A method and system for automatically controlling water flow to clean pollution

Abstract

The present application relates to a kind of water cleaning automatic control method and system;The method of the present application includes: step S1. The pressure difference value generated by the water level difference before and after the trash rack of the water intake of hydropower station, when the pressure difference value reaches the pressure difference threshold, start cleaning machine;Step S2. By using fuzzy control intelligent control algorithm, the depth u of cleaning machine is calculated, the underwater depth C1 that cleaning machine needs to drop to is obtained, C1=u+D, D is the height of the original cleaning machine from water surface;Step S3. Control cleaning machine to drop, and simultaneously control cleaning machine to open rake, when cleaning machine reaches C1 position, control cleaning machine to close rake, simultaneously adjust D to C1;Step S4. Rake is lifted to height C1;Step S5. Compare C1 and the height C2 of cleaning platform to the elevation of trash rack bottom;Step S6. If C2>C1, then cycle step S2-S5, until C2≤C1;If C2≤C1, then it indicates that the cleaning task has been completed, and cleaning machine is closed.The present application realizes the full-automatic water cleaning of the water intake of hydropower station.

Description

Technical Field

[0001] This invention relates to the field of cleaning machines for hydropower stations, and in particular to a fully automatic control method and system for cleaning debris in moving water. Background Technology

[0002] Existing technology has achieved motorized water cleaning for hydroelectric cleaning, but it still requires manual judgment and operation of the entire cleaning process to ultimately complete the cleaning work at the hydroelectric power station's intake. Furthermore, most hydroelectric power stations currently still use still water cleaning. With technological advancements, the development trend for small and medium-sized hydroelectric power stations is towards intelligent hydroelectric power stations. A prerequisite for intelligent hydroelectric power stations is automated judgment and control. Therefore, research into automated cleaning using motorized cleaning machines is imperative to adapt to this development trend. Summary of the Invention

[0003] The purpose of this invention is to adapt to the intelligent development trend of small and medium-sized hydropower stations, solve the problem of automated cleaning of water intakes in hydropower stations, free up labor, and develop a fully automatic control device for cleaning water in flowing water.

[0004] To achieve the above objectives, the present invention is implemented through the following technical solution.

[0005] This invention proposes a fully automatic control method for cleaning and decontaminating moving water. This method utilizes a cleaning machine to clean and decontaminate the water at the intake of a hydropower station. The method includes:

[0006] Step S1. Determine the pressure difference caused by the water level difference between the front and back of the trash rack at the intake of the hydropower station. When the pressure difference reaches the pressure difference threshold, start the trash rack cleaning machine.

[0007] Step S2. By using the fuzzy intelligent control algorithm, calculate the descent depth u of the cleaning machine, and obtain the underwater depth C1 that the cleaning machine needs to descend to, C1 = u + D, where D is the original height of the cleaning machine above the water surface;

[0008] Step S3. Control the cleaning machine to descend and simultaneously control the cleaning machine to open the rake bucket. When the cleaning machine reaches position C1, control the cleaning machine to close the rake bucket and adjust D to C1.

[0009] Step S4. Raise the bucket to height C1;

[0010] Step S5. Compare C1 with the elevation C2 from the cleaning platform to the bottom of the trash rack;

[0011] Step S6. If C2>C1, repeat steps S2-S5 until C2≤C1; if C2≤C1, the cleaning task is complete and the cleaning machine is turned off.

[0012] As an improvement to the above technical solution, the fuzzy control intelligent control algorithm includes the following steps:

[0013] Step 1) Divide the differential pressure value into change levels and fuzzy levels, and create a fuzzy control matrix for the differential pressure value based on the divided change levels and fuzzy levels; divide the descent depth into change levels and fuzzy levels, and create a fuzzy control matrix for the descent depth based on the divided change levels and fuzzy levels; formulate fuzzy control rules;

[0014] Step 2) Solve for the fuzzy control rule matrix using the pressure difference fuzzy control matrix and the descent depth fuzzy control matrix;

[0015] Step 3) Solve the fuzzy matrix of descent depth using the pressure difference value and the fuzzy control rule matrix;

[0016] Step 4) Defuzzify the fuzzy matrix of the descent depth to obtain the descent depth.

[0017] As an improvement to the above technical solution, in step 1), the differential pressure value is divided into change levels and fuzzy levels, and a fuzzy control matrix for the differential pressure value is created based on the divided change levels and fuzzy levels; the descent depth is divided into change levels and fuzzy levels, and a fuzzy control matrix for the descent depth is created based on the divided change levels and fuzzy levels, specifically including:

[0018] Step 1-1) Divide the differential pressure range 0-P into 4 levels of variation: 0, ... P and 4 fuzziness levels ZO e NS e NM e NB e Where P is the differential pressure threshold;

[0019] Step 1-2) Based on the four change levels and four fuzzy levels of the differential pressure value in Step 1-1), the Gaussian function is used to calculate the element values ​​of the differential pressure value fuzzy matrix, thereby obtaining the differential pressure value fuzzy control matrix.

[0020] Steps 1-3) divide the descent depth range 0-u into 4 levels of variation: 0, ... u and 4 fuzziness levels ZO u NS u NM u NB u Where u is the descent depth threshold;

[0021] Steps 1-4) Based on the four change levels and four fuzziness levels of the descent depth in Steps 1-3), the Gaussian function is used to calculate the values ​​of each element of the descent depth fuzziness matrix, thereby obtaining the descent depth fuzziness control matrix.

[0022] As one improvement to the above technical solution, the Gaussian function used in steps 1-2) and 1-4) is... The expression is:

[0023]

[0024] Where e is the natural index, a i b is the center value of the function. i The width of the function;

[0025] When calculating the elements of the pressure difference fuzzy matrix using the Gaussian function in steps 1-2), x takes the values ​​0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 ... and P;b i for ZO e The corresponding a i The value is 0, NS e The corresponding a i Value NM e The corresponding a i Value NB e The corresponding a i The value is P;

[0026] When calculating the values ​​of each element of the descent depth fuzzy matrix using the Gaussian function in steps 1-4), x takes the values ​​0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 ... and u,b i for ZO u The corresponding a i The value is 0, NS u The corresponding a i Value NM e The corresponding a i Value NB e The corresponding a i The value is u;

[0027] The expressions for the pressure difference fuzzy control matrix obtained in steps 1-2) and the descent depth fuzzy control matrix obtained in steps 1-4) are both:

[0028]

[0029] In the fuzzy control matrix, the element values ​​represent the membership relationship between the change level and the fuzzy level: when the element value is 1, the membership degree between the change level and the fuzzy level is the highest; when the element value is 0.5, the membership degree between the change level and the fuzzy level is moderate; and when the element value is 0, the membership degree between the change level and the fuzzy level is low.

[0030] As an improvement to the above technical solution, in step 1), the fuzzy control rules include:

[0031] If the differential pressure value fuzziness level ZO is selected e If the row matrix is ​​such that the descent depth fuzziness level ZO is selected, then... u A row matrix;

[0032] If you select the differential pressure value fuzziness level NS e If the row matrix is ​​such that the descent depth fuzziness level NB is selected, then... u A row matrix;

[0033] If the differential pressure value fuzzy level NM is selected e If the row matrix is ​​such that the descent depth fuzziness level NM is selected, then... u A row matrix;

[0034] If you select the differential pressure value fuzziness level NB e If the row matrix is ​​such that the descent depth blur level NS is selected... u A row matrix.

[0035] As one improvement to the above technical solution, step 2) specifically includes:

[0036] ZO e and ZO u The row matrices are multiplied to obtain the submatrix R1 of the fuzzy control rule matrix R;

[0037] NS e and NB u The row matrices are multiplied to obtain the fractional matrix R2 of the fuzzy control rule matrix R;

[0038] NM e and NM u The row matrices are multiplied to obtain the submatrix R3 of the fuzzy control rule matrix R;

[0039] NB e and NS u The row matrices are multiplied to obtain the fractional matrix R4 of the fuzzy control rule matrix R;

[0040] The fuzzy control rule matrix R is calculated based on R1, R2, R3, and R4, using the following formula:

[0041] R = R0∪R1∪R2∪R3.

[0042] As an improvement to the above technical solution, in step 3), the expression for the fuzzy matrix U of the descent depth u is:

[0043] U=ER

[0044] Where E is the fuzzy control matrix for differential pressure.

[0045] As an improvement to the above technical solution, step 4) specifically includes:

[0046] Step 4-1) For the fuzzy matrix U = [U1 U2 U3 U4] of the descent depth u, obtain the fuzzy subset u0 = {u1, u2, u3, u4} of the descent depth u;

[0047] Step 4-2) For the fuzzy subset of descent depth u, select the descent depth change level according to the principle of maximum membership degree to obtain the descent depth, specifically including:

[0048] In the fuzzy subset u0, u1 corresponds to the descent depth change level 0, and in the fuzzy subset u0, u2 corresponds to the descent depth change level. The change level of descent depth is corresponding to u3 in the fuzzy subset u0. The change level u of the descent depth is assigned to u4 in the fuzzy subset u0;

[0049] The value closest to 1 among u1, u2, u3, and u4 is the descent depth u, which corresponds to the level of change in descent depth.

[0050] The present invention also proposes a fully automatic control system for dynamic water cleaning, the system comprising a dynamic water cleaning control module and a cleaning machine control module;

[0051] The dynamic water cleaning and decontamination control module is used to monitor the pressure difference caused by the water level difference between the front and back of the trash rack at the intake of the hydropower station, and to start the cleaning machine control module when the pressure difference reaches the pressure difference threshold; it is also used to calculate the descent depth using a fuzzy control intelligent control algorithm.

[0052] The cleaning machine control module is used to control the cleaning machine to complete the cleaning task based on the descent depth calculated by the dynamic water cleaning control module.

[0053] As an improvement to the above technical solution

[0054] The cleaning machine control module includes:

[0055] The motor is used to control the cleaning machine;

[0056] Drive circuit, used to drive the motor;

[0057] Monitoring devices are used to monitor the water level and pressure before and after the trash rack at the intake of a hydropower station; and

[0058] Hydraulic sensors are used to output monitoring data from the monitoring device;

[0059] The dynamic water cleaning and decontamination control module includes:

[0060] The arithmetic logic unit is used to calculate the descent depth using fuzzy intelligent control algorithms.

[0061] The preset unit is used to set the differential pressure threshold.

[0062] The configuration unit is used to configure the relevant position parameters during the operation of the cleaning machine;

[0063] The monitoring unit is used to transmit the water level and water pressure data monitored by the monitoring device to the arithmetic logic unit; and

[0064] The motor circuit drive unit is used to control the descent depth drive circuit based on the calculation of the arithmetic logic unit.

[0065] The advantages of this invention compared to the prior art are:

[0066] 1. By utilizing the water level difference and water pressure difference before and after the intake screen of the hydropower station, the system can automatically determine the best time and conditions for cleaning, thereby achieving fully automatic water cleaning of the hydropower station intake without affecting power generation efficiency and saving manpower and time.

[0067] 2. It has achieved fully automated water cleaning and decontamination, laying the foundation for intelligent and smart hydropower stations, while saving manpower and time. Attached Figure Description

[0068] Figure 1 This is a schematic diagram of the fully automatic water cleaning and decontamination control system of the present invention;

[0069] Figure 2 This is a schematic diagram of the structure of the dynamic water cleaning control unit and the processor of the present invention;

[0070] Figure 3 This is a schematic diagram of the structure of the dynamic water cleaning control unit and the control unit connected in this invention. Detailed Implementation

[0071] To achieve the above objectives, a fully automatic control device for dynamic water cleaning and decontamination has been developed and invented, which is applied to the control system of a decontamination cleaning machine. The control system of the decontamination cleaning machine mainly includes a motor, a drive circuit, a monitoring device, and a hydraulic sensor. The fully automatic control device for dynamic water cleaning and decontamination mainly includes a dynamic water cleaning and decontamination control unit and a decontamination cleaning machine control subsystem. The dynamic water cleaning and decontamination control unit is a programmable logic device, which includes a preset unit, a configuration unit, a monitoring unit, and a motor circuit drive unit.

[0072] At least one dynamic water cleaning control unit is installed on a programmable logic device and connected one-to-one with the motors in the cleaning machine control subsystem. The preset unit in the dynamic water cleaning control unit stores and sends various preset parameters of the cleaning machine, and the configuration unit can set the control conditions that trigger the start of the cleaning machine.

[0073] The technical solutions provided by the present invention will be further illustrated below with reference to the embodiments.

[0074] Example 1

[0075] First, set the initial parameters of the cleaning machine system in the preset unit. In the configuration unit, configure the relevant position parameters of the cleaning machine during operation according to the on-site conditions of the hydropower station intake.

[0076] 2. Hydraulic sensors are deployed in front of and behind the trash rack at the intake of the hydropower station to monitor the water level and pressure information in front of and behind the rack.

[0077] Third, the monitoring device in the cleaning machine control subsystem collects the voltage, current, and position data of the cleaning machine motor, and collects the water level and water pressure data in front of and behind the hydropower station intake gate from the hydraulic sensor, and transmits the collected data to the monitoring unit of the dynamic water cleaning control unit.

[0078] Fourth, the processor sends the data from the monitoring unit, preset unit, and configuration unit to the arithmetic logic unit for processing. The processor then transmits the processing results to the drive circuit in the cleaning machine control subsystem through the motor circuit drive unit. The drive circuit controls the cleaning machine motor.

[0079] like Figure 1 The diagram shown is a schematic diagram of the fully automatic water cleaning and decontamination control system of the present invention.

[0080] like Figure 2 The diagram shown is a schematic diagram of the connection between the dynamic water cleaning control unit and the processor of the present invention.

[0081] like Figure 3 The diagram shown is a schematic diagram of the connection between the dynamic water cleaning control unit and the control unit of the present invention. Figure 2 and Figure 3 This demonstrates that the results of this invention can be achieved using both processors and microcontrollers. In fact, the implementation of the system of this invention is not limited to using only processors and microcontrollers.

[0082] Example 2

[0083] The present invention provides a fully automatic control method for dynamic water cleaning and decontamination.

[0084] V. Specific Algorithm

[0085] 1. The obtained pressure difference value e is divided into fuzzy levels. The total pressure difference is 0-0.12 MPa, divided into 4 fuzzy levels: ZO, PS, PM, and PB. Fuzzification processing is performed on the pressure difference value obtained from the equipment to obtain the fuzzy level under this pressure difference condition. Finally, the corresponding fuzzy matrix is ​​obtained through the fuzzy control table of pressure difference e.

[0086]

[0087] Using the Gaussian function: (where e is the natural exponent, a) i b is the center value of the function. i Calculate the value in the fuzzy control table for the width of the function.

[0088] Fuzzyization of pressure difference value e: x takes values ​​{0, P / 3, 2P / 3, P}, let b be P / 3 in the formula, then { ZO e NS e NM e NB e} Corresponding to a i value The values ​​are {0, P / 3, 2P / 3, P}.

[0089] The values ​​in the fuzzy control table represent the level of change. With fuzzy level {ZO e NS e NM e NB e The membership degree relationship of} is as follows: when the value in the control table is 1, it means that the membership degree of the current change level and fuzzy level is the highest; when it is 0.5, it means that the membership degree is average; when it is 0, it means that the membership degree is low.

[0090] 2. The descent depth u is divided into fuzzy levels, with an output value of 0-3m, and is divided into 4 fuzzy levels: ZO, PS, PM, and PB. The fuzzy control table for the descent depth u is created based on the fuzzy levels as shown in the table below.

[0091]

[0092]

[0093] Using the Gaussian function: (where e is the natural index) Calculate the value in the fuzzy control table.

[0094] Fuzzyization of control quantity u: u takes values ​​{0, u / 3, 2u / 3, u}, then b is u / 3, and a takes values ​​of 0, u / 3, 2u / 3, u respectively.

[0095] The values ​​in the fuzzy control table represent the level of change. With fuzzy level {ZO u NS u NM u NB u The membership relationship of} is as follows: when the value in the matrix is ​​1, it means that the membership degree of the current change level and fuzzy level is the highest; when it is 0.5, it means that the membership degree is average; when it is 0, it means that the membership degree is low.

[0096] 3. Develop fuzzy control rules for the system.

[0097] 1. If e is 0, then u is 0;

[0098] 2. If e is small, then u is large;

[0099] 3. If e is the middle, then u is the middle;

[0100] 4. If e is large, then u is small.

[0101] THEN <![CDATA[ZO u ]]> <![CDATA[NB u ]]> <![CDATA[NM u ]]> <![CDATA[NS u ]]>

[0102] 4. Solve for the matrix expression R of the fuzzy control rule.

[0103]

[0104]

[0105] R2 and R3 omitted.

[0106] The matrix expression R for the fuzzy control rule is then:

[0107]

[0108] 5. Solve for the fuzzy matrix of the descent depth u. The fuzzy matrix of the pressure difference e is obtained from step 1, and the matrix expression R of the fuzzy control rule is obtained from step 4. The fuzzy matrix of the descent depth u is obtained by multiplying the fuzzy matrix of the pressure difference e by the matrix expression R of the fuzzy control rule.

[0109] u=e×R

[0110] 6. Defuzzify the fuzzy matrix of the descent u to obtain the actual descent depth of the system. The fuzzy matrix obtained in step 5 is written as a Zadeh expression for the fuzzy subset.

[0111] Assuming the fuzzy matrix of u is [0.5 0.5 0.5 1], then its fuzzy subset expression is:

[0112] u={0.5 / 0, 0.5 / 1, 0.5 / 2, 1 / 3}

[0113] According to the principle of maximizing membership, the fuzzy subset of the control quantity in the above formula should be selected as control level "3", that is, the depth to which the cleaning machine should descend is 3 meters.

[0114] The descent depth u takes values ​​of {u1, u2, u3, u4}. The descent depth is determined by which value in {u1, u2, u3, u4} is closest to 1. The value in.

[0115] VI. When the pressure difference reaches 0.12 MPa, the cleaning machine starts. Using a fuzzy intelligent control algorithm, the cleaning machine control system obtains the descent depth *u* derived from the algorithm. The original height *D* of the cleaning machine above the water surface can be used to determine the total descent depth *C1* = *u* + *D*. The motor drive unit controls the motor to begin descent simultaneously with the cleaning machine opening its rake bucket. Upon reaching position *C1*, the cleaning machine closes the rake bucket and adjusts the height *D* to equal *C1*.

[0116] 7. Lift the closed bucket to a height of C1.

[0117] 8. If the elevation C2 from the cleaning platform to the bottom of the trash rack is greater than C1, the cleaning machine will repeat steps five, six, and seven to continue the cleaning process. This process will continue until C2 <= C1, at which point the cleaning machine will complete the current trash cleaning task and send a signal to terminate all operations.

[0118] As can be seen from the above detailed description of the present invention, the optimal time and conditions for cleaning are determined by utilizing the water level difference and water pressure difference before and after the intake gate of the hydropower station, thereby realizing fully automatic water cleaning of the intake gate of the hydropower station.

[0119] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A fully automatic control method for cleaning and decontaminating moving water, wherein the method utilizes a decontamination cleaning machine to clean and decontaminate the water at the intake of a hydropower station; the method includes: Step S1. Determine the pressure difference caused by the water level difference between the front and back of the trash rack at the intake of the hydropower station. When the pressure difference reaches the pressure difference threshold, start the trash rack cleaning machine. Step S2. By using the fuzzy intelligent control algorithm, calculate the descent depth u of the cleaning machine, and obtain the underwater depth C1 that the cleaning machine needs to descend to, C1=u+D, where D is the original height of the cleaning machine above the water surface; Step S3. Control the cleaning machine to descend and simultaneously control the cleaning machine to open the rake bucket. When the cleaning machine reaches position C1, control the cleaning machine to close the rake bucket and adjust D to C1. Step S4. Raise the bucket to height C1; Step S5. Compare C1 with the elevation C2 from the cleaning platform to the bottom of the trash rack; Step S6. If C2>C1, repeat steps S2-S5 until C2≤C1; if C2≤C1, the cleaning task is complete and the cleaning machine is turned off. The fuzzy control intelligent control algorithm includes the following steps: Step 1) Divide the differential pressure value into change levels and fuzzy levels, and create a fuzzy control matrix for the differential pressure value based on the divided change levels and fuzzy levels; divide the descent depth into change levels and fuzzy levels, and create a fuzzy control matrix for the descent depth based on the divided change levels and fuzzy levels; formulate fuzzy control rules; Step 2) Solve for the fuzzy control rule matrix using the pressure difference fuzzy control matrix and the descent depth fuzzy control matrix; Step 3) Solve the fuzzy matrix of descent depth using the pressure difference value and the fuzzy control rule matrix; Step 4) Defuzzify the fuzzy matrix of the descent depth to obtain the descent depth; In step 1), the differential pressure value is divided into change levels and fuzzy levels, and a fuzzy control matrix for the differential pressure value is created based on the divided change levels and fuzzy levels; the descent depth is divided into change levels and fuzzy levels, and a fuzzy control matrix for the descent depth is created based on the divided change levels and fuzzy levels, specifically including: Step 1-1) Divide the differential pressure range 0-P into 4 levels of variation: 0, ... , P and 4 fuzzy levels ZO e NS e NM e NB e Where P is the differential pressure threshold; Step 1-2) Based on the four change levels and four fuzzy levels of the differential pressure value in Step 1-1), the Gaussian function is used to calculate the element values ​​of the differential pressure value fuzzy matrix, thereby obtaining the differential pressure value fuzzy control matrix; Steps 1-3) Set the descent depth range to 0- u It is divided into 4 levels of change: 0, , , u and 4 fuzzy levels ZO u NS u NM u NB u ;in, u The threshold for descent depth; Steps 1-4) Based on the four change levels and four fuzziness levels of the descent depth in Steps 1-3), the Gaussian function is used to calculate the values ​​of each element of the descent depth fuzziness matrix, thereby obtaining the descent depth fuzziness control matrix.

2. The fully automatic control method for dynamic water cleaning and decontamination according to claim 1, characterized in that, The Gaussian function used in steps 1-2) and 1-4) The expression is: in, e For natural index, a i The central value of the function. b i The width of the function; When calculating the element values ​​of the pressure difference fuzzy matrix using the Gaussian function in steps 1-2), x They were respectively assigned the values ​​0, ... , and P; b i for ZO e corresponding a i The value is 0, NS e corresponding a i Value NM e corresponding a i Value NB e corresponding a i Value P ; When calculating the element values ​​of the descent depth fuzziness matrix using the Gaussian function in steps 1-4), x They were respectively assigned the values ​​0, ... , and u , b i for ZO u corresponding a i The value is 0, NS u corresponding a i Value NM e corresponding a i Value NB e corresponding a i Value u ; The expressions for the pressure difference fuzzy control matrix obtained in steps 1-2) and the descent depth fuzzy control matrix obtained in steps 1-4) are both: In the fuzzy control matrix, the element values ​​represent the membership relationship between the change level and the fuzzy level: when the element value is 1, the membership degree between the change level and the fuzzy level is the highest; when the element value is 0.5, the membership degree between the change level and the fuzzy level is moderate; and when the element value is 0, the membership degree between the change level and the fuzzy level is low.

3. The fully automatic control method for moving water cleaning and decontamination according to claim 2, characterized in that, In step 1), the fuzzy control rules include: If the differential pressure value fuzziness level ZO is selected e If the row matrix is ​​such that the descent depth fuzziness level ZO is selected, then... u A row matrix; If you select the differential pressure value fuzziness level NS e If the row matrix is ​​such that the descent depth fuzziness level NB is selected, then... u A row matrix; If the differential pressure value fuzzy level NM is selected e If the row matrix is ​​such that the descent depth fuzziness level NM is selected, then... u A row matrix; If you select the differential pressure value fuzziness level NB e If the row matrix is ​​such that the descent depth blur level NS is selected... u A row matrix.

4. The fully automatic control method for dynamic water cleaning and decontamination according to claim 3, characterized in that, Step 2) specifically includes: ZO e and ZO u The fuzzy control rule matrix is ​​obtained by multiplying the row matrices. R The fractional matrix R 1; NS e and NB u The fuzzy control rule matrix is ​​obtained by multiplying the row matrices. R The fractional matrix R 2; NM e and NM u The fuzzy control rule matrix is ​​obtained by multiplying the row matrices. R The fractional matrix R 3; NB e and NS u The fuzzy control rule matrix is ​​obtained by multiplying the row matrices. R The fractional matrix R 4; based on R 1. R 2. R 3 and R 4. Calculate the fuzzy control rule matrix R The calculation formula is: 。 5. The fully automatic control method for moving water cleaning and decontamination according to claim 4, characterized in that, In step 3), the expression for the fuzzy matrix U of the descent depth u is: U=E R Where E is the fuzzy control matrix for differential pressure.

6. The fully automatic control method for moving water cleaning and decontamination according to claim 5, characterized in that, Step 4) specifically includes: Step 4-1) For the fuzzy matrix U=[U1 U2 U3 U4] of the descent depth u, obtain the fuzzy subset u0={u1, u2, u3, u4} of the descent depth u; Step 4-2) For the fuzzy subset of descent depth u, select the descent depth change level according to the principle of maximum membership degree to obtain the descent depth, specifically including: In the fuzzy subset u0, u1 corresponds to the descent depth change level 0, and in the fuzzy subset u0, u2 corresponds to the descent depth change level. The change level of descent depth corresponding to u3 in the fuzzy subset u0. The change level u of the descent depth is corresponding to u4 in the fuzzy subset u0; The value closest to 1 among u1, u2, u3, and u4 is the descent depth u, which corresponds to the level of change in descent depth.

7. A system based on the fully automatic control method for dynamic water cleaning and decontamination as described in claim 1, characterized in that, The system includes a dynamic water cleaning and decontamination control module and a cleaning machine control module; The dynamic water cleaning and decontamination control module is used to monitor the pressure difference caused by the water level difference between the front and back of the trash rack at the intake of the hydropower station, and to start the cleaning machine control module when the pressure difference reaches the pressure difference threshold; it is also used to calculate the descent depth using a fuzzy control intelligent control algorithm. The cleaning machine control module is used to control the cleaning machine to complete the cleaning task based on the descent depth calculated by the dynamic water cleaning control module.

8. The system according to claim 7, characterized in that, The cleaning machine control module includes: The motor is used to control the cleaning machine; Drive circuit, used to drive the motor; Monitoring devices are used to monitor the water level and pressure before and after the trash rack at the intake of a hydropower station; and Hydraulic sensors are used to output monitoring data from the monitoring device; The dynamic water cleaning and decontamination control module includes: The arithmetic logic unit is used to calculate the descent depth using fuzzy intelligent control algorithms. The preset unit is used to set the differential pressure threshold. The configuration unit is used to configure the relevant position parameters during the operation of the cleaning machine; The monitoring unit is used to transmit the water level and water pressure data monitored by the monitoring device to the arithmetic logic unit; and The motor circuit drive unit is used to control the descent depth drive circuit based on the calculation of the arithmetic logic unit.

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