An automatic mass correction method and system for fan unbalance

Abstract

The present invention discloses an automatic mass compensation and correction method and system for fan imbalance, including the following steps: collecting geometric parameters and material properties in the static state of the fan to construct a mechanical distribution model of the fan; collecting vibration signals and airflow characteristics in real time in the dynamic operation state, calculating the imbalance during operation and decomposing it into the main component and the secondary component; predicting the trend based on the imbalance, determining the mass compensation range and performing multi-point mass compensation operations through the dispensing technology, and simultaneously using a fiber optic sensor to monitor the mass compensation effect; if the residual imbalance after mass compensation still exceeds the standard, real-time compensation adjustment is performed through the electromagnetic torque control module. The present invention realizes the full-process automatic correction from static to dynamic and from mass compensation to fine adjustment, has the characteristics of real-time, accuracy and intelligence, can effectively reduce the vibration and noise during the operation of the fan, and improve the operation stability and service life of the equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of dynamic balance correction, and in particular to a method and system for automatically correcting fan imbalance. Background Art

[0002] With the widespread application of fans in industrial ventilation equipment, household appliances, and aviation turbomachinery, their operational stability and long-term reliability are receiving increasing attention. The imbalance generated during fan operation is the main cause of vibration, noise, reduced energy efficiency, and equipment wear. The sources of imbalance usually include geometric errors in the rotor manufacturing process, uneven material distribution, and dynamic imbalance generated during long-term operation. This imbalance not only has a negative impact on the performance of the equipment, but may also increase the risk of failure during operation. Therefore, how to efficiently and accurately correct the imbalance of the fan has become an important research topic in modern dynamic balancing technology.

[0003] In the existing technology, the correction methods for fan imbalance are generally divided into two categories: static correction and dynamic correction. The static correction method mainly adjusts the mass distribution of the rotor through mechanical processing, weighting, weight reduction and other means during the rotor manufacturing stage to reduce the initial imbalance. However, this correction method cannot solve the dynamic imbalance problem caused by external force, material aging or temperature change during the actual operation of the equipment. Its application scenarios and effects have great limitations. Dynamic correction technology collects vibration signals or imbalance in real time, and combines correction devices to compensate for the quality deviation during fan operation. However, the existing dynamic correction technology still has significant deficiencies in real-time, accuracy and intelligence.

[0004] Existing dynamic correction methods are relatively lacking in real-time performance. Usually, the equipment needs to suspend operation to complete the detection and correction of the imbalance. This step-by-step processing method leads to discontinuity in the operation of the equipment and is not suitable for dynamic balancing scenarios with high real-time requirements. For the imbalance generated by the fan during actual operation, traditional technology is difficult to correct while running, which is inefficient; the accuracy of dynamic correction is also difficult to meet the needs of high-performance equipment. Existing technologies often estimate the imbalance based on static data, and fail to fully consider the airflow disturbance, vibration signal and its coupling effect during fan operation. This makes it difficult to completely eliminate the dynamic imbalance after correction, especially under complex operating conditions, and the correction accuracy is further reduced.

[0005] Existing dynamic correction technologies have a low level of intelligence and rely heavily on manual operation. For example, the judgment of imbalance, the formulation of correction strategies, and the adjustment of correction parameters are usually completed by operators, which not only increases the complexity of the correction process, but is also easily affected by human errors. At the same time, there is a lack of data-driven historical correction optimization capabilities, and the correction strategy cannot be dynamically adjusted according to changes in the equipment's operating status, further limiting the adaptability and stability of the technology. After the quality compensation operation is completed, the existing technology lacks effective means to deal with the residual imbalance. When the quality compensation effect does not meet expectations, it is usually necessary to re-execute the complete correction process, and efficient real-time fine-tuning compensation cannot be achieved.

[0006] Therefore, how to provide a method and system for automatically correcting fan imbalance is an urgent problem that those skilled in the art need to solve. Summary of the Invention

[0007] One purpose of the present invention is to propose a method and system for automatic quality correction of fan imbalance. The present invention fully combines multimodal data acquisition technology, real-time signal processing algorithm, flexible micro-nano dispensing technology and electromagnetic torque dynamic control method, and describes in detail the complete correction process from static modeling to dynamic quality correction and fine-tuning compensation. It has the advantages of strong real-time performance, high correction accuracy and high degree of intelligence.

[0008] A method and system for automatically correcting fan imbalance according to an embodiment of the present invention includes the following steps:

[0009] S1. When the fan is stationary, use a built-in multimodal sensing module to collect geometric parameters and material properties of the fan rotor to generate a multidimensional mechanical distribution model. The multimodal sensing module transmits the geometric parameters and material properties in a three-dimensional coordinate data format to a calculation module via a built-in data processing unit for generating a mass distribution function.

[0010] S2. Place the fan in a dynamic operating state and use the embedded inertial measurement unit and airflow disturbance sensor to collect multimodal signals including vibration signals, rotation trajectory, and airflow disturbance characteristics in real time. Combined with the multidimensional mechanical distribution model of the static state, the real-time operating imbalance of the fan is calculated.

[0011] S3. Based on the real-time unbalance, an unbalance response matrix is ​​constructed. This matrix decomposes the unbalance into primary and secondary components, and combines the dynamic operating conditions to predict the dynamic trend of the rotor mass deviation as the operating conditions change.

[0012] S4. Automatically identify restricted areas in the fan structure based on the imbalance response matrix, including ribs, weak points, or areas with high airflow resistance, and divide the refill range within the allowable area so that the refill operation does not affect the fan's structural strength and aerodynamic performance;

[0013] S5. Use flexible micro-nano dispensing technology to perform multi-point dispensing within the dispensing range. Rapidly solidify the colloid through non-contact UV excitation, and use fiber optic weight sensors to monitor and adjust dispensing quality in real time to match the requirements of the unbalanced response matrix. The dispensing device has interference avoidance capabilities, can sense obstacles and operating components in the environment, and flexibly select dispensing locations through dynamic path adjustment, while also recording dispensing locations and quality distribution.

[0014] S6. After completing the preliminary correction, collect the multimodal signals in the running state for the second time, detect the residual imbalance after correction, optimize the quality compensation effect through fluid-mechanical coupling analysis, and correct the quality compensation deviation caused by operation;

[0015] S7. If the residual unbalance exceeds the set threshold, the electromagnetic torque control module is activated to perform real-time fine-tuning compensation. The module adjusts the rotor operating state by generating dynamic electromagnetic torque until dynamic balance is achieved.

[0016] S8. After the calibration is completed, the key data of the calibration process, including the position of the refilled mass, the mass of the refilled mass, the imbalance before and after the calibration, the vibration parameters and the operating conditions are recorded to the host computer, and the dynamic balance model is updated in combination with the historical data. The dynamic balance model is used to predict the imbalance trend in future operation and automatically trigger the re-calibration operation.

[0017] Optionally, the S1 specifically includes:

[0018] S11. Using a built-in multimodal sensing module to collect geometric parameters of the fan rotor, the geometric parameters including external contour dimensions, thickness distribution, and cross-sectional radius variation, are collected using 3D scanning technology and laser measurement equipment;

[0019] S12. Collecting material properties of the fan rotor, including material density distribution, elastic modulus, and uniformity, using density analysis equipment and material testing equipment;

[0020] S13. Calculate the mass distribution function of the fan rotor based on the acquired geometric parameters and material properties:

[0021] ;

[0022] in, represents the mass distribution of the rotor in three-dimensional space, represents the density distribution of the material, Indicates the volume of the corresponding volume unit;

[0023] S14. Calculate the total mass and center of gravity position of the fan rotor, where the center of gravity position includes , , Coordinates in three directions, representing the equilibrium point of the rotor mass distribution;

[0024] S15. Combining the mass distribution function, the center of gravity position, and the initial mass deviation to generate a multi-dimensional mechanical distribution model of the fan.

[0025] Optionally, the S2 specifically includes:

[0026] S21, collecting three-dimensional vibration signals during the operation of the fan through an embedded inertial measurement unit, wherein the inertial measurement unit has The accelerometer range is , the sampling frequency is not less than The vibration signals collected include Acceleration components in three directions , , ;

[0027] S22. Synchronously collect the airflow characteristics when the fan is running using an airflow disturbance sensor, wherein the airflow disturbance sensor has a velocity field measurement range of , the pressure field measurement range is The airflow characteristics collected include airflow velocity field and pressure field distribution of

[0028] S23, perform signal processing on the collected three-dimensional vibration signal, use Fourier transform to convert the vibration signal from time domain to frequency domain, and extract the main vibration frequency component of the fan operation and analyze transient vibration characteristics through wavelet transform;

[0029] S24, combined with the processing results of Fourier transform and wavelet transform, and the characteristics of airflow disturbance and pressure field Together, we establish a vibration response model for the fan under dynamic operation, where the vibration response function Expressed as:

[0030] ;

[0031] in, is the total vibration amplitude, , , are the three-dimensional acceleration components;

[0032] S25, based on vibration response function and airflow disturbance characteristics , , combined with the multi-dimensional mechanical distribution model generated in the static state, the real-time imbalance value of the fan during operation is calculated through the functional relationship between the vibration response function and the airflow disturbance characteristics :

[0033] ;

[0034] S26. Calculate the distribution characteristics of the real-time unbalance, including the phase angle of the unbalance and amplitude :

[0035] ;

[0036] ;

[0037] in, Indicates the phase angle of the operating imbalance relative to the rotating axis, Indicates the real-time amplitude of the imbalance;

[0038] S27, the distribution characteristics of the real-time unbalance quantity, including the phase angle , amplitude and time-related characteristics, which are stored as dynamic unbalance characteristic data.

[0039] Optionally, the S3 specifically includes:

[0040] S31, the vibration response function collected in real time and real-time imbalance As input data, construct the imbalance response matrix The imbalance response matrix is ​​based on the distribution characteristics of vibration amplitude, phase angle and real-time imbalance:

[0041] ;

[0042] in, is the response change rate;

[0043] S32, based on the unbalanced response matrix , the principal component analysis algorithm is used to decompose it into principal components and secondary components, where the principal component matrix describes the main mass deviation and phase characteristics, and the secondary component matrix represents the transient residual characteristics of complex vibration;

[0044] S33. Combine the dynamic distribution characteristics of the main component and the secondary component to calculate the trend function of the imbalance of the fan rotor under different rotation conditions over time. :

[0045] ;

[0046] in, As the main component, For secondary amount;

[0047] S34. Combined trend function , predict the mass deviation distribution of the fan rotor at a specific time point in the future through dynamic time series analysis method ;

[0048] S35, distributing the predicted quality deviation and the unbalanced response matrix combining, generating a dynamic response model, the model including the distribution of imbalance components at future time points;

[0049] S36. The dynamic response model is stored as dynamic imbalance characteristic data, and the data is used as an input basis for quality correction and optimization correction strategies to optimize the dynamic adaptability and accuracy of the fan under operating conditions.

[0050] Optionally, the S4 specifically includes:

[0051] S41, based on the generated imbalance response matrix and trend function , calculate the required mass of the fan rotor :

[0052] ;

[0053] in, is the complement ratio factor, and are the imbalance amounts of the main component and the secondary component respectively;

[0054] S42. Using a dynamic identification algorithm based on topology optimization and combined with the mechanical model of fan operation, the replenishment restriction area is automatically identified through iterative optimization. The optimization goal is to minimize structural stress while satisfying mechanical performance constraints:

[0055] ;

[0056] in, represents the stress distribution of the fan rotor in three-dimensional space, Indicates the volume of the structure;

[0057] S43. After generating the preliminary restricted area through topology optimization, the adaptive optimization algorithm is combined with the dynamic response data of the fan as input to continuously update the boundaries of the mass-replenishing restricted area, including the reinforcement ribs, weak points, and areas with significant airflow disturbances;

[0058] S44. Based on the detected restricted area, use finite element analysis tools to simulate the impact of the mass replenishment operation on the mechanical characteristics and aerodynamic performance of the fan, and divide the allowable mass replenishment range so that the mass replenishment operation does not affect the structural strength and aerodynamic efficiency of the fan;

[0059] S45. Optimize the replenishment position based on the allowable replenishment range and the real-time calculated imbalance distribution And the distribution of supplements:

[0060] ;

[0061] in, It is the spatial scope of the tonic effect;

[0062] S46, generate a fan mass distribution model based on the optimization results, the model includes mass distribution position, mass distribution and the dynamic distribution characteristics of the complement range.

[0063] Optionally, the S5 specifically includes:

[0064] S51, based on the generated replenishment distribution model, dynamically determine the dispensing path and operation parameters within the replenishment range, the parameters include the replenishment position , improve quality and dispensing distribution characteristics to satisfy the unbalanced response matrix and real-time correction needs;

[0065] S52. Performing a refill operation on the dispensing path using flexible micro-nano dispensing technology. The dispensing device is driven by a servo motor and has interference avoidance capabilities. The sensor module detects the location of interference sources in real time, including the trajectory of rotating components and external obstacles. The dispensing path is dynamically optimized using a path adjustment algorithm to ensure that the refill operation avoids interference areas.

[0066] S53, in the dispensing process, real-time non-contact Encourage quick curing of dispensing, The curing equipment dynamically adjusts the light intensity, irradiation angle and irradiation time to adapt to the thickness of the colloid and the ambient temperature, so that the curing effect meets the calibration requirements;

[0067] S54, real-time monitoring of the quality of the repair through optical fiber weight sensor and theoretical demand and theoretical mass distribution For comparison, if , then the closed-loop feedback control system is triggered;

[0068] S55, combining real-time monitoring data and replenishment distribution model, dynamically optimize dispensing path, colloid flow and Excitation parameters, the adjusted operating parameters are used for quality supplementation and re-execution, so that the quality supplementation distribution meets the correction requirements of the unbalanced response matrix;

[0069] S56: After the replenishment is completed, the mass distribution after the replenishment is calculated based on the real-time monitoring data. and residual unbalance ,like Exceeding the preset threshold , then update the quality replenishment path and parameters, repeat the operations from S51 to S55 until the correction effect meets the requirements, and store all parameters of the quality replenishment operation and the final correction effect as correction result data.

[0070] Optionally, the S7 specifically includes:

[0071] S71, if the calculated residual unbalance Exceeding the set threshold , start the electromagnetic torque control module to generate dynamic electromagnetic torque in real time , fine-tune and compensate the operating status of the fan rotor;

[0072] S72, electromagnetic torque control module includes electromagnetic coil, inertial measurement unit, optical fiber weight sensor and control system. The electromagnetic coil dynamically adjusts the current intensity. and direction , the calculation formula of the generated dynamic electromagnetic torque is:

[0073] ;

[0074] in, is the electromagnetic torque constant, is the current intensity, is the phase angle of the imbalance;

[0075] S73, control system based on The control algorithm dynamically adjusts the regulation process. The control algorithm includes proportional control term, integral control term, and differential control term;

[0076] S74, based on the residual unbalance value monitored in real time and vibration response function , calculate the dynamic adjustment parameters , the dynamic electromagnetic torque Apply to the rotor so that the direction of the torque is consistent with the direction of the residual unbalance;

[0077] S75, real-time monitoring of the compensated vibration response through an inertial measurement unit and a fiber optic weight sensor and the new residual unbalance ,like , then update the control system parameters and repeat the compensation process from S72 to S74;

[0078] S76, after the compensation is completed, the dynamic electromagnetic torque parameter , vibration response and the final residual unbalance Stored as correction result data.

[0079] Optional modules include:

[0080] Multimodal sensing module: used to collect geometric parameters, material properties, vibration signals, airflow disturbance characteristics and rotation trajectory when the fan is in static and dynamic operation states, and provide data support for generating multidimensional mechanical distribution models and dynamic response models;

[0081] Data processing and modeling module: Based on the data collected by the multimodal sensing module, it constructs a multidimensional mechanical distribution model of the fan, calculates the real-time imbalance, generates an imbalance response matrix, decomposes the main and secondary components, and predicts the dynamic change trend of the rotor mass deviation;

[0082] The refill operation module performs flexible micro-nano dispensing operations based on the refill distribution model generated by the data processing and modeling module. The dispensing device has dynamic obstacle avoidance capabilities, can sense interference factors during fan operation in real time and adjust the refill path. The servo motor drives the dispensing head to complete flexible refill operations, and the fiber optic weight sensor monitors the refill quality in real time.

[0083] Electromagnetic torque control module: It is used to make real-time fine-tuning compensation for the residual unbalance after the quality supplement operation is completed, and to adjust the rotor operation state by dynamically generating electromagnetic torque. The control algorithm adjusts the current intensity and direction to achieve dynamic balance;

[0084] Data storage and optimization module: used to store key data on quality replenishment operations, vibration response, residual imbalance, and electromagnetic control processes, and generate long-term dynamic balance optimization models based on historical data to predict imbalance trends in future operations and optimize correction strategies.

[0085] The beneficial effects of the present invention are:

[0086] Through the multimodal sensing module, the present invention can collect geometric parameters and material properties when the fan is stationary, and obtain data such as vibration signals, airflow disturbance characteristics and rotation trajectory in real time during dynamic operation, providing accurate input data for constructing a multidimensional mechanical distribution model and an unbalanced response matrix. This all-round, multi-dimensional data acquisition method makes up for the incomplete data defects in traditional correction technology and ensures the accuracy and adaptability of the correction strategy.

[0087] The present invention can effectively decompose the imbalance generated during fan operation, split it into primary and secondary components, and accurately grasp the changing pattern of the imbalance through dynamic trend prediction. This decomposition method not only improves the efficiency of processing the imbalance, but also significantly enhances the targeted correction, so that the correction operation can be more accurately concentrated in key areas, avoiding large-scale ineffective adjustments in traditional correction methods.

[0088] This invention utilizes flexible micro-nano dispensing technology and real-time UV curing equipment to dynamically adjust the dispensing path, dispensing flow rate, and curing parameters, ensuring uniform distribution of the dispensing material within the dispensing area. Fiber optic weight sensors also dynamically monitor the actual dispensing quality. This technology achieves highly accurate and automated dispensing operations, reducing human error during the dispensing process and effectively addressing calibration failures caused by uneven dispensing or insufficient curing.

[0089] This invention innovatively incorporates an interference avoidance feature, enabling the recharge device to perceive obstacles and the position of operating components in the surrounding environment in real time. Using a dynamic path adjustment algorithm, it flexibly selects the recharge path and location, ensuring efficient and safe recharge operations. Compared to traditional methods, this feature significantly improves the recharge operation's adaptability in complex environments and further enhances the accuracy of the calibration process.

[0090] The present invention uses the electromagnetic torque control module to perform real-time fine-tuning compensation, which combines the dynamic torque generation formula and The control algorithm dynamically adjusts the current intensity and direction based on real-time monitoring data, generating a dynamic electromagnetic torque that precisely matches the direction and magnitude of the residual imbalance. Compared to traditional static compensation methods, this module demonstrates greater adaptability and efficiency in handling residual imbalance under complex operating conditions, effectively avoiding repeated corrections.

[0091] The present invention uses a data storage and optimization module to store key data in the correction process, including the re-quality position, re-quality quality, residual imbalance and vibration response parameters, as correction result data, and constructs a long-term dynamic balance optimization model. This module not only realizes the long-term preservation of correction data, but also can perform automatic analysis based on historical data, optimize the re-quality path and correction strategy, and has adaptive correction and prediction functions, which greatly improves the intelligence level of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0093] Figure 1This is a flow chart of a method and system for automatically correcting fan imbalance proposed by the present invention;

[0094] Figure 2 Schematic diagram of the construction of a multi-dimensional mechanical distribution model and an imbalance response matrix generated based on real-time signal processing and modeling;

[0095] Figure 3 This is a schematic diagram of the composition of the electromagnetic torque control module and the generation and fine-tuning compensation of dynamic torque. DETAILED DESCRIPTION

[0096] The present invention will now be described in further detail with reference to the accompanying drawings, which are simplified schematic diagrams that illustrate the basic structure of the present invention in a schematic manner.

[0097] refer to Figure 1-3 A method and system for automatically correcting fan imbalance, comprising the following steps:

[0098] S1. When the fan is stationary, use a built-in multimodal sensing module to collect geometric parameters and material properties of the fan rotor to generate a multidimensional mechanical distribution model. The multimodal sensing module transmits the geometric parameters and material properties in a three-dimensional coordinate data format to a calculation module via a built-in data processing unit for generating a mass distribution function.

[0099] S2. Place the fan in a dynamic operating state and use the embedded inertial measurement unit and airflow disturbance sensor to collect multimodal signals including vibration signals, rotation trajectory, and airflow disturbance characteristics in real time. Combined with the multidimensional mechanical distribution model of the static state, the real-time operating imbalance of the fan is calculated.

[0100] S3. Based on the real-time unbalance, an unbalance response matrix is ​​constructed. This matrix decomposes the unbalance into primary and secondary components, and combines the dynamic operating conditions to predict the dynamic trend of the rotor mass deviation as the operating conditions change.

[0101] S4. Automatically identify restricted areas in the fan structure based on the imbalance response matrix, including ribs, weak points, or areas with high airflow resistance, and divide the refill range within the allowable area so that the refill operation does not affect the fan's structural strength and aerodynamic performance;

[0102] S5. Use flexible micro-nano dispensing technology to perform multi-point dispensing within the dispensing range. Rapidly solidify the colloid through non-contact UV excitation, and use fiber optic weight sensors to monitor and adjust dispensing quality in real time to match the requirements of the unbalanced response matrix. The dispensing device has interference avoidance capabilities, can sense obstacles and operating components in the environment, and flexibly select dispensing locations through dynamic path adjustment, while also recording dispensing locations and quality distribution.

[0103] S6. After completing the preliminary correction, collect the multimodal signals in the running state for the second time, detect the residual imbalance after correction, optimize the quality compensation effect through fluid-mechanical coupling analysis, and correct the quality compensation deviation caused by operation;

[0104] S7. If the residual unbalance exceeds the set threshold, the electromagnetic torque control module is activated to perform real-time fine-tuning compensation. The module adjusts the rotor operating state by generating dynamic electromagnetic torque until dynamic balance is achieved.

[0105] S8. After the calibration is completed, the key data of the calibration process, including the position of the refilled mass, the mass of the refilled mass, the imbalance before and after the calibration, the vibration parameters and the operating conditions are recorded to the host computer, and the dynamic balance model is updated in combination with the historical data. The dynamic balance model is used to predict the imbalance trend in future operation and automatically trigger the re-calibration operation.

[0106] In this embodiment, S1 specifically includes:

[0107] S11. Using a built-in multimodal sensing module to collect geometric parameters of the fan rotor, the geometric parameters including external contour dimensions, thickness distribution, and cross-sectional radius variation, are collected using 3D scanning technology and laser measurement equipment;

[0108] S12. Collecting material properties of the fan rotor, including material density distribution, elastic modulus, and uniformity, using density analysis equipment and material testing equipment;

[0109] S13. Calculate the mass distribution function of the fan rotor based on the acquired geometric parameters and material properties:

[0110] ;

[0111] in, represents the mass distribution of the rotor in three-dimensional space, represents the density distribution of the material, Indicates the volume of the corresponding volume unit;

[0112] S14. Calculate the total mass and center of gravity position of the fan rotor, where the center of gravity position includes , , Coordinates in three directions, representing the equilibrium point of the rotor mass distribution;

[0113] S15. Combining the mass distribution function, the center of gravity position, and the initial mass deviation to generate a multi-dimensional mechanical distribution model of the fan.

[0114] In this embodiment, S2 specifically includes:

[0115] S21, collecting three-dimensional vibration signals during the operation of the fan through an embedded inertial measurement unit, wherein the inertial measurement unit has The accelerometer range is , the sampling frequency is not less than The vibration signals collected include Acceleration components in three directions , , ;

[0116] S22. Synchronously collect the airflow characteristics when the fan is running using an airflow disturbance sensor, wherein the airflow disturbance sensor has a velocity field measurement range of , the pressure field measurement range is The airflow characteristics collected include airflow velocity field and pressure field distribution of

[0117] S23, perform signal processing on the collected three-dimensional vibration signal, use Fourier transform to convert the vibration signal from time domain to frequency domain, and extract the main vibration frequency component of the fan operation and analyze transient vibration characteristics through wavelet transform;

[0118] S24, combined with the processing results of Fourier transform and wavelet transform, and the characteristics of airflow disturbance and pressure field Together, we establish a vibration response model for the fan under dynamic operation, where the vibration response function Expressed as:

[0119] ;

[0120] in, is the total vibration amplitude, , , are the three-dimensional acceleration components;

[0121] S25, based on vibration response function and airflow disturbance characteristics , , combined with the multi-dimensional mechanical distribution model generated in the static state, the real-time imbalance value of the fan during operation is calculated through the functional relationship between the vibration response function and the airflow disturbance characteristics :

[0122] ;

[0123] S26. Calculate the distribution characteristics of the real-time unbalance, including the phase angle of the unbalance and amplitude :

[0124] ;

[0125] ;

[0126] in, Indicates the phase angle of the operating imbalance relative to the rotating axis, Indicates the real-time amplitude of the imbalance;

[0127] S27, the distribution characteristics of the real-time unbalance quantity, including the phase angle , amplitude and time-related characteristics, which are stored as dynamic unbalance characteristic data.

[0128] In this embodiment, S3 specifically includes:

[0129] S31, the vibration response function collected in real time and real-time imbalance As input data, construct the imbalance response matrix The imbalance response matrix is ​​based on the distribution characteristics of vibration amplitude, phase angle and real-time imbalance:

[0130] ;

[0131] in, is the response change rate;

[0132] S32, based on the unbalanced response matrix , the principal component analysis algorithm is used to decompose it into principal components and secondary components, where the principal component matrix describes the main mass deviation and phase characteristics, and the secondary component matrix represents the transient residual characteristics of complex vibration;

[0133] S33. Combine the dynamic distribution characteristics of the main component and the secondary component to calculate the trend function of the imbalance of the fan rotor under different rotation conditions over time. :

[0134] ;

[0135] in, As the main component, For secondary amount;

[0136] S34. Combined trend function , predict the mass deviation distribution of the fan rotor at a specific time point in the future through dynamic time series analysis method ;

[0137] S35, distributing the predicted quality deviation and the unbalanced response matrix combining, generating a dynamic response model, the model including the distribution of imbalance components at future time points;

[0138] S36. The dynamic response model is stored as dynamic imbalance characteristic data, and the data is used as an input basis for quality correction and optimization correction strategies to optimize the dynamic adaptability and accuracy of the fan under operating conditions.

[0139] In this embodiment, the S4 specifically includes:

[0140] S41, based on the generated imbalance response matrix and trend function , calculate the required mass of the fan rotor :

[0141] ;

[0142] in, is the complement ratio factor, and are the imbalance amounts of the main component and the secondary component respectively;

[0143] S42. Using a dynamic identification algorithm based on topology optimization and combined with the mechanical model of fan operation, the replenishment restriction area is automatically identified through iterative optimization. The optimization goal is to minimize structural stress while satisfying mechanical performance constraints:

[0144] ;

[0145] in, represents the stress distribution of the fan rotor in three-dimensional space, Indicates the volume of the structure;

[0146] S43. After generating the preliminary restricted area through topology optimization, the adaptive optimization algorithm is combined with the dynamic response data of the fan as input to continuously update the boundaries of the mass-replenishing restricted area, including the reinforcement ribs, weak points, and areas with significant airflow disturbances;

[0147] S44. Based on the detected restricted area, use finite element analysis tools to simulate the impact of the mass replenishment operation on the mechanical characteristics and aerodynamic performance of the fan, and divide the allowable mass replenishment range so that the mass replenishment operation does not affect the structural strength and aerodynamic efficiency of the fan;

[0148] S45. Optimize the replenishment position based on the allowable replenishment range and the real-time calculated imbalance distribution And the distribution of supplements:

[0149] ;

[0150] in, It is the spatial scope of the tonic effect;

[0151] S46, generate a fan mass distribution model based on the optimization results, the model includes mass distribution position, mass distribution and the dynamic distribution characteristics of the complement range.

[0152] In this embodiment, the S5 specifically includes:

[0153] S51, based on the generated replenishment distribution model, dynamically determine the dispensing path and operation parameters within the replenishment range, the parameters include the replenishment position , improve quality and dispensing distribution characteristics to satisfy the unbalanced response matrix and real-time correction needs;

[0154] S52. Performing a refill operation on the dispensing path using flexible micro-nano dispensing technology. The dispensing device is driven by a servo motor and has interference avoidance capabilities. The sensor module detects the location of interference sources in real time, including the trajectory of rotating components and external obstacles. The dispensing path is dynamically optimized using a path adjustment algorithm to ensure that the refill operation avoids interference areas.

[0155] S53, in the dispensing process, real-time non-contact Encourage quick curing of dispensing, The curing equipment dynamically adjusts the light intensity, irradiation angle and irradiation time to adapt to the thickness of the colloid and the ambient temperature, so that the curing effect meets the calibration requirements;

[0156] S54, real-time monitoring of the quality of the repair through optical fiber weight sensor and theoretical demand and theoretical mass distribution For comparison, if , then the closed-loop feedback control system is triggered;

[0157] S55, combining real-time monitoring data and replenishment distribution model, dynamically optimize dispensing path, colloid flow and Excitation parameters, the adjusted operating parameters are used for quality supplementation and re-execution, so that the quality supplementation distribution meets the correction requirements of the unbalanced response matrix;

[0158] S56: After the replenishment is completed, the mass distribution after the replenishment is calculated based on the real-time monitoring data. and residual unbalance ,like Exceeding the preset threshold , then update the quality replenishment path and parameters, repeat the operations from S51 to S55 until the correction effect meets the requirements, and store all parameters of the quality replenishment operation and the final correction effect as correction result data.

[0159] In this embodiment, the S7 specifically includes:

[0160] S71, if the calculated residual unbalance Exceeding the set threshold , start the electromagnetic torque control module to generate dynamic electromagnetic torque in real time , fine-tune and compensate the operating status of the fan rotor;

[0161] S72, electromagnetic torque control module includes electromagnetic coil, inertial measurement unit, optical fiber weight sensor and control system. The electromagnetic coil dynamically adjusts the current intensity. and direction , the calculation formula of the generated dynamic electromagnetic torque is:

[0162] ;

[0163] in, is the electromagnetic torque constant, is the current intensity, is the phase angle of the imbalance;

[0164] S73, control system based on The control algorithm dynamically adjusts the regulation process. The control algorithm includes proportional control term, integral control term, and differential control term;

[0165] S74, based on the residual unbalance value monitored in real time and vibration response function , calculate the dynamic adjustment parameters , the dynamic electromagnetic torque Apply to the rotor so that the direction of the torque is consistent with the direction of the residual unbalance;

[0166] S75, real-time monitoring of the compensated vibration response through an inertial measurement unit and a fiber optic weight sensor and the new residual unbalance ,like , then update the control system parameters and repeat the compensation process from S72 to S74;

[0167] S76, after the compensation is completed, the dynamic electromagnetic torque parameter , vibration response and the final residual unbalance Stored as correction result data.

[0168] In this embodiment, the following modules are included:

[0169] Multimodal sensing module: used to collect geometric parameters, material properties, vibration signals, airflow disturbance characteristics and rotation trajectory when the fan is in static and dynamic operation states, and provide data support for generating multidimensional mechanical distribution models and dynamic response models;

[0170] Data processing and modeling module: Based on the data collected by the multimodal sensing module, it constructs a multidimensional mechanical distribution model of the fan, calculates the real-time imbalance, generates an imbalance response matrix, decomposes the main and secondary components, and predicts the dynamic change trend of the rotor mass deviation;

[0171] The refill operation module performs flexible micro-nano dispensing operations based on the refill distribution model generated by the data processing and modeling module. The dispensing device has dynamic obstacle avoidance capabilities, can sense interference factors during fan operation in real time and adjust the refill path. The servo motor drives the dispensing head to complete flexible refill operations, and the fiber optic weight sensor monitors the refill quality in real time.

[0172] Electromagnetic torque control module: It is used to make real-time fine-tuning compensation for the residual unbalance after the quality supplement operation is completed, and to adjust the rotor operation state by dynamically generating electromagnetic torque. The control algorithm adjusts the current intensity and direction to achieve dynamic balance;

[0173] Data storage and optimization module: used to store key data on quality replenishment operations, vibration response, residual imbalance, and electromagnetic control processes, and generate long-term dynamic balance optimization models based on historical data to predict imbalance trends in future operations and optimize correction strategies.

[0174] Example 1:

[0175] In order to verify the feasibility of the present invention in implementation, the present invention is applied to industrial production. Large-scale ventilation equipment often faces serious vibration and noise problems due to its long-term operation and complex working conditions. The main fan of a certain steel plant has been used for many years, and the imbalance of the rotor causes high-frequency vibration during operation, which not only threatens the life of the equipment, but also causes excessive noise in the working environment, directly affecting production efficiency and workers' work comfort. The traditional static correction method can no longer meet the dynamic operation requirements of the fan, and the semi-automatic dynamic correction method with manual participation has not been able to completely solve the problem due to its complex operation, low efficiency and unstable correction effect. In response to this situation, an automatic quality correction system and method for fan imbalance proposed in the present invention is used to perform real-time dynamic correction on the fan.

[0176] During the calibration process, static data of the fan's rotor was collected through a multimodal sensing module to obtain its geometric parameters and material properties, including the rotor's external contour dimensions, thickness distribution, and cross-sectional radius changes. At the same time, the material's density distribution, elastic modulus, and uniformity characteristics were measured using density analysis equipment and material testing devices. Based on these data, a multidimensional mechanical distribution model of the rotor was constructed, and the static characteristics and initial mass deviation of the rotor's mass distribution were calculated.

[0177] While the fan is running, the system activates dynamic data acquisition, capturing vibration signals and airflow disturbance characteristics in real time through an embedded inertial measurement unit and airflow disturbance sensor. The collected vibration signals include acceleration components along the x, y, and z directions, while the airflow disturbance characteristics include velocity and pressure field distribution data. Combining this real-time data with a static mechanical model, the system generates a dynamic imbalance response matrix for the rotor, decomposing the imbalance into primary and secondary components. This allows for the prediction of rotor mass deviation trends under different operating conditions.

[0178] According to the system calculation results, flexible micro-nano dispensing technology was used to perform multi-point filling operations within the filling range allowed by the rotor. The dispensing path and filling quality were dynamically determined by the real-time generated filling distribution model. The dispensing head completed the operation under the precise drive of the servo motor. At the same time, the UV curing equipment quickly cured the filling material after dispensing, with a curing time of 0.8 seconds each time, ensuring the stability and uniformity of the colloid. During the filling process, the fiber optic weight sensor monitored the filling quality in real time and found that the actual quality of the initial filling deviated from the theoretical demand by 2.1%. The system automatically adjusted the dispensing flow and path. In the corrected filling operation, the deviation was controlled within 0.2%, significantly improving the correction accuracy. The dispensing device has an interference avoidance function. By real-time sensing the rotor rotation trajectory and possible obstacles, combined with the dynamic path adjustment algorithm to optimize the dispensing path, the filling operation avoids the interference area, ensuring the efficiency and safety of the filling process.

[0179] After the replenishment operation was completed, the system performed a second vibration test on the fan. The test results showed that there was still a slight deviation in the residual imbalance, which was mainly reflected in the transient vibration response during dynamic operation. The electromagnetic torque control module was started to fine-tune and compensate for the residual imbalance by dynamically generating electromagnetic torque. The module adjusted the current intensity and direction of the electromagnetic coil in real time based on the vibration signal and the phase angle of the imbalance, and completed the dynamic balance adjustment within 2 seconds, reducing the final residual imbalance to within 0.02%.

[0180] After the calibration is complete, all calibration data, including the static mass distribution, imbalance response matrix, real-time vibration signals, mass replenishment operating parameters, and residual imbalance, are stored in the data storage module. Combined with historical data, a dynamic balance optimization model is generated. Based on data analysis, the system predicts that the ventilator will maintain a stable operation for the next two months. If the calibration trigger conditions are met, the system will automatically initiate the mass replenishment calibration process without manual intervention.

[0181] After calibration, the fan's vibration amplitude dropped from 3.2 mm / s before calibration to 0.3 mm / s, and its noise level decreased from 85 decibels to 68 decibels, meeting national environmental noise standards. The calibration process took approximately 15 minutes, significantly improving calibration efficiency compared to the three hours required by traditional calibration methods. Furthermore, through a combination of automatic re-calibration and fine-tuning compensation, calibration accuracy was increased by more than 20 times compared to traditional methods. The calibrated fan now operates stably, eliminating the need for further downtime for adjustments, significantly extending the equipment's service life.

[0182] Table 1 Fan imbalance correction process related data table

[0183]

[0184] As can be seen from the table, the overall calibration process takes about 20 minutes, of which the quality replenishment operation phase takes the longest, 6 minutes. The remaining phases, such as static and dynamic data acquisition, electromagnetic torque fine-tuning, etc., are all controlled within 1 to 5 minutes. Compared with the traditional method that takes 3 hours, the calibration efficiency is significantly improved. The static geometric parameters and material property data are collected through the multimodal sensing module to construct the initial mechanical distribution model. The static mass deviation is controlled within 0.8%. The dynamic data acquisition phase captures the vibration signals and airflow disturbance characteristics of the fan in real time. The vibration amplitude is reduced from the initial 3.2 The significant reduction in the speed of the fan during operation (mm / s) demonstrates that the dynamic response model accurately reflects the imbalance characteristics during operation. During the reconditioning phase, flexible micro-nano dispensing technology was used. The initial reconditioning deviation was 2.1%, which was corrected to 0.2% through real-time monitoring and adjustment by the fiber optic weight sensor, demonstrating the high precision and dynamic adaptability of the correction operation. After the reconditioning operation, the system used the electromagnetic torque control module to fine-tune the residual imbalance in real time. The PID control algorithm was used to adjust the current intensity and direction, ultimately reducing the residual imbalance to 0.02%, effectively resolving subtle imbalance issues under complex operating conditions. The fan's vibration amplitude was reduced to 0.3 mm / s, and the noise level was reduced from 85 decibels to 68 decibels, meeting national environmental noise standards. This significantly improved the equipment's operational stability and extended its service life. The data storage module records all key parameters during the correction process and, combined with historical data, generates a dynamic balance optimization model to support subsequent correction predictions and automated optimization.

[0185] In summary, this invention achieves significant breakthroughs in real-time performance, correction accuracy, and intelligent operation. It can complete the entire correction process, from data acquisition to quality control and fine-tuning compensation, in real time. This effectively reduces vibration and noise during fan operation, extending the service life of the equipment, while significantly improving its operational stability and reliability. This invention is suitable for applications requiring high-precision dynamic balancing, such as industrial ventilation equipment, household appliances, and aviation turbomachinery, and possesses broad application prospects and technological dissemination value.

[0186] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A method for automatically correcting fan imbalance, characterized in that: The steps include: S1. When the fan is stationary, the built-in multimodal sensing module is used to collect geometric parameters and material properties of the fan rotor to generate a multidimensional mechanical distribution model. The multimodal sensing module transmits the geometric parameters and material properties to the calculation module in a three-dimensional coordinate data format through a built-in data processing unit to generate a mass distribution function. S2. Put the fan into a dynamic operation state, collect multimodal signals including vibration signals, rotation trajectories and airflow disturbance characteristics in real time through an embedded inertial measurement unit and an airflow disturbance sensor, and calculate the real-time operation imbalance of the fan by combining a multidimensional mechanical distribution model of a static state; S3. Based on the real-time unbalanced quantity, an unbalanced response matrix is ​​constructed. The unbalanced quantity is decomposed into a primary component and a secondary component, and the dynamic trend of the rotor mass deviation as the working condition changes is predicted in combination with the dynamic working condition. S4. According to the unbalanced response matrix, the restricted areas in the fan structure are automatically identified, including reinforcing ribs, weak parts or areas with large airflow resistance, and the quality replenishment range is divided within the allowed area so that the quality replenishment operation will not affect the structural strength and aerodynamic performance of the fan; S5. Use flexible micro-nano dispensing technology to perform multi-point filling operations within the filling range, use non-contact UV excitation to quickly cure the dispensing in real time, and dynamically monitor the filling quality through optical fiber weight sensors, adjust the filling distribution to match the requirements of the unbalanced response matrix, and record the filling position and weight distribution; S6. After completing the preliminary correction, collect the multi-modal signals in the running state for the second time, detect the residual imbalance after correction, optimize the quality supplement effect through fluid-mechanical coupling analysis, and correct the quality supplement deviation caused by operation; S7. If the residual unbalance exceeds the set threshold, the electromagnetic torque control module is started to perform real-time fine-tuning compensation. The module adjusts the rotor operation state by generating dynamic electromagnetic torque until dynamic balance is achieved; S8. After the calibration is completed, the key data of the calibration process, including the position of the quality supplement, the quality of the quality supplement, the imbalance before and after the calibration, the vibration parameters and the operating conditions are recorded to the host computer, and the dynamic balance model is updated in combination with the historical data. The dynamic balance model is used to predict the imbalance trend in the future operation and automatically trigger the re-calibration operation.

2. The method for automatically correcting fan imbalance according to claim 1, characterized in that: The S1 specifically includes: S11, using a built-in multi-modal sensor module to collect geometric parameters of the fan rotor, wherein the geometric parameters include external contour dimensions, thickness distribution, and radius variation of a cross section, and the collection is achieved through three-dimensional scanning technology and laser measurement equipment; S12, collecting material properties of the fan rotor, wherein the material properties include material density distribution, elastic modulus and uniformity properties, and are obtained by density analysis equipment and material testing equipment; S13. Based on the collected geometric parameters and material properties, the mass distribution function of the fan rotor is calculated: ； in, represents the mass distribution of the rotor in three-dimensional space, represents the density distribution of the material, Indicates the volume of the corresponding volume unit; S14, calculate the total mass and center of gravity position of the fan rotor, where the center of gravity position includes , , Coordinates in three directions, representing the equilibrium point of the rotor mass distribution; S15, combining the mass distribution function, the center of gravity position and the initial mass deviation to generate a multi-dimensional mechanical distribution model of the fan.

3. The method for automatically correcting fan imbalance according to claim 1, characterized in that: The S2 specifically includes: S21, collecting three-dimensional vibration signals during the operation of the fan through an embedded inertial measurement unit, wherein the inertial measurement unit has The accelerometer range is 0.001g, the sampling frequency is not less than The collected vibration signal includes acceleration components along the x, y, and z directions. , , ; S22, using an airflow disturbance sensor to synchronously collect airflow characteristics when the fan is running, wherein the airflow disturbance sensor has a velocity field measurement range of , the pressure field measurement range is The airflow characteristics collected include airflow velocity field and pressure field Distribution of S23, perform signal processing on the collected three-dimensional vibration signal, use Fourier transform to convert the vibration signal from time domain to frequency domain, and extract the main vibration frequency component of the fan operation and analyze transient vibration characteristics by wavelet transform; S24, combined with the processing results of Fourier transform and wavelet transform, and the characteristics of airflow disturbance and pressure field Together, a vibration response model of the fan under dynamic operation is established, where the vibration response function It is expressed as: ； in, is the total vibration amplitude, , , are the three-dimensional acceleration components; S25, based on vibration response function and airflow disturbance characteristics , , combined with the multi-dimensional mechanical distribution model generated in the static state, the real-time imbalance of the fan during operation is calculated through the functional relationship between the vibration response function and the airflow disturbance characteristics. : ； S26. Calculate the distribution characteristics of the real-time unbalance, including the phase angle of the unbalance and amplitude : ； ； in, It indicates the phase angle of the operating unbalance relative to the rotating axis. Indicates the real-time amplitude of the unbalance; S27, the distribution characteristics of the real-time unbalance quantity, including the phase angle , Amplitude and time-related characteristics are stored as dynamic unbalance characteristic data.

4. The method for automatically correcting fan imbalance according to claim 1, characterized in that: The S3 specifically includes: S31, the vibration response function collected in real time and real-time imbalance As input data, construct the unbalanced response matrix , the unbalance response matrix is ​​based on the distribution characteristics of vibration amplitude, phase angle and real-time unbalance quantity: ； in, is the response change rate; S32, based on the unbalanced response matrix , the principal component analysis algorithm is used to decompose it into principal components and secondary components, where the principal component matrix describes the main mass deviation and phase characteristics, and the secondary component matrix represents the transient residual characteristics of complex vibrations; S33. Combine the dynamic distribution characteristics of the main component and the secondary component to calculate the trend function of the fan rotor's imbalance under different rotation conditions over time. : ； in, As the main component, For secondary weight; S34. Combined trend function , predict the mass deviation distribution of the fan rotor at a specific time point in the future through dynamic time series analysis method ; S35, distributing the predicted quality deviation and the unbalanced response matrix combining, generating a dynamic response model, the model including the distribution of imbalance components at future time points; S36. The dynamic response model is stored as dynamic unbalance characteristic data, and is used as an input basis for quality correction and optimization correction strategies to optimize the dynamic adaptability and accuracy of the fan under operating conditions.

5. The method for automatically correcting fan imbalance according to claim 1, characterized in that: The S4 specifically includes: S41. Calculate the required amount of fan rotor mass : ； in, is the complementary ratio factor, and are the imbalance of the main component and the secondary component respectively; S42. Using the dynamic identification algorithm based on topology optimization and the mechanical model of the fan operation, the quality restriction area is automatically identified through iterative optimization. The optimization goal is to minimize the structural stress while satisfying the mechanical performance constraints: ； in, represents the stress distribution of the fan rotor in three-dimensional space, Indicates the volume of the structure; S43, after generating the preliminary restricted area through topology optimization, combining with the adaptive optimization algorithm, taking the dynamic response data of the fan as input, continuously updating the boundary of the quality-replenishing restricted area, including the reinforcement ribs, weak parts and areas with significant airflow disturbance; S44. Based on the detected restricted area, the influence of the mass replenishment operation on the mechanical characteristics and aerodynamic performance of the fan is simulated by using a finite element analysis tool, and the permissible mass replenishment range is divided so that the mass replenishment operation will not affect the structural strength and aerodynamic efficiency of the fan; S45. Optimize the replenishment position based on the allowable replenishment range and the real-time calculated imbalance distribution And the distribution of tonic: ； in, It is the spatial scope of the tonic effect; S46, generating a fan quality supplement distribution model based on the optimization results, the model including quality supplement position, quality supplement and dynamic distribution characteristics of the complementary quality range.

6. The method for automatically correcting fan imbalance according to claim 1, characterized in that: The S5 specifically includes: S51, based on the generated replenishment distribution model, dynamically determine the dispensing path and operation parameters within the replenishment range, the parameters include the replenishment position , improve quality and dispensing distribution characteristics to meet the unbalanced response matrix and real-time correction requirements; S52, using flexible micro-nano dispensing technology to perform a mass replenishment operation on the dispensing path, wherein the dispensing device is driven by a servo motor, and the position and flow rate of the dispensing head are adjusted in real time to make the colloid evenly distributed within the mass replenishment range and match the mass replenishment distribution model; S53, in the dispensing process, real-time non-contact Stimulate the quick curing of glue dispensed. The curing equipment dynamically adjusts the light intensity, irradiation angle and irradiation time to adapt to the colloid thickness and ambient temperature, so that the curing effect meets the calibration requirements; S54, real-time monitoring of the quality of the repair through the optical fiber weight sensor , and the theoretical demand and theoretical mass distribution For comparison, if , then the closed-loop feedback control system is triggered; S55, combining real-time monitoring data and replenishment distribution model, dynamically optimize dispensing path, colloid flow and Excitation parameters, the adjusted operating parameters are used for quality supplementation and re-execution, so that the quality supplementation distribution meets the correction requirements of the unbalanced response matrix; S56: After the quality supplement is completed, the quality distribution after the quality supplement is calculated based on the real-time monitoring data and residual unbalance ,like Exceeding the preset threshold , then update the quality-replenishing path and parameters, repeat the operations from S51 to S55 until the correction effect meets the requirements, and store all parameters of the quality-replenishing operation and the final correction effect as correction result data.

7. The method for automatically correcting fan imbalance according to claim 1, characterized in that: The S7 specifically includes: S71, if the calculated residual unbalance Exceeding the set threshold , start the electromagnetic torque control module to generate dynamic electromagnetic torque in real time , fine-tune and compensate the operating status of the fan rotor; S72, electromagnetic torque control module includes electromagnetic coil, inertial measurement unit, optical fiber weight sensor and control system. The electromagnetic coil dynamically adjusts the current intensity. and direction , the calculation formula of the generated dynamic electromagnetic torque is: ； in, is the electromagnetic torque constant, is the current intensity, is the phase angle of the unbalanced quantity; S73, control system based on The control algorithm dynamically adjusts the regulation process. The control algorithm includes proportional control term, integral control term and differential control term; S74, based on the residual unbalance value monitored in real time and the vibration response function , calculate the dynamic adjustment parameters , the dynamic electromagnetic torque Apply to the rotor so that the direction of the torque is consistent with the direction of the residual unbalance; S75, real-time monitoring of compensated vibration response through inertial measurement unit and fiber optic weight sensor and the new residual unbalance ,like , then update the control system parameters and repeat the compensation process from S72 to S74; S76, after the compensation is completed, the dynamic electromagnetic torque parameter , vibration response and the final residual unbalance Stored as correction result data.

8. An automatic quality correction system for fan imbalance, characterized in that: Includes the following modules: Multimodal sensing module: used to collect geometric parameters, material properties, vibration signals, airflow disturbance characteristics and rotation trajectory when the fan is in static and dynamic operation states, and provide data support for generating multidimensional mechanical distribution models and dynamic response models; Data processing and modeling module: Based on the data collected by the multimodal sensor module, a multidimensional mechanical distribution model of the fan is constructed to calculate the real-time imbalance, generate an imbalance response matrix, decompose the main component and the secondary component, and predict the dynamic change trend of the rotor mass deviation; Quality replenishment operation module: According to the quality replenishment distribution model generated by the data processing and modeling module, the flexible micro-nano dispensing operation is performed, and the dispensing head is driven by the servo motor to adjust the path and parameters in real time. The curing equipment completes dynamic replenishment and monitors the replenishment quality in real time through the optical fiber weight sensor; Electromagnetic torque control module: It is used to make real-time fine-tuning compensation for the residual unbalance after the quality supplement operation is completed, and adjust the rotor operation state by dynamically generating electromagnetic torque. The control algorithm adjusts the current intensity and direction to achieve dynamic balance; Data storage and optimization module: used to store key data of quality replenishment operation, vibration response, residual imbalance, and electromagnetic control process, and generate a long-term dynamic balance optimization model based on historical data to predict the imbalance trend in future operation and optimize the correction strategy.

Images