A static and dynamic balance test method and system for compressor blades based on data analysis

Abstract

The present invention relates to the technical field of static and dynamic balancing of machines, and discloses a static and dynamic balancing test method and system for compressor blades based on data analysis, wherein the method comprises: establishing a coating thickness distribution model and calculating the coating thickness deviation; establishing an aerodynamic disturbance model of a peeling area; collecting vibration signals during blade operation in real time, and extracting high-frequency components of the peeling interference signal; adjusting and optimizing a dynamic compensation matrix; compared with the prior art, in which it is difficult to accurately extract the peeling interference signal under complex working conditions of compressor blade coating peeling, especially in a static and dynamic balancing test environment with high speed and high-frequency vibration, the technical problem of being unable to achieve accurate modeling and compensation of the disturbance in the peeling area is solved. The present application realizes precise adjustment and optimization of static and dynamic balancing tests under complex operating conditions through dynamic modeling of the coating peeling area and a dynamic compensation matrix, thereby avoiding the distortion of the vibration signal caused by coating peeling and improving the efficiency and accuracy of the balancing test.

Description

Technical Field

[0001] The present invention belongs to the technical field of static and dynamic balancing of machines, and in particular relates to a static and dynamic balancing test method and system for compressor blades based on data analysis. Background Art

[0002] At present, the application of machine static and dynamic balancing technology under complex working conditions of air compressor blades is insufficient. For example, when the coating of the air compressor blade peels off or wears off, the peeling area will cause disturbances to the airflow distribution and the dynamic characteristics of the blade. The existing technology cannot accurately extract the interference signal caused by the peeling, and it is difficult to achieve accurate modeling and dynamic compensation of the disturbance in the peeling area. Therefore, during the operation of the compressor blade, the vibration signal is easily distorted by complex interference, and the effect of static and dynamic balance compensation is often poor. Most of the existing technologies are based on static working conditions for balance testing, lacking adaptability to changes in dynamic characteristics under high speed and high frequency vibration environments, and cannot fully meet the accuracy and efficiency requirements of static and dynamic balance testing under complex working conditions. Therefore, there is an urgent need for a method that can accurately extract the peeling interference signal and achieve accurate modeling and dynamic compensation of the disturbance in the peeling area under complex working conditions such as coating peeling, so as to improve the accuracy, efficiency and adaptability of static and dynamic balance testing. Summary of the Invention

[0003] In response to the above-mentioned technical deficiencies, the purpose of the present invention is to propose a static and dynamic balance test method for compressor blades based on data analysis, aiming to solve the technical problem in the existing technology that it is difficult to accurately extract the peeling interference signal under the complex working conditions of compressor blade coating peeling, especially in the static and dynamic balance test environment of high speed and high frequency vibration, and it is impossible to achieve accurate modeling and compensation of the disturbance in the peeling area.

[0004] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a static and dynamic balance test method for compressor blades based on data analysis.

[0005] The static and dynamic balance test method of the compressor blade based on data analysis includes:

[0006] Step S10: Obtain the three-dimensional point cloud data P(x, y, z) of the machine compressor blade through the laser scanning device, (x, y, z) represents the three-dimensional point coordinates, and obtain the compressor blade scanning coating thickness T based on the three-dimensional point cloud data of the machine compressor blade scanned (x,y), combined with the preset compressor blade standard coating thickness T ideal (x, y) is calculated to obtain the compressor blade coating thickness deviation matrix ΔT(x, y);

[0007] Step S20: Preset the compressor blade thickness peeling threshold T th, based on the compressor blade thickness peeling threshold T th The compressor blade coating peeling area Ω is determined by the compressor blade coating thickness deviation matrix ΔT(x, y), and the total area of the compressor blade peeling area is calculated based on the compressor blade coating peeling area Ω; the airflow velocity when the compressor blade is running is obtained, and the total area of the compressor blade peeling area A is calculated. Ω As a global correction factor, the compressor blade aerodynamic disturbance model P is established by combining the airflow velocity when the compressor blade is running. Ω (x,y);

[0008] Step S30: Use a multi-sensor array to collect the multi-directional compressor blade vibration signal x(t) at time t during the operation of the compressor blade, use a mixed signal separation method to decompose the multi-directional compressor blade vibration signal x(t) into the compressor blade peeling interference signal and other vibration signals, and introduce the peeling signal feature enhancement factor W k Extract the high-frequency component x of the compressor blade peeling interference signal Ω (t);

[0009] Step S40: Combine the compressor blade aerodynamic disturbance model P Ω (x,y) and the high-frequency component x of the compressor blade peeling interference signal Ω (t) generating a compressor blade dynamic compensation matrix; calculating the current vibration amplitude A(t) and the current vibration frequency f(t) based on the multi-directional compressor blade vibration signal x(t), and calculating the compressor blade vibration amplitude deviation |ΔA(t)| and the compressor blade frequency deviation |Δf(t|) in combination with the preset standard vibration amplitude and standard vibration frequency;

[0010] Step S50: Introduce the balance amplitude and frequency optimization factor λ, set the compressor blade dynamic compensation matrix optimization objective function F, dynamically adjust the compressor blade dynamic compensation matrix to minimize the compressor blade dynamic compensation matrix optimization objective function F, and obtain the optimized compressor blade dynamic compensation matrix M. The optimized compressor blade dynamic compensation matrix M is applied to the static and dynamic balance test of the blade; collect the compensated multi-directional compressor blade vibration signal x in real time comp (t), and compared with the multi-directional compressor blade vibration signal x(t) before compensation, the static and dynamic balance test adjustment completion conditions are set, and the static and dynamic balance test adjustment completion conditions are met, and it is determined that the static and dynamic balance test adjustment is completed.

[0011] Preferably, in step S10, the calculation formula of the compressor blade coating thickness deviation matrix ΔT(x,y) is ΔT(x,y)=T ideal (x,y)-T scanned (x,y).

[0012] Preferably, in step S20, the compressor blade coating peeling area Ω is defined as satisfying the condition |ΔT(x,y)|>T th The area of Ω={(x,y)||ΔT(x,y)|>T th}.

[0013] Preferably, in step S20, the compressor blade aerodynamic disturbance model P Ω The formula for (x,y) is:

[0014]

[0015] Wherein, k is the preset aerodynamic coefficient; A ref is the reference area of the compressor blade peeling area; v is the air flow velocity when the compressor blade is running.

[0016] Preferably, in step S30, the high frequency component x of the compressor blade peeling interference signal Ω The extraction formula of (t) is:

[0017]

[0018] Among them, the IMF k (t) is the kth intrinsic mode function, which is used to decompose the frequency components of the multi-directional compressor blade vibration signal x(t); n is the total number of preset intrinsic mode functions.

[0019] Preferably, in step S50, the static and dynamic balance test adjustment completion conditions are:

[0020] If |ΔA(t)| max and |Δf(t)|>f min , then the balance adjustment is completed, where A max is the preset compressor blade vibration amplitude deviation threshold; f min is the compressor blade frequency deviation threshold.

[0021] Preferably, in step S40, the compressor blade dynamic compensation matrix optimizes the objective function F=|ΔA(t)|+λ·|Δf(t)|.

[0022] The present invention also provides a compressor blade static and dynamic balance test system based on data analysis, comprising:

[0023] The scanning and thickness deviation calculation module is used to obtain the three-dimensional point cloud data P(x, y, z) of the machine compressor blade through the laser scanning device. (x, y, z) represents the three-dimensional point coordinates. The compressor blade scanning coating thickness T is obtained based on the three-dimensional point cloud data of the machine compressor blade. scanned (x,y), combined with the preset compressor blade standard coating thickness T ideal ​(x, y) is calculated to obtain the compressor blade coating thickness deviation matrix ΔT(x, y);

[0024] The peeling area and aerodynamic disturbance modeling module is used to preset the compressor blade thickness peeling threshold T th , based on the compressor blade thickness peeling threshold T th The compressor blade coating peeling area Ω is determined by the compressor blade coating thickness deviation matrix ΔT(x, y), and the total area of the compressor blade peeling area is calculated based on the compressor blade coating peeling area Ω; the airflow velocity when the compressor blade is running is obtained, and the total area of the compressor blade peeling area A is calculated. Ω As a global correction factor, the compressor blade aerodynamic disturbance model P is established by combining the airflow velocity when the compressor blade is running. Ω (x,y);

[0025] The vibration signal acquisition and interference signal extraction module is used to use a multi-sensor array to collect the multi-directional compressor blade vibration signal x(t) at time t during the operation of the compressor blade. The multi-directional compressor blade vibration signal x(t) is decomposed into the compressor blade peeling interference signal and other vibration signals using the mixed signal separation method, and the peeling signal feature enhancement factor W is introduced. k Extract the high-frequency component x of the compressor blade peeling interference signal Ω (t);

[0026] Dynamic compensation model construction and deviation calculation module, used to combine the compressor blade aerodynamic disturbance model P Ω (x,y) and the high-frequency component x of the compressor blade peeling interference signal Ω (t) generating a compressor blade dynamic compensation matrix; calculating the current vibration amplitude A(t) and the current vibration frequency f(t) based on the multi-directional compressor blade vibration signal x(t), and calculating the compressor blade vibration amplitude deviation |ΔA(t)| and the compressor blade frequency deviation |Δf(t|) in combination with the preset standard vibration amplitude and standard vibration frequency;

[0027] The real-time optimization and compensation application module is used to introduce the balance amplitude and frequency optimization factor λ, set the compressor blade dynamic compensation matrix optimization objective function F, and dynamically adjust the compressor blade dynamic compensation matrix to obtain the optimized compressor blade dynamic compensation matrix M with the goal of minimizing the compressor blade dynamic compensation matrix optimization objective function F. The optimized compressor blade dynamic compensation matrix M is applied to the static and dynamic balance test of the blade; and real-time acquisition of the compensated multi-directional compressor blade vibration signal x comp (t), and compared with the multi-directional compressor blade vibration signal x(t) before compensation, the static and dynamic balance test adjustment completion conditions are set, and the static and dynamic balance test adjustment completion conditions are met, and it is determined that the static and dynamic balance test adjustment is completed.

[0028] The present invention also provides a computer program product, including a compressor blade static and dynamic balance test program based on data analysis, which implements the compressor blade static and dynamic balance test method based on data analysis when executed by a processor.

[0029] The beneficial effect of the present invention is that compared with the prior art, it is difficult to accurately extract the peeling interference signal under the complex working conditions of compressor blade coating peeling, especially in the static and dynamic balance test environment of high speed and high frequency vibration, and it is impossible to achieve accurate modeling and compensation of the peeling area disturbance. This application realizes the precise adjustment and optimization of the static and dynamic balance test under complex operating conditions through the dynamic modeling of the coating peeling area and the real-time optimization mechanism of the dynamic compensation matrix, thereby avoiding the vibration signal distortion caused by coating peeling and improving the efficiency and accuracy of the balance test. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0031] Figure 1 This is a flow chart of a first embodiment of a compressor blade static and dynamic balance testing method based on data analysis according to the present invention.

[0032] Figure 2 This is a schematic diagram of equipment for a compressor blade static and dynamic balance testing method based on data analysis of the present invention. DETAILED DESCRIPTION

[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0034] Example 1: Figure 1 1 is a flow chart of a first embodiment of a method for testing the static and dynamic balance of compressor blades based on data analysis according to the present invention, and a first embodiment of a method for testing the static and dynamic balance of compressor blades based on data analysis according to the present invention is proposed.

[0035] In a first embodiment, the static and dynamic balancing test method for compressor blades based on data analysis includes:

[0036] Step S10: Obtain the three-dimensional point cloud data P(x, y, z) of the machine compressor blade through the laser scanning device, (x, y, z) represents the three-dimensional point coordinates, and obtain the compressor blade scanning coating thickness T based on the three-dimensional point cloud data of the machine compressor blade scanned (x,y), combined with the preset compressor blade standard coating thickness T ideal (x, y) is calculated to obtain the compressor blade coating thickness deviation matrix ΔT(x, y);

[0037] It should be understood that in order to better identify the thickness deviation of the compressor blade surface coating, the three-dimensional point cloud data obtained by the laser scanning equipment can generate a coating thickness distribution model with extremely high resolution. Compared with the traditional contact measurement method, this non-contact scanning technology not only greatly improves the measurement efficiency, but also avoids potential mechanical damage to the blade surface; by calculating the coating thickness deviation matrix, the present invention can accurately locate the coating peeling area and its distribution characteristics, providing reliable initial data support for subsequent static and dynamic balance adjustments. At the same time, the method is real-time and highly sensitive, and can effectively cope with complex blade surface geometries and small thickness changes, thereby significantly improving the accuracy and adaptability of compressor blade static and dynamic balance tests.

[0038] For example, the coating thickness of a compressor blade under design conditions is T ideal (x, y) = 2.0 mm, the actual coating thickness is measured by laser scanning equipment as T scanned (x,y)=1.5mm, then the coating thickness deviation at this position is ΔT(x,y)=T ideal (x,y)-T scanned (x, y) = 2.0-1.5 = 0.5 mm. By performing the same calculation on the entire blade surface, the thickness deviation matrix ΔT(x, y) can be obtained, as shown in the following example:

[0039]

[0040] Step S20: Preset the compressor blade thickness peeling threshold T th , based on the compressor blade thickness peeling threshold T th The compressor blade coating peeling area Ω is determined by the compressor blade coating thickness deviation matrix ΔT(x, y), and the total area of the compressor blade peeling area is calculated based on the compressor blade coating peeling area Ω; the airflow velocity when the compressor blade is running is obtained, and the total area of the compressor blade peeling area A is calculated. Ω As a global correction factor, the compressor blade aerodynamic disturbance model P is established by combining the airflow velocity when the compressor blade is running. Ω (x,y);

[0041] It should be understood that in order to better describe the overall disturbance characteristics of the peeling area of the compressor blade, the present invention establishes a dynamic aerodynamic disturbance model by combining the thickness deviation matrix and the total area. Compared with the existing technology, this model can not only reflect the local peeling characteristics, but also reflect the global impact of large-area peeling on the overall balance state of the blade; the aerodynamic disturbance model provides a quantitative evaluation of the impact of the peeling area on the aerodynamic performance and static and dynamic balance of the compressor blade, providing reliable data support for subsequent dynamic compensation.

[0042] For example, the coating thickness peeling threshold T th =0.3mm, the thickness deviation matrix of a compressor blade is According to |ΔT(x,y)|>T th The peeling area Ω includes coordinate points (x2, y1), (x2, y2), (x2, y3), (x3, y2), etc. Calculate the total area A of the peeling area Ω , assuming that the grid area corresponding to each point is 1mm 2 , then A Ω =4mm 2 , air flow velocity v = 300m / s, the aerodynamic disturbance model is k=0.02Pa / mm·m 2 / s 2 , reference area A ref =10mm 2 ; For the point (x2, y2), |ΔT(x2, y2)|=0.7mm, and the aerodynamic disturbance is Through this calculation method, the impact of the peeling area on the airflow disturbance can be accurately analyzed.

[0043] Step S30: Use a multi-sensor array to collect the multi-directional compressor blade vibration signal x(t) at time t during the operation of the compressor blade, use a mixed signal separation method to decompose the multi-directional compressor blade vibration signal x(t) into the compressor blade peeling interference signal and other vibration signals, and introduce the peeling signal feature enhancement factor W k Extract the high-frequency component x of the compressor blade peeling interference signal Ω (t);

[0044] It should be understood that in order to better extract the coating peeling interference signal, the present invention combines time domain and frequency domain analysis, decomposes the vibration signal into multiple modal functions through a mixed signal separation method, and introduces a feature enhancement factor for the high-frequency mode to improve the accuracy of signal extraction. The extracted high-frequency component of coating peeling is not only the input data for subsequent dynamic compensation, but also can effectively eliminate the influence of other low-frequency interference signals, thereby improving the accuracy of static and dynamic balance tests.

[0045] Step S40: Combine the compressor blade aerodynamic disturbance model P Ω (x,y) and the high-frequency component x of the compressor blade peeling interference signal Ω (t) generating a compressor blade dynamic compensation matrix; calculating the current vibration amplitude A(t) and the current vibration frequency f(t) based on the multi-directional compressor blade vibration signal x(t), and calculating the compressor blade vibration amplitude deviation |ΔA(t)| and the compressor blade frequency deviation |Δf(t|) in combination with the preset standard vibration amplitude and standard vibration frequency;

[0046] It should be understood that in order to better optimize the static and dynamic balance state of the compressor blades, the present invention adjusts the blades in real time through a dynamic compensation matrix, and combines the vibration amplitude deviation and frequency deviation to realize dynamic feedback control of the vibration signal. By analyzing the changing trend of the deviation value, the dynamic compensation matrix of the compressor blades can be adjusted in real time, so that the blades can still maintain a balanced state under complex operating conditions, thereby improving the adaptability and accuracy of static and dynamic balance tests.

[0047] Step S50: Introduce the balance amplitude and frequency optimization factor λ, set the compressor blade dynamic compensation matrix optimization objective function F, dynamically adjust the compressor blade dynamic compensation matrix to minimize the compressor blade dynamic compensation matrix optimization objective function F, and obtain the optimized compressor blade dynamic compensation matrix M. The optimized compressor blade dynamic compensation matrix M is applied to the static and dynamic balance test of the blade; collect the compensated multi-directional compressor blade vibration signal x in real time comp (t), and compared with the multi-directional compressor blade vibration signal x(t) before compensation, the static and dynamic balance test adjustment completion conditions are set, and the static and dynamic balance test adjustment completion conditions are met, and it is determined that the static and dynamic balance test adjustment is completed.

[0048] It should be noted that the compressor blade dynamic compensation matrix optimization objective function F = |ΔA(t)| + λ·|Δf(t)|.

[0049] It should be understood that in order to better meet the dynamic balance requirements under complex working conditions, the present invention introduces a feedback mechanism, collects the compensated vibration signal in real time, combines it with the optimization result of the objective function, and gradually adjusts the dynamic compensation matrix, thereby achieving continuous optimization of the static and dynamic balance of the blade during operation. This method effectively avoids the balance failure problem caused by changes in working conditions in traditional static compensation methods, and improves the dynamic adaptability of balance adjustment.

[0050] For example, the current vibration amplitude A(t) = 0.7 mm, the design reference vibration amplitude A design = 0.5mm, calculate the vibration amplitude deviation |ΔA(t)| = |A(t)-A design|=|0.7-0.5|=0.2mm; current vibration frequency f(t)=55Hz, design reference frequency f design =50Hz, calculate the vibration frequency deviation |Δf(t)|=|f(t)-f design |=|55-50|=5Hz; Assume that the weight factor λ=0.1, the optimization objective function is F=|ΔA(t)|+λ·|Δf(t)|=0.2+0.1·5=0.7, adjust the dynamic compensation matrix M according to the optimization objective function F, and gradually reduce |ΔA(t)| and |Δf(t)|. After compensation, A(t)=0.55mm, f(t)=51Hz, then: |ΔA(t)|=|0.55-0.5|=0.05min, |Δf(t)|=|51-50|=1Hz, F=0.05+0.1·1=0.15; If the preset threshold condition |ΔA(t| is met max =0.1mm and |Δf(t)| <f min =2Hz, it is determined that the static and dynamic balance adjustment is completed.

[0051] In addition, the present invention provides a compressor blade static and dynamic balance test system based on data analysis, which adopts a compressor blade static and dynamic balance test method based on data analysis in the above embodiment, and can solve the technical problem of a compressor blade static and dynamic balance test based on data analysis. Compared with the prior art, the beneficial effects of the compressor blade static and dynamic balance test system based on data analysis provided by the present invention are the same as the beneficial effects of the compressor blade static and dynamic balance test method based on data analysis provided by the above embodiment, and the other technical features of the compressor blade static and dynamic balance test system based on data analysis are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0052] The present invention provides a compressor blade static and dynamic balance test equipment based on data analysis, please refer to Figure 2 ​A compressor blade static and dynamic balance test device based on data analysis includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the compressor blade static and dynamic balance test method based on data analysis in the above-mentioned embodiment 1. A compressor blade static and dynamic balance test device based on data analysis in an embodiment of the present invention may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. A compressor blade static and dynamic balance test device based on data analysis is merely an example and should not impose any limitations on the functions and scope of use of the embodiments of the present invention. A data analysis-based static and dynamic balancing test device for compressor blades may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in a read-only memory (ROM) 1002 or programs loaded from a storage device 1003 into a random access memory (RAM) 1004. RAM 1004 also stores various programs and data required for the operation of the data analysis-based static and dynamic balancing test device for compressor blades. Processing device 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, hard disk, etc.; and communication devices 1009. Communication devices 1009 can allow a data analysis-based static and dynamic balancing test device for compressor blades to communicate wirelessly or wired with other devices to exchange data. While the figure shows a data analysis-based static and dynamic balancing test device for compressor blades with various systems, it should be understood that not all of the illustrated systems are required to be implemented or present. More or fewer systems may alternatively be implemented or present.

[0053] The present invention also provides a computer program product comprising a computer program that, when executed by a processor, implements the steps of the aforementioned method for testing the static and dynamic balance of compressor blades based on data analysis. The computer program product provided by the present invention can solve the technical problem of testing the static and dynamic balance of compressor blades based on data analysis. Compared to the prior art, the beneficial effects of the computer program product provided by the present invention are the same as those of the method for testing the static and dynamic balance of compressor blades based on data analysis provided in the aforementioned embodiment, and are not further elaborated here.

[0054] In particular, according to the embodiments disclosed in the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present invention are performed.

[0055] It should be understood that the various parts disclosed in the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any appropriate manner in any one or more embodiments or examples.

[0056] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A static and dynamic balance test method for compressor blades based on data analysis, characterized in that: Methods include: Step S10: Obtain the three-dimensional point cloud data P(x, y, z) of the machine compressor blade through the laser scanning device, (x, y, z) represents the three-dimensional point coordinates, and obtain the compressor blade scanning coating thickness T based on the three-dimensional point cloud data of the machine compressor blade scanned (x,y), combined with the preset compressor blade standard coating thickness T ideal (x, y) is calculated to obtain the compressor blade coating thickness deviation matrix ΔT(x, y); Step S20: Preset the compressor blade thickness peeling threshold T th , based on the compressor blade thickness peeling threshold T th The compressor blade coating peeling area Ω is determined by the compressor blade coating thickness deviation matrix ΔT(x, y), and the total area of the compressor blade peeling area is calculated based on the compressor blade coating peeling area Ω; the airflow velocity when the compressor blade is running is obtained, and the total area of the compressor blade peeling area A is calculated. Ω As a global correction factor, the compressor blade aerodynamic disturbance model P is established by combining the airflow velocity when the compressor blade is running. Ω (x,y); Step S30: Use a multi-sensor array to collect the multi-directional compressor blade vibration signal x(t) at time t during the operation of the compressor blade, use a mixed signal separation method to decompose the multi-directional compressor blade vibration signal x(t) into the compressor blade peeling interference signal and other vibration signals, and introduce the peeling signal feature enhancement factor W k Extract the high-frequency component x of the compressor blade peeling interference signal Ω (t); Step S40: Combine the compressor blade aerodynamic disturbance model P Ω (x,y) and the high-frequency component x of the compressor blade peeling interference signal Ω (t) generating a compressor blade dynamic compensation matrix; calculating the current vibration amplitude A(t) and the current vibration frequency f(t) based on the multi-directional compressor blade vibration signal x(t), and calculating the compressor blade vibration amplitude deviation |ΔA(t)| and the compressor blade frequency deviation |Δf(t|) in combination with the preset standard vibration amplitude and standard vibration frequency; Step S50: Introduce the balance amplitude and frequency optimization factor λ, set the compressor blade dynamic compensation matrix optimization objective function F, dynamically adjust the compressor blade dynamic compensation matrix to minimize the compressor blade dynamic compensation matrix optimization objective function F, and obtain the optimized compressor blade dynamic compensation matrix M. The optimized compressor blade dynamic compensation matrix M is applied to the static and dynamic balance test of the blade; collect the compensated multi-directional compressor blade vibration signal x in real time comp (t), and compared with the multi-directional compressor blade vibration signal x(t) before compensation, the static and dynamic balance test adjustment completion conditions are set, and the static and dynamic balance test adjustment completion conditions are met, and it is determined that the static and dynamic balance test adjustment is completed.

2. A compressor blade static and dynamic balance test method based on data analysis according to claim 1, characterized in that: In step S10, the calculation formula of the compressor blade coating thickness deviation matrix ΔT(x,y) is ΔT(x,y)=T ideal (x,y)-T scanned (x,y).

3. The method for testing static and dynamic balance of compressor blades based on data analysis according to claim 1, characterized in that: In step S20, the compressor blade coating peeling area Ω is defined as satisfying the condition |ΔT(x,y)| > T th in the region, Ω = {(x, y) ∣ |ΔT(x, y)| > T th}.

4. The method for testing static and dynamic balance of compressor blades based on data analysis according to claim 1, characterized in that: In step S20, the compressor blade aerodynamic disturbance model P Ω The formula for (x,y) is: Wherein, k is the preset aerodynamic coefficient; A ref is the reference area of the compressor blade peeling area; v is the air flow velocity when the compressor blade is running.

5. The method for testing static and dynamic balance of compressor blades based on data analysis according to claim 1, characterized in that: In step S30, the high frequency component x of the compressor blade peeling interference signal Ω The extraction formula of (t) is: Among them, the IMF k (t) is the kth intrinsic mode function, which is used to decompose the frequency components of the multi-directional compressor blade vibration signal x(t); n is the total number of preset intrinsic mode functions.

6. The method for testing static and dynamic balance of compressor blades based on data analysis according to claim 1, characterized in that: In step S50, the static and dynamic balance test adjustment completion conditions are: If |ΔA(t)| max and |Δf(t)|>f min , then the balance adjustment is completed, where A max is the preset compressor blade vibration amplitude deviation threshold; f min is the compressor blade frequency deviation threshold.​ 7. The method for testing static and dynamic balance of compressor blades based on data analysis according to claim 1, characterized in that: In step S40 , the compressor blade dynamic compensation matrix is optimized to obtain an objective function F=|ΔA(t)|+λ·|Δf(t)|.

8. A static and dynamic balance test system for compressor blades based on data analysis, characterized in that: The compressor blade static and dynamic balance test system based on data analysis includes: The scanning and thickness deviation calculation module is used to obtain the three-dimensional point cloud data P(x, y, z) of the machine compressor blade through the laser scanning device. (x, y, z) represents the three-dimensional point coordinates. The compressor blade scanning coating thickness T is obtained based on the three-dimensional point cloud data of the machine compressor blade. scanned (x,y), combined with the preset compressor blade standard coating thickness T ideal (x, y) is calculated to obtain the compressor blade coating thickness deviation matrix ΔT(x, y); The peeling area and aerodynamic disturbance modeling module is used to preset the compressor blade thickness peeling threshold T th , based on the compressor blade thickness peeling threshold T th The compressor blade coating peeling area Ω is determined by the compressor blade coating thickness deviation matrix ΔT(x, y), and the total area of the compressor blade peeling area is calculated based on the compressor blade coating peeling area Ω; the airflow velocity when the compressor blade is running is obtained, and the total area of the compressor blade peeling area A is calculated. Ω As a global correction factor, the compressor blade aerodynamic disturbance model P is established by combining the airflow velocity when the compressor blade is running. Ω (x,y); The vibration signal acquisition and interference signal extraction module is used to use a multi-sensor array to collect the multi-directional compressor blade vibration signal x(t) at time t during the operation of the compressor blade. The multi-directional compressor blade vibration signal x(t) is decomposed into the compressor blade peeling interference signal and other vibration signals using the mixed signal separation method, and the peeling signal feature enhancement factor W is introduced. k Extract the high-frequency component x of the compressor blade peeling interference signal Ω (t); Dynamic compensation model construction and deviation calculation module, used to combine the compressor blade aerodynamic disturbance model P Ω (x,y) and the high-frequency component x of the compressor blade peeling interference signal Ω (t) generating a compressor blade dynamic compensation matrix; calculating the current vibration amplitude A(t) and the current vibration frequency f(t) based on the multi-directional compressor blade vibration signal x(t), and calculating the compressor blade vibration amplitude deviation |ΔA(t)| and the compressor blade frequency deviation |Δf(t|) in combination with the preset standard vibration amplitude and standard vibration frequency; The real-time optimization and compensation application module is used to introduce the balance amplitude and frequency optimization factor λ, set the compressor blade dynamic compensation matrix optimization objective function F, and dynamically adjust the compressor blade dynamic compensation matrix to obtain the optimized compressor blade dynamic compensation matrix M with the goal of minimizing the compressor blade dynamic compensation matrix optimization objective function F. The optimized compressor blade dynamic compensation matrix M is applied to the static and dynamic balance test of the blade; and real-time acquisition of the compensated multi-directional compressor blade vibration signal x comp (t), and compared with the multi-directional compressor blade vibration signal x(t) before compensation, the static and dynamic balance test adjustment completion conditions are set, and the static and dynamic balance test adjustment completion conditions are met, and it is determined that the static and dynamic balance test adjustment is completed.

9. A static and dynamic balance test equipment for compressor blades based on data analysis, characterized in that: The data analysis-based static and dynamic balance test equipment for compressor blades includes: a memory, a processor, and a data analysis-based static and dynamic balance test program for compressor blades stored in the memory and executable on the processor. When the data analysis-based static and dynamic balance test program for compressor blades is executed by the processor, the data analysis-based static and dynamic balance test method for compressor blades described in any one of claims 1 to 7 is implemented.

10. A computer program product, characterized in that The computer program product includes a compressor blade static and dynamic balance test program based on data analysis, and when the compressor blade static and dynamic balance test program based on data analysis is executed by a processor, it implements the compressor blade static and dynamic balance test method based on data analysis described in any one of Claims 1 to 7.

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