CN112434561B - Method for automatically judging effectiveness of shock wave signal - Google Patents
Method for automatically judging effectiveness of shock wave signal Download PDFInfo
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- CN112434561B CN112434561B CN202011207801.7A CN202011207801A CN112434561B CN 112434561 B CN112434561 B CN 112434561B CN 202011207801 A CN202011207801 A CN 202011207801A CN 112434561 B CN112434561 B CN 112434561B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
- G06F2218/04—Denoising
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L5/00—Apparatus for, or methods of, measuring force, work, mechanical power, or torque, specially adapted for specific purposes
- G01L5/0052—Apparatus for, or methods of, measuring force, work, mechanical power, or torque, specially adapted for specific purposes measuring forces due to impact
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/12—Classification; Matching
Abstract
The invention discloses a method for automatically judging the effectiveness of a shock wave signal. When the shock wave signal acquisition terminal is provided with a high-speed wireless transmission link, the data processing process is carried out in the upper computer, otherwise, the data processing process is carried out in the acquisition terminal. A data matching template is established in the upper computer after a series of data processing, and the similarity of each data is calculated by using the template, so that the signal effectiveness is judged; and judging whether the shock wave signal is normal or not by mainly checking whether the rising phase of the collected signal is shorter, whether the signal larger than the peak value of the rising phase appears in the attenuation process again and whether the attenuation process accords with the physical rule from fast to slow at the signal collecting terminal. The method for automatically judging the effectiveness of the shock wave signal has the advantages of high response speed, high real-time efficiency, high accuracy and stronger adaptability.
Description
Technical Field
The invention belongs to the technical field of mode identification and signal processing, in particular to the technical field of information processing of shock wave signals, and more particularly relates to a method for automatically judging the effectiveness of shock wave signals.
Background
In order to accurately measure and evaluate the shock wave signal, real-time measurement is required on site by adopting an overpressure sensor and the like. In general, the field condition for acquiring the shock wave signal data is complex, and the signal acquired by the sensor can be interfered by various unknown factors, so that the accuracy of signal measurement is affected, for example, the sensor acquires abnormal signals due to direct impact of flying stones and fragments on the sensor. In order to obtain accurate impact signals, validity judgment is needed to be carried out on the collected impact signals, and the explosion effect can be accurately estimated after invalid signals are removed.
The currently mainstream method for judging the effectiveness of the shock wave signal mainly carries out judgment by manpower, the problem of low efficiency and low accuracy exists in the manual judgment, and no method capable of automatically judging the effectiveness of the shock wave signal on a signal acquisition terminal or an upper computer exists at present, so that a method capable of automatically judging the effectiveness of the shock wave signal is needed to replace the manual judgment.
Disclosure of Invention
In view of this, the present invention provides a method for automatically determining the effectiveness of a shockwave signal.
To achieve the purpose, the invention adopts the following technical scheme: a method for automatically judging the effectiveness of a shock wave signal comprises the steps of firstly utilizing an acquisition terminal to acquire waveform data, then carrying out data processing on an upper computer or the acquisition terminal, and finally judging the effectiveness of the shock wave signal.
Preferably, when the shock wave signal acquisition terminal has a high-speed wireless transmission link, the data processing process is performed in the upper computer, and the data processing steps are as follows:
step 1: the upper computer receives waveform data acquired by a plurality of signal acquisition terminals;
step 2: the upper computer performs noise reduction and filtering on all waveform data;
step 3: detecting respective occurrence moments of all waveform data respectively, and aligning signals by taking the occurrence moments as centers;
step 4: selecting a time window of 1ms for each waveform data respectively, and carrying out normalization processing on all data in the time window;
step 5: carrying out wavelet transformation on the normalized data, and converting the normalized data into corresponding time-frequency signals;
step 6: symbol mapping is carried out on the time-frequency domain signal, the time-frequency domain signal is equally divided into three sections according to the absolute value of the time-frequency domain signal, and then three-value mapping is carried out;
step 7: calculating the similarity of different terminal data after symbol mapping, selecting three data with highest correlation, merging the same parts in the data to generate a data matching template;
step 8: firstly, symbol mapping is carried out on data from different acquisition terminals, then, the similarity between the data after symbol mapping and a data matching template is calculated, the effectiveness of the shock wave signals is judged according to the similarity, and the effectiveness signals can be judged if the similarity is more than 70%.
Preferably, when the shock wave signal acquisition terminal does not have a high-speed wireless transmission link, the data processing process is performed at the signal acquisition terminal, and the data processing steps are as follows:
step one: detecting a shock wave starting point at a system acquisition terminal;
step two: after the detection of the shock wave, comparing signal values at different moments, and detecting a shock wave signal peak value v_max;
step three: calculating the decay time of the shock wave signal;
step four: signal abnormality judgment is carried out;
step five: judging the confidence level of the signal;
step six: and transmitting the peak value data and the waveform confidence information of the impulse wave signal of the effective signal to the upper computer.
Preferably, the method of the process of data processing at the signal acquisition terminal is performed for a single waveform signal.
Preferably, in the first step, the start point of the shock wave is detected, and when v (n) -v (m) > TH0 and n-m=2, the signal start point time t1=n, where n and m are different sampling moments, and v (n) and v (m) are sampling signal values corresponding to n and m, respectively.
Preferably, the method for calculating the signal shock wave attenuation time in the third step is as follows: calculating the average value of the sampled signal value v (T) from the time T1, and when the average value is smaller than v_max, the corresponding time is T2, and the first stage is called; calculating the average value of the sampling signal v (T) from the time T2, and when the average value is smaller than v_max, the corresponding time is T3, which is called the second stage; calculating the average value of the sampling signal v (T) from the time T3, and when the average value is smaller than v_max, the corresponding time is T4, which is called the third stage; wherein a, b and c are signal attenuation coefficients, and the three components form a decreasing arithmetic progression with the value range of 0.2-0.8.
Preferably, the method for judging the abnormal signal in the fourth step includes: when T1 is more than TH1, the shock wave signal is an abnormal signal; or when v_max2> v_max5/4, the shock wave signal is an abnormal signal, wherein TH1 is the signal rising reference time set by a user according to the system characteristic and the characteristic of the sensor; v_max2 is the signal maximum value of the signal decay period.
Preferably, in the fifth step, confidence judgment is performed according to TH2 x k2< (T2-T1) < TH2 x k1; (T2-T1) k4< (T3-T2) < (T2-T1) k3; (T3-T2) k6< (T4-T3) < (T3-T2) k5, wherein k1, k2, k3, k4, k5 and k6 are constraint coefficients, the value range is 0.5-2, and the TH2 is a time parameter of a first stage of signal attenuation set by a user according to the sensor characteristics.
The beneficial effects of the invention are as follows: when the automatic judging method of the effectiveness of the shock wave signal is used for judging the effectiveness of the signal by an upper computer, wavelet transformation is firstly carried out on normalized data, common characteristics of multi-source data are counted according to time-frequency information during signal generation, a plurality of data with highest correlation degree are selected to establish a matching template, and then the similarity of each data is calculated by using the template, and the similarity has strong universal adaptability and has small correlation with factors such as sensor characteristics, shock wave size and the like;
when the signal acquisition terminal judges the signal effectiveness, judging whether the shock wave signal is abnormal or not by generating a new larger peak signal or not when the shock wave generates a time from the rise to the maximum peak and decays, wherein the time from the maximum peak to the maximum peak is related to the strength of the signal and needs to be set according to the field condition; the confidence coefficient calculation of the signal is to divide the signal attenuation process into three stages, determine the proportionality coefficient of the three stages and the maximum peak value according to the response characteristic of the sensor, then obtain the proportionality relation of the corresponding attenuation time according to the signal attenuation characteristic, obtain a confidence coefficient information by judging whether the actual data accords with the proportionality relation, and carry out data processing at the acquisition terminal simply and easily;
the automatic judging method for the effectiveness of the shock wave signals can select a corresponding judging method according to whether the acquisition terminal has a high-speed wireless transmission link or not, and compared with the traditional manual judging method, the automatic judging method for the effectiveness of the shock wave signals has the advantages of high response speed, real-time efficiency, high accuracy and stronger adaptability.
Drawings
FIG. 1 is a flow chart of the method for automatically determining the effectiveness of a shock wave signal according to the present invention for data processing in an upper computer.
Detailed Description
Those of ordinary skill in the art will recognize that the embodiments described herein are for the purpose of aiding the reader in understanding the principles of the present invention and should be understood that the scope of the invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific modifications and combinations from the teachings of the present disclosure without departing from the spirit thereof, and such modifications and combinations remain within the scope of the present disclosure.
The invention will now be described in detail with reference to the drawings and specific examples.
The method comprises the steps of firstly utilizing an acquisition terminal to acquire waveform data, then carrying out data processing on an upper computer or the acquisition terminal, and finally carrying out shock wave signal validity judgment.
Specifically, when the shock wave signal acquisition terminal has a high-speed wireless transmission link, the data processing process in the method for automatically judging the effectiveness of the shock wave signal is performed in the upper computer, and the steps are as follows as shown in fig. 1:
step 1: the upper computer receives waveform data acquired by a plurality of signal acquisition terminals;
step 2: the upper computer performs noise reduction and filtering on all waveform data;
step 3: detecting respective occurrence moments of all waveform data respectively, and aligning signals by taking the occurrence moments as centers;
step 4: selecting a time window of 1ms for each waveform data respectively, and carrying out normalization processing on all data in the time window;
step 5: wavelet transformation is carried out on the normalized data, wherein a Morse wavelet is selected as a kernel function, a symmetry parameter (gamma) is 3, a signal is expressed by s (t), and an acquisition signal is converted into a 2-dimensional time-frequency domain signal WT (a, b), as shown in a formula (1):
WT(a，b)＝CWT(s(t)，Morse，gamma)(1)
step 6: symbol mapping is carried out on the time-frequency domain signals WT (a, b) through a symbol dynamic filtering method, the time-frequency domain signals WT (a, b) are divided into three sections according to the absolute value of the WT (a, b), and then the WT (a, b) is mapped in three values;
step 7: calculating the similarity of different terminal data after symbol mapping, selecting three data with highest correlation, merging the same parts in the data to generate a data matching template; two different data correlation calculation methods are shown in formula (2):
step 8: and carrying out symbol mapping on the data from different acquisition terminals, calculating the similarity between the data after symbol mapping and the data matching template, judging the effectiveness of the shock wave signals according to the similarity, and judging that the similarity is more than 70% as effective signals.
The template calculation and the matching calculation in the steps 7 and 8 are based on the symbol mapped data.
When the shock wave signal acquisition terminal does not have a high-speed wireless transmission link, the data processing process is carried out on the signal acquisition terminal, the judgment result of the data processing process is obtained by the peak value data and the waveform confidence information of the shock wave, and the equivalent evaluation of the shock wave can be completed only by returning the peak value data and the confidence information to the upper computer. The shock wave signal will generate a fast rising signal in a short time (< 10 us) and then will decay slowly, for a period of about 0.3 to 1ms. In the present invention, the signal generation phase is referred to as a rising phase, and the subsequent 0.3 to 1ms is referred to as a decay phase. The data processing step at the signal acquisition terminal is as follows:
step one: the shock wave starting point detection is carried out at a system acquisition terminal, and the specific detection method comprises the following steps: taking sampling values value=v (1), v (2), v (3), … … and v (t); when v (n) -v (m) > TH0 and n-m=2, obtaining signal starting time T0=n, wherein n and m are different values of time T, and v (n) and v (m) are signal sampling values corresponding to n and m moments respectively;
step two: after the impact is detected, comparing signal values at different moments, detecting the peak value of the impact wave signal, wherein the detection time is smaller than a threshold value T_max, the value T_max is related to the position of a sensor, the intensity of the impact wave and other information and is not a fixed value, the detected maximum value is peak value data (v_max) of the impact wave in the time T_max, the data can be uploaded to an upper computer, and the time corresponding to the detected peak value of the signal is T1;
step three: the method for calculating the decay time of the shock wave signal comprises the following specific steps: calculating the average value of the sampled signal value v (T) from the time T1, and when the average value is smaller than v_max, the corresponding time is T2, and the first stage is called; calculating the average value of the sampling signal v (T) from the time T2, and when the average value is smaller than v_max, the corresponding time is T3, which is called the second stage; calculating the average value of the sampling signal v (T) from the time T3, and when the average value is smaller than v_max, the corresponding time is T4, which is called the third stage; wherein a, b and c are signal attenuation coefficients, and the three are in descending arithmetic progression, and the value range is 0.2-0.8, for example, a=0.8, b=0.6 and c=0.4;
step four: the signal abnormality judgment method comprises the following steps: when T1 is more than TH1, the shock wave signal is an abnormal signal; or when v_max2> v_max5/4, the shock wave signal is an abnormal signal, wherein TH1 is the signal rising reference time set by a user according to the system characteristic and the characteristic of the sensor; v_max2 is the signal maximum value of the signal decay period;
step five: judging the signal confidence, wherein the judgment basis is TH2 x k2< (T2-T1) < TH2 x k1; (T2-T1) k4< (T3-T2) < (T2-T1) k3; (T3-T2) k6< (T4-T3) < (T3-T2) k5, wherein k1, k2, k3, k4, k5 and k6 are constraint coefficients, the value range is 0.5-2, and the TH2 is a time parameter of a first stage of signal attenuation set by a user according to the sensor characteristics;
step six: and transmitting the peak value data and the waveform confidence information of the impulse wave signal of the effective signal to the upper computer.
The method for processing data at the acquisition terminal is only carried out for a single waveform signal, and the method mainly judges whether the signal is a normal shock wave signal or not by checking whether the rising phase of the signal of the acquired signal is shorter, whether the signal attenuation process is larger than the peak signal in the rising phase again or not and whether the signal attenuation process accords with the physical rule from fast to slow or not.
In summary, when the signal effectiveness is judged by the upper computer, wavelet transformation is firstly carried out on normalized data, common characteristics of multi-source data are counted according to time-frequency information when the signal is generated, a plurality of data with highest correlation degree are selected to establish a matching template, and then the similarity of each data is calculated by utilizing the template, wherein the similarity has stronger universal adaptability and has small correlation with factors such as sensor characteristics, shock wave size and the like;
when the signal acquisition terminal judges the signal effectiveness, judging whether the shock wave signal is abnormal or not by generating a new larger peak signal or not when the shock wave generates a time from the rise to the maximum peak and decays, wherein the time from the maximum peak to the maximum peak is related to the strength of the signal and needs to be set according to the field condition; the confidence coefficient calculation of the signal is to divide the signal attenuation process into three stages, determine the proportionality coefficient of the three stages and the maximum peak value according to the response characteristic of the sensor, then obtain the proportionality relation of the corresponding attenuation time according to the signal attenuation characteristic, and obtain a confidence coefficient information by judging whether the actual data accords with the proportionality relation.
The automatic judging method for the effectiveness of the shock wave signals can select a corresponding judging method according to whether the acquisition terminal has a high-speed wireless transmission link or not, and compared with the traditional manual judging method, the automatic judging method for the effectiveness of the shock wave signals has the advantages of high response speed, real-time efficiency, high accuracy and stronger adaptability.
Claims (3)
1. The method is characterized in that the method firstly utilizes an acquisition terminal to acquire waveform data, then carries out data processing on an upper computer or the acquisition terminal, and finally carries out the judgment of the effectiveness of the shock wave signal;
when the shock wave signal acquisition terminal does not have a high-speed wireless transmission link, the data processing process is performed at the signal acquisition terminal, and the data processing steps are as follows:
step one: aiming at a single waveform signal, detecting a shock wave starting point at a system acquisition terminal;
step two: after the detection of the shock wave, comparing signal values at different moments, and detecting a shock wave signal peak value v_max;
step three: calculating the decay time of the shock wave signal;
step four: signal abnormality judgment is carried out;
step five: judging the confidence level of the signal;
step six: transmitting the peak value data and the waveform confidence information of the impulse wave signal of the effective signal to an upper computer;
detecting a shock wave starting point in the first step, and when v (n) -v (m) > TH0 and n-m=2, the signal starting point time T1=n, wherein n and m are different sampling moments, and v (n) and v (m) are sampling signal values corresponding to n and m respectively;
the method for calculating the signal shock wave attenuation time in the third step comprises the following steps: calculating the average value of the sampled signal value v (T) from the time T1, and when the average value is smaller than v_max, the corresponding time is T2, and the first stage is called; calculating the average value of the sampling signal v (T) from the time T2, and when the average value is smaller than v_max, the corresponding time is T3, which is called the second stage; calculating the average value of the sampling signal v (T) from the time T3, and when the average value is smaller than v_max, the corresponding time is T4, which is called the third stage; wherein a, b and c are signal attenuation coefficients, and the three components form a decreasing arithmetic progression with the value range of 0.2-0.8;
the method for judging the abnormal signal in the fourth step comprises the following steps: when T1> TH1, the shock wave signal is an abnormal signal; or when v_max2> v_max5/4, the shock wave signal is an abnormal signal, wherein TH1 is a signal rising reference time set by a user according to the characteristics of the system and the characteristics of the sensor; v_max2 is the signal maximum value of the signal decay period.
2. The method for automatically determining the validity of a shock wave signal according to claim 1, wherein when the shock wave signal acquisition terminal is provided with a high-speed wireless transmission link, the data processing process is performed in an upper computer, and the data processing comprises the following steps:
step 1: the upper computer receives waveform data acquired by a plurality of signal acquisition terminals;
step 2: the upper computer performs noise reduction and filtering on all waveform data;
step 3: detecting respective occurrence moments of all waveform data respectively, and aligning signals by taking the occurrence moments as centers;
step 4: selecting a time window of 1ms for each waveform data respectively, and carrying out normalization processing on all data in the time window;
step 5: carrying out wavelet transformation on the normalized data, and converting the normalized data into corresponding time-frequency signals;
step 6: symbol mapping is carried out on the time-frequency domain signal, the time-frequency domain signal is equally divided into three sections according to the absolute value of the time-frequency domain signal, and then three-value mapping is carried out;
step 7: calculating the similarity of different terminal data after symbol mapping, selecting three data with highest correlation, merging the same parts in the data to generate a data matching template;
step 8: firstly, symbol mapping is carried out on data from different acquisition terminals, then, the similarity between the data after symbol mapping and a data matching template is calculated, the effectiveness of the shock wave signals is judged according to the similarity, and the effectiveness signals can be judged if the similarity is more than 70%.
3. The method according to claim 1, wherein the confidence level determination is performed in the fifth step according to TH2 x k2< (T2-T1) < TH2 x k1; (T2-T1) k4< (T3-T2) < (T2-T1) k3; (T3-T2) k6< (T4-T3) < (T3-T2) k5, wherein k1, k2, k3, k4, k5 and k6 are constraint coefficients, the value range is 0.5-2, and the TH2 is a time parameter of a first stage of signal attenuation set by a user according to the sensor characteristics.
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