Gas turbine blade fault diagnosis method based on sound pressure signals

Abstract

The invention aims to provide a gas turbine blade fault diagnosis method based on a sound pressure signal, and belongs to the field of gas turbine diagnosis, and the method comprises the following steps: monitoring the sound pressure of a gas turbine, and collecting the rotating speed of the gas turbine; the rotating speed of the gas turbine is stored in sequence; giving a steady-state criterion of the gas turbine, and recording a noise monitoring value when the gas turbine is in a steady-state operation condition; calculating the frequency spectrum of the gas turbine sound pressure; calculating rotating speed and rotating frequency according to the key phase signal; calculating the passing frequency of the blade at a specific rotating speed, and obtaining the amplitude corresponding to the passing frequency of each stage of blade; counting according to different rotating speeds, and taking a boundary band value + / -epsilon as an alarm threshold value; the alarm threshold values at different rotating speeds are subjected to segmented stepped modeling, and sound pressure alarm limit bands at different running rotating speeds of the gas turbine are constructed; when the characteristic frequency exceeds an alarm limit, a corresponding alarm is given. The problem of equipment operation state monitoring under the condition that the gas turbine is limited to be additionally provided with a vibration sensor at present is solved.

Description

Technical Field

[0001] The present invention relates to a gas turbine diagnosis method, in particular to a blade diagnosis method. Background Art

[0002] As an important power machine, gas turbine has the characteristics of compact structure, stable operation, high thermal efficiency, etc., and its application range is becoming more and more extensive. The safe and reliable operation of gas turbines is very demanding. In the daily operation of gas turbines, the health of the unit is monitored and various abnormal conditions that may occur are analyzed and detected to avoid or facilitate timely handling of major faults of the gas turbine.

[0003] The compressor and turbine of a gas turbine are composed of multi-stage blades. During the operation of the gas turbine, high-speed airflow will make noise when passing through the blades. The noise frequency generated by the airflow passing through the blades with different numbers of blades in the gas turbine is different, and the noise generated by the airflow at different speeds is also different. In order to effectively extract the characteristics of the airflow passing through the blades at each stage of the blade from these noises and realize the fault diagnosis of gas turbine blades, a general gas turbine blade passing frequency extraction method is needed. Summary of the invention

[0004] The object of the present invention is to provide a gas turbine blade fault diagnosis method based on acoustic pressure signals, which can solve the problems of equipment operation status monitoring under the current gas turbine limitation of adding vibration sensors.

[0005] The object of the present invention is achieved in that:

[0006] The present invention provides a gas turbine blade fault diagnosis method based on acoustic pressure signals, which is characterized by comprising the following steps:

[0007] (1) Arrange an acoustic pressure sensor on the compressor side of the gas turbine to monitor the acoustic pressure of the gas turbine; read the key phase signal of the gas turbine speed to collect the gas turbine speed;

[0008] (2) storing the gas turbine speeds in sequence and adopting the first-in-first-out principle to obtain a gas turbine speed sequence;

[0009] (3) Given the steady-state criterion of the gas turbine, As the steady-state criterion, n max is the maximum value of the speed sequence, n min is the minimum value of the speed sequence; when e<1%, the gas turbine is in a steady-state operating condition, and the gas turbine noise monitoring value is recorded at this time;

[0010] (4) Using fast Fourier transform, calculate the frequency spectrum M of the gas turbine sound pressure i ;

[0011] (5) Calculate the speed n and frequency f based on the key phase signal r , assuming that the speed measuring gear disc has m teeth, then:

[0012] fr = n / m;

[0013] (6) Select any blade of a certain level, calculate the passing frequency of the blade of this level at a specific speed according to the number of blades, and obtain the amplitude corresponding to the passing frequency of each level of blades;

[0014] (7) For the historical operating data of the amplitude corresponding to the frequency of each blade passing under normal operation, statistics are collected according to different speeds, and the boundary band value ±ε is used as the alarm threshold;

[0015] (8) The alarm thresholds at different speeds are modeled in sections and steps to construct the sound pressure alarm limit band at different operating speeds of the gas turbine;

[0016] (9) When the characteristic frequency exceeds the alarm limit, a corresponding alarm is given to realize gas turbine blade fault diagnosis based on the sound pressure signal.

[0017] The present invention may also include:

[0018] 1. In step (3), the method for finding the maximum value and the minimum value of the speed sequence is the linear scanning method:

[0019] A. Initialize two variables: value_max and value_min, and assign the amplitude of the first element of the speed sequence to these two variables;

[0020] B. Traverse the speed array, and compare each time whether the current iteration value is greater than value_max and less than value_min. If so, update the variable value, if not, continue iterating;

[0021] C. After the traversal is completed, the values ​​of the two variables are the maximum and minimum values ​​of the speed sequence.

[0022] 2. After the rotation frequency is obtained in step (5), a peak search is performed in the range of fr±fr*0.1 near the rotation frequency to obtain the double rotation frequency f r ; Calculate each frequency domain feature in the following intervals by doubling the frequency:

[0023] The amplitude of the rotation frequency: P 1 =max(M fr-f r *0.1 , M fr+f r *0.1 )

[0024] The amplitude of double rotation frequency: P 2 =max(M 2fr-fr*0.1 , M2f r +f r *0.1 )

[0025] Amplitude of triple rotation frequency: P 3 =max(M 3fr-fr*0.1 , M 3f r +f r *0.1 )

[0026] The amplitude of the four-fold rotation frequency: P 4 =max(M 4fr-fr*0.1 , M 4f r +f r *0.1 )

[0027] Amplitude of half frequency division: P 5 =max(M 1 / 2fr-fr*0.05 , M 1 / 2f r +f r *0.05 )

[0028] Amplitude of one-third frequency division: P 6 =max(M 1 / 3fr-fr*0.05 , M 1 / 3f r +f r *0.05 ).

[0029] 3. The amplitude search method is the insertion sort method. The specific steps are as follows:

[0030] ① Starting from the first element, the element is considered to have been sorted;

[0031] ② Take out the next element and scan from the back to the front in the sorted element sequence;

[0032] ③If the element is larger than the new element, move the element to the next position;

[0033] ④ Repeat step ③ until you find a position where the sorted element is less than or equal to the new element;

[0034] ⑤After inserting the new element into this position;

[0035] ⑥ Repeat steps ③-⑤ until all elements are sorted;

[0036] ⑦According to the sorted array, the maximum amplitude value in each frequency range is obtained.

[0037] 4. Step (6) The method for selecting the amplitude corresponding to the frequency of each blade passing is:

[0038]

[0039] 5. Step (8) is specifically:

[0040] i. Get the speed alarm threshold from 50 to 5000 RPM at intervals of 50 RPM;

[0041] ii. Based on the obtained alarm threshold points, draw an alarm threshold line graph to obtain the sound pressure alarm limit band.

[0042] The advantages of the present invention are as follows: the present invention solves the problems of equipment operation status monitoring under the current situation that gas turbines are restricted from installing vibration sensors. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic diagram for placement of data devices;

[0044] Figure 2 Schematic diagram of spectrum extraction in step (6);

[0045] Figure 3 Schematic diagram of the sound pressure alarm band limit in step (8);

[0046] Figure 4 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0047] The present invention is described in more detail below with reference to the accompanying drawings:

[0048] Combination Figure 1-4 The steps of a gas turbine blade fault diagnosis method based on acoustic pressure signals of the present invention are as follows:

[0049] Step 1: According to the specific situation of the gas turbine, arrange the sound pressure sensor about 1 meter away from the compressor side of the gas turbine to realize the sound pressure monitoring of the gas turbine; read the key phase signal of the gas turbine speed to realize the collection of the gas turbine speed.

[0050] Step 2: Store the gas turbine speed in sequence, using the first-in-first-out principle to obtain a gas turbine speed sequence.

[0051] Step 3: Given the steady-state criterion of the gas turbine. As the steady-state criterion, n max is the maximum value of the speed sequence, n min When e<1%, the gas turbine is considered to be in steady-state operation, and the noise monitoring value of the gas turbine is recorded at this time.

[0052] The method for finding the maximum and minimum values ​​of the speed sequence is the linear scanning method. The specific steps are as follows:

[0053] 1. Initialize two variables, value_max and value_min, and assign the amplitude of the first element of the speed sequence to these two variables;

[0054] 2. Traverse the speed array, and compare each time whether the current iteration value is greater than value_max and less than value_min. If so, update the variable value, if not, continue iterating;

[0055] 3. After the traversal is completed, the values ​​of the two variables are the maximum and minimum values ​​of the speed sequence.

[0056] Step 4: Use fast Fourier transform to calculate the spectrum M of the gas turbine sound pressure i .

[0057] Step 5: Calculate the speed n and frequency fr according to the key phase signal. Assuming the speed measuring gear has m teeth, then:

[0058] f r =n / m

[0059] After the frequency is obtained, the range of f is r ±f r *0.1 peak search to obtain double the rotation frequency f r . Each frequency domain feature is calculated in the following intervals by doubling the frequency.

[0060] The amplitude of the rotation frequency: P 1 =max(M fr-fr*0.1 , M fr+f r *0.1 )

[0061] The amplitude of double rotation frequency: P 2 =max(M 2fr-fr*0.1 , M 2f r +f r *0.1 )

[0062] Amplitude of triple rotation frequency: P 3 =max(M 3fr-fr*0.1 , M 3f r +f r *0.1 )

[0063] The amplitude of the four-fold rotation frequency: P 4 =max(M 4fr-fr*0.1 , M 4f r +f r *0.1 )

[0064] Amplitude of half frequency division: P 5 =max(M 1 / 2fr-fr*0.05 , M 1 / 2fr +f r *0.05 )

[0065] Amplitude of one-third frequency division: P 6 =max(M 1 / 3fr-fr*0.05 , M 1 / 3f r +fr*0.05 )

[0066] The amplitude search method is the insertion sort method, and the specific steps are as follows:

[0067] 1. Starting from the first element, the element can be considered to have been sorted;

[0068] 2. Take out the next element and scan from the back to the front in the sorted element sequence;

[0069] 3. If the element (already sorted) is greater than the new element, move the element to the next position;

[0070] 4. Repeat step 3 until you find a position where the sorted element is less than or equal to the new element;

[0071] 5. After inserting the new element into this position;

[0072] 6. Repeat steps 2-5 until all elements are sorted;

[0073] 7. Based on the sorted array, get the maximum amplitude within each frequency range.

[0074] Step 6: Select any blade stage, calculate the passing frequency of the blade stage at a specific speed based on the number of blades, and obtain the amplitude corresponding to the passing frequency of each blade stage.

[0075] The method for selecting the amplitude corresponding to the frequency of blade passing at each level is:

[0076]

[0077] Step 7: For the historical operating data of the amplitude corresponding to the frequency of each blade passing through collected under normal operating conditions, statistics are performed according to different speeds, and (boundary band value ± ε) is used as the alarm threshold (where ε is empirically taken as 1-5 times the standard deviation of the statistical result).

[0078] Step 8: Model the alarm thresholds at different speeds in sections and steps to construct the sound pressure alarm limit bands at different operating speeds of the gas turbine. The specific steps are as follows:

[0079] 1. Get the speed alarm threshold from 50 to 5000 RPM at 50 RPM intervals;

[0080] 2. Based on the obtained alarm threshold points, draw an alarm threshold line graph to obtain the sound pressure alarm limit band.

[0081] Step 9: When one or several characteristic frequencies exceed the alarm limit, a corresponding alarm is given to realize gas turbine blade fault diagnosis based on the sound pressure signal.

Claims

1. A gas turbine blade fault diagnosis method based on acoustic pressure signals, characterized in that: The steps include: (1) Arrange an acoustic pressure sensor on the compressor side of the gas turbine to monitor the acoustic pressure of the gas turbine; read the key phase signal of the gas turbine speed to collect the gas turbine speed; (2) storing the gas turbine speeds in sequence and adopting the first-in-first-out principle to obtain a gas turbine speed sequence; (3) Given the steady-state criterion of the gas turbine, As the steady-state criterion, n max is the maximum value of the speed sequence, n min is the minimum value of the speed sequence; when e<1%, the gas turbine is in a steady-state operating condition, and the gas turbine noise monitoring value is recorded at this time; (4) Using fast Fourier transform, calculate the frequency spectrum M of the gas turbine sound pressure i ; (5) Calculate the speed n and frequency f based on the key phase signal r , assuming that the speed measuring gear disc has m teeth, then: f r =n / m; (6) Select any blade of a certain level, calculate the passing frequency of the blade of this level at a specific speed according to the number of blades, and obtain the amplitude corresponding to the passing frequency of each level of blades; (7) For the historical operating data of the amplitude corresponding to the frequency of each blade passing under normal operation, statistics are collected according to different speeds, and the boundary band value ±ε is used as the alarm threshold; (8) The alarm thresholds at different speeds are modeled in sections and steps to construct the sound pressure alarm limit band at different operating speeds of the gas turbine; (9) When the characteristic frequency exceeds the alarm limit, a corresponding alarm is given to realize gas turbine blade fault diagnosis based on the sound pressure signal.

2. The method for gas turbine blade fault diagnosis based on acoustic pressure signals according to claim 1 is characterized in that: In step (3), the method for finding the maximum value and the minimum value of the speed sequence is the linear scanning method: A. Initialize two variables: value_max and value_min, and assign the amplitude of the first element of the speed sequence to these two variables; B. Traverse the speed array, and compare each time whether the current iteration value is greater than value_max and less than value_min. If so, update the variable value, if not, continue iterating; C. After the traversal is completed, the values ​​of the two variables are the maximum and minimum values ​​of the speed sequence.

3. The method for gas turbine blade fault diagnosis based on acoustic pressure signals according to claim 1 is characterized by: After the frequency conversion is obtained in step (5), a range of f is performed near the frequency conversion. r ±f r *0.1 peak search to obtain double the rotation frequency f r ; Calculate each frequency domain feature in the following intervals by doubling the frequency: Frequency amplitude: P1 = max(M fr-fr*0.1 , M fr+fr*0.1 ) The amplitude of the double frequency: P2 = max(M 2fr-fr*0.1 , M 2fr+fr*0.1 ) The amplitude of the triple frequency: P3 = max(M 3fr-fr*0.1 , M 3fr+fr*0.1 ) The amplitude of the four-fold rotation frequency: P4 = max(M 4fr-fr*0.1 , M 4fr+fr*0.1 ) The amplitude of the half frequency division: P5 = max(M 1 / 2fr-fr*0.05 , M 1 / 2fr+fr*0.05 ) Amplitude of one-third frequency division: P6 = max(M 1 / 3fr-fr*0.05 , M 1 / 3fr+fr*0.05 ).

4. The method for gas turbine blade fault diagnosis based on acoustic pressure signals according to claim 3 is characterized by: The amplitude search method is the insertion sort method, and the specific steps are as follows: ① Starting from the first element, the element is considered to have been sorted; ② Take out the next element and scan from the back to the front in the sorted element sequence; ③If the element is larger than the new element, move the element to the next position; ④ Repeat step ③ until you find a position where the sorted element is less than or equal to the new element; ⑤After inserting the new element into this position; ⑥ Repeat steps ③-⑤ until all elements are sorted; ⑦According to the sorted array, the maximum amplitude value in each frequency range is obtained.

5. The method for gas turbine blade fault diagnosis based on acoustic pressure signals according to claim 1 is characterized in that: Step (6) The method for selecting the amplitude corresponding to the frequency of each blade passing through is:

6. The method for gas turbine blade fault diagnosis based on acoustic pressure signals according to claim 1 is characterized by: Step (8) is specifically: i. Get the speed alarm threshold from 50 to 5000 RPM with 50 RPM interval; ii. Based on the obtained alarm threshold points, draw an alarm threshold line graph to obtain the sound pressure alarm limit band.

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