Information determination method, equipment and medium

Abstract

The invention relates to an information determination method, equipment and a medium. The method comprises the following steps: acquiring software and hardware data corresponding to different pieces of equipment respectively; according to the software and hardware data corresponding to the different devices respectively, determining device life values corresponding to the different devices respectively; and determining the health degree of the system according to the device life values corresponding to the different devices.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and more specifically, to an information determination method, device and medium. Background Art

[0002] During the operation of the system, emergencies often occur. If a device suddenly stops working or is damaged at a certain time, the entire system may not work properly. The relevant technology is aimed at a single device and is applied to the monitoring of the hardware components of the device. The data analysis dimension is single, mainly detecting the life form of the hardware, and it is impossible to comprehensively evaluate the life form of a device or system. Summary of the invention

[0003] One purpose of the embodiments of the present disclosure is to provide a new technical solution for information determination.

[0004] According to a first aspect of the present disclosure, there is provided an information determination method, the method comprising:

[0005] Get the software and hardware data corresponding to different devices;

[0006] Determine the device life values ​​corresponding to the different devices respectively according to the software and hardware data corresponding to the different devices respectively;

[0007] The health of the system is determined according to the device life values ​​corresponding to the different devices.

[0008] Optionally, the software and hardware data includes software data and hardware data.

[0009] The hardware data includes at least one of the following: daily parameter monitoring data, abnormal fluctuation monitoring data, fault statistics data, and alarm statistics data;

[0010] The software data includes at least one of the following: CPU fluctuation range, disk occupancy range, memory fluctuation range, process enablement status, application enablement status, port occupancy status, fault statistics data, and alarm statistics data.

[0011] Optionally, determining the device life value of the device according to the software and hardware data of the device includes:

[0012] Determine the event occurrence rates corresponding to the events of the device according to the hardware and software data of the device and the weight values ​​corresponding to the events of the device;

[0013] Determining the life coefficient of the device according to the event occurrence rates corresponding to the events and the device parameters of the device;

[0014] The device life value of the device is determined according to the life coefficient of the device.

[0015] Optionally, determining the health of the system according to the device life values ​​corresponding to the different devices respectively includes:

[0016] Obtaining weight values ​​corresponding to the different devices respectively;

[0017] The health of the system is determined according to the weight values ​​respectively corresponding to the different devices and the device life values ​​respectively corresponding to the different devices.

[0018] Optionally, the method further comprises:

[0019] First mapping data reflecting the correspondence between time and the device life value of the device is established.

[0020] Optionally, after establishing the first mapping data reflecting the correspondence between the time and the device life value of the device, the method further includes:

[0021] Obtaining a critical life value of the device;

[0022] determining, based on the critical life value, whether the device will fail in the future;

[0023] In the case where it is determined that the device will fail in the future, the time when the device will fail in the future is estimated based on the first mapping data and the future life value of the device.

[0024] Optionally, the method further comprises:

[0025] Second mapping data reflecting the corresponding relationship between time, device life value corresponding to at least one of the different devices, and health of the system are established.

[0026] Optionally, the method further comprises:

[0027] Obtaining a critical health of the system and a critical life value corresponding to each of the at least one device;

[0028] determining whether the system will fail in the future according to the critical health and the critical life value corresponding to the at least one device;

[0029] When it is determined that the system will fail in the future, the time when the system will fail in the future is estimated according to the second mapping data, the future health of the system and the at least one corresponding future life value.

[0030] According to a second aspect of the present disclosure, an electronic device is provided, comprising a memory and a processor, wherein the memory is used to store an executable computer program; and the computer program is used to control the processor to execute the method according to the first aspect of the present disclosure.

[0031] According to a third aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method described in the first aspect of the present disclosure is implemented.

[0032] One beneficial effect of the disclosed embodiment is that it counts the software and hardware data of each device in the system, obtains the device life value of the device based on the software and hardware data of the device, and obtains the health of the system based on the device life values ​​corresponding to different devices in the system. In other words, the sampled data includes software data and hardware data, and the device life value of the device can be obtained based on the software and hardware data of a single device, and the health of the entire system can be obtained based on the device life values ​​corresponding to different devices, so that the life status of different devices and the life form of the entire system can be known.

[0033] Further features and advantages of the present invention will become apparent from the following detailed description of exemplary embodiments of the present invention with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0035] Figure 1 A block diagram showing a hardware configuration of an electronic device that can implement an embodiment of the present disclosure;

[0036] Figure 2 is a flowchart of an information determination method according to an embodiment of the present disclosure;

[0037] Figure 3 is a schematic diagram of first mapping data according to an embodiment of the present disclosure;

[0038] Figure 4 is a schematic diagram of second mapping data according to an embodiment of the present disclosure;

[0039] Figure 5 is a block diagram of an information determination device according to an embodiment of the present disclosure;

[0040] Figure 6 is a block diagram of an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0041] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless otherwise specifically stated.

[0042] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0043] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered as part of the specification.

[0044] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0045] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0046] <Hardware Configuration>

[0047] Figure 1 A block diagram showing a hardware configuration of an electronic device 1000 that can implement an embodiment of the present disclosure is shown.

[0048] The electronic device 1000 may be a portable computer, a desktop computer, a mobile phone, a tablet computer, etc. Figure 1 As shown, the electronic device 1000 may include a processor 1100, a memory 1200, an interface device 1300, a communication device 1400, a display device 1500, an input device 1600, a speaker 1700, a microphone 1800, and the like. Among them, the processor 1100 may be a central processing unit CPU, a microprocessor MCU, and the like. The memory 1200 includes, for example, a ROM (read-only memory), a RAM (random access memory), a non-volatile memory such as a hard disk, and the like. The interface device 1300 includes, for example, a USB interface, a headphone interface, and the like. The communication device 1400 is, for example, capable of wired or wireless communication, and may specifically include Wifi communication, Bluetooth communication, 2G / 3G / 4G / 5G communication, and the like. The display device 1500 is, for example, a liquid crystal display screen, a touch display screen, and the like. The input device 1600 may include, for example, a touch screen, a keyboard, a somatosensory input, and the like. The user may input / output voice information through the speaker 1700 and the microphone 1800.

[0049] Figure 1The electronic device shown is merely illustrative and does not in any way imply any limitation on the present disclosure, its application or use. In the embodiments of the present disclosure, the memory 1200 of the electronic device 1000 is used to store instructions, and the instructions are used to control the processor 1100 to operate to perform any one of the information determination methods provided in the embodiments of the present disclosure. It should be understood by those skilled in the art that although Figure 1 In the electronic device 1000, multiple devices are shown, but the present disclosure may only involve some of the devices, for example, the electronic device 1000 only involves the processor 1100 and the storage device 1200. A technician can design instructions according to the scheme disclosed in the present disclosure. How instructions control the processor to operate is well known in the art, so it will not be described in detail here.

[0050] <Method Example>

[0051] The present disclosure embodiment discloses a method for determining information, such as Figure 2 As shown, the information determination method includes the following steps S2100 to S2300.

[0052] Step S2100, obtaining software and hardware data corresponding to different devices.

[0053] The software and hardware data include software data and hardware data. The hardware data includes at least one of the following: daily parameter monitoring data, abnormal fluctuation monitoring data, fault statistics data, and alarm statistics data.

[0054] The software data includes at least one of the following: CPU fluctuation range, disk occupancy range, memory fluctuation range, process enablement status, application enablement status, port occupancy status, fault statistics data, and alarm statistics data.

[0055] In this embodiment, the system may include different devices. After the system goes online and starts running, each device monitors its own software and hardware running status and reports the software and hardware data to the data server periodically or in real time through the gateway. The data server collects historical software and hardware data and current software and hardware data.

[0056] Exemplarily, the system includes device 1, device 2, and device 3, and can collect the software and hardware data corresponding to device 1, device 2, and device 3, respectively. For example, the hardware data corresponding to any device includes, but is not limited to, daily monitoring data Q1, abnormal fluctuation monitoring data Q2, fault statistics data Q3, and alarm statistics data Q4. The software data corresponding to any device includes, but is not limited to, CPU fluctuation range Q5, disk occupancy range Q6, memory fluctuation range Q7, process enablement status Q8, application enablement status Q9, port occupancy status Q10, as well as fault statistics Q11, alarm statistics Q12...Qm.

[0057] After executing the above step S2100 to obtain the software and hardware data corresponding to different devices, enter:

[0058] Step S2200: Determine the device life values ​​corresponding to the different devices respectively according to the software and hardware data corresponding to the different devices respectively.

[0059] In this embodiment, the data processing server in the data server processes the collected software and hardware data to first determine the device life value of the device.

[0060] In an optional embodiment, this step S2200, according to the software and hardware data corresponding to the different devices, determines the device life values ​​corresponding to the different devices respectively, and may further include the following steps S2210 to S2230:

[0061] Step S2210: determining the event occurrence rates corresponding to the events of the device according to the hardware and software data of the device and the weight values ​​corresponding to the events of the device.

[0062] Among them, events include, for example but not limited to, alarm events and fault events, and there is a corresponding relationship between events and software and hardware data.

[0063] Among them, the occurrence rate of an event refers to the probability of occurrence of the corresponding event. The occurrence rate of an event is determined based on the data corresponding to the event and the weight value of the event. The weight value of the event is usually a value set according to the actual application scenario and actual needs, and this embodiment does not limit this.

[0064] Continuing with the above example, the hardware data corresponding to any device includes, but is not limited to, daily monitoring data Q1, abnormal fluctuation monitoring data Q2, fault statistics data Q3, and alarm statistics data Q4. The software data corresponding to any device includes, but is not limited to, CPU fluctuation interval Q5, disk occupancy interval Q6, memory fluctuation interval Q7, process enablement status Q8, application enablement status Q9, port occupancy status Q10, as well as fault statistics Q11, alarm statistics Q12...Qm. Then the weight value of event 1 is L1, the weight value of event 2 is L2, the weight value of event 3 is L3, the weight value of event 4 is L4...the weight value of event m is Lm, where event 1 corresponds to daily monitoring data Q1, event 2 corresponds to abnormal fluctuation monitoring data Q2, event 3 corresponds to fault statistics data Q3...event m corresponds to Qm. Among them, the event occurrence rate of event 1 is S1=Q1*L1, the event occurrence rate of event 2 is S2=Q2*L2, the event occurrence rate of event 3 is S3=Q3*L3... and the event occurrence rate of event m is Sm=Qm*Lm.

[0065] Step S2220, determining the life coefficient of the device according to the event occurrence rates corresponding to the events and the device parameters of the device.

[0066] The equipment parameters include, for example but not limited to, dynamic coefficient, cycle time, interval time and number of occurrences.

[0067] In this step S2220, the life coefficient of the device can be determined based on the event occurrence rate corresponding to each event of the device, the dynamic coefficient of the device, the cycle time, the interval time and the number of occurrences.

[0068] Among them, the life coefficient p of any device is:

[0069] p=(S1+S2+S3+…+Sm)*c*(△T / T) num .

[0070] Among them, S1 represents the event occurrence rate of event 1 of any device, S2 represents the event occurrence rate of event 2 of any device, S3 represents the event occurrence rate of event 3 of any device…Sm represents the event occurrence rate of event m of any device, c represents the dynamic coefficient of any device, T represents the cycle time of any device, △T represents the interval time of any device, and num represents the number of occurrences of any device.

[0071] Continuing with the above example, according to this step S2220, the life coefficient p1 of device 1, the life coefficient p2 of device 2, and the life coefficient p3 of device 3 can be obtained.

[0072] Step S2230: Determine the device life value of the device according to the life coefficient of the device.

[0073] In this step S2230, the device life value of the device can be determined according to the life coefficient of the device.

[0074] Among them, the device health value of any device is Where p is the life coefficient of the arbitrary device, q can be the number of events that occur in the arbitrary device, or the number of parts of the arbitrary device. Continuing with the above example, according to this step S2230, the device life value of device 1 can be obtained, for example, Among them, p1 is the life coefficient of device 1, q1 can be the number of events that occurred in device 1, or the number of parts of device 1; the device life value of device 2 Among them, p2 is the life coefficient of device 2, q2 can be the number of events that occurred in device 2, or the number of parts of device 2; and the device life value of device 3 Among them, p3 is the life coefficient of device 3, q3 can be the number of events occurring in device 3, or the number of parts of device 3.

[0075] After executing the above step S2200 to determine the device life values ​​corresponding to the different devices according to the software and hardware data corresponding to the different devices, proceed to:

[0076] Step S2300: determining the health of the system according to the device life values ​​corresponding to the different devices.

[0077] In this embodiment, after the data processing server processes the collected software and hardware data to obtain the device life values ​​corresponding to different devices, the health of the system can be determined according to the device life values ​​corresponding to different devices.

[0078] In an optional embodiment, this step S2300 determines the health of the system according to the device life values ​​corresponding to the different devices, and can further include: obtaining the weight values ​​corresponding to the different devices respectively; determining the health of the system according to the weight values ​​corresponding to the different devices and the device life values ​​corresponding to the different devices respectively.

[0079] The weight value of a device is related to the degree of downtime hazard of the device, so that devices that play a more important role in the system can have a stronger impact on the health of the system. Generally, the weight value of a device can be adjusted accordingly based on the historical failure rate of the device. It should be noted that corresponding weight values ​​can be set for different types of devices or different devices in the system.

[0080] Among them, the system health HS satisfies:

[0081]

[0082] In the above, n represents the number of devices, and H1 represents the weight value of device 1. represents the device health value of device 1, H2 represents the weight value of device 2, represents the device health value of device 2, H3 represents the weight value of device 3, Indicates the health value of device 3...H n Represents the weight value of device n, Indicates the device health value of device n.

[0083] Continuing with the above example, based on the weight value H1 of device 1 and the device health value of device 1 The weight value H2 of device 2 and the device health value of device 2 The weight value H3 of device 3 and the device health value of device 3 Get the health of the system

[0084] According to the embodiment of the present disclosure, it will count the software and hardware data of each device in the system, and obtain the device life value of the device based on the software and hardware data of the device, and obtain the health of the system based on the device life values ​​corresponding to different devices in the system. In other words, the sampled data includes software data and hardware data. The device life value of the device can be obtained based on the software and hardware data of a single device, and the health of the entire system can be obtained based on the device life values ​​corresponding to different devices. In this way, the life status of different devices and the life form of the entire system can be known.

[0085] In one embodiment, after executing the above step S2300 to determine the health of the system according to the device life values ​​corresponding to the different devices, the information determination method of the embodiment of the present disclosure further includes:

[0086] Establishing first mapping data reflecting the correspondence between time and the device life value of the device; and establishing second mapping data reflecting the correspondence between time, the device life value corresponding to at least one of the different devices, and the health of the system.

[0087] The first mapping data may be a first mapping curve, referring to Figure 3 The first mapping curve is located in a two-system coordinate system that reflects the corresponding relationship between time X and device life value Y. There is a corresponding relationship between the first mapping data and the device, for example, one device corresponds to one first mapping data, that is, the first mapping data is usually multiple.

[0088] The second mapping data may be a second mapping curve, referring to Figure 4 , the second mapping curve is located in a three-system coordinate system reflecting the corresponding relationship between time X, device life value Y corresponding to at least one device in different devices, and system health Z. It can be understood that the second mapping data is usually one. The at least one device is usually a key device among different devices, and can also be understood as a device that can strongly affect the health of the system.

[0089] In this embodiment, the data processing server records the time and the device life value of the device into the corresponding two-system coordinate system, and records the time, the device life value corresponding to at least one device, and the health of the system into the three-system coordinate system, and transmits the coordinate system point information to the logic processing server. The logic server reprocesses and models to obtain the second mapping data and the first mapping data of the device and transmits them to the client. The client displays the first mapping data and the second mapping data, and the user can see the full life status of the system and the full life status of the device.

[0090] In one embodiment, after executing the above steps to establish the first mapping data reflecting the correspondence between the time and the device life value of the device, the information determination method of the embodiment of the present disclosure further includes the following steps S3100 to S3300:

[0091] Step S3100, obtaining the critical life value of the device.

[0092] Among them, the critical life value of the device can be set according to the actual application scenario, and this embodiment does not limit this.

[0093] Step S3200, determining whether the device will fail in the future based on the critical life value.

[0094] In this embodiment, the budget server can determine whether the device will fail in the future based on the critical life value of the device. For example, if the future life value of the device is close to the critical life value, it indicates that the device is in a healthy or sub-healthy state, and it can be processed or not according to the actual situation. For another example, if the future life value of the device is constantly approaching the critical life value, it indicates that the device is in a critical state and needs to be processed.

[0095] Step S3300: When it is determined that the device will fail in the future, estimate the time when the device will fail in the future according to the first mapping data and the future life value of the device.

[0096] In this embodiment, when the device is in a critical state and needs to be processed, the budget server will use reverse thinking to perform coordinate mapping to infer the x value in the coordinate system based on the first mapping data f=(x, y) corresponding to the device and the future life value y of the device. The x value will be infinitely close to the real x value with each fluctuation. The x value obtained at this time is the real hypothetical value. If the x value is N, it can be determined that the device will most likely fail N days in the future, and relevant personnel are required to check or handle it N days in advance.

[0097] At the same time, the budget server will also pass the budget results to the client, and the client will convert the budget results into visual charts to inform and remind the user.

[0098] In one embodiment, after executing the above steps to establish the second mapping data reflecting the correspondence between the time, the device life value corresponding to at least one of the different devices, and the health of the system, the information determination method of the embodiment of the present disclosure further includes the following steps S4100 to S4300:

[0099] Step S4100, obtaining the critical health of the system and the critical life value corresponding to the at least one device.

[0100] The critical health of the system may be set according to actual application scenarios, which is not limited in this embodiment.

[0101] Step S4200, determining whether the system will fail in the future based on the critical health and the critical life value corresponding to the at least one device.

[0102] In this embodiment, the budget server can determine whether the system will fail in the future based on the critical health of the system and the critical life value corresponding to at least one device. For example, if the future health of the system is close to the critical health, and the future life value of at least one device is close to its corresponding critical life value, it indicates that the system is in a healthy or sub-healthy state, and it can be processed or not according to the actual situation. For another example, if the future health of the system is constantly approaching the critical health, and the future life value of at least one device is constantly approaching its corresponding critical life value, it indicates that the system is in a critical state and needs to be processed.

[0103] Step S4300, when it is determined that the system will fail in the future, estimate the time when the system will fail in the future according to the second mapping data, the future health of the system and the at least one corresponding future life value.

[0104] In this embodiment, when the system is in a critical state and needs to be processed, the budget server will use reverse thinking to perform coordinate mapping to infer the x value in the coordinate system based on the second mapping data f=(x, y, z) and the future health z of the system and the future life value y corresponding to at least one device. The x value will be infinitely close to the real x value with each fluctuation. The x value obtained at this time is the real hypothetical value. If the x value is N, it can be determined that the system will most likely fail N days in the future, and relevant personnel are required to check or handle it N days in advance.

[0105] At the same time, the budget server will also pass the budget results to the client, and the client will convert the budget results into visual charts to inform and remind the user.

[0106] It should be noted that, on the one hand, the existing technology focuses on components, that is, hardware, and mainly detects the life state of hardware. The embodiment of the present disclosure focuses on the life state of the entire device and the life form of the entire system, which is sampled from different data samples, including software data and hardware data, so that the data samples can be used for the final life form calculation or prediction later.

[0107] On the other hand, the embodiments of the present disclosure obtain the life cycle of a system or device through data accumulation and calculation, and can predict through data reverse reasoning whether the system or device will fail or alarm at some time in the future, and provide early warning and maintenance.

[0108] <Device Example>

[0109] The present disclosure also provides an information determination device 500, such as Figure 5 As shown, the information determination device 500 includes an acquisition module 510 , a first determination module 520 and a second determination module 530 .

[0110] An acquisition module 510 is used to acquire software and hardware data corresponding to different devices;

[0111] A first determination module 520, configured to determine device life values ​​corresponding to the different devices respectively according to the software and hardware data corresponding to the different devices respectively;

[0112] The second determination module 530 is used to determine the health of the system according to the device life values ​​corresponding to the different devices.

[0113] In one embodiment, the software and hardware data includes software data and hardware data.

[0114] The hardware data includes at least one of the following: daily parameter monitoring data, abnormal fluctuation monitoring data, fault statistics data, and alarm statistics data;

[0115] The software data includes at least one of the following: CPU fluctuation range, disk occupancy range, memory fluctuation range, process enablement status, application enablement status, port occupancy status, fault statistics data, and alarm statistics data.

[0116] In one embodiment, the first determination module 520 is specifically used to determine the event occurrence rate corresponding to each event of the device according to the software and hardware data of the device and the weight value corresponding to each event of the device; determine the life coefficient of the device according to the event occurrence rate corresponding to each event and the device parameters of the device; determine the device life value of the device according to the life coefficient of the device.

[0117] In one embodiment, the second determination module 520 is specifically used to obtain weight values ​​corresponding to the different devices respectively; and determine the health of the system according to the weight values ​​corresponding to the different devices respectively and the device life values ​​corresponding to the different devices respectively.

[0118] In one embodiment, the apparatus 500 further includes a first establishing module (not shown in the figure).

[0119] The first establishing module is used to establish first mapping data reflecting the corresponding relationship between time and the device life value of the device.

[0120] In one embodiment, the apparatus 500 further includes a third determination module and a first estimation module (neither of which are shown in the figure).

[0121] The acquisition module 510 is further used to obtain the critical life value of the device;

[0122] A third determination module is used to determine whether the device will fail in the future according to the critical life value; and

[0123] The first estimation module is used to estimate the time when the device will fail in the future according to the first mapping data and the future life value of the device when it is determined that the device will fail in the future.

[0124] In one embodiment, in one embodiment, the apparatus 500 further includes a second establishing module (not shown in the figure).

[0125] The second establishing module is used to establish second mapping data reflecting the corresponding relationship between time, the device life value corresponding to at least one device among the different devices, and the health of the system.

[0126] In one embodiment, the apparatus 500 further includes a fourth determination module and a second estimation module (neither shown in the figure).

[0127] The acquisition module 510 is further used to acquire the critical health of the system and the critical life value corresponding to the at least one device;

[0128] a fourth determination module, configured to determine whether the system will fail in the future based on the critical health and the critical life value corresponding to the at least one device; and

[0129] The second estimation module is used to estimate the time when the system will fail in the future based on the second mapping data, the future health of the system and the at least one corresponding future life value when it is determined that the system will fail in the future.

[0130] According to the embodiment of the present disclosure, it will count the software and hardware data of each device in the system, and obtain the device life value of the device based on the software and hardware data of the device, and obtain the health of the system based on the device life values ​​corresponding to different devices in the system. In other words, the sampled data includes software data and hardware data. The device life value of the device can be obtained based on the software and hardware data of a single device, and the health of the entire system can be obtained based on the device life values ​​corresponding to different devices. In this way, the life status of different devices and the life form of the entire system can be known.

[0131] <Electronic equipment>

[0132] In this embodiment, an electronic device 600 is also provided. Figure 6 As shown, a memory 620 and a processor 610 are included.

[0133] The memory 620 is used to store an executable computer program; the computer program is used to control the processor 610 to execute any one of the information determination methods provided in this embodiment.

[0134] In this embodiment, the electronic device 600 may be Figure 1 The electronic device 1000 shown may also be a device with other hardware structures, which is not limited here.

[0135] In another embodiment, the electronic device 600 may include the above information determining device 500 .

[0136] <Computer Readable Storage Medium>

[0137] In this embodiment, a computer-readable storage medium is further provided, on which a computer program is stored. When the computer program is executed by a processor, the information determination method of any embodiment of the present disclosure is implemented.

[0138] The present invention may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present invention.

[0139] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0140] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0141] The computer program instructions for performing the operation of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present invention.

[0142] Various aspects of the present invention are described herein with reference to the flow charts and / or block diagrams of the methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each box of the flow chart and / or block diagram and the combination of each box in the flow chart and / or block diagram can be implemented by computer-readable program instructions.

[0143] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0144] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0145] The flow charts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a part of a module, a program segment or an instruction, and a part of the module, a program segment or an instruction contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that it is equivalent to implement it by hardware, implement it by software, and implement it by combining software and hardware.

[0146] Embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The choice of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements to the technology in the marketplace, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the present invention is defined by the appended claims.

Claims

1. A method for determining information, characterized in that: The method comprises: Get the software and hardware data corresponding to different devices; Determine the device life values ​​corresponding to the different devices respectively according to the software and hardware data corresponding to the different devices respectively; The health of the system is determined according to the device life values ​​corresponding to the different devices.

2. The method according to claim 1, characterized in that The software and hardware data include software data and hardware data. The hardware data includes at least one of the following: daily parameter monitoring data, abnormal fluctuation monitoring data, fault statistics data, and alarm statistics data; The software data includes at least one of the following: CPU fluctuation range, disk occupancy range, memory fluctuation range, process enablement status, application enablement status, port occupancy status, fault statistics data, and alarm statistics data.

3. The method according to claim 1, characterized in that Determining the device life value of the device according to the software and hardware data of the device, including: Determine the event occurrence rates corresponding to the events of the device according to the hardware and software data of the device and the weight values ​​corresponding to the events of the device; Determining the life coefficient of the device according to the event occurrence rates corresponding to the events and the device parameters of the device; The device life value of the device is determined according to the life coefficient of the device.

4. The method according to claim 1, characterized in that: The determining the health of the system according to the device life values ​​corresponding to the different devices respectively includes: Obtaining weight values ​​corresponding to the different devices respectively; The health of the system is determined according to the weight values ​​respectively corresponding to the different devices and the device life values ​​respectively corresponding to the different devices.

5. The method according to claim 1, characterized in that The method further comprises: First mapping data reflecting the correspondence between time and the device life value of the device is established.

6. The method according to claim 5, characterized in that After establishing the first mapping data reflecting the correspondence between the time and the device life value of the device, the method further includes: Obtaining a critical life value of the device; determining, based on the critical life value, whether the device will fail in the future; In the case where it is determined that the device will fail in the future, the time when the device will fail in the future is estimated based on the first mapping data and the future life value of the device.

7. The method according to claim 1, characterized in that The method further comprises: Second mapping data reflecting the corresponding relationship between time, device life value corresponding to at least one of the different devices, and health of the system are established.

8. The method according to claim 7, characterized in that The method further comprises: Obtaining a critical health of the system and a critical life value corresponding to each of the at least one device; determining whether the system will fail in the future according to the critical health and the critical life value corresponding to the at least one device; When it is determined that the system will fail in the future, the time when the system will fail in the future is estimated according to the second mapping data, the future health of the system and the at least one corresponding future life value.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory is used to store an executable computer program; and the computer program is used to control the processor to execute the method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

Images