CN110780100B - Oscilloscope automatic setting method based on frequency rapid measurement algorithm - Google Patents
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Abstract
The invention discloses an oscilloscope automatic setting method based on a time domain software measurement amplitude and frequency rapid measurement algorithm, which comprises the following steps: extracting a plurality of characteristic arrays with different time intervals from data to be processed; judging the peak value and the minimum integral period number of the characteristic arrays to find the arrays which can represent the peak value and the frequency characteristics of the signal; and setting a horizontal time base gear and a vertical amplitude gear according to the array. The invention has the characteristics of low cost, high speed, wide application range and the like.
Description
Technical Field
The invention belongs to the field of electronic measuring instruments, and particularly relates to a rapid measuring algorithm for measuring amplitude and frequency by time domain software and a rapid automatic setting method for a digital oscilloscope based on the algorithm.
Background
The oscilloscope, which is the most commonly used measuring instrument in the field of electronic information, plays a great role in various universities, laboratories, companies and the like, but the horizontal time base and the vertical amplitude are required to be manually adjusted to ensure that the waveform display effect is good when the oscilloscope is used, and the automatic setting function can automatically set the horizontal time base and the vertical amplitude to meet the requirements of users.
The automatic setting function is actually to measure the amplitude and frequency of the signal to determine the horizontal time base and the vertical amplitude to be selected, and the rough method is to initialize an amplitude gear, then obtain the amplitude or frequency by a specific method, and if the amplitude gear is not suitable, the amplitude gear needs to be adjusted to measure again.
In the existing methods, the measurement of the signal amplitude can be divided into two categories, namely software and hardware. Wherein the hardware is generally implemented by a peak detection circuit; the software generally obtains the maximum and minimum values of the sampled data by traversing the sampled data once, and the maximum and minimum values are subtracted to obtain the amplitude of the signal. Frequency measurement for unknown signals can be roughly divided into two categories, hardware and software. The hardware mainly outputs square waves related to the frequency of an input signal through a comparison circuit after the input signal is shaped, and then the frequency of the square waves is measured by using a frequency measurement circuit, wherein the common method comprises the following steps: direct frequency measurement, multi-cycle frequency measurement, etc.; the software frequency measurement can be divided into a time domain frequency measurement and a frequency domain frequency measurement, the time domain frequency measurement generally performs two-time traversal on sampling data, the signal frequency is calculated by calculating the number of sampling points in each signal period, the frequency domain frequency measurement generally adopts the method that the sampling data is subjected to fast Fourier transform and is converted into a frequency domain, then the frequency of the maximum value of the frequency component except the direct current component in the signal is found out, and the signal frequency can be regarded as the signal frequency.
However, the above methods have problems in use. For example, the "automatic setting method of a digital oscilloscope" disclosed in chinese patent CN101609106A and the "automatic setting control method of a digital fluorescence oscilloscope" disclosed in chinese patent CN103809002A are both methods of measuring frequency and amplitude by using a hardware circuit and a software method, and adjusting the amplitude gear by bisection and then repeatedly measuring. In actual use, a frequency measurement circuit requires proper amplitude gear setting, large input signal amplitude and reasonable comparison level setting, time domain software requires reasonable time gear setting for amplitude measurement, data of at least one period is traversed, the higher the sampling rate is, the more time is spent, and meanwhile, due to mutual constraint of frequency measurement and amplitude measurement, repeated measurement is often required for automatic setting, so that a large amount of time is consumed, and the accuracy is lower.
The automatic setting method of the digital oscilloscope disclosed by the Chinese patent CN105510664A and the quick automatic setting method of the digital oscilloscope based on hardware concentration disclosed by the Chinese patent CN106597048A are modes of measuring frequency and amplitude by using a hardware circuit and detecting a hardware peak value. The frequency measurement still faces the above problem, and although the peak detection mode adopted by the method avoids the disadvantages of large computation amount and much time consumption of time domain software frequency measurement, the allowable signal frequency is low, and the method is difficult to apply to high-frequency signals.
The Chinese patent CN108037339A discloses a 'control method for automatic setting of a digital oscilloscope', which uses a software amplitude measurement and frequency measurement mode of frequency domain software. The software amplitude measurement and sampling are synchronously carried out, so that the defect of amplitude measurement in the patent is avoided, but the software amplitude measurement and sampling are not suitable for an oscilloscope with high sampling rate, and when the data acquisition speed is higher than the processing speed of an FPGA (field programmable gate array), the amplitude measurement and the sampling cannot be kept synchronous, so that the consumed time is increased. 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 also increases, and the time consumption also increases significantly. In addition, as the sampling data needs to be processed in parallel and subjected to fast Fourier transform, a hardware processor such as an FPGA (field programmable gate array) is required to be used, and as the sampling rate of the oscilloscope is increased, the resource is occupied more greatly, and the cost is higher.
In summary, most of the existing automatic oscilloscope setting methods have disadvantages in speed, accuracy, applicable frequency range, cost, and the like.
Disclosure of Invention
The invention provides an automatic oscilloscope setting method based on a time domain software amplitude and frequency measurement fast algorithm, aiming at solving the problems of how to achieve the automatic setting speed, wide applicable frequency range and low cost of an oscilloscope in the aspect of realizing the automatic setting function.
The invention provides an oscilloscope automatic setting method based on a time domain software amplitude and frequency measurement quick algorithm, which comprises 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 amplitude gear is shiftedvSetting the range as the maximum range;
s12: shifting time baseSet to minimum, according to the automatically set minimum recognition frequency fminAnd the maximum sampling rate f corresponding to the minimum time base gearmaxAnd determining the number N of the sampling points for sampling:
s13: extracting M characteristic Array with different time intervals from sampling data1To ArrayM；
S14, performing one-time traversal on each feature array in the M feature arrays to obtain the maximum value MAX of the feature arraysiAnd minimum MINiAnd i is 1,2, … and M, and the difference is made to obtain the peak-to-peak value Vpp of the characteristic arrayi＝MAXi-MINiAnd 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 Vppmax；
S15: judging the maximum peak value VppmaxWhether or not greater than Sv×, 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 shiftedvAdjusted to be greater than VppmaxAnd 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 ArrayiPeak to peak value Vpp ofiWhether less than α× Vppmaxα 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 algorithmjAnd judging whether the minimum integer period Num is zero or not, if so, determining whether the minimum integer period Num is zero or notIf the minimum number of integer cycles Num is zero, let i equal to j +1, if i>M, then the feature Array is usedjStep 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 usedjAs a judgment array, continuing to step S3;
s3: according to the judgment ArrayjMAX of (3)jAnd minimum MINjDetermining 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 ArrayjPeak to peak value Vpp ofjAnd median value
Wherein, the peak-to-peak value Vpp is used as the basisjDetermining the range of the range as SvSo that it satisfies 0.4 × Sv≤Vppj≤0.8×SvAnd 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.
Furthermore, 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 the multiple A, and the time interval DT is sequentially 1/f from low to highmax、A/fmax、……、A^(M-1)/fmaxWherein, the number M of the feature array is calculated as follows:
wherein A, M, N, K needs to satisfy the following equation:
A^(M-1)×K＝N。
further, 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, ΔjIs the width of the comparison window;
array for feature ArrayjA high comparison threshold of;
array for feature ArrayjThe low comparison threshold of (a) is,
then the feature Array is alignedjPerforming 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.
In one possible embodiment, in step S24, when the minimum number Num of whole cycles is calculated for the feature array, it is determined whether the top of the signal or the bottom of the signal appears first, and the array that reaches the bottom first is denoted by C when the top is reachedsThe array that reaches the bottom last is labeled Ce(ii) a Otherwise, the array which reaches the top for the first time is marked as CsThe array that reaches the top last is labeled Ce。
Further, according to the judgment ArrayjC of (A)s、CeCorresponding time interval DTjAnd the minimum integral period Num, the frequency f of the signal can be calculated, and the time base gear position can be further determined
In particular, when Num is 0, which indicates that the minimum number Num of integer periods of the signal in the feature array of the maximum time interval is less than 2, the range of the signal frequency f can be determined:
fmin≤f<2fmin。
in a possible implementation, the specific process of step S32 may be as follows:
array based on judgmentjThe minimum number Num of integer cycles, the corresponding time interval DTjAnd the group size K, calculating the frequency range of the signal according to the following formula, and further determining the time-base gear
In particular, if Num is equal to 0, which indicates that the number of periods of the signal in the characteristic array of the maximum time interval is less than 2, the range of the signal frequency f can be determined
fmin≤f<2fmin。
Therefore, the invention provides an algorithm for rapidly measuring amplitude and frequency on the basis of a method for realizing automatic setting, which obviously reduces the data amount to be processed by extracting a plurality of characteristic arrays with different time intervals from huge sampling data, determines the characteristic arrays capable of approximately representing the signal amplitude and frequency characteristics through a peak-to-peak value criterion and a minimum whole period criterion, and further sets a time-base gear and an amplitude gear. The algorithm changes the time complexity of the calculation of the amplitude and the frequency from O (n) to O (log (n)), and the running time is greatly reduced. In the adjustment of the amplitude gear, the gear adjustment is carried out only when the maximum peak value of the extracted array is judged to be smaller than the threshold value by adopting a coarse adjustment mode and comparing the maximum peak value with the threshold value, so that the frequency of amplitude adjustment in automatic setting is reduced, the frequency of resampling is also reduced, and the automatic setting is quicker.
The invention has the beneficial effects that:
1) the invention provides a data extraction method, which is characterized in that a plurality of equally spaced data are extracted from original data, so that the data quantity is reduced, and partial characteristics of signals are kept; the method for calculating the minimum whole period number is provided, and under the condition that the amplitude of the signal is close to the actual amplitude, the number of the whole periods at least containing the signal in the data can be calculated, for example, when the value of the number is 1, the data at least contains the signal of one whole period, but the whole period is not more than 2; a rapid algorithm for measuring signal amplitude and frequency by software based on multi-equal-interval data extraction is provided, a plurality of extracted equal-interval arrays are judged according to a peak-to-peak criterion and a minimum whole-period criterion, an array capable of representing signal amplitude and frequency information is found, and the amplitude and the frequency of a signal are further determined; the method for roughly adjusting the amplitude gear when the oscilloscope is automatically set is provided, so that a signal is ensured to have a certain amplitude, the frequency of adjusting the amplitude gear in the automatic setting process is reduced, and the time consumed by automatic setting is reduced.
2) In the implementation of automatic setting, because the measurement of the amplitude and the frequency adopts a software algorithm, no additional hardware circuit is needed, no special requirement is required for a processing unit, and even a program can be embedded into a main controller of the oscilloscope, thereby approximately reaching zero cost.
3) The algorithm of the invention needs small processing operand, so the speed is very fast, and even under the condition of increasing the sampling rate, the algorithm operand is increased very little, so the algorithm is applicable to oscilloscopes with high sampling rates and has larger advantages.
Drawings
FIG. 1 is a flow chart of an oscilloscope automatic setting method based on a frequency fast algorithm according to the present invention;
FIG. 2 is a flow chart of a minimum whole cycle algorithm of the present invention;
FIG. 3 is a graph showing the results of the minimum integer number algorithm according to an embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings and examples, it being understood that the examples described below are intended to facilitate the understanding of the invention, and are not intended to limit it in any way.
The invention adopts a software amplitude measuring mode and a time domain software frequency measuring mode on the automatic setting method of the oscilloscope, and is different from the traditional software frequency measuring mode and amplitude measuring mode in that a plurality of characteristic arrays with different time intervals (wherein the time interval of each array is fixed, and the time intervals of different characteristic arrays are different) are extracted from data to be processed; judging the peak value and the minimum integral period number of the characteristic arrays to find the arrays which can represent the peak value and the frequency characteristics of the signal; and setting a horizontal time base gear and a vertical amplitude gear according to the array. Specifically, the oscilloscope automatic setting method based on the time domain software amplitude and frequency rapid measurement algorithm of the invention, as shown in fig. 1, comprises the following steps:
s1: preliminary adjustment of amplitude gear
When the automatic setting of the oscilloscope is started, the amplitude gear is initially (roughly) adjusted, so that the amplitude of the measured signal meets the requirement, and then the amplitude and the frequency are measured. The specific process is as follows:
s11, at the beginning, the range S of the amplitude gear is shiftedvSetting the range as the maximum range;
s12: setting the time-base gear to minimum, according to the automatically set minimum recognition frequency fminAnd the maximum sampling rate f corresponding to the minimum time base gear of the oscilloscopemaxAnd determining the number N of the sampling points for sampling:
s13: extracting M characteristic Array with different time intervals from sampling data1To ArrayMWherein, the size of each array is K, K can be set according to the requirement of the oscilloscope, and the corresponding time interval DT is sequentially increased by multiple AIncreasing 1/f from low to highmax、A/fmax、……、A^(M-1)/fmaxWhere M is calculated as follows:
wherein A, M, N, K needs to satisfy the following equation:
A^(M-1)×K＝N。
s14, traversing each feature array once to obtain the maximum value MAXiAnd minimum MINi(i is 1,2, …, M), and the two are subtracted to obtain the peak-to-peak value Vpp of the feature arrayiThen comparing the peak value of all the characteristic arrays to obtain the maximum peak value Vppmax；
S15: judging the maximum peak value VppmaxWhether or not greater than Sv×, a threshold constant whose size can be adjusted according to the resolution of ADC (analog-to-digital converter) and instrument noise, if it is larger than the threshold constant, the step S2 is proceeded, otherwise, the amplitude shift is adjusted to its measuring range SvGreater than VppmaxAnd returns to step S12 for resampling.
S2: and finding a judgment array capable of representing the signal amplitude and frequency characteristics according to the peak-to-peak value criterion and the minimum whole period criterion. The peak-to-peak criterion is that: for a plurality of feature arrays with different time intervals, the maximum peak value Vpp can be consideredmaxIs the peak-to-peak value of the actual signal, if the peak-to-peak value of a certain feature array is not close to VppmaxIt means that the signature array must not capture the entire period of the signal. The minimum whole period criterion is that: for the feature array with the peak-to-peak value close to the actual signal, when the minimum integral cycle number is 0, the feature array may not contain one cycle of the signal, and therefore the feature array is judged to be the feature array with a slightly larger time interval; and when the minimum integer cycle number is larger than 0 and the characteristic array with smaller time interval is not close to the actual signal, or the minimum integer cycle number is 0, the characteristic array can be considered to be capable of approximately representing the amplitude and frequency characteristics of the signal.
The specific process of the step is as follows:
s21: initializing i to 1;
s22: judging feature ArrayiPeak to peak value Vpp ofiWhether less than α× Vppmax(α is a constant), if the value is less than the value, the characteristic array is determined to be unable to acquire the whole period of the signal, let i equal to i +1, return to step S22 to continue the determination, otherwise, the peak-to-peak value of the characteristic array is considered to be close to the amplitude of the actual signal, and continue;
s23: let j equal i;
s24: according to the minimum whole period algorithm, the feature Array is subjected tojAnd calculating to obtain the minimum integer period Num and judging whether the minimum integer period Num is zero or not. If yes, the characteristic array may not acquire the whole period of the signal, let i be j +1, if i is>M (Explanation Array)jHas been the largest time interval), the feature Array is assignedjStep 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, the characteristic Array not only contains the amplitude characteristic of the signal, but also at least contains one integral period of the signal, and the characteristic Array is arrangedjAs the judgment array, the process proceeds to step S3.
The minimum whole period algorithm is as follows:
first, a threshold comparison is determined as follows:
Vpp＝MAX-MIN
Vh＝Voff+Δ
VL＝Voff-Δ
wherein MAX is the maximum value of the feature array; MIN is the minimum value of the feature array; voffIs the median of the feature array, β is the threshold constant, ΔIs the width of the comparison window; vhA high comparison threshold; vLIs a low comparison threshold.
Then, traversing the feature array once to find out the value greater than the high comparison threshold value V in the arrayhAnd is less than the low comparison threshold VLThe minimum integer number Num is the smaller value of Num _ h and Num _ L minus 1, that is, Num ═ min (Num _ L, Num _ h) -1, and the specific algorithm flowchart is shown in fig. 2.
The algorithm can calculate the minimum number of whole cycles of the signature array containing the signal, where the minimum represents that the number of whole cycles measured may be less than the number of whole cycles actually contained, but is at most 1, as shown in fig. 3, where Num _ h is 4 and Num _ L is 3, then the last calculated Num is 2 and the number of whole cycles actually contained is 3.
S3: according to the judgment ArrayjDetermination of time-based and amplitude gears
According to the judgment ArrayjMAX of (3)jAnd minimum MINjIn some possible embodiments, the frequency of the amplitude gear may be calculated according to the minimum number Num of the whole cycles of the judgment array and the number of points included in the whole cycles (hereinafter, Ce-Cs is the number of data points included in Num whole cycles), and then the time-based gear is determined according to the frequency. The specific process is as follows:
s31: the judgment Array has been calculated in the above stepsjPeak to peak value Vpp ofjAnd median value
Wherein, the peak-to-peak value Vpp is used as the basisjDetermining an amplitude gear with a range of SvSo that it satisfies 0.4 × Sv≤Vppj≤0.8×SvThat is, the median value is measured
As a dc bias for the channel;
s32: in the process of performing minimum rounding on the feature arrayWhen the number of cycles is calculated, whether the top of the signal or the bottom of the signal appears first is judged, and when the top of the signal appears, the array which reaches the bottom for the first time is marked as CsThe array that reaches the bottom last is labeled Ce(ii) a Otherwise, the array which reaches the top for the first time is marked as CsThe array that reaches the top last is labeled Ce. In the minimum whole period algorithm, the high and low comparison thresholds are designed to eliminate the influence of signal noise, and may be defined as the high comparison threshold VhThe portion of Max at the highest point is the top of the signal, the low comparison threshold VLHigh comparison threshold VhThe part (c) is a middle part, the lowest point Min is a low comparison threshold VLThe part of (a) is the bottom. The concept of "arrival" as referred to herein is not a simple determination of whether the value of each point is greater than VhOr less than VLBut reaches the first point of the section from the other section. As shown in fig. 3, the Cs point is the point that reaches the bottom of the signal for the first time, and none of the points at the same bottom after this point reaches (e.g., the corresponding point on the Min line at the lowest point), and Ce is the point that reaches the bottom of the signal for the third time, and the two points contain two whole periods of the signal therebetween.
According to the judgment ArrayjC of (A)s、CeCorresponding time interval DTjAnd the frequency f of the signal can be calculated by the minimum integral period Num, so as to determine the time-base gear
In a possible embodiment, the determination of the time base gear can also be easily determined by determining the ArrayjAnd a corresponding time interval DTjAnd the size K of the array, simply calculating the frequency range of the signal according to the following formula, and further determining the time-base gear.
In particular, when Num is 0, which indicates that the number of cycles of the signal in the signature array of the maximum time interval is less than 2, the range of the signal frequency f can be determined:
fmin≤f<2fmin。
particularly, the method for rapidly measuring the amplitude and the frequency by software provided by the invention not only can be used for automatic setting of an oscilloscope, but also can be suitable for frequency calculation of signals with unknown frequency range or signals with wide frequency range. And the algorithm can set the precision of frequency calculation according to requirements, and after calculating the low-precision frequency as in step S32, the algorithm can select a proper time interval and a proper amount of sampling data to perform frequency calculation again according to the precision requirement. For example, if it is required to ensure that the feature array of the calculated frequency should satisfy at least 1000 sampling points (i.e., accuracy requirement 1/1000) in a cycle, and the signal frequency measured by the algorithm is 800Hz (the accuracy of the result frequency is low), the feature array with the time interval of 1 μ s and the sampling points of 5000 may be extracted to recalculate the frequency, thereby achieving the purpose of reducing the time consumption of the algorithm while ensuring the accuracy of the frequency measurement.
In addition, for a multi-channel oscilloscope, the method is still applicable because the data acquisition of multiple channels is carried out simultaneously, and except for the sampling time, the calculation amount of the algorithm is small, the running time is extremely short, and therefore, the automatic setting time is not increased basically.
It will be apparent to those skilled in the art that various modifications and improvements can be made to the embodiments of the present invention without departing from the inventive concept thereof, and these modifications and improvements are intended to be within the scope of the 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 adjustedvSet as the maximum measuring range；
S12: setting the time-base gear to minimum, according to the automatically set minimum recognition frequency fminAnd the maximum sampling rate f corresponding to the minimum time base gearmaxAnd determining the number N of the sampling points for sampling:
s13: extracting M characteristic Array with different time intervals from sampling data1To ArrayMThe 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 highmax、A/fmax、……、A^(M-1)/fmaxWherein, 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 arraysiAnd minimum MINiAnd i is 1,2, … and M, and the difference is made to obtain the peak-to-peak value Vpp of the characteristic arrayi＝MAXi-MINiAnd 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 Vppmax；
S15: judging the maximum peak value VppmaxWhether or not greater than Sv×, 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 shiftedvAdjusted to be greater than VppmaxAnd 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 ArrayiPeak to peak value Vpp ofiWhether less than α× Vppmaxα 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 algorithmjJudging 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 ArrayjStep 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 usedjAs a judgment array, continuing to step S3;
s3: according to the judgment ArrayjMAX of (3)jAnd minimum MINjDetermining 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 ArrayjPeak to peak value Vpp ofjAnd median value
Wherein, the peak-to-peak value Vpp is used as the basisjDetermining the range of the range as SvSo that it satisfies 0.4 × Sv≤Vppj≤0.8×SvAnd 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, ΔjIs the width of the comparison window;
array for feature ArrayjA high comparison threshold of;
array for feature ArrayjThe low comparison threshold of (a) is,
then the feature Array is alignedjPerforming 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 CsThe array that reaches the bottom last is labeled Ce(ii) a Otherwise, the array which reaches the top for the first time is marked as CsThe array that reaches the top last is labeled CeThe 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 determinedjC of (A)s、CeCorresponding time interval DTjAnd 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 judgmentjThe minimum number Num of integer cycles, the corresponding time interval DTjAnd 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:
fmin≤f＜2fmin。
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