Error correction method, device and equipment of vibration sensor data, and storage medium

Abstract

The application discloses a kind of error correction methods, device, equipment and storage medium of vibration sensor data, which includes: obtaining the historical vibration signal data of target sensor group, and based on operating condition data and sensor error range data, the historical vibration signal data is carried out data aggregation analysis, and the vibration characteristic data of the target sensor group is determined;Real-time vibration signal data of target sensor group is collected, and according to the vibration correlation characteristic data of the target sensor group, the real-time vibration signal data is carried out data error analysis;According to the data error analysis result, the real-time vibration signal data is carried out data error correction.Through the above technical scheme, the effectiveness and stability of continuous detection for monitoring equipment are improved.

Description

Technical Field

[0001] This invention relates to the field of data error correction technology, and in particular to a method, apparatus, device, and storage medium for error correction of vibration sensor data. Background Technology

[0002] Vibration sensor arrays are widely used in industrial monitoring, aerospace, automotive, and building structural health monitoring, providing multi-dimensional vibration data to help analyze and diagnose the operating status of systems.

[0003] In the field of nuclear power plant applications, vibration sensor arrays are mainly used to monitor the vibration status of key equipment and structures in nuclear power plants to ensure the safe operation of nuclear power plants. Summary of the Invention

[0004] This invention provides a method, apparatus, device, and storage medium for error correction of vibration sensor data, which improves the effectiveness and stability of continuous monitoring of vibration sensors while ensuring the accuracy of the data collected by the vibration sensor.

[0005] According to one aspect of the present invention, an error correction method for vibration sensor data is provided, the method comprising:

[0006] Historical vibration signal data of the target sensor group is acquired, and based on operating condition data and sensor error range data, data aggregation analysis is performed on the historical vibration signal data to determine the vibration characteristic data of the target sensor group; wherein, the vibration characteristic data is used to characterize the allowable error range of the vibration signal data collected by the target sensor group under different operating conditions.

[0007] Real-time vibration signal data of the target sensor group is collected, and data error analysis is performed on the real-time vibration signal data based on the vibration correlation characteristic data of the target sensor group.

[0008] The real-time vibration signal data is corrected for errors based on the data error analysis results.

[0009] According to another aspect of the present invention, an error correction device for vibration sensor data is provided, the device comprising:

[0010] The historical data analysis module is used to acquire historical vibration signal data of the target sensor group, and perform data aggregation analysis on the historical vibration signal data based on operating condition data and sensor error range data to determine the vibration characteristic data of the target sensor group; wherein, the vibration characteristic data is used to characterize the allowable error range of the vibration signal data collected by the target sensor group under different operating conditions.

[0011] The real-time data analysis module is used to collect real-time vibration signal data of the target sensor group and perform data error analysis on the real-time vibration signal data based on the vibration correlation characteristic data of the target sensor group.

[0012] The data correction module is used to correct data errors in the real-time vibration signal data based on the data error analysis results.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] At least one processor;

[0015] and a memory communicatively connected to the at least one processor;

[0016] The memory stores a computer program that can be executed by the at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform the error correction method for vibration sensor data according to any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the error correction method for vibration sensor data according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer program product is provided, the computer program product comprising a computer program that, when executed by a processor, implements the error correction method for vibration sensor data according to any embodiment of the present invention.

[0019] The technical solution of this invention determines the vibration characteristic data of the target sensor group by performing correlation analysis on the historical vibration signal data of the target sensor group based on operating conditions. Then, based on the vibration correlation characteristic data, error analysis is performed on the real-time vibration signal data of the target sensor group, and error correction is performed on the real-time vibration signal data based on the error analysis results. This ensures the accuracy of the acquired data and avoids the impact on the analysis of the operating status of the monitoring equipment caused by the discontinuous vibration data acquisition due to the removal of equipment under unreasonable or inappropriate circumstances. This improves the effectiveness and stability of continuous monitoring of the monitoring equipment.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of an error correction method for vibration sensor data provided in Embodiment 1 of the present invention;

[0023] Figure 2 This is a flowchart of an error correction method for vibration sensor data provided in Embodiment 2 of the present invention;

[0024] Figure 3 This is a schematic diagram of the structure of an error correction device for vibration sensor data provided in Embodiment 3 of the present invention;

[0025] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the error correction method for vibration sensor data according to an embodiment of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] Example 1

[0029] Figure 1This is a flowchart illustrating an error correction method for vibration sensor data according to Embodiment 1 of the present invention. This embodiment is applicable to the field of nuclear power plant applications, specifically for error correction of sensor data collected by a vibration sensor array. This method can be executed by an error correction device for vibration sensor data, which can be implemented in hardware and / or software and can be configured in various general-purpose computing devices. For example... Figure 1 As shown, the method includes:

[0030] S110. Acquire historical vibration signal data of the target sensor group, and based on the operating condition data and sensor error range data, perform data aggregation analysis on the historical vibration signal data to determine the vibration characteristic data of the target sensor group.

[0031] The target sensor group can be a sensor group to be corrected for errors. This group includes at least two vibration sensors, deployed in different locations to monitor vibrations in different dimensions of the target equipment. It should be noted that the target equipment can refer to nuclear power equipment.

[0032] Operating condition data can characterize the operating conditions of a vibration sensor when it is in operation, and may include the location of the vibration source, the number of vibration sources, the temperature of the environment and the target device, and the structural dimensions of the target device.

[0033] Sensor error range data refers to the standard error range that a vibration sensor is allowed to tolerate. It should be noted that different types of vibration sensors may have different corresponding sensor error range data.

[0034] Vibration characteristic data can be used to characterize the allowable error range of vibration signal data collected by the target sensor group under different operating conditions.

[0035] In this embodiment of the invention, the target sensor group itself consists of multiple vibration sensors capable of measuring different dimensions, acquiring vibration signals generated by the vibration source in different dimensions and directions. However, vibration sensors themselves have a limited lifespan, and therefore, errors may occur in the acquired vibration data when the lifespan is nearing its limit. Typically, this error is addressed by replacing or repairing the vibration sensor after the error is fully determined. However, this approach can easily cause discontinuity in monitoring vibration sensors used for real-time monitoring of nuclear power equipment, affecting the monitoring effect. Furthermore, the error of vibration sensors, especially those nearing their lifespan, has a stable directionality and may not necessarily require repair or replacement; monitoring can continue by reasonably correcting the collected data.

[0036] S120. Collect real-time vibration signal data of the target sensor group, and perform data error analysis on the real-time vibration signal data based on the vibration correlation characteristic data of the target sensor group.

[0037] Optionally, based on the vibration correlation characteristic data of the target sensor group, data error analysis is performed on the real-time vibration signal data, including: determining the vibration characteristic data corresponding to each vibration sensor in the target sensor group based on the vibration characteristic data of the target sensor group; and determining whether the real-time vibration signal data conforms to the vibration characteristic data corresponding to its respective vibration sensor.

[0038] Specifically, by identifying the vibration characteristic data of each vibration sensor in the target sensor group under different operating conditions, and based on the sensor type and operating condition of the vibration sensor to which the real-time collected vibration characteristic data belongs, it can be determined whether the real-time collected vibration signal data is within the data range represented by the vibration characteristic data.

[0039] S130. Correct the data error of the real-time vibration signal data based on the data error analysis results.

[0040] Optionally, in this embodiment of the invention, the error-corrected real-time vibration signal data can be used as historical vibration signal data to expand the historical vibration signal data, providing a rich data source for determining vibration characteristic data and improving the accuracy of vibration characteristic data.

[0041] The technical solution of this invention determines the vibration characteristic data of the target sensor group by performing correlation analysis on the historical vibration signal data of the target sensor group based on operating conditions. Then, based on the vibration correlation characteristic data, error analysis is performed on the real-time vibration signal data of the target sensor group, and error correction is performed on the real-time vibration signal data based on the error analysis results. This ensures the accuracy of the acquired data and avoids the impact on the analysis of the operating status of the monitoring equipment caused by the discontinuous vibration data acquisition due to the removal of equipment under unreasonable or inappropriate circumstances. This improves the effectiveness and stability of continuous monitoring of the monitoring equipment.

[0042] Example 2

[0043] Figure 2 This is a flowchart of a vibration sensor data error correction method provided in Embodiment 2 of the present invention. This embodiment further refines the above embodiment, providing specific steps for performing data aggregation analysis on the historical vibration signal data based on operating condition data and sensor error range data to determine the vibration characteristic data of the target sensor group. It should be noted that for parts not described in detail in this embodiment, please refer to the relevant descriptions in other embodiments, which will not be repeated here. Figure 2 As shown, the method includes:

[0044] S210. Based on the operating condition data, divide the historical vibration signal data of the target sensor into operating conditions and determine at least one group of historical vibration signal data for each operating condition.

[0045] In this embodiment of the invention, the sensor data (vibration signal values) collected by the vibration sensor within the theoretically permissible or collectable range are not discrete. Therefore, a linear relationship can be determined for the discrete sensor data collected by the vibration sensor. However, the operating conditions of the vibration sensor will affect the sensor data collected to some extent. Therefore, the sensor data can be clustered according to the operating conditions of the vibration sensor to obtain continuous historical vibration signal data collected by the vibration sensor under different operating conditions, so as to ensure that the clustered historical vibration signal data have obvious correlation characteristics.

[0046] It should be noted that the vibration signal data may include sensor data collected by the vibration sensor, the timestamp information of the time when the sensor data was collected, and the operating condition data of the vibration sensor when it was collecting sensor data.

[0047] Specifically, historical vibration signal data can be clustered and divided according to operating condition data and the sensor type of the vibration sensor to generate historical vibration signal data groups for each operating condition. It should be noted that each historical vibration signal data group corresponds to a different operating condition, and different historical vibration signal data groups for different operating conditions may correspond to a single vibration sensor.

[0048] S220. For the historical vibration signal data set under working conditions, generate a sequence of historical vibration signal values ​​corresponding to different vibration sensors in the historical vibration signal data set under working conditions, according to the order of the acquisition timestamps.

[0049] S230. Perform linear correlation analysis on the numerical variation relationship in the historical vibration signal value sequence to determine the linear vibration relationship corresponding to the historical vibration signal value sequence.

[0050] Among them, linear vibration relationship can refer to the linear relationship between vibration signal value and acquisition timestamp information.

[0051] S240. Perform error range analysis on the linear vibration relationship and the sensor error range data corresponding to its vibration sensor to determine the vibration characteristic data corresponding to the vibration sensor.

[0052] Optionally, an error range analysis is performed on the linear vibration relationship and the sensor error range data corresponding to the vibration sensor to determine the vibration characteristic data corresponding to the vibration sensor. This includes: determining the standard vibration value corresponding to the linear vibration relationship at each acquisition time point based on the linear vibration relationship; and determining the maximum and minimum permissible vibration values ​​corresponding to the vibration sensor at each acquisition time point based on the standard vibration value and the sensor error range data corresponding to the vibration sensor.

[0053] The standard vibration value can refer to the vibration signal value corresponding to the acquisition timestamp in a linear vibration relationship.

[0054] The sensor error range data can define the maximum downward deviation error threshold and the maximum upward deviation error threshold corresponding to the vibration sensor. It should be noted that the maximum permissible vibration value can be determined based on the standard vibration value and the maximum upward deviation error threshold, and the minimum permissible vibration value can be determined based on the standard vibration value and the maximum downward deviation error threshold.

[0055] In this embodiment of the invention, outside the range of the independent variable parameter (time stamp variable) in the linear vibration relationship, the standard vibration value is extended. The maximum and minimum permissible vibration values ​​corresponding to the extended standard vibration value are the sums of the standard vibration value and the maximum upper deviation error threshold and the maximum lower deviation error threshold, respectively.

[0056] Optionally, after determining the maximum and minimum permissible vibration values ​​of the vibration sensor at each acquisition timestamp, the method further includes: determining a maximum vibration linear relationship based on the linear vibration relationship and the maximum permissible vibration value; and determining a minimum vibration linear relationship based on the linear vibration relationship and the minimum permissible vibration value.

[0057] For example, the maximum and minimum linear vibration relationships can be determined by displacement based on the maximum and minimum permissible vibration values.

[0058] Optionally, the real-time vibration signal data can be corrected for errors based on the data error analysis results. This includes: if the real-time vibration signal data matches the vibration characteristic data corresponding to its respective vibration sensor, then the real-time vibration signal data is corrected for errors based on the linear vibration relationship corresponding to that vibration sensor. For example, the standard vibration value corresponding to the acquisition timestamp of the real-time vibration signal data in the new vibration relationship is used as the corrected result. If the real-time vibration signal data does not match the vibration characteristic data corresponding to its respective vibration sensor, it indicates that the vibration sensor needs to be replaced.

[0059] The technical solution of this invention divides historical vibration signal data according to working conditions, generates a collection sequence of historical vibration signal data according to the collection timestamp information, performs linear analysis on this collection sequence to determine the linear relationship of different collection sequences, and generates vibration characteristic data corresponding to the vibration sensor by combining the sensor error range data corresponding to the vibration sensor, thereby improving the accuracy of vibration characteristic data.

[0060] Example 3

[0061] Figure 3 This is a schematic diagram of the structure of an error correction device for vibration sensor data provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes:

[0062] The historical data analysis module 310 is used to acquire historical vibration signal data of the target sensor group, and perform data aggregation analysis on the historical vibration signal data based on operating condition data and sensor error range data to determine the vibration characteristic data of the target sensor group; wherein, the vibration characteristic data is used to characterize the allowable error range of the vibration signal data collected by the target sensor group under different operating conditions.

[0063] The real-time data analysis module 320 is used to collect real-time vibration signal data of the target sensor group and perform data error analysis on the real-time vibration signal data based on the vibration correlation characteristic data of the target sensor group.

[0064] The data correction module 330 is used to correct data errors in the real-time vibration signal data based on the data error analysis results.

[0065] The technical solution of this invention determines the vibration characteristic data of the target sensor group by performing correlation analysis on the historical vibration signal data of the target sensor group based on operating conditions. Then, based on the vibration correlation characteristic data, error analysis is performed on the real-time vibration signal data of the target sensor group, and error correction is performed on the real-time vibration signal data based on the error analysis results. This ensures the accuracy of the acquired data and avoids the impact on the analysis of the operating status of the monitoring equipment caused by the discontinuous vibration data acquisition due to the removal of equipment under unreasonable or inappropriate circumstances. This improves the effectiveness and stability of continuous monitoring of the monitoring equipment.

[0066] Optional, the historical data analysis module 310 includes:

[0067] The operating condition division unit is used to divide the historical vibration signal data of the target sensor into operating conditions based on the operating condition data, and determine at least one group of historical vibration signal data under operating conditions.

[0068] The data sequence unit is used to generate a sequence of historical vibration signal values ​​corresponding to different vibration sensors in the historical vibration signal data group of the working condition, according to the order of the acquisition timestamps.

[0069] The linear analysis unit is used to generate a sequence of historical vibration signal values ​​corresponding to different vibration sensors in the historical vibration signal data set of the working condition, according to the order of the acquisition timestamps.

[0070] The error range generation unit is used to perform error range analysis on the linear vibration relationship and the sensor error range data corresponding to its vibration sensor, and to determine the vibration characteristic data corresponding to the vibration sensor.

[0071] Optionally, the error range generation unit may be specifically used to: determine the standard vibration value corresponding to the linear vibration relationship at each acquisition time stamp based on the linear vibration relationship; and, based on the standard vibration value, determine the maximum and minimum permissible vibration values ​​of the vibration sensor at each acquisition time stamp according to the sensor error range data corresponding to the vibration sensor.

[0072] Optionally, the historical data analysis module 310 also includes:

[0073] The first linear unit is used to determine the maximum vibration linear relationship based on the linear vibration relationship and the maximum allowable vibration value;

[0074] The second linear unit is used to determine the minimum vibration linear relationship based on the linear vibration relationship and the minimum allowable vibration value.

[0075] Optionally, the real-time data analysis module 320 may be specifically used to: determine the vibration characteristic data corresponding to each vibration sensor in the target sensor group based on the vibration characteristic data of the target sensor group; and determine whether the real-time vibration signal data matches the vibration characteristic data corresponding to its respective vibration sensor.

[0076] Optionally, the target sensor group is a sensor group to be corrected for errors. The sensor group includes at least two vibration sensors, which are deployed in different positions to monitor the vibration of the target device in different dimensions.

[0077] The vibration sensor data error correction device provided in the embodiments of the present invention can execute the vibration sensor data error correction method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0078] Example 4

[0079] Figure 4 A schematic diagram of an electronic device 410 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0080] like Figure 4 As shown, the electronic device 410 includes at least one processor 411 and a memory, such as a read-only memory (ROM) 412 or a random access memory (RAM) 413, communicatively connected to the at least one processor 411. The memory stores computer programs executable by the at least one processor. The processor 411 can perform various appropriate actions and processes based on the computer program stored in the ROM 412 or loaded from storage unit 418 into the RAM 413. The RAM 413 may also store various programs and data required for the operation of the electronic device 410. The processor 411, ROM 412, and RAM 413 are interconnected via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0081] Multiple components in electronic device 410 are connected to I / O interface 415, including: input unit 416, such as keyboard, mouse, etc.; output unit 417, such as various types of displays, speakers, etc.; storage unit 418, such as disk, optical disk, etc.; and communication unit 419, such as network card, modem, wireless transceiver, etc. Communication unit 419 allows electronic device 410 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0082] Processor 411 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 411 performs the various methods and processes described above, such as error correction methods for vibration sensor data.

[0083] In some embodiments, the error correction method for vibration sensor data may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 418. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 410 via ROM 412 and / or communication unit 419. When the computer program is loaded into RAM 413 and executed by processor 411, one or more steps of the error correction method for vibration sensor data described above may be performed. Alternatively, in other embodiments, processor 411 may be configured to perform the error correction method for vibration sensor data by any other suitable means (e.g., by means of firmware).

[0084] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0085] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0086] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0087] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0088] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0089] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0090] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0091] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for error correction of vibration sensor data, characterized in that, include: Historical vibration signal data of the target sensor group is acquired, and based on operating condition data and sensor error range data, data aggregation analysis is performed on the historical vibration signal data to determine the vibration characteristic data of the target sensor group; wherein, the vibration characteristic data is used to characterize the allowable error range of the vibration signal data collected by the target sensor group under different operating conditions. Real-time vibration signal data of the target sensor group is collected, and data error analysis is performed on the real-time vibration signal data based on the vibration correlation characteristic data of the target sensor group. The real-time vibration signal data is corrected for data errors based on the data error analysis results. The step of performing data aggregation analysis on the historical vibration signal data based on operating condition data and sensor error range data to determine the vibration characteristic data of the target sensor group includes: Based on the operating condition data, the historical vibration signal data of the target sensor is divided into operating conditions to determine at least one group of historical vibration signal data for each operating condition. For the aforementioned historical vibration signal data set, a sequence of historical vibration signal values ​​corresponding to different vibration sensors in the historical vibration signal data set is generated according to the order of the acquisition timestamps. A linear correlation analysis is performed on the numerical variation relationship in the historical vibration signal value sequence to determine the linear vibration relationship corresponding to the historical vibration signal value sequence. By performing error range analysis on the linear vibration relationship and the sensor error range data corresponding to its vibration sensor, the vibration characteristic data corresponding to the vibration sensor can be determined. The step of performing error range analysis on the linear vibration relationship and the sensor error range data corresponding to its respective vibration sensor to determine the vibration characteristic data corresponding to the vibration sensor includes: Based on the linear vibration relationship, determine the standard vibration value corresponding to the linear vibration relationship at each acquisition timestamp; Based on the standard vibration value, and according to the sensor error range data corresponding to the vibration sensor, the maximum and minimum permissible vibration values ​​of the vibration sensor at each acquisition time point are determined; wherein, the sensor error range data is used to define the maximum downward deviation error threshold and the maximum upward deviation error threshold corresponding to the vibration sensor. The maximum vibration linear relationship is determined based on the linear vibration relationship and the maximum permissible vibration value; Based on the linear vibration relationship and the minimum permissible vibration value, determine the minimum vibration linear relationship; The step of correcting the real-time vibration signal data based on the data error analysis results includes: If the real-time vibration signal data matches the vibration characteristic data corresponding to its respective vibration sensor, then the real-time vibration signal data is corrected for error based on the linear vibration relationship corresponding to that vibration sensor. If the real-time vibration signal data does not match the vibration characteristic data corresponding to its vibration sensor, it indicates that the vibration sensor to which the real-time vibration signal data belongs needs to be replaced.

2. The method according to claim 1, characterized in that, The step of performing data error analysis on the real-time vibration signal data based on the vibration correlation characteristic data of the target sensor group includes: Based on the vibration characteristic data of the target sensor group, determine the vibration characteristic data corresponding to each vibration sensor in the target sensor group; Determine whether the real-time vibration signal data matches the vibration characteristic data corresponding to its respective vibration sensor.

3. The method according to claim 1, characterized in that, The target sensor group is a sensor group to be corrected for errors. The sensor group includes at least two vibration sensors. The different vibration sensors are deployed in different positions to monitor the vibration of the target device in different dimensions.

4. An error correction device for vibration sensor data, characterized in that, include: The historical data analysis module is used to acquire historical vibration signal data of the target sensor group, and perform data aggregation analysis on the historical vibration signal data based on operating condition data and sensor error range data to determine the vibration characteristic data of the target sensor group; wherein, the vibration characteristic data is used to characterize the allowable error range of the vibration signal data collected by the target sensor group under different operating conditions. The real-time data analysis module is used to collect real-time vibration signal data of the target sensor group and perform data error analysis on the real-time vibration signal data based on the vibration correlation characteristic data of the target sensor group. The data correction module is used to correct data errors in the real-time vibration signal data based on the data error analysis results. The historical data analysis module includes: The operating condition division unit is used to divide the historical vibration signal data of the target sensor into operating conditions based on the operating condition data, and determine at least one group of historical vibration signal data under operating conditions. The data sequence unit is used to generate a sequence of historical vibration signal values ​​corresponding to different vibration sensors in the historical vibration signal data group of the working condition, according to the order of the acquisition timestamps. The linear analysis unit is used to perform linear correlation analysis on the numerical change relationship in the historical vibration signal value sequence to determine the linear vibration relationship corresponding to the historical vibration signal value sequence. The error range generation unit performs error range analysis on the linear vibration relationship and the sensor error range data corresponding to its vibration sensor to determine the vibration characteristic data corresponding to the vibration sensor. Specifically, the error range generation unit is used for: Based on the linear vibration relationship, the standard vibration value corresponding to the linear vibration relationship at each acquisition time point is determined; using the standard vibration value as a benchmark, and based on the sensor error range data corresponding to the vibration sensor, the maximum allowable vibration value and the minimum allowable vibration value corresponding to the vibration sensor at each acquisition time point are determined; the sensor error range data is used to define the maximum downward deviation error threshold and the maximum upward deviation error threshold corresponding to the vibration sensor. The historical data analysis module further includes: The first linear unit is used to determine the maximum vibration linear relationship based on the linear vibration relationship and the maximum allowable vibration value; The second linear unit is used to determine the minimum vibration linear relationship based on the linear vibration relationship and the minimum allowable vibration value; Specifically, the data correction module is used for: If the real-time vibration signal data matches the vibration characteristic data corresponding to its respective vibration sensor, then the real-time vibration signal data is corrected for error based on the linear vibration relationship corresponding to that vibration sensor. If the real-time vibration signal data does not match the vibration characteristic data corresponding to its vibration sensor, it indicates that the vibration sensor to which the real-time vibration signal data belongs needs to be replaced.

5. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform the error correction method for vibration sensor data according to any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the error correction method for vibration sensor data according to any one of claims 1-3.

7. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the error correction method for vibration sensor data according to any one of claims 1-3.

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