Centrifugal fan energy efficiency optimization method and system

Abstract

The invention provides a centrifugal fan energy efficiency optimization method and system, and relates to the technical field of energy efficiency optimization, and the method comprises the steps: carrying out the dynamic operation monitoring of a target centrifugal fan, and obtaining the target operation information; activating a running energy efficiency evaluator to evaluate and analyze the target running state information to obtain a comprehensive energy efficiency index; performing feedback adjustment on the comprehensive energy efficiency index according to target working condition environment information extracted from the target operation working condition information to obtain a target energy efficiency index; when the target energy efficiency index does not reach the energy efficiency index limit value, an optimization instruction is sent out; traversing the target working condition feature information in a centrifugal fan control database to obtain a target control strategy; and performing control energy efficiency optimization on the target centrifugal fan by taking the target control strategy as an optimization reference. The technical problems that in the prior art, a centrifugal fan cannot effectively adapt to dynamic changes of environmental factors in the operation process, the optimal energy efficiency can not be achieved, energy waste is caused, and the operation cost is increased are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy efficiency optimization, and in particular to a centrifugal fan energy efficiency optimization method and system. Background Art

[0002] As a key energy-consuming equipment, the energy efficiency of centrifugal fans directly affects the operating cost and energy consumption efficiency of the system. The energy efficiency performance of traditional centrifugal fans varies under different operating conditions, failing to achieve optimal energy utilization efficiency, resulting in energy waste and increased operating costs. In addition, the existing system is slow to respond to changes in environmental factors and is unable to adjust the operating strategy in time to optimize energy efficiency. In addition, traditional control strategies are usually based on static settings or simple empirical rules, failing to fully consider the optimization needs under dynamic operating conditions, resulting in limited control effects. Summary of the invention

[0003] The present application provides a centrifugal fan energy efficiency optimization method and system, aiming to solve the technical problem that the prior art centrifugal fans cannot effectively adapt to the dynamic changes of environmental factors during operation, may fail to achieve optimal energy efficiency, and lead to energy waste and increased operating costs.

[0004] The first aspect disclosed in the present application provides a method for optimizing the energy efficiency of a centrifugal fan, the method comprising: dynamically monitoring the operation of a target centrifugal fan to obtain target operation information, the target operation information comprising target operation condition information and target operation status information; activating an operation energy efficiency evaluator to evaluate and analyze the target operation status information to obtain a comprehensive energy efficiency index; feedback-adjusting the comprehensive energy efficiency index based on target condition environment information extracted from the target operation condition information to obtain a target energy efficiency index; issuing an optimization instruction when the target energy efficiency index does not reach an energy efficiency index limit; traversing the target condition feature information in a centrifugal fan control database based on the optimization instruction to obtain a target control strategy, wherein the target condition feature information is extracted from the target operation condition information; and optimizing the control energy efficiency of the target centrifugal fan using the target control strategy as an optimization benchmark.

[0005] In a second aspect disclosed in the present application, a centrifugal fan energy efficiency optimization system is provided, the system is used for the above-mentioned centrifugal fan energy efficiency optimization method, the system comprises: a dynamic operation monitoring module, the dynamic operation monitoring module is used to dynamically monitor the operation of the target centrifugal fan to obtain target operation information, the target operation information comprises target operation condition information and target operation status information; an evaluation and analysis module, the evaluation and analysis module is used to activate an operation energy efficiency evaluator to evaluate and analyze the target operation status information to obtain a comprehensive energy efficiency index; a feedback adjustment module, the feedback adjustment module is used to adjust the target operation condition information according to the target operation condition information extracted from the target operation condition information. The comprehensive energy efficiency index is fed back and adjusted based on the environmental information to obtain a target energy efficiency index; an optimization instruction issuing module, the optimization instruction issuing module is used to issue an optimization instruction when the target energy efficiency index does not reach the energy efficiency index limit; a control strategy acquisition module, the control strategy acquisition module is used to traverse the target operating condition characteristic information in the centrifugal fan control database based on the optimization instruction to obtain a target control strategy, wherein the target operating condition characteristic information is extracted from the target operating condition information; a control energy efficiency optimization module, the control energy efficiency optimization module is used to optimize the control energy efficiency of the target centrifugal fan based on the target control strategy as the optimization benchmark.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] By dynamically monitoring the operation and evaluating the operation status of the target centrifugal fan, the comprehensive energy efficiency index can be calculated in real time. This index reflects the energy efficiency performance of the centrifugal fan under the current operation status, and realizes the dynamic optimization of energy efficiency. The comprehensive energy efficiency index is adjusted according to the target operating environment information, so that the system can better adapt to environmental changes. For example, in a high temperature or high vibration environment, the control strategy is adjusted to maintain or optimize energy efficiency and improve system stability and reliability. When the target energy efficiency index does not reach the energy efficiency index limit, an optimization instruction is issued. Based on the issued optimization instruction, the target operating condition characteristic information is traversed in the centrifugal fan control database to generate a targeted optimization control strategy to ensure that the centrifugal fan can achieve the best energy efficiency under different operating conditions, thereby reducing energy consumption and operating costs. In summary, the centrifugal fan energy efficiency optimization method effectively solves the technical problems in the existing centrifugal fan energy efficiency optimization through real-time data acquisition, intelligent analysis and feedback control, and achieves more efficient and intelligent energy efficiency management and control effects.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A schematic flow chart of a centrifugal fan energy efficiency optimization method provided in an embodiment of the present application;

[0010] Figure 2 A schematic diagram of the structure of a centrifugal fan energy efficiency optimization system provided in an embodiment of the present application.

[0011] Explanation of the reference numerals: dynamic operation monitoring module 10 , evaluation and analysis module 20 , feedback adjustment module 30 , optimization instruction issuing module 40 , control strategy acquisition module 50 , control energy efficiency optimization module 60 . DETAILED DESCRIPTION

[0012] The embodiment of the present application provides a method for optimizing the energy efficiency of a centrifugal fan, thereby solving the technical problem that the centrifugal fan in the prior art cannot effectively adapt to the dynamic changes of environmental factors during operation, may fail to achieve optimal energy efficiency, and leads to energy waste and increased operating costs.

[0013] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced below in conjunction with the accompanying drawings of the specification. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0014] like Figure 1 As shown, an embodiment of the present application provides a method for optimizing energy efficiency of a centrifugal fan, the method comprising:

[0015] Dynamic operation monitoring is performed on the target centrifugal fan to obtain target operation information, wherein the target operation information includes target operation condition information and target operation status information.

[0016] Various sensors are installed at key parts of the target centrifugal fan, such as flow sensors, pressure sensors, temperature sensors, vibration sensors, speed sensors, etc. These sensors are used to monitor the operating parameters of the fan in real time. After data collection, data related to the external environment and working conditions, such as ambient temperature, ambient vibration, airflow speed, etc., are obtained as target operating condition information; data related to the internal operating status of the fan, such as flow, static pressure, total pressure, speed, etc., are obtained as target operating status information. The target operating condition information and target operating status information are integrated to obtain the target operating information.

[0017] The operation energy efficiency evaluator is activated to evaluate and analyze the target operation status information to obtain a comprehensive energy efficiency index.

[0018] The operation energy efficiency evaluator is a tool for analyzing and evaluating the operation status information of the fan, including the first energy efficiency evaluation channel, the second energy efficiency evaluation channel and the third energy efficiency evaluation channel. After the three channels are evaluated, the first energy efficiency index, the second energy efficiency index and the third energy efficiency index are obtained respectively. The first energy efficiency index, the second energy efficiency index and the third energy efficiency index are weighted averaged to obtain a comprehensive energy efficiency index, which is used to comprehensively reflect the energy efficiency level of the fan in the current operation state.

[0019] Further, including:

[0020] The operation energy efficiency evaluator includes a first energy efficiency evaluation channel, a second energy efficiency evaluation channel and a third energy efficiency evaluation channel; the first operation status information is evaluated and analyzed through the first energy efficiency evaluation channel to obtain a first energy efficiency index, wherein the first operation status information is extracted from the target operation status information; the second operation status information is evaluated and analyzed through the second energy efficiency evaluation channel to obtain a second energy efficiency index, wherein the second operation status information is extracted from the target operation status information; the third operation status information is evaluated and analyzed through the third energy efficiency evaluation channel to obtain a third energy efficiency index, wherein the third operation status information is extracted from the target operation status information; the average of the first energy efficiency index, the second energy efficiency index and the third energy efficiency index is recorded as the comprehensive energy efficiency index.

[0021] The operation energy efficiency evaluator consists of three independent energy efficiency evaluation channels, including a first energy efficiency evaluation channel, a second energy efficiency evaluation channel and a third energy efficiency evaluation channel.

[0022] The first operating status information is extracted from the target operating status information, the first operating status information including operating control parameters of the fan, including flow rate, static pressure, total pressure, speed, etc. The first operating status information is evaluated and analyzed through a first energy efficiency evaluation channel, and a first energy efficiency index is calculated using a predetermined first predetermined energy efficiency evaluation function, which is used to measure the energy efficiency level of the fan operating control parameters. The specific evaluation and analysis process is described in detail in the subsequent steps and will not be repeated here.

[0023] The second operating status information is extracted from the target operating status information. The second operating status information includes directly monitored power consumption data of the wind turbine, such as real-time power consumption. The directly monitored power consumption is evaluated and analyzed through a second energy efficiency evaluation channel. The evaluation and analysis method is similar to the first energy efficiency index. The second energy efficiency index is calculated to measure the energy efficiency level of the wind turbine power consumption.

[0024] The third operating state information is extracted from the target operating state information. The third operating state information includes data of input power and output power. The ratio of input power to output power is evaluated and analyzed through a third energy efficiency evaluation channel. The evaluation and analysis method is similar to that of the first energy efficiency index. The third energy efficiency index is calculated to measure the energy efficiency level of the ratio of input power to output power of the fan.

[0025] Add the first energy efficiency index, the second energy efficiency index and the third energy efficiency index, and then divide them by the number of the three indexes to get the comprehensive energy efficiency index, which reflects the overall energy efficiency level of the fan.

[0026] Further, including:

[0027] A first predetermined energy efficiency evaluation function is embedded in the first energy efficiency evaluation channel; the first predetermined state feature is traversed in the target operating state information to obtain the first operating state information, and the first operating state information includes a flow value, a static pressure value, a total pressure value and a speed value; the flow value, the static pressure value, the total pressure value and the speed value are analyzed according to the first predetermined energy efficiency evaluation function to obtain the first energy efficiency index.

[0028] The first energy efficiency evaluation channel has a first predetermined energy efficiency evaluation function embedded therein, which is a specific function for calculating the energy efficiency index based on the operating parameters of the centrifugal fan, specifically calculating the energy efficiency index based on parameters such as flow rate, static pressure, total pressure and speed.

[0029] The first predetermined state feature is an important state parameter that is pre-set or paid attention to during the operation of the fan, including flow parameters, static pressure parameters, total pressure parameters and speed parameters. In the target operating state information, the first predetermined state feature is traversed, and the corresponding specific values ​​are extracted to obtain the first operating state information, including specific values ​​of parameters such as flow value, static pressure value, total pressure value and speed value.

[0030] The flow value, the static pressure value, the total pressure value and the rotation speed value are input into the first predetermined energy efficiency evaluation function, and a first energy efficiency index is obtained through function calculation.

[0031] Furthermore, the expression of the first predetermined energy efficiency evaluation function is as follows:

[0032]

[0033] Among them, ET(x) refers to the first energy efficiency index of the target centrifugal fan x, f(x) refers to the flow value, F(x) refers to the ideal flow of the target centrifugal fan x, p(x) and p0(x) refer to the total pressure value and the static pressure value, respectively, P(x) refers to the required pressure of the target centrifugal fan x, v(x) refers to the speed value, e refers to the attenuation coefficient, α and β refer to the flow coefficient and pressure coefficient, respectively, and α+β=1.

[0034] The expression of the first predetermined energy efficiency evaluation function is as follows:

[0035]

[0036] In this function, the flow term represents the ratio of the actual flow rate of the target centrifugal fan to the ideal flow rate to the eth power, and then multiplied by the coefficient α. This part evaluates the contribution of the flow rate to energy efficiency. The value of the attenuation coefficient e can adjust the weight between the actual flow rate and the ideal flow rate; the pressure term represents the ratio of the total pressure and static pressure of the target centrifugal fan to the required pressure to the eth power, and then multiplied by the coefficient β. This part evaluates the contribution of pressure to energy efficiency. The value of the attenuation coefficient e can adjust the impact of pressure on energy efficiency.

[0037] The flow term and pressure term are calculated separately first, and then their sum is used as the overall weight and multiplied by the square of the speed to obtain the final energy efficiency index ET(x). This function integrates the impact of flow, pressure and speed on the energy efficiency of the centrifugal fan, and evaluates the energy efficiency performance of the target centrifugal fan under a given working condition through weight and index calculations.

[0038] The comprehensive energy efficiency index is feedback-adjusted according to the target operating condition environment information extracted from the target operating condition information to obtain a target energy efficiency index.

[0039] Extract relevant environmental data from the target operating condition information, including ambient temperature data and ambient vibration data, obtain the target ambient temperature time series and target ambient vibration time series, and integrate to obtain the target operating condition environmental information. Use the predetermined environmental impact assessment rules to analyze the extracted target ambient temperature time series and target ambient vibration time series, respectively obtain the target ambient temperature coefficient and target ambient vibration coefficient, calculate the coefficient mean of the target ambient temperature coefficient and the target ambient vibration coefficient, and obtain the overall environmental impact coefficient. According to the environmental impact coefficient, feedback adjustment is made to the comprehensive energy efficiency index. The adjusted target energy efficiency index integrates the impact of the external environment on the fan energy efficiency, thereby more accurately reflecting the actual operating energy efficiency of the fan.

[0040] Further, including:

[0041] The target operating condition environment information includes a target environment temperature timing and a target environment vibration timing; a predetermined environmental impact assessment rule is read, and based on the predetermined environmental impact assessment rule, the target environment temperature timing and the target environment vibration timing are evaluated and analyzed in turn to obtain a target environment temperature coefficient and a target environment vibration coefficient, respectively; based on the coefficient mean of the target environment temperature coefficient and the target environment vibration coefficient, the comprehensive energy efficiency index is feedback-adjusted to obtain the target energy efficiency index.

[0042] The target working condition environment information includes a target environment temperature time series and a target environment vibration time series. The target environment temperature time series refers to the change data of the environment temperature over time, and the target environment vibration time series refers to the change data of the environment vibration over time.

[0043] The predetermined environmental impact assessment rules are a set of rules set in advance and used to evaluate the impact of environmental factors on system performance. According to the predetermined environmental impact assessment rules, the target ambient temperature time series is evaluated and analyzed to obtain a target ambient temperature coefficient, which is used to describe the degree of ambient temperature impact; the target ambient vibration time series is evaluated and analyzed to obtain a target ambient vibration coefficient, which is used to describe the degree of ambient vibration impact.

[0044] The target ambient temperature coefficient and the target ambient vibration coefficient are averaged to obtain a comprehensive target ambient coefficient, and the target ambient coefficient is used to perform feedback adjustment on the comprehensive energy efficiency index. For example, a product operation is directly performed to obtain a target energy efficiency index. The target energy efficiency index combines the impact of environmental factors on the energy efficiency of the centrifugal fan and is more in line with actual working conditions.

[0045] Further, including:

[0046] Based on the predetermined environmental impact assessment rules, the target temperature multi-domain characteristics of the target ambient temperature time series are obtained; the target temperature multi-domain characteristics are input into the temperature impact assessor to obtain the target ambient temperature coefficient; wherein the temperature impact assessor is an intelligent model obtained by machine learning of a first training data set based on the principle of a neural network, the first training data set includes a first ambient temperature multi-domain characteristic and a first ambient temperature coefficient, and the first ambient temperature multi-domain characteristic includes a first time domain characteristic and a first frequency domain characteristic of a first ambient temperature time series.

[0047] The predetermined environmental impact assessment rules are a set of rules set in advance, which are used to evaluate the impact of environmental factors on system performance. Multi-domain features are extracted based on the target ambient temperature time series data, aiming to more comprehensively describe the characteristics of temperature changes. The multi-domain features include time domain features, such as mean, variance, waveform factor, etc., and frequency domain features, such as spectral energy distribution, etc. After multi-domain feature extraction, the target temperature multi-domain features are obtained, which are used to more comprehensively describe the characteristics of temperature changes.

[0048] The temperature impact evaluator uses a neural network as its core algorithm. The neural network can establish a mapping relationship between complex inputs and outputs by learning and optimizing a large amount of training data, thereby achieving effective processing and prediction capabilities for complex problems. The first training data set is a data set used to train the temperature impact evaluator, including a first ambient temperature multi-domain feature and a first ambient temperature coefficient, wherein the first ambient temperature multi-domain feature is a multi-dimensional feature extracted based on ambient temperature time series data, such as time domain features and frequency domain features, and the first ambient temperature coefficient is the target output for training the neural network, that is, the predicted ambient temperature impact coefficient.

[0049] During the training phase, the neural network uses the back-propagation algorithm and optimizer to adjust the weights and biases in the network to minimize the error between the predicted output and the actual ambient temperature coefficient. Through repeated iterative training, the neural network gradually improves its prediction ability, enabling it to accurately predict the ambient temperature coefficient based on the input target temperature characteristics.

[0050] When the neural network training is completed and reaches sufficient accuracy, the multi-domain features of the target temperature are input to predict the corresponding target ambient temperature coefficient. This coefficient reflects the potential impact of ambient temperature changes on the performance of the centrifugal fan, providing an important reference for subsequent energy efficiency optimization.

[0051] Further, including:

[0052] Based on the predetermined environmental impact assessment rules, the target vibration multi-domain characteristics of the target environmental vibration time series are obtained; the target vibration multi-domain characteristics are input into a vibration impact assessor to obtain the target environmental vibration coefficient; wherein the vibration impact assessor is an intelligent model obtained by machine learning of a second training data set based on the principle of a neural network, the second training data set includes a first environmental vibration multi-domain characteristic and a first environmental vibration coefficient, and the first environmental vibration multi-domain characteristic includes a second time domain characteristic and a second frequency domain characteristic of a first environmental vibration time series.

[0053] Based on the predetermined environmental impact assessment rules, multi-domain feature extraction is performed on the target environmental vibration time series, including time domain features such as mean, variance, waveform factor, etc., and frequency domain features such as spectral energy distribution. After multi-domain feature extraction, multi-domain features of the target vibration are obtained to more comprehensively describe the characteristics of vibration changes.

[0054] The structure and training process of the vibration impact evaluator are similar to those of the aforementioned temperature impact evaluator, and are obtained by training using the second training data set. The target vibration multi-domain features are input to predict the corresponding target environmental vibration coefficient, which reflects the potential impact of environmental vibration changes on the performance of the centrifugal fan and provides an important reference for subsequent energy efficiency optimization.

[0055] When the target energy efficiency index does not reach the energy efficiency index limit, an optimization instruction is issued.

[0056] An energy efficiency index limit is pre-set, which represents the minimum energy efficiency requirement for fan operation. This limit can be determined based on industry standards and historical data. The target energy efficiency index is compared with the preset energy efficiency index limit. If the target energy efficiency index is lower than the energy efficiency index limit, it means that the fan's current operating energy efficiency does not meet the standard and needs to be optimized. The optimization command is automatically issued to adjust and improve the fan's operating status.

[0057] Based on the optimization instruction, the target operating condition characteristic information is traversed in the centrifugal fan control database to obtain a target control strategy, wherein the target operating condition characteristic information is extracted from the target operating condition information.

[0058] Based on the optimization instruction, the target operating condition characteristic information is extracted from the target operating condition information. The target operating condition characteristic information includes key parameters describing the fan operating conditions, such as ambient temperature, ambient vibration, flow, static pressure, total pressure and speed. The centrifugal fan control database contains a large amount of historical operating data and corresponding control strategies. The historical control records matching the current target operating condition characteristic information are searched in the centrifugal fan control database. The similarity between the target operating condition characteristic information and the operating condition characteristic information in the historical control records is calculated using a similarity algorithm. The control record set whose similarity meets the similarity threshold is screened out, and the optimal control strategy is extracted from the matched control record set as the target control strategy. The target control strategy refers to the control method that can most effectively improve the fan operating energy efficiency under the current operating conditions.

[0059] Further, including:

[0060] Extract the first control record from the centrifugal fan control database, wherein the first control record includes first operating condition characteristic information and a first control strategy; when the first operating condition similarity between the target operating condition characteristic information and the first operating condition characteristic information reaches a similarity limit, obtain the first efficiency point of the first control strategy; when the first efficiency point is at the optimal efficiency point threshold, use the first control strategy as the target control strategy.

[0061] The centrifugal fan control database is a database that stores control records of various operating conditions of the centrifugal fan, and these control records include different operating condition characteristic information and corresponding control strategies. A record is randomly extracted from the centrifugal fan control database as a first control record, and the first control record includes first operating condition characteristic information and a corresponding first control strategy.

[0062] The target operating condition characteristic information is extracted from the target operating condition information, which is characteristic data collected when the centrifugal fan is currently running. The target operating condition characteristic information is compared with the first operating condition characteristic information, and a similarity calculation method such as Euclidean distance, cosine similarity or other statistical indicators is used to calculate the similarity between them. The first operating condition similarity is obtained through similarity calculation.

[0063] The similarity limit is a pre-set threshold value used to determine whether the target operating condition characteristic information is sufficiently similar to the first operating condition characteristic information. When the similarity reaches this limit, it means that the target operating condition is highly similar to the operating condition of the first control record, and the next step can be continued.

[0064] The first efficiency point refers to the optimized efficiency point obtained from the first control strategy under similar operating conditions. This refers to the highest efficiency point that has been verified under the operating conditions. If the efficiency point is high enough, it can be directly applied to the current target operating conditions to improve the energy efficiency performance of the centrifugal fan.

[0065] The best efficiency point threshold is a pre-set threshold used to determine whether the first efficiency point has reached a sufficiently optimized state. This threshold is associated with the design parameters or standard efficiency value of the centrifugal fan and is used to evaluate whether the current operation has reached the best efficiency level.

[0066] When the first efficiency point reaches or exceeds the optimal efficiency point threshold, the first control strategy is used as the target control strategy and applied to the current centrifugal fan operation, which means that it is determined that the first control strategy has proven its effectiveness under similar conditions and is suitable for current working conditions.

[0067] The target control strategy is used as an optimization benchmark to optimize the control energy efficiency of the target centrifugal fan.

[0068] According to the target control strategy, specific operations are performed on the fan, including adjusting the fan speed, adjusting the opening of the air inlet and outlet, adjusting the angle of the blades or cleaning the blades to ensure smooth airflow, etc., to ensure that the fan operates in the optimal state.

[0069] In summary, the centrifugal fan energy efficiency optimization method provided in the embodiment of the present application has the following technical effects:

[0070] By dynamically monitoring the operation and evaluating the operation status of the target centrifugal fan, the comprehensive energy efficiency index can be calculated in real time. This index reflects the energy efficiency performance of the centrifugal fan under the current operation status, and realizes the dynamic optimization of energy efficiency. The comprehensive energy efficiency index is adjusted according to the target operating environment information, so that the system can better adapt to environmental changes. For example, in a high temperature or high vibration environment, the control strategy is adjusted to maintain or optimize energy efficiency and improve system stability and reliability. When the target energy efficiency index does not reach the energy efficiency index limit, an optimization instruction is issued. Based on the issued optimization instruction, the target operating condition characteristic information is traversed in the centrifugal fan control database to generate a targeted optimization control strategy to ensure that the centrifugal fan can achieve the best energy efficiency under different operating conditions, thereby reducing energy consumption and operating costs. In summary, the centrifugal fan energy efficiency optimization method effectively solves the technical problems in the existing centrifugal fan energy efficiency optimization through real-time data acquisition, intelligent analysis and feedback control, and achieves more efficient and intelligent energy efficiency management and control effects.

[0071] Based on the same inventive concept as the centrifugal fan energy efficiency optimization method in the above embodiment, Figure 2 As shown, an embodiment of the present application provides a centrifugal fan energy efficiency optimization system, the system comprising:

[0072] A dynamic operation monitoring module 10 is used to dynamically monitor the operation of the target centrifugal fan to obtain target operation information, wherein the target operation information includes target operation condition information and target operation status information; an evaluation and analysis module 20 is used to activate an operation energy efficiency evaluator to evaluate and analyze the target operation status information to obtain a comprehensive energy efficiency index; a feedback adjustment module 30 is used to feedback and adjust the comprehensive energy efficiency index according to the target operating condition environment information extracted from the target operating condition information to obtain a target energy efficiency index. number; an optimization instruction issuing module 40, the optimization instruction issuing module 40 is used to issue an optimization instruction when the target energy efficiency index does not reach the energy efficiency index limit; a control strategy acquisition module 50, the control strategy acquisition module 50 is used to traverse the target operating condition characteristic information in the centrifugal fan control database based on the optimization instruction to obtain a target control strategy, wherein the target operating condition characteristic information is extracted from the target operating condition information; a control energy efficiency optimization module 60, the control energy efficiency optimization module 60 is used to optimize the control energy efficiency of the target centrifugal fan based on the target control strategy as the optimization benchmark.

[0073] Furthermore, the system further includes an energy efficiency evaluation module to perform the following operation steps:

[0074] The operation energy efficiency evaluator includes a first energy efficiency evaluation channel, a second energy efficiency evaluation channel and a third energy efficiency evaluation channel; the first operation status information is evaluated and analyzed through the first energy efficiency evaluation channel to obtain a first energy efficiency index, wherein the first operation status information is extracted from the target operation status information; the second operation status information is evaluated and analyzed through the second energy efficiency evaluation channel to obtain a second energy efficiency index, wherein the second operation status information is extracted from the target operation status information; the third operation status information is evaluated and analyzed through the third energy efficiency evaluation channel to obtain a third energy efficiency index, wherein the third operation status information is extracted from the target operation status information; the average of the first energy efficiency index, the second energy efficiency index and the third energy efficiency index is recorded as the comprehensive energy efficiency index.

[0075] Furthermore, the system further includes a first energy efficiency index acquisition module to perform the following operation steps:

[0076] A first predetermined energy efficiency evaluation function is embedded in the first energy efficiency evaluation channel; the first predetermined state feature is traversed in the target operating state information to obtain the first operating state information, and the first operating state information includes a flow value, a static pressure value, a total pressure value and a speed value; the flow value, the static pressure value, the total pressure value and the speed value are analyzed according to the first predetermined energy efficiency evaluation function to obtain the first energy efficiency index.

[0077] Furthermore, the expression of the first predetermined energy efficiency evaluation function is as follows:

[0078] Among them, ET(x) refers to the first energy efficiency index of the target centrifugal fan x, f(x) refers to the flow value, F(x) refers to the ideal flow of the target centrifugal fan x, p(x) and p0(x) refer to the total pressure value and the static pressure value, respectively, P(x) refers to the required pressure of the target centrifugal fan x, v(x) refers to the speed value, e refers to the attenuation coefficient, α and β refer to the flow coefficient and pressure coefficient, respectively, and α+β=1. Further, the system also includes a target energy efficiency index acquisition module to perform the following operation steps:

[0079] The target operating condition environment information includes a target environment temperature timing and a target environment vibration timing; a predetermined environmental impact assessment rule is read, and based on the predetermined environmental impact assessment rule, the target environment temperature timing and the target environment vibration timing are evaluated and analyzed in turn to obtain a target environment temperature coefficient and a target environment vibration coefficient, respectively; based on the coefficient mean of the target environment temperature coefficient and the target environment vibration coefficient, the comprehensive energy efficiency index is feedback-adjusted to obtain the target energy efficiency index.

[0080] Furthermore, the system further includes a target ambient temperature coefficient acquisition module to perform the following operation steps:

[0081] Based on the predetermined environmental impact assessment rules, the target temperature multi-domain characteristics of the target ambient temperature time series are obtained; the target temperature multi-domain characteristics are input into the temperature impact assessor to obtain the target ambient temperature coefficient; wherein the temperature impact assessor is an intelligent model obtained by machine learning of a first training data set based on the principle of a neural network, the first training data set includes a first ambient temperature multi-domain characteristic and a first ambient temperature coefficient, and the first ambient temperature multi-domain characteristic includes a first time domain characteristic and a first frequency domain characteristic of a first ambient temperature time series.

[0082] Furthermore, the system further includes a target environment vibration coefficient acquisition module to perform the following operation steps:

[0083] Based on the predetermined environmental impact assessment rules, the target vibration multi-domain characteristics of the target environmental vibration time series are obtained; the target vibration multi-domain characteristics are input into a vibration impact assessor to obtain the target environmental vibration coefficient; wherein the vibration impact assessor is an intelligent model obtained by machine learning of a second training data set based on the principle of a neural network, the second training data set includes a first environmental vibration multi-domain characteristic and a first environmental vibration coefficient, and the first environmental vibration multi-domain characteristic includes a second time domain characteristic and a second frequency domain characteristic of a first environmental vibration time series.

[0084] Furthermore, the system further includes a target control strategy acquisition module to perform the following operation steps:

[0085] Extract the first control record from the centrifugal fan control database, wherein the first control record includes first operating condition characteristic information and a first control strategy; when the first operating condition similarity between the target operating condition characteristic information and the first operating condition characteristic information reaches a similarity limit, obtain the first efficiency point of the first control strategy; when the first efficiency point is at the optimal efficiency point threshold, use the first control strategy as the target control strategy.

[0086] Through the above-mentioned detailed description of a centrifugal fan energy efficiency optimization method in this specification, those skilled in the art can clearly understand a centrifugal fan energy efficiency optimization system in this embodiment. Since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0087] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A centrifugal fan energy efficiency optimization method, characterized in that: The method comprises: Dynamically monitor the operation of the target centrifugal fan to obtain target operation information, wherein the target operation information includes target operation condition information and target operation status information; Activate the operation energy efficiency evaluator to evaluate and analyze the target operation status information to obtain a comprehensive energy efficiency index; Feedback adjustment is performed on the comprehensive energy efficiency index according to the target operating condition environment information extracted from the target operating condition information to obtain a target energy efficiency index; When the target energy efficiency index does not reach the energy efficiency index limit, issuing an optimization instruction; Based on the optimization instruction, the target operating condition characteristic information is traversed in the centrifugal fan control database to obtain a target control strategy, wherein the target operating condition characteristic information is extracted from the target operating condition information; The target control strategy is used as an optimization benchmark to optimize the control energy efficiency of the target centrifugal fan.

2. A centrifugal fan energy efficiency optimization method according to claim 1, characterized in that: include: The operation energy efficiency evaluator includes a first energy efficiency evaluation channel, a second energy efficiency evaluation channel and a third energy efficiency evaluation channel; Evaluate and analyze first operating state information through the first energy efficiency evaluation channel to obtain a first energy efficiency index, wherein the first operating state information is extracted from the target operating state information; Evaluate and analyze the second operating state information through the second energy efficiency evaluation channel to obtain a second energy efficiency index, wherein the second operating state information is extracted from the target operating state information; evaluating and analyzing the third operating state information through the third energy efficiency evaluation channel to obtain a third energy efficiency index, wherein the third operating state information is extracted from the target operating state information; The average of the first energy efficiency index, the second energy efficiency index and the third energy efficiency index is recorded as the comprehensive energy efficiency index.

3. A centrifugal fan energy efficiency optimization method according to claim 2, characterized in that: include: The first energy efficiency evaluation channel has a first predetermined energy efficiency evaluation function embedded therein; Traversing the first predetermined state feature in the target operating state information to obtain the first operating state information, wherein the first operating state information includes a flow value, a static pressure value, a total pressure value, and a speed value; The flow value, the static pressure value, the total pressure value and the rotation speed value are analyzed according to the first predetermined energy efficiency evaluation function to obtain the first energy efficiency index.

4. A centrifugal fan energy efficiency optimization method according to claim 3, characterized in that: The expression of the first predetermined energy efficiency evaluation function is as follows: Among them, ET(x) refers to the first energy efficiency index of the target centrifugal fan x, f(x) refers to the flow value, F(x) refers to the ideal flow of the target centrifugal fan x, p(x) and p0(x) refer to the total pressure value and the static pressure value, respectively, P(x) refers to the required pressure of the target centrifugal fan x, v(x) refers to the speed value, e refers to the attenuation coefficient, α and β refer to the flow coefficient and pressure coefficient, respectively, and α+β=1.

5. The method for optimizing the energy efficiency of a centrifugal fan according to claim 1, characterized in that: include: The target working condition environment information includes a target environment temperature time series and a target environment vibration time series; Reading a predetermined environmental impact assessment rule, and evaluating and analyzing the target environmental temperature time series and the target environmental vibration time series in sequence based on the predetermined environmental impact assessment rule, to obtain a target environmental temperature coefficient and a target environmental vibration coefficient respectively; The comprehensive energy efficiency index is feedback-adjusted based on the coefficient average of the target ambient temperature coefficient and the target ambient vibration coefficient to obtain the target energy efficiency index.

6. A centrifugal fan energy efficiency optimization method according to claim 5, characterized in that: include: Acquire a target temperature multi-domain feature of the target ambient temperature time series based on the predetermined environmental impact assessment rule; Inputting the target temperature multi-domain feature into a temperature impact evaluator to obtain the target ambient temperature coefficient; Among them, the temperature impact evaluator is an intelligent model obtained by machine learning of the first training data set based on the principle of neural network, the first training data set includes the first ambient temperature multi-domain characteristics and the first ambient temperature coefficient, and the first ambient temperature multi-domain characteristics include the first time domain characteristics and the first frequency domain characteristics of the first ambient temperature time series.

7. A centrifugal fan energy efficiency optimization method according to claim 5, characterized in that: include: Acquire the target vibration multi-domain characteristics of the target environmental vibration time series based on the predetermined environmental impact assessment rule; Inputting the target vibration multi-domain feature into a vibration impact evaluator to obtain the target environment vibration coefficient; Among them, the vibration impact evaluator is an intelligent model obtained by machine learning of the second training data set based on the principle of neural network, the second training data set includes the multi-domain characteristics of the first environmental vibration and the first environmental vibration coefficient, and the first environmental vibration multi-domain characteristics include the second time domain characteristics and the second frequency domain characteristics of the first environmental vibration time series.

8. The method for optimizing the energy efficiency of a centrifugal fan according to claim 1, characterized in that: include: Extracting a first control record from the centrifugal fan control database, wherein the first control record includes first operating condition characteristic information and a first control strategy; When the first operating condition similarity between the target operating condition characteristic information and the first operating condition characteristic information reaches a similarity limit, obtaining a first efficiency point of the first control strategy; When the first efficiency point is at the optimal efficiency point threshold, the first control strategy is used as the target control strategy.

9. A centrifugal fan energy efficiency optimization system, characterized in that: For implementing a centrifugal fan energy efficiency optimization method according to any one of claims 1 to 8, the system comprises: A dynamic operation monitoring module, the dynamic operation monitoring module is used to perform dynamic operation monitoring on the target centrifugal fan to obtain target operation information, the target operation information includes target operation condition information and target operation status information; An evaluation and analysis module, the evaluation and analysis module is used to activate an operation energy efficiency evaluator to evaluate and analyze the target operation status information to obtain a comprehensive energy efficiency index; A feedback adjustment module, the feedback adjustment module is used to perform feedback adjustment on the comprehensive energy efficiency index according to the target operating condition environment information extracted from the target operating condition information to obtain a target energy efficiency index; An optimization instruction issuing module, wherein the optimization instruction issuing module is used to issue an optimization instruction when the target energy efficiency index does not reach the energy efficiency index limit; A control strategy acquisition module, the control strategy acquisition module is used to traverse the target operating condition characteristic information in the centrifugal fan control database based on the optimization instruction to obtain a target control strategy, wherein the target operating condition characteristic information is extracted from the target operating condition information; A control energy efficiency optimization module, wherein the control energy efficiency optimization module is used to optimize the control energy efficiency of the target centrifugal fan based on the target control strategy as an optimization benchmark.

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