Water turbine guide vane efficiency optimization method and system considering multi-parameter signals

Abstract

The invention discloses a water turbine guide vane efficiency optimization method and system considering multi-parameter signals, and belongs to the technical field of hydroelectric generation, and the method comprises the steps: setting an optimization target, collecting data corresponding to the optimization target when a water turbine works, and calculating effective parameter data; different parameter data are combined, the influence of different parameter combinations on the water turbine guide vane efficiency is evaluated, and the optimal parameter combination is determined; the angle of the impact water wheel is adjusted according to the optimal parameter combination, the optimal impact water wheel angle is achieved, and the water turbine guide vane efficiency is improved. According to the method, the scientificity of water turbine guide vane efficiency optimization is ensured through fine management of the optimization target and data acquisition. Through parameter combination evaluation of priority, relevance and target requirements, optimization efficiency and quality are improved. Finally, by adjusting the angle of the impact water turbine and considering interference signals, real-time, efficient and stable guide vane efficiency improvement is achieved, and the overall performance of the water turbine is remarkably enhanced.

Description

Technical Field

[0001] The invention relates to the technical field of hydropower generation, and in particular to a method and system for optimizing the efficiency of a water turbine guide vane by considering multi-parameter signals. Background Art

[0002] In the field of hydropower generation, optimization of turbine guide vane efficiency has always been the focus of engineers and technicians. With the continuous development of technology, existing methods for optimizing turbine guide vane efficiency have made certain progress, mainly including improvements in guide vane shape, upgrades in control systems, and optimization and adjustment of single parameters. These methods have improved the operating efficiency of turbines to a certain extent, but there are still some shortcomings. On the one hand, traditional methods often only focus on the optimization of a single parameter, ignoring the impact of the interaction between multiple parameters on the guide vane efficiency; on the other hand, existing technologies lack the full utilization of real-time data, as well as the identification and processing of interference signals, resulting in poor optimization effects under complex working conditions.

[0003] In response to these problems, the method for optimizing the efficiency of turbine guide vanes considering multi-parameter signals proposed in the present invention came into being. This method not only covers the collection and calculation of multiple key parameters such as friction coefficient, energy conversion rate, heat exchange rate and flow resistance coefficient, but also deeply analyzes the impact of these parameters and their combinations on the guide vane efficiency. The existing technology fails to fully consider the priority, correlation and optimization goals between parameters, resulting in difficulty in achieving optimal efficiency in the multi-parameter optimization process. The present invention achieves refined management and optimization of multi-parameter combinations by introducing priority requirements, correlation requirements and target requirements, thereby hopefully improving the efficiency of turbine guide vanes while solving the deficiencies in the existing technology and opening up a new path for improving turbine operating efficiency. Summary of the invention

[0004] In view of the above-mentioned existing problems, the purpose of the present invention is to solve the technical difficulties and defects of traditional optimization methods in dealing with multi-parameter interactions, real-time data utilization, interference signal identification and systematic adjustment, by accurately collecting and calculating key parameters, evaluating the impact of different parameter combinations, and dynamically adjusting the guide vane angle to improve the turbine guide vane efficiency, reduce energy consumption, and enhance the system's adaptability to changes in operating conditions.

[0005] In order to solve the above technical problems, a method for optimizing the efficiency of turbine guide vanes considering multi-parameter signals is proposed, including:

[0006] Set the optimization target, collect the data corresponding to the optimization target when the turbine is working and calculate the effective parameter data; combine different parameter data, evaluate the impact of different parameter combinations on the efficiency of the turbine guide vanes, and determine the optimal parameter combination; adjust the angle of impact on the water wheel according to the optimal parameter combination to achieve the optimal impact angle on the water wheel, thereby improving the efficiency of the turbine guide vanes.

[0007] As a preferred solution of the method for optimizing the efficiency of a water turbine guide vane considering multi-parameter signals described in the present invention, wherein: the parameter data include friction coefficient, energy conversion rate, heat exchange rate and flow resistance coefficient;

[0008] The data collected by the friction coefficient are water flow velocity v, water density and water pressure change. The water pressure loss is calculated according to the water pressure change, and the current friction coefficient C is calculated by combining the water flow velocity and water density. f The value of

[0009] The data collected by the energy conversion rate is the output energy E of the turbine system. out and input energy E in ;

[0010] The data collected by the heat exchange rate is heat change;

[0011] The data collected for the flow resistance coefficient are flow resistance, water density, water flow velocity and flow cross-sectional area. The flow resistance coefficient k is obtained by calculating the ratio of the resistance generated by the fluid on the guide vane and the fluid dynamic pressure. Cd The value of .

[0012] As a preferred solution of the method for optimizing the efficiency of a water turbine guide vane considering multi-parameter signals described in the present invention, the evaluation includes considering the influence of each parameter and different parameter combinations on the efficiency of the water turbine guide vane, and sorting the obtained comprehensive influence values ​​to obtain the optimal parameter combination;

[0013] The influence of each parameter on the turbine guide vane efficiency is:

[0014]

[0015] Among them, η f represents the efficiency of the guide vane after considering the effect of friction, η 0 is the guide vane efficiency without considering friction loss, k f is the slope of the friction loss curve, C f0 is the reference friction coefficient, η E is the effect of energy loss on guide vane efficiency, E out is the effective output energy after passing through the guide vanes and turbine, k E is the efficiency loss caused by the difference between input and output energy, ηQ is the effect of heat loss on the guide vane efficiency, Q in is the input temperature, Q out is the output temperature, k Q Indicates the influence of temperature difference on efficiency, η Cd is the effect of final flow resistance on efficiency, R flow Indicates the amount of resistance generated when water flows through the guide vanes;

[0016] For η f , η E , η Q and η Cd The comprehensive influence values ​​are sorted from high to low to obtain the optimal parameters, and the influence of each parameter on the efficiency of the turbine guide vane is considered, and multiple parameters are combined according to the requirements of multi-parameter combination.

[0017] As a preferred solution of the method for optimizing the efficiency of a water turbine guide vane considering multi-parameter signals described in the present invention, wherein: the multi-parameter combination requirement includes a priority requirement, a correlation requirement, and a target requirement;

[0018] The priority requirement includes, when combining parameters, by sorting the impact values ​​of the various parameters, giving priority to selecting the optimal parameter to combine with the remaining selected parameters;

[0019] The correlation requirement includes considering the interaction between different parameters, evaluating the mutual influence between different parameters, and selecting parameters with high mutual influence and linear change trend for combination;

[0020] The target requirement includes determining a parameter combination according to an optimization target of the turbine and selecting parameters that are consistent with the optimization target direction for combination.

[0021] As a preferred solution of the method for optimizing the efficiency of a water turbine guide vane considering multi-parameter signals described in the present invention, wherein: the optimal parameter combination includes, after obtaining the final parameter combination according to the multi-parameter combination requirements, being consistent with the single parameter, considering the influence of different parameter combinations on the efficiency of the water turbine guide vane;

[0022] Considering the interference signal after the multi-parameter combination, the efficiency influence value of the multi-parameter combination is updated, and the updated comprehensive influence value is sorted from high to low to obtain the optimal parameter combination. The optimal parameters and the optimal parameter combination are compared, and the optimal parameter or the optimal parameter combination with the highest comprehensive influence value is selected as the optimization adjustment parameter or parameter combination affecting the efficiency of the turbine guide vane.

[0023] As a preferred solution of the method for optimizing the efficiency of a water turbine guide vane considering multi-parameter signals described in the present invention, the updating includes, in combination with the anti-interference capability, considering the interference signal I, and obtaining the efficiency correction result:

[0024]

[0025] Among them, α is the correction coefficient;

[0026] The guide vane efficiency is divided into current efficiency and historical efficiency. The historical efficiency is used To compare and dynamically adjust the current efficiency, obtain the efficiency improvement rate W(η), adjust the correction coefficient α' according to the efficiency improvement rate, and re-enter Get the latest efficiency impact values.

[0027] As a preferred solution of the method for optimizing the efficiency of a water turbine guide vane considering multi-parameter signals described in the present invention, wherein: the adjusting the angle of the impinging water wheel includes adjusting the angle of the impinging water wheel according to the obtained comprehensive influence value after obtaining the optimal parameter or the optimal parameter combination, adjusting the angle of the impinging water wheel by obtaining the optimal impinging water wheel angle with the set optimization target as the adjustment purpose, and obtaining the result ω of the adjusted angle;

[0028] When ω>ω th When the guide vane is adjusted, the guide vane angle is lowered by adjusting the mechanical device to reduce the angle with the water flow to ω = ω th Achieve the best angle ω th ; When ω<ω th When the guide vane angle is increased, the angle with the water flow is increased until ω = ω th Achieve the best angle ω th .

[0029] Another object of the present invention is to provide a turbine guide vane efficiency optimization system that considers multi-parameter signals. The present invention solves the technical problems faced by turbines during operation, including improving guide vane efficiency, reducing energy loss, optimizing multi-parameter combinations to cope with interactions between parameters, and achieving dynamic adjustment to adapt to changing working conditions, while enhancing the system's anti-interference ability. Through automated and intelligent data collection and processing, the operating performance and economic benefits of the turbine are improved, human intervention is reduced, and the stability and reliability of the optimization results are ensured.

[0030] As a preferred solution of the turbine guide vane efficiency optimization system considering multi-parameter signals described in the present invention, it is characterized by comprising a data processing module, a parameter evaluation module, a multi-parameter combination analysis module, and an impact wheel angle adjustment module;

[0031] The data processing module collects data when the turbine is working, calculates parameter data of friction coefficient, energy conversion rate, heat exchange rate and flow resistance coefficient, and transmits the calculated parameter data to the parameter evaluation module;

[0032] The parameter evaluation module combines different parameter data, evaluates the influence of each parameter and parameter combination on the efficiency of the turbine guide vane, sorts the parameters according to the evaluation results, determines the optimal parameters and the optimal parameter combination, and transmits the optimal parameters and the optimal parameter combination to the multi-parameter combination analysis module;

[0033] The multi-parameter combination analysis module further analyzes the optimal parameter combination according to the priority requirements, correlation requirements and target requirements, considers the interference signal, updates the efficiency impact value of the multi-parameter combination, and transmits the finally determined optimal parameter or optimal parameter combination to the impact water wheel angle adjustment module;

[0034] The impact wheel angle adjustment module adjusts the angle of the impact wheel according to the comprehensive influence value of the optimal parameter or the optimal parameter combination, and adjusts the guide vane angle through a mechanical device to achieve the optimal impact wheel angle.

[0035] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of the method for optimizing the efficiency of a turbine guide vane considering multi-parameter signals are implemented.

[0036] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the method for optimizing the efficiency of a water turbine guide vane considering multi-parameter signals are implemented.

[0037] Beneficial effects of the present invention: The present invention's refined management of the turbine guide vane efficiency optimization process can comprehensively evaluate the performance of the turbine under actual working conditions; it provides an accurate data basis for subsequent efficiency optimization, ensuring the scientificity and accuracy of the optimization process, thereby helping to improve the overall operating efficiency of the turbine.

[0038] By combining different parameter data and evaluating the impact of these combinations on the efficiency of turbine guide vanes, the optimal parameter combination is determined. Through the priority requirement, the present invention can ensure that the parameters with the greatest impact on efficiency are given priority when combining parameters, thereby improving the optimization efficiency; secondly, the correlation requirement ensures that the interaction between parameters is considered when combining parameters, so that the optimization result is more in line with the actual situation; finally, the target requirement ensures that the selection of parameter combination is consistent with the optimization target, which helps to improve the specific performance of turbine guide vanes in a targeted manner. These measures work together to make the optimization of turbine guide vane efficiency more comprehensive and effective.

[0039] The angle of impacting the water wheel is adjusted according to the optimal parameter combination to achieve the optimal impact angle of the water wheel, further improving the efficiency of the turbine guide vane; the theoretical optimal parameter combination is converted into an angle adjustment in actual operation, realizing the concretization of the optimization target. By dynamically adjusting the guide vane angle, the present invention can respond to changes in the working conditions of the turbine in real time, ensuring that the optimal guide vane efficiency can be maintained under various working conditions. In addition, by considering the influence of interference signals and performing efficiency correction, the present invention improves the stability and anti-interference ability of the turbine system, thereby achieving higher efficiency and more reliable performance in practical applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work, among which:

[0041] Figure 1 An overall flow chart of a method for optimizing turbine guide vane efficiency by considering multi-parameter signals provided in accordance with an embodiment of the present invention.

[0042] Figure 2 A schematic diagram of modules of a turbine guide vane efficiency optimization system considering multi-parameter signals provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0044] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0045] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it an embodiment that is mutually exclusive with other embodiments, either individually or selectively.

[0046] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0047] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0048] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0049] Example 1, reference Figure 1 , which is the first embodiment of the present invention, provides a method for optimizing the efficiency of a water turbine guide vane by considering multi-parameter signals, comprising:

[0050] S1: Set the optimization target, collect the data corresponding to the optimization target when the turbine is working, and calculate the effective parameter data.

[0051] Specifically, the parameter data include friction coefficient, energy conversion rate, heat exchange rate and flow resistance coefficient;

[0052] The data collected by the friction coefficient are water flow velocity v, water density and water pressure change. The water pressure loss is calculated according to the water pressure change, and the current friction coefficient C is calculated by combining the water flow velocity and water density. f The value of

[0053] The data collected by the energy conversion rate is the output energy E of the turbine system. out and input energy E in ;

[0054] The data collected by the heat exchange rate is heat change;

[0055] The data collected for the flow resistance coefficient are flow resistance, water density, water flow velocity and flow cross-sectional area. The flow resistance coefficient k is obtained by calculating the ratio of the resistance generated by the fluid on the guide vane and the fluid dynamic pressure. Cd The value of .

[0056] Furthermore, the influence of each parameter and different parameter combinations on the turbine guide vane efficiency is considered separately, and the obtained comprehensive influence values ​​are ranked to obtain the optimal parameter combination;

[0057] The influence of each parameter on the turbine guide vane efficiency is:

[0058]

[0059] Among them, η f represents the efficiency of the guide vane after considering the effect of friction, η 0 is the guide vane efficiency without considering friction loss, k f is the slope of the friction loss curve, C f0 is the reference friction coefficient, η E is the effect of energy loss on guide vane efficiency, E out is the effective output energy after passing through the guide vanes and turbine, k E is the efficiency loss caused by the difference between input and output energy, η Q is the effect of heat loss on the guide vane efficiency, Q in is the input temperature, Q out is the output temperature, k Q Indicates the influence of temperature difference on efficiency, η Cd is the effect of final flow resistance on efficiency, R flow Indicates the amount of resistance generated when water flows through the guide vanes;

[0060] For η f , η E , η Q and η Cd The comprehensive influence values ​​are sorted from high to low to obtain the optimal parameters, and the influence of each parameter on the efficiency of the turbine guide vane is considered, and multiple parameters are combined according to the requirements of multi-parameter combination.

[0061] S2: Combine different parameter data, evaluate the impact of different parameter combinations on turbine guide vane efficiency, and determine the optimal parameter combination.

[0062] Furthermore, the multi-parameter combination requirements include priority requirements, relevance requirements, and target requirements;

[0063] The priority requirement includes, when combining parameters, by sorting the influence values ​​of each parameter, giving priority to selecting the optimal parameter for combination with the remaining selected parameters; for example: if the influence value of the friction coefficient is significantly higher than the flow resistance coefficient, the friction coefficient should be combined with other selected parameters in priority, rather than placing the parameter with a lower influence value in the combination.

[0064] The correlation requirements include considering the interaction between different parameters, evaluating the mutual influence between different parameters, and selecting parameters with high mutual influence and linear change trends for combination; for example: if the friction coefficient and heat exchange rate show a linear change trend under different working conditions, then combining them can reveal their comprehensive impact on the performance of the turbine.

[0065] The target requirements include determining the parameter combination according to the optimization target of the turbine and selecting the parameters that are consistent with the optimization target direction for combination; for example: if the goal is to reduce energy consumption, the focus should be on selecting the parameters corresponding to the energy conversion rate and the friction coefficient, rather than only considering the parameters of the flow resistance coefficient.

[0066] It should be noted that after obtaining the final parameter combination according to the multi-parameter combination requirements, it is consistent with the single parameter, considering the influence of different parameter combinations on the turbine guide vane efficiency:

[0067]

[0068] Among them, η com represents the overall efficiency evaluation of the turbine, m represents the number of parameter combinations, j is the variable index, and D j represents the jth parameter combination, F j Indicates the adjustment strength of the jth parameter combination, H j represents the importance of the jth parameter combination in the overall efficiency calculation, G j Indicates the running state change value corresponding to the jth parameter combination;

[0069] Considering the interference signal after the multi-parameter combination, the efficiency influence value of the multi-parameter combination is updated, and the updated comprehensive influence value is sorted from high to low to obtain the optimal parameter combination. The optimal parameters and the optimal parameter combination are compared, and the optimal parameter or the optimal parameter combination with the highest comprehensive influence value is selected as the optimization adjustment parameter or parameter combination affecting the efficiency of the turbine guide vane.

[0070] Combined with the anti-interference capability and considering the interference signal I, the efficiency correction result is obtained:

[0071]

[0072] Among them, α is the correction coefficient;

[0073] The guide vane efficiency is divided into current efficiency and historical efficiency. The historical efficiency is used To compare and dynamically adjust the current efficiency, obtain the efficiency improvement rate W(η):

[0074]

[0075] Adjust the correction factor according to the efficiency improvement rate:

[0076] α'=α(1+βW(η))

[0077] Among them, α' is the adjusted correction coefficient, re-enter Get the latest efficiency impact values.

[0078] S3: Adjust the angle of the water wheel impact according to the optimal parameter combination to achieve the optimal water wheel impact angle, thereby improving the efficiency of the turbine guide vane.

[0079] Furthermore, after obtaining the optimal parameter or the optimal parameter combination, the impact wheel angle is adjusted according to the obtained comprehensive impact value, and the optimal impact wheel angle is adjusted with the set optimization target as the adjustment purpose;

[0080]

[0081] Among them, ω 0 is the initial angle, X is the adjustment coefficient, η' is the optimal efficiency including the influence value of the optimal parameters η com Or the impact value of the optimal parameter combination is the historical average efficiency, R f is the flow intensity parameter, R t is the characteristic parameter of the guide vane, c is the constant corresponding to the change of water velocity v, Δv rel is the change in flow velocity;

[0082] When ω>ω th When the guide vane is adjusted, the guide vane angle is lowered by adjusting the mechanical device to reduce the angle with the water flow to ω = ω th Reach the best angle; when ω<ω th When the guide vane angle is increased, the angle with the water flow is increased until ω = ω th Achieve the best angle.

[0083] Embodiment 2, the second embodiment of the present invention, is different from the first two embodiments in that:

[0084] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0085] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0086] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0087] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0088] Example 3, reference Figure 2 , which is the third embodiment of the present invention, and provides a turbine guide vane efficiency optimization system considering multi-parameter signals, including a data processing module, a parameter evaluation module, a multi-parameter combination analysis module, and an impact wheel angle adjustment module;

[0089] The data processing module collects data when the turbine is working, calculates parameter data of friction coefficient, energy conversion rate, heat exchange rate and flow resistance coefficient, and transmits the calculated parameter data to the parameter evaluation module;

[0090] The parameter evaluation module combines different parameter data, evaluates the influence of each parameter and parameter combination on the efficiency of the turbine guide vane, sorts the parameters according to the evaluation results, determines the optimal parameters and the optimal parameter combination, and passes the optimal parameters and the optimal parameter combination to the multi-parameter combination analysis module;

[0091] The multi-parameter combination analysis module further analyzes the optimal parameter combination according to the priority requirements, correlation requirements and target requirements, considers the interference signal, updates the efficiency impact value of the multi-parameter combination, and transmits the final optimal parameter or optimal parameter combination to the impact water wheel angle adjustment module;

[0092] The impact wheel angle adjustment module adjusts the angle of the impact wheel according to the comprehensive influence value of the optimal parameter or the optimal parameter combination, and adjusts the guide vane angle through a mechanical device to achieve the optimal impact wheel angle.

[0093] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for optimizing the efficiency of a hydraulic turbine guide vane considering multi-parameter signals, characterized in that: include, Set the optimization target, collect the data corresponding to the optimization target when the turbine is working, and calculate the effective parameter data; Combine different parameter data, evaluate the impact of different parameter combinations on turbine guide vane efficiency, and determine the optimal parameter combination; The angle of impacting the water wheel is adjusted according to the optimal parameter combination to achieve the optimal impacting water wheel angle, thereby improving the efficiency of the turbine guide vane.

2. The method for optimizing the efficiency of a water turbine guide vane by considering multi-parameter signals according to claim 1, characterized in that: The parameter data include friction coefficient, energy conversion rate, heat exchange rate and flow resistance coefficient; The data collected by the friction coefficient are water flow velocity v, water density and water pressure change. The water pressure loss is calculated according to the water pressure change, and the current friction coefficient C is calculated by combining the water flow velocity and water density. f The value of The data collected by the energy conversion rate is the output energy E of the turbine system. out and input energy E in ; The data collected by the heat exchange rate is heat change; The data collected for the flow resistance coefficient are flow resistance, water density, water flow velocity and flow cross-sectional area. The flow resistance coefficient k is obtained by calculating the ratio of the resistance generated by the fluid on the guide vane and the fluid dynamic pressure. Cd The value of .

3. The method for optimizing the efficiency of a water turbine guide vane by considering multi-parameter signals according to claim 2, characterized in that: The evaluation includes considering the influence of each parameter and different parameter combinations on the efficiency of the turbine guide vanes, and ranking the obtained comprehensive influence values ​​to obtain the optimal parameter combination; The influence of each parameter on the turbine guide vane efficiency is: Among them, η f represents the efficiency of the guide vane after considering the influence of friction, η0 is the efficiency of the guide vane without considering the friction loss, k f is the slope of the friction loss curve, C f0 is the reference friction coefficient, η E is the effect of energy loss on guide vane efficiency, E out is the effective output energy after passing through the guide vanes and turbine, k E is the efficiency loss caused by the difference between input and output energy, η Q is the effect of heat loss on guide vane efficiency, Q in is the input temperature, Q out is the output temperature, k Q Indicates the influence of temperature difference on efficiency, η Cd is the effect of final flow resistance on efficiency, R flow Indicates the amount of resistance generated when water flows through the guide vanes; For η f , η E , η Q and η Cd The comprehensive influence values ​​are sorted from high to low to obtain the optimal parameters, and the influence of each parameter on the efficiency of the turbine guide vane is considered, and multiple parameters are combined according to the requirements of multi-parameter combination.

4. The method for optimizing the efficiency of a water turbine guide vane by considering multi-parameter signals according to claim 3, characterized in that: The multi-parameter combination requirements include priority requirements, relevance requirements, and target requirements; The priority requirement includes, when combining parameters, by sorting the impact values ​​of the various parameters, giving priority to selecting the optimal parameter to combine with the remaining selected parameters; The correlation requirement includes considering the interaction between different parameters, evaluating the mutual influence between different parameters, and selecting parameters with high mutual influence and linear change trend for combination; The target requirement includes determining a parameter combination according to an optimization target of the turbine and selecting parameters that are consistent with the optimization target direction for combination.

5. The method for optimizing the efficiency of a water turbine guide vane by considering multi-parameter signals according to claim 4, characterized in that: The optimal parameter combination includes, after obtaining the final parameter combination according to the multi-parameter combination requirements, being consistent with the single parameter, and considering the influence of different parameter combinations on the turbine guide vane efficiency; Considering the interference signal after the multi-parameter combination, the efficiency influence value of the multi-parameter combination is updated, and the updated comprehensive influence value is sorted from high to low to obtain the optimal parameter combination. The optimal parameters and the optimal parameter combination are compared, and the optimal parameter or the optimal parameter combination with the highest comprehensive influence value is selected as the optimization adjustment parameter or parameter combination affecting the efficiency of the turbine guide vane.

6. The method for optimizing the efficiency of a water turbine guide vane by considering multi-parameter signals according to claim 5, characterized in that: The updating includes combining the anti-interference capability and taking the interference signal I into consideration to obtain the efficiency correction result: Among them, α is the correction coefficient; The guide vane efficiency is divided into current efficiency and historical efficiency. The historical efficiency is used To compare and dynamically adjust the current efficiency, obtain the efficiency improvement rate Wη, adjust the correction coefficient α' according to the efficiency improvement rate, and re-enter Get the latest efficiency impact values.

7. The method for optimizing the efficiency of a water turbine guide vane by considering multi-parameter signals according to claim 6, characterized in that: The adjusting of the angle of the impact water wheel comprises adjusting the angle of the impact water wheel according to the obtained comprehensive influence value after obtaining the optimal parameter or the optimal parameter combination, adjusting the angle of the impact water wheel to obtain the best impact water wheel angle with the set optimization target as the adjustment purpose, and obtaining the result ω of the adjustment angle; When ω>ω th When the guide vane is adjusted, the guide vane angle is lowered by adjusting the mechanical device to reduce the angle with the water flow to ω = ω th Achieve the best angle ω th ; When ω<ω th When the guide vane angle is increased, the angle with the water flow is increased until ω = ω th Achieve the best angle ω th .

8. A system using the method for optimizing the efficiency of a water turbine guide vane by considering multi-parameter signals as claimed in any one of claims 1 to 7, characterized in that: It includes data processing module, parameter evaluation module, multi-parameter combination analysis module and impact water wheel angle adjustment module; The data processing module collects data when the turbine is working, calculates parameter data of friction coefficient, energy conversion rate, heat exchange rate and flow resistance coefficient, and transmits the calculated parameter data to the parameter evaluation module; The parameter evaluation module combines different parameter data, evaluates the influence of each parameter and parameter combination on the efficiency of the turbine guide vane, sorts the parameters according to the evaluation results, determines the optimal parameters and the optimal parameter combination, and transmits the optimal parameters and the optimal parameter combination to the multi-parameter combination analysis module; The multi-parameter combination analysis module further analyzes the optimal parameter combination according to the priority requirements, correlation requirements and target requirements, considers the interference signal, updates the efficiency impact value of the multi-parameter combination, and transmits the finally determined optimal parameter or optimal parameter combination to the impact water wheel angle adjustment module; The impact wheel angle adjustment module adjusts the angle of the impact wheel according to the comprehensive influence value of the optimal parameter or the optimal parameter combination, and adjusts the guide vane angle through a mechanical device to achieve the optimal impact wheel angle.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for optimizing the efficiency of a water turbine guide vane considering multi-parameter signals are implemented as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for optimizing the efficiency of a water turbine guide vane considering multi-parameter signals are implemented as described in any one of claims 1 to 7.

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