CN110780100B - Oscilloscope automatic setting method based on frequency rapid measurement algorithm - Google Patents

Abstract

The invention discloses an automatic setting method of an oscilloscope based on a time domain software measuring amplitude and frequency fast measurement algorithm, which comprises: extracting a plurality of characteristic arrays with different time intervals from the data to be processed; Determine the peak value and the minimum number of integer cycles, and find an array that can represent the peak-to-peak value and frequency characteristics of the signal; then set the horizontal time base and vertical amplitude gears according to the array. The invention has the characteristics of low cost, high speed, wide application range and the like.

Description

An automatic setting method of oscilloscope based on fast frequency measurement algorithm

technical field

The invention belongs to the field of electronic measuring instruments, in particular to a fast measurement algorithm for measuring amplitude and frequency by time domain software, and a fast automatic setting method for a digital oscilloscope based on the algorithm.

Background technique

As the most commonly used measuring instrument in the field of electronic information, the oscilloscope plays a huge role in major universities, laboratories, companies, etc., but it is often necessary to manually adjust the horizontal time base and vertical amplitude to make the waveform display well. , and the automatic setting function can automatically set the horizontal time base and vertical amplitude to meet the user's requirements.

The automatic setting function actually measures the amplitude and frequency of the signal to determine the horizontal time base and vertical amplitude that should be selected. The general method is to initialize an amplitude gear first, and then obtain its amplitude or frequency through a specific method. If If the amplitude gear is not suitable, it is necessary to adjust the amplitude gear and measure again.

In the existing methods, the measurement of signal amplitude can be divided into two categories: software and hardware. The hardware is generally implemented by a peak detection circuit; while the software generally obtains the maximum and minimum values by traversing the sampled data once, and the amplitude of the signal can be obtained by making the difference between the two. The frequency measurement of unknown signals can also be roughly divided into two categories: hardware and software. Among them, the hardware is mainly to output a square wave related to the frequency of the input signal through the comparison circuit after shaping the input signal, and then use the frequency measurement circuit to measure its frequency. Common methods include: direct frequency measurement method, multi-cycle frequency measurement method etc.; software frequency measurement can be divided into time domain frequency measurement and frequency domain frequency measurement. Time domain frequency measurement generally traverses the sampled data twice, and calculates the signal frequency by calculating the number of sampling points in each signal cycle. Frequency domain frequency measurement generally adopts the fast Fourier transform of the sampled data to convert it into frequency domain and finds the frequency of the maximum frequency component in the signal except the DC component, which can be regarded as the signal frequency.

However, the above methods all have certain problems in use. For example, the "automatic setting method of digital oscilloscope" disclosed in Chinese patent CN101609106A and the "automatic setting control method of digital phosphor oscilloscope" disclosed in Chinese patent CN103809002A both use hardware circuits to measure frequency, software methods to measure amplitude, and then use the dichotomy method to measure the amplitude. A method of repeating the measurement again after the gear has been adjusted. In actual use, the frequency measurement circuit requires that the amplitude gear is set properly, the input signal amplitude is large enough and the comparison level is set reasonably, while the time domain software measurement of the amplitude requires the time base gear to be set reasonably and traverse at least one cycle of data. , the higher the sampling rate, the more time it takes. At the same time, due to the mutual constraints of frequency measurement and amplitude measurement, the automatic setting often requires repeated measurements, which consumes a lot of time and has low accuracy.

The "automatic setting method of a digital oscilloscope" disclosed by Chinese patent CN105510664A and the "fast automatic setting method of a digital oscilloscope based on hardware centralized type" disclosed by Chinese patent CN106597048A both use hardware circuits to measure frequency, and hardware peak detection to measure amplitude. Way. Its frequency measurement still faces the above problems, and although the peak detection mode it adopts avoids the shortcomings of time-domain software frequency measurement, which requires a large amount of computation and time-consuming, its allowable signal frequency is low, which is difficult to apply to high-frequency signals. .

Chinese patent CN108037339A discloses "a control method for automatic setting of digital oscilloscope" using software to measure amplitude and frequency domain software to measure frequency. It synchronizes software amplitude measurement and sampling, which avoids the shortcomings of the above-mentioned patents in amplitude measurement, but it is not suitable for oscilloscopes with high sampling rate. When the data acquisition speed is higher than the processing speed of FPGA, the amplitude measurement and sampling cannot be maintained. synchronization, resulting in an increase in the consumption time. The measurement of the frequency requires fast Fourier transform of the data, and as the sampling rate increases, the amount of data to be calculated will also increase, and the time consumption will also increase significantly. In addition, since it requires parallel processing of sampled data and fast Fourier transform, a hardware processor such as FPGA is required, and as the sampling rate of the oscilloscope increases, the resource occupation is larger and the cost is higher.

To sum up, most of the current oscilloscope automatic setting methods have their own shortcomings in terms of speed, accuracy, applicable frequency range, and cost.

SUMMARY OF THE INVENTION

In order to solve the problems of fast automatic setting speed, wide applicable frequency range and low cost of oscilloscope in realizing automatic setting function, the present invention proposes an oscilloscope automatic setting method based on time domain software measuring amplitude and frequency fast algorithm. The peak-to-peak value and the minimum number of integer cycles are compared between the characteristic arrays of different time intervals, so as to realize the rapid measurement of the signal amplitude and frequency, and then achieve the purpose of automatic setting.

The present invention provides an oscilloscope automatic setting method based on time domain software measuring amplitude and frequency fast algorithm, comprising the following steps:

S1: Initially adjust the amplitude gear at the beginning of automatic setting. The specific process is as follows:

S11: At the beginning, set the range S _v of the amplitude gear to the maximum range;

S12: Set the time base gear to the minimum, and determine the number of sampling points N for sampling according to the automatically set minimum recognition frequency f _min and the maximum sampling rate f _max corresponding to the minimum time base gear:

S13: Extract M feature arrays Array ₁ to Array _M with different time intervals from the sampled data;

再将所有特征数组的峰峰值比较，得到最大峰峰值Vpp_max；S14: Perform a traversal of each feature array in the M feature arrays, and obtain the maximum value MAX _i and the minimum value MIN _i of the feature array, i=1, 2, ..., M, and the difference between the two is obtained. The peak-to-peak value of the characteristic array Vpp _i =MAX _i -MIN _i , the sum of the two is averaged to obtain the median value of the characteristic array

Then compare the peak-to-peak values of all feature arrays to obtain the maximum peak-to-peak value Vpp _max ;

S15: Determine whether the maximum peak-to-peak Vpp _max is greater than S _v ×ε, where ε is the threshold constant, if it is greater than it, go to step S2, otherwise, adjust the range S _v of the amplitude gear to the minimum range greater than Vpp _max , and return to step S12 to re- sampling;

S2: According to the peak-to-peak criterion and the minimum whole period criterion, find a judgment array that can represent the signal amplitude and frequency characteristics. The specific process is as follows:

S21: initialize i=1;

S22: Determine whether the peak-to-peak value Vpp _i of the feature array Array _i is less than α×Vpp _max , where α is a constant, if it is less than, set i=i+1, and return to step S22 to continue the judgment, otherwise, go to step S23;

S23: let j=i;

S24: Calculate the minimum integer period Num of the feature array Array _j according to the minimum integer period algorithm, and determine whether the minimum integer period Num is zero. If the minimum integer period Num is zero, set i=j+1 , if i>M, then use the characteristic array Array _j as the judgment array, and go to step S3, otherwise return to step S22 to continue the judgment; if the minimum integer cycle number Num is not zero, then use the characteristic array Array _j as the judgment array, and continue step S3;

S3: Determine the amplitude gear according to the maximum value MAX _j and the minimum value MIN _j of the judgment array Array _j , and then calculate the frequency of the signal and determine the time base gear according to the frequency. The specific process is as follows:

其中，根据峰峰值Vpp_j确定幅度挡位的量程为S_v，使其满足0.4×S_v≤Vpp_j≤0.8×S_v，并把中值

作为相应通道的直流偏置；S31: Calculate the peak-to-peak value Vpp _j and the median value of the judgment array Array _j according to the algorithm of step S14

Among them, according to the peak-to-peak Vpp _j , the range of the amplitude gear is determined as S _v , so that it satisfies 0.4×S _v ≤Vpp _j ≤0.8×S _v , and the median value is

as the DC bias of the corresponding channel;

S32: Calculate the frequency f of the signal, and then determine the time base gear.

Further, the size of each feature array in the M feature arrays is K, the time interval DT corresponding to each feature array is sequentially increased by a multiple of A, and the time interval DT from low to high is 1/f _max , A/f _max , ..., A^(M-1)/f _max , where the number M of feature arrays is calculated as follows:

Among them, A, M, N, K need to satisfy the following formula:

A^(M-1)*K=N.

Further, in step S24, the minimum integer cycle algorithm is specifically as follows:

First, the comparison threshold is judged as follows:

为特征数组Array_j的高比较阈值；

为特征数组Array_j的低比较阈值，Among them, β is the threshold constant; Δ _j is the width of the comparison window;

is the high comparison threshold of the feature array Array _j ;

is the low comparison threshold of the feature array Array _j ,

的部分数量Num_h和小于低比较阈值

的部分数量Num_L，最后得到的是最小整周期数Num为Num_h和Num_L中较小的值减1。Then perform a traversal of the feature array Array _j to find out if the value of the array is greater than the high comparison threshold

The number of parts Num_h and less than the low comparison threshold

The number of parts of Num_L, the final result is the minimum integer cycle number Num is the smaller value of Num_h and Num_L minus 1.

In a possible implementation, in step S24, when calculating the minimum number of integer cycles Num for the feature array, it is determined whether the top of the signal or the bottom of the signal appears first, and if it is the top, it will reach the bottom for the first time C _s , the last array that reaches the bottom is marked as C _e ; otherwise, the array that reaches the top for the first time is marked as C _s , and the last array that reaches the top is marked as C _e .

Further, according to the C _s , C _e of the judgment array Array _j , the corresponding time interval DT _j and the minimum number of integer cycles Num, the frequency f of the signal can be calculated, and then the time base gear can be determined.

In particular, when Num=0, it means that the minimum number of integer cycles Num in the characteristic array of the maximum time interval of the signal is less than 2, then the range of the signal frequency f can be determined:

f _min ≤f<2f _min .

In a possible implementation manner, the specific process of step S32 may be as follows:

Based on the minimum integer cycle number Num of the judgment array Array _j , the corresponding time interval DT _j and the array size K, the frequency range of the signal is calculated according to the following formula, and then the time base gear is determined

In particular, also when Num=0, it means that the number of cycles of the signal in the characteristic array of the maximum time interval is less than 2, then the range of the signal frequency f can be determined

f _min ≤f<2f _min .

Therefore, in the method of realizing automatic setting, the present invention proposes an algorithm for quickly measuring amplitude and frequency. By extracting a plurality of feature arrays with different time intervals from the huge sampling data, the amount of data to be processed is significantly reduced. The peak-to-peak criterion and the minimum full period criterion determine the characteristic array that can approximately characterize the amplitude and frequency characteristics of the signal, and then set the time base gear and amplitude gear. This algorithm makes the time complexity of the calculation of amplitude and frequency change from O(n) to O(log(n)), and the running time is greatly reduced. In the adjustment of the amplitude gear, the present invention adopts the method of coarse adjustment. By comparing the maximum peak-to-peak value of the extracted array with the threshold value, it is judged that it is smaller than the threshold value before the gear adjustment is performed, so that the number of amplitude adjustments in the automatic setting is reduced, and the sampling is performed again. The number of times is reduced, so the automatic setup completes faster.

Beneficial effects of the present invention:

1) The present invention proposes a data extraction method, through which the original data is extracted at multiple equal intervals, while reducing the amount of data while retaining part of the characteristics of the signal; a calculation method for the minimum number of integer cycles is proposed, which can be used when the signal amplitude is close to the actual value. In the case of amplitude, the data contains at least the number of integer periods of the signal. For example, when the value is 1, then the data contains at least one full period of the signal, but the full period will not be greater than 2; The software of interval data extraction is a fast algorithm for measuring signal amplitude and frequency. It judges multiple extracted equal-spaced arrays through the peak-to-peak criterion and the minimum whole period criterion, finds the array that can represent the signal amplitude and frequency information, and then determines the signal's amplitude and frequency. Amplitude and frequency; a method for coarse adjustment of the amplitude gear during the automatic setting of the oscilloscope is proposed, which not only ensures that the signal has a certain amplitude, but also reduces the number of times of adjusting the amplitude gear during the automatic setting process, and reduces the time consumed by the automatic setting.

2) In the realization of the automatic setting, the present invention adopts software algorithms for the measurement of amplitude and frequency, no additional hardware circuit is required, and there is no special requirement for the processing unit, and the program can even be embedded in the main controller of the oscilloscope. , approximately to zero cost.

3) The algorithm of the present invention needs to process a small amount of computation, so the speed is very fast. Even when the sampling rate increases, the computational amount of the algorithm increases very little, so it is also applicable to oscilloscopes with high sampling rate, and has greater advantages.

Description of drawings

Fig. 1 is the flow chart of the oscilloscope automatic setting method based on the frequency fast algorithm of the present invention;

Fig. 2 is the minimum whole cycle algorithm flow chart of the present invention;

FIG. 3 is a result diagram of a minimum integer number of cycles algorithm according to an embodiment of the present invention.

Detailed ways

The present invention will be further described below with reference to the accompanying drawings and embodiments, and it should be understood that the following embodiments are intended to facilitate the understanding of the present invention, but do not have any limiting effect on it.

In the method of automatic setting of the oscilloscope, the present invention adopts the methods of software amplitude measurement and time domain software frequency measurement. Different from the traditional software frequency measurement and amplitude measurement, the present invention extracts a plurality of different time intervals from the data to be processed. Characteristic array (the time interval of each array is fixed, and the time interval of different characteristic arrays is different); judge the peak-to-peak value and the minimum number of integer cycles for these multiple characteristic arrays, and find an array that can represent the peak-to-peak value and frequency characteristics of the signal ; Then set the horizontal time base gear and vertical amplitude gear according to the array. Specifically, the oscilloscope automatic setting method based on the time domain software measuring amplitude and frequency fast measuring algorithm of the present invention, as shown in FIG. 1 , includes the following steps:

S1: Preliminary adjustment of the amplitude gear

When the automatic setting of the oscilloscope starts, the amplitude gear is initially (roughly) adjusted so that the amplitude of the measured signal is satisfied, and then the amplitude and frequency can be measured. The specific process is as follows:

S11: At the beginning, set the range S _v of the amplitude gear to the maximum range;

S12: Set the time base gear to the minimum, and determine the number of sampling points N for sampling according to the automatically set minimum recognition frequency f _min and the maximum sampling rate f _max corresponding to the minimum time base gear of the oscilloscope:

S13: Extract M feature arrays Array ₁ to Array _M with different time intervals from the sampled data, wherein the size of each array is K, and K can be set according to the requirements of the oscilloscope, and the corresponding time interval DT is in order of multiples A Incrementally, from low to high, it is 1/f _max , A/f _max , ..., A^(M-1)/f _max , where M is calculated as follows:

Among them, A, M, N, K need to satisfy the following formula:

A^(M-1)*K=N.

S14: Perform a traversal of each feature array to obtain its maximum value MAX _i and minimum value MIN _i (i=1, 2, ..., M), and the difference between the two is used to obtain the peak-to-peak value Vpp _i of the feature array, and then all Compare the peak-to-peak value of the characteristic array to obtain its maximum peak-to-peak value Vpp _max ;

S15: Determine whether the maximum peak-to-peak Vpp _max is greater than S _v ×ε, and ε is the threshold constant, and its size can be adjusted according to the resolution of the ADC (analog-to-digital converter) and the instrument noise. If it is greater than it, go to step S2, otherwise the amplitude The gear is adjusted to the minimum amplitude gear whose range S _v is greater than Vpp _max , and returns to step S12 for re-sampling.

S2: According to the peak-to-peak criterion and the minimum integer period criterion, find a judgment array that can represent the signal amplitude and frequency characteristics. The peak-to-peak criterion refers to: for multiple feature arrays with different time intervals, the maximum peak-to-peak value Vpp _max can be considered to be the peak-to-peak value of the actual signal. If the peak-to-peak value of a feature array is not close to Vpp _max , it means that the The signature array must not capture the full period of the signal. The minimum integer period criterion refers to: for a characteristic array whose peak-to-peak value is close to the actual signal, when the minimum integer period number is 0, it means that the characteristic array may not contain one period of the signal, so it should be judged that the characteristic array is a time interval A slightly larger eigenarray; and when the minimum number of integer cycles is greater than 0, and the eigenarray with a slightly smaller time interval, either the peak-to-peak value is not close to the actual signal, or the minimum number of integer cycles is 0, it can be considered that the eigenarray can approximate Characterize the amplitude and frequency characteristics of a signal.

The specific process of this step is as follows:

S21: initialize i=1;

S22: Determine whether the peak-to-peak value Vpp _i of the characteristic array Array _i is less than α×Vpp _max (α is a constant), if it is smaller, it means that the characteristic array must fail to obtain the entire period of the signal, let i=i+1, Return to step S22 to continue to judge, otherwise the peak-to-peak value of the feature array is considered to be close to the amplitude of the actual signal, and continue;

S23: let j=i;

S24: Calculate the characteristic array Array _j according to the minimum integer period algorithm to obtain the minimum integer period Num and determine whether the minimum integer period Num is zero. If so, it means that the characteristic array may not obtain the entire period of the signal, let i=j+1, if i>M (indicating that Array _j is already the largest time interval), then the characteristic array Array _j is used as the judgment array, Enter step S3, otherwise return to step S22 to continue judgment; if the minimum integer cycle number Num is not zero, it means that the feature array contains both the amplitude characteristics of the signal and at least one integer cycle of the signal, then the feature array Array _j as the judgment array, go to step S3.

Among them, the minimum whole cycle algorithm is as follows:

First, the comparison threshold is judged as follows:

Vpp=MAX-MIN

V _h =V _off +Δ

V _L =V _off -Δ

Among them, MAX is the maximum value of the feature array; MIN is the minimum value of the feature array; V _off is the median value of the feature array; β is the threshold constant; Δ is the width of the comparison window; V _h is the high comparison threshold; _VL is the low Compare thresholds.

Then traverse the feature array once to find out the number of parts Num_h greater than the high comparison threshold V _h and the number of parts Num_L less than the low comparison threshold _VL in the array, and finally the minimum integer cycle number Num is the smaller of Num_h and Num_L The value of is minus 1, that is, Num=min(Num_L,Num_h)-1, and the specific algorithm flowchart is shown in Figure 2.

This algorithm can calculate the minimum number of integer cycles of the signal contained in the feature array, where the minimum indicates that the number of integer cycles measured may be less than the actual number of integer cycles contained, but at most 1, as shown in Figure 3, its Num_h The value is 4, and the Num_L value is 3, then the final calculated Num value is 2, and the number of integer cycles that actually contains the signal is 3.

S3: Determine the time base gear and the amplitude gear according to the judgment array Array _j

The amplitude range can be determined according to the maximum value MAX _j and the minimum value MIN _j of the judgment array Array _j . In some possible implementations, the minimum integer period Num of the judgment array and the number of points ( The Ce-Cs mentioned below is the number of data points contained in Num whole cycles) to calculate its frequency, and then determine the time base gear according to the frequency. The specific process is as follows:

其中，根据峰峰值Vpp_j确定幅度挡位，该幅度挡位的量程为S_v，使其满足0.4×S_v≤Vpp_j≤0.8×S_v即可，并把中值

作为该通道的直流偏置；S31: The peak-to-peak value Vpp _j and the median value of the judgment array Array _j have been calculated in the above steps

Among them, the amplitude gear is determined according to the peak-to-peak value Vpp _j , and the range of the amplitude gear is S _v , so that it satisfies 0.4×S _v ≤Vpp _j ≤0.8×S _v , and the median value is

as the DC bias for this channel;

S32: When calculating the minimum number of integer cycles for the characteristic array, at the same time judge whether the top of the signal or the bottom of the signal appears first. If it is the top, the array that first reaches the bottom is marked as C _s , and the last one that reaches the bottom is marked as C s . The lower array is marked as C _e ; otherwise, the lower array that reaches the top for the first time is marked as C _s , and the lower array that reaches the top last is marked as C _e . In the minimum whole cycle algorithm, the high and low comparison thresholds are designed to eliminate the influence of signal noise. The part from the high comparison threshold V _h to the highest point Max can be defined as the top of the signal, and the low comparison threshold _VL to the high comparison threshold V _h The part is the middle part, and the part from the lowest point Min to the low comparison threshold _VL is the bottom part. The concept of "reaching" mentioned here is not simply to judge whether the value of each point is greater than V _h or less than _VL , but to reach the first point of the part from other parts. As shown in Figure 3, the Cs point is the point that reaches the bottom of the signal for the first time, and the same bottom point after this point is not reached (for example, the corresponding point on the line of the lowest point Min), and Ce is the first point. Three times the point at which the bottom of the signal is reached, between these two points contains two full periods of the signal.

The frequency f of the signal can be calculated according to the C _s , C _e of the judgment array Array _j , the corresponding time interval DT _j and the minimum number of integer cycles Num, and then the time base gear is determined.

In a possible implementation, when determining the time base gear, it is also possible to simply judge the minimum integer cycle number Num of the array Array _j , the corresponding time interval DT _j and the array size K, according to the following formula: Calculate the frequency range of the signal, and then determine the time base gear.

In particular, when Num=0, it means that the number of cycles of the signal in the characteristic array of the maximum time interval is less than 2, then the range of the signal frequency f can be determined:

f _min ≤f<2f _min .

In particular, the method for rapidly measuring amplitude and frequency by software proposed in the present invention can not only be used in automatic setting of oscilloscope, but also can be applied to frequency calculation for signals with unknown frequency range or signals with wide frequency range. And the algorithm can set the accuracy of frequency calculation according to the requirements. After calculating its low-precision frequency as in step S32, it can select an appropriate time interval and an appropriate amount of sampling data to re-calculate the frequency according to the accuracy requirements. For example, if you want to ensure that the feature array of the calculated frequency should satisfy at least 1000 sampling points per cycle (that is, the accuracy requirement is 1/1000), and the signal frequency measured by the algorithm is 800Hz (the accuracy of the result frequency is low), then A feature array with a time interval of 1 μs and a sampling point of 5000 can be extracted to recalculate its frequency, which ensures the accuracy of frequency measurement and reduces the time consumption of the algorithm.

In addition, for multi-channel oscilloscopes, the present invention is still applicable, because the multi-channel data acquisition is carried out at the same time, and except for the sampling time, the calculation amount of the algorithm is very small, and the running time is extremely short, so the automatic setting is basically not increased. time.

For those of ordinary skill in the art, without departing from the inventive concept of the present invention, several modifications and improvements can also be made to the embodiments of the present invention, which all belong to the protection scope of the present invention.

Claims (5)

1. An oscilloscope automatic setting method based on a frequency rapid measurement algorithm is characterized by comprising the following steps:

s1: the automatic setting carries out preliminary adjustment to the range gear earlier when beginning, and specific process is as follows:

s11: at the beginning, the range S of the range gear is adjusted_vSet as the maximum measuring range；

S12: setting the time-base gear to minimum, according to the automatically set minimum recognition frequency f_minAnd the maximum sampling rate f corresponding to the minimum time base gear_maxAnd determining the number N of the sampling points for sampling:

s13: extracting M characteristic Array with different time intervals from sampling data₁To Array_MThe size of each feature array in the M feature arrays is K, the time interval DT corresponding to each feature array is sequentially increased by multiple A, and the time interval DT is 1/f from low to high_max、A/f_max、……、A^(M-1)/f_maxWherein, the number M of the feature array is calculated as follows:

wherein A, M, N, K satisfies the following equation:

A^(M-1)×K＝N；

s14: traversing each feature array in the M feature arrays once to obtain the maximum value MAX of the feature arrays_iAnd minimum MIN_iAnd i is 1,2, … and M, and the difference is made to obtain the peak-to-peak value Vpp of the characteristic array_i＝MAX_i-MIN_iAnd the two are added and averaged to obtain the median value of the characteristic array

Then comparing the peak value of all the characteristic arrays to obtain the maximum peak value Vpp_max；

S15: judging the maximum peak value Vpp_maxWhether or not greater than S_v×, is a threshold constant, if it is larger than the threshold constant, the step S2 is proceeded, otherwise the range S of the range is shifted_vAdjusted to be greater than Vpp_maxAnd returning to step S12 for resampling;

s2: according to the peak-to-peak value criterion and the minimum whole period criterion, finding a judgment array capable of representing the signal amplitude and frequency characteristics, which comprises the following specific processes:

s21: initializing i to 1;

s22: judging feature Array_iPeak to peak value Vpp of_iWhether less than α× Vpp_maxα is a constant, if the value is less than the value, i is made to be i +1, the step is returned to the step S22 to continue the judgment, otherwise, the step is entered into the step S23;

s23: let j equal i;

s24: calculating a feature Array according to a minimum whole period algorithm_jJudging whether the minimum integral cycle number Num is zero, if the minimum integral cycle number Num is zero, making i equal to j +1, if i is greater than M, then setting the characteristic Array_jStep S3 is entered as the judgment array, otherwise, the step S22 is returned to continue the judgment; if the minimum integral period number Num is not zero, then the characteristic Array is used_jAs a judgment array, continuing to step S3;

s3: according to the judgment Array_jMAX of (3)_jAnd minimum MIN_jDetermining an amplitude gear, calculating the frequency of the signal, and determining a time-base gear according to the frequency, wherein the specific process is as follows:

s31: calculating according to the algorithm of the step S14 to obtain a judgment Array_jPeak to peak value Vpp of_jAnd median value

Wherein, the peak-to-peak value Vpp is used as the basis_jDetermining the range of the range as S_vSo that it satisfies 0.4 × S_v≤Vpp_j≤0.8×S_vAnd the median value is calculated

As a dc bias for the respective channel;

s32: and calculating the frequency f of the signal to further determine the time base gear.

2. The method according to claim 1, wherein in step S24, the minimum whole period algorithm is specifically as follows:

first, a threshold comparison is determined as follows:

wherein β is a threshold constant, Δ_jIs the width of the comparison window;

array for feature Array_jA high comparison threshold of;

array for feature Array_jThe low comparison threshold of (a) is,

then the feature Array is aligned_jPerforming one-time traversal to find out the threshold value which is larger than the high comparison threshold value in the array

And is less than the low comparison threshold value

The resulting minimum number of integer cycles Num is the smaller of Num _ h and Num _ L minus 1.

3. The method of claim 2, wherein in step S24, when calculating the minimum number of integer cycles Num of the feature array, it is determined whether the top of the signal or the bottom of the signal appears first, and if the top is reached, the bottom is reached firstThe label is C_sThe array that reaches the bottom last is labeled C_e(ii) a Otherwise, the array which reaches the top for the first time is marked as C_sThe array that reaches the top last is labeled C_eThe top of the signal is greater than the high comparison threshold

The bottom of the signal means less than a low comparison threshold

The part (a) of (b) of (a),

in step S32, Array is determined_jC of (A)_s、C_eCorresponding time interval DT_jAnd the minimum integer number Num, calculating the frequency f of the signal:

4. the method according to claim 1, wherein step S32 is implemented as follows:

array based on judgment_jThe minimum number Num of integer cycles, the corresponding time interval DT_jAnd array size K, calculating the frequency range of the signal:

5. the method according to claim 3 or 4, wherein when the minimum number of integer periods Num is 0, the signal frequency f ranges as follows:

f_min≤f＜2f_min。

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