EFT filtering processing method and system

Abstract

The invention provides an EFT filtering processing method and system, and belongs to the technical field of signal processing. The method comprises the following steps: circularly storing a first preset number of latest acquired signal data to a predefined array; calculating a first signal change value between each signal data in the predefined array and the adjacent signal data collected at the previous moment; calculating a signal mean value of the second preset number of latest collected signal data; judging the difference value change of a third preset number of continuous and latest collected signal data to obtain a second signal change value; and determining an output signal effective value according to the signal mean value, the first signal change value, the second signal change value, the current signal effective value, a preset take-off value and a preset tolerance value. By setting the preset take-off value and the preset tolerance value, spikes generated when the signals are interfered are filtered out, and filtering out of the EFT signals is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of signal processing, and in particular to an EFT filtering processing method and system. Background Art

[0002] Software filtering mainly performs multiple uniform sampling of the input signal, averages the sampling results, and then uses the averaging or sliding average method to filter out interference signals.

[0003] However, the EFT fast pulse group experiment will produce a large amount of pulse interference, causing a large number of spikes in the signal with high repeatability. The accuracy of the signal after using the mean filter will exceed the accuracy range, and the interference cannot be completely filtered out. Therefore, the interference of the EFT experiment cannot be effectively filtered out by the above mean filtering method. How to improve the filtering quality of the EFT experiment interference signal has become an urgent problem to be solved. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide an EFT filtering processing method and system to at least solve the above-mentioned problem that the filtering quality of the EFT experimental interference signal cannot be effectively improved.

[0005] In order to achieve the above object, the present invention provides an EFT filtering processing method in a first aspect, comprising:

[0006] Circularly storing a first preset number of newly acquired signal data into a predefined array;

[0007] Calculate the first signal change value between each signal data in the predefined array and the signal data collected at the previous moment;

[0008] Calculating a signal mean of a second preset number of the most recently collected signal data;

[0009] Determine the difference change of a third preset number of consecutive and most recently collected signal data to obtain a second signal change value;

[0010] The output signal effective value is determined according to the signal mean value, the first signal change value, the second signal change value, the current signal effective value, the preset jump value and the preset tolerance value.

[0011] Optionally, the above-mentioned determining the output signal effective value according to the signal mean value, the first signal change value, the second signal change value, the current signal effective value, the preset jump value and the preset tolerance value includes:

[0012] Perform a first judgment based on the absolute value of the difference between the signal mean value and the current signal effective value and the preset jump value;

[0013] If the absolute value of the difference between the signal mean and the current signal effective value is less than the preset jump value, the output signal effective value is the current signal effective value; otherwise, a second judgment is performed based on the first signal change value, the second signal change value and the preset tolerance value.

[0014] Optionally, performing a second judgment based on the first signal change value, the second signal change value and a preset tolerance value includes:

[0015] If the second signal change value is less than the preset tolerance value, the output signal effective value is updated to the signal mean value; otherwise, a third judgment is performed based on the first signal change value.

[0016] Optionally, performing a third determination based on the first signal change value includes:

[0017] According to the first signal change value, determining a change trend between the corresponding signal data and the signal data collected at the previous adjacent moment;

[0018] If the change trends corresponding to all signal data in the predefined array are consistent, the output signal effective value is updated to the signal mean. Otherwise, a fourth judgment is made based on the difference between each signal data in the predefined array and the current signal effective value and the preset tolerance value.

[0019] Optionally, the fourth judgment based on the difference between each signal data in the predefined array and the current signal valid value and a preset tolerance value includes:

[0020] If the difference between each signal data in the predefined array and the current signal effective value is greater than the preset tolerance value, the output signal effective value is updated to the signal mean value; otherwise, the output signal effective value is the current signal effective value.

[0021] Optionally, judging, according to the first signal change value, a change trend between the corresponding signal data and the signal data collected at the previous adjacent moment includes:

[0022] Based on any first signal change value and a preset change trend table, a change trend between the corresponding signal data and the signal data collected at the previous adjacent moment is determined, wherein the preset change trend table stores the corresponding relationship between the size of the first signal change value and the change trend.

[0023] Optionally, the EFT filtering processing method further includes:

[0024] Define the storage array for changing trends;

[0025] The change trend between any signal data in the predefined array and the corresponding signal data collected at the previous moment is stored in the change trend storage array.

[0026] A second aspect of the present invention provides an EFT filtering processing system, comprising:

[0027] A signal data storage module, used for cyclically storing a first preset number of newly collected signal data into a predefined array;

[0028] A first signal change value calculation module, used to calculate a first signal change value between each signal data in a predefined array and the signal data collected at the previous adjacent moment;

[0029] A signal mean value calculation module, used to calculate the signal mean value of a second preset number of the most recently collected signal data;

[0030] A difference change judgment module is used to judge the difference change of a third preset number of consecutive and latest collected signal data to obtain a second signal change value;

[0031] The signal effective value determination module is used to determine the output signal effective value according to the signal mean value, the first signal change value, the second signal change value, the current signal effective value, the preset jump value and the preset tolerance value.

[0032] In a third aspect of the present invention, a machine-readable storage medium is provided, on which instructions are stored. When the instructions are executed by a processor, the processor is configured to execute the above-mentioned EFT filtering processing method.

[0033] In a fourth aspect of the present invention, an electronic device is provided. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the EFT filtering method is implemented.

[0034] Through the above technical solution, an EFT filtering processing method and system calculates the first signal change value between each signal data and the signal data collected at the adjacent previous moment, the signal mean value of the second preset number of the latest collected signal data, and the second signal change value of the third preset number of continuous and latest collected signal data based on the predefined array. The difference between the signal mean value and the current signal effective value is compared with the preset jump value and the preset tolerance value to judge the change of the signal effective value and determine the output signal effective value, so that the spikes generated when the signal is interfered are filtered out by setting the preset jump value and the preset tolerance value, and the EFT signal is filtered out.

[0035] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0037] Figure 1 is a flow chart of an EFT filtering processing method provided by one embodiment of the present invention;

[0038] Figure 2 is a flow chart of another EFT filtering processing method provided by one embodiment of the present invention;

[0039] Figure 3 is a block diagram of an EFT filtering processing system provided by one embodiment of the present invention;

[0040] Figure 4 It is a schematic diagram of the structure of an electronic device provided by a preferred embodiment of the present invention.

[0041] Description of Reference Numerals

[0042] 10 - electronic device, 100 - processor, 101 - memory, 102 - computer program. DETAILED DESCRIPTION

[0043] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0044] Figure 1 FIG. 1 is a flow chart of an EFT filtering method provided by an embodiment of the present invention. Figure 1 As shown, an embodiment of the present invention provides an EFT filtering processing method, comprising:

[0045] S110: cyclically storing a first preset number of newly collected signal data into a predefined array;

[0046] The first preset number is n.

[0047] Specifically, an array, namely a predefined array, is defined in advance, and the size of the predefined array can be defined as n according to actual needs, and n latest collected signal data are cyclically stored in the predefined array.

[0048] S120: Calculating a first signal change value between each signal data in the predefined array and the signal data collected at the previous moment;

[0049] The first signal change value corresponding to any signal data can reflect the change trend of the signal data compared with the signal data collected at the previous moment.

[0050] Exemplarily, the magnitude of the above-mentioned first signal change value may be in the following cases: 1. The difference between the signal data and the signal data collected at the previous adjacent moment is less than the preset jump value; 2. The signal data is at least greater than the signal data collected at the previous adjacent moment by a preset jump value; 3. The signal data is at least less than the signal data collected at the previous adjacent moment by a preset jump value. The above-mentioned change trend may include an increasing trend, a stable trend, and a decreasing trend. If the difference between the signal data and the signal data collected at the previous adjacent moment is greater than the first preset value, the change trend is an increasing trend. If the difference between the signal data and the signal data collected at the previous adjacent moment is less than the second preset value, the change trend is a decreasing trend. If the difference between the signal data and the signal data collected at the previous adjacent moment is greater than the second preset value and less than the first preset value, the change trend is a stable trend.

[0051] S130: Calculating the signal mean of a second preset number of the most recently collected signal data;

[0052] The second preset number may be n / 2. According to tests, the second preset number n / 2 balances the response time and the filtering effect.

[0053] Specifically, the n / 2 most recently collected signal data in the predefined array are summed and averaged to obtain the signal mean value of the n / 2 most recently collected signal data.

[0054] S140: Determine a difference change of a third preset number of consecutive and most recently collected signal data to obtain a second signal change value;

[0055] The third preset number may be n / 2.

[0056] Specifically, the second signal change value can reflect the change difference of the n / 2 consecutive and latest collected signal data.

[0057] For example, if n is 4, the second signal change value can reflect the change difference between two consecutive and latest collected signal data, that is, the absolute value of the difference between the two consecutive and latest collected signal data.

[0058] If n is 10, the second signal change value can reflect the change difference of 5 consecutive latest collected signal data, that is, the absolute value of the difference between the maximum value and the minimum value of the 5 consecutive latest collected signal data.

[0059] S150: Determine the output signal effective value according to the signal mean value, the first signal change value, the second signal change value, the current signal effective value, the preset jump value and the preset tolerance value.

[0060] The EFT filtering method sets two indicators: a preset jump value and a preset tolerance value. The preset jump value and the preset tolerance value specify the degree of smoothing of the algorithm to the spike interference and the tolerance to the spike.

[0061] Exemplarily, the preset jump value is the resolution of the signal, and the preset tolerance value is half of the signal accuracy. When the predefined array has not stored enough of the first preset number of the latest collected signal data, the current signal effective value can be a default value predefined by the user, and the default value is used as the initial signal effective value. When an output signal effective value has been generated, the output signal effective value can be used as the current signal effective value when the EFT filtering is performed next time.

[0062] Specifically, the method first calculates the first signal change value between each signal data and the signal data collected at the previous moment, the signal mean value of the second preset number of the latest collected signal data, and the second signal change value of the third preset number of continuous and latest collected signal data based on the predefined array. Then, the difference between the signal mean value and the current signal effective value is compared with the preset jump value and the preset tolerance value to judge the change of the signal effective value and determine the output signal effective value, so as to achieve the filtering of the spikes generated when the signal is interfered by setting the preset jump value and the preset tolerance value, and also achieve the filtering of the EFT signal.

[0063] In some implementations of this embodiment, the above-mentioned determining the output signal effective value according to the signal mean value, the first signal change value, the second signal change value, the current signal effective value, the preset jump value and the preset tolerance value includes:

[0064] Perform a first judgment based on the absolute value of the difference between the signal mean value and the current signal effective value and the preset jump value;

[0065] If the absolute value of the difference between the signal mean and the current signal effective value is less than the preset jump value, the output signal effective value is the current signal effective value; otherwise, a second judgment is performed based on the first signal change value, the second signal change value and the preset tolerance value.

[0066] Specifically, if the difference between the signal mean and the current signal effective value is less than the preset jump value, the output signal effective value is the current signal effective value; otherwise, it is considered that the signal mean reaches the jump condition and enters the second judgment.

[0067] In some implementations of this embodiment, the second determination based on the first signal change value, the second signal change value and the preset tolerance value includes:

[0068] If the second signal change value is less than the preset tolerance value, the output signal effective value is updated to the signal mean value; otherwise, a third judgment is performed based on the first signal change value.

[0069] Specifically, if the second signal change value is less than the preset tolerance value, it means that the difference of the third preset number of consecutive and latest collected signal data changes little and is within the preset tolerance value range, and the output signal effective value is the signal mean. If the second signal change value is greater than the preset tolerance value, it means that the fluctuation of the third preset number of consecutive and latest collected signal data is large and exceeds the preset tolerance value range, and the third judgment is performed.

[0070] In some implementations of this embodiment, performing the third determination based on the first signal change value includes:

[0071] According to the first signal change value, determining a change trend between the corresponding signal data and the signal data collected at the previous adjacent moment;

[0072] If the change trends corresponding to all signal data in the predefined array are consistent, the output signal effective value is updated to the signal mean. Otherwise, a fourth judgment is made based on the difference between each signal data in the predefined array and the current signal effective value and the preset tolerance value.

[0073] Specifically, it is determined whether the change trends corresponding to the signal data in the predefined array are consistent, that is, whether they are continuously rising, continuously stable, or continuously falling. If the change trends are consistent, that is, they satisfy monotonic changes, the output signal effective value is updated to the signal mean. If the change trend is not monotonic, the fourth judgment is performed.

[0074] In some implementations of this embodiment, the fourth determination based on the difference between each signal data in the predefined array and the current signal valid value and the preset tolerance value includes:

[0075] If the difference between each signal data in the predefined array and the current signal effective value is greater than the preset tolerance value, the output signal effective value is updated to the signal mean value; otherwise, the output signal effective value is the current signal effective value.

[0076] Specifically, the difference between each signal data in the predefined array and the current signal effective value is compared with the preset tolerance value. If the difference between all signal data in the predefined array and the current signal effective value is greater than the preset tolerance value, the output signal effective value is updated to the signal mean. In other cases, the output signal effective value is maintained as the current signal effective value.

[0077] In some implementations of this embodiment, judging the change trend between the corresponding signal data and the signal data collected at the previous moment according to the first signal change value includes:

[0078] Based on any first signal change value and a preset change trend table, a change trend between the corresponding signal data and the signal data collected at the previous adjacent moment is determined, wherein the preset change trend table stores the corresponding relationship between the size of the first signal change value and the change trend.

[0079] In some implementations of this embodiment, the EFT filtering processing method further includes:

[0080] Define the storage array for changing trends;

[0081] The change trend between any signal data in the predefined array and the corresponding signal data collected at the previous moment is stored in the change trend storage array.

[0082] Specifically, a change trend storage array is defined to store the change trend between any signal data in the predefined array and the corresponding signal data collected at the previous moment, so that the change trend corresponding to all signal data in the predefined array is temporarily stored through the change trend storage array for use in the third judgment process.

[0083] Please refer to Figure 2 , Figure 2 The flowchart of another EFT filtering method provided by an embodiment of the present invention is shown. As an embodiment of this embodiment, the specific steps of an EFT filtering method are as follows: input a new value (the new value is the latest collected signal data), use the new value to update n elements of the array and sum the latest n / 2 elements. Record the change trend of the new value and the previous value. Calculate the mean of the latest n / 2 signals, judge the change trend of the mean and the current signal effective value, when the change is less than the jump value, the signal effective value remains unchanged, and the EFT filtering algorithm ends. When the change is greater than the jump value, continue to execute the EFT filtering algorithm. Determine the change of the difference between the consecutive n / 2 latest values. When the change is small and within the tolerance value range, update the signal effective value to the mean of the latest n / 2 signals. When the change is large and exceeds the tolerance value, continue to execute the EFT filtering algorithm. Determine whether the changes of the n values ​​in the array are monotonous. When they are monotonically rising or falling, update the signal effective value to the mean of the latest n / 2 signals; when the change is not monotonous, continue to execute the EFT filtering algorithm. Determine the difference between the n values ​​in the array and the effective value of the signal and the tolerance value. When the difference between the n values ​​in the array and the effective value of the signal is greater than the tolerance value, update the effective value of the signal to the average of the most recent n / 2 signals; otherwise, keep the effective value of the signal unchanged. End the EFT filtering algorithm and filter out the EFT interference signal.

[0084] Figure 3 FIG. 1 is a block diagram of an EFT filtering processing system provided by one embodiment of the present invention. Figure 3 As shown, an embodiment of the present invention provides an EFT filtering processing system, comprising:

[0085] A signal data storage module, used for cyclically storing a first preset number of newly collected signal data into a predefined array;

[0086] A first signal change value calculation module, used to calculate a first signal change value between each signal data in a predefined array and the signal data collected at the previous adjacent moment;

[0087] A signal mean value calculation module, used to calculate the signal mean value of a second preset number of the most recently collected signal data;

[0088] A difference change judgment module is used to judge the difference change of a third preset number of consecutive and latest collected signal data to obtain a second signal change value;

[0089] The signal effective value determination module is used to determine the output signal effective value according to the signal mean value, the first signal change value, the second signal change value, the current signal effective value, the preset jump value and the preset tolerance value.

[0090] Specifically, the system first calculates the first signal change value between each signal data and the signal data collected at the previous moment, the signal mean value of the second preset number of the latest collected signal data, and the second signal change value of the third preset number of continuous and latest collected signal data based on the predefined array. Then, the difference between the signal mean value and the current signal effective value is compared with the preset jump value and the preset tolerance value to judge the change of the signal effective value and determine the output signal effective value, so as to achieve the filtering of the spikes generated when the signal is interfered by setting the preset jump value and the preset tolerance value, and thus achieve the filtering of the EFT signal.

[0091] The embodiment of the present invention further provides a machine-readable storage medium, on which instructions are stored. When the instructions are executed by the processor 100, the processor 100 is configured to execute the above-mentioned EFT filtering processing method.

[0092] Machine-readable storage media include permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0093] The embodiment of the present invention further provides an electronic device 10, which includes a memory 101, a processor 100, and a computer program 102 stored in the memory 101 and executable on the processor 100. When the processor 100 executes the computer program 102, the above-mentioned EFT filtering processing method is implemented.

[0094] like Figure 4 FIG. 1 is a schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 4 As shown, the electronic device 10 of this embodiment includes: a processor 100, a memory 101, and a computer program 102 stored in the memory 101 and executable on the processor 100. When the processor 100 executes the computer program 102, the steps in the above method embodiment are implemented. Alternatively, when the processor 100 executes the computer program 102, the functions of each module / unit in the above device embodiment are implemented.

[0095] Exemplarily, the computer program 102 may be divided into one or more modules / units, one or more modules / units are stored in the memory 101, and are executed by the processor 100 to complete the present invention. One or more modules / units may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program 102 in the terminal device 10. For example, the computer program 102 may be divided into a signal data storage module, a first signal change value calculation module, a signal mean value calculation module, a difference change judgment module, and a signal effective value determination module.

[0096] The electronic device 10 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 10 may include, but is not limited to, a processor 100 and a memory 101. Those skilled in the art will appreciate that Figure 4 It is only an example of the electronic device 10 and does not constitute a limitation of the electronic device 10. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0097] The processor 100 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0098] The memory 101 may be an internal storage unit of the electronic device 10, such as a hard disk or memory of the electronic device 10. The memory 101 may also be an external storage device of the electronic device 10, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 10. Further, the memory 101 may also include both an internal storage unit of the electronic device 10 and an external storage device. The memory 101 is used to store computer programs and other programs and data required by the electronic device 10. The memory 101 may also be used to temporarily store data that has been output or is to be output.

[0099] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0100] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program 102 products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program 102 product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0101] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program 102 products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by the computer program 102 instructions. These computer program 102 instructions can be provided to a processor 100 of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor 100 of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0102] These computer program 102 instructions may also be stored in a computer readable memory 101 that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory 101 produce an article of manufacture including an instruction device that implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0103] These computer program 102 instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0104] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0105] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. An EFT filtering processing method, characterized in that: include: Circularly storing a first preset number of newly acquired signal data into a predefined array; Calculating a first signal change value between each signal data in the predefined array and the signal data collected at the previous adjacent moment; Calculating a signal mean of a second preset number of the most recently collected signal data; Determine the difference change of a third preset number of consecutive and most recently collected signal data to obtain a second signal change value; The output signal effective value is determined according to the signal mean value, the first signal change value, the second signal change value, the current signal effective value, the preset jump value and the preset tolerance value.

2. The EFT filtering processing method according to claim 1, characterized in that: The step of determining the output signal effective value according to the signal mean value, the first signal change value, the second signal change value, the current signal effective value, the preset jump value and the preset tolerance value comprises: Perform a first judgment based on the absolute value of the difference between the signal mean value and the current signal effective value and a preset jump value; If the absolute value of the difference between the signal mean and the current signal effective value is less than the preset jump value, the output signal effective value is the current signal effective value; otherwise, a second judgment is performed based on the first signal change value, the second signal change value and the preset tolerance value.

3. The EFT filtering processing method according to claim 2, characterized in that: The performing a second judgment based on the first signal change value, the second signal change value and a preset tolerance value includes: If the second signal change value is smaller than the preset tolerance value, the output signal effective value is updated to the signal mean value; otherwise, a third judgment is performed based on the first signal change value.

4. The EFT filtering processing method according to claim 3, characterized in that: The performing a third judgment based on the first signal change value comprises: According to the first signal change value, determining a change trend between the corresponding signal data and the signal data collected at the previous moment; If the change trends corresponding to all signal data in the predefined array are consistent, the output signal effective value is updated to the signal mean; otherwise, a fourth judgment is performed based on the difference between each signal data in the predefined array and the current signal effective value and the preset tolerance value.

5. The EFT filtering processing method according to claim 4, characterized in that: The fourth determination based on the difference between each signal data in the predefined array and the current signal valid value and the preset tolerance value includes: If the differences between each signal data in the predefined array and the current signal effective value are all greater than the preset tolerance value, the output signal effective value is updated to the signal mean value; otherwise, the output signal effective value is the current signal effective value.

6. The EFT filtering processing method according to claim 4, characterized in that: The step of determining, according to the first signal change value, a change trend between the corresponding signal data and the signal data collected at the previous adjacent moment, comprises: Based on any first signal change value and a preset change trend table, the change trend between the corresponding signal data and the signal data collected at the previous adjacent moment is determined, wherein the preset change trend table stores the corresponding relationship between the size of the first signal change value and the change trend.

7. The EFT filtering processing method according to claim 4, characterized in that: Also includes: Define the storage array for changing trends; The change trend between any signal data in the predefined array and the corresponding signal data collected at the previous moment is stored in the change trend storage array.

8. An EFT filtering processing system, characterized in that: include: A signal data storage module, used for cyclically storing a first preset number of newly collected signal data into a predefined array; A first signal change value calculation module, used to calculate a first signal change value between each signal data in the predefined array and the signal data collected at the previous adjacent moment; A signal mean value calculation module, used to calculate the signal mean value of a second preset number of the most recently collected signal data; A difference change judgment module is used to judge the difference change of a third preset number of consecutive and latest collected signal data to obtain a second signal change value; The signal effective value determination module is used to determine the output signal effective value according to the signal mean value, the first signal change value, the second signal change value, the current signal effective value, the preset jump value and the preset tolerance value.

9. A machine-readable storage medium having instructions stored thereon, characterized in that: When the instruction is executed by a processor, the processor is configured to perform the EFT filtering processing method according to any one of claims 1 to 7.

10. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the EFT filtering processing method according to any one of claims 1 to 7 is implemented.

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