Intelligent decision-making method and system for working state of damping grid based on data fusion

Abstract

The invention relates to the field of damping gates, and discloses a damping gate working state intelligent decision-making method and system based on data fusion, and the method comprises the following steps: calculating the flowing state of a fluid in an inverted siphon section of a water conveying pipeline through deploying an electromagnetic miniature flow velocity sensor array in the inverted siphon section of the water conveying pipeline, and calculating the working state of the damping gate in combination with an analogue simulation mode; the optimal opening and closing angle of the flow deflector in the damping grid connected with the inverted siphon section of the water conveying pipeline is calculated, finally, the shape memory alloy flow deflector and the damping grid are combined through temperature control treatment, and control over the optimal opening and closing angle of the flow deflector is achieved. The opening and closing angles of the flow deflectors can be dynamically adjusted according to the real-time flow velocity data to achieve dynamic flow state matching, and the rectification efficiency is improved. Meanwhile, the working state of the damping grid can be optimized in real time, head loss is reduced, eddy current is restrained, and the overall performance of the system is improved.

Description

Technical Field

[0001] The present invention relates to the field of rectifying grids, in particular to an intelligent decision-making method and system for the working state of a rectifying grid based on data fusion. Background Art

[0002] In long-distance water diversion and regulation projects, the water conveyance line is long, the water diversion flow is large, the terrain conditions passed through are complex, and the water flow patterns are complex and changeable under the coupling of multiple working conditions. There are multiple water flow forms coexisting, such as non-pressure tunnels, pressure tunnels, inverted siphons, and the connection between pressure flow and non-pressure flow. Special and complex hydraulic phenomena such as stagnant air masses and alternation of open-channel and full-flow are extremely likely to occur, affecting the water conveyance efficiency of the project and even causing abnormal hydraulic oscillations. Therefore, it is urgent to propose engineering measures to avoid adverse water flow phenomena, such as improved rectifying grid devices, to provide a scientific basis for the operation scheduling and hydraulic control of the water conveyance system.

[0003] Traditional grid-type rectifying devices have a simple structure and low manufacturing cost, but there are obvious deficiencies in actual applications: 1) Due to the limitation of the grid structure of traditional grid-type rectifying devices, the water flow will be subject to a large resistance when passing through the grid. This not only increases the energy consumption during the water flow conveyance process, but also may cause a decrease in system pressure, affecting the operation efficiency of the entire system. 2) Traditional grid-type rectifying devices cannot respond to changes in fluid parameters in a timely manner and have a regulation lag. When the fluid passes through the grid bars, parameters such as flow velocity, water temperature, and impurity content will change at any time. Traditional grid-type rectifying devices lack real-time dynamic adjustment capabilities, and their rectifying effects will be greatly reduced. 3) Traditional rectifying grid technologies have poor adaptability when facing complex flow patterns. Complex flow patterns often cover situations such as large fluctuations in flow velocity, disordered flow directions, and uneven internal pressure distribution of the fluid. Because the grid bar spacing and angle are fixed and cannot be adjusted according to the changes in the flow pattern, when the flow velocity fluctuates greatly, the fixed grid is difficult to match the changing flow velocity, and turbulence is easily generated when the fluid passes through, forming fluid fluctuations; when the flow direction is disordered, the grid cannot guide specifically, resulting in the fluid colliding randomly within the device, exacerbating the disorder of the flow; and when the internal pressure distribution is uneven, pressure differences will be generated in different regions of the fluid, thereby causing pressure pulsation phenomena. These continuous fluid fluctuations and pressure pulsations will cause the internal components of the equipment to withstand irregular impacts and vibrations, resulting in continuous wear of the surface material and a gradual decrease in structural strength, seriously shortening the service life of the equipment. At the same time, the performance of the equipment is unstable due to wear and it is difficult to work in coordination with other equipment under established parameters.

[0004] Considering the above disadvantages of existing rectifying grids, through physical model tests, numerical simulations, and deep learning algorithms, an intelligent rectifying grid control device for the inverted siphon section of a water diversion and regulation project has been developed, that is, an intelligent decision-making method and system for the working state of a rectifying grid based on data fusion is proposed. Summary of the Invention

[0005] The present invention overcomes the deficiencies of the prior art and provides an intelligent decision-making method and system for the working state of a straightening grid based on data fusion.

[0006] To achieve the above object, the technical solution adopted by the present invention is as follows: The first aspect of the present invention provides an intelligent decision-making method for the working state of a straightening grid based on data fusion, including the following steps: Determine a straightening grid that matches the inverted siphon section of the water conveyance pipeline, and deploy an electromagnetic micro flow velocity sensor array inside the inverted siphon section of the water conveyance pipeline to test the water flow state of the inverted siphon section of the water conveyance pipeline; Construct an internal flow field simulation model of the straightening grid to simulate the turbulent flow state of the fluid, and calculate the optimal opening angle of the guide vanes of the qualified target straightening grid in real time based on the turbulent flow state of the fluid; Based on the optimal opening angle of the guide vanes of the qualified target straightening grid, combined with the shape memory alloy guide vanes, perform temperature control processing on the guide vanes of the qualified target straightening grid.

[0007] Further, in a preferred embodiment of the present invention, the step of determining a straightening grid that matches the inverted siphon section of the water conveyance pipeline and deploying an electromagnetic micro flow velocity sensor array inside the inverted siphon section of the water conveyance pipeline to test the water flow state of the inverted siphon section of the water conveyance pipeline is specifically as follows: Obtain the water conveyance pipeline, determine the inverted siphon section in the water conveyance pipeline, and mark it as the inverted siphon section of the water conveyance pipeline; Calculate the bending angles at different positions of the inverted siphon section of the water conveyance pipeline, preset a bending angle threshold, and mark the position of the inverted siphon section of the water conveyance pipeline where the bending angle is maintained within the bending angle threshold as the sensor deployment position; Install electromagnetic micro flow velocity sensors at all sensor deployment positions, obtain signal modules in all electromagnetic micro flow velocity sensors, control the signal modules of all electromagnetic micro flow velocity sensors to emit connection signals, and obtain the connection signals received by the controller module from different electromagnetic micro flow velocity sensors; Perform Kalman filtering on the connection signals, and perform signal interaction on the filtered connection signals in the controller module to construct an electromagnetic micro flow velocity sensor array; Combined with the electromagnetic micro flow velocity sensor array, test the water flow state of the inverted siphon section of the water conveyance pipeline.

[0008] Further, in a preferred embodiment of the present invention, the step of combining the electromagnetic micro flow velocity sensor array to test the water flow state of the inverted siphon section of the water conveyance pipeline is specifically as follows: Control the operation of all electromagnetic micro flow sensors. Among them, the operation of the electromagnetic micro flow sensor is to control the electromagnetic micro flow sensor to deploy a magnetic field in the inverted siphon section of the water conveyance pipeline, and to monitor in real time the cutting rate of the magnetic induction lines in the inverted siphon section of the water conveyance pipeline; Based on the cutting rate of the magnetic induction lines in the inverted siphon section of the water conveyance pipeline, calculate the magnitude of the induced electromotive force output by the electromagnetic micro flow sensor. Combining the magnitude of the induced electromotive force output by the electromagnetic micro flow sensor, calculate the real-time fluid velocity at different sensor deployment positions; Obtain the rectifying grid connected to the inverted siphon section of the water conveyance pipeline, calibrate it as the target rectifying grid, connect an electromagnetic micro flow sensor array to the target rectifying grid, and update the real-time fluid velocity at different sensor deployment positions; Conduct a test on the eddy current suppression response time in the target rectifying grid. Combining the test results, calculate the eddy current suppression response time of the target rectifying grid. At the same time, preset the maximum response time. If the eddy current suppression response time of the target rectifying grid is greater than the maximum response time, then perform firmware update on the target rectifying grid, and at the same time perform firmware update on the electromagnetic micro flow sensor array connected to the target rectifying grid until the eddy current suppression response time of the target rectifying grid is not greater than the maximum response time, and obtain a qualified target rectifying grid.

[0009] Furthermore, in a preferred embodiment of the present invention, the internal flow field simulation model of the rectifying grid is constructed to simulate the turbulent flow state of the fluid, and based on the turbulent flow state of the fluid, the optimal opening angle of the guide vanes of the qualified target rectifying grid is calculated in real time. Specifically: Introduce a laser scanning device to scan and analyze the dimension data of the inverted siphon section of the water conveyance pipeline, obtain the dimension data of the inverted siphon section of the water conveyance pipeline, and combine the bending angles at different positions of the inverted siphon section of the water conveyance pipeline. At the same time, determine the installation position of the qualified target rectifying grid, and output the specification parameters of the inverted siphon section of the water conveyance pipeline; Based on the specification parameters of the inverted siphon section of the water conveyance pipeline, establish a three-dimensional geometric model in three-dimensional geometric modeling software, calibrate it as the target three-dimensional model, and determine the position and boundary of the guide vanes in the target three-dimensional model; Among them, the boundary includes the fluid inlet and fluid outlet of the inverted siphon section of the water conveyance pipeline; Combining the target three-dimensional model and the corresponding guide vane position and boundary parameters, construct a turbulent model of the target three-dimensional model, calibrate it as the target three-dimensional turbulent model, and at the same time perform mesh division on the target three-dimensional turbulent model to calculate the quantization index threshold of the flow field in the target three-dimensional turbulent model; Among them, the quantization index threshold of the flow field in the target three-dimensional turbulent model includes the flow velocity uniformity threshold and the head loss coefficient threshold; Combined with the quantization index threshold of the flow field in the target three-dimensional turbulence model, perform a turbulence simulation operation on the target three-dimensional turbulence model, and in combination with the results of the turbulence simulation operation, calculate the optimal opening and closing angle of the guide vanes of the qualified target flow straightener in real time.

[0010] Further, in a preferred embodiment of the present invention, the performing a turbulence simulation operation on the target three-dimensional turbulence model and in combination with the results of the turbulence simulation operation to calculate the optimal opening and closing angle of the guide vanes of the qualified target flow straightener in real time is specifically as follows: Perform a turbulence simulation operation on the target three-dimensional turbulence model, and conduct an orthogonal experiment on the model corresponding to the qualified target flow straightener during the turbulence simulation operation to generate different flow field characteristic data sets, wherein the fluid velocities at the boundaries and the opening and closing angles of the guide vanes in different flow field characteristic data sets are different; Based on different flow field characteristic data sets, generate a CFD predicted flow field, and in combination with the real-time fluid velocities at different sensor deployment positions, correct the boundary conditions of the CFD predicted flow field to generate a target CFD predicted flow field; Through the Gaussian regression algorithm, perform a principal component analysis on the fluid velocity data in the target CFD predicted flow field, and based on the quantization index threshold of the flow field in the target three-dimensional turbulence model, construct the objective function of the algorithm; During the principal component analysis process, in combination with the objective function of the algorithm, generate the optimal opening and closing angles of the guide vanes at different fluid velocities, wherein the optimal opening and closing angles of the guide vanes need to ensure that the quantization indexes output at different fluid velocities are maintained within the quantization index threshold; If there is no opening and closing angle of the guide vane to keep the quantization index output by the fluid velocity within the quantization index threshold, then perform dynamic error correction on the target CFD predicted flow field through the extended Kalman filter algorithm, and introduce a genetic algorithm during the output process of the extended Kalman filter algorithm to perform secondary correction and convergence on the boundary conditions of the target CFD predicted flow field until there is an opening and closing angle of the guide vane to keep the quantization index output by the fluid velocity within the quantization index threshold.

[0011] Further, in a preferred embodiment of the present invention, the performing a temperature control process on the guide vanes of the qualified target flow straightener in combination with the shape memory alloy guide vanes based on the optimal opening and closing angle of the guide vanes of the qualified target flow straightener is specifically as follows: Obtain the shape memory alloy guide vane and determine the material parameters of the shape memory alloy guide vane; Introduce a big data network, and based on the material parameters of the shape memory alloy guide vane in the big data network, retrieve the corresponding recovery states when different temperatures are applied to the shape memory alloy guide vane, and construct a guide vane - temperature change map; The control module for obtaining a qualified target rectifying grid replaces the shape memory alloy guide vane into the qualified target rectifying grid, and a heating module is connected in parallel in the control module of the qualified target rectifying grid. At the same time, the guide vane - temperature change map is imported into the control module of the qualified target rectifying grid; Based on the control module of the qualified target rectifying grid, temperature control is performed on the shape memory alloy guide vane. Among them, the temperature control of the shape memory alloy guide vane is that according to the real - time temperature of the fluid flowing through the qualified target rectifying grid, the shape memory alloy guide vane automatically follows the temperature for plastic treatment. After the shape memory alloy guide vane is plastically deformed, if the required opening and closing angle of the shape memory alloy guide vane is greater than the current opening and closing angle, continue to perform automatic plastic treatment according to the real - time temperature of the fluid flowing through the qualified target rectifying grid; If the required opening and closing angle of the shape memory alloy guide vane is less than the current opening and closing angle, then in combination with the guide vane - temperature change map, the control module controls the heating module to apply the temperature corresponding to the optimal opening and closing angle of the shape memory alloy guide vane to the shape memory alloy guide vane.

[0012] The second aspect of the present invention also provides an intelligent decision - making system for the working state of a rectifying grid based on data fusion. The working - state intelligent decision - making system includes a memory and a processor. The memory stores a working - state intelligent decision - making method. When the working - state intelligent decision - making method is executed by the processor, the following steps are realized: Determine the rectifying grid that matches the inverted siphon section of the water conveyance pipeline, and deploy an electromagnetic micro - flow velocity sensor array inside the inverted siphon section of the water conveyance pipeline to test the water flow state of the inverted siphon section of the water conveyance pipeline; Construct an internal flow field simulation model of the rectifying grid to simulate the turbulent flow state of the fluid, and calculate the optimal opening and closing angle of the guide vane of the qualified target rectifying grid in real - time based on the turbulent flow state of the fluid; Based on the optimal opening and closing angle of the guide vane of the qualified target rectifying grid, in combination with the shape memory alloy guide vane, perform guide vane temperature control on the qualified target rectifying grid.

[0013] The present invention solves the technical defects in the background art and has the following beneficial effects: By deploying an electromagnetic micro - flow velocity sensor array inside the inverted siphon section of the water conveyance pipeline, calculating the flow state of the fluid in the inverted siphon section of the water conveyance pipeline, combining with the form of simulation, calculating the optimal opening and closing angle of the guide vane in the rectifying grid connected to the inverted siphon section of the water conveyance pipeline, and finally through temperature control, realizing the combination of the shape memory alloy guide vane and the rectifying grid, and realizing the control of the optimal opening and closing angle of the guide vane. The present invention can dynamically adjust the opening and closing angle of the guide vane according to real - time flow velocity data to achieve dynamic flow state matching, improve the rectification efficiency. At the same time, it can optimize the working state of the rectifying grid in real - time, reduce the head loss, suppress the eddy current, and improve the overall performance of the system. Brief Description of the Drawings

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings of embodiments can also be obtained based on these drawings.

[0015] Figure 1 Shows the flowchart of the intelligent decision-making method for the working state of the fairing based on data fusion; Figure 2 Shows the flowchart of the method for calculating the optimal opening angle of the guide vanes of the qualified target fairing; Figure 3 Shows the program view of the intelligent decision-making system for the working state of the fairing based on data fusion. Detailed Embodiments

[0016] In order to be able to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention will be further described in detail below in conjunction with the drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0017] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0018] Figure 1 Shows the flowchart of the intelligent decision-making method for the working state of the fairing based on data fusion, including the following steps: S102: Determine the fairing that matches the siphon section of the water conveyance pipeline, and deploy an electromagnetic micro flow velocity sensor array inside the siphon section of the water conveyance pipeline for testing the water flow state of the siphon section of the water conveyance pipeline; S104: Construct an internal flow field simulation model of the fairing to simulate the turbulent flow state of the fluid, and calculate the optimal opening angle of the guide vanes of the qualified target fairing in real time based on the turbulent flow state of the fluid; S106: Based on the optimal opening angle of the guide vanes of the qualified target fairing, combined with the shape memory alloy guide vanes, perform temperature control processing on the guide vanes of the qualified target fairing.

[0019] Further, in a preferred embodiment of the present invention, the method for determining the flow rectifying grid matching the inverted siphon section of the water conveyance pipeline and deploying an electromagnetic micro flow velocity sensor array inside the inverted siphon section of the water conveyance pipeline for testing the water flow state of the inverted siphon section of the water conveyance pipeline is specifically as follows: Obtain the water conveyance pipeline, determine the inverted siphon section in the water conveyance pipeline, and label it as the inverted siphon section of the water conveyance pipeline; Calculate the bending angles at different positions of the inverted siphon section of the water conveyance pipeline, preset a bending angle threshold, and label the positions of the inverted siphon section of the water conveyance pipeline where the bending angles are maintained within the bending angle threshold as the sensor deployment positions; Install electromagnetic micro flow velocity sensors at all sensor deployment positions, obtain signal modules from all electromagnetic micro flow velocity sensors, control the signal modules of all electromagnetic micro flow velocity sensors to emit connection signals, and obtain the connection signals received by the controller module from different electromagnetic micro flow velocity sensors; Perform Kalman filtering on the connection signals, and perform signal interaction on the filtered connection signals in the controller module to construct an electromagnetic micro flow velocity sensor array; Combine the electromagnetic micro flow velocity sensor array to test the water flow state of the inverted siphon section of the water conveyance pipeline.

[0020] It should be noted that there is a certain lag in the flow velocity monitoring of traditional flow rectifying grids, mainly because the monitoring and feedback of water flow velocity are relatively slow. The micro flow velocity sensor array can monitor the water flow velocity in real time and transmit the data to the control system. The micro flow velocity sensor array can achieve accurate measurement of the water flow velocity. After comparison of various micro flow velocity sensors, the electromagnetic micro flow velocity sensor is more suitable for various common water conservancy structures, such as large water conservancy project water conveyance channels, etc., which have strict requirements for water flow resistance, complex flow states, and require rapid response regulation systems. Before installing the sensor, it is necessary to determine the sensor installation position. The sensor needs to be installed at the diameter mutation and bending sections of the inverted siphon section of the water conveyance pipeline to calculate the flow velocity distribution characteristics. Therefore, the bending angles at different positions of the inverted siphon section of the water conveyance pipeline are calculated to obtain the installation positions. Since the fluid flow velocities at different positions may be different, it is necessary to analyze by combining the fluid flow velocities at all positions, construct an electromagnetic micro flow velocity sensor array, and fuse and analyze the signals of different sensors. At the same time, the collected data may have heavy data noise. Therefore, it is necessary to combine the Kalman filtering algorithm to perform Kalman filtering on the signals to achieve the purpose of noise reduction. The electromagnetic micro flow velocity sensor has the advantages of small water flow resistance, fast response speed, not affected by fluid impurities and bubbles, can accurately measure the flow velocity and direction under complex flow states, high precision, can accurately measure the flow velocity in complex environments, and moderate maintenance cost compared with piezoelectric, ultrasonic, and thermal sensors. Therefore, the electromagnetic micro flow velocity sensor is selected.

[0021] Furthermore, in a preferred embodiment of the present invention, the combined electromagnetic micro flow velocity sensor array is used to test the water flow state in the inverted siphon section of the water conveyance pipeline, specifically as follows: Control the operation of all electromagnetic micro flow velocity sensors. Among them, the operation of the electromagnetic micro flow velocity sensor is to control the electromagnetic micro flow velocity sensor to arrange a magnetic field in the inverted siphon section of the water conveyance pipeline and real-time monitor the cutting rate of the magnetic induction lines in the inverted siphon section of the water conveyance pipeline; Based on the cutting rate of the magnetic induction lines in the inverted siphon section of the water conveyance pipeline, calculate the magnitude of the induced electromotive force output by the electromagnetic micro flow velocity sensor. Combine the magnitude of the induced electromotive force output by the electromagnetic micro flow velocity sensor to calculate the real-time flow velocity of the fluid at different sensor deployment positions; Obtain the straightening grid connected to the inverted siphon section of the water conveyance pipeline, calibrate it as the target straightening grid, connect the electromagnetic micro flow velocity sensor array to the target straightening grid, and update the real-time flow velocity of the fluid at different sensor deployment positions; Conduct a test on the eddy current suppression response time in the target straightening grid. Combine the test results to calculate the eddy current suppression response time of the target straightening grid. At the same time, preset the maximum response time. If the eddy current suppression response time of the target straightening grid is greater than the maximum response time, update the firmware of the target straightening grid, and at the same time update the firmware of the electromagnetic micro flow velocity sensor array connected to the target straightening grid until the eddy current suppression response time of the target straightening grid is not greater than the maximum response time to obtain a qualified target straightening grid.

[0022] It should be noted that the electromagnetic micro flow velocity sensor works based on the principle of electromagnetic induction. Its core is to make the fluid flow in a magnetic field. When the fluid cuts the magnetic induction lines as a conductor, an induced electromotive force will be generated. By detecting the magnitude of this electromotive force, the flow velocity of the fluid can be calculated. Whether it is a complex river channel with rapid water flow and vortices, or a water conservancy project with poor water quality and a large amount of sediment, it can accurately and quickly measure the flow velocity and direction, providing an accurate and reliable basis for the stable operation of the water conservancy structure. The target straightening grid is an intelligent straightening grid device. The electromagnetic micro flow velocity sensor array is connected inside the target straightening grid, significantly reducing the time delay from abnormal flow state identification to eddy current suppression response. This low-delay characteristic enables the intelligent straightening grid to quickly capture abnormal situations and make timely adjustments, improving the control efficiency of abnormal flow states. The built-in micro flow velocity sensor array can monitor the water flow in real time with high precision, significantly improving the monitoring efficiency of the water flow. This high-precision monitoring ability enables the intelligent straightening grid to more accurately identify abnormal flow states, providing reliable data support for subsequent eddy current suppression.

[0023] The advantages of the present invention are that the micro flow velocity sensor array can monitor the water flow velocity in real time and provide high-precision data support. It changes the situation of the traditional flow rectifying grid with lagging and inaccurate real-time data acquisition, adopts independent data acquisition and transmission, and transmits the data to the control center in real time, providing reliable data support for subsequent intelligent control.

[0024] Furthermore, in a preferred embodiment of the present invention, for the best opening and closing angle of the guide vane based on the qualified target flow rectifying grid, combined with the shape memory alloy guide vane, temperature control processing is performed on the guide vane of the qualified target flow rectifying grid, specifically as follows: Obtain the shape memory alloy guide vane and determine the material parameters of the shape memory alloy guide vane; Introduce the big data network, and based on the material parameters of the shape memory alloy guide vane in the big data network, retrieve the corresponding recovery states when different temperatures are applied to the shape memory alloy guide vane, and construct a guide vane-temperature change map; Obtain the control module of the qualified target flow rectifying grid, replace the shape memory alloy guide vane into the qualified target flow rectifying grid, and connect a heating module in parallel in the control module of the qualified target flow rectifying grid, and at the same time import the guide vane-temperature change map into the control module of the qualified target flow rectifying grid; Based on the control module of the qualified target flow rectifying grid, perform temperature control processing on the shape memory alloy guide vane. Among them, the temperature control processing of the shape memory alloy guide vane is that according to the real-time temperature of the fluid flowing through the qualified target flow rectifying grid, the shape memory alloy guide vane automatically follows the temperature for plastic processing. After the shape memory alloy guide vane is plastically deformed, if the shape memory alloy guide vane needs to control the opening and closing angle to be greater than the current opening and closing angle, continue to perform automatic plastic processing according to the real-time temperature of the fluid flowing through the qualified target flow rectifying grid; If the shape memory alloy guide vane needs to control the opening and closing angle to be less than the current opening and closing angle, then in combination with the guide vane-temperature change map, control the heating module through the control module to apply the temperature corresponding to the best opening and closing angle of the shape memory alloy guide vane to the shape memory alloy guide vane.

[0025] It should be noted that shape memory alloy (SMA) has unique shape memory effect and superelasticity. It can deform under the action of external force and return to its original shape when the temperature changes. This device deforms the shape memory alloy flow deflector to the optimal angle by controlling the temperature. The shape memory alloy flow deflector can automatically adjust the opening and closing angle of the deflector according to the change of water temperature. After the shape memory alloy undergoes plastic deformation at low temperature, when heated to a certain specific temperature, it can return to the shape before deformation. That is, if a larger opening and closing angle of the deflector is required, the opening and closing angle can be automatically adjusted directly according to the temperature. If a smaller opening and closing angle is required, heating is needed to restore the opening and closing angle. Since the water temperature changes with different flow rates, the opening and closing angle of the deflector can also be analyzed according to the flow rate.

[0026] This intelligent device innovatively applies memory metal to the rectifying grid. Shape memory alloy (SMA) has unique shape memory effect and superelasticity, and can automatically adjust the opening and closing angle of the deflector according to the change of water temperature. Through the thermosensitive characteristics of SMA material, the automatic adjustment function of the deflector is realized, reducing manual intervention and improving the intelligent level of the system.

[0027] Figure 2 The method flow chart for calculating the optimal opening and closing angle of the deflector of a qualified target rectifying grid is shown, including the following steps: S202: Construct a simulation model of the internal flow field of the rectifying grid to simulate the turbulent flow state of the fluid, and calculate the optimal opening and closing angle of the deflector of the qualified target rectifying grid in real time based on the turbulent flow state of the fluid; S204: Conduct a turbulent simulation run on the target three-dimensional turbulent model, and calculate the optimal opening and closing angle of the deflector of the qualified target rectifying grid in real time in combination with the results of the turbulent simulation run.

[0028] Furthermore, in a preferred embodiment of the present invention, the constructing a simulation model of the internal flow field of the rectifying grid to simulate the turbulent flow state of the fluid, and calculating the optimal opening and closing angle of the deflector of the qualified target rectifying grid in real time is specifically as follows: Introduce a laser scanning device to scan and analyze the dimensional data of the inverted siphon section of the water conveyance pipeline, obtain the dimensional data of the inverted siphon section of the water conveyance pipeline, and combine the bending angles at different positions of the inverted siphon section of the water conveyance pipeline to determine the installation position of the qualified target rectifying grid at the same time, and output the specification parameters of the inverted siphon section of the water conveyance pipeline; Based on the specification parameters of the inverted siphon section of the water conveyance pipeline, establish a three-dimensional geometric model in three-dimensional geometric modeling software, calibrate it as the target three-dimensional model, and determine the position and boundary of the deflector within the target three-dimensional model; Among them, the boundary includes the fluid inlet and fluid outlet of the inverted siphon section of the water conveyance pipeline; Combined with the target three-dimensional model and the corresponding positions and boundary parameters of the guide vanes, a turbulence model of the target three-dimensional model is constructed and calibrated as the target three-dimensional turbulence model. At the same time, grid division is performed on the target three-dimensional turbulence model to calculate the quantization index thresholds of the flow field in the target three-dimensional turbulence model; Among them, the quantization index thresholds of the flow field in the target three-dimensional turbulence model include the flow velocity uniformity threshold and the head loss coefficient threshold; Combined with the quantization index thresholds of the flow field in the target three-dimensional turbulence model, turbulent flow simulation operation is carried out on the target three-dimensional turbulence model, and combined with the results of the turbulent flow simulation operation, the optimal opening and closing angle of the guide vanes of the qualified target rectifying grid is calculated in real time.

[0029] It should be noted that computational fluid dynamics (CFD) is a numerical method used to simulate fluid flow and related physical processes. A control algorithm is developed that can dynamically adjust the working state of the rectifying grid according to real-time flow velocity data. By means of CFD simulation, an internal flow field model of the rectifying grid is established. According to the real-time flow velocity data provided by the sensor array, the optimal opening and closing angle of the guide vanes and the working state of the rectifying grid are quickly calculated to achieve dynamic flow state matching. First, it is necessary to perform three-dimensional modeling on the inverted siphon section of the water conveyance pipeline, so it is necessary to obtain the specification parameters of the inverted siphon section of the water conveyance pipeline, which can be obtained through laser scanning analysis. Secondly, it is necessary to determine the position and boundary of the guide vanes because boundary conditions are required to construct the CFD flow field. The purpose of constructing the turbulence model is to enhance the ability to capture separated flow and swirling flow, and the purpose of grid division is to improve the efficiency when calculating the flow field. The quantization index thresholds of the flow field include the flow velocity uniformity threshold and the head loss coefficient threshold, both of which are key indicators for controlling the opening and closing angle of the guide vanes.

[0030] Further, in a preferred embodiment of the present invention, the turbulent flow simulation operation is carried out on the target three-dimensional turbulence model, and combined with the results of the turbulent flow simulation operation, the optimal opening and closing angle of the guide vanes of the qualified target rectifying grid is calculated in real time, specifically as follows: Perform turbulent flow simulation operation on the target three-dimensional turbulence model, and conduct orthogonal experiments on the model corresponding to the qualified target rectifying grid during the turbulent flow simulation operation to generate different flow field characteristic data sets, where the fluid flow velocities at the boundaries and the opening and closing angles of the guide vanes in different flow field characteristic data sets are different; Based on different flow field characteristic data sets, generate a CFD predicted flow field, and combined with the real-time flow velocities of the fluid at different sensor deployment positions, correct the boundary conditions of the CFD predicted flow field to generate a target CFD predicted flow field; Through the Gaussian regression algorithm, perform principal component analysis on the flow velocity data of the fluid in the target CFD predicted flow field, and based on the quantization index thresholds of the flow field in the target three-dimensional turbulence model, construct the objective function of the algorithm; During the principal component analysis process, in combination with the objective function of the algorithm, the optimal opening and closing angles of the guide vanes at different fluid flow rates are generated. Among them, the optimal opening and closing angles of the guide vanes need to ensure that the quantization indexes output at different fluid flow rates are maintained within the quantization index threshold; If there is no opening and closing angle of the guide vane that can keep the quantization index of the fluid flow rate output within the quantization index threshold, the extended Kalman filter algorithm is used to dynamically correct the error of the target CFD predicted flow field, and the genetic algorithm is introduced during the output process of the extended Kalman filter algorithm to perform secondary correction and convergence of the boundary conditions of the target CFD predicted flow field until there is an opening and closing angle of the guide vane that can keep the quantization index of the fluid flow rate output within the quantization index threshold.

[0031] It should be noted that during the turbulent flow simulation operation, orthogonal experiments are carried out on the models corresponding to the qualified target fairings, and different flow field characteristic data sets can be generated. The purpose is to judge the corresponding optimal opening and closing angles under different flow field characteristic data and use them to generate the CFD predicted flow field. At the same time, the flow field boundary conditions are corrected in combination with the known flow rate data, such as local vorticity, pressure pulsation amplitude, etc. The method for making intelligent decisions on the opening and closing angles of the guide vanes is to quantify the uncertainty of the prediction through the Gaussian process regression method, and perform principal component analysis on the flow rate field data through the feature dimensionality reduction method to realize the judgment of the opening and closing angle control of the guide vanes at different flow rates. The objective function is the key data for dynamically optimizing and controlling the opening and closing angles. If the CFD simulation evaluation results show that the predicted working state can achieve a better fairing effect, the control system will generate corresponding control instructions according to the predicted working state. After the fairing is adjusted to the new working state, the change of the flow field is continuously monitored in real time through the sensor. If it is found that the actual fairing effect does not match the expectation, for example, the flow rate distribution is still uneven or there are large eddies, the control system will use these feedback information as new data to input to the target CFD predicted flow field for adjustment, that is, the extended Kalman filter algorithm is used to dynamically correct the error of the target CFD predicted flow field, and the genetic algorithm is introduced during the output process of the extended Kalman filter algorithm to perform secondary correction and convergence of the boundary conditions of the target CFD predicted flow field until there is an opening and closing angle of the guide vane that can keep the quantization index of the fluid flow rate output within the quantization index threshold. The extended Kalman filter algorithm dynamically corrects the CFD predicted flow field error through real-time data to improve the flow field prediction accuracy, while the genetic algorithm can converge quickly and improve the efficiency.

[0032] The innovation of the present invention is to dynamically adjust the opening and closing angles of the guide vanes according to the real-time flow rate data, realize dynamic flow pattern matching, and improve the fairing efficiency.

[0033] such as Figure 3As shown in the figure, the second aspect of the present invention further provides an intelligent decision-making system for the working state of a flow straightener based on data fusion. The intelligent decision-making system for the working state includes a memory 31 and a processor 32. The memory 31 stores an intelligent decision-making method for the working state. When the intelligent decision-making method for the working state is executed by the processor 32, the following steps are implemented: Determine a flow straightener that matches the inverted siphon section of the water conveyance pipeline, and deploy an electromagnetic micro flow velocity sensor array inside the inverted siphon section of the water conveyance pipeline to test the water flow state of the inverted siphon section of the water conveyance pipeline; Construct an internal flow field simulation model of the flow straightener to simulate the turbulent flow state of the fluid, and calculate the optimal opening angle of the guide vanes of the qualified target flow straightener in real time based on the turbulent flow state of the fluid; Based on the optimal opening angle of the guide vanes of the qualified target flow straightener, combined with a shape memory alloy guide vane, perform temperature control processing on the guide vanes of the qualified target flow straightener.

[0034] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A smart decision-making method for the operating state of a rectifying grid based on data fusion, characterized in that, The following steps are involved: Determine a rectifier grid matching the inverted siphon section of the water pipeline, and deploy an electromagnetic micro flow velocity sensor array in the inverted siphon section of the water pipeline to perform a water flow state test on the inverted siphon section of the water pipeline; Construct a simulation model of the flow field inside the rectifier grid to simulate the turbulent flow state of the fluid, and calculate the optimal guide vane opening and closing angle of the qualified target rectifier grid in real time based on the turbulent flow state of the fluid; Based on the optimal guide vane opening and closing angle of the qualified target rectifier grid and combined with the shape memory alloy guide vane, the guide vane temperature control treatment is performed on the qualified target rectifier grid.

2. The intelligent decision-making method for the working state of a rectifying grid based on data fusion according to claim 1, characterized in that The determining of the rectifying grid matching the inverted siphon section of the water pipeline and the deployment of an electromagnetic micro flow velocity sensor array in the inverted siphon section of the water pipeline for testing the water flow state of the inverted siphon section of the water pipeline are specifically as follows: Acquire a water pipeline, and determine an inverted siphon section in the water pipeline, and mark it as the inverted siphon section of the water pipeline; Calculate the bending angles of the inverted siphon section of the water pipeline at different positions, preset a bending angle threshold, and calibrate the position of the inverted siphon section of the water pipeline where the bending angle is maintained within the bending angle threshold as the sensor deployment position; Install electromagnetic micro flow rate sensors in all sensor deployment locations, obtain signal modules in all electromagnetic micro flow rate sensors, control the signal modules of all electromagnetic micro flow rate sensors to transmit connection signals, and obtain controller modules to receive connection signals from different electromagnetic micro flow rate sensors; Perform Kalman filtering on the connection signal, and perform signal interaction on the filtered connection signal in the controller module to construct an electromagnetic micro flow velocity sensor array; Combined with the electromagnetic micro flow velocity sensor array, the water flow state test of the inverted siphon section of the water pipeline is carried out.

3. The intelligent decision-making method for the operating state of the rectifying grid based on data fusion according to claim 2, wherein The electromagnetic micro flow velocity sensor array is combined to test the water flow state of the inverted siphon section of the water pipeline, specifically: Controlling the operation of all electromagnetic micro flow velocity sensors, wherein the operation of the electromagnetic micro flow velocity sensors is to control the electromagnetic micro flow velocity sensors to arrange the magnetic field in the inverted siphon section of the water pipeline, and to monitor in real time the cutting rate of the magnetic flux lines in the inverted siphon section of the water pipeline; Based on the cutting rate of the magnetic flux lines in the inverted siphon section of the water pipeline, the magnitude of the induced electromotive force output by the electromagnetic micro-flow velocity sensor is calculated. Combined with the magnitude of the induced electromotive force output by the electromagnetic micro-flow velocity sensor, the real-time flow velocity of the fluid in different sensor deployment positions is calculated. A rectifying grid connected to the inverted siphon section of the water pipeline is obtained and calibrated as a target rectifying grid, an electromagnetic micro flow velocity sensor array is connected to the target rectifying grid, and the real-time flow velocity of the fluid in different sensor deployment positions is updated; An eddy current suppression response time test is performed in the target rectifier grid. The eddy current suppression response time of the target rectifier grid is calculated based on the test results, and the maximum response time is preset. If the eddy current suppression response time of the target rectifier grid is greater than the maximum response time, the firmware of the target rectifier grid is updated, and the firmware of the electromagnetic micro flow velocity sensor array connected to the target rectifier grid is updated at the same time, until the eddy current suppression response time of the target rectifier grid is no greater than the maximum response time, and a qualified target rectifier grid is obtained.

4. The intelligent decision-making method for the operating state of a rectifying grid based on data fusion according to claim 1, wherein The internal flow field simulation model of the constructed rectifying grid is used to simulate the turbulent flow state of the fluid, and the optimal opening angle of the guide vane of the qualified target rectifying grid is calculated in real time based on the turbulent flow state of the fluid. Specifically: A laser scanning device is introduced to scan and analyze the dimensional data of the siphon section of the water conveyance pipeline, obtain the dimensional data of the siphon section of the water conveyance pipeline, and combine the bending angles at different positions of the siphon section of the water conveyance pipeline to determine the installation position of the qualified target rectifying grid at the same time, and output the specification parameters of the siphon section of the water conveyance pipeline; Based on the specification parameters of the siphon section of the water conveyance pipeline, a three-dimensional geometric model is established in three-dimensional geometric modeling software, calibrated as the target three-dimensional model, and the position and boundary of the guide vane are determined within the target three-dimensional model; Among them, the boundary includes the fluid inlet and fluid outlet of the siphon section of the water conveyance pipeline; Combined with the target three-dimensional model and the corresponding guide vane position and boundary parameters, a turbulent model of the target three-dimensional model is constructed, calibrated as the target three-dimensional turbulent model, and at the same time, grid division is performed on the target three-dimensional turbulent model to calculate the quantization index threshold of the flow field in the target three-dimensional turbulent model; Among them, the quantization index threshold of the flow field in the target three-dimensional turbulent model includes the flow velocity uniformity threshold and the head loss coefficient threshold; Combined with the quantization index threshold of the flow field in the target three-dimensional turbulent model, turbulent simulation operation is performed on the target three-dimensional turbulent model, and combined with the turbulent simulation operation results, the optimal opening angle of the guide vane of the qualified target rectifying grid is calculated in real time.

5. The intelligent decision-making method for the operating state of the rectifying grid based on data fusion according to claim 4, wherein The turbulent simulation operation is performed on the target three-dimensional turbulent model, and combined with the turbulent simulation operation results, the optimal opening angle of the guide vane of the qualified target rectifying grid is calculated in real time. Specifically: Perform turbulent simulation operation on the target three-dimensional turbulent model, and perform orthogonal experiments on the model corresponding to the qualified target rectifying grid during the turbulent simulation operation to generate different flow field characteristic data sets. Among them, the fluid flow velocity at the boundary and the opening angle of the guide vane in different flow field characteristic data sets are different; Based on different flow field characteristic data sets, a CFD predicted flow field is generated, combined with the real-time flow velocity of the fluid at different sensor deployment positions, the boundary conditions of the CFD predicted flow field are corrected, and a target CFD predicted flow field is generated; Through the Gaussian regression algorithm, principal component analysis is performed on the flow velocity data of the fluid in the target CFD predicted flow field, and based on the quantization index threshold of the flow field in the target three-dimensional turbulent model, the objective function of the algorithm is constructed; During the principal component analysis process, combined with the objective function of the algorithm, the optimal opening angle of the guide vane at different fluid flow velocities is generated. Among them, the optimal opening angle of the guide vane needs to ensure that the quantization indexes output at different fluid flow velocities are maintained within the quantization index threshold; If there is no opening angle of the guide vane that can keep the quantization index of the fluid flow velocity within the quantization index threshold, the extended Kalman filter algorithm is used to dynamically correct the error of the target CFD predicted flow field, and the genetic algorithm is introduced during the output process of the extended Kalman filter algorithm to perform secondary correction and convergence of the boundary conditions of the target CFD predicted flow field until there is an opening angle of the guide vane that can keep the quantization index of the fluid flow velocity within the quantization index threshold.

6. The intelligent decision-making method for the working state of a rectifying grid based on data fusion according to claim 1, characterized in that Based on the optimal opening angle of the qualified target flow rectifying grid, combined with the shape memory alloy flow guide vane, temperature control treatment is carried out on the flow guide vane of the qualified target flow rectifying grid, specifically as follows: Obtain the shape memory alloy flow guide vane and determine the material parameters of the shape memory alloy flow guide vane; Introduce a big data network, and based on the material parameters of the shape memory alloy flow guide vane in the big data network, retrieve the corresponding recovery states when different temperatures are applied to the shape memory alloy flow guide vane, and construct a flow guide vane - temperature change map; Obtain the control module of the qualified target flow rectifying grid, replace the shape memory alloy flow guide vane into the qualified target flow rectifying grid, and connect a heating module in parallel in the control module of the qualified target flow rectifying grid, and at the same time import the flow guide vane - temperature change map into the control module of the qualified target flow rectifying grid; Based on the control module of the qualified target flow rectifying grid, carry out temperature control treatment on the shape memory alloy flow guide vane. Among them, the temperature control treatment on the shape memory alloy flow guide vane is that according to the real-time temperature of the fluid flowing through the qualified target flow rectifying grid, the shape memory alloy flow guide vane automatically follows the temperature for plastic treatment. After the shape memory alloy flow guide vane is plasticized, if the shape memory alloy flow guide vane needs to control the opening angle to be greater than the current opening angle, continue to perform automatic plasticization according to the real-time temperature of the fluid flowing through the qualified target flow rectifying grid; If the shape memory alloy flow guide vane needs to control the opening angle to be less than the current opening angle, then in combination with the flow guide vane - temperature change map, control the heating module through the control module to apply the temperature corresponding to the optimal opening angle of the shape memory alloy flow guide vane on the shape memory alloy flow guide vane.

7. The intelligent decision-making system for the working state of the rectifying grid based on data fusion, characterized in that, The intelligent decision-making system includes a memory and a processor. The memory stores an intelligent decision-making method program. When the intelligent decision-making method program is executed by the processor, the steps of the intelligent decision-making method described in any one of claims 1 - 6 are realized.

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