CN107729980B - Waveform signal self-adaptive counting method - Google Patents
Waveform signal self-adaptive counting method Download PDFInfo
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- CN107729980B CN107729980B CN201710976861.7A CN201710976861A CN107729980B CN 107729980 B CN107729980 B CN 107729980B CN 201710976861 A CN201710976861 A CN 201710976861A CN 107729980 B CN107729980 B CN 107729980B
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- G06M1/27—Design features of general application for representing the result of count in the form of electric signals, e.g. by sensing markings on the counter drum
- G06M1/272—Design features of general application for representing the result of count in the form of electric signals, e.g. by sensing markings on the counter drum using photoelectric means
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Abstract
The invention discloses a waveform signal self-adaptive counting method, which comprises the following steps: carrying out frequency division processing on the waveform input signal to obtain a high level or a low level of a new signal, wherein the high level or the low level of the new signal is the whole period of the original signal; counting the high level after frequency division by using a clock signal; calculating a difference value of the counts; judging the absolute value of the difference value and the threshold lambda of the difference value; outputting normal data, and outputting a normal value after performing addition operation on abnormal data; finally, the total count is obtained. According to the invention, the waveform input signal is subjected to frequency division treatment, the high level subjected to frequency division is counted by using the clock signal, the counts are grouped, whether the counts belong to normal data is judged according to the groups, and finally, the desired data is output, so that the waveform signal self-adaptive counting result is obtained, and the signal period calculation accuracy is effectively improved.
Description
Technical Field
The invention relates to the technical field of special signal testing and detection, in particular to a waveform signal self-adaptive counting method.
Background
The digital electronic counter has important application value in the fields of geological exploration, general tests and other special requirements.
The Chinese intellectual property office website discloses a digital electronic counter (application number: 201110107653.6), which comprises a CPU, a display module, a signal acquisition module, an alarm module, a real-time clock data storage module, a keyboard and a power module, wherein the CPU is respectively connected with the display module, the signal acquisition module, the real-time clock data storage module and the keyboard, the display module is connected with the alarm module, and the power module is respectively connected with the CPU, the display module, the signal acquisition module, the alarm module, the real-time clock data storage module and the keyboard. Compared with the prior art, the invention has the advantages of higher responsivity, dual purposes of alternating current and direct current, low energy consumption, low price, no mechanical collision, no abrasion, long service life and the like. However, the digital counter cannot count correctly for slow rising edges of low-frequency signals, and erroneous judgment is easily caused when the level of the rising edge of the input counted and detected signal is between the high level and the low level of the digital counter, so that high-frequency counting is performed for many times. For example, the 3.3V interface of FPGA can easily determine the rising period of the detected rising edge between 0.8V and 2V as a waveform for many times, and the rising or falling is only one edge of the detected counting signal.
Since the rising edge and the falling edge of the low frequency signal are both slow, when the signal rises or falls to the middle level of the high level or the low level of the signal detection digital processor, the level at this time is determined to be 1 or 0, and the counting error is caused.
In the prior art, a large amount of hardware detection systems are mainly needed for detecting the rising edge and the falling edge of a waveform, otherwise, the waveform frequency detection counting error can be caused. However, the introduction of these hardware will bring about a large increase in power consumption, cost, and design space, and also easily cause a lifetime problem due to level mismatch.
Therefore, it is of great significance to develop a method for counting the signal frequency with simple process, convenient operation and suitable for the transition level between the high level and the low level of the digital device.
Disclosure of Invention
The invention provides a waveform signal self-adaptive counting method, which is a method for counting signal frequency aiming at error information generated by multiple counting caused by transition level between high level and low level of a digital device, and is particularly suitable for conditions of low power consumption, small volume, high signal quality, low frequency, sine wave input and the like, and the specific technical scheme is as follows:
a waveform signal adaptive counting method is characterized in that: the method comprises the following steps:
step one, performing frequency division processing on a waveform input signal to obtain a high level or a low level of a new signal, wherein the high level or the low level of the new signal is the whole period of an original signal;
step two, utilizing the clock signal to count the high level after frequency division, and dividing the count into N groups in sequence, wherein each group comprises m counting results, wherein: n is a natural number more than or equal to 1, and m is 8-15;
step three, sequentially calculating the difference value of two adjacent counts in the ith group as delta Tj, wherein i is a natural number which is greater than or equal to 1 and less than or equal to N, and j is a natural number which is greater than or equal to 1 and less than or equal to m-1;
step four, judging the size of the | delta Tj | and the difference threshold lambda, if the | delta Tj | is less than or equal to the difference threshold lambda, directly outputting the counting results in the ith group in sequence, and otherwise, entering the next step;
step five, if the absolute value delta Tj is larger than the difference threshold lambda, judging the data to be normal data, and directly and sequentially outputting the normal data in the ith group; if the value of delta Tj is less than or equal to the difference threshold lambda, judging that the data are abnormal data, and entering the next step;
step six, outputting a normal value after performing addition operation on the abnormal data, and entering the next step;
step seven, taking i as i + 1; if i is less than or equal to N, returning to the third step; and if i is larger than N, ending.
Preferably, in the above technical solution, the adding operation of the abnormal data in the sixth step specifically includes:
step 6.1, adding the first e counting results in the abnormal data to obtain a sum value QeThen adding the sum QeCalculating the difference P from the most recent normal datae(ii) a Wherein: e is the number of the total abnormal data which is more than or equal to 2 and less than or equal to the total abnormal data;
step 6.2, dividing the difference value PeIs compared with a difference threshold lambda if PeIf | is greater than the difference threshold λ, the sum Q is addedeJudging the data to be normal values, judging normal data and abnormal data again, and returning to the step 6.1; otherwise, entering the next step;
step 6.3, taking e as e +1, judging the sizes of e +1 and m, and if e +1 is larger than m, finishing addition operation; otherwise, the step 6.1 is returned.
Preferably, in the above technical solution, the difference threshold λ is 90-95% of the maximum period count data of the signal to be measured.
Preferably, in the above technical solution, the frequency division processing in the step one is a frequency division by two processing.
By applying the technical scheme of the invention, the effects are as follows:
1. the invention can adopt the original hardware, does not need to increase other hardware detection systems, not only can not increase the power consumption, the cost and the design space, but also can ensure the level matching and prolong the service life.
2. The invention adopts a voltage conditioning module formed by waveform signals through operational amplifiers to input the waveform signals into an FPGA or CPLD chip for counting, and specifically comprises the following steps: the waveform input signal is subjected to frequency division processing, the high level subjected to frequency division is counted by using a clock signal, the counts are grouped, whether the counts belong to normal data or not is judged according to the groups, and finally, desired data is output, so that a waveform signal self-adaptive counting result is obtained, and the signal period calculation accuracy is effectively improved.
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Fig. 1 is a schematic diagram of a hardware structure of a waveform signal adaptive counting method according to embodiment 1 of the present invention;
FIG. 2 is a waveform signal diagram according to embodiment 1 of the present invention;
fig. 3 is a flowchart of a waveform signal adaptive counting method according to embodiment 1 of the present invention.
Detailed Description
The embodiments of the present invention will be described in detail with reference to the accompanying drawings so that the advantages and features of the invention can be more easily understood by those skilled in the art, and the scope of the invention will be clearly and clearly defined.
Example 1:
a waveform signal adaptive counting method, hardware is shown in fig. 1, and specifically includes: the waveform signal is input into an FPGA (field programmable gate array) or CPLD (complex programmable logic device) chip for counting through a voltage conditioning module formed by an operational amplifier.
The waveform signals are shown in fig. 2: if the rising edge of the waveform is slow and the frequency is low, a high-frequency counting clock for counting high frequency counts to count error waveform counting data generated by undetermined voltage (a region from v1 to v 2) in the middle of the high and low levels of the IO interface; correct count data for a low frequency input signal can be obtained if a low frequency clock frequency count is used, but since the period of the clock signal is longer than the clock period for a high frequency, data will not be available for a high frequency signal.
The present embodiment is analyzed in the following manner, specifically including the following steps, as shown in fig. 3:
step one, performing frequency division on a waveform input signal to obtain a high level or a low level of a new signal, wherein the high level or the low level of the new signal is the whole period of an original signal;
step two, utilizing the clock signal to count the high level after frequency division, and dividing the count into N groups in sequence, wherein each group comprises m counting results, wherein: n is a natural number more than or equal to 1, and m is 8-15;
step three, sequentially calculating the difference value of two adjacent counts in the ith group as delta Tj, wherein i is a natural number which is greater than or equal to 1 and less than or equal to N, and j is a natural number which is greater than or equal to 1 and less than or equal to m-1;
step four, judging the size of the | delta Tj | and the difference threshold lambda, if the | delta Tj | is less than or equal to the difference threshold lambda, directly outputting the counting results in the ith group in sequence, and otherwise, entering the next step;
step five, if the absolute value delta Tj is larger than the difference threshold lambda, judging the data to be normal data, and directly and sequentially outputting the normal data in the ith group; if the value of delta Tj is less than or equal to the difference threshold lambda, judging that the data are abnormal data, and entering the next step;
step six, outputting a normal value after performing addition operation on the abnormal data, and entering the next step; the addition operation in this step specifically includes the following steps:
step 6.1, adding the first e counting results in the abnormal data to obtain a sum value QeThen adding the sum QeCalculating the difference P from the most recent normal datae(ii) a Wherein: e is the number of the total abnormal data which is more than or equal to 2 and less than or equal to the total abnormal data;
step 6.2, dividing the difference value PeIs compared with a difference threshold lambda if|PeIf | is greater than the difference threshold λ, the sum Q is addedeJudging the data to be normal values, judging normal data and abnormal data again, and returning to the step 6.1; otherwise, entering the next step;
step 6.3, taking e as e +1, judging the sizes of e +1 and m, and if e +1 is larger than m, finishing addition operation; otherwise, returning to the step 6.1;
step seven, taking i as i + 1; if i is less than or equal to N, returning to the third step; and if i is larger than N, ending.
By adopting the technical scheme of the embodiment, hardware does not need to be added with a new system, and a software system can be upgraded; the invention adopts a voltage conditioning module formed by waveform signals through operational amplifiers to input the waveform signals into an FPGA or CPLD chip for counting, and specifically comprises the following steps: the waveform input signal is subjected to frequency division processing, the high level subjected to frequency division is counted by using a clock signal, the counts are grouped, whether the counts belong to normal data or not is judged according to the groups, and finally, desired data is output, so that a waveform signal self-adaptive counting result is obtained, and the signal period calculation accuracy is effectively improved.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes performed by the present specification and drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (4)
1. A waveform signal adaptive counting method is characterized in that: the method comprises the following steps:
step one, performing frequency division processing on a waveform input signal to obtain a high level or a low level of a new signal, wherein the high level or the low level of the new signal is the whole period of an original signal;
step two, utilizing the clock signal to count the high level after frequency division, and dividing the count into N groups in sequence, wherein each group comprises m counting results, wherein: n is a natural number more than or equal to 1, and m is 8-15;
step three, sequentially calculating the difference value of two adjacent counts in the ith group as delta Tj, wherein i is a natural number which is greater than or equal to 1 and less than or equal to N, and j is a natural number which is greater than or equal to 1 and less than or equal to m-1;
step four, judging the size of the | delta Tj | and the difference threshold lambda, if the | delta Tj | is less than or equal to the difference threshold lambda, directly outputting the counting results in the ith group in sequence, and otherwise, entering the next step;
step five, if the absolute value delta Tj is larger than the difference threshold lambda, judging the data to be normal data, and directly and sequentially outputting the normal data in the ith group; if the value of delta Tj is less than or equal to the difference threshold lambda, judging that the data are abnormal data, and entering the next step;
step six, outputting a normal value after performing addition operation on the abnormal data, and entering the next step;
step seven, taking i as i + 1; if i is less than or equal to N, returning to the third step; and if i is larger than N, ending.
2. The adaptive waveform signal counting method according to claim 1, wherein the adding of the abnormal data in the sixth step is specifically:
step 6.1, adding the first e counting results in the abnormal data to obtain a sum value QeThen adding the sum QeCalculating the difference P from the most recent normal datae(ii) a Wherein: e is the number of the total abnormal data which is more than or equal to 2 and less than or equal to the total abnormal data;
step 6.2, dividing the difference value PeIs compared with a difference threshold lambda if PeIf | is greater than the difference threshold λ, the sum Q is addedeJudging the data to be normal values, judging normal data and abnormal data again, and returning to the step 6.1; otherwise, entering the next step;
step 6.3, taking e as e +1, judging the sizes of e +1 and m, and if e +1 is larger than m, finishing addition operation; otherwise, the step 6.1 is returned.
3. The adaptive waveform signal counting method according to any one of claims 1 to 2, wherein the difference threshold λ is 90 to 95% of the maximum cycle count data of the signal to be measured.
4. The waveform signal adaptive counting method according to claim 1, wherein the frequency division processing in the first step is a frequency division by two processing.
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