Surge detection method for a centrifugal compressor

Abstract

This invention relates to the technical field of centrifugal compressors, and in particular to a surge detection method for centrifugal compressors. The method includes: real-time acquisition and filtering of the compressor's current signal based on a sliding window; extraction and calculation of time-domain and frequency-domain characteristic parameters based on the filtered discrete current signal of each sliding window; comparative analysis of the time-domain and frequency-domain characteristic parameters under two adjacent sliding windows to obtain a surge characteristic factor; calculation of the surge factor under the current sliding window based on the surge characteristic factor; if the surge factor is greater than or equal to a preset surge threshold, it is determined that the compressor has experienced surge; outputting multi-level alarm signals based on the magnitude of the surge factor, and determining whether the surge has been eliminated based on changes in the time-domain and frequency-domain characteristic parameters to decide whether to stop the warning or shut down the compressor for protection. This invention comprehensively considers multiple characteristic information, significantly improving the accuracy and reliability of surge detection.

Description

Technical Field

[0001] This invention relates to the technical field of centrifugal compressors, and in particular to a method for detecting surge in centrifugal compressors. Background Technology

[0002] Centrifugal compressors are widely used in industrial and commercial fields such as chemical, metallurgical, and heating sectors, and are a type of turbine compressor. Under certain operating conditions, centrifugal compressors can experience surge, characterized by significant vibration and loud noise, along with periodic and large fluctuations in compressor operating parameters. Surge significantly affects the operational stability of centrifugal compressors and can, in severe cases, directly damage equipment parts. Therefore, surge prevention control is crucial for centrifugal compressors.

[0003] Common surge control methods involve regressing surge curves based on test data or software data, and then controlling relevant instruments to limit the operating conditions of the centrifugal compressor within the surge curve range, thereby preventing surge from occurring. However, due to test errors or theoretical calculation errors, the obtained surge curves are not entirely consistent with the actual operating conditions. Therefore, a method for real-time surge detection and identification is needed.

[0004] In existing technologies, manual surge detection methods mainly rely on observing various operating parameters of the centrifugal compressor and making judgments based on experience. Automatic surge detection methods mainly detect and identify surges through a single time-domain amplitude characteristic, but the time-domain amplitude characteristic changes significantly during system startup, loading, or unloading, which can easily lead to misjudgments. Summary of the Invention

[0005] To overcome the problems in the prior art, this invention proposes a surge detection method for centrifugal compressors.

[0006] The technical solution of the present invention to solve the above-mentioned technical problems is as follows: This invention provides a method for detecting surge in a centrifugal compressor, comprising the following steps: Step 100: Preset a sliding window, collect the compressor's current signal in real time based on the sliding window and perform filtering processing to obtain discrete current signals after filtering of each sliding window; Step 200: Based on the discrete current signal after filtering by each sliding window, extract and calculate the time-domain and frequency-domain feature parameters, which include amplitude feature parameters, periodicity feature parameters, fundamental frequency feature parameters, and harmonic proportion feature parameters; Step 300: Based on the time-domain and frequency-domain characteristic parameters under two adjacent sliding windows and the preset threshold parameters, the surge characteristic factor is obtained by comparative analysis; Step 400: Calculate the surge factor under the current sliding window based on the surge characteristic factor. If the surge factor is greater than or equal to the preset surge threshold, it is determined that the compressor has experienced a surge phenomenon. Step 500: Output multi-level alarm signals based on the magnitude of the surge factor; at the same time, record the time-domain and frequency-domain characteristic parameters of the current data in the current sliding window, and determine whether the surge has been eliminated based on the changes in the time-domain and frequency-domain characteristic parameters, so as to decide whether to stop the warning or stop the machine protection.

[0007] Further, step 200 includes: performing time-domain signal analysis on the discrete current signal after each sliding window filtering process, and obtaining the amplitude characteristic parameters of each sliding window by calculating the mean and standard deviation of the discrete current signal after each sliding window filtering process.

[0008] Furthermore, step 200 also includes: Based on the filtered discrete current signal and its mean value under each sliding window, the autocorrelation function of the filtered discrete current signal under each sliding window is calculated, and the autocorrelation function is normalized. Set peak detection conditions and find the time delay corresponding to the first significant peak based on the normalized autocorrelation function, i.e., the peak delay; Based on the peak delay, the fundamental period and frequency are calculated; the first significant peak obtained is used as the periodic characteristic parameter, and the fundamental frequency is used as the fundamental frequency characteristic parameter.

[0009] Furthermore, step 200 also includes: The calculated fundamental frequency characteristic parameters are used as the fundamental frequency for harmonic analysis; if the fundamental frequency is not 0, the signal amplitude of the fundamental frequency, the signal amplitude of the second harmonic, and the signal amplitude of the third harmonic are calculated respectively based on the single-frequency discrete Fourier transform method. The harmonic proportion characteristic parameters are calculated based on the signal amplitude of the fundamental frequency, the signal amplitude of the second harmonic, and the signal amplitude of the third harmonic.

[0010] Furthermore, in step 300, the surge characteristic factor includes an amplitude characteristic factor, a periodic characteristic factor, a fundamental frequency characteristic factor, and a harmonic proportion characteristic factor; The periodic characteristic parameter of the next sliding window in adjacent time sliding windows is the periodic characteristic factor. Calculate the proportional values ​​of amplitude characteristic parameters, fundamental frequency characteristic parameters, and harmonic proportion characteristic parameters of adjacent time sliding windows, and then normalize them using a normalization function to obtain amplitude characteristic factor, fundamental frequency characteristic factor, and harmonic proportion characteristic factor.

[0011] Further, in step 400, calculating the surge factor under the current sliding window based on the surge feature factor includes: calculating the surge factor under the current sliding window based on the surge feature factor and the preset weight coefficients of the corresponding surge feature factor; wherein, the sum of the weight coefficients of the surge feature factor is 1, and the weight coefficient of each surge feature factor is greater than 0.

[0012] Further, in step 400, if the surge factor is greater than or equal to the preset surge threshold, it is determined that the compressor has experienced a surge phenomenon, including: The surge threshold is divided into a warning threshold and a shutdown threshold. The shutdown threshold is greater than the warning threshold. If the surge factor is greater than or equal to the warning threshold, it is determined that the compressor has experienced a surge phenomenon.

[0013] Furthermore, in step 500, outputting multi-level alarm signals based on the magnitude of the surge factor includes: When the surge factor is greater than or equal to the warning threshold and less than the shutdown threshold, a warning signal is output; When the surge factor is greater than or equal to the shutdown threshold, a shutdown signal is output.

[0014] Further, in step 500, recording the time-domain and frequency-domain characteristic parameters of the current data within the current sliding window, and determining whether surge has been eliminated based on changes in the time-domain and frequency-domain characteristic parameters to decide whether to stop the warning or shutdown protection includes: Record the time-domain and frequency-domain characteristic parameters of the current data within the current sliding window. The time-domain and frequency-domain characteristic parameters include amplitude characteristic parameters, fundamental frequency characteristic parameters, and harmonic proportion characteristic parameters. If the time-domain and frequency-domain characteristic parameters meet the preset conditions for normal operation, it is considered that the surge has been significantly eliminated and the warning signal is stopped. Otherwise, it is considered that the surge has not been suppressed and a shutdown signal is output.

[0015] Compared with the prior art, the present invention has the following technical effects: (1) This invention acquires and processes compressor current signals in real time through a preset sliding window, extracts characteristic parameters such as amplitude, periodicity, fundamental frequency, and harmonic ratio from multiple dimensions in the time and frequency domains, and calculates surge characteristic factors based on the characteristic parameters of adjacent sliding windows, thereby obtaining surge factors to judge surge phenomena. Compared with traditional automatic detection methods based on single time-domain amplitude characteristics, this scheme comprehensively considers multiple characteristic information, which can effectively avoid misjudgments caused by changes in time-domain amplitude under operating conditions such as system startup, loading, or unloading, and significantly improves the accuracy and reliability of surge detection.

[0016] (2) This invention sets warning thresholds and shutdown thresholds, and outputs multi-level alarm signals based on the surge factor. When the surge factor is within different ranges, a warning signal or a shutdown signal is output respectively. At the same time, it judges whether the surge has been eliminated based on the recorded changes in time-domain and frequency-domain characteristic parameters, so as to decide whether to stop the warning or shutdown protection. This multi-level, dynamic judgment and processing mechanism makes the anti-surge control more flexible, which can issue warnings for minor surges in a timely manner, and take emergency shutdown protection measures for severe surges, thus ensuring the safe and stable operation of the compressor. Attached Figure Description

[0017] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic flowchart of a surge detection method for a centrifugal compressor according to the present invention. Detailed Implementation

[0019] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the specific implementation methods, structures, features, and effects of the technical solutions proposed according to the present invention are described in detail below with reference to the accompanying drawings and preferred embodiments. Specific features, structures, or characteristics in one or more embodiments may be combined in any suitable form. Unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0020] In this embodiment, refer to Figure 1 A surge detection method for centrifugal compressors is provided, comprising the following steps: Step 100: Preset a sliding window, collect the compressor's current signal in real time based on the sliding window and perform filtering processing to obtain discrete current signals after filtering of each sliding window; Step 200: Based on the discrete current signal after filtering by each sliding window, extract and calculate the time-domain and frequency-domain feature parameters, which include amplitude feature parameters, periodicity feature parameters, fundamental frequency feature parameters, and harmonic proportion feature parameters; Step 300: Based on the time-domain and frequency-domain characteristic parameters under two adjacent sliding windows and the preset threshold parameters, the surge characteristic factor is obtained by comparative analysis; Step 400: Calculate the surge factor under the current sliding window based on the surge characteristic factor. If the surge factor is greater than or equal to the preset surge threshold, it is determined that the compressor has experienced a surge phenomenon. Step 500: Output multi-level alarm signals based on the magnitude of the surge factor; at the same time, record the time-domain and frequency-domain characteristic parameters of the current data in the current sliding window, and determine whether the surge has been eliminated based on the changes in the time-domain and frequency-domain characteristic parameters, so as to decide whether to stop the warning or stop the machine protection.

[0021] The following is a detailed explanation of each of the above steps: Step 100: Set a sliding window, collect the compressor's current signal in real time based on the sliding window and perform filtering processing to obtain discrete current signals after filtering of each sliding window.

[0022] The size of the preset sliding window is determined by the sampling frequency and the sampling time length, i.e.: ; In the above formula, Indicates the size of the sliding window; Indicates the sampling frequency; This indicates the sampling time length. The sampling period and acquisition time length are set based on the possible period values ​​of the surge signal.

[0023] After acquiring the current signal, the acquired current signals of each sliding window are subjected to first-order low-pass filtering to remove the influence of high-frequency noise, resulting in discrete current signals after filtering each sliding window. First-order low-pass filtering is a commonly used signal processing method that effectively removes high-frequency noise components from the signal while retaining useful low-frequency information, making subsequent feature extraction and analysis more accurate and reliable.

[0024] Step 200: Based on the discrete current signal after filtering by each sliding window, extract and calculate the time-domain and frequency-domain feature parameters, which include amplitude feature parameters, periodicity feature parameters, fundamental frequency feature parameters, and harmonic proportion feature parameters.

[0025] As an example, this step includes: Step 210: Perform time-domain signal analysis on the discrete current signal after filtering for each sliding window, and obtain the amplitude characteristic parameters of each sliding window by calculating the mean and standard deviation.

[0026] For the The specific steps for calculating amplitude characteristic parameters using a sliding window include: According to the The discrete current signal values ​​after filtering under the nth sliding window are analyzed in the time domain. By calculating the mean and standard deviation, the nth value is obtained. Amplitude characteristic parameters under a sliding window Specifically, it includes: Let the first Discrete current signal after sliding window filtering for: ; In the above formula, This represents the sampled value of the discrete current signal at the nth sampling point, where... .

[0027] Calculate the first The mean of discrete current signals within a sliding window : ; When a compressor experiences surge, the current signal exhibits large-amplitude periodic oscillations, with the oscillation amplitude significantly increased compared to normal operating conditions. Calculate the standard deviation of the discrete current signal. The calculation formula is as follows: ; Standard deviation Standard deviation can measure the dispersion of a set of data, but when performing compressor surge detection, it is necessary to compare the dispersion of multiple different sets of data; therefore, it cannot be directly used for analysis. Here, we discuss the standard deviation... Perform dimensionless processing, based on the first Calculate the mean and standard deviation of the discrete current signal within each sliding window. The amplitude characteristic parameters under each sliding window are calculated using the following formulas: ; In the above formula, Indicates the first Amplitude characteristic parameters under a sliding window.

[0028] Similarly, calculate the first... Amplitude characteristic parameters under a sliding window .

[0029] Step 220: Perform periodic analysis on the discrete current signal after filtering for each sliding window; obtain the periodic characteristic parameters under each sliding window by calculating the autocorrelation function of the discrete current signal, and obtain the fundamental frequency characteristic parameters by finding the first significant peak of the autocorrelation coefficient.

[0030] Based on the filtered discrete current signal and its mean value under each sliding window, the autocorrelation function of the filtered discrete current signal under each sliding window is calculated, and the autocorrelation function is normalized. Peak detection conditions are set, and the time delay corresponding to the first significant peak value, i.e., the peak delay, is found based on the normalized autocorrelation function. The fundamental period and frequency are calculated based on the peak delay. The calculated first significant peak value is then... As a periodic characteristic parameter, the fundamental frequency is used as the fundamental frequency characteristic parameter.

[0031] For the The specific steps for calculating the periodic characteristic parameters and fundamental frequency characteristic parameters using a sliding window include: Based on the Calculate the discrete current signal and its mean after filtering under the sliding window. The autocorrelation function of the discrete current signal after filtering under a sliding window. The current signal of a centrifugal compressor contains a large proportion of DC component. When calculating the autocorrelation function, the actual signal needs to be subtracted from the signal mean to avoid the influence of the DC component. The specific calculation method of the autocorrelation function is as follows: ; In the above formula, Indicates a time delay of The autocorrelation function value at time; Indicates the time delay parameter; Represents discrete current signal Move backward on the timeline The signal obtained afterward.

[0032] when When = 0, the autocorrelation function value Let be the total signal power. To standardize the periodicity measurement under different sliding windows, the autocorrelation function above is normalized as follows.

[0033] ; In the above formula, This represents the value of the autocorrelation function after normalization.

[0034] Set peak detection conditions and apply them to the normalized autocorrelation function. To find the time delay corresponding to the first significant peak, the following peak detection conditions must be met: First, the autocorrelation function value at the significant peak must be greater than the adjacent autocorrelation function values, ensuring that a local maximum is found. Second, the autocorrelation function value at the significant peak must be greater than a preset threshold. This preset threshold is set according to the specific application and signal characteristics to exclude insignificant fluctuations and focus only on truly meaningful peaks. The time delay corresponding to the first peak that meets the above peak detection conditions is called the peak delay. .

[0035] Based on peak delay The fundamental period and frequency are calculated. Specifically, the fundamental period is obtained by multiplying the derivative of the sampling frequency by the peak delay, and the fundamental frequency is the reciprocal of the fundamental period. The first significant peak value obtained is then used to calculate the fundamental period. As a periodic characteristic parameter The fundamental frequency is used as a fundamental frequency characteristic parameter. .

[0036] Similarly, we obtain the first... Periodic feature parameters under a sliding window Fundamental frequency characteristic parameters .

[0037] Step 230: Perform single-frequency discrete Fourier transform calculation and analysis on the discrete current signal after filtering for each sliding window to obtain the harmonic proportion characteristic parameters of each sliding window.

[0038] For the The discrete current signal after filtering under the sliding window is analyzed by performing single-frequency discrete Fourier transform calculation to obtain the first... Harmonic proportion characteristic parameters under a sliding window Specifically, it includes: The calculated fundamental frequency characteristic parameters The fundamental frequency is used for harmonic analysis; if the fundamental frequency is not 0, the signal amplitude of the fundamental frequency is calculated based on the single-frequency discrete Fourier transform method. 2 times the frequency signal amplitude and the amplitude of a 3 times frequency The calculation steps are as follows: For a finite discrete signal, its corresponding Discrete Fourier Transform (DFT) is: ; In the above formula, For the first The complex values ​​of each frequency component For frequency index, compared with actual frequency The correspondence is .

[0039] The complete discrete Fourier transform calculation is complex, affecting the efficiency of compressor surge analysis, while the aforementioned fundamental frequency characteristic parameters... The fundamental frequency of the discrete current signal has already been obtained through the autocorrelation function during the calculation, so it is not necessary to calculate the fundamental frequency based on DFT here. When the compressor experiences surge, the current signal will exhibit obvious distortion characteristics, that is, the proportion of harmonics is significantly higher than that of the normal signal, and it is mainly the low-order harmonics.

[0040] To calculate the amplitude of a fundamental and harmonic signal at a specified frequency, a single-frequency-point discrete Fourier transform calculation method is provided, including: expanding the discrete Fourier transform described above and removing the frequency index. The value restrictions will and actual frequency Substituting the relational expression into the original formula and rearranging, we obtain the formula for calculating the spectral components of any specified frequency. The specific calculation formula is as follows: ; in, For actual frequency, Sampling frequency, For actual frequency The corresponding components.

[0041] According to the above formula, we get real part and the virtual part They are respectively: ; The signal amplitude at the corresponding frequency in a single-sided spectrum can then be calculated using the following formula. : ; Substituting the frequencies corresponding to the fundamental frequency, second harmonic, and third harmonic into the above formula, we can obtain the corresponding signal amplitudes. , , .

[0042] After calculating the amplitudes of the fundamental and harmonic signals, the characteristic parameters of the harmonic proportions are obtained according to the following formula: ; In the above formula, This represents the characteristic parameter indicating the proportion of harmonics.

[0043] Similarly, the analysis and calculation yielded the first... Harmonic proportion characteristic parameters under a sliding window .

[0044] Step 300: Based on the time-domain and frequency-domain characteristic parameters under two adjacent sliding windows and the preset threshold parameters, a comparative analysis is performed to obtain the surge characteristic factor, which includes the amplitude characteristic factor. Periodic characteristic factors Fundamental frequency characteristic factor and harmonic proportion characteristic factor .

[0045] The periodicity is an inherent characteristic of the compressor during surge and does not need to be compared with the previous sliding window, therefore the periodicity is... Periodic characteristic parameters of a sliding window That is, periodic characteristic factor Periodic characteristic factors Since the range is already between 0 and 1, normalization is not required here.

[0046] When surge occurs, the amplitude of the current waveform will increase significantly, the fundamental frequency will decrease significantly, and the proportion of harmonics will increase significantly. The proportional values ​​of the amplitude characteristic parameter, fundamental frequency characteristic parameter, and harmonic proportion characteristic parameter for adjacent time sliding windows are calculated sequentially. , , .

[0047] Because multiple parameters have different physical meanings, the ratio value cannot be directly used as a characteristic factor for judging surge. To achieve normalization of surge characteristic parameters, a normalization function based on an improved form of the Sigmoid function is proposed, with the following form: ; in, and This function adjusts the parameters used to regulate the curve's steepness and center point position. It modifies the Sigmod function... Axis translation, Axis translation and scaling transformations normalize the scaling values ​​and ensure the continuity of the function when the scaling value is 1.

[0048] Step 400: Calculate the surge factor under the current sliding window based on the surge characteristic factor. If the surge factor is greater than or equal to the preset surge threshold, it is determined that the compressor has experienced a surge phenomenon.

[0049] Calculate the surge factor under the current sliding window based on the surge characteristic factor and its corresponding weight coefficient. : ; In the above formula, The weighting coefficients corresponding to the surge characteristic factor are preset parameters and meet the following requirements: ; The surge threshold is divided into a warning threshold and a shutdown threshold, where the shutdown threshold is greater than the warning threshold; if the surge factor... If the value is greater than or equal to the warning threshold, it is determined that the compressor has experienced surge.

[0050] Step 500: Based on the magnitude of the surge factor, output multi-level alarm signals and transmit them to the corresponding compressor control system; at the same time, record the time-domain and frequency-domain characteristic parameters of the current data in the current sliding window, and determine whether the surge has been eliminated based on the changes in the time-domain and frequency-domain characteristic parameters, so as to decide whether to stop the warning or stop the machine for protection.

[0051] When surge factor When the surge factor is greater than or equal to the warning threshold and less than the shutdown threshold, the surge is considered minor, and a warning signal is output; when the surge factor... When the value is greater than or equal to the shutdown threshold, a shutdown signal is output to avoid damage to the compressor.

[0052] After a preset delay time, the amplitude characteristic parameter of the current signal within the sliding window is assumed to be... The fundamental frequency characteristic parameters are The characteristic parameters of harmonic proportion are: If the amplitude characteristic parameters meet the preset normalization conditions, it is considered that the surge has been significantly eliminated and the warning signal is stopped; otherwise, it is considered that the surge has not been suppressed, and a shutdown signal is output to protect the equipment. The normalization conditions include: ; In the above formula, , , These are configurable coefficients; This represents the amplitude characteristic parameter of the current signal within the sliding window when an early warning signal is output; This represents the fundamental frequency characteristic parameter of the current signal within the sliding window when an early warning signal is output; This represents the characteristic parameter indicating the harmonic proportion of the current signal within the sliding window when outputting a warning signal.

[0053] The preset time is determined based on the surge period, and the delay time = min(fundamental period multiple, set absolute value), that is, the delay time is the minimum value between the fundamental period multiple and the set absolute value. Wherein, the fundamental period multiple is the [missing value]. The fundamental period obtained from the window analysis is 3-5 times; the absolute value is set for safety reasons and depends on different units. A reference value can be set to 10s-30s.

[0054] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A surge detection method for a centrifugal compressor, characterized by, Includes the following steps: Step 100: Preset a sliding window, collect the compressor's current signal in real time based on the sliding window and perform filtering processing to obtain discrete current signals after filtering of each sliding window; Step 200: Based on the discrete current signal after filtering by each sliding window, extract and calculate the time-domain and frequency-domain feature parameters, which include amplitude feature parameters, periodicity feature parameters, fundamental frequency feature parameters, and harmonic proportion feature parameters; Step 300: Based on the time-domain and frequency-domain characteristic parameters under two adjacent sliding windows and the preset threshold parameters, the surge characteristic factor is obtained by comparative analysis; Step 400: Calculate the surge factor under the current sliding window based on the surge characteristic factor. If the surge factor is greater than or equal to the preset surge threshold, it is determined that the compressor has experienced a surge phenomenon. Step 500: Output multi-level alarm signals based on the magnitude of the surge factor; at the same time, record the time-domain and frequency-domain characteristic parameters of the current data in the current sliding window, and determine whether the surge has been eliminated based on the changes in the time-domain and frequency-domain characteristic parameters, so as to decide whether to stop the warning or stop the machine protection.

2. A surge detection method for a centrifugal compressor according to claim 1, characterized by, Step 200 includes: performing time-domain signal analysis on the discrete current signal after each sliding window filtering process, and obtaining the amplitude characteristic parameters of each sliding window by calculating the mean and standard deviation of the discrete current signal after each sliding window filtering process.

3. The surge detection method for a centrifugal compressor according to claim 2, characterized in that, Step 200 also includes: Based on the filtered discrete current signal and its mean value under each sliding window, the autocorrelation function of the filtered discrete current signal under each sliding window is calculated, and the autocorrelation function is normalized. Set peak detection conditions and find the time delay corresponding to the first significant peak based on the normalized autocorrelation function, i.e., the peak delay; Based on the peak delay, the fundamental period and frequency are calculated; the first significant peak obtained is used as the periodic characteristic parameter, and the fundamental frequency is used as the fundamental frequency characteristic parameter.

4. The surge detection method for a centrifugal compressor according to claim 3, characterized in that, Step 200 also includes: The calculated fundamental frequency characteristic parameters are used as the fundamental frequency for harmonic analysis; if the fundamental frequency is not 0, the signal amplitude of the fundamental frequency, the signal amplitude of the second harmonic, and the signal amplitude of the third harmonic are calculated respectively based on the single-frequency discrete Fourier transform method. The harmonic proportion characteristic parameters are calculated based on the signal amplitude of the fundamental frequency, the signal amplitude of the second harmonic, and the signal amplitude of the third harmonic.

5. The surge detection method for a centrifugal compressor according to claim 1, characterized in that, In step 300, the surge characteristic factor includes an amplitude characteristic factor, a periodic characteristic factor, a fundamental frequency characteristic factor, and a harmonic proportion characteristic factor. The periodic characteristic parameter of the next sliding window in adjacent time sliding windows is the periodic characteristic factor. Calculate the proportional values ​​of amplitude characteristic parameters, fundamental frequency characteristic parameters, and harmonic proportion characteristic parameters of adjacent time sliding windows, and then normalize them using a normalization function to obtain amplitude characteristic factor, fundamental frequency characteristic factor, and harmonic proportion characteristic factor.

6. The surge detection method for a centrifugal compressor according to claim 1, characterized in that, Step 400, which calculates the surge factor under the current sliding window based on the surge feature factor, includes: calculating the surge factor under the current sliding window based on the surge feature factor and the preset weight coefficients of the corresponding surge feature factor; wherein, the sum of the weight coefficients of the surge feature factor is 1, and the weight coefficient of each surge feature factor is greater than 0.

7. The surge detection method for a centrifugal compressor according to claim 6, characterized in that, In step 400, if the surge factor is greater than or equal to the preset surge threshold, it is determined that the compressor has experienced a surge phenomenon, including: The surge threshold is divided into a warning threshold and a shutdown threshold. The shutdown threshold is greater than the warning threshold. If the surge factor is greater than or equal to the warning threshold, it is determined that the compressor has experienced a surge phenomenon.

8. The surge detection method for a centrifugal compressor according to claim 7, characterized in that, In step 500, the output of multi-level alarm signals based on the magnitude of the surge factor includes: When the surge factor is greater than or equal to the warning threshold and less than the shutdown threshold, a warning signal is output; When the surge factor is greater than or equal to the shutdown threshold, a shutdown signal is output.

9. The surge detection method for a centrifugal compressor according to claim 8, characterized in that, Step 500 involves recording the time-domain and frequency-domain characteristic parameters of the current data within the current sliding window, and determining whether surge has been eliminated based on changes in these parameters, in order to decide whether to stop the warning or shutdown protection. Record the time-domain and frequency-domain characteristic parameters of the current data within the current sliding window. The time-domain and frequency-domain characteristic parameters include amplitude characteristic parameters, fundamental frequency characteristic parameters, and harmonic proportion characteristic parameters. If the time-domain and frequency-domain characteristic parameters meet the preset conditions for normal operation, it is considered that the surge has been significantly eliminated and the warning signal is stopped. Otherwise, it is considered that the surge has not been suppressed and a shutdown signal is output.

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