Automatic control method for wet desulfurization slurry circulation pump

Abstract

The present invention relates to the field of automatic control technology, and more specifically, to an automatic control method for a wet flue gas desulfurization slurry circulation pump, the method comprising: obtaining a preset local range of a data point in three flow data time series sequences of sulfur dioxide, replacing the data point in the preset local range by an interpolation method, and obtaining a reference local range of the data point; obtaining the noise level of the data point by the difference between the flow value and the fitting value of the data point in the preset local range and the reference local range, and the difference between the flow data time series sequences; dividing the flow data time series sequence into a plurality of data segments by the noise level of the data point in a Fisher optimal solution method, setting a sliding window based on the size of the obtained sliding window to denoise the flow data time series sequence, and determining the slurry flow required by the slurry circulation pump to realize automatic control of the slurry circulation pump, thereby effectively improving the accuracy of automatic control of the slurry circulation pump.

Description

Technical Field

[0001] The present invention relates to the field of automatic control technology, and more specifically, to an automatic control method for a wet desulfurization slurry circulation pump. Background Art

[0002] Wet desulfurization is an environmentally friendly technology, mainly used to remove sulfur dioxide from fuels such as coal and fuel oil to reduce atmospheric pollutant emissions. During the wet desulfurization process, the slurry circulation pump continuously circulates the desulfurization slurry in the absorption tower to ensure that the sulfur dioxide in the flue gas can be completely absorbed. In order to ensure the desulfurization efficiency, it is necessary to determine the slurry flow required for desulfurization through the key parameters in the desulfurization process to achieve automatic control of the slurry circulation pump.

[0003] There are many studies on the control methods of circulating pumps in the prior art, and most of them realize automatic control of circulating pumps by analyzing the characteristics of their flow data. For example, the patent application document with publication number CN114281042A discloses an energy-saving control method and device for a wet desulfurization circulation system. The application automatically calculates the amount of theoretical reducing agent according to the total amount of sulfur dioxide removed by the wet desulfurization device or the flue gas volume at the inlet of the desulfurization device, the sulfur dioxide concentration in the inlet flue gas, the outlet flue gas volume, and the sulfur dioxide emission concentration value in the outlet flue gas; and automatically adjusts the frequency of the circulating pump according to the sulfur dioxide emission concentration value in the outlet flue gas to achieve the best energy-saving effect.

[0004] The existing technology can control the circulation pump by obtaining the flow data of sulfur dioxide. However, when collecting the flow data of sulfur dioxide, noise data may exist in the flow data due to interference from the collection environment, thereby affecting the accuracy of the circulation pump control and failing to achieve the best energy-saving effect.

[0005] Based on this, how to accurately remove the noise interference in the flow data so as to accurately realize the automatic control of the slurry circulation pump is an urgent problem to be solved by those skilled in the art. Summary of the invention

[0006] In order to solve the above technical problem of how to accurately remove the noise interference in the flow data and thus accurately realize the automatic control of the slurry circulation pump, the present invention proposes a wet desulfurization slurry circulation pump automatic control method, the method comprising the following steps:

[0007] Obtain the preset local range of the data point in the three flow data time series of sulfur dioxide, replace the data point in the preset local range by interpolation method, and obtain the reference local range of the data point; perform curve fitting on the flow values ​​of the data points in the preset local range and the reference local range respectively, and obtain the initial noise level of the data point by the difference between the flow value and the fitting value; make a difference between each data point in a flow data time series and the corresponding data point in the other two flow data time series, and obtain the mean of the variance of the two difference time series, and use the product of the mean of the variance and the initial noise level of the data point as the variable input of the hyperbolic tangent function to obtain the noise level of the data point in the flow data time series; divide the flow data time series into multiple data segments by the noise level of the data point in the Fisher optimal solution method, and calculate the size of the sliding window in the data segment: ; In the formula, Indicates The size of the sliding window within a data segment, Indicates the size of the preset reference window. Indicates The mean noise level of the data points in the data segment, Indicates the rounding down symbol; the sliding window is set based on the size of the sliding window, and after denoising the flow data time series, the slurry flow required by the slurry circulation pump is determined to achieve automatic control of the slurry circulation pump.

[0008] The present invention can accurately obtain the initial noise level of each data point by obtaining the deviation between the actual flow value and the fitting value of each data point in the sulfur dioxide flow data time series sequence. On this basis, the present invention takes into account that the initial noise level cannot distinguish between normal data changes and noise data, and therefore corrects the initial noise level by obtaining the consistency between the flow data time series sequences, thereby effectively improving the accuracy of the slurry circulation pump control; in addition, the present invention also takes into account that the noise data in the flow data time series sequence appears randomly, and therefore calculates the filter window in each segment after data segmentation to achieve accurate data denoising, thereby effectively improving the accuracy of the flow data time series sequence denoising, thereby effectively improving the accuracy of the automatic control of the slurry circulation pump.

[0009] According to a wet flue gas desulfurization slurry circulation pump automatic control method provided by the present invention, the preset local range of the data points in the three flow data time series of sulfur dioxide is obtained, including: three collection devices are arranged around the middle position point of the flue, and three flow values ​​are collected at each moment, and finally three flow data time series of sulfur dioxide are obtained; the size of the preset local range is obtained , taking the data point as the center, obtain equal amounts on both sides of the data point data points constitute the preset local range of the data point.

[0010] The present invention constructs a preset local range of a data point by acquiring a number of data points equally on both sides of the data point, and can simultaneously consider the change of local data on both sides of the data point, thereby accurately obtaining the fluctuation of the data point.

[0011] According to an automatic control method for a wet desulfurization slurry circulation pump provided by the present invention, curve fitting is performed on the flow values ​​of data points in a preset local range and a reference local range respectively, including: taking the time series number of the data point in the preset local range or the reference local range as the horizontal coordinate and taking the flow value of the data point as the vertical coordinate, performing curve fitting to obtain the fitting value corresponding to each data point in the preset local range or the reference local range.

[0012] According to a method for automatically controlling a wet desulfurization slurry circulation pump provided by the present invention, the initial noise level of a data point is obtained by the difference between a flow value and a fitting value, comprising: recording the absolute value cumulative sum of the difference between the flow value and the fitting value of a data point in a preset local range of the data point as a first indicator; recording the absolute value cumulative sum of the difference between the flow value and the fitting value of a data point in a reference local range as a second indicator; and recording the ratio of the absolute value of the difference between the first indicator and the second indicator to the size of the preset local range of the data point as the initial noise level of the data point.

[0013] The present invention can obtain the data fluctuation situation of the data point in a preset local range through the data fluctuation situation of the data point, and the noise generally appears as a prominent point in the local range. The greater the noise level of the data point in the local range, the greater the destructiveness to the data change in the local range. The noise level of the data point can be accurately obtained by the degree of damage of the data point to the entire local range.

[0014] According to a wet flue gas desulfurization slurry circulation pump automatic control method provided by the present invention, the sliding window is set based on the size of the sliding window, and after the flow data time series sequence is denoised, the slurry flow required by the slurry circulation pump is determined, including: removing the data points corresponding to the flow values ​​in the sliding window that are greater than the preset noise threshold to obtain the denoised flow data time series sequence; taking the average of the data points in the three flow data time series sequences after filtering and denoising at each moment as the actual flow value at that moment; calculating the slurry flow required by the slurry circulation pump: ; In the formula, represents the slurry flow rate required by the slurry circulation pump at the i-th moment, represents the actual flow value at the i-th moment, Indicates the preset desulfurization efficiency target, Indicates the preset liquid-gas ratio.

[0015] According to a method for automatic control of a wet flue gas desulfurization slurry circulation pump provided by the present invention, the automatic control of the slurry circulation pump comprises: obtaining a deviation signal through the deviation between the slurry flow rate of the slurry circulation pump at the current moment and the required slurry flow rate; inputting the deviation signal into a PID control system to adjust the rotation speed of the slurry circulation pump to achieve the slurry flow rate required by the slurry circulation pump.

[0016] According to a method for automatic control of a wet flue gas desulfurization slurry circulation pump provided by the present invention, the automatic control of the slurry circulation pump is realized, and then the method further includes: abnormal monitoring of the control process of the slurry circulation pump, and if the slurry flow required by the slurry circulation pump exceeds a preset abnormal threshold, an early warning is issued.

[0017] The present invention takes into account that the slurry circulation pump is an important device in the desulfurization system, and its operating state directly affects the desulfurization efficiency of the system. During the automatic control process, if the circulation pump is abnormal, such as insufficient flow, abnormal pressure, etc., it may cause a decrease in desulfurization efficiency and even affect the stable operation of the entire system. Therefore, the automatic control process of the slurry circulation pump can be abnormally detected to reduce safety hazards.

[0018] According to a method for automatically controlling a wet desulfurization slurry circulation pump provided by the present invention, the issuing of an early warning further includes: collecting data during desulfurization at preset time intervals and establishing a desulfurization abnormality parameter database; wherein the parameter data includes the sulfur dioxide flow data corresponding to each moment and the slurry flow required by the slurry circulation pump.

[0019] The present invention can understand whether the operating status of the desulfurization system and the working performance of the slurry circulation pump change over time by performing trend analysis on the collected data, so that potential abnormal situations can be discovered in time and corresponding preventive measures can be taken.

[0020] The present invention has the following beneficial effects:

[0021] Based on the above technical scheme, when the present invention realizes the automatic control of the wet flue gas desulfurization slurry circulation pump, the initial noise level of each data point can be accurately obtained by obtaining the deviation between the actual flow value and the fitting value of each data point in the flow data time series sequence of sulfur dioxide. On this basis, the present invention takes into account that the initial noise level cannot distinguish between normal data changes and noise data, and therefore corrects the initial noise level by obtaining the consistency between the flow data time series sequences, thereby effectively improving the accuracy of the slurry circulation pump control; in addition, the present invention also takes into account that the noise data in the flow data time series sequence appears randomly, and therefore, through data segmentation, the filter window in each segment is calculated to achieve accurate data denoising, which effectively improves the accuracy of the flow data time series sequence denoising, thereby effectively improving the accuracy of the automatic control of the slurry circulation pump. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0023] Figure 1 A schematic flow chart of an automatic control method for a wet desulfurization slurry circulation pump provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0025] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0026] It should be noted that during the wet desulfurization process, the slurry circulation pump continuously circulates the desulfurization slurry in the absorption tower to ensure that the sulfur dioxide in the flue gas can be completely absorbed. In order to ensure the desulfurization efficiency, the slurry flow rate required by the slurry circulation pump can be determined by collecting the flow data of sulfur dioxide during the desulfurization process to achieve automatic control of the slurry circulation pump.

[0027] However, when collecting sulfur dioxide flow data, there may be noise data, which will affect the accuracy of circulating pump control.

[0028] Based on this, the embodiment of the present invention discloses a method for automatically controlling a wet flue gas desulfurization slurry circulation pump. The method obtains the noise level of each data point in the sulfur dioxide flow data sequence, segments the data according to the noise level, and accurately obtains the size of the filter window in each data segment based on the noise level of the data point in each data segment, thereby achieving accurate denoising of the data points in each data segment and effectively improving the accuracy of the automatic control of the wet flue gas desulfurization slurry circulation pump. For details, please refer to Figure 1 As shown, Figure 1 A schematic flow chart of a method for automatically controlling a wet desulfurization slurry circulation pump is provided in an embodiment of the present invention. The method specifically comprises the following steps S1 to S5.

[0029] S1: Obtain a preset local range of a data point in three flow data time series of sulfur dioxide, replace the data point in the preset local range using an interpolation method, and obtain a reference local range of the data point.

[0030] The interpolation method may be a cubic spline interpolation method; the interpolation method may be specifically set according to actual needs, and the embodiment of the present invention does not impose too many restrictions here. The specific steps of replacing data points by interpolation method to obtain the reference local range of data points can be implemented by existing technologies, and the embodiment of the present invention will not be repeated here.

[0031] For example, the size of the preset local range can be set to 15; the size of the preset local range is the number of data points contained in the preset local range. The size of the preset local range can be set to an odd number, which can be set according to actual needs. The embodiment of the present invention does not impose too many restrictions on this.

[0032] It should be noted that the flue gas flow data in the wet flue gas desulfurization process is easily interfered by noise during the collection process. If the slurry flow is directly calculated using the collected flue gas flow data, the accuracy of the obtained slurry flow is low, which leads to low accuracy of automatic control of the slurry circulation pump. Therefore, it is necessary to denoise the collected flue gas flow data. However, the use of a fixed-size filter window in the traditional denoising algorithm leads to over-smoothing or under-smoothing problems when filtering the flow data, and the denoising effect is poor.

[0033] Based on this, the embodiment of the present invention obtains the noise level by analyzing the data fluctuation performance of each data point in the flow data in its local range, and determines the size of the filter window according to the noise level to achieve accurate control of the slurry circulation pump.

[0034] For example, in an embodiment of the present invention, obtaining a preset local range of data points in three flow data time series of sulfur dioxide includes: arranging three collection devices around the middle position of the flue, collecting three flow values ​​at each moment, and finally obtaining three flow data time series of sulfur dioxide; obtaining the size of the preset local range , taking the data point as the center, and obtaining equal amounts on both sides of the data point data points constitute the preset local range of the data point.

[0035] For example, the collection device may be a flue gas flow monitor, and the sampling frequency may be set to 0.1 Hz. The collection device and the sampling frequency may be set according to actual needs, and the embodiment of the present invention does not impose too many restrictions thereon.

[0036] Specifically, at the same time, three flow values ​​can be obtained at the middle position of the flue through the collection device, each flow value is used as a data point, and the data points collected by each collection device are arranged in time series to obtain the flow data time series sequence corresponding to the collection device.

[0037] In this way, the embodiment of the present invention acquires a number of data points equally on both sides of the data point to construct a preset local range of the data point, and can simultaneously consider the data changes on both sides of the data point, thereby accurately obtaining the fluctuation of the data point.

[0038] For example, in the embodiment of the present invention, the preset local range of the data point is obtained, and it is also possible to: take the data point as the end and obtain the historical data of the data point. data points constitute the preset local range of the data point.

[0039] When obtaining the preset local range of a data point, if the number of data points around the data point is insufficient to construct the preset local range of the data point, the actual number of data points around the data point is used as the preset local range of the data point.

[0040] In this way, the embodiment of the present invention constructs a preset local range of a data point by acquiring historical data of the data point, thereby reducing data waiting time and being able to obtain fluctuations of the data point in a timely and accurate manner directly based on data changes in the historical range.

[0041] Based on the above steps, the preset local range and the reference local range of each data point can be obtained, and the noise level of the data point can be obtained by analyzing the change characteristics of the data point in the preset local range and the reference local range respectively. The embodiment of the present invention is described by analyzing the noise level of a data point in a flow data time series sequence as an example, but it does not mean that the embodiment of the present invention is limited to this.

[0042] S2: curve fitting is performed on the flow values ​​of the data points in the preset local range and the reference local range respectively, and the initial noise level of the data points is obtained through the difference between the flow value and the fitting value.

[0043] It should be noted that the data fluctuation situation of the data point in a preset local range can be used to obtain the data fluctuation situation, and the noise generally appears as a prominent point in the local range. The greater the noise level of the data point in the local range, the more destructive it is to the data change in the local range. The noise level of the data point can be obtained by the degree of damage the data point has on the entire local range.

[0044] Based on this, the embodiment of the present invention obtains the destructiveness of the data point by obtaining the difference between the data fluctuation change in the preset local range of the data point and the reference local range.

[0045] By way of example, in an embodiment of the present invention, curve fitting is performed on the flow values ​​of data points in a preset local range and a reference local range, respectively, including: taking the time series number of the data points in the preset local range or the reference local range as the horizontal coordinate and taking the flow value of the data point as the vertical coordinate, performing curve fitting to obtain the fitting value corresponding to each data point in the preset local range or the reference local range.

[0046] It is understandable that by processing the actual change of data in the preset local range of the data point by interpolation method, the reference local range of the data point can be determined, and the degree of damage to the data change caused by the data point can be obtained by the data deviation between the reference local range and the preset local range. Based on this, the embodiment of the present invention accurately obtains the noise level of the data point by analyzing the error change in the curve fitting process of the preset local range and the reference local range of the data point.

[0047] By way of example, in an embodiment of the present invention, the initial noise level of a data point is obtained by the difference between the flow value and the fitting value, including: recording the absolute value of the difference between the flow value and the fitting value of the data point in a preset local range of the data point as a first indicator; recording the absolute value of the difference between the flow value and the fitting value of the data point in a reference local range as a second indicator; and recording the ratio of the absolute value of the difference between the first indicator and the second indicator to the size of the preset local range of the data point as the initial noise level of the data point.

[0048] For example, in the embodiment of the present invention, the initial noise level of the data point is determined, and specifically, the following relationship can be referred to:

[0049] ;

[0050] In the formula, represents the initial noise level of the ith data point, represents the number of data points in the preset local range or reference local range of the i-th data point, represents the fitted value of the jth data point in the preset local range of the i-th data point, represents the flow value of the jth data point in the preset local range of the i-th data point, represents the fitted value of the i-th data point with reference to the j-th data point in the local range, It indicates the flow value of the i-th data point in reference to the j-th data point in the local range, Represents the absolute value symbol.

[0051] In the above formula, Represents the first indicator. The larger the value, the greater the fitting error when the curve is fitted in the preset local range of the i-th data point. Represents the second indicator. The larger the value is, the greater the fitting error when the reference local range of the i-th data point is used for curve fitting, and the larger the gap between the first indicator and the second indicator is, indicating that the greater the fitting deviation when the preset local range of the i-th data point and the reference local range are used for curve fitting, the greater the degree of damage caused by the i-th data point to the data change in the local range, and the greater the corresponding noise level.

[0052] It can be understood that since the number of data points in the preset local range of each data point is not exactly the same, in order to facilitate the comparison of the noise level of each data point in the sulfur dioxide flow data time series on the same dimension, the embodiment of the present invention obtains the mean of the fitting deviation between the preset local range of the data point and the reference local range as the initial noise level of the data point, and continues to execute the following steps.

[0053] S3: Subtract each data point in a flow data time series sequence from the corresponding data point in the other two flow data time series sequences to obtain the mean of the variances of the two difference time series sequences, and use the product of the mean of the variances and the initial noise level of the data point as the variable input of the hyperbolic tangent function to obtain the noise level of the data point in the flow data time series sequence.

[0054] It should be noted that the initial noise level of the data point can be obtained by obtaining the fitting error deviation between the preset local range and the reference local range of the data point based on the above steps. However, in the process of wet desulfurization, factors such as the change in the inlet temperature of the sulfur dioxide flue gas pipeline will cause drastic changes in the sulfur dioxide flow data time series, which may result in the determination of the noise data point based on the initial noise level obtained in the above steps. Normally changing flow data may be determined as noise data, resulting in filtering errors.

[0055] Based on this, the embodiment of the present invention further obtains the other two flow data time series sequences corresponding to the flow data time series sequence where the current data point is located. When the data changes normally, the data changes between the three flow data time series sequences are consistent. The higher the consistency, the higher the possibility that the data change belongs to the normal data change. The initial noise level of the data point is corrected based on the consistency between the flow data time series sequences, and the real noise level of the data point can be accurately obtained.

[0056] For example, in the embodiment of the present invention, the noise level of a data point is determined, and specifically, the following relationship can be referred to:

[0057] ;

[0058] In the formula, represents the noise level of the ith data point, represents the initial noise level of the ith data point, , Respectively represent the variance of one and the other difference time series, represents the hyperbolic tangent function.

[0059] In the above formula, It represents the mean of the variance of two difference time series. The larger the value is, the worse the consistency between the traffic data time series is. The more likely it is that the change of data points in the traffic data time series is a noise change, the smaller the possibility of normal data change is, and the greater the noise level of the corresponding data points is.

[0060] The hyperbolic tangent function is used to obtain the normalized value of the correction result to facilitate subsequent data processing.

[0061] Based on the above steps, the noise level of each data point in the three flow data time series can be obtained. The size of the filter window is determined by the noise level of each data point, and accurate denoising of the flow data time series can be achieved, that is, continue to execute the following steps.

[0062] S4: In the Fisher optimal solution method, the traffic data time series is divided into multiple data segments according to the noise level of the data points, and the size of the sliding window in the data segment is calculated.

[0063] It should be noted that the data points in the traffic data time series are in a changing state, and the noise level is not evenly distributed, and there are local differences. Directly determining the filter window of the traffic data time series based on the noise level of the data points will cause the size of the filter window to be unable to adapt to complex data changes, resulting in insufficient or over-smoothing of the traffic data.

[0064] Based on this, in the Fisher optimal solution, the embodiment of the present invention divides the flow data time series into multiple data segments by the noise level of the data points, and the data noise levels in each data segment are relatively consistent. By determining the size of the filter window in each segment, the local characteristics of the data can be better preserved, while accurately smoothing the noise and avoiding over-smoothing or under-smoothing.

[0065] For example, when the traffic data time series sequence is divided into multiple data segments according to the noise level of the data points in the Fisher optimal solution method, the number of segments of the traffic data time series sequence can be preset to divide the traffic data time series sequence into multiple initial data segments; the loss function of the noise level of the data points in the initial data segments is calculated, all possible segmentation methods are traversed, and the segmentation method corresponding to the minimum loss function is determined to be the final segmentation method, and the traffic data time series sequence is divided into multiple data segments based on the final segmentation method.

[0066] For example, the number of segments of the preset traffic data time series sequence can be set according to actual needs, and the embodiment of the present invention does not impose too many restrictions on this.

[0067] The specific steps of performing data segmentation by using the Fisher optimal solution method can be implemented by the existing technology, and will not be described in detail in the embodiment of the present invention.

[0068] After the traffic data time series sequence is divided into multiple data segments based on the above steps, the size of the filtering sliding window in each data segment can be obtained according to the data noise performance in each data segment.

[0069] For example, in an embodiment of the present invention, the size of the sliding window in the data segment is determined, and the specific relationship can be as follows:

[0070] ;

[0071] In the formula, Indicates The size of the sliding window within a data segment, Indicates the size of the preset reference window. Indicates The mean noise level of the data points in the data segment, Indicates the floor symbol.

[0072] The size of the preset reference window may be set to 5. The size of the preset reference window may be set according to actual needs, and the embodiment of the present invention does not impose too many restrictions on this.

[0073] In this way, the embodiment of the present invention can achieve accurate denoising of the sulfur dioxide flow data time series sequence by obtaining the size of the sliding window of each data segment in the flow data time series sequence, and the slurry flow required by the slurry circulation pump can be accurately obtained based on the denoised flow data time series sequence.

[0074] S5: The sliding window is set based on the size of the sliding window, and after denoising the flow data time series, the slurry flow required by the slurry circulation pump is determined to achieve automatic control of the slurry circulation pump.

[0075] It should be noted that after obtaining the size of the sliding window of each data segment based on the above steps, accurate denoising of the flow data time series sequence can be achieved, and accurate control of the slurry circulation pump can be achieved based on the denoised flow data time series sequence.

[0076] By way of example, in an embodiment of the present invention, a sliding window is set based on the size of the sliding window, and after denoising the flow data time series sequence, the slurry flow required by the slurry circulation pump is determined, including: removing data points in the sliding window whose flow values ​​are greater than a preset noise threshold to obtain a denoised flow data time series sequence; taking the average of the data points in the three flow data time series sequences after filtering and denoising at each moment as the actual flow value at that moment; and calculating the slurry flow required by the slurry circulation pump.

[0077] For example, 60% of the difference between the maximum and minimum values ​​of all flow values ​​in a data segment can be used as the preset noise threshold in the data segment; the preset noise threshold can be set specifically according to actual needs, and the embodiments of the present invention do not impose too many restrictions on this.

[0078] After eliminating data points greater than the preset noise threshold based on the above steps, the flow value at the position of the noise data point can be supplemented by interpolation. The specific setting can be made according to actual needs, and the embodiment of the present invention will not be described in detail here.

[0079] For example, in an embodiment of the present invention, the slurry flow rate required by the slurry circulation pump is determined based on the denoised flow data time series sequence, and the specific details can be referred to the following relationship:

[0080] ;

[0081] In the formula, represents the slurry flow rate required by the slurry circulation pump at the i-th moment, represents the actual flow value at the i-th moment, Indicates the preset desulfurization efficiency target, Indicates the preset liquid-gas ratio.

[0082] Among them, the desulfurization efficiency target can be preset to 95%, and the liquid-gas ratio can be preset to 5:1; the desulfurization efficiency target and the liquid-gas ratio can be set according to actual needs, and the embodiment of the present invention does not impose too many restrictions here.

[0083] After obtaining the slurry flow rate required by the slurry circulation pump based on the above formula, the slurry flow rate required by the slurry circulation pump can be input into the slurry circulation pump to realize automatic control of the slurry circulation pump.

[0084] By way of example, in an embodiment of the present invention, the slurry flow rate required by the slurry circulation pump is determined to achieve automatic control of the slurry circulation pump, including: obtaining a deviation signal through the deviation between the slurry flow rate of the slurry circulation pump at a current moment and the required slurry flow rate; inputting the deviation signal into the PID regulation system to adjust the rotational speed of the slurry circulation pump to achieve the slurry flow rate required by the slurry circulation pump.

[0085] Specifically, when the deviation signal is input into the PID regulation system to adjust the rotational speed of the slurry circulation pump to achieve the slurry flow rate required by the slurry circulation pump, the deviation signal can be input into the PID control algorithm to obtain the output value of the controller, and the output value of the PID controller can be converted into a control signal and output to the actuator. The above steps are repeated until the slurry flow rate required by the slurry circulation pump is achieved.

[0086] It should be further explained that the slurry circulation pump is an important equipment in the desulfurization system, and its operating status directly affects the desulfurization efficiency of the system. During the automatic control process, if the slurry circulation pump has an abnormality, such as insufficient flow, abnormal pressure, etc., it may cause a decrease in desulfurization efficiency and even affect the stable operation of the entire system.

[0087] Based on this, it is necessary to perform abnormal detection on the automatic control process of the slurry circulation pump.

[0088] For example, in an embodiment of the present invention, automatic control of a slurry circulation pump is implemented, and then the method further includes: abnormal monitoring of the control process of the slurry circulation pump, and issuing an early warning if the slurry flow required by the slurry circulation pump exceeds a preset abnormal threshold.

[0089] The preset abnormal threshold value may be set according to actual needs, and the embodiment of the present invention does not impose too many limitations on this.

[0090] In this way, the embodiment of the present invention can detect and handle abnormalities in a timely manner by performing abnormality monitoring on the control process of the slurry circulation pump, thereby ensuring stable operation of the system.

[0091] For example, in an embodiment of the present invention, an early warning is issued, and then the following steps are included: collecting data in desulfurization at preset time intervals and establishing a desulfurization abnormality parameter database; wherein the parameter data includes the sulfur dioxide flow data corresponding to each moment and the slurry flow required by the slurry circulation pump.

[0092] Among them, the time interval can be preset to 3 hours; the time interval can be specifically set according to actual needs, and the embodiment of the present invention does not impose too many restrictions on this.

[0093] In this way, the embodiment of the present invention can understand whether the operating status of the desulfurization system and the working performance of the slurry circulation pump change over time by performing trend analysis on the collected data, so that potential abnormal situations can be discovered in time and corresponding preventive measures can be taken.

[0094] It can be seen that in the embodiment of the present invention, when realizing the automatic control of the wet flue gas desulfurization slurry circulation pump, the preset local range of the data point in the three flow data time series sequences of sulfur dioxide can be obtained, and the data point is replaced by the interpolation method in the preset local range to obtain the reference local range of the data point; the flow values ​​of the data points in the preset local range and the reference local range are respectively subjected to curve fitting, and the initial noise level of the data point is obtained by the difference between the flow value and the fitting value; each data point in a flow data time series sequence is subtracted from the corresponding data point in the other two flow data time series sequences to obtain the mean of the variance of the two difference time series sequences, and the product of the mean of the variance and the initial noise level of the data point is used as the variable input of the hyperbolic tangent function to obtain the noise level of the data point in the flow data time series sequence; in the Fisher optimal solution method, the flow data time series sequence is divided into multiple data segments according to the noise level of the data point, and the size of the sliding window in the data segment is calculated; the sliding window is set based on the size of the sliding window, and after the flow data time series sequence is denoised, the slurry flow required by the slurry circulation pump is determined to realize the automatic control of the slurry circulation pump.

[0095] It can be seen that in the embodiment of the present invention, the initial noise level of each data point can be accurately obtained by obtaining the deviation between the actual flow value and the fitting value of each data point in the sulfur dioxide flow data time series sequence. On this basis, the embodiment of the present invention takes into account that the initial noise level cannot distinguish between normal data changes and noise data, and therefore corrects the initial noise level by obtaining the consistency between the flow data time series sequences, thereby effectively improving the accuracy of the slurry circulation pump control; in addition, the embodiment of the present invention also takes into account that the noise data in the flow data time series sequence appears randomly, and therefore through data segmentation, the filter window in each data segment is calculated to achieve accurate data denoising, which effectively improves the accuracy of the flow data time series sequence denoising, thereby effectively improving the accuracy of the automatic control of the slurry circulation pump.

[0096] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A wet desulfurization slurry circulation pump automatic control method, characterized in that: include: Obtaining a preset local range of data points in three flow data time series of sulfur dioxide, wherein obtaining the preset local range of data points in three flow data time series of sulfur dioxide includes: Three collection devices are arranged around the middle point of the flue to collect three flow values ​​at each moment, and finally three flow data time series of sulfur dioxide are obtained; The size T of the preset local range is obtained, and (T-1) / 2 data points are equally obtained on both sides of the data point with the data point as the center to form the preset local range of the data point; The data point is replaced by an interpolation method in a preset local range to obtain a reference local range of the data point; the flow values ​​of the data points in the preset local range and the reference local range are respectively subjected to curve fitting, and the initial noise level of the data point is obtained by the difference between the flow value and the fitting value, wherein the initial noise level of the data point is obtained by the difference between the flow value and the fitting value, including: The absolute value cumulative sum of the difference between the flow value of the data point and the fitting value in the preset local range of the data point is recorded as the first indicator; the absolute value cumulative sum of the difference between the flow value of the data point and the fitting value in the reference local range is recorded as the second indicator; the ratio of the absolute value of the difference between the first indicator and the second indicator to the size of the preset local range of the data point is recorded as the initial noise level of the data point; Subtract each data point in a flow data time series from the corresponding data point in the other two flow data time series to obtain the mean of the variance of the two difference time series, and use the product of the mean of the variance and the initial noise level of the data point as the variable input of the hyperbolic tangent function to obtain the noise level of the data point in the flow data time series; In the Fisher optimal solution, the traffic data time series is divided into multiple data segments according to the noise level of the data points, and the size of the sliding window in the data segment is calculated: ; In the formula, Indicates The size of the sliding window within a data segment, Indicates the size of the preset reference window. Indicates The mean noise level of the data points in a data segment, Indicates the floor symbol; The sliding window is set based on its size, and after denoising the flow data time series, the slurry flow required by the slurry circulation pump is determined to achieve automatic control of the slurry circulation pump.

2. The automatic control method for a wet desulfurization slurry circulation pump according to claim 1 is characterized in that: The curve fitting of the flow values ​​of the data points in the preset local range and the reference local range respectively includes: The time series number of the data point in the preset local range or the reference local range is used as the horizontal coordinate, and the flow value of the data point is used as the vertical coordinate to perform curve fitting to obtain the fitting value corresponding to each data point in the preset local range or the reference local range.

3. The automatic control method for a wet desulfurization slurry circulation pump according to claim 1 is characterized in that: The method of setting the sliding window based on the size of the sliding window and denoising the flow data time series to determine the slurry flow required by the slurry circulation pump includes: Eliminate the data points in the sliding window whose flow values ​​are greater than the preset noise threshold to obtain the denoised flow data time series; The mean of the data points in the three flow data time series after filtering and denoising at each moment is taken as the actual flow value at that moment; the slurry flow required by the slurry circulation pump is calculated: ; In the formula, represents the slurry flow rate required by the slurry circulation pump at the i-th moment, represents the actual flow value at the i-th moment, Indicates the preset desulfurization efficiency target, Indicates the preset liquid-gas ratio.

4. The automatic control method for a wet desulfurization slurry circulation pump according to claim 1 is characterized in that: The automatic control of the slurry circulation pump includes: A deviation signal is obtained by the deviation between the slurry flow rate of the slurry circulation pump at the current moment and the required slurry flow rate; the deviation signal is input into the PID control system to adjust the speed of the slurry circulation pump to achieve the slurry flow rate required by the slurry circulation pump.

5. The automatic control method for a wet desulfurization slurry circulation pump according to claim 1 is characterized in that: The method for realizing automatic control of the slurry circulation pump further comprises: The control process of the slurry circulation pump is monitored for abnormalities. If the slurry flow required by the slurry circulation pump exceeds the preset abnormal threshold, an early warning is issued.

6. The automatic control method for a wet desulfurization slurry circulation pump according to claim 5 is characterized in that: The said issuing of a warning to the outside may also include: The data in desulfurization are collected at preset time intervals to establish a database of abnormal desulfurization parameters; wherein the parameter data include the sulfur dioxide flow data corresponding to each moment and the slurry flow required by the slurry circulation pump.

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