CN112504426B - Peak search-based rotor blade vortex interference noise whole-period averaging method - Google Patents
Peak search-based rotor blade vortex interference noise whole-period averaging method Download PDFInfo
- Publication number
- CN112504426B CN112504426B CN202011309542.9A CN202011309542A CN112504426B CN 112504426 B CN112504426 B CN 112504426B CN 202011309542 A CN202011309542 A CN 202011309542A CN 112504426 B CN112504426 B CN 112504426B
- Authority
- CN
- China
- Prior art keywords
- data
- peak
- interference noise
- whole
- array
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H1/00—Measuring characteristics of vibrations in solids by using direct conduction to the detector
- G01H1/003—Measuring characteristics of vibrations in solids by using direct conduction to the detector of rotating machines
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64F—GROUND OR AIRCRAFT-CARRIER-DECK INSTALLATIONS SPECIALLY ADAPTED FOR USE IN CONNECTION WITH AIRCRAFT; DESIGNING, MANUFACTURING, ASSEMBLING, CLEANING, MAINTAINING OR REPAIRING AIRCRAFT, NOT OTHERWISE PROVIDED FOR; HANDLING, TRANSPORTING, TESTING OR INSPECTING AIRCRAFT COMPONENTS, NOT OTHERWISE PROVIDED FOR
- B64F5/00—Designing, manufacturing, assembling, cleaning, maintaining or repairing aircraft, not otherwise provided for; Handling, transporting, testing or inspecting aircraft components, not otherwise provided for
- B64F5/60—Testing or inspecting aircraft components or systems
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P3/00—Measuring linear or angular speed; Measuring differences of linear or angular speeds
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
Abstract
The invention belongs to the technical field of helicopter model rotor wing tests, and particularly relates to a rotor wing propeller vortex interference noise whole-period averaging method based on peak value search. The method can effectively avoid the problem that the rotor wing vortex interference noise time domain average data cannot be used due to the fact that the rotor wing vortex interference noise time domain average data are staggered caused by the fluctuation of the rotating speed of the rotor wing.
Description
Technical Field
The invention belongs to the technical field of helicopter model rotor wing tests, and particularly relates to a rotor wing propeller vortex interference noise whole-period averaging method based on peak value searching.
Background
Rotor blade vortex interference noise is typical noise generated by a helicopter rotor, and particularly in the low-speed forward flight and inclined descent state, the energy of the blade vortex interference noise accounts for 80% of the total energy of the helicopter noise, so that the rotor blade vortex interference noise is a main research field of reducing the noise of the helicopter at present.
At present, the method for analyzing the interference noise data of the rotor blade vortex at home and abroad mainly focuses on a frequency domain, and most of the methods adopt conventional spectrum analysis, order analysis and wavelet analysis. However, in the time domain, although there are many analysis methods, these methods have specificity of unsteady state period because the influence of factors such as rotor noise, rotation speed fluctuation and gust interference is not considered, the analysis efficiency and the analysis accuracy are not high, and the problem that the average data in the whole period is dislocated and cannot be used exists.
Disclosure of Invention
The purpose of the invention is as follows: the method can effectively avoid the problem that the rotor wing vortex interference noise time domain average data cannot be used due to the dislocation of the rotor wing vortex interference noise time domain average data caused by the fluctuation of the rotating speed of the rotor wing.
The technical scheme of the invention is as follows: in order to achieve the above object, the present invention provides a peak search-based rotor blade vortex interference noise whole-period averaging method, wherein the rotor blade vortex interference noise time domain data is collected on a model rotor wing test bed, and a rotation speed sensor and a noise sensor are installed on the model rotor wing test bed and are respectively used for acquiring rotation speed and blade vortex interference noise data; the rotating speed sensor and the noise sensor are electrically connected with a data acquisition system, and rotating speed data and propeller vortex interference noise data can be synchronously acquired through the data acquisition system; the method specifically comprises the following steps:
s1: synchronously acquiring a rotating speed data set and a propeller vortex interference noise data set;
s2: setting a rotating speed peak value threshold value according to the rotating speed data group and the propeller vortex interference noise data group collected in the step S1, and searching a rotating speed peak value position in the rotating speed data group according to the rotating speed peak value threshold value to obtain a peak value position array;
s3: according to the peak position array obtained in the step S2, removing the final position data of the peak position array to obtain a peak starting point array, calculating the length of each period data according to the adjacent peak position of the peak starting point array to obtain a period data length array, selecting the maximum mode in the period data length array as the length of the whole period data, and simultaneously obtaining the whole period starting point array;
s4: according to the length of the whole-period data obtained in the step S3, carrying out whole-period data interception on the propeller vortex interference noise data set to correspondingly obtain each whole-period data set of the propeller vortex interference noise data set;
s5: aiming at each whole-period data set of the propeller vortex interference noise data set obtained in the step S4, performing data alignment through Euclidean distance analysis to obtain an aligned whole-period propeller vortex interference noise data set;
s6: and carrying out whole-period data averaging on the aligned whole-period propeller vortex interference noise data sets in the step S5.
In one possible embodiment, in said step S1, the rotation speed and the paddle vortex interference noise are acquired synchronously with a frequency n of at least 8 turns.
In one possible embodiment, in step S2, a peak rotational speed threshold value Psp is initially set, which is used to compare the rotational speed data set [ Spa ] in step S1 1 ,Spa 2 ,…,Spa x ]The peak value searching is carried out, x is the number of sampling points, and the method specifically comprises the following steps:
s201: the rotational speed data array [ Spa 1 ,Spa 2 ,…,Spa x ]Taking odd number t points from the current search position, and if the t points are all larger than the rotation speed peak value threshold value Psp, the rotation speed values of the front (t-1)/2 points are gradually increased, and the rotation speed values of the rear (t-1)/2 points are gradually decreased, the position of the (t-1)/2 +1 point in the rotation speed data is a peak value point;
the initial search starts from the first data point Spa 1 Starting to search;
s202: if the peak point is found, recording the rotation speed data array [ Spa ] of the peak point 1 ,Spa 2 ,…,Spa x ]Skipping S data points from the current peak position to the next time as the current search position, wherein S is larger than or equal to t, and repeating S201 to continue searching the peak point;
if the peak point is not found, moving the searching position from the current position backward by 1 position to serve as the current searching position, and repeating S201 to continue searching the peak point;
s203: when the rotational speed data group [ Spa ] in the step S1 is compared 1 ,Spa 2 ,…,Spa x ]After all the rotational speed data are searched, if the number of the found peak positions is greater than the rotational speed and the synchronous acquisition frequency n of the propeller vortex interference noise, the numerical value of the rotational speed peak threshold value needs to be increased to 110% of the original rotational speed peak threshold value Psp, then the current search position is set as a first data point Spa1, and S201-S202 are repeated; if the number of the found peak positions is smaller than the synchronous acquisition frequency n of the rotating speed and the propeller vortex interference noise, reducing the numerical value of the rotating speed peak threshold value to 90% of the original rotating speed peak threshold value Psp, then setting the current search position as a first data point Spa1, and repeating S201-S202; when the number of the found peak position is equal to the synchronous acquisition frequency n of the rotating speed and the propeller vortex interference noise, the peak search is ended, and finally the peak position array [ La ] is obtained 0 ,La 1 ,…,La n ]。
Preferably, in step S2, the rotational speed data set [ Spa ] is first compared 1 ,Spa 2 ,…,Spa x ]Obtaining an absolute value rotating speed data array [ Spb ] by taking an absolute value of the rotating speed data 1 ,Spb 2 ,…,Spb x ]And replacing said set of speed data [ Spa ] 1 ,Spa 2 ,…,Spa x ]。
In one possible embodiment, the threshold value Psp for the peak rotational speed is typically 10% to 50% of the maximum rotational speed in the rotational speed data set acquired in step S1.
In a possible embodiment, in the first step of step S2, the value of t is greater than or equal to 3.
In one possible embodiment, in the step S3, the peak position array [ La ] is determined 0 ,La 1 ,…,La n ]Finally, the position data is removed to obtain a peak value starting point array [ La ] 0 ,La 1 ,…,La (n-1) ]Calculating to obtain a periodic data length array [ La ] of 1 -La 0 ,La 2 -La 1 ,…,La (n-1) -La (n-2) ]Selecting the maximum mode Lf in the period data length array as the whole period data length, and obtaining the whole period with the period data length Lf according to the peak position arrayArray of epoch Start points [ j ] 0 ,j 1 ,…j m ]。
In a possible embodiment, in step S4, the rotor blade vortex interference noise data array [ Ni ] is obtained by using the data length of the whole period obtained in step S3 1 ,Ni 2 ,…,Ni x ]Intercepting m whole period rotor wing vortex interference noise data array [ Ni 11 ,Ni 12 ,…Ni 1Lf ]、[Ni 21 ,Ni 22 ,…Ni 2Lf ]、…[Ni m1 ,Ni m2 ,…Ni mLf ]。
In a possible embodiment, in the step S5, the following steps are specifically included:
s501: rotor blade vortex interference noise data array [ Ni ] in 1 st whole period 11 ,Ni 12 ,…Ni 1Lf ]Respectively calculating the Euclidean distance between each other whole-period rotor blade vortex interference noise data array and the 1 st whole-period rotor blade vortex interference noise data array according to an Euclidean distance calculation formula for reference, wherein each whole-period rotor blade vortex interference noise data array further comprises each data combination of front Lf-1 data points in the array which are sequentially translated backwards; the Euclidean distance calculates the distance between two points on the space, and when the distance between the two points is the minimum, the correlation between the two points is the highest;
s502: and respectively finding the corresponding data combination when the Euclidean distance between each other whole-period rotor blade vortex interference noise data array and the 1 st whole-period rotor blade vortex interference noise data array is minimum, and obtaining the aligned whole-period rotor blade vortex interference noise data arrays.
In one possible embodiment, in step S6, performing an arithmetic average on each corresponding position data point in each aligned whole-cycle blade vortex interference noise data set obtained in step S5 to finally obtain a required whole-cycle average data set of rotor blade vortex interference noise
The invention has the beneficial effects that: the invention provides a peak value search-based rotor blade vortex interference noise whole-period averaging method, which can effectively avoid the problem that the rotor blade vortex interference noise time domain average data cannot be used due to the dislocation of the whole-period average data of the rotor blade vortex interference noise time domain data caused by the fluctuation of the rotating speed of a rotor.
Drawings
FIG. 1 is a flow chart of the method of the present invention
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the flowchart of the method of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a peak search based rotor blade vortex interference noise whole-period averaging method is provided, where acquisition of rotor blade vortex interference noise time domain data is performed on a model rotor wing test bed, and a rotation speed sensor and a noise sensor are installed on the model rotor wing test bed and are respectively used for acquiring rotation speed and blade vortex interference noise data; the rotating speed sensor and the noise sensor are connected with a data acquisition system, and rotating speed data and propeller vortex interference noise data can be synchronously acquired through the data acquisition system; the method specifically comprises the following steps:
s1: synchronously acquiring a rotating speed data set and a propeller vortex interference noise data set; the synchronous acquisition frequency of the rotating speed and the propeller vortex interference noise is n, and n is at least 8 circles;
s2: setting a rotating speed peak value threshold value according to the rotating speed data group and the propeller vortex interference noise data group collected in the step S1, and searching a rotating speed peak value position in the rotating speed data group according to the rotating speed peak value threshold value to obtain a peak value position array;
s3: according to the peak position array obtained in the step S2, removing the final position data of the peak position array to obtain a peak starting point array, calculating the length of each period data according to the adjacent peak position of the peak starting point array to obtain a period data length array, selecting the maximum mode in the period data length array as the length of the whole period data, and simultaneously obtaining the whole period starting point array;
s4: according to the length of the whole-period data obtained in the step S3, carrying out whole-period data interception on the propeller vortex interference noise data set to correspondingly obtain each whole-period data set of the propeller vortex interference noise data set;
s5: aiming at each whole-period data set of the propeller vortex interference noise data set obtained in the step S4, carrying out data alignment through Euclidean distance analysis to obtain an aligned whole-period propeller vortex interference noise data set;
s6: carrying out whole-cycle data averaging on the aligned whole-cycle propeller vortex interference noise data groups in the step S5;
in step S2, a speed peak threshold value Psp is first set, which is used to compare the speed data set [ Spa ] in step S1 1 ,Spa 2 ,…,Spa x ]The peak value searching is carried out, x is the number of sampling points, and the method specifically comprises the following steps:
s201: the rotational speed data array [ Spa 1 ,Spa 2 ,…,Spa x ]Taking odd number t points from the current search position, and if the t points are all larger than the rotation speed peak value threshold value Psp, the rotation speed values of the front (t-1)/2 points are gradually increased, and the rotation speed values of the rear (t-1)/2 points are gradually decreased, the position of the (t-1)/2 +1 point in the rotation speed data is a peak value point;
the initial search starts from the first data point Spa 1 Starting to search;
s202: if the peak point is found, recording the peak point in the rotating speed data array [ Spa [ ] 1 ,Spa 2 ,…,Spa x ]The peak position in the middle, and s data points are skipped from the current peak position to the backIf the current search position is the current search position and S is larger than or equal to t, repeating S201 to continuously search the peak point;
if the peak point is not found, moving the search position from the current position backward by 1 position to serve as the current search position, and repeating S201 to continue searching the peak point;
s203: when comparing the rotational speed data set [ Spa ] in the step S1 1 ,Spa 2 ,…,Spa x ]After all the rotational speed data are searched, if the number of the found peak positions is greater than the rotational speed and the synchronous acquisition frequency n of the propeller vortex interference noise, the numerical value of the rotational speed peak threshold value needs to be increased to 110% of the original rotational speed peak threshold value Psp, then the current search position is set as a first data point Spa1, and S201-S202 are repeated; if the number of the found peak positions is smaller than the synchronous acquisition frequency n of the rotating speed and the propeller vortex interference noise, reducing the numerical value of the rotating speed peak threshold value to 90% of the original rotating speed peak threshold value Psp, then setting the current search position as a first data point Spa1, and repeating S201-S202; when the number of the found peak positions is equal to the synchronous acquisition frequency n of the rotating speed and the propeller vortex interference noise, the peak search is ended, and finally the peak position array [ La ] is obtained 0 ,La 1 ,…,La n ]；
Preferably, in step S2, the rotational speed data set [ Spa ] is first checked 1 ,Spa 2 ,…,Spa x ]Obtaining an absolute value rotating speed data array [ Spb ] by taking the absolute value of the rotating speed data 1 ,Spb 2 ,…,Spb x ]And replacing said set of speed data [ Spa ] 1 ,Spa 2 ,…,Spa x ]；
The rotating speed peak value threshold value Psp is generally 10% -50% of the maximum rotating speed value in the rotating speed data group collected in the step S1;
in the step S201, the value of t is greater than or equal to 3;
in the step S3, the peak position array [ La ] is set 0 ,La 1 ,…,La n ]Finally, the position data is removed to obtain a peak value starting point array [ La ] 0 ,La 1 ,…,La (n -1)]Calculating to obtain a periodic data length array [ La 1 -La 0 ,La 2 -La 1 ,…,La (n-1) -La (n-2) ]Selecting the maximum mode Lf in the period data length array as the whole period data length, and obtaining a whole period starting point array [ j ] with the period data length Lf according to the peak position array 0 ,j 1 ,…j m ]；
In the step S4, the data length of the whole period obtained in the step S3 is utilized to enable the rotor blade vortex interference noise data array [ Ni 1 ,Ni 2 ,…,Ni x ]Intercepting m whole-period rotor wing vortex interference noise data arrays [ Ni 11 ,Ni 12 ,…Ni 1Lf ]、[Ni 21 ,Ni 22 ,…Ni 2Lf ]、…[Ni m1 ,Ni m2 ,…Ni mLf ]；
In the step S5, the method specifically includes the following steps:
s501: rotor blade vortex interference noise data array [ Ni ] in 1 st whole period 11 ,Ni 12 ,…Ni 1Lf ]Respectively calculating the Euclidean distance between each other whole-period rotor blade vortex interference noise data array and the 1 st whole-period rotor blade vortex interference noise data array according to an Euclidean distance calculation formula for reference, wherein each whole-period rotor blade vortex interference noise data array further comprises each data combination of front Lf-1 data points in the array which are sequentially translated backwards; the Euclidean distance calculates the distance between two points on the space, and when the distance between the two points is the minimum, the correlation between the two points is the highest;
s502: respectively finding the corresponding data combination when the Euclidean distance between each other whole-cycle rotor blade vortex interference noise data array and the 1 st whole-cycle rotor blade vortex interference noise data array is minimum to obtain the aligned whole-cycle rotor blade vortex interference noise data arrays;
in step S6, performing arithmetic averaging on each corresponding position data point in each aligned whole-cycle propeller vortex interference noise data set obtained in step S5, and finally obtaining the required whole-cycle mean data set of rotor propeller vortex interference noise
Example 1:
s1: synchronous acquisition of rotating speed and propeller vortex interference noise
Simultaneously accessing a rotating speed signal and a propeller vortex interference noise signal into a data acquisition system with a synchronous acquisition function, electrifying and preheating for 30 minutes, operating a test bench to a test rotating speed specified by a test task book, then carrying out total distance increasing operation to a total distance 7 degrees to be subjected to dynamic balance adjustment, setting a sampling frequency according to the calculated sampling frequency after waiting for 10 seconds and waiting for a test state to be stable, and then acquiring 8 circles of rotating speed data array Spa =
[0，0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，
<xnotran> 0,0,0,0,0,0,0,0,0,0,0,0,0, 10, 10,0,0,0,0,0,0,0,0,0,0,0] Ni = </xnotran>
[0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0.2，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3]；
S2: speed peak position search
Obtaining a new absolute value rotating speed data array Spb =by taking the absolute value of the numerical value of the rotating speed data of the acquired 8 circles
[0，0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0，
0，0，0，0，0，0，0，0，0，0，0，0，0，10，10，0，0，0，0，0，0，0，0，0，0，0]
Setting a rotating speed peak value threshold value Psp =1.5V, carrying out peak value position search on the rotating speed data of each circle by using the threshold value Psp, and searching the obtained peak value position array [13,38,64,91,117,143,170,196];
s3: full cycle data length calculation
Removing the final position data by using the peak position array to obtain a peak starting point array [13,38,64,91,117,143,170], and subtracting adjacent elements of the peak position array to obtain a data length array [25,26,27,26 ];
full cycle data length statistical analysis
From the data length array, the data length 26 is most significant, i.e., the mode L f =26, the peak start array and the data length data elements are the same in number (one-to-one correspondence), so the elements in the peak start array corresponding to the element with the mode number of 26 in the data length array constitute the whole period start array [38, 91,117, 170 =26]；
S4: whole cycle data interception
According to the numerical value of the element in the whole period starting point array, namely the starting point position representing the start of interception in the interference noise data array, the peak value starting point array and the data length L obtained by calculation are utilized f =26, array Ni interference noise data of rotor blade vortex 1 Obtaining 4 complete-turn (i.e. m =4, determined by the number of data elements at the start of the complete cycle) rotor wing vortex interference noise data arrays
[0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3]、[0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4]、[0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3]、[0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2]；
S5: euclidean distance analysis and data alignment
Based on the 1 st full-cycle (i.e., the 1 st cycle) rotor blade vortex interference noise data array [0.2,0.3,0.4,0.5,0.6,0.5,0.4,0.3,0.2,0.1, 0.2,0.3,0.4,0.5,0.6,0.5,0.4,0.3,0.2,0.1,0,0.1,0.2,0.3], it and the other 4 cycles are calculated as follows:
D 1-2-1 ＝((0.2-0.5) 2 +(0.3-0.4) 2 +(0.4-0.3) 2 +…+(0.5-0)) 1/2 ；
D 1-2-2 ＝((0.2-0.4) 2 +(0.3-0.3) 2 +(0.4-0.2) 2 +…+(0.5-0.1)) 1/2 ；
…
D 1-2-9 ＝((0.2-0.3) 2 +(0.3-0.4) 2 +(0.4-0.5) 2 +…+(0.5-0.4)) 1/2 ；
by carrying out Euclidean distance algorithm analysis on a large amount of rotor blade vortex interference noise test data, the offset with the minimum Euclidean distance cannot exceed 9 times, and if the offset exceeds 9 times, the data cannot be used if the original data is found to be lost possibly;
euclidean distance [ D ] obtained from the above calculation 1-2-1 ,D 1-2-2 ,…D 1-2-9 ]Find the minimum distance D in 1-2-8 =0, then shift position 8 is obtained, the 2 nd whole period array [0.5,0.4,0.3,0.2,0.1, 0.2,0.3,0.4,0.5,0.6,0.5,0.4,0.3,0.2,0.1,0,0.1,0.2,0.3,0.4,0.5,0.6,0.5,0.4]Shift forward by 8 bits, obtaining the arrays [0.2,0.3,0.4,0.5,0.6,0.5,0.4,0.3,0.2,0.1, 0.2,0.3,0.4,0.5,0.6,0.5,0.4,0.3,0.2,0.1,0，0.1]；
and other circles calculate the Euclidean distance according to the formula, find the minimum distance number, and shift after obtaining the shift position. Finally obtaining an aligned 4 whole-cycle rotor blade vortex interference noise data array
[0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3]、
[0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.5，0.4，0.3，0.2，0.1，0，0.1，]、[0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.3，0.2，0.1，0，0.1]、[0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.3，0.4，0.5，0.6，0.5，0.4，0.3，0.2，0.1，0，0.1，0.2，0.1]；
S6: whole cycle data averaging
Averaging the 4-turn rotor blade vortex interference noise data arrays (namely 4 turns) according to the following formula to obtain a finally required array of rotor blade vortex interference noise whole-period average data arrays
…
The foregoing is illustrative of the present invention and is not to be construed as limiting thereof. The scope of the present invention is not limited thereto, and any changes or substitutions that can be easily made by those skilled in the art within the technical scope of the present invention will be covered by the scope of the present invention. The protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. The method is characterized in that the acquisition of rotor blade vortex interference noise time domain data is carried out on a model rotor wing test bed, and a rotating speed sensor and a noise sensor are mounted on the model rotor wing test bed and are respectively used for acquiring rotating speed and blade vortex interference noise data; the rotating speed sensor and the noise sensor are electrically connected with a data acquisition system, and rotating speed data and propeller vortex interference noise data can be synchronously acquired through the data acquisition system; the method specifically comprises the following steps:
s1: synchronously acquiring a rotating speed data set and a propeller vortex interference noise data set;
s2: setting a rotating speed peak value threshold value according to the rotating speed data group and the propeller vortex interference noise data group collected in the step S1, and searching a rotating speed peak value position in the rotating speed data group according to the rotating speed peak value threshold value to obtain a peak value position array;
s3: according to the peak position array obtained in the step S2, removing the final position data of the peak position array to obtain a peak starting point array, calculating the length of each period data according to the adjacent peak position of the peak starting point array to obtain a period data length array, selecting the maximum mode in the period data length array as the length of the whole period data, and simultaneously obtaining the whole period starting point array;
s4: according to the length of the whole-period data obtained in the step S3, carrying out whole-period data interception on the propeller vortex interference noise data set to correspondingly obtain each whole-period data set of the propeller vortex interference noise data set;
s5: aiming at each whole-period data set of the propeller vortex interference noise data set obtained in the step S4, carrying out data alignment through Euclidean distance analysis to obtain an aligned whole-period propeller vortex interference noise data set; the method specifically comprises the following steps:
s501: rotor blade vortex interference noise data array [ Ni ] in 1 st whole period 11 ,Ni 12 ,…Ni 1Lf ]Respectively calculating the Euclidean distance between each other whole-period rotor blade vortex interference noise data array and the 1 st whole-period rotor blade vortex interference noise data array according to an Euclidean distance calculation formula for reference, wherein each whole-period rotor blade vortex interference noise data array further comprises each data combination of front Lf-1 data points in the array which are sequentially translated backwards; lf is the length of the whole period data;
s502: respectively finding out the corresponding data combination when the Euclidean distance between each other whole-period rotor blade vortex interference noise data array and the 1 st whole-period rotor blade vortex interference noise data array is minimum to obtain the aligned whole-period rotor blade vortex interference noise data arrays;
s6: and carrying out whole-period data averaging on the aligned whole-period propeller vortex interference noise data sets in the step S5.
2. The peak search based rotor blade vortex interference noise whole cycle averaging method according to claim 1, wherein in the step S1, the rotation speed and the blade vortex interference noise are synchronously acquired at a frequency n, wherein n is at least 8 circles.
3. The method for the whole-cycle averaging of the disturbance noise of the rotor blade vortex based on the peak search according to claim 2, wherein in the step S2, a rotating speed peak threshold value Psp is firstly set, and the rotating speed data set [ Spa ] in the step S1 is subjected to the rotating speed peak threshold value Psp 1 ,Spa 2 ,…,Spa x ]Carrying out peak value search, wherein x is the number of sampling points, and the method specifically comprises the following steps:
s201: will turn toSpeed data array [ Spa ] 1 ,Spa 2 ,…,Spa x ]Taking odd number t points from the current search position, and if the t points are all larger than the rotation speed peak value threshold value Psp, the rotation speed values of the front (t-1)/2 points are gradually increased, and the rotation speed values of the rear (t-1)/2 points are gradually decreased, the position of the (t-1)/2 +1 point in the rotation speed data is a peak value point;
the initial search starts from the first data point Spa 1 Starting to search;
s202: if the peak point is found, recording the rotation speed data array [ Spa ] of the peak point 1 ,Spa 2 ,…,Spa x ]Skipping S data points from the current peak position to the next time as the current search position, wherein S is larger than or equal to t, and repeating S201 to continue searching the peak point;
if the peak point is not found, moving the searching position from the current position backward by 1 position to serve as the current searching position, and repeating S201 to continue searching the peak point;
s203: when the rotational speed data group [ Spa ] in the step S1 is compared 1 ,Spa 2 ,…,Spa x ]After all the rotational speed data are searched, if the number of the found peak positions is greater than the rotational speed and the synchronous acquisition frequency n of the propeller vortex interference noise, the value of the rotational speed peak threshold value needs to be increased to 110% of the original rotational speed peak threshold value Psp, then the current search position is set as a first data point Spa1, and S201-S202 are repeated; if the number of the found peak positions is smaller than the synchronous acquisition frequency n of the rotating speed and the propeller vortex interference noise, reducing the value of the rotating speed peak value threshold to 90% of the original rotating speed peak value threshold Psp, then setting the current search position as a first data point Spa1, and repeating S201-S202; when the number of the found peak positions is equal to the synchronous acquisition frequency n of the rotating speed and the propeller vortex interference noise, the peak search is ended, and finally the peak position array [ La ] is obtained 0 ,La 1 ,…,La n ]。
4. The peak search based rotor blade vortex interference noise full cycle averaging method according to claim 3, wherein in the stepIn step S2, the rotational speed data set [ Spa ] is first subjected to 1 ,Spa 2 ,…,Spa x ]Obtaining an absolute value rotating speed data array [ Spb ] by taking an absolute value of the rotating speed data 1 ,Spb 2 ,…,Spb x ]And replacing said set of speed data [ Spa ] 1 ,Spa 2 ,…,Spa x ]。
5. The peak search based rotor blade vortex interference noise whole cycle averaging method according to claim 4, wherein the rotation speed peak value threshold Psp is 10% -50% of the maximum rotation speed value in the rotation speed data set collected in the step S1.
6. The method for rotor wing vortex interference noise whole-cycle averaging based on peak search according to claim 5, wherein in step S201, t is greater than or equal to 3.
7. A method according to any one of claims 3-6, wherein in step S3, the array [ La ] of peak positions is determined 0 ,La 1 ,…,La n ]Finally, the position data is removed to obtain a peak value starting point array [ La ] 0 ,La 1 ,…,La (n-1) ]Calculating to obtain a periodic data length array [ La 1 -La 0 ,La 2 -La 1 ,…,La (n-1) -La (n-2) ]Selecting the maximum mode Lf in the period data length array as the whole period data length, and obtaining a whole period starting point array [ j ] with the period data length Lf according to the peak position array 0 ,j 1 ,…j m ]。
8. The peak search based rotor blade vortex interference noise whole cycle averaging method according to claim 7, wherein in the step S4, the rotor blade vortex interference noise data array [ Ni ] is obtained by using the whole cycle data length obtained in the step S3 1 ,Ni 2 ,…,Ni x ]Is cut into m wholePeriodic rotor blade vortex interference noise data array [ Ni 11 ,Ni 12 ,…Ni 1Lf ]、[Ni 21 ,Ni 22 ,…Ni 2Lf ]、…[Ni m1 ,Ni m2 ,…Ni mLf ]。
9. The peak search-based rotor blade vortex interference noise whole-cycle averaging method according to claim 8, wherein in step S6, the arithmetic mean is performed on each corresponding position data point in each aligned whole-cycle blade vortex interference noise data set obtained in step S5, so as to finally obtain the required rotor blade vortex interference noise whole-cycle average data array
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011309542.9A CN112504426B (en) | 2020-11-20 | 2020-11-20 | Peak search-based rotor blade vortex interference noise whole-period averaging method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011309542.9A CN112504426B (en) | 2020-11-20 | 2020-11-20 | Peak search-based rotor blade vortex interference noise whole-period averaging method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112504426A CN112504426A (en) | 2021-03-16 |
| CN112504426B true CN112504426B (en) | 2022-10-18 |
Family
ID=74958955
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011309542.9A Active CN112504426B (en) | 2020-11-20 | 2020-11-20 | Peak search-based rotor blade vortex interference noise whole-period averaging method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112504426B (en) |
Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB1103901A (en) * | 1965-07-30 | 1968-02-21 | Copperfield Corp | Helicopter rotor |
| FR2551209A1 (en) * | 1983-08-09 | 1985-03-01 | Becton Dickinson Co | METHOD AND APPARATUS FOR IMBALANCE MEASUREMENT |
| JPH1062543A (en) * | 1996-08-26 | 1998-03-06 | Oki Electric Ind Co Ltd | Development function generation method and apparatus for ocean acoustic tomography |
| WO2011106527A2 (en) * | 2010-02-24 | 2011-09-01 | Ampersand International, Inc. | Method for noise filtering based on confidence interval evaluation |
| CN105510043A (en) * | 2015-11-26 | 2016-04-20 | 中国船舶工业系统工程研究院 | Marine diesel engine work stability analysis method and apparatus |
| CN107505497A (en) * | 2017-07-24 | 2017-12-22 | 同济大学 | A kind of passive magnetoelectricity signals of rotational speed sensor peak-to-peak value ime-domain measuring method |
| CN108088546A (en) * | 2017-12-03 | 2018-05-29 | 中国直升机设计研究所 | Amplifier terminals loosen recognition methods under a kind of rotor platform working speed state |
| CN108100300A (en) * | 2017-12-03 | 2018-06-01 | 中国直升机设计研究所 | A kind of whirlpool generating means for whole elimination room paddle-vortex interaction experiment |
| CN108106827A (en) * | 2017-12-03 | 2018-06-01 | 中国直升机设计研究所 | A kind of rotor platform rises amplifier terminals under rotary regimes and loosens recognition methods |
| CN108573240A (en) * | 2018-04-25 | 2018-09-25 | 常州大学 | A kind of combination shape sequence and the normalized gait identification of linear session |
| CN108910079A (en) * | 2018-06-26 | 2018-11-30 | 中国直升机设计研究所 | A kind of rotor model.test system dynamic balancing adjustment phase recognition methods |
| CN110794367A (en) * | 2019-10-12 | 2020-02-14 | 中国直升机设计研究所 | Method for positioning sound source interfered by propeller vortexes |
| CN110844115A (en) * | 2019-10-18 | 2020-02-28 | 中国直升机设计研究所 | Method for judging effectiveness of data of propeller vortex interference noise and blade flapping load |
| CN110987438A (en) * | 2019-12-04 | 2020-04-10 | 国网福建省电力有限公司 | Method for detecting periodical vibration impact signals of hydraulic generator in variable rotating speed process |
| CN111089729A (en) * | 2018-10-24 | 2020-05-01 | 汽车交通工程有限公司 | Method and system for forecasting maintenance of a component by means of a solid-state acoustic sensor |
| CN111366774A (en) * | 2020-03-19 | 2020-07-03 | 上海梓一测控技术有限公司 | Reverse electromotive force testing equipment and method for automobile EPS motor |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP7293778B2 (en) * | 2019-03-22 | 2023-06-20 | 富士通株式会社 | NOISE JUDGMENT METHOD, NOISE JUDGMENT PROGRAM AND NOISE JUDGMENT DEVICE |
| CN110469462B (en) * | 2019-08-21 | 2020-08-18 | 北京天泽智云科技有限公司 | Wind turbine generator system intelligent state monitoring system based on multiple templates |
| CN111046493A (en) * | 2019-12-04 | 2020-04-21 | 中国直升机设计研究所 | Rotor wing aerodynamic noise calculation method based on concentrated load |
-
2020
- 2020-11-20 CN CN202011309542.9A patent/CN112504426B/en active Active
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB1103901A (en) * | 1965-07-30 | 1968-02-21 | Copperfield Corp | Helicopter rotor |
| FR2551209A1 (en) * | 1983-08-09 | 1985-03-01 | Becton Dickinson Co | METHOD AND APPARATUS FOR IMBALANCE MEASUREMENT |
| JPH1062543A (en) * | 1996-08-26 | 1998-03-06 | Oki Electric Ind Co Ltd | Development function generation method and apparatus for ocean acoustic tomography |
| WO2011106527A2 (en) * | 2010-02-24 | 2011-09-01 | Ampersand International, Inc. | Method for noise filtering based on confidence interval evaluation |
| CN105510043A (en) * | 2015-11-26 | 2016-04-20 | 中国船舶工业系统工程研究院 | Marine diesel engine work stability analysis method and apparatus |
| CN107505497A (en) * | 2017-07-24 | 2017-12-22 | 同济大学 | A kind of passive magnetoelectricity signals of rotational speed sensor peak-to-peak value ime-domain measuring method |
| CN108106827A (en) * | 2017-12-03 | 2018-06-01 | 中国直升机设计研究所 | A kind of rotor platform rises amplifier terminals under rotary regimes and loosens recognition methods |
| CN108100300A (en) * | 2017-12-03 | 2018-06-01 | 中国直升机设计研究所 | A kind of whirlpool generating means for whole elimination room paddle-vortex interaction experiment |
| CN108088546A (en) * | 2017-12-03 | 2018-05-29 | 中国直升机设计研究所 | Amplifier terminals loosen recognition methods under a kind of rotor platform working speed state |
| CN108573240A (en) * | 2018-04-25 | 2018-09-25 | 常州大学 | A kind of combination shape sequence and the normalized gait identification of linear session |
| CN108910079A (en) * | 2018-06-26 | 2018-11-30 | 中国直升机设计研究所 | A kind of rotor model.test system dynamic balancing adjustment phase recognition methods |
| CN111089729A (en) * | 2018-10-24 | 2020-05-01 | 汽车交通工程有限公司 | Method and system for forecasting maintenance of a component by means of a solid-state acoustic sensor |
| CN110794367A (en) * | 2019-10-12 | 2020-02-14 | 中国直升机设计研究所 | Method for positioning sound source interfered by propeller vortexes |
| CN110844115A (en) * | 2019-10-18 | 2020-02-28 | 中国直升机设计研究所 | Method for judging effectiveness of data of propeller vortex interference noise and blade flapping load |
| CN110987438A (en) * | 2019-12-04 | 2020-04-10 | 国网福建省电力有限公司 | Method for detecting periodical vibration impact signals of hydraulic generator in variable rotating speed process |
| CN111366774A (en) * | 2020-03-19 | 2020-07-03 | 上海梓一测控技术有限公司 | Reverse electromotive force testing equipment and method for automobile EPS motor |
Non-Patent Citations (1)
| Title |
|---|
| 旋翼桨涡干扰噪声特性试验技术研究;刘正江 等;《直升机技术》;20191231(第199期);43-47+42 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112504426A (en) | 2021-03-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107784325B (en) | Spiral fault diagnosis method based on data-driven incremental fusion | |
| CN105547698B (en) | The method for diagnosing faults and device of rolling bearing | |
| CN106487359B (en) | The building method of Morphologic filters based on self-adapting multi-dimension AVG-Hat transformation | |
| CN109255333B (en) | Fault hybrid diagnosis method for rolling bearing of large wind turbine generator | |
| CN109655266B (en) | Wind turbine generator bearing fault diagnosis method based on AVMD and spectrum correlation analysis | |
| CN114216682B (en) | Service life prediction method and device of rolling bearing based on TCN and BLS | |
| CN110749442A (en) | Rolling bearing fault feature extraction method based on Laplace wavelet self-adaptive sparse representation | |
| CN109696906B (en) | Underwater robot propeller fault diagnosis method based on wavelet correction Bayes convolution energy | |
| CN106897957B (en) | Automatic weather station real-time data quality control method based on PCA and PSO-E L M | |
| CN110701087A (en) | Axial flow compressor pneumatic instability detection method based on single-classification overrun learning machine | |
| CN112504426B (en) | Peak search-based rotor blade vortex interference noise whole-period averaging method | |
| CN110472335B (en) | Sensor fault diagnosis threshold value determination method based on particle swarm optimization algorithm | |
| CN109540523A (en) | A kind of ship centrifugal pump Fault Diagnosis of Roller Bearings | |
| CN117453447A (en) | Simulation test method for automobile electric drive system | |
| CN115062665A (en) | Rolling bearing early fault diagnosis method based on self-adaptive variational modal decomposition | |
| CN112487360B (en) | Rotor wing propeller vortex interference noise whole-period averaging method based on statistical analysis | |
| CN106500991A (en) | Based on the bearing fault signal characteristic extracting methods that self-adapting multi-dimension AVGH is converted | |
| CN113295420A (en) | Rolling bearing fault diagnosis method and system based on period guidance group sparse model | |
| CN111399036B (en) | Design method of seismic data efficient acquisition observation system | |
| CN112668807B (en) | Wind speed prediction method for wind power plant power prediction | |
| CN113221986B (en) | Method for separating vibration signals of through-flow turbine | |
| CN107563904A (en) | A kind of wind power output reconstructing method based on the division of wind process | |
| CN113850174A (en) | Unknown fault-containing wind turbine generator main bearing fault diagnosis method | |
| CN113157761A (en) | Electric vehicle charging and discharging fault analysis method based on association rule mining | |
| CN110334310B (en) | Method and device for determining power curve of fan |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |