CN115221004B

CN115221004B - Single board state analysis method, device, equipment and readable storage medium

Info

Publication number: CN115221004B
Application number: CN202210784132.2A
Authority: CN
Inventors: 谢雨松; 郭华
Original assignee: Beijing Wisdom Tiancheng Technology Co ltd
Current assignee: Beijing Wisdom Tiancheng Technology Co ltd
Priority date: 2022-07-05
Filing date: 2022-07-05
Publication date: 2023-03-21
Anticipated expiration: 2042-07-05
Also published as: CN115221004A

Abstract

The application relates to a method, a device, equipment and a readable storage medium for analyzing a single board state, which are applied to the technical field of communication, wherein the method comprises the following steps: acquiring a plurality of device performance data of each communication device based on a CORBA protocol; classifying the performance data of the plurality of devices to obtain state data corresponding to a plurality of single boards in the communication device, wherein the state data comprises temperature performance data, memory data and CPU utilization data; judging whether to generate single board early warning information or not based on the state data; and if the single board early warning information is judged to be generated, outputting the type of the early warning information and the positioning information of the single board with the early warning information. The method and the system have the advantages that the maintenance personnel can check the running condition of the veneer conveniently, the position positioning information of the veneer with early warning is output simultaneously, the maintenance personnel can reduce the fault screening range quickly, abnormal data can be found in advance according to the early warning information, the abnormal communication equipment is intervened in advance to be processed, and the veneer can be guaranteed to run continuously, stably and healthily.

Description

Single board state analysis method, device, equipment and readable storage medium

Technical Field

The present application relates to the field of communications technologies, and in particular, to a method, an apparatus, a device, and a readable storage medium for analyzing a board status.

Background

Along with the rapid development of society, people have more and more vigorous demands on various services of communication. Communication equipment is widely used, and existing communication equipment includes single boards, where the single boards may include a transmission interface board, a main control board, a signaling processing board, a frame processing board, a power supply board, a baseband board, and the like according to functional division, and the single boards are connected through a backplane switching bus.

The single board needs to periodically inspect the running state of the single board in the application process, so that whether the single board fails or not is judged. The existing inspection mode is a mode of regularly exporting recent performance data of each single board in the communication equipment on management software, generating an EXCL table according to the exported performance data, checking whether the running state of the recent equipment is normal or not according to the EXCL table manually, and having or not having a phenomenon of performance degradation, but along with the continuous increase of a network, the number of the single boards in the communication equipment is also continuously increased, so that various performance data of the single boards which need to be paid attention in daily life are continuously increased, the defect that manpower screening hidden danger is low in timeliness in the presence of massive data is more and more prominent, meanwhile, in the existing inspection mode, only after the corresponding single board fails, maintenance personnel can find the failure based on the exported performance data table, and the failure finding of the single board is easily caused to be untimely.

Disclosure of Invention

In order to facilitate the maintenance personnel to check the operation condition of the single board and enable the single board to send abnormal data in time before the single board fails, the application provides a single board state analysis method, a single board state analysis device, a single board state analysis equipment and a readable storage medium.

In a first aspect, the present application provides a method for analyzing a state of a board, which adopts the following technical scheme:

a single board state analysis method comprises the following steps:

acquiring a plurality of device performance data of each communication device based on a CORBA protocol;

classifying the multiple pieces of equipment performance data to obtain state data corresponding to multiple single boards in the communication equipment, wherein the state data comprises temperature performance data, memory data and CPU utilization data;

judging whether to generate single board early warning information or not based on the state data;

and if the single board early warning information is judged to be generated, outputting the type of the early warning information and the positioning information of the single board with the early warning information.

By adopting the technical scheme, when the veneer early warning information is generated, the maintenance personnel can check the early warning information, the maintenance personnel can check the running condition of the veneer conveniently, the position positioning information of the veneer with early warning is output simultaneously, the maintenance personnel can reduce the fault screening range quickly, abnormal data can be found in advance according to the early warning information, the abnormal communication equipment is intervened in advance, and the continuous, stable and healthy running environment of the veneer is ensured.

Optionally, the determining, based on the state data, whether to generate the board warning information includes:

acquiring a plurality of temperature performance data of each single board in a current first statistical period;

if the temperature performance data contains the temperature not less than the first temperature threshold, judging to generate single-board real-time temperature early warning information;

if the difference value between the maximum temperature value and the minimum temperature value in the temperature performance data in the current first statistical period is not smaller than a second temperature threshold, judging to generate single-board short-term temperature early warning information; and/or the presence of a gas in the gas,

acquiring a plurality of temperature performance data in a current second statistical period, wherein the current second statistical period is greater than a current first statistical period;

and if the difference value between the maximum temperature value and the minimum temperature value in the temperature performance data in the current second statistical period is not less than a third temperature threshold, judging to generate the single-board long-term temperature early warning information.

By adopting the technical scheme, the temperatures corresponding to the plurality of temperature performance data in the first statistical period are respectively compared with the first temperature threshold value, so that the temperature data of the single plate can be acquired in real time; the difference value between the maximum temperature value and the minimum temperature value in the first statistical period can represent the short-term fluctuation condition of the single board in the first statistical period; the difference value between the maximum temperature value and the minimum temperature value in the second statistical period can reflect the long-term fluctuation condition of the single board in the second statistical period, so that the temperature of the single board is pre-warned according to various judgment modes, and the accuracy of the single board temperature pre-warning is improved.

Optionally, the determining whether to generate the board warning information based on the state data further includes:

acquiring a plurality of memory data of each single board in a current third statistical period and a last third statistical period;

and if the minimum value of the memory utilization rate in the memory data in the current third statistical period and the last third statistical period is not less than a memory rate threshold, judging to generate single-board memory early warning information.

By adopting the technical scheme, the minimum value of the memory utilization rate in the memory data in the current third statistical period and the last third statistical period is compared with the memory rate threshold value, whether the early warning data exists in the memory data of the single board or not is judged, and if yes, the single board memory early warning information is generated in time.

Optionally, the determining, based on the state data, whether to generate the board warning information further includes:

acquiring a plurality of CPU utilization data of each single board in a current fourth statistical period and a last fourth statistical period;

and if the minimum value of the CPU utilization rate in the CPU utilization data in the current fourth statistical period and the last fourth statistical period is not less than a utilization rate threshold value, judging to generate single-board CPU utilization rate early warning information.

By adopting the technical scheme, the minimum value of the CPU utilization rate in the CPU utilization data in the current fourth statistical period and the last fourth statistical period is compared with the utilization rate threshold value, whether the single-board CPU utilization data has early warning data or not is judged, and if yes, single-board CPU utilization rate early warning information is generated in time.

Optionally, the method further includes:

comparing the temperature performance data, the memory data and the CPU utilization data with corresponding initial abnormal threshold values respectively to obtain a plurality of abnormal data of the same kind of performance items, wherein the number of the abnormal data is i;

judging whether the number i of the abnormal data is equal to a preset number or not;

if yes, judging and generating single-board multi-data early warning information based on the abnormal data;

if the number i of the abnormal data is larger than the preset number, selecting the preset number of the abnormal data from the i abnormal data, and judging to generate single-board multi-data early warning information based on the selected abnormal data;

if the number i of the abnormal data is smaller than the preset number, adjusting the initial abnormal threshold value to obtain abnormal data of i + n similar performance items, updating the number i of the abnormal data to i + n, and repeatedly executing the step of judging whether the number i of the abnormal data is equal to the preset number, wherein n is a positive number.

By adopting the technical scheme, the abnormal data with higher veneer grade corresponding to the front preset quantity is selected from the abnormal data according to the sorting condition of the abnormal data, so that the abnormal data corresponding to the veneer with higher grade can be preferentially displayed and processed according to different grades of the abnormal data, and the workload of manually screening one by one is reduced.

Optionally, the selecting the preset number of abnormal data from the i abnormal data includes:

acquiring a single board grade corresponding to each abnormal data, and sequencing the abnormal data corresponding to the single boards based on the single board grades to obtain a sequence of the abnormal data;

and selecting the preset number of abnormal data from the i abnormal data based on the arrangement sequence.

By adopting the technical scheme, the single boards are graded based on the importance degrees of the communication equipment corresponding to the single boards, wherein the abnormal data corresponding to the single board with the lower importance degree is data which is not required to be displayed temporarily.

Optionally, the method further includes:

acquiring a plurality of temperature performance data of each single board in the last two first statistical periods adjacent to the current first statistical period;

if the minimum temperature value in the temperature performance data in the first statistical period of three times is not less than the first temperature threshold value for three consecutive times, generating important early warning information of the single board, and acquiring the memory data and the CPU utilization data of the single board at the moment corresponding to the minimum temperature value of three times;

and if the memory utilization rate in the memory data at the corresponding moment of the temperature minimum value which is continuous for three times is not less than the memory rate threshold value and/or the CPU utilization rate in the CPU utilization data is not less than the utilization rate threshold value, generating marking information which comprises the memory data and/or the CPU utilization data and is not less than the corresponding threshold value.

By adopting the technical scheme, the temperature performance data, the memory data and the CPU utilization data in the first statistical period which are continuous for multiple times are checked, so that the single-board state data can be linked in an early warning manner, the number of early warning pieces is reduced, the use of maintainers is simpler, meanwhile, the early warning linkage can reduce the artificial data comparison and checking time, and the fault judgment time is effectively shortened.

In a second aspect, the present application provides a board state analysis device applied to the board state analysis method in the first aspect, and adopts the following technical solution:

a single board state analysis device comprising:

the first acquisition module is used for acquiring a plurality of device performance data of each communication device based on a CORBA protocol;

a classification module, configured to classify the multiple pieces of device performance data to obtain state data corresponding to multiple boards in the communication device, where the state data includes temperature performance data, memory data, and CPU utilization data;

the first judging module is used for judging whether to generate single board early warning information or not based on the state data, and if the single board early warning information is judged to be generated, the single board early warning information is transferred to the output module;

and the output module is used for outputting the type of the early warning information and the positioning information of the single board with the early warning information.

In a third aspect, the present application provides an electronic device, which adopts the following technical solutions:

an electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the board state analysis method of the first aspect.

In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solutions:

a computer-readable storage medium storing a computer program that can be loaded by a processor and executes the board state analysis method according to the first aspect.

Drawings

Fig. 1 is a schematic flowchart of a single board state analysis method according to an embodiment of the present application.

Fig. 2 is a schematic flowchart of a method for analyzing a board state according to an embodiment of the present application.

Fig. 3 is a schematic flowchart of a method for analyzing a board state according to an embodiment of the present application.

Fig. 4 is a block diagram of a single board state analysis device according to an embodiment of the present application.

Fig. 5 is a block diagram of an electronic device according to an embodiment of the present application.

Detailed Description

The present application is described in further detail below with reference to the attached drawings.

The embodiment of the application provides a single board state analysis method, which can be executed by a device, wherein the device can be a server or an electronic device, wherein the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, and a cloud server providing cloud computing services. The electronic device may be, but is not limited to, a smartphone, a tablet, a desktop computer, and the like.

As shown in fig. 1, a method for analyzing a single board state includes the following main processes (steps S101 to S103):

step S101: acquiring a plurality of device performance data of each communication device based on a CORBA protocol;

in this embodiment, the device performance data of the communication device is collected through the northbound CORBA interface protocol, and the collected device performance data is stored, where the device performance data includes state data of a board, laser performance data, error code performance data, and the like.

Step S102: classifying the performance data of the plurality of devices to obtain state data corresponding to a plurality of single boards in the communication device, wherein the state data comprises temperature performance data, memory data and CPU utilization data;

in this embodiment, the state data of the board includes temperature performance data, memory data of the board, and CPU utilization data, and the operating condition of the board can be determined by the temperature performance data, the memory data of the board, and the CPU utilization data.

In this embodiment, the temperature performance data includes a temperature value corresponding to the board, the memory data includes a memory utilization rate corresponding to the board, and the CPU utilization data includes a CPU utilization rate.

Under normal conditions, the temperature performance data, the memory data, and the CPU utilization data of the board are all within a normal range, for example, the temperature corresponding to the temperature performance data is below 40 ℃, the memory rate corresponding to the memory data is below 50%, and the CPU utilization rate corresponding to the CPU utilization data is below 50%.

Step S103: judging whether to generate single board early warning information or not based on the state data, and if so, turning to the step S104;

the following description is directed to a case of determining whether to generate single board warning information:

the first method comprises the following steps: and judging whether to generate temperature early warning based on the temperature performance data, wherein the temperature early warning comprises single-board real-time temperature early warning information, single-board short-term temperature early warning information and single-board long-term temperature early warning information.

Specifically, the step of judging whether to generate the real-time temperature early warning information of the veneer based on the temperature performance data includes: acquiring a plurality of temperature performance data of each single board in a current first statistical period; and if the temperature not less than the first temperature threshold exists in the plurality of temperature performance data, judging to generate the veneer real-time temperature early warning information.

The first statistical period needs to be set by a maintenance person, and the first statistical period may be consistent with a register period of a register for storing status data in the network element device, for example, the first statistical period is 15 minutes. The temperatures corresponding to the multiple temperature performance data in the first statistical period are respectively compared with the first temperature threshold, so that the temperature data of the single board can be acquired in real time.

Judging whether to generate the veneer short-term temperature early warning information based on the temperature performance data comprises the following steps: and if the difference value between the maximum temperature value and the minimum temperature value in the temperature performance data in the current first statistical period is not less than the second temperature threshold, judging to generate the single-board short-term temperature early warning information. The difference value between the maximum temperature value and the minimum temperature value in the first statistical period can represent the short-term fluctuation condition of the single board in the first statistical period.

Judging whether to generate the veneer long-term temperature early warning information based on the temperature performance data comprises the following steps: acquiring a plurality of temperature performance data in a current second statistical period, wherein the current second statistical period is greater than the current first statistical period; and if the difference value between the maximum temperature value and the minimum temperature value in the temperature performance data in the current second statistical period is not less than the third temperature threshold, judging to generate the single-plate long-term temperature early warning information.

The second statistical period needs to be set by a maintenance worker, for example, the second statistical period is 24 hours, and the long-term fluctuation condition of the veneer within 24 hours can be reflected by the difference value between the maximum temperature value and the minimum temperature value within 24 hours, so that the temperature of the veneer is pre-warned according to various judgment modes, and the accuracy of the veneer temperature pre-warning is improved.

And the second method comprises the following steps: and judging whether to generate a memory early warning based on the memory data, wherein the memory early warning comprises single-board memory early warning information.

Specifically, the determining whether to generate the board memory warning information based on the memory data includes: acquiring a plurality of memory data of each single board in a current third statistical period and a last third statistical period; and if the minimum value of the memory utilization rate in the memory data in the current third statistical period and the last third statistical period is not less than the memory rate threshold, judging to generate single-board memory early warning information.

In this embodiment, the third statistical period is the same as the statistical time of the first statistical period, and is also 15 minutes. It is easy to understand that, when determining whether to generate the single-board memory warning information, a plurality of memory data within a third statistical period that continuously exceeds two times may also be compared with the memory rate threshold.

And the third is that: and judging whether to generate a CPU type early warning based on the CPU utilization data, wherein the CPU type early warning comprises single-board CPU utilization rate early warning information.

Specifically, the step of judging whether to generate the single board CPU utilization rate early warning information based on the CPU utilization data includes: acquiring a plurality of CPU utilization data of each single board in a current fourth statistical period and a last fourth statistical period; and if the minimum value of the CPU utilization rate in the CPU utilization data in the current fourth statistical period and the last fourth statistical period is not less than the utilization rate threshold, judging to generate single-board CPU utilization rate early warning information.

In this embodiment, the fourth statistical period is equal to the statistical time of the first statistical period, and is also 15 minutes. It is easy to understand that, when determining whether to generate the single-board CPU utilization rate early warning information, the multiple pieces of CPU utilization data in the fourth statistical period that exceed two times may also be compared with the utilization rate threshold.

In this embodiment, because the number of boards and the state data are more, the application importance of the corresponding communication device for individually generating the board warning information is lower, and the board warning information may not need to be processed in time by the maintenance personnel, but which boards corresponding to the warning needs to be processed preferentially, and the maintenance personnel also needs to perform manual one-by-one screening, as shown in fig. 2, so the board state analysis method further includes the following processing:

step S111: respectively comparing the temperature performance data, the memory data and the CPU utilization data with corresponding initial abnormal threshold values to obtain a plurality of abnormal data of the same type of performance items, wherein the number of the abnormal data is i;

step S112: judging whether the number i of the abnormal data is equal to a preset number or not;

step S113: if yes, judging and generating single-board multi-data early warning information based on the abnormal data;

step S114: judging whether the number i of the abnormal data is larger than a preset number, if so, turning to a step S115, and if not, turning to a step S116;

step S115: selecting a preset number of abnormal data from the i abnormal data, and judging to generate single-board multi-data early warning information based on the selected abnormal data;

step S116: and adjusting the initial abnormal threshold value to obtain abnormal data of i + n similar performance items, updating the number i of the abnormal data to i + n, and repeatedly executing the step of judging whether the number i of the abnormal data is equal to the preset number, wherein n is a positive number.

Step S114 further includes the following processing: acquiring a single board grade corresponding to each abnormal data, and sequencing the abnormal data corresponding to the multiple single boards based on the single board grades to obtain a sequence of the multiple abnormal data; a preset number of abnormal data are selected from the i abnormal data based on the arrangement order.

In this embodiment, the abnormal data is data exceeding a corresponding initial abnormal threshold, the initial abnormal threshold corresponding to the temperature performance data is a first temperature threshold, the initial abnormal threshold corresponding to the memory data is a memory rate threshold, and the CPU uses the initial abnormal threshold corresponding to the data as a utilization rate threshold. For example, the first temperature threshold is 35 ℃, the memory rate threshold is 45%, and the utilization rate threshold is 45%.

The single boards are classified according to the importance degrees of the communication devices corresponding to the single boards, wherein abnormal data corresponding to the single boards with lower importance degrees are data which are not needed to be displayed temporarily, and the importance degrees of the communication devices corresponding to the single boards can be set according to the use scenes.

In this embodiment, the preset number is 10 to 15, and in the case that the number of the abnormal data is greater than 15, the abnormal data with the higher veneer grade corresponding to the first 15 veneers needs to be selected from the plurality of abnormal data according to the sorting condition of the abnormal data, so that the abnormal data corresponding to the veneers with the higher grade can be preferentially displayed and processed according to different grades of the abnormal data, and the workload of manually performing screening one by one is reduced.

Step S104: and outputting the type of the early warning information and the positioning information of the single board with the early warning information.

In this embodiment, the pre-warning modes corresponding to the temperature pre-warning, the memory pre-warning and the CPU pre-warning may include an audible and visual alarm. The abnormal threshold values corresponding to the temperature performance data, the memory data and the CPU utilization data are all smaller than the fault values when the corresponding data are in fault, when the single board early warning information is generated, the position positioning information of the single board in early warning is output at the same time, so that maintenance personnel can conveniently and quickly narrow the fault screening range, find abnormal data in advance according to the early warning information, intervene in the abnormal communication equipment in advance, and guarantee the continuous, stable and healthy running environment of the single board.

As shown in fig. 3, the single board state analysis method further includes the following processing:

step S121: acquiring a plurality of temperature performance data of each single board in the last two first statistical periods adjacent to the current first statistical period;

step S122: judging whether the minimum temperature value in the temperature performance data in the first statistical period which is continuous for three times is not less than the first temperature threshold value for three times, if so, turning to the step S123;

step S123: generating important early warning information of the single board, and acquiring memory data and CPU utilization data of the single board at the moment corresponding to the minimum value of the three temperatures;

step S124: judging whether the memory utilization rate in the memory data at the moment corresponding to the minimum value of the three temperatures is not less than the memory rate threshold value and/or whether the CPU utilization rate in the CPU utilization data is not less than the utilization rate threshold value, if so, turning to the step S125;

step S125: and generating marking information which comprises the memory data and/or the CPU utilization data and is not less than the corresponding threshold value.

In this embodiment, the important single-board early warning information is that the minimum temperature value corresponding to the first statistical period of three consecutive times is not less than the first temperature threshold, that is, the temperature performance of the single board in the first statistical period of three consecutive times is all subjected to abnormal early warning, the important single-board early warning information is generated at this time, the memory data and the CPU utilization data corresponding to the time when the temperature is abnormal need to be checked, the early warning level of the important single-board early warning information is higher, the important single-board early warning information needs to be preferentially displayed at the user terminal, and the display mode can be an audible and visual alarm or a display screen popup window or sending the early warning information to a preset administrator terminal.

When judging whether the important early warning information of the single board is generated or not, the temperature performance data in the first statistical period which is continuously repeated for many times can be compared with the memory rate threshold. Temperature performance data, memory data and CPU utilization data in a first statistical period which is continuous for multiple times are checked, single-board state data can be linked in an early warning mode, the number of early warning pieces is reduced, maintenance personnel can use the single-board state data more simply, meanwhile, manual data comparison and checking time can be reduced through early warning linkage, and fault judgment time is effectively shortened.

Based on the same technical concept, the present application further provides a single board state analysis apparatus, as shown in fig. 4, the analysis apparatus 200 mainly includes:

a first obtaining module 201, configured to obtain multiple pieces of device performance data of each communication device based on a CORBA protocol;

a classification module 202, configured to classify the multiple device performance data to obtain status data corresponding to multiple boards in the communication device, where the status data includes temperature performance data, memory data, and CPU utilization data;

the first judging module 203 is configured to judge whether to generate single board warning information based on the state data, and if it is judged that the single board warning information is generated, switch to the output module;

and the output module 204 is configured to output the type of the warning information and the positioning information of the board in which the warning information appears.

Optionally, the first determining module 203 further includes:

the first obtaining submodule is used for obtaining a plurality of temperature performance data of each single board in a current first statistical period;

the first judgment sub-module is used for judging and generating single-board real-time temperature early warning information when the temperature which is not less than a first temperature threshold value exists in the plurality of temperature performance data;

the second judgment sub-module is used for judging and generating single-board short-term temperature early warning information when the difference value between the maximum temperature value and the minimum temperature value in the temperature performance data in the current first statistical period is not less than a second temperature threshold value; and/or the presence of a gas in the gas,

the second obtaining submodule is used for obtaining a plurality of temperature performance data in a current second statistical period, and the current second statistical period is larger than the current first statistical period;

and the third judgment submodule is used for judging and generating the single-plate long-term temperature early warning information when the difference value between the maximum temperature value and the minimum temperature value in the temperature performance data in the current second statistical period is not less than a third temperature threshold value.

Optionally, the first determining module 203 further includes:

a third obtaining submodule, configured to obtain multiple pieces of memory data of each board in a current third statistical period and a previous third statistical period;

and the fourth judging submodule is used for judging and generating the single-board memory early warning information when the minimum value of the memory utilization rate in the memory data in the current third statistical period and the last third statistical period is not less than the memory rate threshold value.

Optionally, the first determining module 203 further includes:

a fourth obtaining submodule, configured to obtain multiple pieces of CPU utilization data in a current fourth statistical period and a last fourth statistical period of each board;

and the fifth judging submodule is used for judging and generating single-board CPU utilization rate early warning information when the minimum value of the CPU utilization rate in the CPU utilization data in the current fourth statistical period and the last fourth statistical period is not less than the utilization rate threshold value.

Optionally, the analysis apparatus 200 further includes:

the comparison module is used for respectively comparing the temperature performance data, the memory data and the CPU utilization data with corresponding initial abnormal threshold values to obtain a plurality of abnormal data of the same type of performance items, wherein the number of the abnormal data is i;

the second judgment module is used for judging whether the number i of the abnormal data is equal to the preset number, and if so, the generation of a sixth judgment submodule is carried out;

the judging module is used for judging and generating single-board multi-data early warning information based on the abnormal data;

the selection module is used for selecting a preset number of abnormal data from the i abnormal data when the number i of the abnormal data is larger than a preset number, and judging and generating single-board multi-data early warning information based on the selected abnormal data;

and the adjusting module is used for adjusting the initial abnormal threshold value when the number i of the abnormal data is smaller than the preset number, obtaining the abnormal data of i + n similar performance items, updating the number i of the abnormal data to i + n, and repeatedly executing the step of judging whether the number i of the abnormal data is equal to the preset number, wherein n is a positive number.

Optionally, the selecting module further includes:

the fifth obtaining submodule is used for obtaining the veneer grade corresponding to each abnormal data, and sequencing the abnormal data corresponding to the plurality of veneers based on the veneer grade to obtain the arrangement sequence of the plurality of abnormal data;

and the selection submodule is used for selecting a preset number of abnormal data from the i abnormal data based on the arrangement sequence.

Optionally, the analysis apparatus 200 further comprises:

the second obtaining module is used for obtaining a plurality of temperature performance data of each single board in the first statistical period of the last two times adjacent to the current first statistical period;

the generating module is used for generating important early warning information of the single board when the minimum temperature value in the temperature performance data in the first statistic period is not less than the first temperature threshold value for three consecutive times, and acquiring memory data and CPU utilization data of the single board at the moment corresponding to the minimum temperature value for three times;

and the marking module is used for generating marking information which comprises the memory data and/or the CPU utilization data and is not less than the corresponding threshold value when the memory utilization rate in the memory data at the corresponding moment of the three continuous temperature minimum values is not less than the memory rate threshold value and/or the CPU utilization rate in the CPU utilization data is not less than the utilization rate threshold value.

In one example, the modules in any of the above apparatus may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more Digital Signal Processors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), or a combination of at least two of these integrated circuit forms.

For another example, when a module in a device may be implemented in the form of a processing element scheduler, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of invoking programs. As another example, these modules may be integrated together, implemented in the form of a system-on-a-chip (SOC).

Various objects such as various messages/information/devices/network elements/systems/devices/actions/operations/procedures/concepts may be named in the present application, it is to be understood that these specific names do not constitute limitations on related objects, and the named names may vary according to circumstances, contexts, or usage habits, and the understanding of the technical meaning of the technical terms in the present application should be mainly determined by the functions and technical effects embodied/performed in the technical solutions.

It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the apparatus and the module described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

Those of ordinary skill in the art will appreciate that the various illustrative modules and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

Based on the same technical concept, the embodiment of the present application also discloses an electronic device, as shown in fig. 5, the electronic device 300 includes a processor 301 and a memory 302, and may further include one or more of an information input/information output (I/O) interface 303, a communication component 304, and a communication bus 305.

The processor 301 is configured to control the overall operation of the electronic device 300, so as to complete all or part of the steps in the single board state analysis method; the memory 302 is used to store various types of data to support operation at the electronic device 300, such data may include, for example, instructions for any application or method operating on the electronic device 300, as well as application-related data. The Memory 302 may be implemented by any type or combination of volatile and non-volatile Memory devices, such as one or more of Static Random Access Memory (SRAM), electrically Erasable Programmable Read-Only Memory (EEPROM), erasable Programmable Read-Only Memory (EPROM), programmable Read-Only Memory (PROM), read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic or optical disk.

The I/O interface 303 provides an interface between the processor 301 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 304 is used for wired or wireless communication between the electronic device 300 and other devices. Wireless Communication, such as Wi-Fi, bluetooth, near Field Communication (NFC), 2G, 3G, or 4G, or a combination of one or more of them, so that the corresponding Communication component 104 may include: wi-Fi components, bluetooth components, NFC components.

The communication bus 305 may include a path to transfer information between the aforementioned components. The communication bus 305 may be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The communication bus 305 may be divided into an address bus, a data bus, a control bus, and the like.

The electronic Device 300 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components, and is configured to perform the board status analyzing method according to the above embodiments.

The electronic device 300 may include, but is not limited to, a digital broadcast receiver, a mobile terminal such as a PDA (personal digital assistant), a PMP (portable multimedia player), and the like, and a fixed terminal such as a digital TV, a desktop computer, and the like, and may also be a server, and the like.

Based on the same technical concept, an embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the single board state analysis method are implemented.

The computer-readable storage medium may include: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the application referred to in the present application is not limited to the embodiments with a particular combination of the above-mentioned features, but also encompasses other embodiments with any combination of the above-mentioned features or their equivalents without departing from the spirit of the application. For example, the above features may be replaced with (but not limited to) features having similar functions as those described in this application.

Claims

1. A single board state analysis method is characterized by comprising the following steps:

judging whether to generate single board early warning information or not based on the state data; the judging whether to generate the single board early warning information based on the state data comprises: acquiring a plurality of temperature performance data of each single board in a current first statistical period; if the temperature performance data contains the temperature not less than the first temperature threshold, judging to generate single-board real-time temperature early warning information;

if the single board early warning information is judged to be generated, outputting the type of the early warning information and the positioning information of the single board with the early warning information;

after obtaining the status data corresponding to the plurality of boards in the communication device, the method further includes:

if the number i of the abnormal data is smaller than the preset number, adjusting the initial abnormal threshold value to obtain abnormal data of i + n similar performance items, updating the number i of the abnormal data to i + n, and repeatedly executing the step of judging whether the number i of the abnormal data is equal to the preset number, wherein n is a positive number;

and if the memory utilization rate in the memory data at the corresponding moment of the three continuous temperature minimum values is not less than the memory rate threshold value and/or the CPU utilization rate in the CPU utilization data is not less than the utilization rate threshold value, generating marking information which comprises the memory data and/or the CPU utilization data and is not less than the corresponding threshold value.

2. The method of claim 1, wherein the determining whether to generate single board warning information based on the status data further comprises:

3. The method of claim 2, wherein the determining whether to generate single board warning information based on the status data further comprises:

4. The method of claim 3, wherein the determining whether to generate single board warning information based on the status data further comprises:

and if the minimum value of the CPU utilization rate in the CPU utilization data in the current fourth statistical period and the last fourth statistical period is not less than the utilization rate threshold, judging to generate single-board CPU utilization rate early warning information.

5. The method of claim 1, wherein said selecting the preset number of the abnormal data among the i abnormal data comprises:

acquiring a single board grade corresponding to each abnormal data, and sequencing the abnormal data corresponding to the plurality of single boards based on the single board grade to obtain a sequence of the plurality of abnormal data;

6. A single board state analysis device, comprising:

the classification module is used for classifying the plurality of equipment performance data to obtain state data corresponding to a plurality of single boards in the communication equipment, wherein the state data comprises temperature performance data, memory data and CPU utilization data;

the first judging module is used for judging whether to generate single board early warning information or not based on the state data, and if the single board early warning information is judged to be generated, the single board early warning information is transferred to the output module; the first judging module comprises a first obtaining submodule for obtaining a plurality of temperature performance data of each single board in a current first statistic period; the first judgment submodule is used for judging and generating single-board real-time temperature early warning information when the temperature which is not less than a first temperature threshold value exists in the plurality of temperature performance data;

the output module is used for outputting the type of the early warning information and the positioning information of the single board with the early warning information;

after the classification module, the analysis apparatus further comprises:

the second judgment module is used for judging whether the number i of the abnormal data is equal to a preset number, and if so, switching to a sixth judgment sub-module;

a selecting module, configured to select the preset number of abnormal data from the i abnormal data when the number i of the abnormal data is greater than the preset number, and determine to generate early warning information of multiple pieces of single-board data based on the selected abnormal data;

an adjusting module, configured to adjust an initial abnormal threshold when the number i of the abnormal data is smaller than the preset number, to obtain abnormal data of i + n similar performance items, update the number i of the abnormal data to i + n, and repeatedly perform the step of determining whether the number i of the abnormal data is equal to the preset number, where n is a positive number;

after the classification module, the analysis apparatus further comprises:

a second obtaining module, configured to obtain multiple pieces of temperature performance data of each board in a first statistical period of last two times that is adjacent to the current first statistical period;

the generating module is used for generating important early warning information of the single board when the minimum temperature value in the temperature performance data in the first statistical period of three times is not less than the first temperature threshold value for three consecutive times, and acquiring the memory data and the CPU utilization data of the single board at the moment corresponding to the minimum temperature value of three times;

7. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program that can be loaded by the processor and that executes the method according to any of claims 1 to 5.

8. A computer-readable storage medium, in which a computer program is stored which can be loaded by a processor and which executes a method according to any one of claims 1 to 5.