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

Abstract

The invention discloses a digital oscilloscope adaptive time width triggering and time width anomaly detection method, which comprises the following steps: after an ADC (Analog to Digital Converter) acquires a signal, uploading sampling data to an upper computer, obtaining a proper time width triggering condition by utilizing a time width triggering setting adaptive algorithm and a time width anomaly detection adaptive algorithm on the upper computer, and designing a time width triggering module in an FPGA (Field Programmable Gate Array) to realize time width anomaly detection. And then the trigger conditions are issued to a time width trigger module in the FPGA, real-time detection and storage of signals meeting the conditions are completed, and finally the signals meeting the set time width trigger conditions and the signals with abnormal time widths are displayed on the upper computer.

Description

Technical Field

[0001] The invention belongs to the technical field of digital oscilloscopes, and more specifically, relates to a digital oscilloscope adaptive time width trigger and time width anomaly detection method. Background Art

[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 getting higher and higher. The acquisition system is also becoming more and more complex, and the trigger function, as one of the most important components of the acquisition system, is also playing an increasingly complex and important role. Using triggering can stabilize waveform display and capture waveforms with certain characteristics.

[0003] In the past, triggering relied on basic edge triggering to capture waveforms, but nowadays the measured signal does not have only a single feature. Simply detecting the level change trend of the measured signal cannot meet the needs of some test scenarios. Therefore, edge triggering cannot capture complex signals. For this reason, the acquisition system has added many advanced trigger functions. Time width triggering is a trigger type that is frequently used in advanced triggering of acquisition systems. Time width triggering refers to the acquisition system triggering on a specified width of positive or negative time width. Time width triggering is generally used to synchronize circuit behavior and capture abnormal phenomena in signals.

[0004] If you need to analyze a pulse width modulation (PWM) signal, the time width trigger can help users accurately capture and analyze pulse width changes, which is very useful in applications such as motor control and power management. At the same time, the time width trigger allows users to capture transient events of a specific pulse width. For example, in communications, users may need to capture pulses 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 of the user's interest. First, it is necessary to set the appropriate trigger level. The trigger level is the standard for judging the positive and negative time widths. At the same time, it is necessary to set the polarity of the time width, the time width and the logic comparison conditions. However, for users who are not familiar with the trigger function of the acquisition system, it is not possible to set the appropriate conditions to capture the waveform. In the past, it was necessary to use the automatic setting function of the acquisition system 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 that require time width triggering, it is still difficult for users to reasonably set the trigger conditions of the time width trigger.

[0006] Traditional acquisition systems have poor ability to capture abnormal signals of unknown signal shapes, and cannot capture abnormal signals of unknown time width. Therefore, a high-speed acquisition system that can automatically extract signal time width features is needed. By analyzing the distribution characteristics of signal time width, adaptively setting time width abnormality detection conditions, abnormal signals of unknown signal shapes with time width are captured.

[0007] Extract the signal's time width characteristics in real time, select the optimal signal time width value, and set the trigger condition for time width detection through the time width value. When the signal meets the time width trigger condition, the signal that meets the characteristics is stably captured and displayed. Extract the signal's time width distribution characteristics, select the signal's time width nominal range, and set the time width detection condition according to the range, so that the abnormal time width signal that does not meet the condition is captured and displayed at the same time. Summary of the invention

[0008] The purpose of the present invention is to overcome the deficiencies of the prior art and to provide a digital oscilloscope adaptive time width trigger and time width anomaly detection method, which can automatically and quickly capture signals that meet the set time width trigger conditions and signals with time width anomalies.

[0009] To achieve the above-mentioned object of the invention, the present invention provides a method for adaptive time width triggering and time width anomaly detection of a digital oscilloscope, characterized in that it comprises the following steps:

[0010] (1) Power on the digital oscilloscope and connect it to the signal to be measured;

[0011] (2) The acquisition system of the digital oscilloscope collects sampling data of sufficient length and then uploads it to the host computer;

[0012] (3) Set the maximum value threshold and the minimum value threshold; traverse each sampling point, set the first sampling point as the maximum value by default, and then compare each of the three adjacent sampling points. If the value of the middle sampling point is the largest, the middle sampling point is determined to be the maximum value; if the value of the middle sampling point is the smallest, 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, the last sampling point is determined to be the maximum value, otherwise it is determined to be 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 sampling data of a complete cycle based on the distribution characteristics of the maximum and minimum values;

[0014] (5) Repeat steps (2) to (4) for multiple times to obtain multiple sets of complete cycle sampling data, then average and filter the multiple sets of sampling data to obtain standard sampling data for a complete cycle;

[0015] (6) Statistical distribution of time width characteristics of standard sampling data at different trigger levels;

[0016] (7) Setting adaptive time width trigger conditions according to the time width feature distribution;

[0017] Find the duration width value with the least number of occurrences. If there is only one duration width value with the least number of occurrences, set this duration width value as the duration trigger condition. If there are multiple duration width values ​​with the least number of occurrences, calculate the sum of the distances between each duration width value and other duration width values ​​in turn, and then select the duration width value with the largest sum of distances as the duration trigger condition. Finally, set the trigger holdoff time to any integer multiple of the signal period to trigger the duration signal.

[0018] (8) Setting adaptive abnormal time width triggering conditions according to the time width characteristic distribution;

[0019] (8.1) Calculate the mean and standard deviation of all time width values;

[0020] (8.2) Select the time width values ​​that are two times the standard deviation from the mean value, and then regard each time width value as an abnormal time width;

[0021] (8.3) Determine the time width polarity corresponding to each abnormal time width:

[0022] (8.4) Each abnormal time width and the corresponding time width polarity are used as abnormal time width trigger conditions

[0023] (9) Detection and display of measured signals;

[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 conditions, and triggers the time width signal that meets the time width trigger condition and the abnormal signal that meets the abnormal time width trigger condition respectively, and then controls the acquisition system to store the signal and finally display it.

[0025] The object of the invention of the present invention is achieved in this way:

[0026] The method for adaptive time width triggering and time width anomaly detection of a digital oscilloscope of the present invention uploads the sampled data to a host computer after an ADC acquires a signal, uses a time width trigger setting adaptive algorithm and a time width anomaly detection adaptive algorithm on the host computer to obtain a suitable time width trigger condition, designs a time width trigger module in an FPGA at the same time, sends the trigger condition to the time width trigger module in the FPGA, completes real-time detection and storage of signals meeting the conditions, and finally displays signals meeting the set time width trigger condition and signals with time width anomalies on the host computer.

[0027] At the same time, the digital oscilloscope adaptive time width trigger and time width anomaly detection method of the present invention also has the following features:

[0028] Beneficial effects:

[0029] (1) The present invention can help users automatically set the time width trigger conditions and complete the capture of time width signals without requiring users to be familiar with the advanced trigger setting methods of the acquisition system;

[0030] (2) The present invention can capture time-width abnormal signals of unknown form without requiring the user to know the specific form of the time-width abnormal signal;

[0031] (3) The present invention can automatically identify occasional glitch abnormal signals in periodic signals and can be applied to the detection of occasional glitch abnormalities in periodic signals, which helps to solve the problem that users cannot set trigger conditions because they cannot know the abnormal signal shape. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flow chart of the method for adaptive time width triggering and time width anomaly detection of a digital oscilloscope of the present invention;

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

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

[0035] Example

[0036] In this embodiment, if Figure 1 As shown, the present invention provides a digital oscilloscope adaptive time width trigger and time width anomaly detection method, comprising the following steps:

[0037] (1) Power on the digital oscilloscope and connect it to the signal to be measured;

[0038] (2) The acquisition system of the digital oscilloscope collects sampling data of sufficient length and then uploads it to the host computer;

[0039] (3) Set the maximum value threshold and the minimum value threshold; traverse each sampling point, set the first sampling point as the maximum value by default, and then compare each of the three adjacent sampling points. If the value of the middle sampling point is the largest, the middle sampling point is determined to be the maximum value; if the value of the middle sampling point is the smallest, 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, the last sampling point is determined to be the maximum value, otherwise it is determined to be 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;

[0040] For example: for three adjacent sampling points 4, 5, and 6, if the amplitude corresponding to sampling point 5 is the largest, then sampling point 5 is placed in the maximum value group; if the amplitude corresponding to sampling point 5 is the smallest, then sampling point 5 is placed in the minimum value group; otherwise, it is discarded and not placed in any group;

[0041] (4) Extract sampling data of a complete cycle based on the distribution characteristics of the maximum and minimum values;

[0042] (5) Repeat steps (2) to (4) for 5 times to obtain multiple sets of complete cycle sampling data, then average and filter the multiple sets of sampling data to obtain standard sampling data of a complete cycle;

[0043] (6) Statistical distribution of time width characteristics of standard sampling data at 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 sampled data, such as Figure 2 As shown, the maximum value of the sampled data is 4V and the minimum value is 0V.

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

[0046]

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

[0048]

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

[0050] (6.4) Use the double hysteresis comparison method to extract the positive and negative time widths of the standard sampling data;

[0051] Start traversing from the first sampling point of the standard sampling data, start counting from the first sampling point greater than the high trigger level, and end counting at the first sampling point less than the low trigger level to obtain a timing width value, and finally record all timing width values ​​in the standard sampling data;

[0052] Start counting from the first sampling point that is less than the low trigger level, and end counting at the first sampling point that is greater than the high trigger level to obtain a negative time width value. Finally, record all negative time width values ​​in the standard sampling data.

[0053] In this embodiment, taking the positive time width as an example, the time width value of the signal is as follows: Figure 2 As shown, there are several time width values: 8ns, 6ns, 3ns, 4ns, 5ns, and 35ns;

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

[0055] In this embodiment, taking the positive time width as an example, the number of occurrences of each time width value is counted, such as Figure 2 As shown, 5ns appears 3 times, 8ns, 6ns, 3ns, 4ns, and 35ns appear only once;

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

[0057] Find the duration width value with the least number of occurrences. In this embodiment, take the positive duration as an example. Figure 2 As shown, we can see that there are five time width values ​​with the least occurrence, namely: 8ns, 6ns, 3ns, 4ns, and 35ns;

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

[0059] If there are multiple duration width values ​​with the least number of occurrences, the sum of the distances between each duration width value and other duration width values ​​is calculated in turn, and then the duration width value with the largest sum of distances and the corresponding polarity are selected as the duration trigger condition;

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

[0061] First, get the timing width value P wp and negative time width value P wn ;

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

[0063]

[0064]

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

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

[0067] (8) Set the adaptive abnormal time width trigger condition;

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

[0069] First calculate the average value of the positive and negative time width values

[0070] Calculate the deviation of each time width value from the mean:

[0071]

[0072]

[0073] Calculate the standard deviation of positive and negative time width values:

[0074]

[0075]

[0076] Where m represents the number of positive and negative time width values;

[0077] Select the time width value outside the two standard deviations of the mean, and then take each time width value outside the two standard deviations of the mean as the abnormal time width;

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

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

[0080] Timing 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] Where m represents the number of positive and negative time 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 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 located at the first time width value P after the negative time width is sorted wn (1), then set the abnormal time width trigger condition to: negative polarity, time 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 value P after the positive time width is sorted wp (m), then the abnormal time width trigger condition is set to: positive polarity, time width value greater than P wp (m-1); if the abnormal time width is negative and is located at the last time width value P after the negative time width is sorted wn (m), then the abnormal time width trigger condition is set to: negative polarity, time width value greater than P wn (m-1);

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

[0086] In this embodiment, if Figure 2 As shown, when performing time width anomaly detection, taking the positive time width anomaly detection as an example, the average value of the positive time width value is calculated. Standard deviation P =10.663; obvious width value 35ns and average value P wp The difference is greater than twice the standard deviation; combined with the sequence after the positive time width value is sorted: [3, 4, 5, 5, 5, 6, 8, 35], the time width value 35ns is located at the last width value after the positive time width is sorted. Therefore, the abnormal time width trigger condition is set to: positive polarity, time width value greater than 8ns.

[0087] (9) Detection and display of measured signals;

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

[0089] Although the above describes the illustrative specific embodiments of the present invention to facilitate those skilled in the art to understand the present invention, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations using the concept of the present invention are protected.

Claims

1. A digital oscilloscope adaptive time width trigger and time width anomaly detection method, characterized in that: The following steps are involved: (1) Power on the digital oscilloscope and connect it to the signal to be measured; (2) The acquisition system of the digital oscilloscope collects sampling data of sufficient length and then uploads it to the host computer; (3) Set the maximum and minimum thresholds; Traverse each sampling point, set the first sampling point as the maximum value by default, and then compare each of the three adjacent sampling points. If the value of the middle sampling point is the largest, the middle sampling point is determined to be the maximum value; if the value of the middle sampling point is the smallest, 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, the last sampling point is determined to be the maximum value, otherwise it is determined to be the minimum value. Finally, the maximum sampling point is stored in the maximum value group, and the minimum sampling point is stored in the minimum value group; (4) Extract sampling data of a complete cycle based on the distribution characteristics of the maximum and minimum values; (5) Repeat steps (2) to (4) for multiple times to obtain multiple sets of complete cycle sampling data, then average and filter the multiple sets of sampling data to obtain standard sampling data for a complete cycle; (6) Statistical distribution of time width characteristics of standard sampling data at different trigger levels; (7) Setting adaptive time width trigger conditions according to the time width feature distribution; Find the duration width value with the least number of occurrences. If there is only one duration width value with the least number of occurrences, set this duration width value as the duration trigger condition. If there are multiple duration width values ​​with the least number of occurrences, calculate the sum of the distances between each duration width value and other duration width values ​​in turn, and then select the duration width value with the largest sum of distances as the duration trigger condition. Finally, set the trigger holdoff time to any integer multiple of the signal period to trigger the duration signal. (8) Setting adaptive abnormal time width triggering conditions according to the time width characteristic distribution; (8.1) Calculate the mean and standard deviation of all time width values; (8.2) Select the time width values ​​that are two times the standard deviation from the mean value, and then regard each time width value as an abnormal time width; (8.3) Determine the time width polarity corresponding to each abnormal time width: (8.4) Each abnormal time width and the corresponding time width polarity are used as abnormal time width trigger conditions (9) Detection and display of measured signals; 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 conditions, and triggers the time width signal that meets the time width trigger condition and the abnormal signal that meets the abnormal time width trigger condition respectively, and then controls the acquisition system to store the signal and finally display it.

2. A digital oscilloscope adaptive time width trigger and time width anomaly detection method according to claim 1, characterized in that: The statistical method of the time width characteristic distribution is: (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) Use the double hysteresis comparison method to extract the positive and negative time widths of the standard sampling data; Start traversing from the first sampling point of the standard sampling data, start counting from the first sampling point greater than the high trigger level, and end counting at the first sampling point less than the low trigger level to obtain a timing width value, and finally record all timing width values ​​in the standard sampling data; Start counting from the first sampling point that is less than the low trigger level, and end counting at the first sampling point that is greater than the high trigger level to obtain a negative time width value. Finally, record all negative time width values ​​in the standard sampling data. (2.5) Traverse each positive time width value and negative time width value, and count the number of times each time width value appears.

3. A digital oscilloscope adaptive time width trigger and time width anomaly detection method according to claim 1, characterized in that: The standard deviation of the time width value is calculated as follows: First calculate the average value of the positive and negative time width values Calculate the deviation of each time width value from the mean: Calculate the standard deviation of positive and negative time width values: Wherein, m represents the number of positive and negative time width values.

4. A digital oscilloscope adaptive time width trigger and time width anomaly detection method according to claim 1, characterized in that: The method for determining the time width polarity of the abnormal time width is: First, sort the positive and negative time width values ​​from small to large to form two sequences; Timing width: P wp =[P wp (1),P wp (2),…,P wp (i),…,P wp (m)] Negative time width: P wn =[P wn (1),P wn (2),…,P wn (i),…,P wn (m)] Where m represents the number of positive and negative time width values ​​in the abnormal time width; If the abnormal time width is a positive time width and is located at the first time 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 located at the first time width value P after the negative time width is sorted 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 located at the last time width value P after the positive time width is sorted wp (m), then the abnormal time width trigger condition is set to: positive polarity, time width value greater than P wp (m-1); if the abnormal time width is negative and is located at the last time width value P after the negative time width is sorted wn (m), then the abnormal time width trigger condition is set to: negative polarity, time width value greater than P wn (m-1); If the abnormal time width is a positive time width and is located in any time width value P in the middle of the sequence after the positive time width is sorted wp (i), then set the abnormal time width trigger condition to: 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 time width value P in the middle of the sequence after the negative time width is sorted wn (i), then set the abnormal time width trigger condition to: negative polarity, time width value is within the interval [P wn (i-1),P wn (i+1)].

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