A data filtering method, system, device and storage medium based on analog quantity

Abstract

The present invention discloses a data filtering method, system, device and storage medium based on analog quantity, comprising: obtaining a sampled data signal collected by an ADC; performing amplitude limiting and de-jitter filtering on the sampled data signal collected by the ADC; performing sliding mean filtering on the sampled data signal after the amplitude limiting and de-jitter filtering, and outputting the sampled data signal after the sliding mean filtering, thereby completing high-precision real-time data filtering based on analog quantity. The method, system, device and storage medium can effectively filter out interference signals in the data signal, thereby ensuring the accuracy of data measurement and the real-time performance of the data.

Description

Technical Field

[0001] The present invention belongs to the field of data processing and relates to a data filtering method, system, device and storage medium based on analog quantity. Background Art

[0002] In thermal power plants, analog quantity acquisition is a crucial component of the DCS system. High-precision data acquisition is crucial, impacting the safe and reliable operation of the entire control system. The primary analog quantity collected in power plants is current and temperature. Due to the harsh plant environment, high-frequency interference signals can be present in the sampled current and temperature signals, causing sudden changes in the measured data. This can prevent accurate data sampling, severely impacting measurement accuracy and ensuring real-time data integrity.

[0003] In view of this situation, it is urgent to develop a data filtering method suitable for analog data acquisition in power plants, which can effectively filter out interference signals in actual signals, improve actual measurement accuracy, and ensure real-time data. Summary of the Invention

[0004] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a data filtering method, system, device and storage medium based on analog quantity, which can effectively filter out interference signals in data signals and ensure the accuracy of data measurement and the real-time performance of data.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] In one aspect, the present invention provides a data filtering method based on analog quantity, comprising:

[0007] Obtain the sampled data signal collected by ADC;

[0008] Perform amplitude limiting and de-jitter filtering on the sampled data signal collected by ADC;

[0009] The sampling data signal after the amplitude limiting and de-jittering filtering is subjected to sliding mean filtering, and the sampling data signal after the sliding mean filtering is output to complete high-precision real-time data filtering based on analog quantity.

[0010] The analog-based data filtering method of the present invention is further improved in that:

[0011] The specific process of limiting and de-jittering filtering the sampled data signal is as follows:

[0012] 21) Determine whether the difference between the current sampled data value and the sampled data value of the previous sampling period is greater than or equal to the limit debouncing threshold. When the difference between the current sampled data value and the sampled data value of the previous sampling period is less than or equal to the preset limit debouncing threshold, output the current sampled data value; otherwise, go to step 22);

[0013] 22) Determine whether the change direction of the current data sampling value is consistent with the change direction of the sampled data value of the previous sampling period. If the change direction of the current data sampling value is inconsistent with the change direction of the sampled data value of the previous sampling period, output the sampled data value of the previous sampling period; otherwise, go to step 23);

[0014] 23) Determine whether the number of changes in the direction of the sampled data values ​​of each sampling period within the most recent preset time period is greater than or equal to a preset anti-shake threshold. If the number of changes in the direction of the sampled data values ​​of each sampling period is less than or equal to the preset anti-shake threshold, output the sampled data value of the previous sampling period; otherwise, go to step 24);

[0015] 24) Determine whether the differences between the sampled data values ​​of the latest three sampling periods are all less than the preset limit anti-shake threshold. If the differences between the sampled data values ​​of the latest three sampling periods are all less than the preset limit anti-shake threshold, go to step 25). Otherwise, output the current sampled data value.

[0016] 25) Calculate the difference T1 between the current sampled data value and the sampled data value of the previous sampling period, and calculate the difference T2 between the sampled data value of the previous sampling period and the sampled data value of the previous sampling period. When the absolute value of the difference between T1 and T2 is greater than the preset rapid change value, and T1 is greater than or equal to 0, store the current data sampling value.

[0017] Before step 21), the method further includes: presetting a limit de-shaking threshold and a limit anti-shaking threshold.

[0018] The specific operation process of performing sliding mean filtering on the sampled data signal after the amplitude limiting and de-jittering filtering is as follows:

[0019] The first bit of the sampled data value stored in the memory is replaced by the limit de-jitter output value;

[0020] Compare the data sampling values ​​within the preset filter depth range;

[0021] The maximum and minimum values ​​of each data sampling value within the preset filter depth range are eliminated, the remaining data sampling values ​​are summed and averaged, and the summed and averaged result is output as the filtered sampling data signal.

[0022] In a second aspect of the present invention, the present invention provides a high-precision real-time data filtering system based on analog quantity, comprising:

[0023] An acquisition module is used to obtain the sampled data signal collected by the ADC;

[0024] A limiting and de-jittering filtering module is used to perform limiting and de-jittering filtering on the sampled data signal collected by the ADC;

[0025] The sliding mean filter module is used to perform sliding mean filtering on the sampled data signal after the limiting and de-jittering filtering, output the sampled data signal after the sliding mean filtering, and complete high-precision real-time data filtering based on analog quantity.

[0026] The high-precision real-time data filtering system based on analog quantity of the present invention is further improved in that:

[0027] The limiter de-jitter filter module includes:

[0028] A first judgment module is used to judge whether the difference between the current sampled data value and the sampled data value of the previous sampling period is greater than or equal to the limit debouncing threshold value, and output the current sampled data value when the difference between the current sampled data value and the sampled data value of the previous sampling period is less than or equal to the preset limit debouncing threshold value;

[0029] The second judgment module is used to judge whether the change direction of the current data sampling value is consistent with that of the sampled data value of the previous sampling period when the difference between the current data sampling value and the sampled data value of the previous sampling period is greater than the preset limit debouncing threshold value; when the change direction of the current data sampling value is inconsistent with that of the sampled data value of the previous sampling period, output the sampled data value of the previous sampling period;

[0030] a third judgment module, configured to, when the change direction of the current data sampling value is consistent with that of the sampling data value of the previous sampling period, determine whether the number of changes in the change direction of the sampling data values ​​of each sampling period in the most recent preset time period is greater than or equal to a preset anti-shake threshold; and output the sampling data value of the previous sampling period when the number of changes in the change direction of the sampling data values ​​of each sampling period is less than or equal to the preset anti-shake threshold;

[0031] a fourth determination module, configured to, when the number of changes in the direction of change of the sampled data value in each sampling period is greater than a preset anti-shake threshold, determine whether the differences between the sampled data values ​​in the most recent three sampling periods are all less than a preset clipping anti-shake threshold, and output the current sampled data value if the differences between the sampled data values ​​in the most recent three sampling periods are not all less than the preset clipping anti-shake threshold;

[0032] The fifth judgment module is used to calculate the difference T1 between the current sampling data value and the sampling data value of the previous sampling cycle when the difference between the sampling data values ​​of the most recent three sampling cycles is less than the preset limiting anti-shake threshold, and calculate the difference T2 between the sampling data value of the previous sampling cycle and the sampling data value of the previous sampling cycle. When the absolute value of the difference between T1 and T2 is greater than the preset rapid change value and T1 is greater than or equal to 0, the current data sampling value is stored.

[0033] The limiter de-jitter filter module also includes:

[0034] The preset module is used to preset the limit de-jitter threshold and the limit anti-jitter threshold.

[0035] The sliding mean filter module includes:

[0036] A replacement module is used to replace the first bit of the sampled data value stored in the memory with a limiting and de-jittering output value;

[0037] A comparison module, used to compare the data sampling values ​​within a preset filter depth range;

[0038] The data processing module is used to eliminate the maximum and minimum values ​​of each data sampling value within the preset filtering depth range, sum and average the remaining data sampling values, and then output the sum and average result as the filtered sampling data signal.

[0039] In a third aspect, the present invention provides a high-precision real-time data filtering device based on analog quantity, comprising:

[0040] memory for storing computer programs;

[0041] A processor is used to implement the steps of the analog-based data filtering method when executing the computer program.

[0042] In a fourth aspect of the present invention, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and is characterized in that when the computer program is executed by a processor, the steps of the analog-based data filtering method are implemented.

[0043] The present invention has the following beneficial effects:

[0044] During specific operation, the analog quantity-based data filtering method, system, device, and storage medium described in the present invention sequentially perform amplitude limiting and de-jitter filtering and sliding mean filtering on the sampled data signals collected by the ADC. By superimposing the two filtering algorithms, interference signals in the actual sampled signals can be effectively filtered out. The real-time performance of data sampling also meets the needs of the actual site, and the accuracy also meets the index requirements.

[0045] Furthermore, by setting the limit and de-jitter threshold, the interference signal in the actual signal can be effectively filtered out; by judging the change direction of the two adjacent sampling data values, the validity of the actual data can be judged, so as to quickly screen the effective signal and improve the real-time performance of the acquisition. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings, which constitute part of the present invention, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0047] Figure 1 is a flow chart of the present invention;

[0048] Figure 2 It is a structural schematic diagram of the present invention.

[0049] Among them, 1 is the acquisition module, 2 is the limiting and de-jittering filter module, 3 is the sliding mean filter module, 21 is the preset module, 22 is the first judgment module, 23 is the second judgment module, 24 is the third judgment module, 25 is the fourth judgment module, 26 is the fifth judgment module, 31 is the replacement module, 32 is the comparison module, and 33 is the data processing module. DETAILED DESCRIPTION

[0050] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions 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 embodiments described are only 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 making creative efforts should fall within the scope of protection of the present invention.

[0051] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0052] The present invention is described in further detail below with reference to the accompanying drawings:

[0053] As is known, due to the accuracy requirements of analog board measurements, the introduction of decimals must be avoided during the entire data acquisition and filtering calculation. Therefore, before data acquisition, the sampled data is amplified as a whole and processed as integer data.

[0054] refer to Figure 1 In this embodiment, the present invention provides a data filtering method based on analog quantity, which is used to overcome the problem in the prior art that due to the harsh power plant environment, high-frequency interference signals may exist in the sampled current value and temperature value signals, causing data to mutate, so as to improve the accuracy of data sampling and ensure the precision of data sampling. To this end, a method for filtering data using limiting de-jitter filtering and sliding mean filtering is provided to improve the accuracy of data sampling.

[0055] The specific real-time filtering method is that the filtering process is divided into two steps: the first step is to perform limiting and de-jittering filtering on the signal; the second step is to perform sliding mean filtering on the signal after limiting and de-jittering filtering, and the sampled data obtained after filtering is reported as the final output data.

[0056] The analog quantity-based data filtering method of the present invention comprises:

[0057] 1) Obtain the sampled data signal collected by ADC;

[0058] 2) Perform amplitude limiting and de-jitter filtering on the sampled data signal;

[0059] The specific operation process of step 2) is as follows:

[0060] 21) Preset limit de-shake threshold and anti-shake threshold;

[0061] 22) Determine whether the difference between the current sampled data value and the sampled data value of the previous sampling period is greater than or equal to the limit debouncing threshold. If the difference between the current sampled data value and the sampled data value of the previous sampling period is less than or equal to the preset limit debouncing threshold, output the current sampled data value; otherwise, go to step 23);

[0062] 23) Determine whether the change direction of the current data sampling value is consistent with the change direction of the sampled data value of the previous sampling period. If the change direction of the current data sampling value is inconsistent with the change direction of the sampled data value of the previous sampling period, output the sampled data value of the previous sampling period; otherwise, go to step 24);

[0063] 24) Determine whether the number of changes in the direction of the sampled data values ​​output in each sampling period within the most recent preset time period is greater than or equal to a preset anti-shake threshold. If the number of changes in the direction of the sampled data values ​​output in each sampling period is less than or equal to the preset anti-shake threshold, output the sampled data value of the previous sampling period; otherwise, go to step 25);

[0064] 25) Determine whether the differences between the sampled data values ​​of the current three sampling periods are all less than a preset limit anti-shake threshold. If the differences between the sampled data values ​​of the current three sampling periods are all less than or equal to the preset limit anti-shake threshold, go to step 26). Otherwise, output the current sampled data value.

[0065] 26) Calculate the difference T1 between the current sampled data value and the data value of the previous sampling period, and calculate the difference T2 between the sampled data value of the previous sampling period and the sampled data value of the previous sampling period. When the absolute value of the difference between T1 and T2 is greater than the preset rapid change value, and T1 is greater than or equal to 0, store the current data sampling value.

[0066] 3) Performing sliding mean filtering on the sampled data signal after the amplitude limiting and de-jittering filtering, and outputting the sampled data signal after the sliding mean filtering;

[0067] The specific operation process of step 3) is as follows:

[0068] 31) Replace the first bit of the sampled data value stored in the memory with the output value through amplitude limiting and debouncing;

[0069] 32) Compare the data sampling values ​​within the preset filter depth range;

[0070] 33) Eliminate the maximum and minimum values ​​of each data sampling value within the preset filter depth range, sum and average the remaining data sampling values, and then output the sum and average result as the filtered sampling data signal.

[0071] The present invention can effectively filter out interference signals existing in actual signals by setting a limiting and de-jittering threshold; and can judge the validity of actual data by judging the change direction of two adjacent data, so as to quickly screen out valid signals and improve the real-time performance of acquisition.

[0072] In addition, the present invention can effectively filter out interference signals in actual sampled signals through the superposition of two filtering algorithms. The real-time performance of data sampling also meets the needs of actual sites, and the accuracy also meets the index requirements.

[0073] Example 2

[0074] refer to Figure 2 The high-precision real-time data filtering system based on analog quantity of the present invention includes:

[0075] Acquisition module 1, used to obtain the sampled data signal collected by ADC;

[0076] The amplitude limiting and de-jittering filtering module 2 is used to perform amplitude limiting and de-jittering filtering on the sampled data signal collected by the ADC;

[0077] The sliding mean filtering module 3 is used to perform sliding mean filtering on the sampled data signal after the amplitude limiting and de-jittering filtering, output the sampled data signal after the sliding mean filtering, and complete high-precision real-time data filtering based on analog quantity.

[0078] The amplitude limiting and de-jittering filter module 2 includes:

[0079] A first judgment module 22 is configured to judge whether the difference between the current sampled data value and the sampled data value of the previous sampling period is greater than or equal to a limit debouncing threshold value, and output the current sampled data value when the difference between the current sampled data value and the sampled data value of the previous sampling period is less than or equal to a preset limit debouncing threshold value;

[0080] The second judgment module 23 is configured to determine whether the change direction of the current data sampling value is consistent with that of the sampling data value of the previous sampling period when the difference between the current data sampling value and the sampling data value of the previous sampling period is greater than a preset limit debouncing threshold value. If the change direction of the current data sampling value is inconsistent with that of the sampling data value of the previous sampling period, the sampling data value of the previous sampling period is output; otherwise, the process goes to step 23);

[0081] The third judgment module 24 is configured to, when the change direction of the current data sampling value is consistent with that of the sampling data value of the previous sampling period, determine whether the number of changes in the change direction of the sampling data values ​​of each sampling period in the most recent preset time period is greater than or equal to a preset anti-shake threshold, and output the sampling data value of the previous sampling period when the number of changes in the change direction of the sampling data values ​​of each sampling period is less than or equal to the preset anti-shake threshold;

[0082] a fourth determination module 25 configured to, when the number of changes in the direction of the sampled data values ​​in each sampling period exceeds a preset anti-shake threshold, determine whether the differences between the sampled data values ​​in the current three sampling periods are all less than a preset clipping anti-shake threshold; and output the current sampled data value if the differences between the sampled data values ​​in the current three sampling periods are not all less than the preset clipping anti-shake threshold;

[0083] The fifth judgment module 26 is used to calculate the difference T1 between the current sampling data value and the sampling data value of the previous sampling period, and calculate the difference T2 between the sampling data value of the previous sampling period and the sampling data value of the previous sampling period when the differences between the sampling data values ​​of the current three sampling periods are all less than the preset limiting anti-shake threshold. When the absolute value of the difference between T1 and T2 is greater than the preset rapid change value and T1 is greater than or equal to 0, the current data sampling value is stored.

[0084] The amplitude limiting and de-jittering filter module 2 also includes:

[0085] The preset module 21 is used to preset the amplitude limiting de-jitter threshold and the amplitude limiting anti-jitter threshold.

[0086] The sliding mean filter module 3 includes:

[0087] A replacement module 31 is used to replace the first bit of the sampled data value stored in the memory with a value output by limiting and de-jittering;

[0088] A comparison module 32 is used to compare the data sampling values ​​within a preset filtering depth range;

[0089] The data processing module 33 is used to remove the maximum and minimum values ​​of each data sampling value within the preset filtering depth range, sum and average the remaining data sampling values, and then output the sum and average result as the filtered sampling data signal.

[0090] Example 3

[0091] A computer device comprises 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 steps of the analog quantity-based data filtering method are implemented.

[0092] Example 4

[0093] A computer-readable storage medium stores a computer program, which implements the steps of the analog-based data filtering method when executed by a processor.

[0094] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A data filtering method based on analog quantity, characterized in that: include: Obtain the sampled data signal collected by ADC; Perform amplitude limiting and de-jitter filtering on the sampled data signal collected by ADC; Perform sliding mean filtering on the sampled data signal after amplitude limiting and de-jittering filtering, output the sampled data signal after sliding mean filtering, and complete high-precision real-time data filtering based on analog quantity; The specific process of limiting and de-jittering the sampled data signal collected by the ADC is as follows: 21) Determine whether the difference between the current sampled data value and the sampled data value of the previous sampling period is greater than a preset limit debouncing threshold. When the difference between the current sampled data value and the sampled data value of the previous sampling period is less than or equal to the preset limit debouncing threshold, output the current sampled data value. Otherwise, go to step 22); 22) Determine whether the change direction of the current sampled data value is consistent with that of the sampled data value of the previous sampling period. If the change direction of the current sampled data value is inconsistent with that of the sampled data value of the previous sampling period, output the sampled data value of the previous sampling period. Otherwise, go to step 23); 23) Determine whether the number of changes in the direction of the sampled data values ​​of each sampling period within the most recent preset time period is greater than a preset anti-shake threshold. When the number of changes in the direction of the sampled data values ​​of each sampling period is less than or equal to the preset anti-shake threshold, output the sampled data value of the previous sampling period. Otherwise, go to step 24); 24) Determine whether the differences between the sampled data values ​​of the latest three sampling periods are all less than the preset limit debouncing threshold. If the differences between the sampled data values ​​of the latest three sampling periods are all less than the preset limit debouncing threshold, go to step 25). Otherwise, output the current sampled data value. 25) Calculate the difference T1 between the current sampled data value and the sampled data value of the previous sampling period, and calculate the difference T2 between the sampled data value of the previous sampling period and the sampled data value of the previous sampling period. When the absolute value of the difference between T1 and T2 is greater than the preset rapid change value, and T1 is greater than or equal to 0, store the current sampled data value.

2. The data filtering method based on analog quantity according to claim 1, characterized in that: Before step 21), the method further includes setting a preset amplitude limiting de-shake threshold and a preset anti-shake threshold.

3. The data filtering method based on analog quantity according to claim 1, characterized in that: The specific operation process of performing sliding mean filtering on the sampled data signal after the amplitude limiting and de-jittering filtering is as follows: The first bit of the sampled data value stored in the memory is replaced by the limit de-jitter output value; Compare the sampled data values ​​within the preset filter depth range; The maximum and minimum values ​​of each sampled data value within the preset filter depth range are eliminated, the remaining sampled data values ​​are summed and averaged, and the summed and averaged result is output as the filtered sampled data signal.

4. A high-precision real-time data filtering system based on analog quantity, characterized in that: include: An acquisition module (1) is used to acquire the sampled data signal collected by the ADC; A limiting and de-jittering filtering module (2) is used to perform limiting and de-jittering filtering on the sampled data signal collected by the ADC; A sliding mean filtering module (3) is used to perform sliding mean filtering on the sampled data signal after the amplitude limiting and de-jittering filtering, output the sampled data signal after the sliding mean filtering, and complete high-precision real-time data filtering based on analog quantity; The amplitude limiting and de-jittering filter module (2) includes: A first judgment module (22) is used to judge whether the difference between the current sampled data value and the sampled data value of the previous sampling period is greater than a preset limit debouncing threshold, and output the current sampled data value when the difference between the current sampled data value and the sampled data value of the previous sampling period is less than or equal to the preset limit debouncing threshold; A second judgment module (23) is used to judge whether the change direction of the current sampled data value is consistent with that of the sampled data value of the previous sampling period when the difference between the current sampled data value and the sampled data value of the previous sampling period is greater than a preset limit debouncing threshold value, and output the sampled data value of the previous sampling period when the change direction of the current sampled data value is inconsistent with that of the sampled data value of the previous sampling period; A third judgment module (24) is used to judge whether the number of changes in the direction of the sampling data value of each sampling period in the most recent preset time period is greater than a preset anti-shake threshold when the change direction of the current sampling data value is consistent with the change direction of the sampling data value of the previous sampling period, and output the sampling data value of the previous sampling period when the number of changes in the direction of the sampling data value of each sampling period is less than or equal to the preset anti-shake threshold; A fourth judgment module (25) is used to judge whether the difference between the sampled data values ​​of the latest three sampling periods is less than the preset limit de-jitter threshold when the number of changes in the change direction of the sampled data value of each sampling period is greater than the preset de-jitter threshold, and output the current sampled data value when the difference between the sampled data values ​​of the latest three sampling periods is not less than the preset limit de-jitter threshold; The fifth judgment module (26) is used to calculate the difference T1 between the current sampling data value and the sampling data value of the previous sampling period, and calculate the difference T2 between the sampling data value of the previous sampling period and the sampling data value of the previous sampling period when the difference between the sampling data values ​​of the latest three sampling periods is less than the preset limit debouncing threshold value. When the absolute value of the difference between T1 and T2 is greater than the preset rapid change value, and T1 is greater than or equal to 0, the current sampling data value is stored.

5. The high-precision real-time data filtering system based on analog quantity according to claim 4 is characterized in that: The amplitude limiting and de-jittering filter module (2) also includes: The preset module (21) is used to set a preset amplitude limiting de-shaking threshold and a preset anti-shake threshold.

6. The high-precision real-time data filtering system based on analog quantity according to claim 4 is characterized in that: The sliding mean filter module (3) includes: A replacement module (31) is used to replace the first bit of the sampled data value stored in the memory by a limiting and de-jittering output value; A comparison module (32) is used to compare the sampled data values ​​within a preset filter depth range; The data processing module (33) is used to remove the maximum and minimum values ​​of each sampled data value within a preset filtering depth range, sum and average the remaining sampled data values, and then output the sum and average result as a filtered sampled data signal.

7. A high-precision real-time data filtering device based on analog quantity, characterized in that: include: memory for storing computer programs; A processor is configured to implement the steps of the analog quantity-based data filtering method according to any one of claims 1 to 3 when executing the computer program.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the analog quantity-based data filtering method according to any one of claims 1 to 3 are implemented.

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