Equipment data correction method and device, equipment and storage medium

Abstract

The embodiment of the invention discloses an equipment data correction method and device, equipment and a storage medium, and the method comprises the steps: obtaining initial equipment data of target equipment; determining a target data type corresponding to the initial device data; wherein the target data type comprises state type data and numeric type data; and performing data correction on the initial equipment data based on the target data type to obtain target equipment data. According to the technical scheme, the problems that in an existing data correction technology, data correction is mainly carried out based on a fixed interval or a fixed standard, data which dynamically changes in real time cannot be adapted, and the value and usability of finally-produced correction data are low are solved; the corresponding data correction strategy can be matched based on the data type of the equipment data, and the dynamic adaptability and authenticity of data correction are improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of data detection technology, and in particular, to a device data correction method, apparatus, device and storage medium. Background Art

[0002] In the mining positioning software system, it is necessary to connect to various types of equipment including positioning communication base stations, intelligent power supplies, environmental detection sensors, etc. The software system needs to monitor the operating status of each device in real time. If the equipment is abnormal, it is necessary to generate corresponding alarms and notify in time. Currently, the software system and the equipment communicate through the TCP protocol. After receiving the heartbeat and real-time status data of the equipment, the software system triggers data detection and generates corresponding alarms.

[0003] In the actual production process, equipment data is interfered by multiple factors, such as equipment aging, network signal fluctuations, etc., which lead to various abnormal data such as equipment heartbeat interruption and real-time data fluctuations. Moreover, such abnormal data cannot be predicted (such as duration, fluctuation range, etc.).

[0004] Existing solutions usually set the data sample interval based on experience, and use an agreed method to fix an interval or standard data to filter or correct the data. However, if the agreed interval or standard data cannot filter out abnormal data caused by environmental abnormalities, it will affect the efficiency of true state determination, thereby generating abnormal alarm notifications that mislead the production site and related maintenance personnel and cause production losses. Summary of the invention

[0005] The embodiments of the present invention provide a device data correction method, apparatus, device and storage medium. The technical solution of the embodiments of the present invention can match the corresponding data correction strategy based on the data type of the device data, thereby improving the dynamic adaptability and authenticity of the data correction.

[0006] In a first aspect, an embodiment of the present invention provides a method for correcting device data, the method comprising:

[0007] Acquire initial device data of a target device; determine a target data type corresponding to the initial device data; wherein the target data type includes: state data and numerical data; perform data correction on the initial device data based on the target data type to obtain the target device data.

[0008] In a second aspect, an embodiment of the present invention provides a device data correction apparatus, the apparatus comprising:

[0009] A data acquisition module is used to acquire the initial device data of the target device; a data type determination module is used to determine the target data type corresponding to the initial device data; wherein the target data type includes: state data and numerical data; a data correction module is used to correct the initial device data based on the target data type to obtain the target device data.

[0010] In a third aspect, an embodiment of the present invention provides a computer device, the computer device comprising:

[0011] one or more processors;

[0012] A memory for storing one or more programs;

[0013] When the one or more programs are executed by the one or more processors, the one or more processors implement the device data correction method described in any embodiment.

[0014] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the device data correction method described in any embodiment.

[0015] The technical solution provided by the embodiment of the present invention obtains the initial device data of the target device; determines the target data type corresponding to the initial device data; wherein the target data type includes: state data and numerical data; and performs data correction on the initial device data based on the target data type to obtain the target device data. The technical solution of the embodiment of the present invention solves the problem that the existing data correction technology mainly performs data correction based on a fixed interval or a fixed standard, which cannot adapt to real-time dynamically changing data, resulting in low value and availability of the final corrected data. The technical solution can match the corresponding data correction strategy based on the data type of the device data, thereby improving the dynamic adaptability and authenticity of the data correction. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flow chart of a device data correction method provided by an embodiment of the present invention;

[0017] Figure 2 is a flow chart of a method for correcting numerical data provided by an embodiment of the present invention;

[0018] Figure 3 is a flow chart of a method for correcting state data provided by an embodiment of the present invention;

[0019] Figure 4 This is a workflow diagram for performing device data correction provided by an embodiment of the present invention;

[0020] Figure 5 It is a structural schematic diagram of a device data correction apparatus provided by an embodiment of the present invention;

[0021] Figure 6 It is a structural schematic diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] Figure 1 It is a flow chart of a device data correction method provided by an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of correcting the production data of the device. The method can be executed by a device data correction device, and the device can be implemented by software and / or hardware.

[0024] like Figure 1 As shown, the device data correction method includes the following steps:

[0025] S110, obtaining initial device data of the target device.

[0026] The target device may be a device that needs to be tested and corrected for device data. The initial device data may be data about the real-time working status of the target device. For example, the operating status data of the target device may be collected based on a preset device collection device to obtain the initial device data.

[0027] S120: Determine the target data type corresponding to the initial device data.

[0028] Among them, the target data type can be the data type corresponding to the initial device data. Specifically, the target data type may include: state data and numerical data. Among them, the state data may be data used to indicate the normal or abnormal state of the device. For example, the state data may be 0 / 1 type data. Among them, the state of 0 indicates that the device is in a normal state, that is, a standard state; the state data of 1 indicates that the device is in an abnormal state, that is, a non-standard state. Furthermore, the value of the numerical data is not limited to 0 and 1, but a variety of values ​​within a certain range may appear. Exemplarily, the label information about the data type in the initial device data can be identified, and then the target data type corresponding to the initial device data can be determined based on the label information.

[0029] S130 , performing data correction on the initial device data based on the target data type to obtain target device data.

[0030] The target device data may be data obtained after data correction. Specifically, a correction strategy for the initial device data may be determined based on the target data type, and then the initial device data may be corrected based on the correction strategy to obtain the target device data.

[0031] The technical solution provided by the embodiment of the present invention obtains the initial device data of the target device; determines the target data type corresponding to the initial device data; wherein the target data type includes: state data and numerical data; and performs data correction on the initial device data based on the target data type to obtain the target device data. The technical solution of the embodiment of the present invention solves the problem that the existing data correction technology mainly performs data correction based on a fixed interval or a fixed standard, which cannot adapt to real-time dynamically changing data, resulting in low value and availability of the final corrected data. The technical solution can match the corresponding data correction strategy based on the data type of the device data, thereby improving the dynamic adaptability and authenticity of the data correction.

[0032] Figure 2 It is a flow chart of a method for correcting numerical data provided by an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of correcting the production data of the equipment. Based on the above embodiment, this embodiment further illustrates how to correct the initial equipment data based on the target data type to obtain the target equipment data when the target data type is numerical data. The device can be implemented by software and / or hardware and integrated in a computer device with application development function.

[0033] like Figure 2 As shown, the device data correction method includes the following steps:

[0034] S210: Acquire initial device data of a target device, and determine a target data type corresponding to the initial device data.

[0035] The target device may be a device that needs to be tested and corrected for device data. The initial device data may be data about the real-time working status of the target device. For example, the operating status data of the target device may be collected based on a preset device collection device to obtain the initial device data. The target data type may be a data type corresponding to the initial device data. Specifically, the target data type may include: state data and numerical data. The state data may be data used to indicate a normal or abnormal state of the device. For example, the state data may be 0 / 1 type data. A state of 0 indicates that the device is in a normal state, that is, a standard state; a state data of 1 indicates that the device is in an abnormal state, that is, a non-standard state. Furthermore, the value of the numerical data is not limited to 0 and 1, but may be a variety of values ​​within a certain range. Exemplarily, the label information about the data type in the initial device data may be identified, and then the target data type corresponding to the initial device data may be determined based on the label information.

[0036] S220: When the target data type is numerical data, determine a reference numerical data set corresponding to the initial device data, and determine a correction result of the initial device data based on the reference numerical data set.

[0037] Among them, the reference numerical data set can be a numerical data set used as a reference for data correction of the initial device data. Exemplarily, the numerical data collected in the historical period corresponding to the initial device data can be used as the reference numerical data set. After the current numerical data is corrected, it can be added to the historical data set as the historical numerical data corresponding to the next numerical data. That is, the reference numerical data set is dynamically changing, and the reference numerical data sets corresponding to different initial device data are different. Further, the correction determination result can be a determination result on whether the initial device data needs data correction. Specifically, the correction determination result includes a correction determination result and a non-essential correction determination result. Among them, the correction determination result means that the initial device data needs to be corrected. The non-essential description determination result means that the initial device data does not need to be corrected.

[0038] Optionally, determining the revised judgment result of the initial device data based on the reference numerical data set includes: determining a reference numerical data set corresponding to the initial device data; determining an initial abnormal value based on an average value of data in the reference numerical data set and the initial device data; dividing the initial abnormal value by a preset standard deviation value to obtain a target abnormal value, and when the target abnormal value is greater than a preset abnormal threshold, determining the revised judgment result as a revised judgment result.

[0039] Among them, the initial outlier value may be an outlier value of the initial device data relative to a reference numerical data set. Specifically, the average value of the data in the reference numerical data set may be obtained, and the initial device data may be subtracted from the average value of the reference numerical data set to obtain a reference outlier value. The preset standard deviation value may be a preset value for standardizing the outlier value of the initial device data. Specifically, the preset standard deviation value may be set manually. The target outlier value may be a value obtained after standardizing the initial device data. Specifically, the initial outlier value may be divided by the preset standard deviation to obtain the target outlier value. Further, the preset outlier threshold may be a preset reference threshold for determining whether the initial device data needs to be corrected. When the target outlier value is greater than the preset outlier threshold, it may be determined that the deviation of the initial device data from the reference numerical data set is large, and therefore it may be determined that the correction determination result is the correction determination result.

[0040] S230: When the correction determination result is a correction determination result, determine a target correction value based on the reference numerical data set, and perform data correction on the initial device data based on the target correction value to obtain the target device data.

[0041] The target correction value may be a value used to correct the initial device data. The target device data may be data obtained after correcting the initial device data. Specifically, the initial device data and the target correction value may be added together to obtain the target device data.

[0042] Optionally, determining the target correction value based on the reference numerical data set includes: grouping every two adjacent data in the reference numerical data set into a group of reference data pairs; for each reference data pair, determining the data difference between two data in the reference data pair, and taking the average of the data differences of all reference data pairs as the target correction value.

[0043] The reference data pair may be a data pair used to determine the correction value. Specifically, each two adjacent data in the reference numerical data set may be combined to obtain a reference data pair. Furthermore, for each reference data pair, two data in the reference data pair may be subtracted to obtain a data difference value for each reference data pair. Finally, the data difference values ​​of all reference data pairs may be averaged, and the obtained average value may be used as the target correction value.

[0044] The technical solution provided by the embodiment of the present invention can automatically increase or decrease the window size according to the changes in the sample data, buffer the data fluctuations caused by various problems such as the environment within a controllable period, and greatly reduce the distorted data and duplicate data caused by the inability of the existing fixed processing logic to adapt to each abnormal fluctuation period.

[0045] The technical solution provided by the embodiment of the present invention determines the target data type corresponding to the initial device data by acquiring the initial device data of the target device; when the target data type is numerical data, determines the reference numerical data set corresponding to the initial device data, and determines the correction judgment result of the initial device data based on the reference numerical data set; when the correction judgment result is a correction judgment result, determines the target correction value based on the reference numerical data set, and performs data correction on the initial device data based on the target correction value to obtain the target device data. The technical solution of the embodiment of the present invention solves the problem that the existing data correction technology mainly performs data correction based on a fixed interval or a fixed standard, and cannot adapt to real-time dynamically changing data, resulting in low value and availability of the final output corrected data. It can match the corresponding data correction strategy based on the data type of the device data, thereby improving the dynamic adaptability and authenticity of the data correction.

[0046] Figure 3 It is a flow chart of a method for correcting state-type data provided by an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of correcting the production data of the equipment. Based on the above embodiment, this embodiment further explains how to correct the initial equipment data based on the target data type to obtain the target equipment data when the target data type is state-type data. The device can be implemented by software and / or hardware and integrated in a computer device with application development function.

[0047] like Figure 3 As shown, the device data correction method includes the following steps:

[0048] S310: Acquire initial device data of a target device, and determine a target data type corresponding to the initial device data.

[0049] S320: Perform sliding sampling on the initial device data based on an initial sampling window to obtain at least one set of sampled data sets.

[0050] The initial sampling window may be a preset window for sampling the initial device data. The sampled data set may be a data set consisting of multiple data in the initial device data. Specifically, when the target data type is state data, the initial device data may have multiple 0 / 1 type data, and sliding sampling may be performed from the 0 / 1 type data in the initial device data based on the initial sampling window to obtain at least one set of sampled data sets.

[0051] S330: When there is non-standard state data in the current sampling data set, determine a previous sampling data set corresponding to the current sampling data set.

[0052] Among them, the current sampling data set may be the data sampling data set currently being analyzed. Specifically, each data sampling data set may be analyzed in sequence from early to late based on the collection time of the data in the data sampling data set. Non-standard state data may be understood as state-type data of abnormal state. Exemplarily, an embodiment of the present invention may use state data with state data of 1 as non-standard state data; and use state data with state data of 0 as standard state data. Further, the previous sampling data set may be the previous data sampling data set corresponding to the current sampling data set. Exemplarily, in the case where the data sampling data set with a sequence number of 100 is the current sampling data set, the data sampling data set with a sequence number of 99 may be used as the previous sampling data set.

[0053] Specifically, when the data in the current sampling data set contains both non-standard state data and standard state data, the previous sampling data set corresponding to the current sampling data set can be determined. Wherein, when the data in the current sampling data set contains both non-standard state data and standard state data, it reflects that the current device state of the target device fluctuates and may be in an abnormal state. In this case, it can be further determined based on the previous sampling data set corresponding to the current sampling data set.

[0054] Optionally, when all data in the current sampling data set are non-standard state data, a device abnormality signal may be returned to the target device; when all data in the current sampling data set are standard state data, a device normal signal may be returned to the target device.

[0055] Among them, the device abnormality signal may be a signal indicating that the target device is currently in an abnormal state. In the case where the data in the current sampling data set are all non-standard state data, it indicates that the device state of the target device is in an abnormal state and there is no fluctuation, and at this time it can be determined that the target device is currently in an abnormal state. Correspondingly, the device normal signal may be a signal indicating that the target device is currently in a normal state. In the case where the data in the current sampling data set are all standard state data, it indicates that the device state of the target device is in a normal state and there is no fluctuation, and at this time it can be determined that the target device is currently in a normal state.

[0056] S340: When the previous sampling data set is standard state data, the state data in the current sampling data set is corrected to obtain a target sampling data set, and the initial sampling window is adjusted to obtain a reference sampling window.

[0057] The target sampling data set may be a data set obtained by correcting the current sampling data set. Exemplarily, all state data in the current sampling data set may be corrected to standard state data to obtain the target sampling data set.

[0058] Furthermore, the reference sampling window may be a window for subsequent data sampling. The reference sampling window serves as a sampling window for subsequent sliding sampling of the current sampling data set. Specifically, when the previous sampling data set is standard state data, the initial sampling window may be expanded based on a preset window augmentation amount to obtain a reference sampling window. For example, when the initial sampling window is m and the window augmentation amount is c, the reference sampling window may be m+c.

[0059] Optionally, the device data after the current sampling data set may be slidingly sampled based on the reference sampling window to obtain a reference data set; when the data in the reference data set are all standard state data, the reference sampling window is restored to the initial sampling window.

[0060] The reference data set may be a data set obtained by sampling based on the reference sampling window. Specifically, the reference data set may be obtained by sliding sampling the device data after the current sampling data set based on the reference sampling window. Furthermore, when the data in the reference data set are all standard state data, it can be determined that the target device is already in a normal state, and the reference sampling window can be restored to the initial sampling window.

[0061] Optionally, when not all the data in the reference data set are standard state data, and all the data in the previous reference data set corresponding to the reference data set are standard state data, the reference sampling window can be further expanded based on a preset window augmentation amount, and subsequent data sampling is performed based on the expanded reference sampling window. That is, the reference sampling window can be m+nc, where n is an integer.

[0062] The capacity of the sampling window of the embodiment of the present invention will automatically change according to the degree of data fluctuation. The more severe the fluctuation, the more the window will expand, thereby greatly reducing the final data fluctuation. At the same time, a standard state mechanism is set to quickly shrink the window after the data stabilizes, thereby improving the response efficiency of state changes in a stable state.

[0063] Figure 4 FIG. 1 is a flowchart of a process for modifying device data provided by an embodiment of the present invention. Figure 4 As shown, the workflow for device data correction includes the following steps:

[0064] First, you need to determine the subsequent processing plan based on the device data type (status data, numerical data) defined in the initialization:

[0065] For status data:

[0066] (1) Initialization parameters: the initial size of the data acquisition sliding window is m (assumed to be 2), the number of sample data is defined as T, and the standard state data is assumed to be 0;

[0067] (2) Determine whether the sample size meets the conditions for executing the correction algorithm, that is, determine whether the total sample size is greater than the window size.

[0068] (3) When the conditions are met, m samples (including the current sample) are taken from the sample in reverse chronological order, and the window slides.

[0069] (4) Determine whether the current sample state is the standard state. If so, directly return to the standard state, filter out the non-standard state, and then execute the next step.

[0070] (5) Two judgments need to be performed simultaneously here: (1) One is to judge if all samples in the window are non-standard at this time, then return to the non-standard state, otherwise the sample data needs to be corrected to the standard state. Because at this time, the data may be unstable due to uncontrollable factors and the stable abnormal state conditions have not been reached. (2) The other is to judge whether the state fluctuation occurs based on whether the current state changes from the standard state to the non-standard state. If so, the window size needs to be increased and the non-standard state judgment cycle needs to be increased to adapt to the impact of environmental fluctuations.

[0071] (6) If the correction value is in the standard state, it is necessary to determine whether all samples in the window are standard values. If all are standard values, it can be determined that the environment is stable and the sampling window is reduced to the initialization value.

[0072] (7) Execute subsequent business processes based on the corrected device status data. For example, if the device is offline, the standard status is online and the abnormal status is offline. After confirming that the device is offline, it is necessary to generate and push offline alarm notifications and execute related device linkage operations.

[0073] For numeric data:

[0074] (1) Initialize the standard outlier threshold d, the number of samples collected t, and the standard deviation c.

[0075] (2) Collect x pieces of sample data, find the sample data mean avg, calculate the difference between the current sample data and the mean avg, divide the difference by the standard deviation c, and take the absolute value of the result to get the outlier value of the current data.

[0076] (3) Determine whether the outlier value of the current data exceeds the outlier threshold d. If it does not exceed, mark the data as a normal value and put it back directly. Otherwise, mark the data as an outlier and perform data correction.

[0077] (4) After obtaining the abnormal data, take the t-1 pieces of data before the current data, calculate the difference in turn and take the average to obtain the average single-step increment value, correct the current data to the data at the previous time point of the current data + the average single-step increment value, and return the corrected value.

[0078] (5) After the final corrected data close to the real scenario is obtained through calculation, the data can be reused according to different business scenarios (making data reports, diagrams, large-screen displays, etc.), and different threshold-type warnings can be generated and ended for different business functions.

[0079] The technical solution provided by the embodiment of the present invention determines the target data type corresponding to the initial device data by acquiring the initial device data of the target device; performs sliding sampling from the initial device data based on the initial sampling window to obtain at least one set of sampling data sets; in the case where the data in the current sampling data set contains non-standard state data, determines the previous sampling data set corresponding to the current sampling data set; in the case where the previous sampling data set is standard state data, corrects the state data in the current sampling data set to obtain the target sampling data set, and adjusts the initial sampling window to obtain the reference sampling window. The technical solution of the embodiment of the present invention solves the problem that the existing data correction technology mainly performs data correction based on a fixed interval or a fixed standard, cannot adapt to real-time dynamically changing data, and results in low value and availability of the final corrected data. It can match the corresponding data correction strategy based on the data type of the device data, thereby improving the dynamic adaptability and authenticity of the data correction.

[0080] Figure 5 It is a structural schematic diagram of a device data correction apparatus provided in an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of correcting the production data of the device. The device can be implemented by software and / or hardware and integrated into a computer device with application development function.

[0081] like Figure 5 As shown, the device data correction apparatus includes: a data acquisition module 310 , a data type determination module 320 and a data correction module 330 .

[0082] Among them, the data acquisition module 310 is used to acquire the initial device data of the target device; the data type determination module 320 is used to determine the target data type corresponding to the initial device data; wherein the target data type includes: state data and numerical data; the data correction module 330 is used to correct the initial device data based on the target data type to obtain the target device data.

[0083] The technical solution provided by the embodiment of the present invention obtains the initial device data of the target device; determines the target data type corresponding to the initial device data; wherein the target data type includes: state data and numerical data; and performs data correction on the initial device data based on the target data type to obtain the target device data. The technical solution of the embodiment of the present invention solves the problem that the existing data correction technology mainly performs data correction based on a fixed interval or a fixed standard, which cannot adapt to real-time dynamically changing data, resulting in low value and availability of the final corrected data. The technical solution can match the corresponding data correction strategy based on the data type of the device data, thereby improving the dynamic adaptability and authenticity of the data correction.

[0084] In an optional embodiment, the data correction module 330 includes: a numerical data correction unit, used to: when the target data type is numerical data, determine a reference numerical data set corresponding to the initial device data, and determine a correction judgment result of the initial device data based on the reference numerical data set; when the correction judgment result is a correction judgment result, determine a target correction value based on the reference numerical data set, and perform data correction on the initial device data based on the target correction value to obtain the target device data.

[0085] In an optional embodiment, the numerical data correction unit includes: a correction judgment subunit, used to: determine a reference numerical data set corresponding to the initial device data; determine an initial abnormal value based on the average value of the data in the reference numerical data set and the initial device data; divide the initial abnormal value by a preset standard deviation value to obtain a target abnormal value, and when the target abnormal value is greater than a preset abnormal threshold, determine that the correction judgment result is a correction judgment result.

[0086] In an optional embodiment, the numerical data correction unit includes: a correction value determination subunit, used to: group every two adjacent data in the reference numerical data set into a group of reference data pairs; for each reference data pair, determine the data difference between the two data in the reference data pair, and take the average value of the data difference of all reference data pairs as the target correction value.

[0087] In an optional embodiment, the data correction module 330 also includes: a state-type data correction unit, which is used to: when the target data type is state-type data, perform sliding sampling from the initial device data based on an initial sampling window to obtain at least one set of sampling data sets; when there is non-standard state data in the data of the current sampling data set, determine the previous sampling data set corresponding to the current sampling data set; when the previous sampling data set is standard state data, correct the state data in the current sampling data set to obtain a target sampling data set, and adjust the initial sampling window to obtain a reference sampling window; wherein the reference sampling window is used as a sampling window for sliding sampling subsequent to the current sampling data set.

[0088] In an optional embodiment, the state-type data correction unit also includes: a window adjustment subunit, which is used to: perform sliding sampling on the device data after the current sampling data set based on the reference sampling window to obtain a reference data set; when the data in the reference data set are all standard state data, restore the reference sampling window to the initial sampling window.

[0089] In an optional embodiment, the device data correction apparatus further includes: a device signal return module, used to: return a device abnormality signal to the target device when the data in the current sampling data set are all non-standard state data; and return a device normal signal to the target device when the data in the current sampling data set are all standard state data.

[0090] The device data correction apparatus provided in the embodiment of the present invention can execute the device data correction method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0091] Figure 6 A schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Figure 6 A block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention is shown. Figure 6 The computer device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention. The computer device 12 can be any terminal device with computing capability and can be configured in the device data correction device.

[0092] like Figure 6 As shown, the computer device 12 is in the form of a general-purpose computing device. The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0093] The bus 18 may be one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. For example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0094] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0095] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache 32. The computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 6 not shown, usually called a "hard drive"). Although Figure 6 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0096] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0097] The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), one or more devices that enable a user to interact with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed through an input / output (I / O) interface 22. Furthermore, the computer device 12 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter 20. Figure 6 As shown, the network adapter 20 communicates with other modules of the computer device 12 via the bus 18. It should be understood that although Figure 6 Not shown, other hardware and / or software modules may be used in conjunction with computer device 12, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0098] The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing the device data correction method provided by the embodiment of the present invention, the method comprising:

[0099] Acquire initial device data of a target device; determine a target data type corresponding to the initial device data; wherein the target data type includes: state data and numerical data; perform data correction on the initial device data based on the target data type to obtain the target device data.

[0100] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the device data correction method provided by any embodiment of the present invention is implemented, including:

[0101] Acquire initial device data of a target device; determine a target data type corresponding to the initial device data; wherein the target data type includes: state data and numerical data; perform data correction on the initial device data based on the target data type to obtain the target device data.

[0102] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, 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), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0103] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0104] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0105] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or combinations thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0106] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0107] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A device data correction method, characterized in that: include: Get the initial device data of the target device; Determine the target data type corresponding to the initial device data; wherein the target data type includes: state data and value data; The initial device data is modified based on the target data type to obtain target device data.

2. The method according to claim 1, characterized in that In the case where the target data type is numerical data, the step of performing data correction on the initial device data to obtain the target device data includes: Determine a reference numerical data set corresponding to the initial device data, and determine a correction determination result of the initial device data based on the reference numerical data set; In a case where the correction determination result is a correction determination result, a target correction value is determined based on the reference numerical data set, and data correction is performed on the initial device data based on the target correction value to obtain the target device data.

3. The method according to claim 2, characterized in that The determining of the correction determination result of the initial device data based on the reference numerical data set includes: Determine a reference numerical data set corresponding to the initial device data; Determine an initial abnormal value based on an average value of data in the reference numerical data set and the initial device data; The initial abnormal value is divided by a preset standard deviation value to obtain a target abnormal value, and when the target abnormal value is greater than a preset abnormal threshold value, the revised determination result is determined to be a revised determination result.

4. The method according to claim 2, characterized in that: The determining of the target correction value based on the reference numerical data set includes: Every two adjacent data in the reference numerical data set form a set of reference data pairs; For each reference data pair, a data difference between two data in the reference data pair is determined, and an average value of the data differences of all reference data pairs is used as the target correction value.

5. The method according to claim 1, characterized in that In the case where the target data type is state data, performing data correction on the initial device data to obtain the target device data includes: Perform sliding sampling from the initial device data based on an initial sampling window to obtain at least one set of sampled data sets; In the case that the data in the current sampling data set contains non-standard state data, determining a previous sampling data set corresponding to the current sampling data set; In the case where the previous sampling data set is standard state data, the state data in the current sampling data set is corrected to obtain a target sampling data set, and the initial sampling window is adjusted to obtain a reference sampling window; The reference sampling window is used as a sampling window for subsequent sliding sampling of the current sampling data set.

6. The method according to claim 5, characterized in that The method further comprises: Perform sliding sampling on the device data after the current sampling data set based on the reference sampling window to obtain a reference data set; In the case that the data in the reference data set are all standard state data, the reference sampling window is restored to the initial sampling window.

7. The method according to claim 5, characterized in that The method further comprises: When all data in the current sampling data set are non-standard state data, returning a device abnormality signal to the target device; When the data in the current sampling data set are all standard state data, a device normal signal is returned to the target device.

8. A device data correction device, characterized in that: The device comprises: A data acquisition module, used to acquire initial device data of a target device; A data type determination module, used to determine a target data type corresponding to the initial device data; wherein the target data type includes: state data and value data; The data correction module is used to correct the initial device data based on the target data type to obtain the target device data.

9. A computer device, characterized in that: The computer device comprises: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the device data correction method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the device data correction method as described in any one of claims 1 to 7 is implemented.

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