CN114137246B - Method for measuring rotating body real-time rotating speed by applying accelerometer and combining DFA method - Google Patents
Method for measuring rotating body real-time rotating speed by applying accelerometer and combining DFA method Download PDFInfo
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- CN114137246B CN114137246B CN202111658041.6A CN202111658041A CN114137246B CN 114137246 B CN114137246 B CN 114137246B CN 202111658041 A CN202111658041 A CN 202111658041A CN 114137246 B CN114137246 B CN 114137246B
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Abstract
The invention provides a method for measuring the real-time rotating speed of a rotating body by applying an accelerometer and combining a DFA method, which relates to the technical field of rotating speed detection and comprises the following steps executed by a computer: intercepting output signals of a plurality of rotation periods of two vertical sampling channels of an accelerometer in a signal processor, performing down-sampling on the output signals to serve as original data, and giving initial data segmentation parameters; dividing the original data into sections according to data section parameters; the method comprises the steps of sequentially trending each section of data, calculating the sum of zero points of trending data of each section, judging whether current data division is fine enough, calculating the sum of the zero points of the trending data after splicing is completed after conditions are met, and calculating the corresponding rotation period number of the data; and calculating the real-time rotating speed through the time length of the intercepted data. The method is simple and reliable, low in cost and strong in environment parameter fluctuation resistance, has very similar detection effects compared with a constant speed, expands the application range and is an improved new method.
Description
Technical Field
The invention relates to the technical field of detection, in particular to a method for measuring the real-time rotating speed of a rotating body by applying an accelerometer and combining a DFA method.
Background
In the automation equipment and production automation process in various fields such as traffic, electric power, metallurgy, chemical industry, building materials and the like, the rotating speed of the rotating body is an important reference, for example, the rotating speed needs to be measured in the conditions of elevator lifting, machine tool drill rotating speed, numerical control machine tool position movement and the like.
The commonly used rotating speed measuring methods at present comprise: the method comprises the following steps that a photoelectric coded disc speed measurement method, a Hall element speed measurement method, a centrifugal speed measurement method, a tachogenerator speed measurement method and a flash speed measurement method are adopted, most of the methods have the problems of unsatisfactory measurement effect and harsh measurement conditions and difficulty in realization, and for example, the photoelectric coded disc has the defects of sensitivity to strong light, low rotating speed measurement precision and the like; when the hall element is used for measuring speed, if the rotating speed of the measured object is too low, the period of the change of the magnetic induction strengthening is larger than the period of reading pulse signals, and the measurement is inaccurate. When the centrifugal speed measurement method is used for measuring the rotating speed, the end of a tachometer needs to be inserted into a central hole of a rotating shaft of a motor, the shaft of the tachometer needs to be concentric with the shaft of the motor, and otherwise, the reading is easily influenced; tachogenerator tachometers are generally designed with very low flux density and must be guaranteed in the linear region to ensure that the speed of rotation is proportional to the electromotive force generated. The flash velocimetry can only measure high rotation speed, but cannot measure low rotation speed.
Therefore, a method for measuring the rotating speed of the rotating body in real time, which has high measurement accuracy and a simple and convenient measurement mode, is needed to realize the rotating speed detection in the rotating body speed increasing and decreasing process.
Disclosure of Invention
In view of the above, the invention provides a method for measuring the rotating speed of a rotating body in real time by using an accelerometer and combining a DFA method, the accelerometer is used for measuring the rotating speed of the rotating body in real time, the measurement precision is high, the measurement mode is simple and convenient, and the method can be used for detecting the rotating speed of the rotating body in the speed increasing and decreasing processes. Meanwhile, the real-time trend term error of the detection signal in the processes of the rising and the falling of the rotating body is considered, and the detection signal is subjected to real-time data processing by combining with a DFA (deterministic Fluctuation Analysis) method, so that the measurement precision is further improved. At present, no relevant research or application exists in relevant fields such as domestic and foreign detection technologies.
Therefore, the invention provides the following technical scheme:
the invention provides a method for measuring the real-time rotating speed of a rotating body by applying an accelerometer and combining a DFA method, wherein the accelerometer is eccentrically arranged in a signal processing module of the rotating body, and the accelerometer rotates along with the rotating when the rotating body rotates, and the method comprises the following steps:
acquiring original data, collected by the accelerometer in a preset time sequence length, for calculating the rotating speed, and giving initial data segmentation parameters;
dividing the original data into equal parts according to the initial data segmentation parameters, and creating a loop body variable;
removing a trend item of centripetal acceleration in the accelerometer output signal by using a trend fluctuation elimination (DFA) method;
calculating the zero number of each segment of data after the trend fluctuation is eliminated, and judging whether the current data division is fine enough;
when the current data division is fine enough, calculating the sum of zero points of spliced trend fluctuation elimination data, and calculating the rotation period number of the accelerometer based on the sum of the zero points;
and calculating the rotating speed of the rotating body based on the number of the accelerometer rotating cycles and the length of the time sequence.
Further, the dividing the original data into equal parts according to the initial data segmentation parameters, and creating a loop body variable, including:
equally divide the original data into 2 l Segment, l represents an initial data segmentation parameter;
a loop body variable i is created, given its initial value i-1.
Further, calculating the number of zero points in each segment of data after eliminating trend fluctuation, and judging whether the current data division is fine enough, wherein the method comprises the following steps:
calculating the trend item of the ith data, eliminating the trend item from the ith data, and calculating the zero point number m of the trend fluctuation elimination data of the section i ；
When i is less than 2, if i is less than or equal to 2 l And i is i +1, returning the trend item for calculating the ith section of data, removing the trend item from the section of data, and calculating the zero point number m of the section of trend fluctuation elimination data i A step (2);
when i is larger than or equal to 2, sequentially judging whether the absolute value of the difference value of the zero numbers of the adjacent sections is smaller than 2, if the absolute value of the difference value of the zero numbers of the adjacent sections is smaller than 2, dividing the current data into enough fine data, otherwise, making l equal to l +1, and returning to execute the step of equally dividing the original data into 2 l And (5) a step of section.
Further, calculating the sum of zero points of the trend fluctuation elimination data after splicing, and calculating the rotation period number of the accelerometer based on the sum of the zero points, including:
calculating the sum of zero numbers of trend fluctuation eliminating data after splicing
Calculating the rotation period number n of the accelerometer to be m/2; if m% 2 ≠ 0, n ═ n + 1;
correspondingly, calculating the rotating speed of the rotating body based on the number of the accelerometer rotating cycles and the length of the time sequence comprises:
calculating real-time rotating speed of rotating body through time sequence length t of sampling samples of accelerometer
Further, acquiring raw data collected by the accelerometer in a predetermined time sequence length for calculating the rotation speed comprises:
intercepting output waveform signals of two vertical sampling channels of the accelerometer in a preset time sequence length in real time;
down-sampling the output waveform signal as raw data for calculating a rotational speed.
Compared with the prior art, the invention has the following beneficial effects:
the invention discloses a method for detecting the real-time rotating speed of a rotating body, which is characterized in that the real-time rotating speed of the rotating body is an important reference quantity, and an accelerometer is eccentrically arranged in a signal processing module matched with the rotating body to rotate along with the rotating body, so that an acceleration waveform signal detected by the accelerometer is output in real time. Furthermore, considering the trend items existing in the process that the accelerometer measures the speed of the rotating body during the rising and falling of the rotating speed, the trend fluctuation elimination processing is carried out on the output signals, so that zero points exist in data of each rotating period in the rising and falling and speed processes (namely, a wave curve is processed to enable the data to be located near the x axis all the time), the original detection data are gathered near a zero value line, the number of rotating periods of the rotating body is obtained, and the real-time rotating speed is calculated through the sampling time length. The method is simple, reliable, low in cost and strong in environment parameter fluctuation resistance, has very close detection effect compared with the constant speed, expands the application range and is an improved new method.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of a method for measuring the real-time rotating speed of a rotating body by using an accelerometer and combining a DFA method according to an embodiment of the present invention;
FIG. 2 is a diagram of a set of original signal waveforms in an embodiment of the present invention;
FIG. 3 is a waveform diagram of a signal of FIG. 2 after two-stage trend fluctuation elimination according to an embodiment of the present invention;
FIG. 4 is a waveform diagram of a signal of FIG. 2 after eliminating trend fluctuations in four segments according to an embodiment of the present invention;
FIG. 5 is a waveform diagram of signals after eliminating trend fluctuations for the signals of FIG. 2 in eight segments according to an embodiment of the present invention;
Detailed Description
In order to make those skilled in the art better understand the technical solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments 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 of the 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.
DFA (eliminated tendency Analysis) is a scale index calculation method proposed in 1994 based on DNA mechanism for analyzing long-range correlation of time series. The method has the advantages that the method can effectively filter trend components of each order in the sequence, can detect the long-range correlation which contains noise and is superposed with a polynomial trend signal, and is suitable for the long-range power law correlation analysis of a non-stationary time sequence. The analysis method for eliminating trend fluctuation is often applied to comparative analysis for analyzing multiple groups of data with complex trend distribution, such as: comprehensively analyzing the scale characteristics of the stock market by comparing the logarithmic yield sequence of the closing index; analyzing the average air temperature of a certain place in the middle of a plurality of years and the average air temperature of four seasons, and then predicting the change trend of the air temperature of the four seasons in the future; analyzing the rainfall change trend of a certain area for years, summarizing the persistent and random distribution rule, explaining the dynamic rainfall change trend of the area through the change of the vegetation coverage rate of the area, and the like.
As shown in fig. 1, in the method for measuring the real-time rotating speed of a rotating body by using an accelerometer and combining a DFA method in the embodiment of the present invention, for example, when the method is applied to a generator of a motor vehicle to measure the real-time rotating speed, the accelerometer is eccentrically installed in a rotating body signal processing module, and when the rotating body rotates, the accelerometer rotates along with the rotating body, data obtained by a calculator is collected, and then calculation is performed, so that the real-time rotating speed of the rotating body is obtained. Preferably, the accelerometer is a single-axial accelerometer, and the single-axial accelerometer is low in price, convenient to apply, small in required installation space, high in data output sensitivity, stable in performance under normal working conditions and the like, and is commonly used for measuring parameters such as inclination angles and acceleration of equipment. The calculation process mainly comprises the following steps executed by the computer:
s1: acquiring original data used for calculating the real-time rotating speed, and giving initial data segmentation parameters.
The waveform of the acquired raw data is shown in fig. 2. In a specific implementation, S1 includes the steps of:
s11: intercepting output waveform signals of two vertical sampling channels of an accelerometer in a plurality of rotation periods (corresponding to the time sequence with the length of t) in real time;
s12: down-sampling the sampled data to obtain original data for calculating the real-time rotating speed;
s13: a variable l is created as a data segmentation parameter, given its initial value l-1.
S2: and (4) equally dividing the original data into sections according to the data segmentation parameters, and creating a loop body variable.
In a specific implementation, S2 includes the steps of:
s21: the computer equally divides the data into 2 l ＝2 1 2 parts;
s22: a loop body variable i is created, given its initial value i equal to 1.
S3: when the accelerometer rotates, a trend item of centripetal acceleration exists in an output signal of the accelerometer, and the trend item is removed from original data, so that each section of data with trend fluctuation eliminated can be subjected to zero point calculation. And calculating the zero number of each section, judging whether the current data division is fine enough, and determining the subsequent calculation direction.
In a specific implementation, S3 includes the steps of:
s31: calculating the trend item of the ith data, eliminating the trend item from the ith data, and calculating the zero point number m of the trend fluctuation elimination data of the section i ；
S32: when i < 2, execution of S33 is skipped from the current step; when i is larger than or equal to 2, sequentially judging whether the absolute value of the difference value of the number of the zero points of each adjacent section is smaller than 2, if the absolute value of the difference value of the number of the zero points of each adjacent section is smaller than 2, executing S4, otherwise, returning to S21;
sequentially judging whether the absolute value of the difference value of the number of the zero points of each adjacent section is less than 2 can be implemented according to the following modes: and establishing a Boolean variable For setting the judgment result, wherein the initial value is true, establishing a For cycle, sequentially judging whether the absolute value of the difference value of the zero numbers of each adjacent section is less than 2 in the cycle, if all the absolute values are met, the Boolean value is unchanged, and if not, the Boolean value is inverted and the cycle is skipped. And (4) taking the truth of the Boolean value as a judgment basis for judging whether all the Boolean values meet the condition (the absolute value of the difference value of the number of zero points of each adjacent section is less than 2).
S33: if i is less than or equal to 2 l If i is equal to i +1, the process returns to S31, otherwise S4 is executed.
In this embodiment, accelerometer waveform data with t being 1s is obtained, and after the above steps, an acceleration value table after the trend term is eliminated is shown in table 1 below, and a curve is drawn by plotting a numerical value after the trend fluctuation is eliminated, as shown in fig. 5.
TABLE 1
Ignoring the determination condition | m in step S32 i+1 -m i If l is less than 2, when l is 1, the elimination trend fluctuation data distribution is as shown in fig. 3; when l is 2, the tendency elimination fluctuation data distribution is as shown in fig. 4. In this embodiment, the final l is 3, that is, the data is divided again 2 times, thereby skipping m i+1 -m i And (5) completing the calculation under the condition that the | is less than 2. And finally, i is 8, namely the data is finally divided into 8 sections to meet the precision requirement, and the data obtained after the trend fluctuation is eliminated meets the calculation requirement.
S4: and calculating the sum of zero points of the spliced trend fluctuation elimination data, and solving the accelerometer rotation period number corresponding to the data.
In a specific implementation, S4 includes the steps of:
s41: summing the number of zeros of the full data
S42: obtaining the number of the periods n, m/2, 15, wherein the data has 16 accelerometer rotation periods in total because m% 2 is 1 and n +1 is 16;
s5: calculating real-time rotating speed by the time sequence length t ═ 1s corresponding to the accelerometer sampling samples
The initial l is 1, i is 2, that is, the data is divided into 2 segments, and goes through 2 cycles, and finally l is 3, i is 8, that is, the data is divided into 8 segments, so that the division precision is satisfied, and the calculation is completed.
In the embodiment of the invention, the accelerometer is eccentrically arranged in the signal processing module matched with the rotating body so as to rotate along with the rotating body, and the detected acceleration waveform signal is output in real time. Considering trend items existing in the process that an accelerometer measures the rotating speed of a rotating body during rising and falling, trend fluctuation elimination processing is carried out on output signals, so that zero points exist in data of each rotating period in the rising and falling and speed processes (namely, a waveform curve is processed to enable the data to be located near an x axis all the time), original detection data are gathered near a zero line, the number of rotating periods of the rotating body is obtained, and the real-time rotating speed is calculated through the sampling time length. The method is simple and reliable, low in cost and strong in environment parameter fluctuation resistance, has very close detection effects compared with the constant speed, expands the application range, and is an improved new method.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (5)
1. A method for measuring the real-time rotating speed of a rotating body by applying an accelerometer and combining a DFA method is characterized in that the accelerometer is eccentrically arranged in a signal processing module of the rotating body, and the accelerometer rotates along with the rotating when the rotating body rotates, and the method comprises the following steps:
acquiring original data, collected by the accelerometer in a preset time sequence length, for calculating the rotating speed, and giving initial data segmentation parameters;
according to the initial data segmentation parameters, the original data are segmented in an equal-fractional mode, and a loop body variable is created;
removing a trend item of centripetal acceleration in the accelerometer output signal by using a trend fluctuation elimination (DFA) method;
calculating the number of zero points in each segment of data after the trend fluctuation is eliminated, and judging whether the current data division is fine enough;
when the current data division is fine enough, calculating the zero point number sum of the spliced trend fluctuation elimination data, and calculating the rotation period number of the accelerometer based on the zero point number sum;
and calculating the rotating speed of the rotating body based on the number of the accelerometer rotating cycles and the length of the time sequence.
2. The method for real-time rotation speed measurement of a rotating body by using an accelerometer and combining a DFA method according to claim 1, wherein the step of equally dividing the raw data into sections according to the initial data segmentation parameters and creating a cycle body variable comprises the following steps:
equally divide the original data into 2 l Segment, l represents an initial data segmentation parameter;
a loop body variable i is created, given its initial value i equal to 1.
3. The method for measuring the real-time rotating speed of a rotating body by using an accelerometer and combining a DFA method as claimed in claim 2, wherein the step of calculating the number of zero points in each section of data after eliminating trend fluctuation and judging whether the current data division is fine enough comprises the steps of:
calculating the trend item of the ith data, eliminating the trend item from the ith data, and calculating the zero point number m of the trend fluctuation elimination data of the section i ；
When i is less than 2, if i is less than or equal to 2 l I is i +1, and returns the trend item for calculating the ith data and picks it from the dataDividing and calculating the zero point number m of the section of elimination trend fluctuation data i A step (2);
when i is larger than or equal to 2, sequentially judging whether the absolute value of the difference value of the number of zero points of each adjacent segment is smaller than 2, if the absolute value of the difference value of the number of zero points of each adjacent segment is smaller than 2, dividing the current data into enough fine data, otherwise, making l equal to l +1, and returning to execute the operation of equally dividing the original data into 2 l And (5) a step of section.
4. The method for measuring the real-time rotating speed of a rotating body by using an accelerometer and combining a DFA method according to claim 2, wherein the step of calculating the sum of zero points of trend elimination fluctuation data after splicing is completed and calculating the number of the rotating cycles of the accelerometer based on the sum of the zero points comprises the following steps:
calculating the sum of zero numbers of trend fluctuation eliminating data after splicing
Calculating the rotation period number n of the accelerometer to be m/2; if m% 2 ≠ 0, n ═ n + 1;
correspondingly, calculating the rotating speed of the rotator based on the accelerometer rotation period number and the time sequence length, and comprising:
calculating real-time rotating speed of rotating body through time sequence length t of sampling samples of accelerometer
5. The method for measuring the real-time rotating speed of a rotating body by using an accelerometer and combining a DFA method as claimed in claim 1, wherein the step of acquiring raw data collected by the accelerometer in a preset time sequence length for calculating the rotating speed comprises the following steps:
intercepting output waveform signals of two vertical sampling channels of the accelerometer in a preset time sequence length in real time;
down-sampling the output waveform signal as raw data for calculating a rotational speed.
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| JP2007132871A (en) * | 2005-11-11 | 2007-05-31 | Nissan Motor Co Ltd | Rotational frequency measuring method of engine and rotational frequency measuring device |
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| WO2021022656A1 (en) * | 2019-08-02 | 2021-02-11 | 湖南联智桥隧技术有限公司 | Data processing method |
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