Method and system for testing mode of water turbine based on adaptive filtering and signal enhancement

Abstract

This invention discloses a method and system for modal testing of hydro-turbines based on adaptive filtering and signal enhancement. The method includes: acquiring multi-channel vibration signals of the hydro-turbine under in-service operating conditions and simultaneously determining a reference channel; using the reference channel as input, performing adaptive filtering on the multi-channel vibration signals to obtain filtered multi-channel vibration signals; performing independent component analysis on the filtered multi-channel vibration signals to separate structural modal signals and environmental noise; performing sparse time-frequency enhancement processing on the separated structural modal signals to highlight modal characteristic frequency bands and obtain enhanced signals; extracting modal parameters based on the enhanced signals and outputting the extraction results. This method and system can dynamically suppress interference and enhance modal characteristics under complex operating environments, improving the accuracy and robustness of in-service modal testing.

Description

Technical Field

[0001] This invention belongs to the field of hydraulic turbine vibration testing and signal processing technology, and relates to a hydraulic turbine modal testing method and system based on adaptive filtering and signal enhancement. Background Technology

[0002] Modal parameters of a hydro turbine (natural frequencies, damping ratios, and mode shapes) are important indicators reflecting the structural dynamic characteristics of the unit, and their identification results are directly related to operational status monitoring, early fault warning, and life assessment. Traditional modal testing methods mainly include: Shutdown modal testing: Response signals are obtained using an impact hammer or external vibrator, providing relatively clear modal parameters. However, this method requires unit shutdown, impacting production, and cannot reflect the true dynamic characteristics during operation.

[0003] In-service modal testing: Relying on the Output Modal Analysis (OMA) method, modal characteristics are identified from the response signals during operation, avoiding the impact of downtime, and can be carried out under full load, partial load, and other operating conditions. However, in-service test signals are often limited by the following interferences: Power grid interference: The 50Hz power frequency and its harmonics have strong energy and often mask low-frequency modes; Hydraulic disturbances: strong periodic hydraulic pulsations caused by tailrace vortices, blade passage frequency and its harmonics; Operating noise: The combined background noise from the factory and the operating noise from auxiliary equipment results in a low signal-to-noise ratio; Signal aliasing: The frequency bands of structural mode signals and interference signals overlap, making it difficult for traditional filters to separate them.

[0004] Existing methods typically rely on a single bandpass filter or order-synchronous averaging, which can reduce interference to some extent, but have the following shortcomings: The filtering range is fixed, making it difficult to adapt to changes in operating conditions; It cannot effectively separate the mixed components of power frequency, electromagnetic harmonics and environmental noise; Modal features are weakened under low signal-to-noise ratio conditions, resulting in insufficient recognition stability.

[0005] Therefore, there is an urgent need to propose a method that can dynamically suppress interference and enhance modal characteristics in complex operating environments, thereby improving the accuracy and robustness of in-service modal testing. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and system for modal testing of hydro turbines based on adaptive filtering and signal enhancement. This method and system can dynamically suppress interference and enhance modal characteristics under complex operating conditions, thereby improving the accuracy and robustness of in-service modal testing.

[0007] To achieve the above objectives, this invention discloses a method for modal testing of hydro turbines based on adaptive filtering and signal enhancement, comprising: Acquire multi-channel vibration signals of the turbine during its in-service operation and simultaneously determine the reference channel; Using the reference channel as input, the multi-channel vibration signal is subjected to adaptive filtering to obtain the filtered multi-channel vibration signal. Independent component analysis was performed on the filtered multi-channel vibration signal to separate the structural modal signal from the environmental noise. The separated structural modal signals are subjected to sparse time-frequency enhancement processing to highlight the modal characteristic frequency bands, thus obtaining the enhanced signal; Modal parameters are extracted based on the enhanced signal, and the extraction results are output.

[0008] Furthermore, the process of acquiring multi-channel vibration signals of the turbine during its in-service operation and simultaneously determining the reference channel is as follows: The system acquires multi-channel vibration signals of the turbine during its in-service operation and simultaneously collects grid current or voltage signals, using these as reference channels.

[0009] Furthermore, an adaptive noise cancellation method is used to filter the multi-channel vibration signal with the reference channel as input, so as to obtain the filtered multi-channel vibration signal and suppress power frequency and its harmonic interference in real time.

[0010] Furthermore, modal parameters are extracted using a stabilization graph method based on the enhanced signal.

[0011] Furthermore, the process of extracting modal parameters based on the enhanced signal is as follows: Based on the enhanced signal, the natural frequency, damping ratio and mode shape are calculated at different model orders; Cluster the modal points with frequency drift <1%, damping drift <5%, and modal guarantee criterion MAC ≥ 0.9.

[0012] Furthermore, it also includes: Generate drift curves of modal frequencies as they change with operating conditions.

[0013] Furthermore, when the drift exceeds a set threshold, a health warning is triggered.

[0014] This invention discloses a hydraulic turbine modal testing system based on adaptive filtering and signal enhancement, comprising: The acquisition module is used to acquire multi-channel vibration signals of the turbine during its in-service operation and to simultaneously determine the reference channel. The filtering module is used to perform adaptive filtering on the multi-channel vibration signal with the reference channel as input to obtain the filtered multi-channel vibration signal. The analysis module is used to perform independent component analysis on the filtered multi-channel vibration signal to separate the structural modal signal from the environmental noise. The enhancement module is used to perform sparse time-frequency enhancement processing on the separated structural modal signals to highlight the modal characteristic frequency bands and obtain the enhanced signal; The extraction module is used to extract modal parameters based on the enhanced signal and output the extraction results.

[0015] This invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the turbine modal testing method based on adaptive filtering and signal enhancement.

[0016] The present invention discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the turbine modal testing method based on adaptive filtering and signal enhancement.

[0017] The present invention has the following beneficial effects: The turbine modal testing method and system based on adaptive filtering and signal enhancement described in this invention, in practical operation, combines adaptive noise cancellation, independent component analysis, and sparse time-frequency enhancement to dynamically suppress interference such as power frequency harmonics, hydraulic pulsations, and background noise under complex operating environments. This effectively improves the signal-to-noise ratio and stability of modal signals, achieving high-precision identification of natural frequencies, damping ratios, and mode shapes. Compared with traditional filtering or single-mode analysis methods, this invention maintains robustness of identification results under full load, peak shaving, and frequent start-stop conditions, and possesses real-time online updates and health warning functions, demonstrating strong engineering applicability and promotional value. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of the method of the present invention; Figure 2 A comparison chart of the spectrum of in-service signals; Figure 3 The result of VMD decomposition is shown in the figure. Figure 4 This is a graph showing the results of the stable graph identification. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0022] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0023] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0024] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0025] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0027] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0028] Example 1 refer to Figure 1 The turbine modal testing method based on adaptive filtering and signal enhancement described in this invention includes the following steps: 1) Acquire multi-channel vibration signals of the turbine under in-service operation and simultaneously collect grid current or voltage signals, using these as reference channels; Specifically, multi-channel sensors, such as acceleration, displacement, or strain sensors, are deployed during turbine operation to collect vibration signals from the rotor, base, and foundation. Simultaneously, grid voltage or current signals are acquired as reference channels to record unit speed and load parameters. The sampling frequency is set to at least 10 times the main frequency of the original signal to ensure that high-frequency modal components are not distorted.

[0029] 2) Using the adaptive noise cancellation (ANC) method, with the reference channel as input, the multi-channel vibration signal is filtered to obtain the filtered multi-channel vibration signal, so as to suppress power frequency and its harmonic interference in real time; Specifically, a power frequency interference model is constructed using a reference channel, and the weights are dynamically updated through an adaptive filter to achieve real-time suppression of power frequency and harmonic interference. The filter weight update formula is as follows:

[0030] Where w(n) is the nth The filter weights in the next iteration; μ is the step size factor used to adjust the convergence speed and stability; e(n) is the output error signal, representing the difference between the target signal and the filtered output; x(n) is the reference input signal.

[0031] This invention can dynamically track power grid interference, and can effectively suppress its impact even if the power frequency amplitude and phase change with operating conditions.

[0032] 3) Perform independent component analysis (ICA) on the filtered multi-channel vibration signal to separate the structural modal signal from the environmental noise; Even after ANC filtering, the residual signal still contains environmental noise and hydraulic disturbances. This invention uses the ICA algorithm to perform blind source separation on the multi-channel signal.

[0033] Where x represents the observed signal matrix (including structural response and disturbance); W represents the separation matrix, obtained by maximizing non-Gaussianity; and y represents the separated signal matrix, where part of it is the structural modal component.

[0034] The separation criterion uses kurtosis maximization, that is:

[0035] This invention can effectively remove factory noise and random interference while retaining mode-related signal components.

[0036] 4) Perform sparse time-frequency enhancement processing on the separated structural modal signals to highlight the modal characteristic frequency bands and obtain the enhanced signal; To further highlight the modal characteristic frequency bands, a sparse time-frequency representation is performed on the structural signal after ICA separation, using Short Time Fourier Transform (STFT) as follows:

[0037] Where h(τ) represents the window function; X(f,t) represents the time spectrum.

[0038] Calculate energy distribution for:

[0039] Set energy threshold η Extracting high-energy regions Furthermore, the energy bands corresponding to the modes are clustered to enhance modal features.

[0040] 5) Extract modal parameters based on the enhanced signal, including natural frequency, damping ratio and mode shape.

[0041] Based on the enhanced signal, modal parameters are extracted using the stabilization graph method, specifically including: Calculate the natural frequencies, damping ratios, and mode shapes for different model orders; Cluster the modal points with frequency drift <1%, damping drift <5%, and modal guarantee criterion MAC ≥ 0.9; Output the final stable mode parameters.

[0042] 6) Output the results; Output the natural frequency, damping ratio, and mode shape, and generate the drift curve of the mode frequency as a function of operating conditions; When the drift exceeds the set threshold, a health warning is triggered. It should be noted that this invention can be combined with an online monitoring system to achieve real-time updates and long-term trend tracking of modal parameters.

[0043] Example 2 Taking a 100MW bulb turbine as an example, with a unit speed of 125r / min and full-load operation, eight acceleration sensors are installed on the base and foundation, and the grid current signal is collected simultaneously as a reference channel. The specific steps include: 1) Data acquisition and preprocessing: Under the full load operation of the unit, the sampling frequency is set to 2048Hz and the acquisition time is 180s. All channel signals are subjected to DC removal, trend removal and band-limited filtering to ensure the stability of subsequent processing.

[0044] 2) Adaptive Filtering: Using the synchronously acquired grid current signal as a reference input, an LMS adaptive filter is constructed, and the filter weights are updated in real time to eliminate power frequency and harmonic interference. The filtering results show that the energy of the 50Hz and its harmonic components decreases by approximately 15–20 dB, significantly improving the signal-to-noise ratio.

[0045] 3) Independent Component Analysis (ICA) Separation: The 8-channel signal after ANC processing is input into the ICA model, and several independent components are separated by maximizing non-Gaussianity. Among them, some components exhibit broadband random characteristics and are identified as background noise; other components exhibit narrowband modal characteristics and are retained as structural response signals.

[0046] 4) Sparse Time-Frequency Enhancement: Short-Time Fourier Transform (STFT) was performed on the structural response signal obtained from ICA separation to obtain the time-frequency spectrum. Subsequently, an energy threshold was set and a clustering method was applied to extract and enhance the modal frequency bands. The enhanced results show that the first-order mode frequency band is more prominent, and the second and third-order modes form obvious stripes around 15Hz and 28Hz.

[0047] 5) Modal Recognition Results: Based on the sparsely enhanced signal, modal parameters were extracted using the stabilization graph method. The final identified first-order natural frequencies were 8.5Hz, second-order were 15.2Hz, and third-order were 28.0Hz; the corresponding damping ratios were 2.3%, 3.8%, and 4.2%, respectively, and the modal similarity (MAC) values ​​were all greater than 0.9, proving that the method is stable and reliable under complex operating conditions.

[0048] It should be noted that the present invention has the following characteristics: This invention combines adaptive noise cancellation, independent component analysis, and sparse time-frequency enhancement to dynamically suppress interference from power frequency harmonics, hydraulic pulsations, and background noise under complex operating environments. This effectively improves the signal-to-noise ratio and stability of modal signals, achieving high-precision identification of natural frequencies, damping ratios, and mode shapes. Compared to traditional filtering or single-mode analysis methods, this invention maintains robustness in identification results under full load, peak shaving, and frequent start-stop conditions. It also features real-time online updates and health warning functions, demonstrating strong engineering applicability and widespread application value.

[0049] Example 3 The turbine modal testing system based on adaptive filtering and signal enhancement of the present invention includes: The acquisition module is used to acquire multi-channel vibration signals of the turbine during its in-service operation and to simultaneously determine the reference channel. The filtering module is used to perform adaptive filtering on the multi-channel vibration signal with the reference channel as input to obtain the filtered multi-channel vibration signal. The analysis module is used to perform independent component analysis on the filtered multi-channel vibration signal to separate the structural modal signal from the environmental noise. The enhancement module is used to perform sparse time-frequency enhancement processing on the separated structural modal signals to highlight the modal characteristic frequency bands and obtain the enhanced signal; The extraction module is used to extract modal parameters based on the enhanced signal and output the extraction results.

[0050] The module division in this embodiment is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in each embodiment of this application can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0051] Example 4 A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the adaptive filtering and signal enhancement-based hydraulic turbine modal testing method. For example, the method includes: acquiring multi-channel vibration signals of the hydraulic turbine during its in-service operation and simultaneously determining a reference channel; using the reference channel as input, performing adaptive filtering on the multi-channel vibration signals to obtain filtered multi-channel vibration signals; performing independent component analysis on the filtered multi-channel vibration signals to separate structural modal signals and environmental noise; performing sparse time-frequency enhancement processing on the separated structural modal signals to highlight modal characteristic frequency bands and obtain enhanced signals; extracting modal parameters based on the enhanced signals and outputting the extraction results. The memory may include main memory, such as high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device. The processor, network interface, and memory are interconnected via an internal bus, which can be an industry standard architecture bus, a peripheral component interconnection standard bus, an extended industry standard architecture bus, etc. The bus can be divided into address bus, data bus, control bus, etc. The memory is used to store programs; specifically, the program may include program code, which includes computer operation instructions. The memory may include main memory and non-volatile memory, and provides instructions and data to the processor.

[0052] Example 5 A computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the adaptive filtering and signal enhancement-based hydraulic turbine modal testing method. For example, the method includes: acquiring multi-channel vibration signals of the hydraulic turbine under in-service operation and simultaneously determining a reference channel; using the reference channel as input, performing adaptive filtering on the multi-channel vibration signals to obtain filtered multi-channel vibration signals; performing independent component analysis on the filtered multi-channel vibration signals to separate structural modal signals and environmental noise; performing sparse time-frequency enhancement processing on the separated structural modal signals to highlight modal characteristic frequency bands and obtain enhanced signals; extracting modal parameters based on the enhanced signals and outputting the extraction results. Specifically, the computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0053] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0054] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0055] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0056] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0057] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and disclosure of the invention. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0058] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

[0059] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Any simple modifications, alterations, or equivalent structural changes made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for modal testing of hydro turbines based on adaptive filtering and signal enhancement, characterized in that, include: Acquire multi-channel vibration signals of the turbine during its in-service operation and simultaneously determine the reference channel; Using the reference channel as input, the multi-channel vibration signal is subjected to adaptive filtering to obtain the filtered multi-channel vibration signal. Independent component analysis was performed on the filtered multi-channel vibration signal to separate the structural modal signal from the environmental noise. The separated structural modal signals are subjected to sparse time-frequency enhancement processing to highlight the modal characteristic frequency bands, thus obtaining the enhanced signal; Modal parameters are extracted based on the enhanced signal, and the extraction results are output.

2. The method for modal testing of hydro-turbines based on adaptive filtering and signal enhancement according to claim 1, characterized in that, The process of acquiring multi-channel vibration signals of the turbine during its in-service operation and simultaneously determining the reference channel is as follows: The system acquires multi-channel vibration signals of the turbine during its in-service operation and simultaneously collects grid current or voltage signals, using these as reference channels.

3. The method for modal testing of hydro-turbines based on adaptive filtering and signal enhancement according to claim 1, characterized in that, An adaptive noise cancellation method is used to filter the multi-channel vibration signal with a reference channel as input, resulting in a filtered multi-channel vibration signal to suppress power frequency and its harmonic interference in real time.

4. The method for modal testing of hydro-turbines based on adaptive filtering and signal enhancement according to claim 1, characterized in that, Based on the enhanced signal, modal parameters are extracted using the stabilization graph method.

5. The method for modal testing of hydro-turbines based on adaptive filtering and signal enhancement according to claim 1, characterized in that, The process of extracting modal parameters based on enhanced signals is as follows: Based on the enhanced signal, the natural frequency, damping ratio and mode shape are calculated at different model orders; Cluster the modal points with frequency drift <1%, damping drift <5%, and modal guarantee criterion MAC ≥ 0.

9.

6. The method for modal testing of hydro-turbines based on adaptive filtering and signal enhancement according to claim 1, characterized in that, Also includes: Generate drift curves of modal frequencies as they change with operating conditions.

7. The method for modal testing of hydro-turbines based on adaptive filtering and signal enhancement according to claim 6, characterized in that, When the drift exceeds the set threshold, a health warning is triggered.

8. A hydraulic turbine modal testing system based on adaptive filtering and signal enhancement, characterized in that, include: The acquisition module is used to acquire multi-channel vibration signals of the turbine during its in-service operation and to simultaneously determine the reference channel. The filtering module is used to perform adaptive filtering on the multi-channel vibration signal with the reference channel as input to obtain the filtered multi-channel vibration signal. The analysis module is used to perform independent component analysis on the filtered multi-channel vibration signal to separate the structural modal signal from the environmental noise. The enhancement module is used to perform sparse time-frequency enhancement processing on the separated structural modal signals to highlight the modal characteristic frequency bands and obtain the enhanced signal; The extraction module is used to extract modal parameters based on the enhanced signal and output the extraction results.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the turbine modal testing method based on adaptive filtering and signal enhancement as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the turbine modal testing method based on adaptive filtering and signal enhancement as described in any one of claims 1-7.

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