CN113504309A - Blade detection method based on single blade end timing sensor - Google Patents
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Abstract
The invention discloses a blade detection method based on a single blade end timing sensor, in the method, intercepting two sections of displacement data vectors of the two blades at the same rotating speed in the displacement data, adjusting the intercepted positions of the displacement data vectors based on the included angle of the two blades, the two segments of displacement data vectors are intercepted again, the two segments of the intercepted displacement data vectors are point-multiplied to obtain product data vectors after the multiplication of corresponding serial numbers, the product data vectors are filtered by low frequency, then, discrete Fourier transform is carried out to obtain frequency components, the natural frequency difference of the two blades is extracted from the low-frequency components, and judging the reliability of the frequency difference value through the linear combination of the difference values among different blades so as to correct the frequency difference value matrix, extracting the sum of the natural frequency difference values of each blade based on the coefficient matrix constructed by the frequency difference value matrix, and judging the abnormality of the blade when the sum exceeds the preset frequency difference value and the threshold.
Description
Technical Field
The invention belongs to the field of non-contact nondestructive detection of blades, and particularly relates to a blade detection method based on a single blade end timing sensor.
Background
The blade is widely applied to rotary fluid mechanical equipment such as a gas compressor, a gas turbine and an aeroengine, cracks, chipping, rubbing, blade shroud abrasion and the like are common fault forms when the blade is used, and once the fault occurs, the fault is gradually deepened along with the working time, so that larger fault is caused, and safety accidents occur. Therefore, online fault diagnosis of the rotating blades of the key equipment is necessary, and the abnormal conditions of the blades often affect the natural frequency of the blades, so that whether the blades are abnormal or not can be judged by analyzing the natural frequency of the blades. The Blade Tip Timing technology (BTT) is a method for measuring the vibration of a rotating Blade on line in a non-contact manner, but the Blade Tip Timing sampling rate and the rotating speed are related to the number of sensors, and because the mounting position of the sensors is limited in practical situations, the Blade Tip Timing data has a serious undersampling characteristic, and even the mounting of a continuous rotating speed sensor cannot be realized. Blade end displacement measurement with a rotating speed reference method needs to convert blade reaching time difference into blade end displacement by means of rotating speed, in actual use, a plurality of blade end timing sensors are often selected to weaken aliasing influence caused by undersampling, but the rotating speed sensors and the plurality of blade end timing sensors are installed in a practical limited space to cause great trouble, and measurement cost is also increased. On one hand, the algorithms all involve a large amount of operations and cannot realize online real-time detection and diagnosis, and on the other hand, the algorithms directly identify parameters such as the natural frequency of a single blade and the like, so that large errors exist.
The above information disclosed in this background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a blade detection method based on a single blade end timing sensor, which can evaluate the health state of a blade more quickly and accurately.
The invention aims to realize the following technical scheme, and the blade detection method based on the single blade end timing sensor comprises the following steps of:
in the first step, a single blade end timing sensor is used for obtaining the actual reaching time of a rotating blade, and the difference between the theoretical reaching time and the actual reaching time is converted into displacement data of a blade end according to the rotating speed of the rotating blade and the length of the blade;
in the second step, two sections of displacement data vectors of the two blades at the same rotating speed are intercepted from the displacement data,
in the third step, the intercepted position of the displacement data vector is adjusted based on the included angle of the two blades so as to intercept two sections of displacement data vectors again, and the two sections of intercepted displacement data vectors are subjected to point multiplication to obtain a product data vector obtained by multiplying the corresponding serial numbers;
in the fourth step, the product data vector is subjected to low-frequency filtering and then discrete Fourier transform to obtain frequency components, the natural frequency difference value of two blades is extracted from the low-frequency components,
in the fifth step, the blades on the blade disc are combined pairwise, the second step to the fourth step are repeated to obtain all natural frequency difference values and a frequency difference matrix,
in the sixth step, the reliability of the frequency difference value is judged through the linear combination of the difference values among different blades so as to correct the frequency difference value matrix,
and in the seventh step, extracting the sum of the natural frequency difference of each blade based on a coefficient matrix constructed by the frequency difference matrix, and judging that the blade is abnormal when the sum of the natural frequency difference exceeds a preset frequency difference and a threshold.
In the method, in the first step, a single blade end timing sensor acquires the actual reaching time t of the rotating blade with uniform speed increase or uniform speed reduction and the actual reaching time t is determined according to the rotating speed f of the bladerAnd the blade length R converts the difference between the theoretical arrival time and the actual arrival time into blade end displacement, and the expression is as follows:
wherein
Represents the rotation speed at the j-th circle; theta1，kRepresenting the angle of the No. 1 blade and the No. k blade in the static condition; t is ti，jRepresenting the actual arrival time of the ith blade at the jth circle; n isbIndicating the number of blades, wherein
Represents the rotation speed at the j-th circle; theta1，kRepresenting the angle of the No. 1 blade and the No. k blade in the static condition; t is ti，jRepresenting the actual arrival time of the ith blade at the jth circle; n isbIndicating the number of blades. Wherein,
wherein theta isiThe angle of the ith vane is shown with reference to the rotational speed sensor mounting position. Alpha is alphakIndicates the angle, n, of the kth sensor based on the mounting position of the rotation speed sensorjThe rotation speed at the j-th turn.
In the method, the rotation process of the blades is a speed-up or speed-down process with preset acceleration, and the rotation process is stimulated by gas nozzle and air injection simulation gas which are uniformly distributed in the circumferential direction.
In the method, the two displacement data interception intervals are the same and are [ N, M [ ]]Sampling frequency fsComprises the following steps:
wherein
The rotation speed corresponding to the k-th circle is M-N +1, and the length of the intercepted data is M-N + 1.
In the method, two sections of displacement data vectors X of two blades at the same rotating speedi，XjThe intercepted data intervals are all [ c-N, c + N]The vector length is 2N + 1. Wherein c is an index sequence number corresponding to a certain position in the two blade displacement data. (how the index number is obtained)
In the method, the first blade reaching the blade end timing sensor is the No. 1 blade, if the included angle between the ith blade and the jth blade is larger than 180 degrees, the data selection interval of the smaller blade number is translated forwards by 1 unit, and the data interval is changed into [ c-N +1, c + N +1 ].
In the method, in the third step, two segments of displacement data vectors xi，xjNumber of multiplied productsThe data vector is:
extracting natural frequency difference Df of two blades from frequency componentsij，
Where x (n) is the sampled signal, i is an imaginary symbol,
n is an iteration number, from 0 to N-1, i.e. all elements in x are taken, k is an integer from 0 to N-1, and X (k) represents the kth data after discrete Fourier transform.
In the fifth step, different blade combinations are selected
Seed combinations obtained from the two steps to the fourth step
The natural frequency difference values form a natural frequency difference value matrix delta F,
its impact, Δ fij＝fi-fj＝sgn(fi-fj)·Dfij，sgn(fi-fj) Denotes fi＞fjWhen f is a symbol ofi≥fjThe extraction is positive, otherwise negative.
In the method, in the sixth step, the inherent frequency difference is:
Δfki-Δfkj＝Δfji＝-Δfij k，i，j＝1，2，…，nberror margin xi of frequency0When the following formula is satisfied, it indicates that the difference frequency of the region is reliable,
Δkij＝|Δfki-Δfkj+Δfij|≤ξ k＝1，2，…，nb-2；i＝k+1，…，nb-1；j＝i+1，…，nbthe reliability L expression of the frequency difference matrix Δ F is:
and when the reliability L of the inherent frequency difference matrix delta F is less than 0.5, the inherent frequency difference matrix delta F cannot be used for fault diagnosis, and when the reliability of the frequency difference matrix delta F is greater than 0.5, the reliability L of the frequency difference matrix delta F is recalculated after correction and is greater than 0.8, and the matrix can be used for next fault diagnosis.
In the method, in the seventh step, the constructed coefficient matrix is:
sumDk＝ΔF·Akif sumD is presentkIf the number is less than epsilon, judging that the blade has a fault.
The method can extract the inherent frequency difference between different blades from the seriously undersampled data only by a single blade end timing sensor without a rotating speed reference, judges whether the blades have faults or not according to the inherent frequency difference of the different blades, does not need to perform additional signal reconstruction and more blade end timing sensors, has quick and stable operation, is simple and feasible, and can realize the on-line detection of the faults of the rotating blades.
The above description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly apparent, and to make the implementation of the content of the description possible for those skilled in the art, and to make the above and other objects, features and advantages of the present invention more obvious, the following description is given by way of example of the specific embodiments of the present invention.
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Various other advantages and benefits of the present invention will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. It is obvious that the drawings described below are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. Also, like parts are designated by like reference numerals throughout the drawings.
In the drawings:
FIG. 1 is a system diagram of a blade detection method based on a single tip timing sensor;
FIG. 2 is a displacement diagram of the intercepted displacement data of No. 1 and No. 2 blades after mean value removal and normalization;
FIG. 3 is a product vector X obtained by multiplying the intercepted blade data No. 1 and No. 212A time domain graph;
FIG. 4 is a product vector X12A low-pass filtered spectrogram;
FIG. 5 is a schematic diagram of a triangle combination correction of a frequency difference matrix.
The invention is further explained below with reference to the figures and examples.
Detailed Description
Specific embodiments of the present invention will be described in more detail below with reference to fig. 1 to 5. While specific embodiments of the invention are shown in the drawings, it should be understood that the invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
It should be noted that certain terms are used throughout the description and claims to refer to particular components. As one skilled in the art will appreciate, various names may be used to refer to a component. This specification and claims do not intend to distinguish between components that differ in name but not function. In the following description and in the claims, the terms "include" and "comprise" are used in an open-ended fashion, and thus should be interpreted to mean "include, but not limited to. The description which follows is a preferred embodiment of the invention, but is made for the purpose of illustrating the general principles of the invention and not for the purpose of limiting the scope of the invention. The scope of the present invention is defined by the appended claims.
For the purpose of facilitating understanding of the embodiments of the present invention, the following description will be made by taking specific embodiments as examples with reference to the accompanying drawings, and the drawings are not to be construed as limiting the embodiments of the present invention.
A method of blade detection based on a single tip timing sensor includes,
(1) the method comprises the steps of acquiring the arrival time and the rotating speed of a rotating blade by using 1 blade end timing sensor, and converting the difference between the theoretical arrival time and the actual arrival time into blade end displacement according to the rotating speed and the length of the blade.
In the illustrative example, specifically, the single fiber type blade end timing sensor is fixed on the casing, the initial rotating speed is set to be 60Hz, the rotating speed acceleration is 0.5Hz/s, the rotating speed variation range is 60Hz-100Hz-60Hz, and the 100Hz constant speed period time is 20 s. The blade disc adopts a 6-blade integral aluminum alloy blade disc, the radius of the blade disc is 68mm, the thickness d of the blade is 1mm, and the width w of the blade is 20 mm. 4 nozzles are uniformly distributed on a casing, high-pressure gas of 0.5Mpa is sprayed, the reaching time and the rotating speed of the rotating blade are obtained by utilizing a single-blade-end timing sensor, and the difference between the theoretical reaching time and the actual reaching time is converted into blade-end displacement according to the rotating speed and the length of the blade.
(2) Two pieces of displacement data of two blades to be analyzed at approximately the same rotational speed are selected. If the selected data is slow speed-up or slow speed-down data, the length of the intercepted data is not suitable to be too long so as to meet the requirement of approximate constant sampling frequency.
In the illustrative example, specifically, the displacement data of the blade 1 and the blade 2 are selected, and the intercepted data sequence number range is [4786, 5025 ]]. As shown in fig. 2, the corresponding speed variation range estimated by the blade tip timing sensor is: 84.60 Hz-85.53 Hz, approximate sampling frequency fs＝85.06Hz。
(3) Adjusting the intercepted positions of the data vectors according to the angles between the blades, and then performing point multiplication operation on the two data vectors to obtain product data vectors obtained by multiplying corresponding serial numbers;
in the present exemplary embodiment, the angle between blade 1 and blade 2 is
Adjustment of the data vector interception position is not required.
By dividing the two truncated vectors x1，x2Multiplying to obtain a product vector X of the blades 1 and 212。
(4) And low-pass filtering is carried out on the product data vector, frequency components are obtained through discrete Fourier transform, and the natural frequency difference of the two blades is extracted from the low-frequency components.
In the present exemplary example, the cutoff frequency of the low-pass filtering is 40Hz, and the calculation formula of the discrete fourier transform is:
where x (n) is the sampled signal, i is an imaginary symbol,
n is the length of the acquired signal, the number of elements in x, N is an iteration number, and the data traverse from 0 to N-1, namely all the elements in x are taken, k is an integer from 0 to N-1, and X (k) represents the kth data after discrete Fourier transform.
(5) And (5) repeating the steps (2) to (4), and combining the blades on the blade disc pairwise to obtain all frequency difference values to form a frequency difference value matrix.
In the present exemplary example, a 6-blade blisk is used, so nb6, so it is necessaryTo calculate
The frequency difference, and the obtained frequency difference matrix Δ F is:
the frequency error margin ξ used in this example is 5Hz, all the triangular difference frequency combinations of the frequency difference matrix satisfy the frequency margin condition with a confidence level of 1, so no correction is necessary.
6 coefficient matrixes A are constructed by the following expression1、A2、A3、A4、A5、A6：
Multiplying the frequency difference matrix delta F by the 6 coefficient matrixes respectively to obtain 6 difference frequency sum values sumDk
sumDk＝ΔF·Ak (19)
sumD＝[-102.2 33.6 122.8 42.2 -106 24]T
When the threshold value epsilon is selected to be-100, the frequency of the blade No. 1 and the frequency of the blade No. 5 are low, and the condition is not met.
sumDk＜ε (20)
Therefore, it is judged that the natural frequencies of the blade No. 1 and the blade No. 5 are significantly low and abnormal.
The natural frequencies of 6 blades can be extracted through strain gauge measurement by using an electric induction slip ring, the obtained natural frequencies of the blades are relatively close to the calculation result of the method provided by the patent, and the feasibility of the method is illustrated.
TABLE 1 blade frequency obtained by Strain gage measurement method
In practice, the No. 1 blade and the No. 5 blade in the blade disc have cracks, and the natural frequency is lower.
[ application example ]
As shown in a blade end timing test bed in figure 1, a single optical fiber type blade end timing sensor is fixed on a casing, the initial rotating speed is set to be 60Hz, the rotating speed acceleration is 0.5Hz/s, the rotating speed variation range is 60Hz-100Hz-60Hz, and the time of the 100Hz constant speed section is 20 s. The blade disc adopts a 6-blade integral aluminum alloy blade disc, the radius of the blade disc is 68mm, the thickness d of the blade is 1mm, and the width w of the blade is 20 mm. 4 nozzles are uniformly distributed on a casing, high-pressure gas of 0.5Mpa is sprayed, the reaching time of the rotating blade is obtained by utilizing a single-blade-end timing sensor, and the difference between the theoretical reaching time and the actual reaching time is converted into blade-end displacement according to the rotating speed and the length of the blade.
Specifically, displacement data of the blade 1 and the blade 2 are selected, the intercepted data positions are 240 data near the resonance peak value of the blade 1, and the serial number range is [4786, 5025 ]]. As shown in fig. 2, the corresponding rotation speed variation ranges are: 84.60 Hz-85.53 Hz, approximate sampling frequency fs＝85.06Hz。
The angle between the blades 1 and 2 is
Adjustment of the data vector interception position is not required. By dividing the two truncated vectors x1，X2Multiplying to obtain a product vector X of the blades 1 and 212。
And low-pass filtering is carried out on the product data vector, frequency components are obtained through discrete Fourier transform, and the natural frequency difference of the two blades is extracted from the low-frequency components. In the present exemplary example, the cut-off frequency of the low-pass filtering is 40 Hz. Plotting the product vector X12The amplitude-frequency diagram of the low-frequency filtered signal is shown in fig. 4, wherein the obvious frequency component 11.7Hz can be seen, 11.7Hz is the frequency difference frequency calculated by the method of the patent, and the inherent frequency difference between the blade 1 and the blade 2 can be considered to be Δ f12＝-11.7Hz。
When the rotating blades are analyzed by using the electric leading slip ring and the strain gauge, the first-order natural frequencies of 6 blades of the aluminum alloy blade disc are respectively as follows: 341.95Hz, 354.32Hz, 361.29Hz, 354.02Hz, 341.97Hz, 351.53Hz, the inherent frequency difference of the No. 1 blade and the No. 2 blade is 12.37Hz, the inherent frequency difference extracted by the method is 11.7Hz as shown in FIG. 4, the difference is only 0.67Hz, the method is continuously used for calculating the frequency difference between every two blades, and a frequency difference matrix Delta F is obtained, and is shown as the following formula:
the frequency error margin ξ used in this example is 5Hz, all the triangular difference frequency combinations of the frequency difference matrix satisfy the frequency margin condition with a confidence level of 1, so no correction is necessary.
6 coefficient matrixes A are constructed by the following expression1、A2、A3、A4、A5、A6Multiplying the frequency difference matrix delta F by the 6 coefficient matrixes respectively to obtain 6 difference frequency sum values sumDkObtained by 6 times of operation
sumD＝[-102.2 33.6 122.8 42.2 -106 24]T。
When the threshold value epsilon is selected to be-100, the frequency of the blade No. 1 and the frequency of the blade No. 5 are low, and the condition is not met.
SumDk＜ε (20)
Therefore, it is judged that the natural frequencies of the blade No. 1 and the blade No. 5 are significantly low and abnormal.
In practice, the No. 1 blade and the No. 5 blade in the blade disc have cracks, and the natural frequency is lower. This example demonstrates the effectiveness of the proposed method of blade detection without a speed reference single-blade tip timing sensor.
Although the embodiments of the present invention have been described above with reference to the accompanying drawings, the present invention is not limited to the above-described embodiments and application fields, and the above-described embodiments are illustrative, instructive, and not restrictive. Those skilled in the art, having the benefit of this disclosure, may effect numerous modifications thereto without departing from the scope of the invention as defined by the appended claims.
Claims (10)
1. A method of blade detection based on a single tip timing sensor, the method comprising the steps of:
in the first step (S1), a single blade end timing sensor is used to obtain the actual arrival time of the rotating blade, and the difference between the theoretical arrival time and the actual arrival time is converted into displacement data of the blade end according to the rotating speed of the rotating blade and the length of the blade;
in the second step (S2), two segments of displacement data vectors of the two blades at the same rotation speed are cut from the displacement data,
in the third step (S3), adjusting the intercepted position of the displacement data vector based on the included angle of the two blades to reacquire two displacement data vectors, and performing point multiplication on the reacquired two displacement data vectors to obtain a product data vector obtained by multiplying the corresponding serial numbers;
in the fourth step (S4), the product data vector is subjected to low frequency filtering and then discrete Fourier transform to obtain frequency components, the natural frequency difference of the two blades is extracted from the low frequency components,
in the fifth step (S5), the blades on the blade disk are combined two by two, the second to fourth steps are repeated to obtain a frequency difference matrix of all natural frequency differences,
in the sixth step (S6), the confidence of the frequency difference is judged by the linear combination of the differences among different blades to correct the frequency difference matrix,
in the seventh step (S7), the natural frequency difference sum of each blade is extracted based on the coefficient matrix constructed by the frequency difference matrix, and the blade abnormality is judged when it exceeds the predetermined frequency difference sum threshold.
2. The method according to claim 1, wherein preferably, in the first step (S1), a single tip timing sensor acquires a real of a rotating blade that is uniformly accelerated or uniformly deceleratedThe time t is reached and is dependent on the rotational speed f of the bladerAnd the blade length R converts the difference between the theoretical arrival time and the actual arrival time into blade end displacement, and the expression is as follows:
wherein
Represents the rotation speed at the j-th circle; theta1，kRepresenting the angle of the No. 1 blade and the No. k blade in the static condition; t is ti，jRepresenting the actual arrival time of the ith blade at the jth circle; n isbIndicating the number of blades, wherein
Represents the rotation speed at the j-th circle; theta1，kRepresenting the angle of the No. 1 blade and the No. k blade in the static condition; t is ti，jRepresenting the actual arrival time of the ith blade at the jth circle; n isbThe number of blades is expressed, wherein,
wherein theta isiIndicating the angle, alpha, of the ith blade with respect to the mounting position of the rotation speed sensorkIndicates the angle, n, of the kth sensor based on the mounting position of the rotation speed sensorjThe rotation speed at the j-th turn.
3. The method of claim 2, wherein the rotation of the blades is a predetermined acceleration ramp or deceleration, and the gas excitation is simulated by using circumferentially spaced gas nozzles to inject gas during the rotation.
4. The method of claim 1, wherein the two displacement data truncations have the same interval, both [ N, M]Sampling frequency fsComprises the following steps:
wherein
The rotation speed corresponding to the k-th circle is M-N +1, and the length of the intercepted data is M-N + 1.
5. Method according to claim 1, wherein two displacement data vectors X of two blades at the same speed of rotationi，XjThe intercepted data intervals are all [ c-N, c + N]And the length of the vector is 2N +1, wherein c is an index sequence number corresponding to a certain position in the displacement data of the two blades.
6. The method of claim 5, wherein the first blade to tip timing sensor is blade number 1, and if the included angle between the ith and jth blades is greater than 180 °, the data selection interval with the smaller blade number is shifted forward1Unit, data interval becomes [ c-N +1, c + N +1]。
7. The method according to claim 4, wherein in the third step (S3), two segments of displacement data vectors Xi，XjThe multiplied product data vector is:
extracting natural frequency difference Df of two blades from frequency componentsij，
Where x (n) is the sampled signal, i is an imaginary symbol,
n is an iteration number, from 0 to N-1, i.e. all elements in x are taken, k is an integer from 0 to N-1, and X (k) represents the kth data after discrete Fourier transform.
8. The method of claim 1, wherein the first stepIn the five steps (S5), different blade combinations are selected
Seed combinations obtained from the two steps to the fourth step
The natural frequency difference values form a natural frequency difference value matrix delta F,
wherein, Δ fij＝fi-fj＝sgn(fi-fj)·Dfij，sgn(fi-fj) Denotes fi＞fjWhen f is a symbol ofi≥fjThe extraction is positive, otherwise negative.
9. The method according to claim 1, wherein in the sixth step (S6), the inherent frequency difference is: Δ fki-Δfkj＝Δfji＝-Δfij k，i，j＝1，2，…，nbError margin xi of frequency0When the following expression is satisfied, it indicates the difference frequency confidence of the region, Δkij＝|Δfki-Δfkj+Δfij|≤ξ k＝1，2，…，nb-2；i＝k+1，…，nb-1；j＝i+1，…，nbThe reliability L expression of the frequency difference matrix Δ F is:
and when the reliability L of the inherent frequency difference matrix delta F is less than 0.5, the inherent frequency difference matrix delta F cannot be used for fault diagnosis, and when the reliability L of the frequency difference matrix delta F is more than 0.5, the reliability L of the frequency difference matrix delta F is recalculated after correction and is more than 0.8, and the matrix can be used for next fault diagnosis.
10. The method according to claim 1, wherein in the seventh step (S7), the coefficient matrix is constructed as:
sumDk＝ΔF·AkIf sumD is presentkIf the number is less than epsilon, judging that the blade has a fault.
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