CN114244681A - Equipment connection fault early warning method and device, storage medium and electronic equipment - Google Patents
Equipment connection fault early warning method and device, storage medium and electronic equipment Download PDFInfo
- Publication number
- CN114244681A CN114244681A CN202111569883.4A CN202111569883A CN114244681A CN 114244681 A CN114244681 A CN 114244681A CN 202111569883 A CN202111569883 A CN 202111569883A CN 114244681 A CN114244681 A CN 114244681A
- Authority
- CN
- China
- Prior art keywords
- early warning
- target
- parameter
- mode
- value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0604—Management of faults, events, alarms or notifications using filtering, e.g. reduction of information by using priority, element types, position or time
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0823—Errors, e.g. transmission errors
- H04L43/0829—Packet loss
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Environmental & Geological Engineering (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The application discloses an equipment connection fault early warning method, an equipment connection fault early warning device, a storage medium and electronic equipment, and relates to the technical field of Internet of things, wherein the method comprises the following steps: receiving the router signal intensity and the packet loss rate uploaded by the target device; acquiring the off-line times of the target equipment in a target time period, and acquiring target early warning parameters; calculating and processing based on the target early warning parameter, the router signal strength, the packet loss rate and the offline times to obtain an early warning value; and determining an early warning mode of the target equipment according to the early warning value, and executing fault early warning operation corresponding to the early warning mode. The reliability of the early warning of the connection fault of the equipment can be improved.
Description
Technical Field
The application relates to the technical field of Internet of things, in particular to an equipment connection fault early warning method and device, a storage medium and electronic equipment.
Background
With the development of the internet of things, various devices are in endless, various faults are bound to exist in the presence of a large number of devices, and the method has important significance for timely early warning of the faults of the devices. At present, the mode of performing early warning on the connection fault of the equipment is generally performed based on a fixed early warning mode, and the situations of false alarm and failure of alarm are more, so that the early warning cannot be reliably performed.
Disclosure of Invention
The embodiment of the application provides a scheme, and the reliability of the early warning of the connection fault of the equipment can be improved.
The embodiment of the application provides the following technical scheme:
according to one embodiment of the application, an equipment connection fault early warning method comprises the following steps: receiving the router signal intensity and the packet loss rate uploaded by the target device; acquiring the off-line times of the target equipment in a target time period, and acquiring target early warning parameters; calculating and processing based on the target early warning parameter, the router signal strength, the packet loss rate and the offline times to obtain an early warning value; and determining an early warning mode of the target equipment according to the early warning value, and executing fault early warning operation corresponding to the early warning mode.
In some embodiments of the present application, the target early warning parameters include a first parameter, a second parameter, and a third parameter; calculating and processing the target early warning parameter, the router signal strength, the packet loss rate and the offline times to obtain an early warning value, wherein the method comprises the following steps: multiplying the offline times by the first parameter to obtain a first value; summing the router signal strength and the second parameter to obtain an adjustment value; multiplying the adjustment value by the third parameter to obtain a second value; and summing the first value, the second value and the packet loss rate to obtain the early warning value.
In some embodiments of the present application, the first parameter is less than 1, the second parameter is greater than 1, and the third parameter is less than 0.1.
In some embodiments of the present application, the determining an early warning mode of the target device according to the early warning value includes: and if the early warning value is larger than a first preset threshold and smaller than a second preset threshold, determining that the early warning mode of the target equipment is a first mode, wherein the first mode is the early warning mode when the target equipment has suspicion of faults.
In some embodiments of the present application, the determining an early warning mode of the target device according to the early warning value includes: and if the pre-warning values corresponding to the preset number of target devices are larger than a second preset threshold value, determining that the pre-warning mode of the target devices is a second mode, wherein the second mode refers to the pre-warning mode when a server or a network connected with the target devices has a suspected fault.
In some embodiments of the present application, the target early warning parameters include a first parameter, a second parameter, and a third parameter, the first parameter is smaller than 1, the second parameter is greater than 1, the third parameter is smaller than 0.1, the first predetermined threshold is equal to 1, and the second predetermined threshold is equal to 3.
In some embodiments of the present application, the method further comprises: acquiring historical early warning information corresponding to the target equipment, wherein the historical early warning information comprises early warning mode recording information and historical equipment use data when the target equipment carries out fault early warning in history; acquiring current equipment use data of the target equipment; and performing prediction processing by adopting a pre-trained early warning model based on the early warning mode recording information, historical equipment use data and the current equipment use data to obtain the predicted target early warning parameter, the first preset threshold and the second preset threshold.
According to an embodiment of the present application, an apparatus connection failure early warning device includes: the receiving module is used for receiving the router signal strength and the packet loss rate uploaded by the target equipment; the acquisition module is used for acquiring the off-line times of the target equipment in a target time period and acquiring target early warning parameters; the calculation module is used for performing calculation processing based on the target early warning parameter, the router signal strength, the packet loss rate and the online times to obtain an early warning value; and the early warning module is used for determining an early warning mode of the target equipment according to the early warning value and executing fault early warning operation corresponding to the early warning mode.
In some embodiments of the present application, the target early warning parameters include a first parameter, a second parameter, and a third parameter; the calculation module comprises: the first calculating unit is used for multiplying the offline times and the first parameter to obtain a first value; the second calculation unit is used for summing the router signal strength and the second parameter to obtain an adjustment value; the third calculating unit is used for multiplying the adjustment value by the third parameter to obtain a second value; and the fourth calculating unit is used for summing the first value, the second value and the packet loss rate to obtain the early warning value.
In some embodiments of the present application, the first parameter is less than 1, the second parameter is greater than 1, and the third parameter is less than 0.1.
In some embodiments of the present application, the early warning module includes a first determining unit configured to: and if the early warning value is larger than a first preset threshold and smaller than a second preset threshold, determining that the early warning mode of the target equipment is a first mode, wherein the first mode is the early warning mode when the target equipment has suspicion of faults.
In some embodiments of the present application, the early warning module includes a second determining unit, configured to: and if the pre-warning values corresponding to the preset number of target devices are larger than a second preset threshold value, determining that the pre-warning mode of the target devices is a second mode, wherein the second mode refers to the pre-warning mode when a server or a network connected with the target devices has a suspected fault.
In some embodiments of the present application, the target early warning parameters include a first parameter, a second parameter, and a third parameter, the first parameter is smaller than 1, the second parameter is greater than 1, the third parameter is smaller than 0.1, the first predetermined threshold is equal to 1, and the second predetermined threshold is equal to 3.
In some embodiments of the present application, the apparatus further comprises an update calculation module configured to: acquiring historical early warning information corresponding to the target equipment, wherein the historical early warning information comprises early warning mode recording information and historical equipment use data when the target equipment carries out fault early warning in history; acquiring current equipment use data of the target equipment; and performing prediction processing by adopting a pre-trained early warning model based on the early warning mode recording information, historical equipment use data and the current equipment use data to obtain the predicted target early warning parameter, the first preset threshold and the second preset threshold.
According to another embodiment of the present application, a storage medium has stored thereon a computer program which, when executed by a processor of a computer, causes the computer to perform the method of an embodiment of the present application.
According to another embodiment of the present application, an electronic device may include: a memory storing a computer program; and the processor reads the computer program stored in the memory to execute the method in the embodiment of the application.
In the embodiment of the application, the signal intensity and the packet loss rate of the router uploaded by the target device are received; acquiring the off-line times of the target equipment in a target time period, and acquiring target early warning parameters; calculating and processing based on the target early warning parameter, the router signal strength, the packet loss rate and the offline times to obtain an early warning value; and determining an early warning mode of the target equipment according to the early warning value, and executing fault early warning operation corresponding to the early warning mode.
In this way, the early warning value is calculated based on the router signal strength, the packet loss rate, the off-line times and the target early warning parameters of the target device, and the corresponding early warning mode is determined according to the early warning value to execute the fault early warning operation, so that most fault conditions can be flexibly and effectively responded, the conditions of false alarm and failure in alarm are effectively reduced, and the reliability of the device connection fault early warning is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 shows a schematic diagram of a system to which embodiments of the present application may be applied.
Fig. 2 shows a flowchart of a device connection failure early warning method according to an embodiment of the present application.
Fig. 3 shows a block diagram of an apparatus connection failure early warning device according to an embodiment of the present application.
FIG. 4 shows a block diagram of an electronic device according to an embodiment of the application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the description that follows, specific embodiments of the present application will be described with reference to steps and symbols executed by one or more computers, unless otherwise indicated. Accordingly, these steps and operations will be referred to, several times, as being performed by a computer, the computer performing operations involving a processing unit of the computer in electronic signals representing data in a structured form. This operation transforms the data or maintains it at locations in the computer's memory system, which may be reconfigured or otherwise altered in a manner well known to those skilled in the art. The data maintains a data structure that is a physical location of the memory that has particular characteristics defined by the data format. However, the principles of the present application are described in the foregoing text and are not meant to be limiting, as those of ordinary skill in the art will appreciate that various steps and operations described below may be implemented in hardware.
Fig. 1 shows a schematic diagram of a system 100 to which embodiments of the present application may be applied. As shown in fig. 1, the system 100 may include a server 101 and a device 102. Device 102 may be any computer device, such as a computer, a cell phone, a smart watch, a home appliance, and so forth. The server 101 may be a server cluster or a cloud server, etc. In one example, the device 102 is an internet of things device and the server 101 is a cloud server.
In one implementation of this example, the server 101 may: receiving the router signal strength and the packet loss rate uploaded by the target device (which may be the device 102); acquiring the off-line times of the target equipment in a target time period, and acquiring target early warning parameters; calculating and processing based on the target early warning parameter, the router signal strength, the packet loss rate and the offline times to obtain an early warning value; and determining an early warning mode of the target equipment according to the early warning value, and executing fault early warning operation corresponding to the early warning mode.
Fig. 2 schematically shows a flowchart of an apparatus connection failure early warning method according to an embodiment of the present application. The execution subject of the device connection failure early warning method may be any device, such as the server 101 shown in fig. 1.
As shown in fig. 2, the device connection failure early warning method may include steps S210 to S240.
Step S210, receiving the router signal strength and the packet loss rate uploaded by the target device;
step S220, acquiring the off-line times of the target equipment in a target time period, and acquiring a target early warning parameter;
step S230, calculating and processing based on the target early warning parameter, the router signal strength, the packet loss rate and the offline times to obtain an early warning value;
and step S240, determining an early warning mode of the target equipment according to the early warning value, and executing fault early warning operation corresponding to the early warning mode.
The router signal strength is the strength data of the router signal, and the target device determines the router signal strength of the router connected to the target device, for example, the target device may obtain the router signal strength of the current connection through an RTK openwork library. The packet loss rate, that is, the ratio of the packet loss number of the lost data packet to the packet sending number of the sent data group, and the device may call the bottom layer interface to take the packet sending number and the packet loss number to perform division to obtain the packet loss rate.
The target device may upload the router signal strength and the packet loss rate to a processing device (such as the server 101 shown in fig. 1) of the early warning platform through a specific interface (such as an mqtt topoic interface).
The login server of the target device (such as the processing device of the early warning platform) or the target device itself may record the offline times of the target device, and then the processing device may collect the offline times in the target time period from the record, the target time period may be specified according to the requirement, and the offline times may be the times of online and offline of the target device.
The processing device may obtain a target early warning parameter specified by a user or calculated in real time, where the target early warning parameter is a calculation parameter used for calculating an early warning value.
The processing device can perform calculation processing based on the target early warning parameter, the router signal strength, the packet loss rate and the offline times according to a preset early warning value calculation strategy to obtain an early warning value, and the early warning value is used for determining an early warning mode.
The early warning mode can indicate the mode of fault early warning operation, and each early warning mode corresponds a fault early warning operation, and each early warning mode can correspond different equipment failure condition respectively.
In this way, based on steps S210 to S240, the calculation of the early warning value based on the signal intensity, packet loss rate, offline frequency, and target early warning parameter of the router of the target device can be realized, and the corresponding early warning mode is determined according to the early warning value to execute the fault early warning operation, so that most fault conditions can be flexibly and effectively dealt with, the conditions of false alarm and failure alarm are effectively reduced, and the reliability of the device connection fault early warning is improved.
The following describes specific processes of each step performed when performing the device connection fault pre-warning.
In step S210, the router signal strength and the packet loss rate uploaded by the target device are received.
The router signal strength is the strength data of the router signal, and the target device determines the router signal strength of the router connected to the target device, for example, the target device may obtain the router signal strength of the current connection through an RTK openwork library. The packet loss rate, that is, the ratio of the packet loss number of the lost data packet to the packet sending number of the sent data group, and the device may call the bottom layer interface to take the packet sending number and the packet loss number to perform division to obtain the packet loss rate.
The target device may upload the router signal strength and the packet loss rate to a processing device (such as the server 101 shown in fig. 1) of the early warning platform through a specific interface (such as an mqtt topoic interface).
In step S220, the number of times of offline of the target device in the target time period is collected, and a target early warning parameter is obtained.
The login server of the target device (such as the processing device of the early warning platform) or the target device itself may record the offline times of the target device, and then the processing device may collect the offline times in the target time period from the record, the target time period may be specified according to the requirement, and the offline times may be the times of online and offline of the target device.
In step S230, a calculation process is performed based on the target warning parameter, the router signal strength, the packet loss rate, and the offline times, so as to obtain a warning value.
The processing device can perform calculation processing based on the target early warning parameter, the router signal strength, the packet loss rate and the offline times according to a preset early warning value calculation strategy to obtain an early warning value, and the early warning value is used for determining an early warning mode.
In one embodiment, the target early warning parameters include a first parameter, a second parameter and a third parameter; step S230, performing calculation processing based on the target early warning parameter, the router signal strength, the packet loss rate, and the offline times to obtain an early warning value, including:
multiplying the offline times by the first parameter to obtain a first value; summing the router signal strength and the second parameter to obtain an adjustment value; multiplying the adjustment value by the third parameter to obtain a second value; and summing the first value, the second value and the packet loss rate to obtain the early warning value.
The off-line times are x, the signal strength of the router is d, the packet loss rate is L%, the first parameter is c1, the second parameter is c2, the third parameter is c3, and the warning value is I, so that I is x c1+ (c2+ d) c3+ L%.
In one embodiment, the first parameter is less than 1, the second parameter is greater than 1, and the third parameter is less than 0.1.
Further, in one embodiment, the first parameter is equal to 0.3, the second parameter is equal to 70, and the third parameter is equal to 0.05. At this time, I ═ x 0.3+ (70+ d) × 0.05+ L%.
In step S240, an early warning mode of the target device is determined according to the early warning value, and a fault early warning operation corresponding to the early warning mode is executed.
The early warning mode can indicate the mode of fault early warning operation, and each early warning mode corresponds a fault early warning operation, and each early warning mode can correspond different equipment failure condition respectively.
In one embodiment, the step S240 of determining the alert mode of the target device according to the alert value includes: and if the early warning value is larger than a first preset threshold and smaller than a second preset threshold, determining that the early warning mode of the target equipment is a first mode, wherein the first mode is the early warning mode when the target equipment has suspicion of faults.
And determining a first mode when the early warning value is greater than a first preset threshold and less than a second preset threshold, wherein the first mode refers to an early warning mode when the target equipment has a suspected fault, namely, the fault early warning operation when the target equipment has the suspected fault can be executed in the first mode, and the applicant finds that the condition when the target equipment has the suspected fault can be effectively dealt with.
In one embodiment, the step S240 of determining the alert mode of the target device according to the alert value includes: and if the pre-warning values corresponding to the preset number of target devices are larger than a second preset threshold value, determining that the pre-warning mode of the target devices is a second mode, wherein the second mode refers to the pre-warning mode when a server or a network connected with the target devices has a suspected fault.
The predetermined number may be specified according to an actual situation, and if the warning value corresponding to the predetermined number of target devices is greater than a second predetermined threshold, a second mode is determined, where the second mode refers to a warning mode when the server or the network to which the target devices are connected has a suspected fault, that is, a fault warning operation when the server or the network has a suspected fault may be performed in the second mode, and the applicant finds that the condition when the server or the network has a suspected fault may be effectively dealt with.
In one embodiment, the target early warning parameters include a first parameter, a second parameter and a third parameter, the first parameter is smaller than 1, the second parameter is larger than 1, the third parameter is smaller than 0.1, the first predetermined threshold is equal to 1, and the second predetermined threshold is equal to 3. In this way, an extremely accurate early warning can be achieved.
In one embodiment, the method further comprises: acquiring historical early warning information corresponding to the target equipment, wherein the historical early warning information comprises early warning mode recording information and historical equipment use data when the target equipment carries out fault early warning in history; acquiring current equipment use data of the target equipment; and performing prediction processing by adopting a pre-trained early warning model based on the early warning mode recording information, historical equipment use data and the current equipment use data to obtain the predicted target early warning parameter, the first preset threshold and the second preset threshold.
Early warning mode record information when the target device carries out fault early warning in history, namely, record information of an early warning mode corresponding to fault early warning operation carried out before the current early warning processing time of the target device can be specified in time, and the processing device can record the information. The historical device usage data, that is, the device usage data of the target device before the current warning processing time, may be device usage data of a specified time period, the device usage data may be, for example, application-related traffic in the device, device CPU resource consumption data, and the like, and the historical device usage data may belong to the same time period as the warning mode record information.
The method comprises the steps of recording an information sample and a historical device use data sample in an early warning mode in advance, using the information sample and the historical device use data sample as input data of an early warning model based on machine learning, and training by using a target early warning parameter, a first preset threshold and a second preset threshold corresponding to the sample as expected outputs to obtain the early warning model trained in advance.
And inputting the early warning mode recording information, the historical equipment use data and the current equipment use data into the pre-trained early warning model by adopting a pre-trained early warning model, so that the target early warning parameters, the first preset threshold and the second preset threshold which are currently calculated and predicted in real time can be output.
In this way, the target early warning parameter, the first predetermined threshold value and the second predetermined threshold value can be continuously updated based on the historical data, and the early warning effect is further improved.
In order to better implement the device connection fault early warning method provided by the embodiment of the application, the embodiment of the application also provides a device connection fault early warning device based on the device connection fault early warning method. The meaning of the noun is the same as that in the above-mentioned device connection fault early warning method, and specific implementation details can refer to the description in the method embodiment. Fig. 3 shows a block diagram of an apparatus connection failure early warning device according to an embodiment of the present application.
As shown in fig. 3, the device connection failure early warning apparatus 300 may include a receiving module 310, an acquisition module 320, a calculation module 330, and an early warning module 340.
The receiving module 310 may be configured to receive the router signal strength and the packet loss rate uploaded by the target device; the acquisition module 320 may be configured to acquire the number of times of offline of the target device in a target time period, and acquire a target early warning parameter; the calculation module 330 may be configured to perform calculation processing based on the target early warning parameter, the router signal strength, the packet loss rate, and the online times to obtain an early warning value; the early warning module 340 may be configured to determine an early warning mode of the target device according to the early warning value, and execute a fault early warning operation corresponding to the early warning mode.
In some embodiments of the present application, the target early warning parameters include a first parameter, a second parameter, and a third parameter; the calculating module 330 includes: the first calculating unit is used for multiplying the offline times and the first parameter to obtain a first value; the second calculation unit is used for summing the router signal strength and the second parameter to obtain an adjustment value; the third calculating unit is used for multiplying the adjustment value by the third parameter to obtain a second value; and the fourth calculating unit is used for summing the first value, the second value and the packet loss rate to obtain the early warning value.
In some embodiments of the present application, the first parameter is less than 1, the second parameter is greater than 1, and the third parameter is less than 0.1.
In some embodiments of the present application, the early warning module 340 includes a first determining unit, configured to: and if the early warning value is larger than a first preset threshold and smaller than a second preset threshold, determining that the early warning mode of the target equipment is a first mode, wherein the first mode is the early warning mode when the target equipment has suspicion of faults.
In some embodiments of the present application, the early warning module 340 includes a second determining unit, configured to: and if the pre-warning values corresponding to the preset number of target devices are larger than a second preset threshold value, determining that the pre-warning mode of the target devices is a second mode, wherein the second mode refers to the pre-warning mode when a server or a network connected with the target devices has a suspected fault.
In some embodiments of the present application, the target early warning parameters include a first parameter, a second parameter, and a third parameter, the first parameter is smaller than 1, the second parameter is greater than 1, the third parameter is smaller than 0.1, the first predetermined threshold is equal to 1, and the second predetermined threshold is equal to 3.
In some embodiments of the present application, the apparatus further comprises an update calculation module configured to: acquiring historical early warning information corresponding to the target equipment, wherein the historical early warning information comprises early warning mode recording information and historical equipment use data when the target equipment carries out fault early warning in history; acquiring current equipment use data of the target equipment; and performing prediction processing by adopting a pre-trained early warning model based on the early warning mode recording information, historical equipment use data and the current equipment use data to obtain the predicted target early warning parameter, the first preset threshold and the second preset threshold.
In this way, based on the device connection failure early warning apparatus 300, at least calculation of early warning values based on the target device's router signal strength, packet loss rate, offline times, and target early warning parameters can be achieved, and a corresponding early warning mode is determined according to the early warning values to perform failure early warning operations, so that most failure conditions can be flexibly and effectively dealt with, the conditions of false alarm and failure alarm are effectively reduced, and the reliability of device connection failure early warning is improved.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
In addition, an embodiment of the present application further provides an electronic device, where the electronic device may be a terminal or a server, as shown in fig. 4, which shows a schematic structural diagram of the electronic device according to the embodiment of the present application, and specifically:
the electronic device may include components such as a processor 401 of one or more processing cores, memory 402 of one or more computer-readable storage media, a power supply 403, and an input unit 404. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 4 does not constitute a limitation of the electronic device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components. Wherein:
the processor 401 is a control center of the electronic device, connects various parts of the entire computer device using various interfaces and lines, and performs various functions of the computer device and processes data by operating or executing software programs and/or modules stored in the memory 402 and calling data stored in the memory 402, thereby integrally monitoring the electronic device. Optionally, processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly handles operating systems, user pages, application programs, and the like, and the modem processor mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 401.
The memory 402 may be used to store software programs and modules, and the processor 401 executes various functional applications and data processing by operating the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to use of the computer device, and the like. Further, the memory 402 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 access to the memory 402.
The electronic device further comprises a power supply 403 for supplying power to the various components, and preferably, the power supply 403 is logically connected to the processor 401 through a power management system, so that functions of managing charging, discharging, and power consumption are realized through the power management system. The power supply 403 may also include any component of one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.
The electronic device may further include an input unit 404, and the input unit 404 may be used to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.
Although not shown, the electronic device may further include a display unit and the like, which are not described in detail herein. Specifically, in this embodiment, the processor 401 in the electronic device loads the executable file corresponding to the process of one or more computer programs into the memory 402 according to the following instructions, and the processor 401 runs the computer program stored in the memory 402, so as to implement various functions in the foregoing embodiments of the present application, for example, the processor 401 may execute the following steps:
receiving the router signal intensity and the packet loss rate uploaded by the target device; acquiring the off-line times of the target equipment in a target time period, and acquiring target early warning parameters; calculating and processing based on the target early warning parameter, the router signal strength, the packet loss rate and the offline times to obtain an early warning value; and determining an early warning mode of the target equipment according to the early warning value, and executing fault early warning operation corresponding to the early warning mode.
In some embodiments of the present application, the target early warning parameters include a first parameter, a second parameter, and a third parameter; when the calculation processing is performed based on the target early warning parameter, the router signal strength, the packet loss ratio, and the offline times to obtain an early warning value, the processor 401 may execute: multiplying the offline times by the first parameter to obtain a first value; summing the router signal strength and the second parameter to obtain an adjustment value; multiplying the adjustment value by the third parameter to obtain a second value; and summing the first value, the second value and the packet loss rate to obtain the early warning value.
In some embodiments of the present application, the first parameter is less than 1, the second parameter is greater than 1, and the third parameter is less than 0.1.
In some embodiments of the present application, when determining the alert mode of the target device according to the alert value, the processor 401 may perform: and if the early warning value is larger than a first preset threshold and smaller than a second preset threshold, determining that the early warning mode of the target equipment is a first mode, wherein the first mode is the early warning mode when the target equipment has suspicion of faults.
In some embodiments of the present application, when determining the alert mode of the target device according to the alert value, the processor 401 may perform: and if the pre-warning values corresponding to the preset number of target devices are larger than a second preset threshold value, determining that the pre-warning mode of the target devices is a second mode, wherein the second mode refers to the pre-warning mode when a server or a network connected with the target devices has a suspected fault.
In some embodiments of the present application, the target early warning parameters include a first parameter, a second parameter, and a third parameter, the first parameter is smaller than 1, the second parameter is greater than 1, the third parameter is smaller than 0.1, the first predetermined threshold is equal to 1, and the second predetermined threshold is equal to 3.
In some embodiments of the present application, the processor 401 may perform: acquiring historical early warning information corresponding to the target equipment, wherein the historical early warning information comprises early warning mode recording information and historical equipment use data when the target equipment carries out fault early warning in history; acquiring current equipment use data of the target equipment; and performing prediction processing by adopting a pre-trained early warning model based on the early warning mode recording information, historical equipment use data and the current equipment use data to obtain the predicted target early warning parameter, the first preset threshold and the second preset threshold.
It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by a computer program, which may be stored in a computer-readable storage medium and loaded and executed by a processor, or by related hardware controlled by the computer program.
To this end, the present application further provides a storage medium, in which a computer program is stored, where the computer program can be loaded by a processor to execute the steps in any one of the methods provided in the present application.
Wherein the storage medium may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
Since the computer program stored in the storage medium can execute the steps in any method provided in the embodiments of the present application, the beneficial effects that can be achieved by the methods provided in the embodiments of the present application can be achieved, for details, see the foregoing embodiments, and are not described herein again.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains.
It will be understood that the present application is not limited to the embodiments that have been described above and shown in the drawings, but that various modifications and changes can be made without departing from the scope thereof.
Claims (10)
1. An equipment connection fault early warning method is characterized by comprising the following steps:
receiving the router signal intensity and the packet loss rate uploaded by the target device;
acquiring the off-line times of the target equipment in a target time period, and acquiring target early warning parameters;
calculating and processing based on the target early warning parameter, the router signal strength, the packet loss rate and the offline times to obtain an early warning value;
and determining an early warning mode of the target equipment according to the early warning value, and executing fault early warning operation corresponding to the early warning mode.
2. The method of claim 1, wherein the target warning parameters comprise a first parameter, a second parameter, and a third parameter;
calculating and processing the target early warning parameter, the router signal strength, the packet loss rate and the offline times to obtain an early warning value, wherein the method comprises the following steps:
multiplying the offline times by the first parameter to obtain a first value;
summing the router signal strength and the second parameter to obtain an adjustment value;
multiplying the adjustment value by the third parameter to obtain a second value;
and summing the first value, the second value and the packet loss rate to obtain the early warning value.
3. The method of claim 2, wherein the first parameter is less than 1, the second parameter is greater than 1, and the third parameter is less than 0.1.
4. The method of claim 1, wherein determining the alert mode of the target device based on the alert value comprises:
and if the early warning value is larger than a first preset threshold and smaller than a second preset threshold, determining that the early warning mode of the target equipment is a first mode, wherein the first mode is the early warning mode when the target equipment has suspicion of faults.
5. The method of claim 1 or 4, wherein the determining the alert mode of the target device according to the alert value comprises:
and if the pre-warning values corresponding to the preset number of target devices are larger than a second preset threshold value, determining that the pre-warning mode of the target devices is a second mode, wherein the second mode refers to the pre-warning mode when a server or a network connected with the target devices has a suspected fault.
6. The method of claim 5, wherein the target warning parameters include a first parameter, a second parameter, and a third parameter, the first parameter is less than 1, the second parameter is greater than 1, the third parameter is less than 0.1, the first predetermined threshold is equal to 1, and the second predetermined threshold is equal to 3.
7. The method of claim 5, further comprising:
acquiring historical early warning information corresponding to the target equipment, wherein the historical early warning information comprises early warning mode recording information and historical equipment use data when the target equipment carries out fault early warning in history;
acquiring current equipment use data of the target equipment;
and performing prediction processing by adopting a pre-trained early warning model based on the early warning mode recording information, historical equipment use data and the current equipment use data to obtain the predicted target early warning parameter, the first preset threshold and the second preset threshold.
8. An equipment connection failure early warning device, characterized by includes:
the receiving module is used for receiving the router signal strength and the packet loss rate uploaded by the target equipment;
the acquisition module is used for acquiring the off-line times of the target equipment in a target time period and acquiring target early warning parameters;
the calculation module is used for performing calculation processing based on the target early warning parameter, the router signal strength, the packet loss rate and the online times to obtain an early warning value;
and the early warning module is used for determining an early warning mode of the target equipment according to the early warning value and executing fault early warning operation corresponding to the early warning mode.
9. A storage medium having stored thereon a computer program which, when executed by a processor of a computer, causes the computer to carry out the method of any one of claims 1 to 7.
10. An electronic device, comprising: a memory storing a computer program; a processor reading a computer program stored in the memory to perform the method of any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111569883.4A CN114244681B (en) | 2021-12-21 | 2021-12-21 | Equipment connection fault early warning method and device, storage medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111569883.4A CN114244681B (en) | 2021-12-21 | 2021-12-21 | Equipment connection fault early warning method and device, storage medium and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114244681A true CN114244681A (en) | 2022-03-25 |
| CN114244681B CN114244681B (en) | 2023-08-01 |
Family
ID=80760244
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111569883.4A Active CN114244681B (en) | 2021-12-21 | 2021-12-21 | Equipment connection fault early warning method and device, storage medium and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114244681B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115001943A (en) * | 2022-05-27 | 2022-09-02 | 深圳小湃科技有限公司 | Equipment fault identification method and equipment based on big data and storage medium |
Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009042867A (en) * | 2007-08-07 | 2009-02-26 | Fujitsu Ten Ltd | Network system, recording device, and electronic control device |
| US20100087188A1 (en) * | 2008-10-06 | 2010-04-08 | Root Wireless, Inc. | Mobile device and method for collecting location based user quality data |
| CN102970771A (en) * | 2012-11-20 | 2013-03-13 | 西安大唐电信有限公司 | Signal detection and acquisition method and system based on wireless sensor network |
| CN103648113A (en) * | 2013-12-24 | 2014-03-19 | 山东润谱通信工程有限公司 | Indoor wireless network fault autonomous detection and positioning method |
| CN104486790A (en) * | 2014-12-31 | 2015-04-01 | 郭辉 | Wireless communication network fault detecting method and device |
| CN105703934A (en) * | 2014-11-28 | 2016-06-22 | 亿阳信通股份有限公司 | PON network fault diagnosis method and apparatus for household broadband service |
| US20180220476A1 (en) * | 2017-01-31 | 2018-08-02 | Grib Co., Ltd | Internet of things gateway and operating method of the same |
| US20180270126A1 (en) * | 2017-03-14 | 2018-09-20 | Tupl, Inc | Communication network quality of experience extrapolation and diagnosis |
| CN109951858A (en) * | 2017-12-21 | 2019-06-28 | 深圳Tcl新技术有限公司 | Network optimized approach, intelligent terminal and storage medium based on WIFI communication |
| CN109981328A (en) * | 2017-12-28 | 2019-07-05 | 中国移动通信集团陕西有限公司 | A kind of fault early warning method and device |
| CN110535710A (en) * | 2019-09-09 | 2019-12-03 | 锐捷网络股份有限公司 | Remote diagnosis method and system, the network equipment and Cloud Server of the network equipment |
| WO2020048047A1 (en) * | 2018-09-03 | 2020-03-12 | 平安科技（深圳）有限公司 | System fault warning method, apparatus, and device, and storage medium |
| CN112185070A (en) * | 2020-09-11 | 2021-01-05 | 珠海格力电器股份有限公司 | Fault early warning method, storage medium and electronic equipment |
| CN112583617A (en) * | 2019-09-29 | 2021-03-30 | 广东美的制冷设备有限公司 | Fault determination method, server, control terminal and storage medium |
| CN112702184A (en) * | 2019-10-23 | 2021-04-23 | 中国电信股份有限公司 | Fault early warning method and device and computer-readable storage medium |
| CN112888007A (en) * | 2020-12-30 | 2021-06-01 | 美的集团股份有限公司 | Method and device for diagnosing off-line reason of device and storage medium |
| CN112993519A (en) * | 2021-02-07 | 2021-06-18 | 惠州Tcl移动通信有限公司 | Intelligent terminal antenna and signal enhancement control method |
| WO2021227615A1 (en) * | 2020-05-14 | 2021-11-18 | 华为技术有限公司 | Method for improving call quality, and terminal |
| CN113747482A (en) * | 2020-05-29 | 2021-12-03 | 中国移动通信集团湖南有限公司 | Method, system and terminal equipment for detecting and analyzing service network |
-
2021
- 2021-12-21 CN CN202111569883.4A patent/CN114244681B/en active Active
Patent Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009042867A (en) * | 2007-08-07 | 2009-02-26 | Fujitsu Ten Ltd | Network system, recording device, and electronic control device |
| US20100087188A1 (en) * | 2008-10-06 | 2010-04-08 | Root Wireless, Inc. | Mobile device and method for collecting location based user quality data |
| CN102970771A (en) * | 2012-11-20 | 2013-03-13 | 西安大唐电信有限公司 | Signal detection and acquisition method and system based on wireless sensor network |
| CN103648113A (en) * | 2013-12-24 | 2014-03-19 | 山东润谱通信工程有限公司 | Indoor wireless network fault autonomous detection and positioning method |
| CN105703934A (en) * | 2014-11-28 | 2016-06-22 | 亿阳信通股份有限公司 | PON network fault diagnosis method and apparatus for household broadband service |
| CN104486790A (en) * | 2014-12-31 | 2015-04-01 | 郭辉 | Wireless communication network fault detecting method and device |
| US20180220476A1 (en) * | 2017-01-31 | 2018-08-02 | Grib Co., Ltd | Internet of things gateway and operating method of the same |
| US20180270126A1 (en) * | 2017-03-14 | 2018-09-20 | Tupl, Inc | Communication network quality of experience extrapolation and diagnosis |
| CN109951858A (en) * | 2017-12-21 | 2019-06-28 | 深圳Tcl新技术有限公司 | Network optimized approach, intelligent terminal and storage medium based on WIFI communication |
| CN109981328A (en) * | 2017-12-28 | 2019-07-05 | 中国移动通信集团陕西有限公司 | A kind of fault early warning method and device |
| WO2020048047A1 (en) * | 2018-09-03 | 2020-03-12 | 平安科技（深圳）有限公司 | System fault warning method, apparatus, and device, and storage medium |
| CN110535710A (en) * | 2019-09-09 | 2019-12-03 | 锐捷网络股份有限公司 | Remote diagnosis method and system, the network equipment and Cloud Server of the network equipment |
| CN112583617A (en) * | 2019-09-29 | 2021-03-30 | 广东美的制冷设备有限公司 | Fault determination method, server, control terminal and storage medium |
| CN112702184A (en) * | 2019-10-23 | 2021-04-23 | 中国电信股份有限公司 | Fault early warning method and device and computer-readable storage medium |
| WO2021227615A1 (en) * | 2020-05-14 | 2021-11-18 | 华为技术有限公司 | Method for improving call quality, and terminal |
| CN113747482A (en) * | 2020-05-29 | 2021-12-03 | 中国移动通信集团湖南有限公司 | Method, system and terminal equipment for detecting and analyzing service network |
| CN112185070A (en) * | 2020-09-11 | 2021-01-05 | 珠海格力电器股份有限公司 | Fault early warning method, storage medium and electronic equipment |
| CN112888007A (en) * | 2020-12-30 | 2021-06-01 | 美的集团股份有限公司 | Method and device for diagnosing off-line reason of device and storage medium |
| CN112993519A (en) * | 2021-02-07 | 2021-06-18 | 惠州Tcl移动通信有限公司 | Intelligent terminal antenna and signal enhancement control method |
Non-Patent Citations (1)
| Title |
|---|
| 陈若炜;覃文;张鹏;程乔;: "基于无线数据业务智能优化系统算法的研究与应用", 广西通信技术, no. 03 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115001943A (en) * | 2022-05-27 | 2022-09-02 | 深圳小湃科技有限公司 | Equipment fault identification method and equipment based on big data and storage medium |
| CN115001943B (en) * | 2022-05-27 | 2024-03-22 | 深圳小湃科技有限公司 | Equipment fault identification method, equipment and storage medium based on big data |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114244681B (en) | 2023-08-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113157422A (en) | Cloud data center cluster resource scheduling method and device based on deep reinforcement learning | |
| CN113031983B (en) | Intelligent software upgrading method and device based on deep reinforcement learning | |
| CN114244681B (en) | Equipment connection fault early warning method and device, storage medium and electronic equipment | |
| CN115437886A (en) | Fault early warning method, device and equipment based on storage and calculation integrated chip and storage | |
| CN115934344A (en) | Heterogeneous distributed reinforcement learning calculation method, system and storage medium | |
| CN114116275A (en) | Terminal abnormity repairing method and device, storage medium and electronic equipment | |
| CN109981396B (en) | Monitoring method and device for cluster of docker service containers, medium and electronic equipment | |
| CN113886196B (en) | On-chip power consumption management method, electronic device and storage medium | |
| CN115687026A (en) | Multi-node server fault early warning method, device, equipment and medium | |
| CN114034972B (en) | Intelligent cable fault determining method and device based on image data | |
| CN114647509A (en) | Memory cleaning method and device, storage medium and electronic equipment | |
| CN114090054A (en) | Intelligent equipment upgrading method and device, storage medium and electronic equipment | |
| CN114490432A (en) | Memory processing method and device, electronic equipment and computer readable storage medium | |
| CN110213106B (en) | Equipment information management method, device and system and electronic equipment | |
| CN112804104A (en) | Early warning method, device, equipment and medium | |
| CN118152966B (en) | Method, device, equipment and storage medium for processing vehicle information | |
| CN115865751B (en) | Fault detection method and device based on polymorphic data | |
| CN112685246B (en) | Time sequence data processing method and device | |
| CN117407213A (en) | System regulation and control method and device, storage medium and electronic equipment | |
| CN117579524A (en) | Micro-service abnormality detection method and device and electronic equipment | |
| CN117707824A (en) | Determination method and device for exception handler and nonvolatile storage medium | |
| CN118762951A (en) | Dual-electric three-station isolated grounding operation system and method | |
| CN117194234A (en) | Software testing method, device, equipment and storage medium | |
| CN114756433A (en) | Data processing method, device, equipment and storage medium | |
| CN115291860A (en) | Data processing method and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |