Pneumatic optimization design method and system for centrifugal fan

Abstract

The invention relates to the technical field of pneumatic optimization, and discloses a pneumatic optimization design method and system for a centrifugal fan, and the system comprises a parameter obtaining module which is used for obtaining an initial design parameter and a standard operation condition of a to-be-optimized centrifugal fan; the test judgment module is used for judging whether the initial design parameters are optimized or not based on the actual operation parameters and the standard operation working condition; the primary optimization module is used for determining a primary optimization coefficient of the initial design parameter based on the aerodynamic performance deviation index and obtaining a primary optimization design parameter; the verification module is used for judging whether the optimization design parameters are reasonable or not according to the verification operation fluctuation curve; the second-stage optimization module is used for determining a second-stage optimization coefficient of the primary optimization design parameter according to the same-type historical optimization record and obtaining a final design parameter; and a storage module. According to the method, through a two-stage optimization mechanism and historical data multiplexing, the accuracy, the reliability and the intelligent level of pneumatic optimization design of the centrifugal fan are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of aerodynamic optimization, in particular to an aerodynamic optimization design method and system of centrifugal fan. BACKGROUND

[0002] In the traditional design and optimization process of centrifugal fan, it often depends on the accumulation of engineers' experience and repeated physical prototype test, and there are problems such as long design cycle, high optimization cost, strong dependence on experience, etc. The traditional method usually adjusts parameters based on a single working condition or limited working condition points, and it is difficult to fully capture the aerodynamic performance variation law of the fan under different operating conditions, resulting in the possibility of aerodynamic performance deviation and insufficient running stability of the optimized fan in actual complex working conditions. In addition, when performance fluctuation or parameter adjustment bottleneck is encountered in the optimization process, there is a lack of effective historical data support and systematic secondary optimization mechanism, so that the accuracy and reliability of the optimization result are difficult to be fully guaranteed, and the high-precision design demand of modern industry on centrifugal fan for high efficiency, energy saving and stable operation cannot be met.

[0003] Therefore, it is necessary to design an aerodynamic optimization design method and system of centrifugal fan to solve the problems existing in the prior art. SUMMARY

[0004] In view of this, the present application provides an aerodynamic optimization design method and system of centrifugal fan, aiming to solve the problem that the accuracy and reliability of the optimization result are difficult to be guaranteed due to the lack of effective historical data support and systematic secondary optimization mechanism when performance fluctuation or parameter adjustment bottleneck is encountered in optimization, and the high-precision design demand of modern industry on centrifugal fan cannot be met.

[0005] In one aspect, the present application provides an aerodynamic optimization design system of centrifugal fan, comprising: A parameter acquisition module is configured to acquire initial design parameters of a centrifugal fan to be optimized and standard operating conditions. A test judgment module is configured to test the operating conditions of the centrifugal fan to be optimized with standard test parameters, obtain actual operating parameters, and judge whether to optimize the initial design parameters based on the actual operating parameters and the standard operating conditions. A primary optimization module is configured to collect aerodynamic performance indicators related to the centrifugal fan to be optimized when it is determined to optimize the initial design parameters, determine an aerodynamic performance deviation index according to the aerodynamic performance indicators, determine a primary optimization coefficient of the initial design parameters based on the aerodynamic performance deviation index, and obtain primary optimization design parameters. A verification module is configured to test the operating conditions of the centrifugal fan to be optimized with verification test parameters, obtain a verification operating fluctuation curve, and judge whether the optimization design parameters are reasonable according to the verification operating fluctuation curve. The secondary optimization module is configured to, when determining that the optimization design parameter is unreasonable, collect a same-type historical optimization record of the same type of the centrifugal fan to be optimized, determine a secondary optimization coefficient of the primary optimization design parameter according to the same-type historical optimization record, and obtain a final design parameter. The storage module is configured to store the secondary optimization coefficient and the final design parameter.

[0006] Further, the initial design parameter includes a blade inlet angle and a blade outlet angle of the centrifugal fan to be optimized, and the standard operating condition includes a standard air volume, a standard air pressure and a standard impeller speed.

[0007] Further, when determining whether to optimize the initial design parameter based on the actual operating parameter and the standard operating condition, the method comprises: analyzing the actual operating parameter to obtain an actual air volume, an actual air pressure and an actual impeller speed; comparing the actual air volume, the actual air pressure and the actual impeller speed with the standard air volume, the standard air pressure and the standard impeller speed respectively, and determining whether to optimize the initial design parameter according to a comparison result; if an absolute value of an air volume deviation of the actual air volume and the standard air volume exceeds a first preset threshold value, or an absolute value of an air pressure deviation of the actual air pressure and the standard air pressure exceeds a second preset threshold value, or an absolute value of an impeller speed deviation of the actual impeller speed and the standard impeller speed exceeds a third preset threshold value, it is determined to optimize the initial design parameter; otherwise, it is determined not to optimize the initial design parameter.

[0008] Further, when determining the aerodynamic performance deviation index according to the aerodynamic performance index, the method comprises: analyzing the aerodynamic performance index to obtain an aerodynamic efficiency, a pressure recovery ability, an energy loss amount and an airflow stability coefficient; performing direction consistency processing on the aerodynamic efficiency, the pressure recovery ability, the energy loss amount and the airflow stability coefficient according to a performance change direction of each aerodynamic performance index; assigning a corresponding weight value to each aerodynamic performance index after the direction consistency processing based on a preset aerodynamic performance weight distribution rule; calculating a deviation of each aerodynamic performance index between an actual value and a corresponding standard value to obtain a single-item deviation amount of each aerodynamic performance index; calculating the aerodynamic performance deviation index according to the single-item deviation amount and the corresponding weight value.

[0009] Further, when determining the primary optimization coefficient of the initial design parameter based on the aerodynamic performance deviation index and obtaining the primary optimization design parameter, the method comprises: The aerodynamic performance deviation index is compared with the first aerodynamic performance deviation index and the second aerodynamic performance deviation index, and the primary optimization coefficient is determined based on the comparison result; wherein, the first aerodynamic performance deviation index is smaller than the second aerodynamic performance deviation index. When the aerodynamic performance offset index is less than or equal to the first aerodynamic performance offset index, the primary optimization coefficient is determined as the first primary optimization coefficient. When the aerodynamic performance offset index is greater than the first aerodynamic performance offset index and less than or equal to the second aerodynamic performance offset index, the primary optimization coefficient is determined as the second primary optimization coefficient. When the aerodynamic performance offset index is greater than the second aerodynamic performance offset index, the primary optimization coefficient is determined as the third primary optimization coefficient.

[0010] Furthermore, the verification test parameters are a combination of parameters that, based on the standard test parameters, expand the air volume fluctuation range to ±a%, the air pressure fluctuation range to ±b%, and the impeller speed fluctuation range to ±c%.

[0011] Furthermore, when judging whether the optimized design parameters are reasonable based on the verification operation fluctuation curve, this includes: The fluctuation curves of the verification operation are analyzed to obtain the fluctuation curves of the verification air volume, the verification air pressure, and the verification impeller speed. The verification air volume fluctuation curve is compared with the preset standard air volume fluctuation threshold range to determine whether the verification air volume meets the air volume stability judgment condition. The verification wind pressure fluctuation curve is compared with the preset standard wind pressure fluctuation threshold range to determine whether the verification wind pressure meets the wind pressure stability judgment condition. The verification impeller speed fluctuation curve is compared with the preset standard impeller speed fluctuation threshold range to determine whether the verification impeller speed meets the impeller speed stability judgment condition. If the verification air volume, verification air pressure, and verification impeller speed all meet the corresponding stability judgment conditions, then the optimized design parameters are deemed reasonable. Otherwise, the optimized design parameters are deemed unreasonable.

[0012] Furthermore, when determining the secondary optimization coefficients of the primary optimization design parameters based on historical optimization records of the same type, and obtaining the final design parameters, the process includes: Collect the fluctuation curves of the verification operation that do not meet the corresponding stability judgment conditions; Feature extraction is performed on the fluctuation curves of the verification operation that do not meet the stability judgment conditions to obtain the abnormal fluctuation frequency band, peak fluctuation amplitude and fluctuation duration; Based on the abnormal frequency band of fluctuation, the peak amplitude of fluctuation, and the duration of fluctuation, similar historical optimization records with a matching degree exceeding the preset matching threshold are selected from the historical optimization records of the same type. The secondary optimization coefficients of the primary optimization design parameters are determined based on similar historical optimization records.

[0013] Furthermore, when determining the secondary optimization coefficients of the primary optimization design parameters based on similar historical optimization records, the following are included: If a similar historical optimization record is unique, then the historical secondary optimization coefficient in that similar historical optimization record shall be used as the secondary optimization coefficient of the current primary optimization design parameter; If similar historical optimization records are not unique, the average value of the historical secondary optimization coefficients in all similar historical optimization records is obtained and recorded as the average historical secondary optimization coefficient. The average historical secondary optimization coefficient is then used as the secondary optimization coefficient of the current primary optimization design parameters.

[0014] Compared with existing technologies, the beneficial effects of this invention are as follows: The aerodynamic optimization design system for centrifugal fans provided by this invention accurately collects initial design parameters and standard operating conditions through a parameter acquisition module, providing a benchmark for optimization; the test and judgment module scientifically determines whether to initiate the optimization process by comparing actual operating parameters with standard operating conditions, avoiding ineffective optimization operations. The primary optimization module introduces an aerodynamic performance offset index, comprehensively considering multiple dimensions such as aerodynamic efficiency and pressure recovery capability, to achieve precise quantitative adjustment of initial design parameters and generate primary optimized design parameters. The verification module obtains verification operation fluctuation curves by expanding the fluctuation range of verification test parameters, comprehensively evaluating the stability of primary optimized parameters under dynamic operating conditions, and ensuring the reliability of optimization results. When the primary optimized parameters do not meet expectations, the secondary optimization module uses historical optimization records of the same type to select cases that highly match the current fluctuation characteristics, providing a basis for secondary correction of the primary optimized parameters based on practical experience, effectively solving the bottleneck problem of parameter adjustment caused by the lack of historical data support in traditional optimization. The storage module's retention of secondary optimization coefficients and final design parameters not only accumulates valuable data assets for the subsequent optimization design of similar fans, but also constructs a continuously iterating and self-improving optimization knowledge base. The entire system forms a complete closed loop of "parameter acquisition - testing and judgment - primary optimization - verification and evaluation - secondary optimization - data storage." Through the two-level optimization mechanism and historical data reuse, the accuracy, reliability, and intelligence level of centrifugal fan aerodynamic optimization design are significantly improved, effectively meeting the modern industrial demand for high-precision and high-efficiency centrifugal fan design.

[0015] In another aspect, the present invention also proposes an aerodynamic optimization design method for centrifugal fans, comprising the following steps: Obtain the initial design parameters and standard operating conditions of the centrifugal fan to be optimized; The centrifugal fan to be optimized was tested under standard test parameters to obtain actual operating parameters. Based on the actual operating parameters and standard operating conditions, it was determined whether the initial design parameters should be optimized. When it is determined that the initial design parameters need to be optimized, aerodynamic performance indicators related to the centrifugal fan to be optimized are collected, and the aerodynamic performance deviation index is determined based on the aerodynamic performance indicators; the primary optimization coefficient of the initial design parameters is determined based on the aerodynamic performance deviation index, and the primary optimized design parameters are obtained. The centrifugal fan to be optimized was tested under operating conditions to verify the test parameters, and the verification operation fluctuation curve was obtained. The rationality of the optimized design parameters was judged based on the verification operation fluctuation curve. When the optimized design parameters are deemed unreasonable, historical optimization records of the same type as the centrifugal fan to be optimized are collected. Based on the historical optimization records of the same type, the secondary optimization coefficients of the primary optimization design parameters are determined, and the final design parameters are obtained. Store the secondary optimization coefficients and final design parameters.

[0016] It is understandable that the aerodynamic optimization design method and system of the centrifugal fan described above have the same beneficial effects, and will not be elaborated further here. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. 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 effort.

[0018] Figure 1 This is a structural block diagram of the aerodynamic optimization design system for a centrifugal fan provided in an embodiment of the present invention; Figure 2 A flowchart of the aerodynamic optimization design method for a centrifugal fan provided in an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0021] See Figure 1 As shown in some embodiments of this application, this embodiment provides an aerodynamic optimization design system for a centrifugal fan, including: The parameter acquisition module is used to acquire the initial design parameters and standard operating conditions of the centrifugal fan to be optimized. The test and judgment module is used to conduct operating condition tests on the centrifugal fan to be optimized using standard test parameters, obtain actual operating parameters, and determine whether the initial design parameters should be optimized based on the actual operating parameters and standard operating conditions. The primary optimization module is used to collect aerodynamic performance indicators related to the centrifugal fan to be optimized when it is determined that the initial design parameters need to be optimized, determine the aerodynamic performance deviation index based on the aerodynamic performance indicators, determine the primary optimization coefficient of the initial design parameters based on the aerodynamic performance deviation index, and obtain the primary optimized design parameters. The verification module is used to test the operating conditions of the centrifugal fan to be optimized with the verification test parameters, obtain the verification operation fluctuation curve, and judge whether the optimization design parameters are reasonable based on the verification operation fluctuation curve. The secondary optimization module is used to collect historical optimization records of the same type as the centrifugal fan to be optimized when the optimization design parameters are deemed unreasonable. Based on the historical optimization records of the same type, the secondary optimization coefficients of the primary optimization design parameters are determined, and the final design parameters are obtained. The storage module is used to store the secondary optimization coefficients and the final design parameters.

[0022] Understandably, the aerodynamic optimization design system for centrifugal fans provided in this embodiment accurately collects initial design parameters and standard operating conditions through a parameter acquisition module, providing a benchmark for optimization. The testing and judgment module scientifically determines whether to initiate the optimization process by comparing actual operating parameters with standard operating conditions, avoiding ineffective optimization operations. The primary optimization module introduces an aerodynamic performance offset index, comprehensively considering multiple dimensions such as aerodynamic efficiency and pressure recovery capability to achieve precise quantitative adjustment of initial design parameters and generate primary optimized design parameters. The verification module obtains verification operation fluctuation curves by expanding the fluctuation range of verification test parameters, comprehensively evaluating the stability of primary optimized parameters under dynamic operating conditions, ensuring the reliability of optimization results. When the primary optimized parameters do not meet expectations, the secondary optimization module uses historical optimization records of the same type to select cases that highly match the current fluctuation characteristics, providing a basis for secondary correction of the primary optimized parameters based on practical experience, effectively solving the bottleneck problem of parameter adjustment caused by the lack of historical data support in traditional optimization. The storage module's retention of secondary optimization coefficients and final design parameters not only accumulates valuable data assets for the subsequent optimization design of similar fans, but also constructs a continuously iterating and self-improving optimization knowledge base. The entire system forms a complete closed loop of "parameter acquisition - testing and judgment - primary optimization - verification and evaluation - secondary optimization - data storage." Through the two-level optimization mechanism and historical data reuse, the accuracy, reliability, and intelligence level of centrifugal fan aerodynamic optimization design are significantly improved, effectively meeting the modern industrial demand for high-precision and high-efficiency centrifugal fan design.

[0023] Specifically, the initial design parameters include the blade inlet angle and blade outlet angle of the centrifugal fan to be optimized; the standard operating conditions include standard air volume, standard air pressure and standard impeller speed.

[0024] Understandably, among the initial design parameters, the blade inlet angle and outlet angle are the core geometric parameters affecting the aerodynamic performance of centrifugal fans. Their values ​​relate to the flow state and energy conversion efficiency of the airflow within the impeller. The blade inlet angle determines the impact loss of the airflow entering the impeller; a reasonable design can reduce airflow separation and decrease resistance. The blade outlet angle affects the fan's pressure and flow characteristics; different outlet angles result in different performance emphases for the fan. For example, a small outlet angle for backward-curved fans results in high aerodynamic efficiency, while a large outlet angle for forward-curved fans results in high pressure. Under standard operating conditions, standard airflow, pressure, and impeller speed constitute the design target benchmarks. Standard airflow measures the conveying capacity, standard pressure reflects the ability to overcome resistance and increase energy, and standard impeller speed is a crucial parameter for achieving the target, affecting the impeller's work and operational stability. Combining the initial design parameters with the standard operating condition parameters can characterize the features and performance requirements of the fan design state to be optimized, providing a reference and guidance for subsequent testing, judgment, and optimization adjustments.

[0025] Specifically, when determining whether to optimize the initial design parameters based on actual operating parameters and standard operating conditions, the following should be included: The actual operating parameters are analyzed to obtain the actual air volume, actual air pressure, and actual impeller speed. The actual air volume, actual air pressure, and actual impeller speed are compared with the standard air volume, standard air pressure, and standard impeller speed, respectively. Based on the comparison results, it is determined whether the initial design parameters need to be optimized. If the absolute value of the deviation between the actual air volume and the standard air volume exceeds the first preset threshold, or the absolute value of the deviation between the actual air pressure and the standard air pressure exceeds the second preset threshold, or the absolute value of the deviation between the actual impeller speed and the standard impeller speed exceeds the third preset threshold, then it is determined that the initial design parameters should be optimized. Otherwise, it is determined that the initial design parameters will not be optimized.

[0026] Understandably, the preferred values ​​for the first preset threshold are 3%, the second 5%, and the third 2%. These thresholds are set considering the design precision requirements of the centrifugal fan industry, the actual production assembly error range, and the allowable performance fluctuation range under different operating conditions. For example, the airflow deviation threshold is set at 3% because in most industrial applications, airflow fluctuations exceeding this range significantly affect the stability of downstream processes. Air pressure, as a key indicator for overcoming system resistance, has a deviation threshold of 5%, considering both the sensitivity of aerodynamic performance and the dynamic changes in pipeline resistance during actual operation. Impeller speed, as a fundamental parameter of mechanical operation, has high stability requirements; a 2% threshold effectively avoids increased mechanical vibration and energy consumption surges caused by abnormal speed fluctuations. By comparing the deviations of actual operating parameters and standard operating conditions with the corresponding thresholds, clear quantitative judgment standards can be formed, ensuring that the initiation of optimization processes has an objective and operable basis, avoiding the subjectivity and uncertainty of traditional experience-based judgments.

[0027] Specifically, when determining the aerodynamic performance offset index based on aerodynamic performance indicators, the following are included: The aerodynamic performance indicators are analyzed to obtain aerodynamic efficiency, pressure recovery capability, energy loss and airflow stability coefficient; Based on the direction of performance change of each aerodynamic performance index, the aerodynamic efficiency, pressure recovery capability, energy loss and airflow stability coefficient are made consistent in direction. Based on the preset aerodynamic performance weight allocation rules, each aerodynamic performance index after direction consistency processing is assigned a corresponding weight value. The deviation between the actual value and the corresponding standard value of each aerodynamic performance index is calculated to obtain the individual offset of each aerodynamic performance index. The aerodynamic performance offset index is calculated based on the individual offset and its corresponding weight value.

[0028] Understandably, the directional consistency processing includes: for aerodynamic performance indicators such as aerodynamic efficiency, pressure recovery capability, and airflow stability coefficient, whose performance improves with increasing values, the difference between the standard value and the actual value is used as the offset; for aerodynamic performance indicators such as energy loss, whose performance deteriorates with increasing values, the difference between the actual value and the standard value is used as the offset, so that the offsets corresponding to each aerodynamic performance indicator are used to uniformly characterize the degree of aerodynamic performance degradation. The preset aerodynamic performance weight allocation rule refers to setting differentiated weight coefficients for each aerodynamic performance indicator based on the different performance requirements of centrifugal fans in different application scenarios. For example, in ventilation systems where energy saving is the core objective, aerodynamic efficiency is weighted at 0.4 as the primary optimization indicator; in high-pressure air supply scenarios, pressure recovery capability is weighted at 0.35 to ensure the energy conversion effect of the fan under high resistance conditions; energy loss, as a key indicator reflecting flow loss, is weighted at 0.15, focusing on energy dissipation caused by flow field separation and secondary flow within the impeller; and airflow stability coefficient is weighted at 0.1 to evaluate dynamic characteristics such as airflow adhesion on the blade surface and airflow uniformity at the volute outlet, avoiding vibration and noise problems caused by airflow pulsation.

[0029] Specifically, when determining the initial optimization coefficients of the initial design parameters based on the aerodynamic performance offset index, and obtaining the initial optimized design parameters, the process includes: The aerodynamic performance deviation index is compared with the first aerodynamic performance deviation index and the second aerodynamic performance deviation index, and the primary optimization coefficient is determined based on the comparison result; wherein, the first aerodynamic performance deviation index is smaller than the second aerodynamic performance deviation index. When the aerodynamic performance offset index is less than or equal to the first aerodynamic performance offset index, the primary optimization coefficient is determined as the first primary optimization coefficient. When the aerodynamic performance offset index is greater than the first aerodynamic performance offset index and less than or equal to the second aerodynamic performance offset index, the primary optimization coefficient is determined as the second primary optimization coefficient. When the aerodynamic performance offset index is greater than the second aerodynamic performance offset index, the primary optimization coefficient is determined as the third primary optimization coefficient.

[0030] It is understandable that the primary optimization coefficients are represented as (primary blade inlet angle optimization coefficient, primary blade outlet angle optimization coefficient). The preferred values ​​for the first primary optimization coefficient are (0.98, 1.02), the preferred values ​​for the second primary optimization coefficient are (0.95, 1.05), and the preferred values ​​for the third primary optimization coefficient are (0.92, 1.08). These coefficient settings are based on the degree of performance deviation reflected by the aerodynamic performance deviation index. The smaller the deviation index, the smaller the difference between the performance and the standard operating condition, and the smaller the required adjustment range. For example, when the aerodynamic performance deviation index is less than or equal to the first aerodynamic performance deviation index (assuming its value is 5%), it indicates that the current aerodynamic performance only has a slight deviation. In this case, the first primary optimization coefficient (0.98, 1.02) is used, that is, a 2% decrease in the blade inlet angle and a 2% increase in the blade outlet angle are adjusted. This fine-tuning corrects the initial entry angle and energy output state of the airflow to gradually approach the standard performance. When the offset index is greater than the first aerodynamic performance offset index and less than or equal to the second aerodynamic performance offset index (assuming its value is 10%), the performance deviation is moderate. In this case, a second primary optimization coefficient with a larger adjustment range (0.95, 1.05) is selected, i.e., the inlet angle is reduced by 5% and the outlet angle is increased by 5%, which improves the flow separation and energy conversion efficiency of the airflow in the impeller through more significant changes in geometric parameters. If the offset index is greater than the second aerodynamic performance offset index, it indicates that the performance is seriously substandard. In this case, a third primary optimization coefficient with the largest adjustment range (0.92, 1.08) is required, which reduces the inlet angle by 8% and increases the outlet angle by 8%, in order to quickly improve the aerodynamic performance through a larger range of parameter optimization, so that it meets the basic design requirements. After determining the primary optimization coefficients, the primary optimization design parameters are obtained by multiplying the initial design parameters (blade inlet angle and outlet angle) by the corresponding primary optimization coefficients. For example, if the initial blade inlet angle is 30° and the initial blade outlet angle is 45°, and the second primary optimization coefficient (0.95, 1.05) is used, then the primary optimized blade inlet angle is 30° × 0.95 = 28.5° and the primary optimized blade outlet angle is 45° × 1.05 = 47.25°.

[0031] Specifically, the verification test parameters are a combination of parameters that expand the air volume fluctuation range to ±a%, the air pressure fluctuation range to ±b%, and the impeller speed fluctuation range to ±c% based on the standard test parameters.

[0032] Understandably, the preferred values ​​for a, b, and c are 8, 10, and 5, respectively. This means that the verification test parameters, based on the standard test parameters, expand the fluctuation range of airflow from the relatively small range of conventional tests (e.g., ±3%) to ±8%, the fluctuation range of air pressure to ±10%, and the fluctuation range of impeller speed to ±5%. The reason for this setting is that standard test parameters typically only cover the stable region near rated operating conditions, making it difficult to fully reflect the complex dynamic operating conditions that the fan may encounter in actual industrial environments, such as sudden changes in pipeline resistance and instantaneous load changes. By expanding the fluctuation range of airflow, air pressure, and speed, the verification test can simulate more extreme boundary conditions that are closer to actual application scenarios. The resulting verification operation fluctuation curves can more realistically reveal the performance of the initial optimized design parameters under different operating conditions, including their stability margin, anti-interference ability, and aerodynamic efficiency degradation under non-design conditions. For example, a ±8% fluctuation range in airflow can verify the changes in pressure output and efficiency of the fan under overload (8% increase in airflow) and under low load (8% decrease in airflow) conditions; a ±10% fluctuation in air pressure can assess the fan's adaptability to significant increases or decreases in pipeline resistance; and a ±5% fluctuation in impeller speed simulates the impact of motor power supply voltage fluctuations or speed deviations during variable frequency speed regulation on aerodynamic performance. This wide-range verification test allows the verification module to more rigorously select optimization parameters that are stable under various operating conditions, avoiding the judgment of parameters that only meet the standards under ideal operating conditions but whose performance deteriorates sharply under dynamic operating conditions as reasonable, thereby further improving the reliability and robustness of the optimization design.

[0033] Specifically, when judging whether the optimized design parameters are reasonable based on the verification operation fluctuation curve, this includes: The fluctuation curves of the verification operation are analyzed to obtain the fluctuation curves of the verification air volume, the verification air pressure, and the verification impeller speed. The verification air volume fluctuation curve is compared with the preset standard air volume fluctuation threshold range to determine whether the verification air volume meets the air volume stability judgment condition. The verification wind pressure fluctuation curve is compared with the preset standard wind pressure fluctuation threshold range to determine whether the verification wind pressure meets the wind pressure stability judgment condition. The verification impeller speed fluctuation curve is compared with the preset standard impeller speed fluctuation threshold range to determine whether the verification impeller speed meets the impeller speed stability judgment condition. If the verification air volume, verification air pressure, and verification impeller speed all meet the corresponding stability judgment conditions, then the optimized design parameters are deemed reasonable. Otherwise, the optimized design parameters are deemed unreasonable.

[0034] Understandably, the verification airflow fluctuation curve is a curve with time on the horizontal axis and airflow value on the vertical axis. It reflects the continuous fluctuation of airflow over time (or changes in operating conditions) within the range of verification test parameters. The preset standard airflow fluctuation threshold range is usually determined based on the design purpose of the fan and the tolerance of the downstream system. For example, for precision manufacturing environments requiring continuous and stable air supply, the standard airflow fluctuation threshold range may be set to ±2% of the rated airflow; while for some ventilation scenarios that are not sensitive to airflow fluctuations, the threshold range can be appropriately widened to ±5%. By comparing all data points on the verification airflow fluctuation curve with this threshold range point by point, if the curve does not exceed the upper and lower limits of the threshold throughout, it is determined that the verification airflow meets the airflow stability judgment condition, indicating that the primary optimized design parameters have good stability in airflow regulation. Similarly, the analysis and judgment process for the verification air pressure fluctuation curve and the verification impeller speed fluctuation curve is similar. The setting of the standard wind pressure fluctuation threshold range needs to consider the pressure resistance of the system network and the process requirements for wind pressure stability. For example, in a high-pressure dust removal system, excessive wind pressure fluctuations can lead to a significant decrease in dust removal efficiency, so the threshold range may be set at ±3%. The standard impeller speed fluctuation threshold range is mainly based on the speed regulation accuracy of the motor and the stability requirements of the mechanical transmission system, and is generally set at ±1% to ensure the mechanical safety and energy consumption stability of the fan operation. Only when the fluctuation curves of the three core operating parameters—air volume, wind pressure, and speed—are strictly controlled within their respective standard threshold ranges can it be comprehensively determined that the primary optimized design parameters have sufficient stability under dynamic operating conditions and can serve as the basis for subsequent advanced optimization. Conversely, if the fluctuation of any parameter exceeds the threshold range, it indicates that the primary optimized design parameters have performance defects when dealing with complex operating conditions, and it is necessary to return to the parameter adjustment stage for correction.

[0035] Specifically, when determining the secondary optimization coefficients of the primary optimization design parameters based on historical optimization records of the same type, and obtaining the final design parameters, the process includes: Collect the fluctuation curves of the verification operation that do not meet the corresponding stability judgment conditions; Feature extraction is performed on the fluctuation curves of the verification operation that do not meet the stability judgment conditions to obtain the abnormal fluctuation frequency band, peak fluctuation amplitude and fluctuation duration; Based on the abnormal frequency band of fluctuation, the peak amplitude of fluctuation, and the duration of fluctuation, similar historical optimization records with a matching degree exceeding the preset matching threshold are selected from the historical optimization records of the same type. The secondary optimization coefficients of the primary optimization design parameters are determined based on similar historical optimization records.

[0036] Understandably, the matching degree is calculated by comparing the three characteristic parameters—abnormal fluctuation frequency band, fluctuation peak amplitude, and fluctuation duration—with the corresponding features in the historical optimization records of the same type, and then obtaining the comprehensive matching degree through weighted summation. Among them, the similarity weight of the abnormal fluctuation frequency band is the highest, with an optimal value of 0.5, because the frequency band feature directly reflects the frequency characteristics of the fluctuation and is most closely related to the root causes of aerodynamic performance instability (such as the periodicity of airflow separation, the starting frequency of rotational stall, etc.). The fluctuation peak amplitude has the second highest weight, with an optimal value of 0.3, as its magnitude reflects the severity of the fluctuation and determines the urgency of adjustment. The fluctuation duration has a weight of 0.2, which is used to measure the stability of the fluctuation. Short-term peak fluctuations may be caused by transient disturbances, while continuous fluctuations indicate the existence of systemic defects. In specific calculations, for abnormal frequency bands, a cosine similarity algorithm is used to calculate the spectral similarity between the current abnormal frequency band and abnormal frequency bands in historical records. For the peak amplitude of fluctuations, the ratio of the absolute difference between the current peak amplitude and the historical peak amplitude to the historical peak amplitude is calculated, and then this ratio is subtracted from 1 to obtain the amplitude similarity. For the duration of fluctuations, a similar calculation method is used, i.e., 1 is subtracted from the ratio of the absolute difference between the current duration and the historical duration to the historical duration. For example, if the spectral cosine similarity between the current abnormal frequency band and a certain historical record is 0.85, the peak amplitude similarity is 0.7, and the duration similarity is 0.6, then the overall matching degree is 0.755. The preset matching threshold is preferably set to 0.7. When the overall matching degree exceeds 0.7, it is determined to be a similar historical optimized record. After filtering out similar historical optimization records, the corresponding secondary optimization coefficient adjustment strategy is extracted. For example, if in similar historical records, when the abnormal fluctuation frequency band is concentrated in 50-80Hz, the peak fluctuation amplitude is 12% of the rated value, and the fluctuation duration is 3 seconds, the secondary optimization coefficient is (-0.01, 0.01), that is, the optimization coefficient of the primary blade inlet angle is reduced by 0.01 and the optimization coefficient of the primary blade outlet angle is increased by 0.01. Then the secondary optimization coefficient of the current primary optimization design parameters is also determined to be this value. Then, the final design parameters are obtained by multiplying the primary optimization design parameters by (1 + secondary optimization coefficient), so as to achieve precise fine-tuning of the primary optimization to solve specific fluctuation anomaly problems.

[0037] Specifically, when determining the secondary optimization coefficients of the primary optimization design parameters based on similar historical optimization records, the following are included: If a similar historical optimization record is unique, then the historical secondary optimization coefficient in that similar historical optimization record shall be used as the secondary optimization coefficient of the current primary optimization design parameter; If similar historical optimization records are not unique, the average value of the historical secondary optimization coefficients in all similar historical optimization records is obtained and recorded as the average historical secondary optimization coefficient. The average historical secondary optimization coefficient is then used as the secondary optimization coefficient of the current primary optimization design parameters.

[0038] Understandably, the secondary optimization coefficients are represented as (secondary blade inlet angle optimization coefficient, secondary blade outlet angle optimization coefficient). When only one similar historical optimization record is selected, it indicates that the current fluctuation characteristic matches that historical record with a high degree of uniqueness. In this case, the secondary optimization coefficients that have been proven effective in practice can be directly reused from that historical record without additional calculation, ensuring the accuracy and efficiency of the adjustment strategy. For example, if the secondary optimization coefficient used for a specific fluctuation characteristic in the unique similar historical record is (-0.02, 0.03), then the secondary optimization coefficients of the current primary optimization design parameters are directly determined to be (-0.02, 0.03). However, when there are two or more similar historical optimization records, it indicates that there are multiple possible adjustment strategies. To avoid the influence of randomness or special characteristics that may exist in a single historical record, the historical secondary optimization coefficients of all similar historical records need to be comprehensively processed. Specifically, the average blade inlet angle optimization coefficient and the average blade outlet angle optimization coefficient of the historical secondary optimization coefficients in all similar historical records are calculated separately, and these two averages are combined to form the average historical secondary optimization coefficient. For example, if there are three similar historical records with their respective secondary optimization coefficients of (-0.01, 0.02), (-0.03, 0.04), and (-0.02, 0.03), then the average optimization coefficient of the blade inlet angle is [(-0.01) + (-0.03) + (-0.02)] / 3 = -0.02, and the average optimization coefficient of the blade outlet angle is [(0.02) + (0.04) + (0.03)] / 3 = 0.03. Therefore, the average historical secondary optimization coefficient is (-0.02, 0.03), which is used as the secondary optimization coefficient for the current primary optimization design parameters. This method of averaging multiple sets of similar historical data can integrate the adjustment logic of different historical experiences, reduce the interference of individual extreme data on the optimization results, make the determination of the secondary optimization coefficient more robust and reliable, and further improve the universality and optimization effect of the final design parameters. After obtaining the secondary optimization coefficients, the final design parameters are obtained by multiplying the primary optimization design parameters by (1 + secondary optimization coefficients). For example, if the blade inlet angle after primary optimization is 28.5°, the blade outlet angle after primary optimization is 47.25°, and the determined secondary optimization coefficient is (-0.02, 0.03), then the final blade inlet angle is 28.5° × (1 - 0.02) = 28.5° × 0.98 = 27.93°, and the final blade outlet angle is 47.25° × (1 + 0.03) = 47.25° × 1.03 = 48.6675°. Through these two steps of primary and secondary optimization, a progressive optimization process from initial correction to precise fine-tuning of the design parameters is achieved. This ensures rapid correction of significant performance deviations and, through the integration of historical experience data, achieves accurate calibration of subtle fluctuation characteristics, ultimately obtaining aerodynamic design parameters for the centrifugal fan that can operate stably and efficiently under various operating conditions.

[0039] See Figure 2 As shown in some embodiments of this application, this embodiment provides an aerodynamic optimization design method for a centrifugal fan, including the following steps: S100: Obtain the initial design parameters and standard operating conditions of the centrifugal fan to be optimized; S200: Perform operating condition tests on the centrifugal fan to be optimized using standard test parameters, obtain actual operating parameters, and determine whether to optimize the initial design parameters based on the actual operating parameters and standard operating conditions; S300: When it is determined that the initial design parameters need to be optimized, the aerodynamic performance indicators related to the centrifugal fan to be optimized are collected, and the aerodynamic performance deviation index is determined based on the aerodynamic performance indicators; the primary optimization coefficient of the initial design parameters is determined based on the aerodynamic performance deviation index, and the primary optimized design parameters are obtained. S400: Perform operating condition tests on the centrifugal fan to be optimized using the verification test parameters, obtain the verification operation fluctuation curve, and judge whether the optimized design parameters are reasonable based on the verification operation fluctuation curve; S500: When the optimized design parameters are determined to be unreasonable, collect historical optimization records of the same type as the centrifugal fan to be optimized, determine the secondary optimization coefficients of the primary optimization design parameters based on the historical optimization records of the same type, and obtain the final design parameters; S600: Stores secondary optimization coefficients and final design parameters.

[0040] In the description of this invention, it should be understood that the terms "longitudinal", "lateral", "up", "down", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this invention, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention.

[0041] The above embodiments are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. An aerodynamic optimization design system for a centrifugal fan, characterized in that, include: The parameter acquisition module is used to acquire the initial design parameters and standard operating conditions of the centrifugal fan to be optimized. The test and judgment module is used to conduct operating condition tests on the centrifugal fan to be optimized using standard test parameters, obtain actual operating parameters, and determine whether the initial design parameters should be optimized based on the actual operating parameters and standard operating conditions. The primary optimization module is used to collect aerodynamic performance indicators related to the centrifugal fan to be optimized when it is determined that the initial design parameters need to be optimized, and to determine the aerodynamic performance deviation index based on the aerodynamic performance indicators. The initial optimization coefficients of the initial design parameters are determined based on the aerodynamic performance offset index, and the initial optimization design parameters are obtained. The verification module is used to test the operating conditions of the centrifugal fan to be optimized with the verification test parameters, obtain the verification operation fluctuation curve, and judge whether the optimization design parameters are reasonable based on the verification operation fluctuation curve. The secondary optimization module is used to collect historical optimization records of the same type as the centrifugal fan to be optimized when the optimization design parameters are deemed unreasonable. Based on the historical optimization records of the same type, the secondary optimization coefficients of the primary optimization design parameters are determined, and the final design parameters are obtained. The storage module is used to store the secondary optimization coefficients and the final design parameters.

2. The aerodynamic optimization design system for a centrifugal fan according to claim 1, characterized in that, The initial design parameters include the blade inlet angle and blade outlet angle of the centrifugal fan to be optimized; the standard operating conditions include standard air volume, standard air pressure and standard impeller speed.

3. The aerodynamic optimization design system for a centrifugal fan according to claim 2, characterized in that, When determining whether to optimize the initial design parameters based on actual operating parameters and standard operating conditions, the following should be included: The actual operating parameters are analyzed to obtain the actual air volume, actual air pressure, and actual impeller speed. The actual air volume, actual air pressure, and actual impeller speed are compared with the standard air volume, standard air pressure, and standard impeller speed, respectively. Based on the comparison results, it is determined whether the initial design parameters need to be optimized. If the absolute value of the deviation between the actual air volume and the standard air volume exceeds the first preset threshold, or the absolute value of the deviation between the actual air pressure and the standard air pressure exceeds the second preset threshold, or the absolute value of the deviation between the actual impeller speed and the standard impeller speed exceeds the third preset threshold, then it is determined that the initial design parameters should be optimized. Otherwise, it is determined that the initial design parameters will not be optimized.

4. The aerodynamic optimization design system for a centrifugal fan according to claim 3, characterized in that, When determining the aerodynamic performance offset index based on aerodynamic performance indicators, the following are included: The aerodynamic performance indicators are analyzed to obtain aerodynamic efficiency, pressure recovery capability, energy loss and airflow stability coefficient; Based on the direction of performance change of each aerodynamic performance index, the aerodynamic efficiency, pressure recovery capability, energy loss and airflow stability coefficient are made consistent in direction. Based on the preset aerodynamic performance weight allocation rules, each aerodynamic performance index after direction consistency processing is assigned a corresponding weight value. The deviation between the actual value and the corresponding standard value of each aerodynamic performance index is calculated to obtain the individual offset of each aerodynamic performance index. The aerodynamic performance offset index is calculated based on the individual offset and its corresponding weight value.

5. The aerodynamic optimization design system for a centrifugal fan according to claim 4, characterized in that, When determining the initial optimization coefficients of the initial design parameters based on the aerodynamic performance offset index, and obtaining the initial optimization design parameters, the following are included: The aerodynamic performance deviation index is compared with the first aerodynamic performance deviation index and the second aerodynamic performance deviation index, and the primary optimization coefficient is determined based on the comparison result; wherein, the first aerodynamic performance deviation index is smaller than the second aerodynamic performance deviation index. When the aerodynamic performance offset index is less than or equal to the first aerodynamic performance offset index, the primary optimization coefficient is determined as the first primary optimization coefficient. When the aerodynamic performance offset index is greater than the first aerodynamic performance offset index and less than or equal to the second aerodynamic performance offset index, the primary optimization coefficient is determined as the second primary optimization coefficient. When the aerodynamic performance offset index is greater than the second aerodynamic performance offset index, the primary optimization coefficient is determined as the third primary optimization coefficient.

6. The aerodynamic optimization design system for a centrifugal fan according to claim 5, characterized in that, The verification test parameters are a combination of parameters that expand the air volume fluctuation range to ±a%, the air pressure fluctuation range to ±b%, and the impeller speed fluctuation range to ±c% based on the standard test parameters.

7. The aerodynamic optimization design system for a centrifugal fan according to claim 6, characterized in that, When judging whether the optimized design parameters are reasonable based on the fluctuation curve of the verification operation, the following are included: The fluctuation curves of the verification operation are analyzed to obtain the fluctuation curves of the verification air volume, the verification air pressure, and the verification impeller speed. The verification air volume fluctuation curve is compared with the preset standard air volume fluctuation threshold range to determine whether the verification air volume meets the air volume stability judgment condition. The verification wind pressure fluctuation curve is compared with the preset standard wind pressure fluctuation threshold range to determine whether the verification wind pressure meets the wind pressure stability judgment condition. The verification impeller speed fluctuation curve is compared with the preset standard impeller speed fluctuation threshold range to determine whether the verification impeller speed meets the impeller speed stability judgment condition. If the verification air volume, verification air pressure, and verification impeller speed all meet the corresponding stability judgment conditions, then the optimized design parameters are deemed reasonable. Otherwise, the optimized design parameters are deemed unreasonable.

8. The aerodynamic optimization design system for a centrifugal fan according to claim 7, characterized in that, When determining the secondary optimization coefficients of the primary optimization design parameters based on historical optimization records of the same type, and obtaining the final design parameters, the following are included: Collect the fluctuation curves of the verification operation that do not meet the corresponding stability judgment conditions; Feature extraction is performed on the fluctuation curves of the verification operation that do not meet the stability judgment conditions to obtain the abnormal fluctuation frequency band, peak fluctuation amplitude and fluctuation duration; Based on the abnormal frequency band of fluctuation, the peak amplitude of fluctuation, and the duration of fluctuation, similar historical optimization records with a matching degree exceeding the preset matching threshold are selected from the historical optimization records of the same type. The secondary optimization coefficients of the primary optimization design parameters are determined based on similar historical optimization records.

9. The aerodynamic optimization design system for a centrifugal fan according to claim 8, characterized in that, When determining the secondary optimization coefficients of the primary optimization design parameters based on similar historical optimization records, the following are included: If a similar historical optimization record is unique, then the historical secondary optimization coefficient in that similar historical optimization record shall be used as the secondary optimization coefficient of the current primary optimization design parameter; If similar historical optimization records are not unique, the average value of the historical secondary optimization coefficients in all similar historical optimization records is obtained and recorded as the average historical secondary optimization coefficient. The average historical secondary optimization coefficient is then used as the secondary optimization coefficient of the current primary optimization design parameters.

10. An aerodynamic optimization design method for a centrifugal fan, applied to the aerodynamic optimization design system for a centrifugal fan as described in any one of claims 1-9, characterized in that, include: Obtain the initial design parameters and standard operating conditions of the centrifugal fan to be optimized; The centrifugal fan to be optimized was tested under standard test parameters to obtain actual operating parameters. Based on the actual operating parameters and standard operating conditions, it was determined whether the initial design parameters should be optimized. When it is determined that the initial design parameters need to be optimized, aerodynamic performance indicators related to the centrifugal fan to be optimized are collected, and the aerodynamic performance deviation index is determined based on the aerodynamic performance indicators. The initial optimization coefficients of the initial design parameters are determined based on the aerodynamic performance offset index, and the initial optimization design parameters are obtained. The centrifugal fan to be optimized was tested under operating conditions to verify the test parameters, and the verification operation fluctuation curve was obtained. The rationality of the optimized design parameters was judged based on the verification operation fluctuation curve. When the optimized design parameters are deemed unreasonable, historical optimization records of the same type as the centrifugal fan to be optimized are collected. Based on the historical optimization records of the same type, the secondary optimization coefficients of the primary optimization design parameters are determined, and the final design parameters are obtained. Store the secondary optimization coefficients and final design parameters.

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