Digital oscilloscope adaptive time width trigger and time width anomaly detection method

Abstract

The application discloses a digital oscilloscope adaptive time width trigger and time width anomaly detection method, after ADC collects signals, sample data is uploaded to an upper computer, an adaptive algorithm and a time width anomaly detection adaptive algorithm are obtained by using a time width trigger setting in the upper computer, a time width trigger module is designed in FPGA, trigger conditions are sent to the time width trigger module in FPGA, real-time detection and storage of signals meeting the conditions are completed, and finally signals meeting the set time width trigger conditions and time width anomaly signals are displayed on the upper computer.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of digital oscilloscopes, and more particularly relates to a digital oscilloscope adaptive time width trigger and time width anomaly detection method. BACKGROUND

[0002] With the increasing complexity of electrical signals and the rapid development of 5G and 6G technologies, the requirements for observing high-speed electrical signals and acquisition systems are becoming higher and higher, and acquisition systems are becoming more and more complex. As one of the most important components of acquisition systems, the trigger function is also playing an increasingly complex and important role. Using the trigger can stabilize the waveform display and capture waveforms with certain characteristics.

[0003] In the past, the trigger relied on basic edge triggering to achieve waveform capture, but today the signals being measured are not single characteristics, and relying on detecting the level change trend of the measured signal cannot meet the needs of some test scenarios, so edge triggering cannot capture complex signals. Therefore, the acquisition system has added many advanced trigger functions. Time width trigger is a trigger type that is used more frequently in advanced triggers of acquisition systems. Time width trigger refers to triggering the acquisition system on a specified positive or negative time width. Time width trigger is generally used to synchronize circuit behavior and capture abnormal phenomena in signals.

[0004] If you need to analyze pulse width modulation (PWM) signals, time width trigger can help users accurately capture and analyze the width changes of pulses, which is very useful in motor control, power management and other applications. At the same time, time width trigger allows users to capture transient events of a specific pulse width, for example, in communication, users may need to capture a pulse of a specific width to check the quality of data transmission.

[0005] When using time width trigger, users need to set the time width trigger conditions according to the measured signal and the signal characteristics that users are interested in. First, you need to set the appropriate trigger level, which is the standard for judging positive and negative time width, and also need to set the polarity of the time width, the width of the time width and the logic comparison condition. However, for users who are not familiar with the use of the trigger function of the acquisition system, they cannot set appropriate conditions to capture the waveform. In the past, the automatic setting function of the acquisition system was used to configure the trigger function of the acquisition system, but the automatic setting function can only set the trigger conditions of the edge trigger. When users want to observe complex signals and need time width trigger, it is still difficult for users to set the trigger conditions of the time width trigger reasonably.

[0006] The traditional acquisition system has poor abnormal signal capturing ability for unknown signal form, and cannot capture unknown time width abnormality. Therefore, a high-speed acquisition system capable of automatically extracting signal time width features is needed, and the time width abnormality detection condition is set adaptively by analyzing the distribution characteristics of the signal time width, so as to capture the unknown signal form time width abnormality signal.

[0007] The time width features of the signal are extracted in real time, the optimal signal time width value is selected, the trigger condition of the time width detection is set through the time width value, and when the signal meets the time width trigger condition, the signal meeting the characteristics is stably captured and displayed. The time width distribution characteristics of the signal are extracted, the nominal range of the signal time width is selected, the condition of the time width detection is set according to the range, so that the abnormal time width signal not meeting the condition is captured and displayed at the same time. SUMMARY

[0008] The purpose of the present application is to overcome the shortcomings of the prior art, and provide a digital oscilloscope adaptive time width trigger and time width abnormality detection method, which can automatically and quickly capture signals meeting the set time width trigger condition and time width abnormality signals.

[0009] In order to achieve the above-mentioned purpose of the application, the digital oscilloscope adaptive time width trigger and time width abnormality detection method comprises the following steps:

[0010] (1) power on the digital oscilloscope and access the measured signal;

[0011] (2) the acquisition system of the digital oscilloscope acquires sampling data of sufficient time length, and then uploads to the upper computer;

[0012] (3) set the maximum value threshold and the minimum value threshold; traverse each sampling point, and the first sampling point is the maximum value by default, then compare every adjacent 3 sampling points, if the value of the middle sampling point is the maximum, the middle sampling point is determined as the maximum value, if the value of the middle sampling point is the minimum, the middle sampling point is determined as the minimum value; for the last sampling point, compare it with the previous sampling point, if the last sampling point is larger than the previous sampling point, the last sampling point is determined as the maximum value, otherwise, the last sampling point is determined as the minimum value, finally, the maximum value sampling point is stored in the maximum value group, and the minimum value sampling point is stored in the minimum value group;

[0013] (4) extract the sampling data of a complete period according to the distribution characteristics of the maximum value and the minimum value;

[0014] (5) repeat the operations of steps (2)-(4) for multiple times to obtain multiple groups of sampling data of a complete period, then take the mean value of the multiple groups of sampling data and filter to obtain standard sampling data of a complete period;

[0015] (6) the time width characteristic distribution of the statistical standard sampling data under different trigger levels is counted;

[0016] (7) the adaptive time width trigger condition is set according to the time width characteristic distribution;

[0017] the time width width value with the least occurrence frequency is found, if the time width width value with the least occurrence frequency is only one, the time width width value is set as the time width trigger condition, if the time width width value with the least occurrence frequency is multiple, the sum of distances of each time width width value and other time width width values is calculated in turn, then the time width width value with the largest sum of distances is selected as the time width trigger condition, finally the trigger release and suppression time is set as any integer multiple of the signal period, so that the time width signal can be triggered;

[0018] (8) the adaptive abnormal time width trigger condition is set according to the time width characteristic distribution;

[0019] (8.1) the average value and the standard deviation of all time width width values are calculated;

[0020] (8.2) the time width width values outside the two times of the average value and the standard deviation are selected, then each time width width value is regarded as an abnormal time width;

[0021] (8.3) the time width polarity corresponding to each abnormal time width is determined;

[0022] (8.4) each abnormal time width and the corresponding time width polarity are regarded as the abnormal time width trigger condition

[0023] (9) the measured signal is detected and displayed;

[0024] the time width trigger condition and the abnormal time width trigger condition are sent to the time width trigger module in the FPGA, the time width trigger module judges the measured signal according to the sent condition, the time width signal meeting the time width trigger condition and the abnormal signal meeting the abnormal time width trigger condition are triggered respectively, then the acquisition system is controlled to store and finally display the signal.

[0025] The application aims to achieve the following:

[0026] The adaptive time width trigger and time width abnormality detection method of the digital oscilloscope in the application uploads the sampling data to the host computer after the ADC acquires the signal, sets the adaptive algorithm and the adaptive algorithm of the time width abnormality detection in the host computer to obtain the appropriate time width trigger condition, designs the time width trigger module in the FPGA, sends the trigger condition to the time width trigger module in the FPGA, completes the real-time detection and storage of the signals meeting the condition, and finally displays the signals meeting the set time width trigger condition and the time width abnormal signals in the host computer.

[0027] Meanwhile, the digital oscilloscope adaptive time width trigger and time width anomaly detection method also has the following

[0028] Beneficial effects:

[0029] (1), the present application can help users to automatically set the time width trigger condition, complete the capture of time width signal, without the user familiar with the acquisition system of advanced trigger setting method;

[0030] (2), the present application can capture unknown shape of time width anomaly signal, without the user to know the specific shape of the time width anomaly signal;

[0031] (3), for the occasional glitch anomaly signal in the periodic signal, the present application can be automatically identified, can be applied to the occasional glitch anomaly detection of periodic signal, help to solve the user can't know the shape of the anomaly signal and can't set the trigger condition of the trouble. BRIEF DESCRIPTION OF DRAWINGS

[0032] Figure 1 is the flow chart of the digital oscilloscope adaptive time width trigger and time width anomaly detection method of the present application;

[0033] Figure 2 is a signal example diagram; DETAILED DESCRIPTION

[0034] The specific embodiments of the present application will be described below in conjunction with the accompanying drawings, so that those skilled in the art can better understand the present application. It should be particularly noted that in the following description, when the detailed description of known functions and designs may dilute the main content of the present application, these descriptions will be omitted here.

[0035] EMBODIMENT

[0036] In this embodiment, as shown in the figure, the digital oscilloscope adaptive time width trigger and time width anomaly detection method of the present application comprises the following steps: Figure 1

[0037] (1), the digital oscilloscope is powered on, and the measured signal is connected;

[0038] (2), the acquisition system of the digital oscilloscope acquires enough time length of sampling data, and then uploads to the host computer;

[0039] ​(3), set the maximum threshold and minimum threshold; traverse each sampling point, the first sampling point is the maximum value by default, then compare every adjacent 3 sampling points, if the middle sampling point is the maximum value, then determine the middle sampling point as the maximum value, if the middle sampling point is the minimum value, then determine the middle sampling point as the minimum value; for the last sampling point, directly compare with the previous sampling point, if the last sampling point is greater than the previous sampling point, then determine the last sampling point as the maximum value, otherwise determine as the minimum value, finally store the maximum sampling point into the maximum value group, and store the minimum sampling point into the minimum value group;

[0040] For example: the adjacent 3 sampling points 4, 5, 6, if the sampling point 5 is the maximum value, then put the sampling point 5 into the maximum value group, if the sampling point 5 is the minimum value, then put the sampling point 5 into the minimum value group, otherwise discard and not put into any group;

[0041] (4), according to the distribution characteristics of the maximum value and the minimum value, extract the sampling data of a complete period;

[0042] (5), repeat the operation 5 times according to steps (2)-(4), obtain multiple groups of complete period sampling data, then take the average of the multiple groups of sampling data and filter to obtain a complete period of standard sampling data;

[0043] (6), statistics the time width characteristic distribution of the standard sampling data under different trigger levels;

[0044] (6.1), find the maximum value max in the maximum value group and the minimum value min in the minimum value group; find the maximum value in the maximum value group and the minimum value in the minimum value group in the sampling data, as shown in the formula (1), the maximum value in the sampling data is 4V, and the minimum value is 0V. Figure 2

[0045] (6.2), set the high trigger level level h ;

[0046]

[0047] (6.3), set the low trigger level level l ;

[0048]

[0049] Wherein, δ is the noise suppression coefficient;

[0050] (6.4), extract the positive and negative time width of the standard sampling data by using the double hysteresis comparison method;

[0051] ​Traverse the first sampling point of the standard sampling data, count from the first sampling point greater than the high trigger level to the first sampling point less than the low trigger level to obtain a positive time width width value, and finally record all positive time width width values in the standard sampling data;

[0052] Count from the first sampling point less than the low trigger level to the first sampling point greater than the high trigger level to obtain a negative time width width value, and finally record all negative time width width values in the standard sampling data;

[0053] In this embodiment, taking the positive time width as an example, the time width width values of the signal are 8ns, 6ns, 3ns, 4ns, 5ns, and 35ns as shown in Figure 2

[0054] (6.5) Traverse each positive time width width value and negative time width width value, and count the number of times each time width width value appears;

[0055] In this embodiment, taking the positive time width as an example, the number of times each time width width value appears is counted, as shown in Figure 2

[0056] (7) Set the adaptive time width trigger condition;

[0057] Find the time width width value with the least number of appearances. In this embodiment, taking the positive time width as an example, as shown in Figure 2 It can be seen that there are five time width width values with the least number of appearances, which are 8ns, 6ns, 3ns, 4ns, and 35ns;

[0058] If there is only one time width width value with the least number of appearances, set the time width width value and the corresponding polarity as the time width trigger condition;

[0059] If there are multiple time width width values with the least number of appearances, calculate the sum of distances of each time width width value and other time width width values in turn, and then select the time width width value with the largest sum of distances and the corresponding polarity as the time width trigger condition;

[0060] The distance calculation method of the time width is as follows:

[0061] First, obtain the positive time width width value P wp and the negative time width width value P wn ;

[0062] Calculate the sum of distances of each positive and negative time width width value and other time width width values;

[0063] ​​

[0064]

[0065] Among them, D p (i) represents the sum of the distances between the i-th negative time width value and the other positive time width values, D n (i) represents the sum of the distances between the i-th negative time width value and the other negative time width values;

[0066] In this embodiment, taking positive time width as an example, the polarity corresponding to positive time width is positive; such as Figure 2 As shown, the time width value P wp =[3, 4, 5, 5, 5, 6, 8, 35]. There are five time width values ​​that appear the least frequently. Calculate the distance between these five positive time widths and the other time widths. The distances for 3ns, 4ns, 6ns, 8ns, and 35ns time widths are 47, 41, 39, 47, and 209, respectively. Clearly, the 35ns time width value has the largest distance from the other time width values. The time width trigger condition should be set to: positive polarity and a time width value equal to 35ns. Then, send the time width trigger condition to the time width trigger module in the FPGA. Finally, set the trigger release time to any integer multiple of the signal period to trigger the signal of that time width.

[0067] (8) Set adaptive abnormal time-width trigger conditions;

[0068] Calculate the mean and standard deviation of all time width values; the methods for calculating the mean and standard deviation are as follows:

[0069] First, calculate the average width value for both positive and negative values.

[0070] Calculate the deviation between the width value and the average value for each time-width value:

[0071]

[0072]

[0073] Calculate the standard deviation of the width values ​​for both positive and negative cases:

[0074]

[0075]

[0076] Where m represents the number of width values, whether positive or negative;

[0077] Select the time width values ​​that are more than twice the standard deviation from the mean, and then treat each time width value that is more than twice the standard deviation from the mean as an abnormal time width.

[0078] Determine the time width polarity corresponding to the abnormal time width:

[0079] First, the positive and negative time width values are sorted from small to large, respectively, to form two sequences;

[0080] Positive time width: P wp = [P wp (1), P wp (2), …, P wp (i), …, P wp (m)]

[0081] Negative time width: P wn = [P wn (1), P wn (2), …, P wn (i), …, P wn (m)]

[0082] Wherein, m represents the number of positive and negative time width width values in the abnormal time width;

[0083] If the abnormal time width is a positive time width and is located at the first time width width value P wp (1) after sorting the positive time width, the abnormal time width trigger condition is set as: positive polarity, time width width value less than P wp (2); if the abnormal time width is a negative time width and is located at the first time width width value P wn (1) after sorting the negative time width, the abnormal time width trigger condition is set as: negative polarity, time width width value less than P wn (2);

[0084] If the abnormal time width is a positive time width and is located at the last time width width value P wp (m) after sorting the positive time width, the abnormal time width trigger condition is set as: positive polarity, time width width value greater than P wp (m-1); if the abnormal time width is a negative time width and is located at the last time width width value P wn (m) after sorting the negative time width, the abnormal time width trigger condition is set as: negative polarity, time width width value greater than P wn (m-1);

[0085] If the abnormal time width is a positive time width and is located at any time width width value P wp (i) in the sequence after sorting the positive time width, the abnormal time width trigger condition is set as: positive polarity, time width width value in the interval [P wp (i-1), P wp (i+1)]; if the abnormal time width is a negative time width and is located at any time width width value P wn (i) in the sequence after sorting the negative time width, the abnormal time width trigger condition is set as: negative polarity, time width width value in the interval [P wn (i-1), Pwn (i+1)];

[0086] In this embodiment, as shown in Figure 2 When the time width abnormality detection is performed, the average value of the time width width value is calculated Standard deviation σ P = 10.663; the difference between the obvious time width width value 35ns and the average value P wp is greater than twice the standard deviation; combined with the sequence after sorting the time width width value: [3, 4, 5, 5, 5, 6, 8, 35], the time width width value 35ns is located at the last time width width value after sorting, therefore, the abnormal time width trigger condition is set as: positive polarity, time width value greater than 8ns.

[0087] (9), the measured signal detection and display;

[0088] The time width trigger condition set in step (7) and the abnormal time width trigger condition set in step (8) are issued to the time width trigger module in the FPGA, the time width trigger module judges the measured signal according to the issued condition, triggers the time width signal meeting the time width trigger condition and the abnormal signal meeting the abnormal time width trigger condition respectively, and then controls the acquisition system to store and finally display the signal.

[0089] Although the above describes the specific embodiments of the present application for the purpose of facilitating the understanding of the present application by those skilled in the art, it should be clear that the present application is not limited to the scope of the specific embodiments, and for those skilled in the art, it is obvious that various changes are within the spirit and scope of the present application defined and determined by the appended claims, and all the inventions utilizing the concept of the present application are within the scope of protection.

Claims

1. A method for adaptive time-width triggering and time-width anomaly detection in a digital oscilloscope, characterized in that, Includes the following steps: (1) Power on the digital oscilloscope and connect the signal to be measured; (2) The digital oscilloscope's acquisition system acquires sampling data for a sufficient duration and then uploads it to the host computer; (3) Set the maximum and minimum threshold values; Iterate through each sampling point, assuming the first sampling point is the maximum value. Then compare each of the next three adjacent sampling points. If the value of the middle sampling point is the largest, then the middle sampling point is determined to be the maximum value; if the value of the middle sampling point is the smallest, then the middle sampling point is determined to be the minimum value. For the last sampling point, directly compare it with the previous sampling point. If the last sampling point is larger than the previous sampling point, then the last sampling point is determined to be the maximum value; otherwise, it is determined to be the minimum value. Finally, store the maximum value sampling points in the maximum value group and the minimum value sampling points in the minimum value group. (4) Extract sampling data for a complete period based on the distribution characteristics of the maximum and minimum values; (5) Repeat steps (2) to (4) multiple times to obtain multiple sets of complete cycle sampling data. Then, calculate the mean of multiple sets of sampling data and filter them to obtain a complete cycle of standard sampling data. (6) Distribution of time-width characteristics of statistical standard sampled data under different trigger levels; (7) Set adaptive time-width triggering conditions based on the time-width characteristic distribution; Find the time width value that appears least frequently. If there is only one time width value that appears least frequently, set that time width value as the time width trigger condition. If there are multiple time width values ​​that appear least frequently, calculate the sum of the distances between each time width value and the other time width values ​​in turn, and then select the time width value with the largest sum of distances as the time width trigger condition. Finally, set the trigger release time to any integer multiple of the signal period to trigger the time width signal. (8) Set adaptive abnormal time-width triggering conditions based on the time-width characteristic distribution; (8.1) Calculate the average and standard deviation of all time width values; (8.2) Select the time width values ​​that are more than twice the standard deviation from the average value, and then treat each time width value as an abnormal time width; (8.3) Determine the time width polarity corresponding to each abnormal time width; First, sort the positive and negative width values ​​in ascending order to form two sequences; Time width: P wp =[P wp (1),P wp (2),…,P wp (i),...,P wp (k)] Negative time width: P wn =[P wn (1),P wn (2),…,P wn (i),…,P wn (k)] Where k represents the number of positive and negative bandwidth values ​​in the abnormal bandwidth; If the abnormal time width is a positive time width and is the first width value P after the positive time width is sorted. wp (1) Then set the abnormal time-width trigger condition to: positive polarity, time-width value less than P wp (2); If the abnormal time width is a negative time width and is the first width value P after the negative time width sorting. wn (1) Then set the abnormal time-width trigger condition to: negative polarity, time-width value less than P wn (2); If the abnormal time width is a positive time width and is the last width value P after the positive time width sorting... wp (k) then the abnormal time-width trigger condition is set to: positive polarity, time-width value greater than P. wp (k-1); If the abnormal time width is a negative time width and is the last width value P after the negative time width sorting. wn (k) then the abnormal time-width trigger condition is set to: negative polarity, time-width value greater than P. wn (k-1); If the abnormal time width is a positive time width and is located at any width value P in the middle of the sequence after the positive time width is sorted. wp (i) Then the abnormal time-width trigger condition is set as follows: positive polarity, time-width value is within the interval [P] wp (i-1),P wp [i+1]; If the abnormal time width is a negative time width and is located in any middle of the negative time width sorted sequence, the width value P is... wn (i) Then the abnormal time-width trigger condition is set as: negative polarity, time-width value within the interval [P] wn (i-1),P wn (i+1)]; (8.4) Take each abnormal time width and its corresponding time width polarity as the abnormal time width triggering condition; (9) Detection and display of the measured signal; The time-width triggering conditions and abnormal time-width triggering conditions are sent to the time-width triggering module in the FPGA. The time-width triggering module judges the measured signal according to the sent conditions, and triggers the time-width signal that meets the time-width triggering conditions and the abnormal signal that meets the abnormal time-width triggering conditions respectively. Then, it controls the acquisition system to store the signal and finally display it.

2. The method for adaptive time-width triggering and time-width anomaly detection of a digital oscilloscope according to claim 1, characterized in that, The statistical method for the distribution of the time-width feature is as follows: (2.1) Find the maximum value max in the maximum value group and the minimum value min in the minimum value group; (2.2) Set the high trigger level h ; (2.3) Set the low trigger level l ; Where n is the noise suppression coefficient; (2.4) The positive and negative time widths of the standard sampling data are extracted using the double hysteresis comparison method; Starting from the first sampling point of the standard sampled data, the system iterates through the data, counting from the first sampling point that is greater than the high trigger level to the first sampling point that is less than the low trigger level, thus obtaining a positive time width value. Finally, all positive time width values ​​in the standard sampled data are recorded. The counting begins with the first sample point that is less than the low trigger level and ends with the first sample point that is greater than the high trigger level, resulting in a negative time width value. Finally, all negative time width values ​​in the standard sampled data are recorded. (2.5) Iterate through each positive and negative time width value and count the number of times each time width value appears.

3. The method for adaptive time-width triggering and time-width anomaly detection of a digital oscilloscope according to claim 1, characterized in that, The standard deviation of the time-width value is calculated as follows: First, calculate the average width value for both positive and negative values. Calculate the deviation between the width value and the average value for each time-width value: Calculate the standard deviation of the width values ​​for both positive and negative cases: Where m represents the number of width values, whether positive or negative.

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