Equipment state self-adaptive control method and device

Abstract

The invention discloses an equipment state adaptive control method and device, and belongs to the technical field of equipment real-time state monitoring control, and the method comprises the steps: S100, obtaining a historical state data set, and obtaining a historical state feature factor in the historical state data set according to a state type; s200, obtaining a historical restart period based on the historical state characteristic factors in combination with the state type; s300, carrying out real-time state data acquisition and analysis on the target equipment to determine a real-time state type and a real-time state characteristic factor; s400, a historical state characteristic factor corresponding to the real-time state type is called, and a restart factor is determined through comparative analysis of the historical state characteristic factor and the real-time state characteristic factor; s500, correcting a historical restart period of the target equipment according to the restart factor to determine a target restart period, and executing restart operation by the target equipment in response to the target restart period; according to the invention, the problem of high equipment accident rate caused by the absence of a restart operation scheme for optimizing the equipment by sensing the real-time state of the equipment in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of real-time equipment status monitoring and control, and in particular to an equipment status adaptive control method and device. Background Art

[0002] With the improvement of the information level of power system, especially the increase in the proportion of image acquisition in the status information of electrical system, large-scale acquisition, storage, transmission, processing and other behaviors will amplify the abnormal working status or fault problems of related load hardware. At the same time, due to the large scale, the traditional operation and inspection mode that relies on manual experience and operation is stretched in the face of such a situation. Taking the hard disk recorder of image monitoring as an example, it often works in parallel with dozens of camera ports. When encountering abnormal conditions such as high temperature weather, it often leads to the loss of perception ability of the hard disk recorder, a large number of mechanical downtimes, and then a large number of cameras are offline, causing serious monitoring accidents. Furthermore, with the increasingly high requirements for online equipment assessment, as well as the serious lag in the informationization and intelligent technology of communication equipment operation and inspection, it is necessary to propose a restart operation plan optimized by the perception of the status of related equipment to ensure the long-term normal operation of the monitoring equipment and reduce the probability of accidents.

[0003] Chinese patent, publication number: CN114859781A, publication date: August 5, 2022, discloses a power supply management method and system for online monitoring equipment, including: when the online monitoring equipment is detected to be started, each module is controlled to be in a dormant state; every predetermined time, after the online monitoring equipment enters the detection state, the activation time corresponding to the detection module is obtained; the corresponding detection module is activated according to the activation time; after detecting that each detection module is activated, each detection module is controlled to enter a working state, and the non-detection module is controlled to continue to remain in a dormant state; after detecting that the detection of the online monitoring device is completed, each module is controlled to enter a dormant state; and the power supply management method and system for online monitoring equipment proposed in the invention, although it can control the startup and dormancy of the corresponding monitoring equipment according to the activation time, does not perceive the real-time state of the monitoring equipment to optimize the restart operation plan of the monitoring equipment, thereby failing to reduce the accident rate of the monitoring equipment. Summary of the invention

[0004] The purpose of the present invention is to address the problem that the prior art fails to optimize the restart operation plan of the device due to the lack of perception of the real-time status of the device, thereby failing to ensure the long-term normal operation of the device and reduce its accident rate; a device state adaptive control method and device are proposed, which obtains historical state characteristic factors and historical restart cycles through the state types in the device historical state data set, and simultaneously collects the real-time status data of the device for analysis to obtain the real-time status characteristic factors, and compares the real-time status characteristic factors with the historical status characteristic factors to determine the restart factors, and finally corrects the historical restart cycles according to the restart factors, and obtains the device restart operation plan optimized according to the real-time status of the device, which significantly reduces the accident rate of the device.

[0005] In a first aspect, a technical solution provided in an embodiment of the present invention is a method for adaptively controlling a device state, comprising the following steps: S100, obtaining a historical state data set of a target device, and obtaining a historical state characteristic factor in the historical state data set according to the state type; S200, obtaining a historical restart cycle of a corresponding target device based on a historical state characteristic factor combined with a state type; S300, collecting and analyzing real-time status data of the target device to determine the real-time status type and real-time status characteristic factor of the target device; S400, retrieve the historical state characteristic factors in the corresponding historical state data set according to the real-time state type, and determine the restart factor by comparing and analyzing the historical state characteristic factors and the real-time state characteristic factors; S500: Modify a historical reboot cycle of a target device according to a reboot factor to determine a target reboot cycle, and the target device performs a reboot operation in response to the target reboot cycle.

[0006] In this solution, a historical status data set of the target device is obtained, and historical status characteristic factors in the historical status data set are obtained according to the status type. The historical status characteristic factors are screened based on the status type to provide more comprehensive and accurate historical data support for subsequent analysis, making the analysis more accurate and efficient. Then, the historical restart cycle of the corresponding target device is obtained according to the historical status characteristic factors combined with the status type to understand the restart requirements of the target device under different states, providing a basis for optimizing the restart operation plan of the target device. The real-time status data of the target device is collected and analyzed to determine the real-time status type and real-time status characteristic factors of the target device, accurately judge the current state of the target device, and obtain the status of the target device according to the real-time status characteristic factors corresponding to the real-time state of the target device. state type, effectively improving the planning efficiency of the restart operation plan; after the real-time state characteristic factor is determined, the historical state characteristic factor in the corresponding historical state data set is retrieved according to the real-time state type, and the corresponding relationship between the historical state characteristic factor and the real-time state characteristic factor is established using the real-time state type as a bridge, and the historical state characteristic factor and the real-time state characteristic factor with the corresponding relationship are compared and analyzed to determine the restart factor, and the correlation between the real-time state and the historical state of the target device is found; finally, the historical restart cycle of the target device is corrected according to the restart factor to determine the target restart cycle, and the device restart operation plan optimized according to the real-time state of the device is obtained, and the target device performs the restart operation in response to the target restart cycle, which significantly reduces the accident rate of the device.

[0007] Preferably, in S100, the specific process of obtaining the historical state data set of the target device and obtaining the historical state characteristic factor in the historical state data set according to the state type is: S111, obtaining historical status data of the target device and corresponding historical environment data and historical operation data, and constructing a historical status data set according to the status data, environment data and operation data; S112, extracting state features of the historical state data set to determine the state type; S113, performing correlation analysis on the historical environment data and historical operation data corresponding to the state characteristics to determine the historical state characteristic factors; Among them, the historical state characteristic factor characterizes the degree of correlation between the state type and the historical environmental data and the historical operation data. The historical environmental data at least includes the ambient temperature index, the equipment surface temperature index, and the equipment dust accumulation index. The historical operation data at least includes the hardware operation index, the software operation index, and the network operation index.

[0008] In this solution, the historical status data obtained is the historical operation data of the target device containing multi-dimensional information. In addition to the operation changes of the target device itself, there are also changes in the working environment. Comprehensive and integrated consideration is given to the reasons that may affect the abnormal operation of the target device and require restarting. The status type is determined according to the status characteristics, and the data of the abnormal state of the target device in the historical status data and the reasons causing the abnormality are subdivided. The operation status of the target device is classified in combination with the data at the time of the abnormality. Finally, based on the divided abnormal type data, the environmental data and operation data in the same abnormal type data are analyzed using the correlation analysis method, and the relationship between the environmental data affecting the operation data and ultimately causing the target device to work abnormally is obtained, and this relationship is determined as the historical status characteristic factor.

[0009] Preferably, in S200, the specific process of obtaining the historical restart cycle of the corresponding target device based on the historical state characteristic factor combined with the state type is: S211, using the historical state characteristic factor and the state type to filter the historical state data of the target device to obtain characteristic historical operation data; S212: Perform a time series analysis on the characteristic historical operation data to determine a historical restart cycle of the target device.

[0010] In this solution, the historical status data corresponding to the abnormal working status of the target device is first obtained by status type screening, and then the historical status data corresponding to the abnormal working status of the target device is screened by historical status characteristic factors, that is, the mutual influence relationship between different types of data in the historical status data, to obtain characteristic historical operation data associated with the historical restart operation of the target device, and perform time series analysis on the characteristic historical operation data to observe the time series changes of related status data under abnormal conditions to determine the historical restart cycle of the target device.

[0011] Preferably, in S300, the specific process of collecting and analyzing the real-time status data of the target device to determine the real-time status type and the real-time status characteristic factor of the target device is: S311, collecting real-time status data of the target device, as well as real-time environment data and real-time operation data corresponding to the real-time status data, and constructing a real-time status data set according to the real-time status data, the real-time environment data and the real-time operation data; S312, performing status diagnosis of the target device based on the real-time status data set combined with preset real-time status standard conditions, and determining the real-time status type of the target device; S313: Perform correlation analysis on the real-time environment data and the real-time operation data corresponding to the real-time status type to obtain a real-time status characteristic factor.

[0012] In this solution, the real-time operation data, real-time environment data and real-time status data of the target device are collected in multiple dimensions, and a real-time status data set is constructed using these three types of data; at the same time, based on the real-time status data set combined with preset real-time status standard conditions, the status diagnosis of the target device is performed to determine the real-time status type of the target device, judge the real-time operation status of the target device, and find out the abnormal real-time working status of the target device; finally, a correlation analysis is performed on the real-time environment data and real-time operation data corresponding to the real-time status type to obtain the mutual influence relationship between the real-time environment data and the real-time operation data, and this relationship is determined as the real-time status characteristic factor.

[0013] Preferably, in S400, the specific process of retrieving the historical state characteristic factor in the corresponding historical state data set according to the real-time state type is: S411, retrieve the state type in the historical state data set, and the historical state characteristic factor corresponding to the state type; S412, perform similarity analysis on the real-time state type and the state type in the historical state data set to obtain a similar state type data set; S413: Match the historical state characteristic factors corresponding to the state types in the similar state type data set with the real-time state types to obtain the historical state characteristic factors corresponding to the real-time state types.

[0014] In this scheme, a similarity analysis is performed on the real-time state type and the state type in the historical state data set to obtain a similarity relationship between the real-time state type and the historical state type, and the real-time state type and the historical state type are classified into similar types according to the similarity relationship to establish a similar state type data set. At the same time, the historical state feature factors corresponding to the real-time state type and the historical state type are established to correspond to each other according to the similarity relationship, that is, the real-time state and historical state feature factors are matched.

[0015] Preferably, in S400, the specific process of determining the restart factor by comparing and analyzing the historical state characteristic factor and the real-time state characteristic factor is as follows: S421, establishing a corresponding relationship between the historical state factor and the real-time state factor according to the real-time state type; S422: Compare and analyze the real-time status factor with the corresponding historical status factor to obtain a comparison relationship between the real-time status factor and the historical status factor, and determine a restart factor according to the comparison relationship.

[0016] In this solution, the real-time status type can be used as an intermediate medium to link the historical status factor with the real-time status factor, and obtain the corresponding relationship between the historical status factor and the real-time status factor. According to the corresponding relationship, the real-time status factor is compared and analyzed with the corresponding historical status factor to obtain the similarities and differences between the real-time status factor and the historical status factor, and finally the restart factor is determined according to the differences and similarities.

[0017] Preferably, in S500, the specific process of correcting the historical restart period of the target device according to the restart factor to determine the target restart period is: S511, determining a restart node of the target device on a unit time scale based on the restart factor, and extracting a historical restart node on a unit time scale in a historical restart cycle of the target device; S512, adjusting the historical restart node according to the restart node; S513: Modify the historical restart cycle based on the adjusted historical restart node, and determine the modified historical restart cycle as the target restart cycle.

[0018] In this scheme, after using the restart factor to determine the restart node of the target device on a unit time scale, the restart node is used to adjust the historical restart node to obtain the accurate restart operation node of the target device. At the same time, based on the adjusted historical restart node, the historical restart cycle is corrected to make the historical restart cycle more consistent with the real-time operating status of the target device, and the restart operation required for the target device in the current state, that is, the target restart cycle, is obtained.

[0019] On the other hand, a technical solution also provided in an embodiment of the present invention is a device state adaptive control device, comprising: Intelligent control module, data acquisition module, power control module, data storage module, analysis cycle module, and monitoring alarm module; The control end of the intelligent control module is electrically connected to the controlled end of the power control module; The collection end of the data collection module is electrically connected to the first collection end of the data storage module; The first collecting end of the data storage module is electrically connected to the collecting end of the analysis cycle module, and the second collecting end of the data storage module is electrically connected to the first collecting end of the monitoring alarm module; The collecting end of the analysis cycle module is electrically connected to the second collecting end of the monitoring alarm module; The data transmission end of the monitoring and alarm module is electrically connected to the data receiving end of the intelligent control module, and the collection end of the monitoring and alarm module is electrically connected to the second collection end of the data storage module.

[0020] In this solution, the intelligent control module is used to plan the restart operation of the target device to determine the target restart cycle; the data acquisition module collects the real-time operation data of the target device according to the preset cycle; the power control module controls the target device to perform the restart operation in combination with the instructions issued by the intelligent control module; the data storage module is used to store the data involved in the restart operation of the target device; the analysis cycle module is used to analyze the historical status data of the target device to obtain the internal characteristics and relationships between the continuous data; the monitoring and alarm module is used to analyze the real-time operation data of the target device, obtain the working status of the target device and analyze the relationship between the data causing the abnormal status of the target device and the real-time data, as well as the internal characteristic relationship between the real-time data and the historical data, and perform alarm operations according to the analysis results.

[0021] Preferably, the analysis cycle module comprises: a data analysis unit and a cycle analysis unit; The collection end of the data analysis unit serves as the collection end of the analysis cycle module, and the collection end of the data analysis unit is electrically connected to the collection end of the cycle analysis unit; The collection end of the cycle analysis unit serves as the collection end of the analysis cycle module.

[0022] Preferably, the monitoring and alarm module comprises: an equipment monitoring unit and an abnormality alarm unit; The first collection end of the equipment monitoring unit serves as the first collection end of the monitoring alarm module, the second collection end of the equipment monitoring unit serves as the second collection end of the monitoring alarm module, and the collection end of the equipment monitoring unit is electrically connected to the collection end of the abnormal alarm unit; The data transmission end of the abnormal alarm unit serves as the data transmission end of the monitoring alarm module, and the collection end of the abnormal alarm unit serves as the collection end of the monitoring alarm module.

[0023] The present invention has at least the following substantial effects: This application obtains a historical status data set of the target device, obtains historical status characteristic factors in the historical status data set according to the status type, and screens the historical status characteristic factors based on the status type to provide more comprehensive and accurate historical data support for subsequent analysis, making the analysis more accurate and efficient; then, the historical restart cycle of the corresponding target device is obtained according to the historical status characteristic factors combined with the status type, the restart requirements of the target device under different states are understood, and a basis is provided for optimizing the restart operation plan of the target device; and the real-time status data of the target device is collected for analysis to determine the real-time status type and real-time status characteristic factors of the target device, so as to accurately judge the current state of the target device, and the status of the target device is obtained according to the real-time status characteristic factors corresponding to the real-time state of the target device. state type, effectively improving the planning efficiency of the restart operation plan; after the real-time state characteristic factor is determined, the historical state characteristic factor in the corresponding historical state data set is retrieved according to the real-time state type, and the corresponding relationship between the historical state characteristic factor and the real-time state characteristic factor is established using the real-time state type as a bridge, and the historical state characteristic factor and the real-time state characteristic factor with the corresponding relationship are compared and analyzed to determine the restart factor, and the correlation between the real-time state and the historical state of the target device is found; finally, the historical restart cycle of the target device is corrected according to the restart factor to determine the target restart cycle, and the device restart operation plan optimized according to the real-time state of the device is obtained, and the target device performs the restart operation in response to the target restart cycle, which significantly reduces the accident rate of the device. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Other features, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention. Also, the same reference symbols are used throughout the drawings to represent the same parts.

[0025] Figure 1 This is a flow chart of a device state adaptive control method of the present invention; Figure 2 This is a structural diagram of a device state adaptive control device of the present invention. DETAILED DESCRIPTION

[0026] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0027] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) therein can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the drawings; the process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0028] Embodiment 1: like Figure 1 As shown, this embodiment provides a device state adaptive control method, including the following steps: S100: Obtain a historical status data set of a target device, and obtain a historical status characteristic factor in the historical status data set according to a status type.

[0029] In one embodiment, in order to obtain the historical state characteristic factor, this embodiment adopts a state type scheme, which specifically includes the following steps: S111, obtaining historical status data of the target device and corresponding historical environment data and historical operation data, and constructing a historical status data set according to the status data, environment data and operation data; S112, extracting state features of the historical state data set to determine the state type; S113, performing correlation analysis on the historical environment data and historical operation data corresponding to the state characteristics to determine the historical state characteristic factors; Among them, the historical state characteristic factor characterizes the degree of correlation between the state type and the historical environmental data and the historical operation data. The historical environmental data at least includes the ambient temperature index, the equipment surface temperature index, and the equipment dust accumulation index. The historical operation data at least includes the hardware operation index, the software operation index, and the network operation index.

[0030] In this embodiment, the status types include normal operation, downtime, and stopped operation, etc. The historical status characteristic factors are factors affecting the working status of the target device obtained by analyzing historical environmental data and historical operation data, which at least include temperature, humidity, etc.

[0031] S200: Acquire a historical restart cycle of a corresponding target device based on a historical status characteristic factor combined with a status type.

[0032] In one embodiment, in order to obtain the historical restart cycle of the target device, this embodiment adopts a historical state characteristic factor solution, which specifically includes the following steps: S211, using the historical state characteristic factor and the state type to filter the historical state data of the target device to obtain characteristic historical operation data; S212: Perform a time series analysis on the characteristic historical operation data to determine a historical restart cycle of the target device.

[0033] In this embodiment, the historical status data of the target device is filtered by using historical status characteristic factors and status types to obtain characteristic historical operation data, which is specifically the historical operation data corresponding to the abnormal working status of the target device. The data changes reflect the changes in the working status of the target device when encountering abnormal situations. The characteristic historical operation data is subjected to time series analysis to obtain the restart operation process of the target device, and then the historical restart cycle of the target device is determined.

[0034] S300: Collect and analyze real-time status data of the target device to determine the real-time status type and real-time status characteristic factors of the target device.

[0035] In one embodiment, in order to obtain the real-time status type and real-time status characteristic factor of the target device, this embodiment adopts a real-time status data collection and analysis solution, which specifically includes the following steps: S311, collecting real-time status data of the target device, as well as real-time environment data and real-time operation data corresponding to the real-time status data, and constructing a real-time status data set according to the real-time status data, the real-time environment data and the real-time operation data; S312, performing status diagnosis of the target device based on the real-time status data set combined with preset real-time status standard conditions, and determining the real-time status type of the target device; S313: Perform correlation analysis on the real-time environment data and the real-time operation data corresponding to the real-time status type to obtain a real-time status characteristic factor.

[0036] In this embodiment, the preset real-time status standard conditions need to be set according to the real-time status data, that is, the real-time status standard conditions of the target device need to be differentiated according to the type of abnormal working state of the target device and the cause thereof when setting. For example, when the target device is in an abnormal temperature state, the real-time status standard conditions can be set to a temperature range.

[0037] S400: Retrieve historical state characteristic factors from a corresponding historical state data set according to the real-time state type, and determine a restart factor by comparing and analyzing the historical state characteristic factors and the real-time state characteristic factors.

[0038] In one embodiment, in order to establish the connection between historical data and real-time data, this embodiment adopts a similarity analysis scheme, which specifically includes the following steps: S411, retrieve the state type in the historical state data set, and the historical state characteristic factor corresponding to the state type; S412, perform similarity analysis on the real-time state type and the state type in the historical state data set to obtain a similar state type data set; S413: Match the historical state characteristic factors corresponding to the state types in the similar state type data set with the real-time state types to obtain the historical state characteristic factors corresponding to the real-time state types.

[0039] In this embodiment, a similarity analysis is performed on the real-time status type and the historical status type, and a connection is established between the real-time status of the target device and the same status in the historical work. At the same time, based on the connection between the historical status type and the historical status characteristic factor, a connection is established between the real-time status type and the historical status characteristic factor, that is, the historical status characteristic factor corresponding to the status type in the similar status type data set is matched with the real-time status type.

[0040] In one embodiment, in order to obtain the restart factor, this embodiment adopts a comparative analysis scheme, which specifically includes the following steps: S421, establishing a corresponding relationship between the historical state factor and the real-time state factor according to the real-time state type; S422: Compare and analyze the real-time status factor with the corresponding historical status factor to obtain a comparison relationship between the real-time status factor and the historical status factor, and determine a restart factor according to the comparison relationship.

[0041] In this embodiment, a correspondence between historical status factors and real-time status factors is established through real-time status types, and the historical status factors with corresponding relationships are compared and analyzed with the real-time status factors. The similarities and differences between the historical status factors and the real-time status factors are analyzed, which are mainly reflected in the data affecting the working status of the target device, and the restart factor is determined based on the similarities and differences.

[0042] S500: Modify a historical reboot cycle of a target device according to a reboot factor to determine a target reboot cycle, and the target device performs a reboot operation in response to the target reboot cycle.

[0043] In one embodiment, in order to determine the target restart period, this embodiment adopts a restart factor to correct the historical restart period solution, which specifically includes the following steps: S511, determining a restart node of the target device on a unit time scale based on the restart factor, and extracting a historical restart node on a unit time scale in a historical restart cycle of the target device; S512, adjusting the historical restart node according to the restart node; S513: Modify the historical restart cycle based on the adjusted historical restart node, and determine the modified historical restart cycle as the target restart cycle.

[0044] In this embodiment, according to the change of the data corresponding to the restart factor, the time node at which the target device performs a restart operation within a unit time is determined, and the restart node and the historical restart node are correspondingly extracted. At the same time, the restart node is used to adjust the historical restart node, add, delete, and replace the historical restart node, and the adjusted historical restart node is used to correct the historical restart cycle to obtain a target restart cycle that matches the real-time status of the target device.

[0045] like Figure 2 As shown, a technical solution also provided in an embodiment of the present invention is a device state adaptive control device, comprising: Intelligent control module, data acquisition module, power control module, data storage module, analysis cycle module, and monitoring alarm module; The control end of the intelligent control module is electrically connected to the controlled end of the power control module; The collection end of the data collection module is electrically connected to the first collection end of the data storage module; The first collecting end of the data storage module is electrically connected to the collecting end of the analysis cycle module, and the second collecting end of the data storage module is electrically connected to the first collecting end of the monitoring alarm module; The collecting end of the analysis cycle module is electrically connected to the second collecting end of the monitoring alarm module; The data transmission end of the monitoring and alarm module is electrically connected to the data receiving end of the intelligent control module, and the collection end of the monitoring and alarm module is electrically connected to the second collection end of the data storage module.

[0046] In this embodiment, the data acquisition module collects real-time data of the target device according to a preset acquisition cycle, and the preset acquisition cycle needs to be set according to the specific working environment of the target device, the type of data collected, etc.; the power control module is a DSP-based intelligent power control unit, which is deployed in the power supply module of the target device, and the intelligent power control unit is used as an intelligent power strip of the hard disk recorder.

[0047] In one embodiment, the analysis cycle module includes: a data analysis unit and a cycle analysis unit, specifically: the collection end of the data analysis unit serves as the collection end of the analysis cycle module, and the collection end of the data analysis unit is electrically connected to the collection end of the cycle analysis unit; The collection end of the cycle analysis unit serves as the collection end of the analysis cycle module.

[0048] In one embodiment, the monitoring alarm module includes: a device monitoring unit and an abnormal alarm unit, specifically: the first collection end of the device monitoring unit serves as the first collection end of the monitoring alarm module, the second collection end of the device monitoring unit serves as the second collection end of the monitoring alarm module, and the collection end of the device monitoring unit is electrically connected to the collection end of the abnormal alarm unit; The data transmission end of the abnormal alarm unit serves as the data transmission end of the monitoring alarm module, and the collection end of the abnormal alarm unit serves as the collection end of the monitoring alarm module.

[0049] To further explain this embodiment in detail, a hard disk video recorder is used as a target device for explanation: First of all, it is clear that the causes of DVR downtime are overheating, software problems, and network transmission problems; the causes of DVR overheating may be hardware problems, power problems, etc., among which hardware problems may also be related to the manufacturer or model of the DVR, and power problems may be related to unstable power supply or poor power quality; the software problem may be caused by the upgrade of the application system, etc., which leads to the downtime of the DVR; the network transmission problem is the downtime caused by software induced by network failure or data transmission error; therefore, based on the surface temperature and working environment temperature of the DVR, software version, hardware model, equipment supplier, power supply stability index, data communication performance index, radiator working status, software performance index, and equipment dust accumulation degree, etc., research and analysis are conducted to extract the characteristic factors that cause the target equipment to downtime, namely the state characteristic factors, and then the operating data corresponding to the state characteristic factors are analyzed to obtain the set period for automatic restart operation of the target equipment, namely the target restart period.

[0050] Analyze the operating data corresponding to the status characteristic factors, reduce the amount of data calculation and improve calculation efficiency while ensuring the accuracy of the set period setting; in the hard disk recorder, it is specifically manifested as follows: according to the analysis, if the hard disk recorder will naturally crash after working for 30 days, the set period will be set to 28 days, and the set period for automatic restart of the hard disk recorder can also be set in stages by quarter.

[0051] For the hard disk video recorder, in addition to controlling the power supply to perform a forced restart operation, an SDK data port can also be set on the target device. The SDK data port is developed based on the E language program to realize the soft start of the hard disk management at a certain moment, that is, the program-controlled soft restart; the hard disk video recorder is quickly restored after the device automatically operates the preset program to restart, which greatly saves time, improves work efficiency, and enhances economic benefits. In addition, when the soft restart of the hard disk video recorder fails, the DSP-based intelligent power control unit deployed in the power supply module of the hard disk video recorder can be combined with a remotely controlled power distribution unit to achieve a forced restart.

[0052] In addition, the power stability indicators of the hard disk recorder include output stability, load stability, voltage drop stability, on-site vibration, component looseness, and aging; data communication performance indicators include data transmission rate, bandwidth and bit error rate; the working status of the radiator includes abnormal noise, operating failure, etc.; software performance indicators include CPU utilization, memory usage, and disk read and write speeds.

[0053] Secondly, for the convenience of calculation and to ensure that the amount of data is sufficient, this embodiment analyzes the multi-dimensional historical operation data of the hard disk recorder within one year, and extracts the characteristic factors that affect the working state of the hard disk recorder: overheating, radiator abnormality, software performance indicators, and the degree of dust accumulation in the environment and equipment; through the analysis of real-time operation data, it is possible to timely discover equipment abnormalities and send alarm information to the alarm receiving end, which is conducive to better carrying out equipment operation and maintenance work that is not limited to thermal shutdown; the alarm information includes: the heat dissipation of the equipment continues to be poor, and the heat dissipation needs to be strengthened; the equipment load continues to be too high, and adjustments need to be made to the task schedule; the environment temperature is too high at this time, it is recommended to stop working in time; there is a problem with the equipment hardware, it needs to be replaced in time, etc.

[0054] If it is determined during the analysis of the real-time running data that the hard disk video recorder needs to stop working, and after the hard disk video recorder stops working, the automatic restart timing of the hard disk video recorder is reset to zero, and the automatic restart timing is restarted after the hard disk video recorder is running again.

[0055] When the DVR crashes due to abnormal temperature, it is necessary to calculate the difference between the actual temperature and the preset temperature, as well as the duration that the actual temperature exceeds the preset temperature, and comprehensively consider the impact of continuous abnormal temperature operation on the DVR in addition to sudden high and low temperatures.

[0056] This embodiment has at least the following substantial effects: This embodiment obtains a historical status data set of the target device, obtains historical status characteristic factors in the historical status data set according to the status type, and screens the historical status characteristic factors based on the status type to provide more comprehensive and accurate historical data support for subsequent analysis, making the analysis more accurate and efficient; then, the historical restart cycle of the corresponding target device is obtained according to the historical status characteristic factors combined with the status type, the restart requirements of the target device under different states are understood, and a basis is provided for optimizing the restart operation plan of the target device; and the real-time status data of the target device is collected for analysis to determine the real-time status type and real-time status characteristic factors of the target device, so as to accurately judge the current state of the target device, and the status of the target device is obtained according to the real-time status characteristic factors corresponding to the real-time state of the target device. state type, effectively improving the planning efficiency of the restart operation plan; after the real-time state characteristic factor is determined, the historical state characteristic factor in the corresponding historical state data set is retrieved according to the real-time state type, and the corresponding relationship between the historical state characteristic factor and the real-time state characteristic factor is established using the real-time state type as a bridge, and the historical state characteristic factor and the real-time state characteristic factor with the corresponding relationship are compared and analyzed to determine the restart factor, and the correlation between the real-time state and the historical state of the target device is found; finally, the historical restart cycle of the target device is corrected according to the restart factor to determine the target restart cycle, and the device restart operation plan optimized according to the real-time state of the device is obtained, and the target device performs the restart operation in response to the target restart cycle, which significantly reduces the accident rate of the device.

[0057] The above specific embodiments are preferred embodiments of the present invention, and are not intended to limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to the present specific embodiments. All equivalent changes made in accordance with the shape, structure, and method of the present invention are within the protection scope of the present invention.

Claims

1. A device state adaptive control method, characterized in that: The following steps are involved: S100, obtaining a historical state data set of a target device, and obtaining a historical state characteristic factor in the historical state data set according to the state type; S200, obtaining a historical restart cycle of a corresponding target device based on a historical state characteristic factor combined with a state type; S300, collecting and analyzing real-time status data of the target device to determine the real-time status type and real-time status characteristic factor of the target device; S400, calling the historical state characteristic factor in the corresponding historical state data set according to the real-time state type, and determining the restart factor by comparing and analyzing the historical state characteristic factor and the real-time state characteristic factor; S500: Modify a historical reboot cycle of a target device according to a reboot factor to determine a target reboot cycle, and the target device performs a reboot operation in response to the target reboot cycle.

2. A device state adaptive control method according to claim 1, characterized in that: In S100, the specific process of obtaining the historical state data set of the target device and obtaining the historical state characteristic factors in the historical state data set according to the state type is as follows: S111, obtaining historical status data of the target device and corresponding historical environment data and historical operation data, and constructing a historical status data set according to the status data, environment data and operation data; S112, extracting state features of the historical state data set to determine the state type; S113, performing correlation analysis on the historical environment data and historical operation data corresponding to the state characteristics to determine the historical state characteristic factors; Among them, the historical state characteristic factor characterizes the degree of correlation between the state type and the historical environmental data and the historical operation data. The historical environmental data at least includes the ambient temperature index, the equipment surface temperature index, and the equipment dust accumulation index. The historical operation data at least includes the hardware operation index, the software operation index, and the network operation index.

3. The device state adaptive control method according to claim 1, characterized in that: In S200, the specific process of obtaining the historical restart cycle of the corresponding target device based on the historical state characteristic factor combined with the state type is: S211, using the historical state characteristic factor and the state type to filter the historical state data of the target device to obtain characteristic historical operation data; S212: Perform a time series analysis on the characteristic historical operation data to determine a historical restart cycle of the target device.

4. The device state adaptive control method according to claim 1, characterized in that: In S300, the specific process of collecting and analyzing the real-time status data of the target device to determine the real-time status type and real-time status characteristic factor of the target device is as follows: S311, collecting real-time status data of the target device, and real-time environment data and real-time operation data corresponding to the real-time status data, and constructing a real-time status data set according to the real-time status data, the real-time environment data and the real-time operation data; S312, performing status diagnosis of the target device based on the real-time status data set in combination with preset real-time status standard conditions to determine the real-time status type of the target device; S313: Perform correlation analysis on the real-time environment data and the real-time operation data corresponding to the real-time status type to obtain a real-time status characteristic factor.

5. The device state adaptive control method according to claim 1, characterized in that: In S400, the specific process of retrieving the historical state characteristic factor in the corresponding historical state data set according to the real-time state type is as follows: S411, retrieve the state type in the historical state data set, and the historical state characteristic factor corresponding to the state type; S412, performing similarity analysis on the real-time state type and the state type in the historical state data set to obtain a similar state type data set; S413: Match the historical state characteristic factors corresponding to the state types in the similar state type data set with the real-time state types to obtain the historical state characteristic factors corresponding to the real-time state types.

6. The device state adaptive control method according to claim 1, characterized in that: In S400, the specific process of determining the restart factor by comparing and analyzing the historical state characteristic factor and the real-time state characteristic factor is as follows: S421, establishing a corresponding relationship between the historical state factor and the real-time state factor according to the real-time state type; S422: Compare and analyze the real-time status factor with the corresponding historical status factor to obtain a comparison relationship between the real-time status factor and the historical status factor, and determine a restart factor according to the comparison relationship.

7. The device state adaptive control method according to claim 1, characterized in that: In S500, the specific process of modifying the historical restart period of the target device according to the restart factor to determine the target restart period is: S511, determining a restart node of the target device on a unit time scale based on the restart factor, and extracting a historical restart node on a unit time scale in a historical restart cycle of the target device; S512, adjusting the historical restart node according to the restart node; S513: Modify the historical restart cycle based on the adjusted historical restart node, and determine the modified historical restart cycle as the target restart cycle.

8. A device state adaptive control apparatus, applicable to a device state adaptive control method according to any one of claims 1 to 7, characterized in that: Included are: Intelligent control module, data acquisition module, power control module, data storage module, analysis cycle module, and monitoring alarm module; The control end of the intelligent control module is electrically connected to the controlled end of the power control module; The collection end of the data collection module is electrically connected to the first collection end of the data storage module; The first collecting end of the data storage module is electrically connected to the collecting end of the analysis cycle module, and the second collecting end of the data storage module is electrically connected to the first collecting end of the monitoring alarm module; The collecting end of the analysis cycle module is electrically connected to the second collecting end of the monitoring alarm module; The data transmission end of the monitoring and alarm module is electrically connected to the data receiving end of the intelligent control module, and the collection end of the monitoring and alarm module is electrically connected to the second collection end of the data storage module.

9. The device state adaptive control device according to claim 8, characterized in that: The analysis cycle module includes: a data analysis unit and a cycle analysis unit; The collection end of the data analysis unit serves as the collection end of the analysis cycle module, and the collection end of the data analysis unit is electrically connected to the collection end of the cycle analysis unit; The collection end of the cycle analysis unit serves as the collection end of the analysis cycle module.

10. The device state adaptive control device according to claim 8, characterized in that: The monitoring and alarm module includes: an equipment monitoring unit and an abnormal alarm unit; The first collection end of the equipment monitoring unit serves as the first collection end of the monitoring alarm module, the second collection end of the equipment monitoring unit serves as the second collection end of the monitoring alarm module, and the collection end of the equipment monitoring unit is electrically connected to the collection end of the abnormal alarm unit; The data transmission end of the abnormal alarm unit serves as the data transmission end of the monitoring alarm module, and the collection end of the abnormal alarm unit serves as the collection end of the monitoring alarm module.

Images