obtain a fault diagnosis result.
Step 405 in this embodiment can refer to step 205 in the corresponding embodiment of fig. 2, and is not described herein again.
In some optional implementations, the fault diagnosis may also be performed by: first, a preset fault diagnosis rule is obtained. The fault diagnosis rule may include at least one diagnosis conclusion and a fault condition corresponding to each diagnosis conclusion. And then, detecting whether the comprehensive data meets all fault conditions, taking the fault conditions met by the comprehensive data as target fault conditions, and summarizing diagnosis conclusions corresponding to the target fault conditions to obtain fault diagnosis results.
In some alternative implementations, the fault diagnosis rules may include, but are not limited to, at least one of: if the connection mode of the intelligent equipment is wireless connection, network delay from the intelligent equipment to the gateway is abnormal, the wireless signal intensity of the intelligent equipment is abnormal and other data are normal, determining that the wireless signal of the position where the intelligent equipment is located is weak; if the connection mode is wired connection, the online and offline frequency of the intelligent equipment is abnormal, the optical power of a network line of the intelligent equipment is abnormal, the online and offline frequency of a broadband account in the distribution network information is abnormal, the broadband account is online, and other data are normal, determining that the broadband line accessed by the intelligent equipment is abnormal; if the connection mode is wired connection, the online and offline frequency of the intelligent equipment is abnormal, the network rate of the intelligent equipment is abnormal, the broadband account is online, and other data is normal, determining the network cable fault of the intelligent equipment; if the connection mode is wired connection, the broadband account in the distribution network information is on line, the ratio of the uplink network traffic and the bandwidth of the intelligent equipment is abnormal, the number of the intelligent equipment using the broadband account is larger than a preset value, and other data are normal, it is determined that the uplink network bandwidth of the intelligent equipment is insufficient.
In some optional implementations, after obtaining the fault diagnosis result, the execution main body may further add the fault diagnosis result to the history log to update the history log. Thus, real-time updates of the history log can be maintained.
And 406, periodically updating the comprehensive data based on the preset monitoring plan information, and monitoring the fault of the intelligent equipment based on the updated comprehensive data to obtain a fault monitoring result.
In this embodiment, the detection schedule information may be set in advance as necessary so that the execution main body automatically performs the failure monitoring at the set time. Based on the monitoring plan information, the comprehensive data can be updated periodically according to the operations from the step 401 to the step 405, and fault monitoring is performed on the intelligent device based on the updated comprehensive data, so that a fault monitoring result is obtained. The fault monitoring result can be used for indicating whether the intelligent equipment has faults or not, and under the condition of the faults, the fault monitoring result can also comprise a fault diagnosis result. The fault diagnosis operation in the fault monitoring process can be referred to as step 405 above, and is not described herein again.
In this embodiment, if the fault monitoring result indicates that the intelligent device has a fault, alarm information may be output, where the alarm information may include a fault diagnosis result, so as to facilitate troubleshooting and resolution by a user.
As can be seen from fig. 3, compared with the embodiment corresponding to fig. 2, the flow of the fault diagnosis method in this embodiment relates to a step of periodically monitoring faults of the intelligent device based on the monitoring plan information. Therefore, according to the scheme described by the embodiment, even if the fault of the intelligent device is found, the convenience of performing daily maintenance on the intelligent device is improved.
With further reference to fig. 5, as an implementation of the method shown in the above figures, the present application provides an embodiment of a fault diagnosis apparatus, which corresponds to the embodiment of the method shown in fig. 2, and which can be applied in various electronic devices.
As shown in fig. 5, the failure diagnosis apparatus 500 of the present embodiment includes: an obtaining unit 501, configured to obtain an identifier, an internet protocol IP address, and a port number of an intelligent device to be detected; a first querying unit 502, configured to query device data of the smart device from a first system based on the identifier; a second query unit 503, configured to determine distribution network information of the intelligent device based on the IP address and the port number, and query network data associated with the distribution network information from a second system; a generating unit 504, configured to summarize the device data and the network data to generate comprehensive data; and a first fault diagnosis unit 505, configured to perform fault diagnosis on the intelligent device based on the comprehensive data, so as to obtain a fault diagnosis result.
In some optional implementations, the apparatus further includes: the fault monitoring unit is used for regularly updating the comprehensive data based on preset monitoring plan information and carrying out fault monitoring on the intelligent equipment based on the updated comprehensive data to obtain a fault monitoring result; and if the fault monitoring result indicates that the intelligent equipment has faults, outputting alarm information.
In some optional implementations, the generating unit 504 is further configured to query a target data table in the target database based on the identifier; and adding each piece of data in the equipment data and each piece of data in the network data as records to the target data table to obtain comprehensive data.
In some optional implementations, the apparatus further includes: and the second fault diagnosis unit is used for acquiring a history log of the intelligent equipment if the IP address and the port number fail to be acquired or if the intelligent equipment is offline, and performing fault diagnosis on the intelligent equipment based on the history log to obtain a fault diagnosis result.
In some optional implementations, the apparatus further includes: and an updating unit for adding the fault diagnosis result to the history log to update the history log.
In some optional implementation manners, the first fault diagnosis unit 505 is further configured to obtain a preset fault diagnosis rule, where the fault diagnosis rule includes at least one diagnosis conclusion and a fault condition corresponding to each diagnosis conclusion; detecting whether the comprehensive data meet each fault condition; and taking the fault condition met by the comprehensive data as a target fault condition, and summarizing diagnosis conclusions corresponding to the target fault condition to obtain a fault diagnosis result.
In some optional implementations, the fault diagnosis rule includes at least one of: if the connection mode of the intelligent equipment is wireless connection, the network delay from the intelligent equipment to a gateway is abnormal, the wireless network signal intensity of the intelligent equipment is abnormal and other data are normal, determining that the wireless signal at the position of the intelligent equipment is weak; if the connection mode is wired connection, the online and offline frequency of the intelligent device is abnormal, the optical power of a network line of the intelligent device is abnormal, the online and offline frequency of the broadband account in the distribution network information is abnormal, the broadband account is online, and other data are normal, determining that the broadband line accessed by the intelligent device is abnormal; if the connection mode is wired connection, the online and offline frequency of the intelligent device is abnormal, the network rate of the intelligent device is abnormal, the broadband account is online, and other data are normal, determining the network cable fault of the intelligent device; and if the connection mode is wired connection, the broadband account number in the distribution network information is on line, the ratio of the uplink network traffic to the bandwidth of the intelligent equipment is abnormal, the number of the intelligent equipment using the broadband account number is larger than a preset value, and other data are normal, determining that the uplink network bandwidth of the intelligent equipment is insufficient.
The device provided by the above embodiment of the application queries the device data of the intelligent device from the first system through the acquired identifier of the intelligent device to be detected, and queries the network data associated with the distribution network information from the second system through the acquired IP address and port number of the intelligent device, so that the device data and the network data from different systems can be summarized to obtain the comprehensive data, the obtained comprehensive data can be comprehensive, and a perfect data base can be provided for fault diagnosis. The intelligent equipment is subjected to fault diagnosis based on the comprehensive data, and maintenance personnel do not need to go to the door to detect the intelligent equipment and a network accessed by the intelligent equipment, so that a fault diagnosis process is simplified, and the fault diagnosis efficiency is improved. Meanwhile, the process does not depend on manual experience, and the influence of subjective factors can be eliminated, so that the accuracy of fault diagnosis is improved.
Reference is now made to fig. 6, which illustrates a schematic structural diagram of an electronic device for implementing some embodiments of the present application. The electronic device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the range of use of the embodiments of the present application.
As shown in fig. 6, electronic device 600 may include a processing device (e.g., central processing unit, graphics processor, etc.) 601 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage device 608 into a Random Access Memory (RAM) 603. In the RAM603, various programs and data necessary for the operation of the electronic apparatus 600 are also stored. The processing device 601, the ROM 602, and the RAM603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
Generally, the following devices may be connected to the I/O interface 605: input devices 606 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, or the like; output devices 607 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 608 including, for example, magnetic disks, hard disks, and the like; and a communication device 609. The communication means 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. While fig. 6 illustrates an electronic device 600 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 6 may represent one device or may represent multiple devices as desired.
In particular, according to some embodiments of the present application, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network through the communication device 609, or installed from the storage device 608, or installed from the ROM 602. Which when executed by the processing means 601 performs the above-described functions as defined in the methods of some embodiments of the present application.
It should be noted that the computer readable medium described in some embodiments of the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present application, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText transfer protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may be separate and not incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring an identifier, an Internet Protocol (IP) address and a port number of intelligent equipment to be detected; querying the intelligent device from the first system based on the identification; determining distribution network information of the intelligent equipment based on the IP address and the port number, and inquiring network data associated with the distribution network information from the second system; summarizing the equipment data and the network data to generate comprehensive data; and carrying out fault diagnosis on the intelligent equipment based on the comprehensive data to obtain a fault diagnosis result.
Computer program code for carrying out operations for embodiments of the present application may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +; conventional procedural programming languages, such as the "C" programming language or similar programming languages, are also included. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present application may be implemented by software or by hardware. The described units may also be provided in a processor, and may be described as: a processor includes a first determining unit, a second determining unit, a selecting unit, and a third determining unit. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), complex Programmable Logic Devices (CPLDs), and the like.
The foregoing description is only exemplary of the preferred embodiments of the present application and is provided for the purpose of illustrating the general principles of the technology. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present application is not limited to the specific combination of the above-mentioned technical features, and other technical features formed by any combination of the above-mentioned technical features or their equivalents may be covered without departing from the inventive concept described above. For example, the above features and (but not limited to) features with similar functions disclosed in the embodiments of the present application are mutually replaced to form the technical solution.
Claims (10)
1. A fault diagnosis method, characterized in that the method comprises:
acquiring an identifier, an Internet Protocol (IP) address and a port number of intelligent equipment to be detected;
querying the intelligent device for device data from a first system based on the identification;
determining distribution network information of the intelligent equipment based on the IP address and the port number, and inquiring network data associated with the distribution network information from a second system;
summarizing the equipment data and the network data to generate comprehensive data;
and carrying out fault diagnosis on the intelligent equipment based on the comprehensive data to obtain a fault diagnosis result.
2. The method of claim 1, further comprising:
periodically updating the comprehensive data based on preset monitoring plan information, and carrying out fault monitoring on the intelligent equipment based on the updated comprehensive data to obtain a fault monitoring result;
and if the fault monitoring result indicates that the intelligent equipment has a fault, outputting alarm information.
3. The method of claim 1, wherein the aggregating the device data and the network data to generate aggregated data comprises:
querying a target data table in a target database based on the identification;
and taking each piece of data in the equipment data and each piece of data in the network data as records, and adding the records to the target data table to obtain comprehensive data.
4. The method of claim 1, further comprising:
if the IP address and the port number fail to be obtained, or if the intelligent device is offline, obtaining a history log of the intelligent device, and performing fault diagnosis on the intelligent device based on the history log to obtain a fault diagnosis result.
5. The method of claim 4, wherein after obtaining the fault diagnosis, the method further comprises:
adding the fault diagnosis result to the history log to update the history log.
6. The method of claim 1, wherein the performing fault diagnosis on the smart device based on the integrated data to obtain a fault diagnosis result comprises:
acquiring a preset fault diagnosis rule, wherein the fault diagnosis rule comprises at least one diagnosis conclusion and fault conditions corresponding to the diagnosis conclusions;
detecting whether the comprehensive data meet each fault condition;
and taking the fault condition met by the comprehensive data as a target fault condition, and summarizing diagnosis conclusions corresponding to the target fault condition to obtain a fault diagnosis result.
7. The method of claim 6, wherein the fault diagnosis rules comprise at least one of:
if the connection mode of the intelligent equipment is wireless connection, the network delay from the intelligent equipment to the gateway is abnormal, the wireless network signal strength of the intelligent equipment is abnormal, and other data are normal, determining that the wireless signal of the position where the intelligent equipment is located is weak;
if the connection mode is wired connection, the online and offline frequency of the intelligent device is abnormal, the optical power of a network line of the intelligent device is abnormal, the online and offline frequency of a broadband account in the distribution network information is abnormal, the broadband account is online, and other data is normal, determining that the broadband line to which the intelligent device is connected is abnormal;
if the connection mode is wired connection, the online and offline frequency of the intelligent equipment is abnormal, the network rate of the intelligent equipment is abnormal, the broadband account is online, and other data are normal, determining the network cable fault of the intelligent equipment;
and if the connection mode is wired connection, the broadband account in the distribution network information is on line, the ratio of the uplink network flow to the bandwidth of the intelligent equipment is abnormal, the number of the intelligent equipment using the broadband account is larger than a preset value, and other data are normal, determining that the uplink network bandwidth of the intelligent equipment is insufficient.
8. A fault diagnosis apparatus characterized by comprising:
the device comprises an acquisition unit, a detection unit and a control unit, wherein the acquisition unit is used for acquiring the identification, the Internet protocol IP address and the port number of the intelligent device to be detected;
the first query unit is used for querying the device data of the intelligent device from a first system based on the identification;
the second query unit is used for determining the distribution network information of the intelligent equipment based on the IP address and the port number, and querying network data associated with the distribution network information from a second system;
the generating unit is used for summarizing the equipment data and the network data to generate comprehensive data;
and the first fault diagnosis unit is used for carrying out fault diagnosis on the intelligent equipment based on the comprehensive data to obtain a fault diagnosis result.
9. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method recited in any of claims 1-7.
10. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-7.
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