A balancing detection device and detection method for fan manufacturing

Abstract

The present invention relates to the technical field of equipment anomaly detection, and proposes a balancing detection device and detection method for fan manufacturing, including: determining a corrected vibration balance characteristic value based on the vibration data and centrifugal force vector of each fan blade at each moment in the balancing detection process of the fan; determining the balance credibility based on the stability of the change of the local corrected vibration balance characteristic value, the rotation speed at each moment and the vibration data of each fan blade; determining the vibration weight at each moment in combination with the corrected vibration balance characteristic value and the balance credibility, and then determining the vibration abnormality evaluation value at each moment; determining the balance state of the fan based on the vibration abnormality evaluation value. The above technical scheme solves the problem of low accuracy of fan balance detection in the prior art, and is mainly applicable to the field of fan balance detection.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment abnormality detection, and in particular to a balance detection device and a detection method for fan manufacturing. Background Art

[0002] Fan balance refers to the centrifugal torque of each part of the fan canceling each other out during its rotation, so that the fan bearing and bracket are not subjected to additional eccentric force. A fan is usually composed of blades, impellers, shafts, and bearings. When any part of them deviates, the fan will be unbalanced, and an unbalanced fan will produce severe vibration and noise, which not only affects comfort, but also damages surrounding equipment, thereby accelerating the wear of components such as fan bearings and motors, and shortening the service life of the fan. The centrifugal force of a severely unbalanced fan rotating at high speed can cause excessive bending stress in the blades, resulting in blade breakage, causing damage to personnel or equipment, and safety accidents. Therefore, it is crucial to perform a balance test on the fan.

[0003] At present, the balance characteristics of the fan are often obtained by using the similarity of the vibration of all blades in the same electric fan, and then the abnormality of the fan balance characteristics is analyzed by the z-score (standardization method) abnormality detection algorithm to obtain the balance detection result of the fan. However, when using the z-score method to detect abnormalities in the vibration data of the fan, the following problems will arise: the actual center of mass of the fan rotation does not coincide with the shaft, resulting in inconsistent vibrations of different blades, and the balance detection result obtained by relying on the similarity of blade vibration is not accurate; the vibration abnormality of a fan will be transmitted to other blades, and the vibration data of other blades will also show abnormalities, resulting in the vibration data of the blades also having a high similarity, making the accuracy of the fan balance detection result low. Summary of the invention

[0004] The present invention provides a balance detection device and a detection method for fan manufacturing, which solves the problem of low accuracy of fan balance detection in the related art.

[0005] The technical solution of the present invention is as follows:

[0006] In a first aspect, the present invention provides a balance detection method for fan manufacturing, the method comprising:

[0007] Obtain the vibration data and centrifugal force vector of each fan blade at each moment during the balancing detection process of the fan;

[0008] Determine the corrected vibration balance characteristic value of the fan at each moment according to the vibration data and the centrifugal force vector of each fan blade at each moment;

[0009] The balance credibility of the fan at each moment is determined according to the stability of the change of the local corrected vibration balance characteristic value, the rotation speed at each moment and the vibration data of each fan blade;

[0010] Determine the vibration weight at each moment according to the corrected vibration balance characteristic value and balance credibility of the fan at each moment; determine the vibration abnormality evaluation value of the fan at each moment according to the vibration weight at each moment and the vibration data of the fan at each moment;

[0011] The balance state of the fan is determined based on the vibration abnormality evaluation value of the fan at each moment.

[0012] Further, the determining of the corrected vibration balance characteristic value of the fan at each moment according to the vibration data and the centrifugal force vector of each fan blade at each moment includes:

[0013] According to the vibration data of each fan blade at each moment, the vibration degree and vibration similarity of the fan blade are analyzed to determine the preliminary vibration balance characteristic value of the fan at each moment;

[0014] According to the centrifugal force vector of each fan blade at each moment, the force condition of the fan at each moment is analyzed to determine the vibration deviation degree of the fan at each moment;

[0015] The preliminary vibration balance characteristic value is corrected by using the vibration deviation degree to obtain the corrected vibration balance characteristic value of the fan at each moment.

[0016] Furthermore, the vibration data of each fan blade at each moment is used to analyze the vibration degree and vibration similarity of the fan blades, and determine the preliminary vibration balance characteristic value of the fan at each moment, including:

[0017] Taking any moment as a target moment, determining the average value of the vibration data of all the blades at the target moment based on the vibration data of each blade at the target moment, and determining the average value of the difference between the vibration data of each pair of blades at the target moment;

[0018] The preliminary vibration balance characteristic value at the target moment is determined by combining the average value of the vibration data of all the fan blades at the target moment and the average value of the difference between the vibration data of each pair of fan blades.

[0019] Further, the analyzing the force condition of the electric fan at each moment according to the centrifugal force vector of each fan blade at each moment and determining the vibration deviation degree of the fan at each moment includes:

[0020] Determine the force extreme difference value of the electric fan at the target time according to the modulus of the centrifugal force vector of each fan blade at the target time;

[0021] According to the centrifugal force vector of each fan blade at the target time, determine the resultant force in all fan blade directions corresponding to the electric fan at the target time;

[0022] The vibration deviation degree of the fan at the target time is determined by combining the force extreme difference value and the resultant force of the fan at the target time.

[0023] Furthermore, the use of the vibration offset degree to correct the preliminary vibration balance characteristic value to obtain the corrected vibration balance characteristic value of the fan at each moment includes:

[0024] The vibration deviation degree of the fan at the target time and the preliminary vibration balance characteristic value are used to form a two-dimensional vector, and the corrected vibration balance characteristic value of the fan at the target time is obtained according to the two-dimensional vector.

[0025] Further, the determining of the balance credibility of the fan at each moment according to the stability of the change of the local corrected vibration balance characteristic value, the rotation speed at each moment and the vibration data of each fan blade includes:

[0026] A preset number of corrected vibration balance characteristic values ​​are selected around the target time as neighborhood data of the target time, and a straight line is fitted to the corrected vibration balance characteristic values ​​of the target time and each neighborhood data in chronological order to obtain a fitting straight line;

[0027] Determine the first balance credibility factor of the fan at the target moment according to the difference between the fitting value and the actual value at each moment on the fitting straight line; wherein the actual value is the modified vibration balance characteristic value;

[0028] Obtain standard vibration data of the fan blades at each speed, and determine a second balance credibility factor of the fan at the target time based on the similarity between the vibration data of each fan blade at the target time and the standard vibration data of the fan blades at the speed at the target time;

[0029] The balance credibility of the fan at the target moment is determined by combining the first balance credibility factor and the second balance credibility factor of the fan at the target moment.

[0030] Further, the determining of the vibration weight at each moment according to the corrected vibration balance characteristic value and balance credibility of the fan at each moment includes:

[0031] Determine the vibration importance at the target time by combining the corrected vibration balance characteristic value and balance credibility of the fan at the target time;

[0032] The vibration importance at the target moment is normalized to obtain a normalized value, and the normalized value is used as the vibration weight at the target moment.

[0033] Further, the determining the vibration abnormality evaluation value of the fan at each moment according to the vibration weight at each moment and the vibration data of the fan at each moment includes:

[0034] The vibration data of the fan at each moment is weighted and summed using the vibration weight at each moment to obtain a weighted vibration average value;

[0035] Determine the weighted vibration standard deviation according to the weighted vibration average value, the vibration weight at each moment and the vibration data of the fan;

[0036] According to the vibration data, weighted vibration average value and weighted vibration standard deviation of the fan at each moment, the vibration abnormality evaluation value of the fan at each moment is determined by using the z-score algorithm.

[0037] Further, the determining the balance state of the fan according to the vibration abnormality evaluation value of the fan at each moment includes:

[0038] A threshold is determined for the abnormal vibration evaluation value of the fan at each moment. If there is no abnormal vibration data, the balance state of the fan is determined to be excellent. The abnormal vibration data refers to vibration data whose abnormal vibration evaluation value is greater than the evaluation threshold.

[0039] If there is abnormal vibration data, the frequency of occurrence of the abnormal vibration data is counted. When the frequency is less than the first frequency threshold, the balance state of the fan is determined to be good; when the frequency is greater than or equal to the first frequency threshold and less than or equal to the second frequency threshold, the balance state of the fan is determined to be qualified; when the frequency is greater than the second frequency threshold, the balance state of the fan is determined to be unqualified; wherein the first frequency threshold is less than the second frequency threshold.

[0040] In a second aspect, the present invention further provides a balance detection device for fan manufacturing, the device comprising:

[0041] A data acquisition module is used to obtain the vibration data and centrifugal force vector of each fan blade at each moment during the balancing detection process of the fan;

[0042] A first determination module, used to determine a corrected vibration balance characteristic value of the fan at each moment according to the vibration data and the centrifugal force vector of each fan blade at each moment;

[0043] The second determination module is used to determine the balance credibility of the fan at each moment according to the stability of the change of the local corrected vibration balance characteristic value, the rotation speed at each moment and the vibration data of each fan blade;

[0044] The third determination module is used to determine the vibration weight at each moment according to the corrected vibration balance characteristic value and balance credibility of the fan at each moment; and determine the vibration abnormality evaluation value of the fan at each moment according to the vibration weight at each moment and the vibration data of the fan at each moment;

[0045] The fourth determination module is used to determine the balance state of the fan according to the vibration abnormality evaluation value of the fan at each moment.

[0046] The working principle and beneficial effects of the present invention are:

[0047] The present invention determines the vibration anomaly evaluation value by weighting the vibration weight at each moment, so that the fan balance detection result based on the vibration anomaly evaluation value is more accurate, overcomes the defect that the vibration data has a high false similarity due to the actual structural characteristics of the fan rotation, and further improves the accuracy of the balance detection. When determining the vibration weight, the corrected vibration balance eigenvalue is first determined by the vibration data of the fan blades and the centrifugal force vector. Compared with the existing eigenvalue determination method, the present invention takes into account that the vibration abnormality will be transmitted to the normal fan blades, resulting in false similarity in the vibration data. The balance of the fan can be used to make the entire fan force also balanced. The centrifugal force vector is added to the determination of the corrected vibration balance eigenvalue, which helps to improve the numerical accuracy of the corrected vibration balance eigenvalue, and thus improve the accuracy of balance detection based on the eigenvalue; then, the balance credibility of the fan is determined based on the stability of the eigenvalue change and the influence of the rotation speed. The balance credibility is determined because only the relationship between the characteristics of the fan blades at a single moment is used, which is easily disturbed by the environmental noise data, resulting in the eigenvalue not being able to truly reflect the balance performance of the fan, and the balance credibility is conducive to a comprehensive assessment of the fan balance and accurately reflects the balance state of the fan in actual operation; then, the vibration weight of each moment is determined by the corrected vibration balance eigenvalue and the balance credibility. The numerical accuracy of the vibration weight determined by the two aspects is higher, and the vibration abnormality evaluation value determined based on the more accurate vibration weight can make the subsequent fan balance state detection result more reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0049] Figure 1 A flow chart of the steps of a balance detection method for fan manufacturing according to an embodiment of the present invention;

[0050] Figure 2 A flowchart of the steps of determining the corrected vibration balance characteristic value in an embodiment of the present invention;

[0051] Figure 3 A flowchart of the steps of determining the balance credibility in an embodiment of the present invention;

[0052] Figure 4 This is a structural framework diagram of a balance detection device for fan manufacturing according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the technical solutions proposed by the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments may be combined in any suitable form. Among them, in the description of the embodiments of the present invention, unless otherwise specified, " / " means or, for example, A / B can mean A or B: "and / or" in the text is only a description of the association relationship of the associated objects, indicating that there can be three relationships, such as A and / or B, which can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present invention, "multiple" means two or more than two.

[0054] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by a person skilled in the art to which the present invention belongs.

[0055] The specific scenario targeted by the present invention is: performing balance detection on a fan of the fan blade type to improve the accuracy of the z-score anomaly detection algorithm in detecting anomalies in fan vibration data, thereby improving the accuracy of judging the fan balance performance.

[0056] Example 1

[0057] like Figure 1 As shown, this embodiment proposes a balance detection method for fan manufacturing, and the specific implementation steps may include:

[0058] S1, obtaining the vibration data and centrifugal force vector of each fan blade at each moment during the balancing detection process of the fan.

[0059] It should be noted that during the balance detection process, the balance state of the current fan is analyzed by obtaining vibration data and centrifugal force vector. The vibration data can reflect the vibration intensity of each fan blade during rotation, and the centrifugal force vector can reflect the force conditions of the fan in different blade directions. Both are basic data for extracting the balance characteristics of the fan.

[0060] S11, first obtain the vibration data of each fan blade at each moment during the balance detection process of the fan.

[0061] In this embodiment, the vibration data may be the vibration amplitude, which can directly reflect the real-time operating status of the fan. By analyzing the abnormality of the vibration data, it is helpful to comprehensively evaluate the performance of the fan and fully understand the balance state of the fan to be tested.

[0062] Specifically, a vibration sensor is used to collect the vibration amplitude of each fan blade when the fan speed is stable at different speeds, and the vibration amplitude is used as vibration data to obtain the vibration condition of each fan blade.

[0063] S12, then obtaining the centrifugal force vector of each fan blade at each moment during the balance detection process of the fan.

[0064] In this embodiment, the force condition of the fan blades can be characterized by centrifugal force, and the overall movement trend of the fan can be analyzed by centrifugal force. The movement trend refers to the deviation caused by obvious vibration during the rotation of the fan, and the vibration deviation can be used to evaluate the balance of the fan.

[0065] As an example, the step of determining the centrifugal force vector of each blade of the fan may include:

[0066] First, determine the shape and size of the fan blades. Usually, the fan blades can be approximated as a rectangle, arc or other shape; secondly, determine the rotation axis around which the fan blades rotate and the angular velocity of the rotation. The rotation axis is usually located at the center of the fan blades, and the angular velocity can be calculated based on the rotation speed and radius; then, for each fan blade, calculate the radial distance of its center of mass relative to the rotation axis, which can be determined by the geometric shape and the position of the rotation axis; then, use the formula for centrifugal force to calculate the magnitude of the centrifugal force; finally, determine the direction of the centrifugal force. Among them, the calculation process of the centrifugal force vector of the fan blade is a prior art, which is not within the scope of protection of the present invention and will not be elaborated here.

[0067] So far, the present embodiment has obtained vibration data and centrifugal force vectors for subsequent balance analysis.

[0068] S2, determining the corrected vibration balance characteristic value of the fan at each moment according to the vibration data and the centrifugal force vector of each fan blade at each moment.

[0069] It should be noted that the modified vibration balance characteristic value represents the vibration balance characteristic value after the correction operation. The vibration data can be used to analyze the initial uncorrected vibration balance characteristics, and the centrifugal force vector can be used to analyze the degree of deviation of the fan movement trend. The initial uncorrected vibration balance characteristics can be corrected by the degree of deviation, which overcomes the defect that the abnormal vibration data has a high similarity due to the influence of the fan structure characteristics to a certain extent. The steps for determining the modified vibration balance characteristic value are as follows: Figure 2 As shown, the specific implementation steps may include:

[0070] S21, analyzing the vibration degree and vibration similarity of the fan blades according to the vibration data of each fan blade at each moment, and determining the preliminary vibration balance characteristic value of the fan at each moment.

[0071] In this embodiment, based on the similarity of the vibrations of the various blades under dynamic balancing of the fan, the vibration data of each blade at the same moment is used to calculate the preliminary vibration balance characteristic value of the fan at each moment.

[0072] The calculation process of the preliminary vibration balance characteristic value of the fan at each moment is consistent. In order to reduce the description and facilitate understanding, this embodiment takes any moment as an example, takes any moment as the target moment, and determines the preliminary vibration balance characteristic value of the fan at the target moment. The specific implementation steps may include:

[0073] S211, determining the average value of the vibration data of all the fan blades at the target moment based on the vibration data of each fan blade at the target moment, and determining the average value of the difference between the vibration data of each pair of fan blades at the target moment.

[0074] In this embodiment, an unbalanced fan will vibrate when rotating. The vibration data itself can be used to reflect the balance characteristics of the fan. The larger the vibration data, the greater the vibration intensity of the fan, and the worse the balance. The average value of the vibration data of all blades needs to be used as one of the important factors for obtaining the preliminary vibration balance characteristic value. The normal operation of the fan will produce a certain frequency of vibration. The unbalanced rotation of the fan is caused by the inconsistent vibration of the blades. By analyzing the similar vibration conditions of different blades at the same time, the balance characteristics of the voltage can be extracted. The average value of the difference between the vibration data of each pair of blades needs to be used as one of the important factors for obtaining the preliminary vibration balance characteristic value. Among them, the two blades at the target time are combined into a pair to facilitate the analysis of the similarity between the vibration data of each pair of blades.

[0075] S212, combining the average value of the vibration data of all the fan blades at the target moment and the average value of the difference between the vibration data of each pair of fan blades, to determine the preliminary vibration balance characteristic value at the target moment.

[0076] In this embodiment, the average value and the difference average value here are negatively correlated with the balance characteristics of the fan, and the negative correlation means that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. It can be a subtraction relationship, a division relationship, etc.

[0077] Specifically, the reciprocal of the product of the average value and the difference average value can be calculated first, and then the reciprocal can be normalized, and the obtained normalized value can be used as the preliminary vibration balance characteristic value at the target moment. Of course, the implementer can also determine the preliminary vibration balance characteristic value by other calculation methods, without specific limitation.

[0078] As an example, the calculation formula of the preliminary vibration balance characteristic value at the target time can be:

[0079] Where v represents the initial vibration balance characteristic value at the target time, norm represents the linear normalization function, and p i represents the vibration data of the i-th fan blade at the target time, p k represents the vibration data of the kth blade at the target time, i is not equal to k, i and k both represent the serial number of the blade, E(p i ) represents the average value of the vibration data of all the fan blades corresponding to the fan at the target time, E(p i -p k ) represents the average difference between the vibration data of the i-th blade and the k-th blade at the target moment.

[0080] In the calculation formula of the preliminary vibration balance characteristic value, E(p i ) can represent the vibration intensity of the fan at the target time. The greater the vibration intensity, the greater the possibility of abnormal balance of the fan at the target time, that is, the more obvious the imbalance characteristics of the fan, and the smaller the initial vibration balance characteristic value; E(p i -p k ) can characterize the vibration similarity between the two blades at the target time, E(p i -p k ) is larger, the worse the vibration similarity is, the more obvious the imbalance characteristics of the fan are, and the smaller the preliminary vibration balance characteristic value is. On the contrary, the higher the similarity between the vibration data is, the more obvious the vibration balance characteristics are, and the larger the preliminary vibration balance characteristic value is.

[0081] S22, analyzing the force condition of the electric fan at each moment according to the centrifugal force vector of each fan blade at each moment, and determining the vibration deviation degree of the fan at each moment.

[0082] It should be noted that the balance of the fan can balance the force on the entire fan, and the degree of vibration deviation during rotation is determined by using the centrifugal force of the blades and the force on the entire fan during the constant speed operation of each blade. When the fan is unbalanced, different blades will be subjected to forces of different magnitudes, which causes the resultant force on each blade to be non-zero. Since the forces on each blade cannot be offset, the fan as a whole shows an obvious movement trend, that is, there is an obvious vibration deviation during the rotation of the fan. The greater the degree of vibration deviation, the worse the balance of the fan.

[0083] In this embodiment, the calculation process of the vibration deviation degree of the fan at each moment is the same. In order to reduce unnecessary description and facilitate understanding of the solution, taking the target moment as an example, the vibration deviation degree of the fan at the target moment is determined. The specific implementation steps may include:

[0084] S221, determining the force extreme difference value of the electric fan at the target moment according to the modulus of the centrifugal force vector of each fan blade at the target moment.

[0085] It should be noted that the force extreme difference value reflects the fluctuation of the force on the fan blades. The greater the fluctuation of the force on the fan blades, the more serious the force imbalance is and the more obvious the imbalance characteristics of the fan are. The force extreme difference value can be used as an important factor in quantifying the degree of vibration deviation of the fan.

[0086] Specifically, first determine the modulus of the centrifugal force vector of each fan blade at the target moment, then select the maximum vector modulus value and the minimum vector modulus value, and use the difference between the maximum vector modulus value and the minimum vector modulus value as the force extreme difference value of the fan at the target moment.

[0087] S222, determining the resultant force in all fan blade directions corresponding to the electric fan at the target moment based on the centrifugal force vector of each fan blade at the target moment.

[0088] It should be noted that the closer the resultant force acting on the fan is to 0, the more obvious the balanced characteristics of the force acting on the fan are, and the smaller the possibility of vibration deviation is. Therefore, the size of the resultant force acting on the fan can be used as another important factor in analyzing the degree of vibration deviation of the fan.

[0089] Specifically, the cumulative value of the centrifugal force vectors of all the fan blades at the target time is calculated, and the cumulative value of the vector is used as the resultant force on the fan at the target time. The calculation process of the resultant force is a prior art and is not within the scope of protection of the present invention, and will not be elaborated here.

[0090] S223, determining the vibration deviation degree of the fan at the target moment in combination with the force extreme difference value and the resultant force of the fan at the target moment.

[0091] It should be noted that the resultant force is a vector. In order to analyze the magnitude of the resultant force, it is necessary to calculate the scalar of the resultant force, that is, to calculate the modulus of the resultant force. Among them, the calculation process of the modulus of the resultant force is a prior art and is not within the scope of protection of the present invention, and will not be elaborated on here. The force extreme difference value and the magnitude of the resultant force are both positively correlated with the degree of vibration offset. The positive correlation means that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases. The specific relationship can be a multiplication relationship, an addition relationship, etc. Specifically, the product of the force extreme difference value and the modulus of the resultant force is calculated, and the product of the two is used as the degree of vibration offset of the fan at the target moment.

[0092] As an example, the calculation formula for the vibration deviation degree of the fan at the target time may be:

[0093] In the formula, d represents the vibration deviation degree of the fan at the target time, max represents the maximum value function, min represents the minimum value function, and F i represents the centrifugal force vector of the i-th blade at the target time, ‖‖ represents the modulus function, ∑ i F i Represents the resultant force in all blade directions of the fan at the target time.

[0094] In the calculation formula of vibration offset degree, represents the extreme difference of the force on the fan at the target time, ‖∑ i F i ‖ represents the modulus of the resultant force in all blade directions corresponding to the fan at the target moment, that is, the magnitude of the resultant force; the larger the force range, the more obvious the deviation to one side during the rotation of the fan, and the poor balance; on the contrary, the smaller the force range, the more stable the fluctuation of the force magnitude of each blade, thus showing a more obvious balance feature; the magnitude of the resultant force on the fan can reflect the offset of each blade. When the modulus of the resultant force is zero, it means that the force on the fan is eventually offset and the fan reaches a balanced state. On the contrary, the larger the modulus of the resultant force, the more obvious the deviation between the blades, and the poor balance; the degree of vibration offset can reflect the balance feature of the fan from the perspective of the force situation. The smaller the vibration offset, the more obvious the balance feature of the fan; the larger the vibration offset, the more obvious the imbalance feature of the fan.

[0095] S23, correcting the preliminary vibration balance characteristic value by using the vibration deviation degree to obtain a corrected vibration balance characteristic value of the fan at each moment.

[0096] It should be noted that the degree of vibration offset is negatively correlated with the vibration balance characteristics. The greater the degree of vibration offset, the smaller the corrected vibration balance characteristic value. Therefore, it is necessary to perform negative correlation processing on the degree of vibration offset. Specifically, the exp(-) function can be used to perform negative correlation processing on the degree of vibration offset. At the same time, this function also realizes normalization processing. Of course, the implementer can also use other negative correlation processing methods to achieve negative correlation processing.

[0097] Specifically, for the target moment, the vibration deviation degree of the fan at the target moment and the preliminary vibration balance characteristic value are used to form a two-dimensional vector, the modulus of the two-dimensional vector is calculated, and the modulus of the two-dimensional vector is used as the corrected vibration balance characteristic value of the fan at the target moment, which realizes the correction processing of the preliminary vibration balance characteristic value. At the same time, with reference to the determination process of the corrected vibration balance characteristic value of the fan at the target moment, the corrected vibration balance characteristic value of the fan at each moment can be obtained.

[0098] When analyzing the balance characteristics of the fan at different times, this embodiment not only takes into account the similarities between the vibration data of each fan blade, but also takes into account the force conditions of the fan, so that the corrected vibration balance characteristic value can accurately reflect the balance characteristics of the fan at each moment, which is helpful to subsequently obtain more accurate vibration weights.

[0099] So far, this embodiment has obtained the corrected vibration balance characteristic value of the fan at each moment.

[0100] S3, determining the balance credibility of the fan at each moment according to the stability of the change of the local corrected vibration balance characteristic value, the rotation speed at each moment and the vibration data of each fan blade.

[0101] It should be noted that the balance characteristics of the fan at a single moment are easily disturbed by the environmental noise data, resulting in the corrected vibration balance characteristic value not being able to truly reflect the balance performance of the fan. The evaluation of the fan balance is not comprehensive enough and cannot accurately reflect the balance state of the fan in actual operation. Therefore, the stability of the characteristic value changes in time series and the vibration of the fan blades under different speed conditions are used to quantify the credibility of the corrected vibration balance characteristic value of the fan at each moment, that is, the balance credibility. The steps for determining the balance credibility are as follows: Figure 3 As shown, the specific implementation steps may include:

[0102] S31, determining a first balance credibility factor of the fan at each moment according to the modified vibration balance characteristic value of the fan at each moment.

[0103] Regardless of whether the fan is working normally or abnormally, the vibration or force of each fan blade will tend to be stable, so that the characteristic value tends to be stable. The higher the stability, the less likely it is that there is noise. The obtained balance characteristics can reflect the actual fan balance with higher accuracy and greater reference value. The first balance credible factor can characterize the stability of the change of the corrected vibration balance characteristic value of the fan at other times around a certain moment. The steps for determining the first balance credible factor of the fan at the target moment may include:

[0104] S311, selecting a preset number of corrected vibration balance eigenvalues ​​around the target moment as neighborhood data of the target moment, performing straight line fitting on the corrected vibration balance eigenvalues ​​of the target moment and each neighborhood data in chronological order to obtain a fitting straight line.

[0105] When analyzing the stability of eigenvalue changes, it is necessary to analyze the corrected vibration balance eigenvalues ​​at each moment in the local time period. Specifically, multiple corrected vibration balance eigenvalues ​​close to the target moment can be selected around the target moment as neighborhood data to construct local corrected vibration balance eigenvalues. By analyzing the stability of neighborhood data changes, the stability of the target moment can be quantified.

[0106] In this embodiment, 20 moments that are close to the target moment are selected based on experience, and the corrected vibration balance eigenvalues ​​of the 20 moments are obtained as the neighborhood data of the target moment; the least squares method is used to perform horizontal straight line fitting on the selected 20 neighborhood data and the corrected vibration balance eigenvalue of the target moment to obtain a fitting straight line; determining the fitting straight line is helpful to analyze the stability of the data around the target moment over time.

[0107] Among them, the number of neighborhood data at a single moment can be set by the implementer according to the specific actual situation, and is not specifically limited; the implementation process of the least squares method is a prior art and is not within the protection scope of the present invention, and will not be elaborated here.

[0108] S312: Determine a first balance credibility factor of the fan at the target moment according to the difference between the fitting value and the actual value at each moment on the fitting line.

[0109] It should be noted that the greater the difference between the fitting value and the actual value, the worse the stability of the characteristic change around the target moment, the greater the possibility of noise data influence, and the smaller the first balance credibility factor. Among them, each moment on the fitting line has its corresponding actual value and fitting value. The actual value refers to the corrected vibration balance characteristic value, and the fitting value refers to the ordinate size of the fitting line at each moment.

[0110] Specifically, the difference between the fitting value and the actual value at each moment on the fitting line is first calculated, and then the average value of the difference between the fitting value and the actual value is calculated, and the average value is negatively correlated, that is, the reciprocal of the average value is determined, and the reciprocal is used as the first balance credibility factor of the fan at the target moment.

[0111] S32, obtaining standard vibration data of the fan blades at each rotation speed, and determining a second balance credibility factor of the fan at the target moment based on the similarity between the vibration data of each fan blade at the target moment and the standard vibration data of the fan blades at the rotation speed at the target moment.

[0112] It should be noted that the fan speed needs to be adjusted during the actual fan balance test, and the vibration of the fan blades under different speed conditions needs to be examined to achieve the fan balance test; however, the vibration of the fan blades is affected by their own speed, and the characteristic values ​​obtained from the data are inaccurate and have low credibility. Therefore, it is necessary to analyze the similarity between the vibration data of each fan blade at the speed at the target time and the standard vibration data of the fan blade at the speed at the target time to quantify the second balance credibility factor of the fan at the target time.

[0113] S321, obtaining standard vibration data of the fan blades at each rotation speed.

[0114] In this embodiment, a fan with good balance performance is used to fit the speed and vibration. A large amount of historical data is first obtained, the vibration data of the fan blades at different speeds, which can be specifically the vibration data at the first moment corresponding to the change of the speed; based on the historical data, curve fitting can be performed to obtain a change curve, which is recorded as p=f(r), where p represents the vibration data and r represents the fan speed. The standard vibration data of the fan blades at each speed can be obtained through the change curve. Of course, other methods can also be used to obtain the standard vibration data of the fan blades at each speed.

[0115] S322, determining a second balance credibility factor of the fan at the target moment based on the similarity between the vibration data of each fan blade at the target moment and the standard vibration data of the fan blade at the rotation speed at the target moment.

[0116] It should be noted that the greater the difference between the actual vibration data of the fan blade and the standard vibration data, the worse the similarity between the actual vibration data and the standard vibration data, the worse the credibility of the actual vibration data, and the smaller the second balance credibility factor. Therefore, it is necessary to perform negative correlation processing on the difference between the actual vibration data and the standard vibration data.

[0117] Specifically, first calculate the difference between the vibration data of each fan blade at the target moment and the standard vibration data of the fan blade at the speed at the target moment, then select the maximum difference value, perform negative correlation processing on the maximum difference value, and obtain a negative correlation value, such as the inverse of the maximum difference value, and use the negative correlation value as the second balance credibility factor of the fan at the target moment.

[0118] It is worth noting that the larger the difference value, the larger the difference between the vibration data of the fan blade and the standard vibration data. In order to accurately characterize the balance credibility of the fan at the target moment, it is necessary to determine the maximum difference value, and then use the negative correlation value corresponding to the maximum difference value as the second balance credibility factor. Regarding the acquisition of the negative correlation value, the reciprocal of the maximum difference value can be used as the second balance credibility factor.

[0119] S33: Determine the balance credibility of the fan at the target moment by combining the first balance credibility factor and the second balance credibility factor of the fan at the target moment.

[0120] In this embodiment, the first balance credibility factor and the second balance credibility factor are both positively correlated with the balance credibility. The larger the first balance credibility factor and the second balance credibility factor, the smaller the balance credibility. Therefore, the product of the first balance credibility factor and the second balance credibility factor of the fan at the target moment can be used as the balance credibility. With reference to the calculation process of the balance credibility of the fan at the target moment, the balance credibility of the fan at each moment can be obtained.

[0121] When analyzing the balance credibility, combining the stability of characteristic changes in time series and the credibility of vibration data at different speeds can help improve the calculation accuracy of the balance credibility, further improve the reliability of the subsequently determined vibration weights, and facilitate obtaining more accurate balance detection results.

[0122] So far, this embodiment has obtained the balance credibility of the fan at each moment.

[0123] S4, determining the vibration weight at each moment according to the corrected vibration balance characteristic value and balance credibility of the fan at each moment; determining the vibration abnormality evaluation value of the fan at each moment according to the vibration weight at each moment and the vibration data of the fan at each moment.

[0124] It should be noted that when the z-score algorithm performs anomaly detection on the vibration data of the fan, the difference between the data and the normal data is used to obtain the z-score score of the data. However, the sample weight of each vibration data in the traditional algorithm is consistent, resulting in the standard deviation and average value obtained not being able to accurately reflect the characteristics of normal data. The obtained vibration anomaly evaluation value has low accuracy, that is, the z-score score is inaccurate. Therefore, it is necessary to combine the corrected vibration balance characteristic value and the balance credibility to measure the importance of the vibration data at the current moment in the balance detection process, that is, to determine the vibration weight at each moment, and then determine the average value and standard deviation based on the vibration weight, which helps to improve the numerical accuracy of the vibration anomaly evaluation value and overcome the defect of the consistent sample weight of each vibration data in the traditional algorithm.

[0125] S41, determining the vibration weight at each moment according to the corrected vibration balance characteristic value and balance credibility of the fan at each moment.

[0126] In this embodiment, the vibration weight can represent the importance of the vibration data of the fan at each moment. The larger the vibration weight, the greater the importance of the vibration data of the fan at the corresponding moment. The value range of the vibration weight should be between 0 and 1. The importance of the vibration data can be obtained by integrating the corrected vibration balance eigenvalue and balance credibility of the fan at the same moment. The larger the corrected vibration balance eigenvalue and balance credibility, the more obvious the balance characteristics of the vibration data, and the larger the vibration weight. The steps for determining the vibration weight at each moment are consistent. In order to reduce unnecessary descriptions and facilitate understanding of the solution, the vibration weight of the target moment is determined by taking the target moment as an example. The specific implementation steps may include:

[0127] S411, determining the vibration importance at the target moment in combination with the corrected vibration balance characteristic value and balance credibility of the fan at the target moment.

[0128] In this embodiment, the corrected vibration balance characteristic value, the balance credibility and the vibration importance at the target time are positively correlated. The larger the corrected vibration balance characteristic value and the balance credibility, the greater the vibration importance. The product of the corrected vibration balance characteristic value and the balance credibility can be used as the vibration importance at the target time. The vibration importance refers to the importance of the fan's vibration data for balance detection.

[0129] S412, normalizing the vibration importance at the target moment to obtain a normalized value, and using the normalized value as the vibration weight at the target moment.

[0130] In this embodiment, the normalization process may be implemented by the proportion of a single vibration importance to the total importance of all vibrations. The greater the proportion, the greater the vibration weight at the target moment.

[0131] As an example, the calculation formula of the vibration weight at the target moment may be:

[0132] Where W represents the vibration weight at the target time, newη represents the balance credibility of the fan at the target time, nv represents the corrected vibration balance characteristic value of the fan at the target time, (newη×nv) represents the vibration importance at the target time, and (newη×nv) x Indicates the importance of vibration at the xth moment, where x is the time sequence number in the fan balancing detection process.

[0133] S42, determining a vibration abnormality evaluation value of the fan at each moment according to the vibration weight at each moment and the vibration data of the fan at each moment.

[0134] It should be noted that the vibration anomaly evaluation value can be used to evaluate the degree of vibration anomaly during fan balance detection. The larger the vibration anomaly evaluation value, the more abnormal the vibration of the fan at the corresponding moment. The vibration anomaly evaluation value is the z-score of the vibration data at each moment. The specific implementation steps may include:

[0135] S421, performing weighted sum processing on the vibration data of the fan at each moment using the vibration weight at each moment to obtain a weighted vibration average value.

[0136] It should be noted that when determining the z-score, it is necessary to determine the mean and standard deviation of the vibration data at all times. The existing calculation process of the mean and standard deviation ignores the different importance of the vibration data at different times, resulting in low accuracy of the calculated mean and standard deviation, which in turn causes low accuracy of the vibration anomaly evaluation used to evaluate vibration anomalies. This embodiment combines the vibration weights of the fan at different times when determining the mean and standard deviation of the vibration data during the fan balance detection process. The vibration weight can characterize the importance of the vibration data, which effectively improves the numerical accuracy of the weighted vibration mean and weighted vibration standard deviation.

[0137] As an example, the calculation formula for the weighted vibration average value may be:

[0138] newE(p)=∑ x (W x ×p' x ), where newE(p) represents the weighted vibration average value, W x represents the vibration weight at the xth moment, p' x represents the vibration data of the fan at the x-th moment, and the vibration data of the fan may be equal to the average value of the vibration data of all the blades in the fan.

[0139] S422, determining a weighted vibration standard deviation according to the weighted vibration average value, the vibration weight at each moment, and the vibration data of the fan.

[0140] As an example, the calculation formula for the weighted vibration standard deviation can be:

[0141] Where newσ represents the weighted vibration standard deviation.

[0142] S423, determining the vibration abnormality evaluation value of the fan at each moment according to the vibration data, weighted vibration average value and weighted vibration standard deviation of the fan at each moment by using a z-score algorithm.

[0143] In this embodiment, the implementation process of the z-score algorithm is an existing technology. The z-score score can be used to evaluate the abnormal state of data. The specific implementation process of the z-score algorithm is an existing technology and will not be elaborated here.

[0144] As an example, the calculation formula of the vibration abnormality evaluation value of the fan at the xth moment may be:

[0145] In the formula, score x It represents the vibration abnormality evaluation value of the fan at the x-th moment. The vibration abnormality evaluation value is the evaluation value corrected by the vibration weight. That is, the z-score is adjusted by the vibration weight.

[0146] So far, this embodiment has obtained the vibration abnormality evaluation value of the fan at each moment.

[0147] S5, determining the balance state of the fan according to the vibration abnormality evaluation value of the fan at each moment.

[0148] It should be noted that after obtaining the vibration abnormality evaluation value at each moment, the vibration abnormality evaluation value is used to determine the balance state of the fan. The balance state can be defined as excellent, good, qualified, and unqualified. The specific implementation steps for determining the balance state of the fan may include:

[0149] S51, threshold determination is performed on the abnormal vibration evaluation value of the fan at each moment, and if there is no abnormal vibration data, the balance state of the fan is determined to be excellent.

[0150] In this embodiment, an evaluation threshold is set, and the range of abnormal vibration for different balance requirements is different. The implementer can set the size of the evaluation threshold according to the actual situation, without specific limitation. When the vibration abnormality evaluation value of the fan at each moment is greater than the evaluation threshold, it is determined that there is no abnormal vibration data in the balance detection of the fan, and the balance state of the fan can be directly determined to be excellent. Among them, abnormal vibration data refers to vibration data with a vibration abnormality evaluation value greater than the evaluation threshold.

[0151] S52: If there is abnormal vibration data, the frequency of occurrence of the abnormal vibration data is counted, and then a threshold value is determined for the frequency of occurrence to determine the balance state of the fan.

[0152] In this embodiment, when the occurrence frequency is less than the first frequency threshold, the balance state of the fan is determined to be good; when the occurrence frequency is greater than or equal to the first frequency threshold and less than or equal to the second frequency threshold, the balance state of the fan is determined to be qualified; when the occurrence frequency is greater than the second frequency threshold, the balance state of the fan is determined to be unqualified, and there is a safety hazard in the balance of the fan;

[0153] The first frequency threshold is smaller than the second frequency threshold. The first frequency threshold can be set to 1%, and the second frequency threshold can be set to 5%. The implementer can also set the first frequency threshold and the second frequency threshold according to specific actual requirements.

[0154] Thus, this embodiment obtains a more accurate vibration abnormality evaluation value by determining the vibration weight of the fan at each moment, thereby achieving a more reliable balance state of the fan.

[0155] Example 2

[0156] like Figure 4 As shown, this embodiment also provides a balance detection device for fan manufacturing, the detection device comprising:

[0157] The data acquisition module 401 is used to obtain the vibration data and centrifugal force vector of each fan blade at each moment during the balancing detection process of the fan.

[0158] The first determination module 402 is used to determine the corrected vibration balance characteristic value of the fan at each moment according to the vibration data and the centrifugal force vector of each fan blade at each moment.

[0159] The second determination module 403 is used to determine the balance credibility of the fan at each moment according to the stability of the change of the local corrected vibration balance characteristic value, the rotation speed at each moment and the vibration data of each fan blade.

[0160] The third determination module 404 is used to determine the vibration weight at each moment according to the modified vibration balance characteristic value and balance credibility of the fan at each moment; and determine the vibration abnormality evaluation value of the fan at each moment according to the vibration weight at each moment and the vibration data of the fan at each moment.

[0161] The fourth determination module 405 is used to determine the balance state of the fan according to the vibration abnormality evaluation value of the fan at each moment.

[0162] In some possible implementations, the first determination module is further used to analyze the vibration degree and vibration similarity of the fan blades according to the vibration data of each fan blade at each moment, and determine the preliminary vibration balance characteristic value of the fan at each moment; analyze the force condition of the fan at each moment according to the centrifugal force vector of each fan blade at each moment, and determine the vibration deviation degree of the fan at each moment; and use the vibration deviation degree to correct the preliminary vibration balance characteristic value to obtain the corrected vibration balance characteristic value of the fan at each moment.

[0163] In some possible implementations, the first determination module is also used to take any moment as a target moment, determine the average value of the vibration data of all the fan blades at the target moment based on the vibration data of each fan blade at the target moment, and determine the average value of the difference between the vibration data of each pair of fan blades at the target moment; combine the average value of the vibration data of all the fan blades at the target moment and the average value of the difference between the vibration data of each pair of fan blades to determine the preliminary vibration balance characteristic value at the target moment.

[0164] In some possible implementations, the first determination module is further configured to form a two-dimensional vector from the vibration deviation degree of the fan at the target moment and the preliminary vibration balance eigenvalue, and obtain a corrected vibration balance eigenvalue of the fan at the target moment according to the two-dimensional vector.

[0165] In some possible implementations, the first determination module is also used to determine the force extreme difference value of the electric fan at the target moment based on the modulus of the centrifugal force vector of each fan blade at the target moment; determine the resultant force in all fan blade directions corresponding to the electric fan at the target moment based on the centrifugal force vector of each fan blade at the target moment; and determine the degree of vibration deviation of the fan at the target moment by combining the force extreme difference value and the resultant force of the electric fan at the target moment.

[0166] In some possible implementations, the second determination module is further used to select a preset number of corrected vibration balance eigenvalues ​​around the target moment as neighborhood data of the target moment, and perform straight line fitting on the corrected vibration balance eigenvalues ​​at the target moment and each neighborhood data in chronological order to obtain a fitting straight line; determine the first balance credibility factor of the fan at the target moment according to the difference between the fitting value and the actual value at each moment on the fitting straight line; wherein the actual value is the corrected vibration balance eigenvalue; obtain standard vibration data of the fan blades at each speed, and determine the second balance credibility factor of the fan at the target moment according to the similarity between the vibration data of each fan blade at the target moment and the standard vibration data of the fan blade at the speed at the target moment; and determine the balance credibility of the fan at the target moment by combining the first balance credibility factor and the second balance credibility factor of the fan at the target moment.

[0167] In some possible implementations, the third determination module is further used to determine the importance of vibration at the target moment in combination with the corrected vibration balance characteristic value and balance credibility of the fan at the target moment; normalize the importance of vibration at the target moment to obtain a normalized value, and use the normalized value as the vibration weight at the target moment.

[0168] In some possible implementations, the third determination module is further used to perform weighted summation processing on the vibration data of the fan at each moment using the vibration weight at each moment to obtain a weighted vibration average value; determine the weighted vibration standard deviation based on the weighted vibration average value, the vibration weight at each moment and the vibration data of the fan; and determine the vibration abnormality evaluation value of the fan at each moment using a z-score algorithm based on the vibration data of the fan at each moment, the weighted vibration average value and the weighted vibration standard deviation.

[0169] In some possible implementations, the fourth determination module is also used to perform threshold judgment on the vibration abnormality evaluation value of the fan at each moment. If there is no abnormal vibration data, the balance state of the fan is determined to be excellent; wherein the abnormal vibration data represents vibration data with a vibration abnormality evaluation value greater than an evaluation threshold; if there is abnormal vibration data, the frequency of occurrence of the abnormal vibration data is counted, and when the frequency of occurrence is less than a first frequency threshold, the balance state of the fan is determined to be good; when the frequency of occurrence is greater than or equal to the first frequency threshold and less than or equal to the second frequency threshold, the balance state of the fan is determined to be qualified; when the frequency of occurrence is greater than the second frequency threshold, the balance state of the fan is determined to be unqualified; wherein the first frequency threshold is less than the second frequency threshold.

[0170] It should be noted that the device provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device is divided into different functional modules to complete all or part of the functions described above. In addition, the above embodiment provides a balance detection method for fan manufacturing, which belongs to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0171] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A balance detection method for fan manufacturing, characterized in that: include: Obtain the vibration data and centrifugal force vector of each fan blade at each moment during the balancing detection process of the fan; Determine the corrected vibration balance characteristic value of the fan at each moment according to the vibration data and the centrifugal force vector of each fan blade at each moment; The balance credibility of the fan at each moment is determined according to the stability of the change of the local corrected vibration balance characteristic value, the rotation speed at each moment and the vibration data of each fan blade; Determine the vibration weight at each moment according to the corrected vibration balance characteristic value and balance credibility of the fan at each moment; determine the vibration abnormality evaluation value of the fan at each moment according to the vibration weight at each moment and the vibration data of the fan at each moment; Determine the balance state of the fan according to the vibration abnormality evaluation value of the fan at each moment; The method of determining the corrected vibration balance characteristic value of the fan at each moment according to the vibration data and the centrifugal force vector of each fan blade at each moment includes: According to the vibration data of each fan blade at each moment, the vibration degree and vibration similarity of the fan blade are analyzed to determine the preliminary vibration balance characteristic value of the fan at each moment; According to the centrifugal force vector of each fan blade at each moment, the force condition of the fan at each moment is analyzed to determine the vibration deviation degree of the fan at each moment; The preliminary vibration balance characteristic value is corrected by using the vibration deviation degree to obtain the corrected vibration balance characteristic value of the fan at each moment; The method of determining the balance credibility of the fan at each moment according to the stability of the change of the local corrected vibration balance characteristic value, the rotation speed at each moment and the vibration data of each fan blade includes: A preset number of corrected vibration balance characteristic values ​​are selected around a target time as neighborhood data of the target time, and a straight line fitting is performed on the corrected vibration balance characteristic values ​​of the target time and each neighborhood data in time sequence to obtain a fitting straight line; wherein the target time is any time; Determine the first balance credibility factor of the fan at the target moment according to the difference between the fitting value and the actual value at each moment on the fitting straight line; wherein the actual value is the modified vibration balance characteristic value; Obtain standard vibration data of the fan blades at each speed, and determine a second balance credibility factor of the fan at the target time based on the similarity between the vibration data of each fan blade at the target time and the standard vibration data of the fan blades at the speed at the target time; The balance credibility of the fan at the target moment is determined by combining the first balance credibility factor and the second balance credibility factor of the fan at the target moment.

2. A balance detection method for fan manufacturing according to claim 1, characterized in that: The method of analyzing the vibration degree and vibration similarity of the fan blades according to the vibration data of each fan blade at each moment, and determining the preliminary vibration balance characteristic value of the fan at each moment, includes: Determine the average value of the vibration data of all the blades at the target time according to the vibration data of each blade at the target time, and determine the average value of the difference between the vibration data of each pair of blades at the target time; The preliminary vibration balance characteristic value at the target moment is determined by combining the average value of the vibration data of all the fan blades at the target moment and the average value of the difference between the vibration data of each pair of fan blades.

3. A balancing detection method for fan manufacturing according to claim 1, characterized in that: The method of analyzing the force condition of the electric fan at each moment according to the centrifugal force vector of each fan blade at each moment and determining the vibration deviation degree of the fan at each moment includes: Determine the force extreme difference value of the electric fan at the target time according to the modulus of the centrifugal force vector of each fan blade at the target time; According to the centrifugal force vector of each fan blade at the target time, determine the resultant force in all fan blade directions corresponding to the electric fan at the target time; The vibration deviation degree of the fan at the target time is determined by combining the force extreme difference value and the resultant force of the fan at the target time.

4. A balance detection method for fan manufacturing according to claim 1, characterized in that: The method of correcting the preliminary vibration balance characteristic value by using the vibration offset degree to obtain the corrected vibration balance characteristic value of the fan at each moment includes: The vibration deviation degree of the fan at the target time and the preliminary vibration balance characteristic value are used to form a two-dimensional vector, and the corrected vibration balance characteristic value of the fan at the target time is obtained according to the two-dimensional vector.

5. A balance detection method for fan manufacturing according to claim 1, characterized in that: The step of determining the vibration weight at each moment according to the corrected vibration balance characteristic value and balance credibility of the fan at each moment includes: Determine the vibration importance at the target time by combining the corrected vibration balance characteristic value and balance credibility of the fan at the target time; The vibration importance at the target moment is normalized to obtain a normalized value, and the normalized value is used as the vibration weight at the target moment.

6. A balance detection method for fan manufacturing according to claim 1, characterized in that: The step of determining the vibration abnormality evaluation value of the fan at each moment according to the vibration weight at each moment and the vibration data of the fan at each moment comprises: The vibration data of the fan at each moment is weighted and summed using the vibration weight at each moment to obtain a weighted vibration average value; Determine the weighted vibration standard deviation according to the weighted vibration average value, the vibration weight at each moment and the vibration data of the fan; According to the vibration data, weighted vibration average value and weighted vibration standard deviation of the fan at each moment, the vibration abnormality evaluation value of the fan at each moment is determined by using the z-score algorithm.

7. A balance detection method for fan manufacturing according to claim 1, characterized in that: The step of determining the balance state of the fan according to the vibration abnormality evaluation value of the fan at each moment includes: A threshold is determined for the abnormal vibration evaluation value of the fan at each moment. If there is no abnormal vibration data, the balance state of the fan is determined to be excellent. The abnormal vibration data refers to vibration data whose abnormal vibration evaluation value is greater than the evaluation threshold. If there is abnormal vibration data, the frequency of occurrence of the abnormal vibration data is counted. When the frequency is less than the first frequency threshold, the balance state of the fan is determined to be good; when the frequency is greater than or equal to the first frequency threshold and less than or equal to the second frequency threshold, the balance state of the fan is determined to be qualified; when the frequency is greater than the second frequency threshold, the balance state of the fan is determined to be unqualified; wherein the first frequency threshold is less than the second frequency threshold.

8. A balance detection device for fan manufacturing, characterized in that: The device comprises: A data acquisition module is used to obtain the vibration data and centrifugal force vector of each fan blade at each moment during the balancing detection process of the fan; A first determination module, used to determine a corrected vibration balance characteristic value of the fan at each moment according to the vibration data and the centrifugal force vector of each fan blade at each moment; The second determination module is used to determine the balance credibility of the fan at each moment according to the stability of the change of the local corrected vibration balance characteristic value, the rotation speed at each moment and the vibration data of each fan blade; The third determination module is used to determine the vibration weight at each moment according to the corrected vibration balance characteristic value and balance credibility of the fan at each moment; and determine the vibration abnormality evaluation value of the fan at each moment according to the vibration weight at each moment and the vibration data of the fan at each moment; A fourth determination module, used to determine the balance state of the fan according to the vibration abnormality evaluation value of the fan at each moment; The method of determining the corrected vibration balance characteristic value of the fan at each moment according to the vibration data and the centrifugal force vector of each fan blade at each moment includes: According to the vibration data of each fan blade at each moment, the vibration degree and vibration similarity of the fan blade are analyzed to determine the preliminary vibration balance characteristic value of the fan at each moment; According to the centrifugal force vector of each fan blade at each moment, the force condition of the fan at each moment is analyzed to determine the vibration deviation degree of the fan at each moment; The preliminary vibration balance characteristic value is corrected by using the vibration deviation degree to obtain the corrected vibration balance characteristic value of the fan at each moment; The method of determining the balance credibility of the fan at each moment according to the stability of the change of the local corrected vibration balance characteristic value, the rotation speed at each moment and the vibration data of each fan blade includes: A preset number of corrected vibration balance characteristic values ​​are selected around the target time as neighborhood data of the target time, and a straight line is fitted to the corrected vibration balance characteristic values ​​of the target time and each neighborhood data in chronological order to obtain a fitting straight line; Determine the first balance credibility factor of the fan at the target moment according to the difference between the fitting value and the actual value at each moment on the fitting straight line; wherein the actual value is the modified vibration balance characteristic value; Obtain standard vibration data of the fan blades at each speed, and determine a second balance credibility factor of the fan at the target time based on the similarity between the vibration data of each fan blade at the target time and the standard vibration data of the fan blades at the speed at the target time; The balance credibility of the fan at the target moment is determined by combining the first balance credibility factor and the second balance credibility factor of the fan at the target moment.

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