Rotational flow desilting device for water conservancy project

Abstract

The invention relates to the technical field of rotational flow desilting devices, and particularly discloses a rotational flow desilting device for hydraulic engineering, which comprises a rotational flow desilting cylinder, a rotational flow assembly, a sand-water separation assembly, a conveying assembly and a control management unit, a discharging pipe is fixedly connected to the bottom of the rotational flow desilting cylinder, a control valve is fixedly connected to the interior of the discharging pipe, an electric valve is fixedly connected to the interior of the water inlet pipe, and the control management unit is used for monitoring and analyzing the running state of the rotational flow desilting cylinder in real time. According to the invention, through the arrangement of the control management unit, the traditional extensive mode depending on artificial experience judgment can be changed, so that the equipment operation information can be obtained more comprehensively, timely and accurately. Based on the data, different working conditions can be accurately identified, a basis is provided for parameter optimization, and the problem that traditional fixed parameter control cannot adapt to sewage characteristic changes is solved.

Description

Technical Field

[0001] The invention relates to the technical field of cyclone sand settling devices, in particular to a cyclone sand settling device for water conservancy projects. Background Art

[0002] As an important equipment in the fields of water treatment and river dredging, cyclone sand settling machine is widely used to separate solid particles such as sand and silt from sewage.

[0003] Conventional cyclone desilting machine control and management methods primarily rely on empirically defined operating parameters, such as feed flow rate and cyclone speed. Manual observation of desilting performance is typically performed, with regular equipment maintenance and parameter adjustments. However, due to significant variations in wastewater sediment content and particle size distribution under different operating conditions, fixed parameters cannot achieve optimal desilting results. Furthermore, traditional methods lack real-time monitoring and accurate analysis of equipment operating status. Summary of the Invention

[0004] Aiming at the technical problem that traditional cyclone sand settling machines cannot be controlled to achieve the best sand settling effect, the present invention provides a cyclone sand settling device for water conservancy projects.

[0005] The technical solution adopted by the present invention is: a cyclone sedimentation device for water conservancy projects, comprising:

[0006] A cyclone sand settling drum, wherein the outside of the cyclone sand settling drum is fixedly connected to a water inlet pipe and a drain pipe, the bottom of the cyclone sand settling drum is fixedly connected to a discharge pipe, a control valve is fixedly connected to the discharge pipe, and an electric valve is fixedly connected to the water inlet pipe;

[0007] A cyclone assembly, wherein the cyclone assembly is arranged in a cyclone sand settling drum;

[0008] A sand-water separation component, wherein the sand-water separation component is used to separate sand and water;

[0009] A conveying assembly, wherein the conveying assembly is used to convey sand and water into the sand and water separation assembly;

[0010] A control management unit is used to monitor and analyze the operating status of the cyclone sand settling drum in real time.

[0011] The present invention is further configured such that the vortex assembly includes a fixing frame fixedly connected to the top of the vortex sand settling drum, a first motor fixedly connected to the outside of the fixing frame, a rotating rod fixedly connected to the output end of the first motor, and blades fixedly connected to the outside of the rotating rod, the outside of the fixing frame is fixedly connected to a bearing seat, and the rotating rod is fixedly connected to the inner ring of the bearing in the bearing seat.

[0012] The present invention is further configured as follows: the sand-water separation assembly includes a sand-water separation box and a fixed pipe fixedly connected to the sand-water separation box; the outside of the sand-water separation box is fixedly connected to a water outlet pipe; the inside of the sand-water separation box is fixedly connected to an arc-shaped protrusion and a blocking column; the inside of the fixed pipe is rotatably connected to a spiral conveying rod; the area of ​​the fixed pipe located in the sand-water separation box is configured as an opening; one end of the fixed pipe is fixedly connected to a discharge pipe; the outside of the fixed pipe is fixedly connected to a second motor; and the output end of the second motor is fixedly connected to the spiral conveying rod.

[0013] The present invention is further configured such that the conveying component is a pump body, the input end of the pump body is fixedly connected to a first pipe, the output end of the pump body is fixedly connected to a second pipe, the first pipe is fixedly connected to the discharge pipe, and the second pipe is fixedly connected to the sand-water separation box.

[0014] The present invention is further configured such that the control management unit includes a data acquisition module, a data preprocessing module, a working condition analysis model module, a parameter optimization module, an instruction sending module, a dynamic simulation model module, a sand discharge optimization model module, a collaborative control module and an environmental parameter compensation control module.

[0015] The present invention is further configured such that a flow sensor is installed on the water inlet pipe of the data acquisition module to collect the feed flow Q in real time. The collection frequency of the flow sensor is f Q ;

[0016] Pressure sensors are installed at different positions of the cyclone chamber of the cyclone sand settling drum to collect pressure data P at different positions. i (i=1,2,…,n, n is the number of pressure sensors), the pressure sensor acquisition frequency is f P ;

[0017] A speed sensor is installed on the outside of the first motor to collect the motor speed n, with a collection frequency of f n ;

[0018] Install a concentration detector in the discharge pipe to detect the concentration C of discharged sediment. The sampling frequency is f. C ;

[0019] All collected data are transmitted to the control and management system in real time through the data transmission module;

[0020] The pre-processing module filters the collected data to remove noise interference; the mean filtering algorithm is used to filter the collected feed flow data, and the kth filtered value Q f (k) is calculated as follows:

[0021]

[0022] Where m is the filter window size, and Q(i) is the i-th feed flow data originally collected.

[0023] The present invention is further configured such that the operating condition analysis model module first calculates the rate of change of the feed flow rate

[0024]

[0025] Where Δt is the time interval between two adjacent data collections,

[0026] Calculate the pressure gradient in the swirl chamber using pressure data

[0027]

[0028] Where L is the average distance between two adjacent pressure sensors. Combining data such as feed flow rate change rate, pressure gradient, and sediment concentration, a machine learning algorithm was used to establish an operating condition classification model, which categorizes the operating conditions into low-sediment-content stable conditions and high-sediment-content fluctuating conditions.

[0029] The parameter optimization module uses the optimization algorithm to calculate the optimal operating parameters of the cyclone sand settling drum based on the results of the working condition analysis;

[0030] Taking energy consumption E and processing efficiency η as optimization objectives, a multi-objective optimization function is established:

[0031]

[0032] Where ω1 and ω2 are weight coefficients, and ω1+ω2=1;

[0033] The calculation formula for energy consumption E is:

[0034] E=P e ×t;

[0035] Among them, P e is the first motor power, P e =k1n 2 +k2n+k3, k1, k2, k3 are constants related to the first motor characteristics; t is the running time;

[0036] The calculation formula for treatment efficiency η is:

[0037]

[0038] Among them, V s is the volume of sediment separated per unit time, V s =C f Q f ; Vi is the feed volume per unit time, V i =Q f ;

[0039] The instruction sending module calculates the first motor speed n based on the control management system. opt and feed flow Q opt Convert it into a control instruction and send it to the first motor and the electric valve through the control management system;

[0040] Based on the collected data of the first motor current I, the first motor temperature T, and the vibration amplitude A of the external bearing of the rotating rod, the comprehensive state index S is calculated:

[0041]

[0042] Among them, I nom 、T nom 、A nom are the normal nominal values ​​of the first motor current, temperature, and bearing vibration amplitude respectively; I max 、T max 、A max are the maximum allowable values ​​of the first motor current, temperature, and bearing vibration amplitude respectively; α1, α2, and α3 are weight coefficients, and α1+α2+α3=1.

[0043] The present invention is further configured such that the dynamic simulation model module establishes a dynamic simulation model of the internal flow field of the cyclone sand settling chamber based on the principles of computational fluid dynamics; the finite volume method is used to grid the cyclone chamber and discretize it into multiple control volume units;

[0044] Solve the continuity equation, momentum equation and energy equation for each control volume element;

[0045] Continuity equation:

[0046]

[0047] Where ρ is the fluid density, t is the time, is the fluid velocity vector;

[0048] Momentum equation:

[0049]

[0050] Where p is the pressure, μ is the fluid dynamic viscosity, is the gravitational acceleration vector;

[0051] The sand removal optimization model module is used to establish a sand removal optimization model. The specific method is as follows:

[0052] First, calculate the sediment deposition rate V of the discharge piped :

[0053]

[0054] Among them, k d is a coefficient related to the discharge pipe structure and sediment characteristics, m and n are empirical indices;

[0055] Then, set the critical blockage volume V of the discharge pipe c , when the sediment deposition volume V in the discharge pipe s Reaching the critical blockage volume V c When the set ratio is reached, the sand discharge optimization control strategy is started, and the sand discharge control valve opening O and the sand discharge time t are adjusted. s ;

[0056] Establish sediment removal efficiency η s The calculation formula is:

[0057]

[0058] Among them, V e The actual discharged sediment volume is calculated by particle swarm optimization algorithm to optimize the control valve opening O of the discharge pipe and the sediment discharge time t. s Optimize the sediment removal efficiency η s Maximize the objective function and find the valve opening O of the sand outlet opt and sediment discharge time t opt ;

[0059] The present invention is further configured such that the collaborative control module is used to establish a multi-device collaborative control model when multiple cyclone sand settling drums are running simultaneously;

[0060] According to the total water intake Q total and the processing capacity of each cyclone sand settling drum, calculate the optimal distribution flow Q of each cyclone sand settling drum all,i ;

[0061] First, introduce the fairness indicator γ i :

[0062]

[0063] The total energy consumption of all equipment E total Minimum is the objective function, and a multi-device collaborative optimization model is established:

[0064]

[0065] in, is the power of the first motor of the i-th cyclone sand settling drum;

[0066] At the same time, the constraints are met:

[0067]

[0068] 0≤Q all,i ≤Q max,i ;

[0069] The present invention is further configured to establish an environmental parameter compensation model based on the influence of the environmental parameter compensation control module on the operating performance of the cyclone sand settling drum;

[0070] The effect of temperature on fluid viscosity is corrected using the Andrade formula:

[0071]

[0072] Where μ0 is the viscosity at reference temperature T0, B and C are constants related to fluid properties, and T is the actual ambient temperature. The formula for the effect of altitude on atmospheric pressure is:

[0073]

[0074] Where p0 is the atmospheric pressure at sea level, M is the molar mass of air, g is the acceleration due to gravity, h is the altitude, and R is the universal gas constant.

[0075] The present invention achieves the following benefits: It utilizes a cyclonic sedimentation chamber for cyclonic sedimentation and a sand-water separation assembly for sand-water separation. The control and management unit changes the traditional extensive model that relies on manual judgment, enabling more comprehensive, timely, and accurate acquisition of equipment operating information. This data allows for precise identification of different operating conditions, providing a basis for parameter optimization and resolving the issue of traditional fixed-parameter control systems being unable to adapt to changing sewage characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 It is a structural schematic diagram of the present invention;

[0077] Figure 2 It is a structural schematic diagram of the cyclone sand settling drum and the sand-water separation box in the present invention;

[0078] Figure 3 This is a schematic diagram of the structure of the cyclone sand settling tube in the present invention;

[0079] Figure 4 This is a schematic diagram of the internal structure of the cyclone sand settling drum of the present invention;

[0080] Figure 5 This is a schematic diagram of the internal structure of the sand-water separation box of the present invention;

[0081] Figure 6 It is a side structural schematic diagram of the sand-water separation box in the present invention.

[0082] The following are marked in the figure:

[0083] 1. Cyclone sand settling tube; 2. Fixed frame; 3. First motor; 4. Rotating rod; 5. Blades; 6. Drain pipe; 7. Water inlet pipe; 8. Discharge pipe; 9. Control valve; 10. Pump body; 11. First pipeline; 12. Second pipeline; 13. Sand-water separation box; 14. Water outlet pipe; 15. Fixed pipe; 16. Discharge pipe; 17. Second motor; 18. Arc-shaped protrusion; 19. Blocking column; 20. Screw conveying rod. DETAILED DESCRIPTION

[0084] In the description of the present invention, it should be noted that the terms "front", "up", "down", "left", "right", "vertical", "horizontal", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they cannot be understood as limiting the present invention.

[0085] The following is combined with Figure 1-6 The present invention is further described.

[0086] Example 1:

[0087] In order to solve the problems existing in the background technology, the present application proposes the following technical solutions: A cyclone sedimentation device for water conservancy projects, comprising: a cyclone sedimentation drum 1, a cyclone component, a sand-water separation component, a conveying component and a control and management unit. The outside of the cyclone sedimentation drum 1 is fixedly connected to a water inlet pipe 7 and a drain pipe 6, the bottom of the cyclone sedimentation drum 1 is fixedly connected to a discharge pipe 8, a control valve 9 is fixedly connected in the discharge pipe 8, an electric valve is fixedly connected in the water inlet pipe 7, the cyclone component is arranged in the cyclone sedimentation drum 1, the sand-water separation component is used to separate sand and water, and the conveying component is used to convey sand and water to the sand-water separation component; the control and management unit is used to monitor and analyze the operating status of the cyclone sedimentation drum 1 in real time,

[0088] In this embodiment, the cyclone assembly includes a mounting frame 2 fixedly connected to the top of the cyclone sedimentation chamber 1, a first motor 3 fixedly connected to the exterior of the mounting frame 2, a rotating rod 4 fixedly connected to the output end of the first motor 3, and blades 5 fixedly connected to the exterior of the rotating rod 4. A bearing seat is fixedly connected to the exterior of the mounting frame 2, and the rotating rod 4 is fixedly connected to the inner ring of the bearing within the bearing seat. The mounting frame 2, fixedly connected to the top of the cyclone sedimentation chamber 1, is made of high-strength, corrosion-resistant material, providing a stable mounting base for the first motor 3 and subsequent transmission components. In the complex environment of a water conservancy project, whether exposed to long-term immersion in water or facing water impact and sediment erosion, the mounting frame 2 maintains structural stability, ensuring reliable operation of the cyclone assembly. The first motor 3, as the power core of the cyclone assembly, features high torque and low energy consumption, capable of stably outputting power to drive the rotating rod 4. It is encased in a waterproof and dustproof casing to adapt to the humid and dusty working environment of water conservancy projects, reducing motor failures caused by environmental factors and extending its service life.

[0089] Among them, the rotating rod 4 connected to the output end of the first motor 3 is a key component for transmitting power. The rotating rod 4 is tightly fixed to the inner ring of the bearing in the bearing seat. The presence of the bearing greatly reduces the friction resistance of the rotating rod 4 when it rotates, so that the rotating rod 4 can rotate at high speed and smoothly under the drive of the first motor 3, reducing energy loss while improving power transmission efficiency. The bearing seat adopts a sealing design to prevent mud and water from entering the bearing, avoid bearing wear, and ensure the long-term stable operation of the rotating rod 4. The blades 5 fixedly connected to the outside of the rotating rod 4 are the direct executors of the vortex formation. The blades 5 have been specially designed for fluid mechanics, and their shape, angle and distribution have been optimized. When the rotating rod 4 drives the blades 5 to rotate, it can produce a strong stirring effect on the sand and water entering the vortex sand settling tube 1, prompting the sand and water to form a high-speed vortex.

[0090] Among them, in the vortex state, the sand in the sand and water is thrown toward the inner wall of the vortex sedimentation barrel 1 due to the centrifugal force, loses kinetic energy after hitting the inner wall, and quickly settles to the bottom of the barrel under the action of gravity, and gathers at the position corresponding to the discharge pipe 8. Compared with the natural sedimentation method, the vortex forced to form by the vortex component greatly accelerates the sedimentation speed of the sediment and improves the sedimentation efficiency. At the same time, the stable vortex can also make the sand and water evenly distributed in the barrel, avoiding the occurrence of local vortexes or dead corners of water flow, ensuring that each part of the sand and water can be fully processed, and improving the overall sedimentation effect. This design of forcibly forming a vortex through mechanical power overcomes the defects of low efficiency and poor effect of traditional sedimentation that relies on the natural flow of water.

[0091] In this embodiment, the sand-water separation assembly includes a sand-water separation box 13 and a fixed pipe 15 fixedly connected to the sand-water separation box 13. The sand-water separation box 13 is externally fixedly connected to a water outlet pipe 14. An arc-shaped protrusion 18 and a blocking column 19 are fixedly connected to the sand-water separation box 13. A screw conveying rod 20 is rotatably connected to the fixed pipe 15. The area of ​​the fixed pipe 15 located within the sand-water separation box 13 is configured as an opening. One end of the fixed pipe 15 is fixedly connected to a discharge pipe 16. A second motor 17 is externally fixedly connected to the fixed pipe 15. The output end of the second motor 17 is fixedly connected to the screw conveying rod 20. The sand-water separation box 13 serves as the core container for achieving deep separation of sand and water. The arc-shaped protrusion 18 and blocking column 19 fixedly connected to the box disrupt the flow inertia of the sand and water entering the box. When the conveying assembly delivers sand containing a small amount of water to the sand-water separation box 13, the mixed fluid impacts the arc-shaped protrusion 18 and blocking column 19, changing its direction of motion and reducing its flow rate. During this process, the sand, due to its greater gravity, quickly separates from the water and settles at the bottom of the sand-water separation box 13. The water, due to its lower density, remains fluid and gradually accumulates in the upper layers. This method of achieving sand-water separation by physically altering the fluid's motion state eliminates the need for chemical agents, is environmentally friendly, and offers significant separation results.

[0092] Among them, the outlet pipe 14 outside the sand-water separation box 13 is responsible for discharging the separated upper layer of water. It is located at a higher position in the box to ensure that the separated water can be discharged by gravity, avoiding the influence of residual water on subsequent separation operations. The fixed pipe 15 and the spiral conveying rod 20 fixedly connected to the sand-water separation box 13 constitute a sediment discharge system. The area where the fixed pipe 15 is located in the box is set as an opening, so that the sand settled at the bottom of the box can smoothly enter the fixed pipe 15. The second motor 17 outside the fixed pipe 15 provides power for the spiral conveying rod 20. The second motor 17 has good speed regulation performance and can flexibly adjust the speed of the spiral conveying rod 20 according to the amount of sediment deposition and discharge requirements. When the spiral conveying rod 20 rotates, its spiral blades 5 will gradually lift the sand entering the fixed pipe 15 upwards, and transport it to the designated position through the discharge pipe 16, so as to achieve continuous and efficient discharge of sediment.

[0093] The sand-water separation and sediment transport functions are organically combined. The arc-shaped protrusion 18 and the blocking column 19 achieve the initial separation of sand and water, while the spiral conveying rod 20 is responsible for sediment discharge, with clear division of labor and close coordination.

[0094] In this embodiment, the conveying assembly comprises a pump body 10. A first pipe 11 is fixedly connected to the input end of the pump body 10, and a second pipe 12 is fixedly connected to the output end of the pump body 10. The first pipe 11 is fixedly connected to the discharge pipe 8, and the second pipe 12 is fixedly connected to the interior of the sand-water separation chamber 13. As the core of the conveying assembly, the pump body 10 possesses powerful pumping and conveying capabilities. Based on the sediment sedimentation within the cyclone 1, it can promptly and stably extract the water-containing sand deposited at the bottom of the chamber and convey it to the sand-water separation assembly. Its performance parameters have been optimized to prevent clogging and overload when pumping high-concentration sediment mixtures, while maintaining efficient operation and reducing energy consumption even under low flow demands. The input end of the pump body 10 is fixedly connected to the discharge pipe 8 at the bottom of the cyclone 1 via the first pipe 11. This connection is tight and hermetically sealed, preventing sediment leakage during the extraction process and ensuring the safety and reliability of the conveying process.

[0095] Among them, the output end of the pump body 10 is fixedly connected to the inside of the sand-water separation box 13 through the second pipe 12. The layout of the second pipe 12 fully considers the structural characteristics and working requirements of the sand-water separation box 13. Its connection position and angle have been carefully designed so that sand containing a small amount of water can enter the sand-water separation box 13 at a suitable speed and direction, making it easier for the arc-shaped protrusions 18 and the blocking columns 19 in the box to separate and process the mixed fluid. During the transportation process, the pump body 10 can adjust the delivery flow rate according to the working status of the sand-water separation component under the control of the control and management unit. For example, when there is a lot of sediment accumulated in the sand-water separation box 13 and the transportation speed needs to be accelerated, the control and management unit sends a command to the pump body 10 to increase the speed and increase the delivery flow rate; when the separation box is close to full load or the transportation needs to be suspended for cleaning, the pump body 10 reduces the speed or stops working.

[0096] This intelligent conveying control method avoids the lag and inaccuracy of traditional manual control, achieving efficient connection between the cyclone sedimentation drum 1 and the sand-water separation assembly. The close coordination between the conveying assembly, the cyclone sedimentation drum 1, and the sand-water separation assembly forms a complete automated process from sedimentation and extraction to deep separation. Compared with previous methods that relied on manual handling or simple mechanical conveying of sediment, this conveying assembly significantly improves sediment processing efficiency, reduces labor and time costs, and reduces the risk of equipment failure due to improper manual operation. It ensures the continuity and stability of sedimentation operations in water conservancy projects and provides solid technical support for the efficient operation of water conservancy projects.

[0097] The method of using this embodiment is as follows:

[0098] Connect the water inlet pipe 7 to the sand and water conveying pipe, and convey the sand and water into the cyclone 1 at high speed to form a cyclone. Then start the first motor 3, which drives the rotating rod 4 and the blades 5 to rotate. After the sand in the sand hits the inner wall of the cyclone 1, it falls to the inner bottom of the cyclone 1 and corresponds to the discharge pipe 8.

[0099] Subsequently, the pump body 10 is started to transport the precipitated sand containing water into the sand-water separation box 13. The sand mixed with a small amount of water hits the arc-shaped protrusion 18 and the blocking column 19 and settles at the bottom of the sand-water separation box 13. Subsequently, the second motor 17 is started to drive the screw conveying rod 20 to rotate, lifting the sand and transporting it away.

[0100] The water in the sand-water separation box 13 can be discharged through the discharge pipe 16 , and the water in the cyclone sand settling drum 1 can be discharged through the drain pipe 6 .

[0101] Example 2:

[0102] The control management unit includes a control management system, a data acquisition module, a data preprocessing module, a working condition analysis model module, a parameter optimization module, an instruction sending module, a dynamic simulation model module, a sand discharge optimization model module, a collaborative control module and an environmental parameter compensation control module.

[0103] The data acquisition module water inlet pipe 7 is equipped with a flow sensor to collect the feed flow Q in real time. The collection frequency of the flow sensor is f Q ;

[0104] Pressure sensors are installed at different positions of the cyclone chamber of the cyclone sand settling drum 1 to collect pressure data P at different positions. i (i=1,2,…,n, n is the number of pressure sensors), the pressure sensor acquisition frequency is f P ;

[0105] A speed sensor is installed on the outside of the first motor 3 to collect the motor speed n, with a collection frequency of f n ;

[0106] A concentration detector is installed in the discharge pipe 8 to detect the concentration C of discharged sediment. The sampling frequency is f C ;

[0107] All collected data are transmitted to the control and management system in real time through the data transmission module.

[0108] The above technical solution is explained as follows: By installing a variety of sensors, such as flow sensors and pressure sensors, at key locations of the cyclone sedimentation drum 1, multi-dimensional data such as feed flow, pressure, motor speed, and sediment concentration are collected in real time and quickly transmitted to the control and management system. This initiative has changed the traditional way of relying on manual experience to judge the operating status of the equipment, and has achieved comprehensive, accurate, and real-time acquisition of equipment operating information. A large amount of accurate data provides a solid foundation for subsequent working condition analysis and parameter optimization, enabling the control and management system to keep abreast of the equipment's operating dynamics, effectively avoiding problems such as poor sedimentation effects and difficulty in timely detection of equipment failures due to delayed or inaccurate information, thereby ensuring the efficient and stable operation of the cyclone sedimentation drum 1.

[0109] The pre-processing module filters the collected data to remove noise interference. Using the mean filter algorithm, for the collected feed flow data, the kth filtered value Q f (k) is calculated as follows:

[0110]

[0111] Where m is the filter window size, Q(i) is the i-th feed flow data collected originally. The function of this formula is to smooth the data curve by averaging the data within a certain window and reduce the impact of random noise on the data. For pressure data, speed data and sediment concentration data, similar mean filtering algorithms are also used to process them, and the filtered pressure data P is obtained respectively. f ,i, speed data n f and sediment concentration data C f .

[0112] The above technical solution is explained as follows: A mean filtering algorithm is used to process the collected data to remove noise interference. In actual operation, raw data is often affected by various external factors and fluctuates, and this noise can interfere with the judgment of the actual operating status. Through data preprocessing, the data curve can be smoothed, making the data more realistically reflect the equipment's operating conditions. For example, accurate feed flow data can help more accurately analyze operating conditions and avoid misjudgments caused by noise, thereby providing a reliable basis for subsequent data-based decision-making, ensuring that the control and management system can make reasonable parameter adjustments and equipment status assessments based on accurate data, thereby improving the accuracy and reliability of the entire control and management method.

[0113] The operating condition analysis model module first calculates the rate of change of the feed flow

[0114]

[0115] Where Δt is the time interval between two adjacent data collections,

[0116] This formula is used to measure how quickly the feed flow changes over time and reflects the stability of the operating conditions.

[0117] Calculate the pressure gradient in the swirl chamber using pressure data

[0118]

[0119] Where L is the average distance between two adjacent pressure sensors. The pressure gradient can reflect the motion state and swirl intensity of the fluid in the swirl chamber. Combining data such as the feed flow rate change rate, pressure gradient, and sediment concentration, a machine learning algorithm such as a support vector machine (SVM) is used to establish an operating condition classification model, which divides the operating conditions into stable conditions with low sediment concentration and fluctuating conditions with high sediment concentration.

[0120] The above technical solution is explained as follows: A machine learning algorithm is used to establish an operating condition classification model, combining data such as the feed flow rate change rate, pressure gradient, and sediment concentration. Traditional fixed-parameter control methods are unable to adapt to the changing characteristics of sewage under different operating conditions. This step, however, accurately determines the current operating condition based on real-time data, such as stable conditions with low sediment concentrations or fluctuating conditions with high sediment concentrations. Accurate operating condition analysis enables the control and management system to prescribe the right solution, developing appropriate operating strategies for different operating conditions. This allows the cyclone sedimentation drum 1 to adjust to appropriate operating parameters under various complex operating conditions, effectively improving sedimentation efficiency and avoiding inefficient equipment operation or energy waste due to misjudgment of operating conditions.

[0121] The parameter optimization module calculates the optimal operating parameters of the cyclone sand settling drum 1 using an optimization algorithm based on the results of the working condition analysis;

[0122] Taking energy consumption E and processing efficiency η as optimization objectives, a multi-objective optimization function is established:

[0123]

[0124] Among them, ω1 and ω2 are weight coefficients, and ω1+ω2=1; the appropriate weight value is determined through experiments and experience to balance the importance of energy consumption and processing efficiency in the optimization process.

[0125] The calculation formula for energy consumption E is:

[0126] E=P e ×t;

[0127] Among them, P e is the power of the first motor 3, P e =k1n 2+k2n+k3, where k1, k2, and k3 are constants related to the characteristics of first motor 3; and t is the operating time. This formula shows that energy consumption is related to motor power and operating time, and the power of first motor 3 is related to the speed of first motor 3.

[0128] The calculation formula for treatment efficiency η is:

[0129]

[0130] Among them, V s is the volume of sediment separated per unit time, V s =C f Q f ; V i is the feed volume per unit time, V i =Q f The processing efficiency reflects the ability of the sediment separator to separate sediment. The genetic algorithm is used to solve the multi-objective optimization function to obtain the optimal motor speed n under the current working conditions. opt and the optimal feed flow rate Q opt

[0131] The above technical solution is explained as follows: With energy consumption and processing efficiency as optimization goals, a multi-objective optimization function is established, and a genetic algorithm is used to solve the optimal operating parameters. In traditional control methods, it is difficult to balance energy consumption and processing efficiency, and energy waste or poor processing effects often occur. This step uses an optimization algorithm to comprehensively consider factors such as the power of the first motor 3, operating time, and sediment separation volume, and can find the best balance between energy consumption and processing efficiency under different working conditions. Whether it is faced with the need for efficient treatment of high-sand content sewage, or the pursuit of energy saving under low-load conditions, the optimal motor speed and feed flow rate can be calculated to maximize the operating efficiency of the equipment.

[0132] The instruction sending module calculates the speed n of the first motor 3 based on the control management system. opt and feed flow Q opt Converted into control instructions and sent to the control devices corresponding to the first motor 3 and the electric valve through the control management system;

[0133] The speed regulating device of the first motor 3, for example, the PLC for controlling the first motor 3 adjusts the speed of the first motor 3 according to the received speed instruction, and the feed flow regulating device, for example, the PLC for controlling the electric valve adjusts the opening of the feed electric valve according to the flow instruction, thereby realizing the optimization adjustment of the operating parameters of the cyclone sand settling drum 1.

[0134] According to the collected data of the current I of the first motor 3, the temperature T of the first motor 3, and the vibration amplitude A of the external bearing of the rotating rod 4, the comprehensive state index S is calculated:

[0135]

[0136] Among them, I nom 、T nom 、A nom are respectively the normal nominal values ​​of the current, temperature and bearing vibration amplitude of the first motor 3; I max 、T max 、A max are the maximum allowable values ​​of the current, temperature and bearing vibration amplitude of the first motor 3 respectively; α1, α2 and α3 are weight coefficients, and α1+α2+α3=1, root

[0137] Determined by the degree of influence of each parameter on the equipment failure. When the comprehensive index S of the equipment status exceeds the preset threshold S th When a fault occurs, the control and management system will issue a fault warning signal and notify the maintenance personnel through text messages, emails, etc. At the same time, it will record the time of the fault, relevant parameters and other information to facilitate fault analysis and processing.

[0138] The above technical solution is explained as follows: the calculated optimal operating parameters are converted into control instructions and accurately transmitted to the motor speed control device and the feed flow control device. This process achieves a seamless transition from data analysis and parameter optimization to actual equipment control, ensuring that the cyclone sand settling drum 1 can operate according to the optimal parameters in a timely manner. Compared with traditional manual parameter adjustment methods, this method not only greatly improves the adjustment speed and accuracy, but also reduces the possibility of human error, ensuring that the equipment is always in an efficient operating state, fully utilizing the results of parameter optimization calculations, and ensuring the sand settling effect and equipment operational stability.

[0139] The dynamic simulation model module establishes a dynamic simulation model of the internal flow field of the cyclone sand settling chamber 1 based on the principles of computational fluid dynamics; the finite volume method is used to grid the cyclone chamber and discretize it into multiple control volume units;

[0140] Solve the continuity equation, momentum equation and energy equation for each control volume element;

[0141] Continuity equation:

[0142]

[0143] Where ρ is the fluid density, t is the time, is the fluid velocity vector. This equation states that within any control volume, the sum of the rate of change of the fluid mass with time and the mass flux through the control volume surface is zero, ensuring conservation of fluid mass.

[0144] Momentum equation:

[0145]

[0146] Where p is the pressure, μ is the fluid dynamic viscosity, is the gravity acceleration vector. This equation describes the change in momentum of the fluid under the action of inertia, pressure gradient, viscosity and gravity. The feed flow Q collected in real time f , motor speed n f The data are input into the simulation model as boundary conditions to dynamically update the simulation results of the flow field inside the cyclone 1. Calculate the flow velocity distribution in the cyclone chamber Parameters such as pressure distribution p(x, y, z) provide more detailed internal flow field information for subsequent parameter optimization and working condition analysis.

[0147] The above technical solution is explained as follows: Based on the principles of computational fluid dynamics, a dynamic simulation model of the internal flow field of the cyclone 1 is established. Previously, the understanding of the internal flow field of the cyclone 1 was relatively vague. However, this step, by solving the continuity equation and momentum equation, can obtain detailed information on parameters such as the flow velocity distribution and pressure distribution within the cyclone chamber. This internal flow field information provides a more in-depth basis for optimizing operating parameters, helping technicians to gain a deeper understanding of the internal working principles of the equipment, thereby enabling targeted adjustments to operating parameters to make the internal flow field of the cyclone 1 more conducive to sediment separation, further improving the sedimentation effect and tapping the equipment's operational potential.

[0148] The sand removal optimization model module is used to establish a sand removal optimization model. The specific method is as follows:

[0149] First, calculate the sediment deposition rate V of the discharge pipe 8 d :

[0150]

[0151] Among them, k d is a coefficient related to the structure of the discharge pipe 8 and the characteristics of the sediment, and m and n are empirical indices.

[0152] This formula reflects the influence of sediment concentration and feed flow rate on the sediment deposition rate at the discharge outlet.

[0153] Then, set the critical blockage volume V of the discharge pipe 8 c , when the sediment volume V in the discharge pipe 8 s Reaching the critical blockage volume V c When the set ratio is reached, the sand discharge optimization control strategy is started, and the sand discharge control valve 9 opening O and the sand discharge time t are adjusted. s , maximize the efficiency of sand removal and avoid blockage;

[0154] Establish sediment removal efficiency η s The calculation formula is:

[0155]

[0156] Among them, V e The actual discharged sediment volume is calculated by particle swarm optimization algorithm to optimize the opening O of the control valve 9 of the discharge pipe 8 and the sediment discharge time t. s Optimize the sediment removal efficiency η s Maximize the objective function and solve the optimal sand outlet valve opening Q under the condition of no blockage. opt and sediment discharge time t opt , and send the control instructions to the sand discharge outlet control and management system.

[0157] The above technical solution is explained as follows: A sand discharge optimization model is established to address the risk of blockage in the discharge pipe 8 and the sand discharge efficiency issues. In actual operation, blockage in the discharge pipe 8 will affect the normal operation of the equipment, and traditional methods lack effective prevention and solution measures. By calculating the sediment deposition rate, setting the critical blockage volume, and using the particle swarm optimization algorithm to adjust the opening of the control valve 9 of the discharge pipe 8 and the sand discharge time, scientific sand discharge management is achieved. This not only reduces the risk of blockage in the discharge pipe 8 and the number of equipment shutdowns for cleaning, but also improves the sand discharge efficiency, allowing sediment to be discharged in a timely and smooth manner, ensuring the continuous and efficient operation of the cyclone sand settling drum 1, and reducing maintenance workload and costs.

[0158] The collaborative control module is used to establish a multi-device collaborative control model when multiple cyclone sand settling drums 1 are running simultaneously;

[0159] According to the total water intake Q total The processing capacity of each cyclone sand settling drum 1 is determined by its specification parameters and the maximum processing flow Q max,i , i=1,2,…,N, N is the number of cyclone sand settling tubes 1, calculate the optimal distribution flow Q of each cyclone sand settling tube 1 all,i ;

[0160] First, introduce the fairness indicator γ i :

[0161]

[0162] This indicator is used to measure the ratio of the allocated flow to the maximum processing flow of each device, ensuring that the load of each device is relatively balanced. total Minimum is the objective function, and a multi-device collaborative optimization model is established:

[0163]

[0164] in, is the power of the first motor 3 of the i-th cyclone sand settling drum 1;

[0165] At the same time, the constraints are met:

[0166]

[0167] 0≤Q all,i ≤Q max,i ;

[0168] The branch and bound algorithm is used to solve the multi-device collaborative optimization model to obtain the optimal distribution flow Q of each cyclone sand settling tube 1. all,i and optimal motor speed n i,opt , and send control instructions respectively to achieve the coordinated and efficient operation of multiple cyclone sand settling drums 1.

[0169] When multiple cyclone desilting drums 1 operate simultaneously, a collaborative control model is established. Traditionally, multiple devices operate independently, resulting in problems such as unbalanced loads and high energy consumption. By introducing a fairness indicator and minimizing total energy consumption as the objective function, a branch-and-bound algorithm is used to determine the optimal flow rate distribution and speed of the first motor 3 for each device. This achieves collaborative coordination among multiple devices, balancing their loads and preventing over-operation of some devices. This reduces overall energy consumption when processing the same amount of water, while also improving the equipment's comprehensive processing capacity and operational stability, fully leveraging the collaborative advantages of multiple devices.

[0170] The environmental parameter compensation control module considers the influence of environmental factors (such as temperature, humidity, and altitude) on the operating performance of the cyclone sand settling drum 1 and establishes an environmental parameter compensation model;

[0171] The effect of temperature on fluid viscosity is corrected using the Andrade formula:

[0172]

[0173] Where μ0 is the viscosity at reference temperature T0, B and C are constants related to fluid properties, and T is the actual ambient temperature. The formula for the effect of altitude on atmospheric pressure is:

[0174]

[0175] Where p0 is the atmospheric pressure at sea level, M is the molar mass of air, g is the acceleration due to gravity, h is the altitude above sea level, and R is the universal gas constant. Based on the corrected fluid viscosity and atmospheric pressure, the parameter optimization calculation model from step 4 is compensated and adjusted to recalculate the optimal operating parameters under the current environmental conditions, ensuring that the cyclone desilting chamber 1 maintains good operating performance under various environments.

[0176] This step considers the impact of environmental factors such as temperature, humidity, and altitude on the equipment's operating performance and establishes an environmental parameter compensation model. Fluid viscosity, atmospheric pressure, and other factors can change under different environmental conditions, affecting the performance of the cyclone 1. Traditional control methods typically ignore these factors. This step compensates and adjusts the operating parameter optimization model by correcting parameters such as fluid viscosity and atmospheric pressure. This ensures that the cyclone 1 can adjust to appropriate operating parameters based on actual conditions under different temperatures and altitudes, maintaining stable operating performance. This expands the equipment's application range and improves its environmental adaptability.

[0177] In this embodiment, it also includes:

[0178] The control and management system stores all collected operating data, operating condition analysis results, parameter optimization calculation results, and equipment status monitoring data in a database. This stored data is regularly analyzed using data mining algorithms (such as the Apriori algorithm for association rule mining) to analyze the correlation between operating parameters and sedimentation performance and energy consumption under different operating conditions. This analysis summarizes the optimized operating rules and provides a more accurate basis for subsequent parameter optimization and operating condition analysis.

[0179] The control and management system is connected to the remote monitoring center via a network communication module. Maintenance personnel can use the remote monitoring center's client software to view real-time information such as the cyclone 1's operating status, operating parameters, and equipment status assessment results. Furthermore, the remote monitoring center can send control commands to the control and management system, enabling remote control and management of the cyclone 1, such as adjusting operating parameters and starting or stopping the equipment.

[0180] The control and management system features adaptive learning capabilities, continuously adjusting the parameters of the operating condition analysis model, parameter optimization calculation model, and equipment status assessment model based on historical operating data and optimization results. For example, the operating condition classification model is trained using a neural network algorithm to improve its accuracy. Based on the discrepancy between actual operating results and the optimization objectives, the weight coefficients in the multi-objective optimization function are adjusted to ensure that parameter optimization better meets actual needs, thereby achieving continuous optimization of the control and management method and enhancing its adaptive capabilities.

[0181] Regularly inspect and maintain the hardware equipment of the control and management system (such as sensors, control modules, data transmission modules, etc.) to ensure normal operation of the equipment. At the same time, according to technological developments and actual application needs, upgrade the control and management system software, update algorithm models, optimize the user interface, etc., to improve the system's performance and functionality.

[0182] We developed a human-machine interactive intelligent decision support system, leveraging natural language processing (NLP) technology to enable natural language interaction between maintenance personnel and the control and management system. Maintenance personnel can input questions via voice or text, such as "How can I further improve processing efficiency under current operating conditions?" The system then uses knowledge graph technology to reason and analyze historical data, real-time operating data, and operating condition analysis results, generating detailed decision-making recommendation reports, including parameter adjustment plans and equipment maintenance suggestions. These reports are presented to maintenance personnel in the form of visual charts and text descriptions, helping them make more scientific and reasonable decisions.

[0183] In summary, in this embodiment, data acquisition and processing is performed in real time using multiple sensors to collect data such as feed flow, pressure, and rotational speed. A mean filtering algorithm is then applied to remove noise, providing a precise and reliable data foundation for subsequent analysis. This changes the traditional, extensive model that relies on manual judgment and experience, making the acquisition of equipment operating information more comprehensive, timely, and accurate. Based on this data, operating condition analysis utilizes machine learning algorithms to establish an operating condition classification model, which accurately identifies different operating conditions and provides a basis for parameter optimization, resolving the problem that traditional fixed parameter control cannot adapt to changing sewage characteristics.

[0184] By establishing a multi-objective optimization function and combining it with a genetic algorithm, we achieve the optimal balance between energy consumption and processing efficiency under different operating conditions. The control instruction transmission step ensures that the optimized parameters are accurately transmitted to the equipment, enabling fast and accurate automatic adjustment, reducing human operational errors and ensuring efficient equipment operation. Equipment status monitoring and fault warnings calculate equipment status indicators based on multiple parameters, detect potential faults in advance, issue warnings, and record information, reducing the risk of sudden equipment failure.

[0185] The operational data storage and analysis function leverages data mining algorithms to uncover correlations between data, providing more empirical support for parameter optimization and operating condition analysis, and continuously improving the scientific nature of control methods. Remote monitoring and management overcomes geographical restrictions, allowing maintenance personnel to monitor equipment status in real time and operate remotely, improving management efficiency and shortening fault response time. Adaptive learning and optimization enable the system to evolve based on operational data, continuously adjusting model parameters to enhance system adaptability and optimization effectiveness. System maintenance and upgrades regularly update software and hardware to ensure long-term stable operation.

[0186] Based on computational fluid dynamics principles, in-depth analysis of the equipment's internal flow field provides a more in-depth basis for optimizing operating parameters. Environmental parameter compensation control considers the impact of environmental factors on equipment performance. Through parameter correction and compensation adjustments, it expands the equipment's application range and enhances environmental adaptability. The human-computer interactive intelligent decision support system utilizes natural language processing and knowledge graph technology to reduce the expertise required of maintenance personnel and improve the scientific nature and efficiency of decision-making.

[0187] To sum up, the operating efficiency, sand settling effect, equipment reliability and intelligent management level of the cyclone sand settling drum 1 are comprehensively improved, energy consumption and maintenance costs are effectively reduced, it has significant economic benefits and practical value, and provides a strong technical guarantee for the efficient and stable operation of the cyclone sand settling drum 1.

[0188] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood broadly. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to direct connections, indirect connections through an intermediary, or internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0189] While the embodiments of the present invention have been shown and described, it will be apparent to those skilled in the art that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A cyclone sedimentation device for water conservancy projects, characterized in that: include: A cyclone sand settling drum (1), wherein the outside of the cyclone sand settling drum (1) is fixedly connected to a water inlet pipe (7) and a drain pipe (6), the bottom of the cyclone sand settling drum (1) is fixedly connected to a discharge pipe (8), a control valve (9) is fixedly connected to the discharge pipe (8), and an electric valve is fixedly connected to the inside of the water inlet pipe (7); A cyclone assembly, the cyclone assembly being arranged in a cyclone sand settling drum (1); A sand-water separation component, wherein the sand-water separation component is used to separate sand and water; A conveying assembly, wherein the conveying assembly is used to convey sand and water into the sand and water separation assembly; A control management unit is provided, wherein the control management unit is used for real-time monitoring and analysis of the operating state of the cyclone sand settling drum (1).

2. A cyclone sedimentation device for water conservancy projects according to claim 1, characterized in that: The cyclone assembly comprises a fixing frame (2) fixedly connected to the top of the cyclone sand settling drum (1), a first motor (3) fixedly connected to the outside of the fixing frame (2), a rotating rod (4) fixedly connected to the output end of the first motor (3), and a blade (5) fixedly connected to the outside of the rotating rod (4); the outside of the fixing frame (2) is fixedly connected to a bearing seat, and the rotating rod (4) is fixedly connected to the inner ring of a bearing in the bearing seat.

3. A cyclone sedimentation device for water conservancy projects according to claim 2, characterized in that: The sand-water separation assembly comprises a sand-water separation box (13) and a fixed pipe (15) fixedly connected to the sand-water separation box (13); the outside of the sand-water separation box (13) is fixedly connected to a water outlet pipe (14); the inside of the sand-water separation box (13) is fixedly connected to an arc-shaped protrusion (18) and a blocking column (19); the inside of the fixed pipe (15) is rotatably connected to a spiral conveying rod (20); the area of ​​the fixed pipe (15) located in the sand-water separation box (13) is set as an opening; one end of the fixed pipe (15) is fixedly connected to a discharge pipe (16); the outside of the fixed pipe (15) is fixedly connected to a second motor (17); the output end of the second motor (17) is fixedly connected to the spiral conveying rod (20).

4. A cyclone sedimentation device for water conservancy projects according to claim 3, characterized in that: The conveying assembly is a pump body (10), the input end of the pump body (10) is fixedly connected to a first pipe (11), the output end of the pump body (10) is fixedly connected to a second pipe (12), the first pipe (11) is fixedly connected to a discharge pipe (8), and the second pipe (12) is fixedly connected to the inside of a sand-water separation box (13).

5. The cyclone sedimentation device for water conservancy projects according to claim 1, characterized in that: The control management unit includes a data acquisition module, a data preprocessing module, a working condition analysis model module, a parameter optimization module, an instruction sending module, a dynamic simulation model module, a sand discharge optimization model module, a collaborative control module and an environmental parameter compensation control module.

6. A cyclone sedimentation device for water conservancy projects according to claim 5, characterized in that: The water inlet pipe (7) of the data acquisition module is equipped with a flow sensor to collect the feed flow Q in real time. The collection frequency of the flow sensor is f Q ; Pressure sensors are installed at different positions of the cyclone chamber of the cyclone sand settling drum (1) to collect pressure data P at different positions. i (i=1,2,…,n, n is the number of pressure sensors), the pressure sensor acquisition frequency is f P ; A speed sensor is installed on the outside of the first motor (3) to collect the motor speed n, with a collection frequency of f n ; A concentration detector is installed in the discharge pipe (8) to detect the concentration C of discharged sediment. The sampling frequency is f C ; All collected data is transmitted to the control and management system in real time through the data transmission module; The pre-processing module filters the collected data to remove noise interference; Using the mean filtering algorithm, for the collected feed flow data, the kth filtered value Q f (k) is calculated as follows: Where m is the filter window size, and Q(i) is the i-th feed flow data originally collected.

7. A cyclone sedimentation device for water conservancy projects according to claim 6, characterized in that: The operating condition analysis model module first calculates the rate of change of the feed flow Where Δt is the time interval between two adjacent data collections, Calculate the pressure gradient in the swirl chamber using pressure data Where L is the average distance between two adjacent pressure sensors. Combining data such as feed flow rate change rate, pressure gradient, and sediment concentration, a machine learning algorithm was used to establish an operating condition classification model, which categorizes the operating conditions into low-sediment-content stable conditions and high-sediment-content fluctuating conditions. The parameter optimization module calculates the optimal operating parameters of the cyclone sand settling drum (1) using an optimization algorithm based on the results of the working condition analysis; Taking energy consumption E and processing efficiency η as optimization objectives, a multi-objective optimization function is established: Where ω1 and ω2 are weight coefficients, and ω1+ω2=1; The calculation formula for energy consumption E is: E=P e ×t; Among them, P e is the power of the first motor (3), P e =k1n 2 +k2n+k3, k1, k2, k3 are constants related to the characteristics of the first motor (3); t is the running time; The calculation formula for treatment efficiency η is: Among them, V s is the volume of sediment separated per unit time, V s =C f Q f ; V i is the feed volume per unit time, V i =Q f ; The instruction sending module calculates the speed n of the first motor (3) based on the control management system. opt and feed flow Q opt Converting the command into a control command and sending it to the first motor (3) and the electric valve through the control management system; Based on the collected data of the current I of the first motor (3), the temperature T of the first motor (3), and the vibration amplitude A of the external bearing of the rotating rod (4), the comprehensive state index S is calculated: Among them, I nom 、T nom 、A nom are respectively the normal nominal values ​​of the current, temperature and bearing vibration amplitude of the first motor (3); I max 、T max 、A max They are respectively the maximum allowable values ​​of the current, temperature and bearing vibration amplitude of the first motor (3); α1, α2 and α3 are weight coefficients, and α1+α2+α3=1.

8. A cyclone sedimentation device for water conservancy projects according to claim 7, characterized in that: The dynamic simulation model module is based on the principle of computational fluid dynamics to establish a dynamic simulation model of the internal flow field of the cyclone sedimentation chamber (1); the finite volume method is used to mesh the cyclone chamber and discretize it into multiple control volume units; Solve the continuity equation, momentum equation and energy equation for each control volume element; Continuity equation: Where ρ is the fluid density, t is the time, is the fluid velocity vector; Momentum equation: Where p is the pressure, μ is the fluid dynamic viscosity, is the gravitational acceleration vector; The sand removal optimization model module is used to establish a sand removal optimization model. The specific method is as follows: First, calculate the sediment deposition rate V of the discharge pipe (8) d : Among them, k d is the coefficient related to the structure of the discharge pipe (8) and the characteristics of the sediment, and m and n are empirical indices; Then, set the critical blockage volume V of the discharge pipe (8) c , when the sediment volume V of the discharge pipe (8) s Reaching the critical blockage volume V c When the set ratio is reached, the sand discharge optimization control strategy is started, and the sand discharge control valve (9) opening O and the sand discharge time t are adjusted. s ; Establish sediment removal efficiency η s The calculation formula is: Among them, V e The particle swarm optimization algorithm is used to optimize the opening O of the control valve (9) of the discharge pipe (8) and the discharge time t for the actual discharged sediment volume. s Optimize the sediment removal efficiency η s Maximize the objective function and find the valve opening O of the sand outlet opt and sediment discharge time t opt。 9. A cyclone sedimentation device for water conservancy projects according to claim 8, characterized in that: The collaborative control module is used to establish a multi-device collaborative control model when multiple cyclone sand settling drums (1) are running simultaneously; According to the total water intake Q total and the processing capacity of each cyclone sand settling drum (1), calculate the optimal distribution flow Q of each cyclone sand settling drum (1) all,i ; First, introduce the fairness indicator γ i : The total energy consumption of all equipment E total Minimum is the objective function, and a multi-device collaborative optimization model is established: in, is the power of the first motor (3) of the i-th cyclone sand settling drum (1); At the same time, the constraints are met: 0≤Q all,i ≤Q max,i 。 10. A cyclone sedimentation device for water conservancy projects according to claim 9, characterized in that: The influence of the environmental parameter compensation control module on the operating performance of the cyclone sand settling drum (1) is studied, and an environmental parameter compensation model is established; The effect of temperature on fluid viscosity is corrected using the Andrade formula: Where μ0 is the viscosity at the reference temperature T0, B and C are constants related to the fluid properties, and T is the actual ambient temperature; The formula for the effect of altitude on atmospheric pressure is: Where p0 is the atmospheric pressure at sea level, M is the molar mass of air, g is the acceleration due to gravity, h is the altitude, and R is the universal gas constant.

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