Digital signal identification method

Abstract

The invention discloses a digital signal identification method, which belongs to the data analysis field and comprises the seven steps of: offset sampling, line segment searching, line segment classifying, hop identifying, pull-up and pull-down identifying, filter wave identifying and signal determining. The present invention is based on the characteristics of a digital signal; and through the acquisition of multistage waveform data, the signal identification accuracy is high. The determining method is simple and the various identification parameter values in the method can be changed according to the specific conditions so that the method can be adapted to the detection of data waveforms in different conditions.

Description

technical field

[0001] The invention relates to the technical field of data analysis, in particular to a method for identifying digital signals. Background technique

[0002] Usually, in the process of collecting data, the signal waveforms collected are divided into two types: analog signals and digital signals. The essential difference between an analog signal and a digital signal is that the analog signal changes continuously, while the digital signal changes between different level values.

[0003] The existing signal recognition process is generally more complex and cumbersome, and the recognition speed and accuracy cannot reach a good balance value, resulting in low analysis efficiency, which is not suitable for the development needs of today's society.

[0004] It is generally difficult to identify the digital interface of existing electronic equipment or circuit boards, especially when a certain product is unknown, it is difficult to accurately and quickly detect the...

Examples

Embodiment 1

[0061] like figure 1 As shown, a digital signal recognition method includes the following steps:

[0062] (1) Offset sampling

[0063] Set the voltage difference between the reference ground of the oscilloscope channel and the ground wire of the object under test to be X volts, and then collect a section of voltage waveform as the waveform to be tested;

[0064] (2) Find the line segment

[0065] Set sampling point interval = 10, that is, the difference between the index values ​​of two adjacent sampling points, that is, sampling every 9 actual sampling points; number of sampling points = 4 = number of sampling segments + 1, two adjacent sampling points The data in between is a section of sampling; the discrete value of the sampling point = 0.1V, the absolute value of the difference between the voltage value of any sampling point and the average voltage value of all sampling points is used to judge the validity of the sampling; the number of filtering points = 3, When used ...

Embodiment 2

[0094] Embodiment 2: as figure 2 and image 3 as shown, figure 2 for two pull-ups and one transition, image 3 It is two pull-downs and one jump, and the rest are the same as in Embodiment 1, except that: in the step (7), after detection, the above-mentioned line segments meet the following judgment conditions: the number of pull-ups ≥ 0 and the number of pull-downs ≥ 0 And the number of times of pull-up and pull-down ≥ 1 and the number of filtering ≤ 1 and the number of jumps = 3 - the number of pull-ups - the number of pull-down - the number of filtering = 1, so it is a tri-state digital signal.

Embodiment 3

[0095] Embodiment 3: as Figure 4 As shown, the remaining parts are the same as in Embodiment 1, except that the N=5.

[0096] In the present invention, first look for a horizontal line segment with equal level values ​​from the collected waveform data, and traverse all the collected data backwards in this way to find all the line segments; secondly, merge all the line segments and judge that the average voltage value of the line segment is in the Within the preset range; identify the change data between two adjacent line segments again; finally determine the type of signal; in engineering applications, when the identification parameters are manually set according to the actual signal waveform, the computer will automatically record these identification parameter values In order to achieve the purpose of self-learning, it lays the data foundation for automatic matching and identification of parameter values ​​according to the collected waveforms.

[0097] Based on the above, ...

technical field

[0001] The invention relates to the technical field of data analysis, in particular to a method for identifying digital signals. Background technique

[0002] Usually, in the process of collecting data, the signal waveforms collected are divided into two types: analog signals and digital signals. The essential difference between an analog signal and a digital signal is that the analog signal changes continuously, while the digital signal changes between different level values.

[0003] The existing signal recognition process is generally more complex and cumbersome, and the recognition speed and accuracy cannot reach a good balance value, resulting in low analysis efficiency, which is not suitable for the development needs of today's society.

[0004] It is generally difficult to identify the digital interface of existing electronic equipment or circuit boards, especially when a certain product is unknown, it is difficult to accurately and quickly detect the...

Examples

Embodiment 1

[0061] like figure 1 As shown, a digital signal recognition method includes the following steps:

[0062] (1) Offset sampling

[0063] Set the voltage difference between the reference ground of the oscilloscope channel and the ground wire of the object under test to be X volts, and then collect a section of voltage waveform as the waveform to be tested;

[0064] (2) Find the line segment

[0065] Set sampling point interval = 10, that is, the difference between the index values ​​of two adjacent sampling points, that is, sampling every 9 actual sampling points; number of sampling points = 4 = number of sampling segments + 1, two adjacent sampling points The data in between is a section of sampling; the discrete value of the sampling point = 0.1V, the absolute value of the difference between the voltage value of any sampling point and the average voltage value of all sampling points is used to judge the validity of the sampling; the number of filtering points = 3, When used ...

Embodiment 2

[0094] Embodiment 2: as figure 2 and image 3 as shown, figure 2 for two pull-ups and one transition, image 3 It is two pull-downs and one jump, and the rest are the same as in Embodiment 1, except that: in the step (7), after detection, the above-mentioned line segments meet the following judgment conditions: the number of pull-ups ≥ 0 and the number of pull-downs ≥ 0 And the number of times of pull-up and pull-down ≥ 1 and the number of filtering ≤ 1 and the number of jumps = 3 - the number of pull-ups - the number of pull-down - the number of filtering = 1, so it is a tri-state digital signal.

Embodiment 3

[0095] Embodiment 3: as Figure 4 As shown, the remaining parts are the same as in Embodiment 1, except that the N=5.

[0096] In the present invention, first look for a horizontal line segment with equal level values ​​from the collected waveform data, and traverse all the collected data backwards in this way to find all the line segments; secondly, merge all the line segments and judge that the average voltage value of the line segment is in the Within the preset range; identify the change data between two adjacent line segments again; finally determine the type of signal; in engineering applications, when the identification parameters are manually set according to the actual signal waveform, the computer will automatically record these identification parameter values In order to achieve the purpose of self-learning, it lays the data foundation for automatic matching and identification of parameter values ​​according to the collected waveforms.

[0097] Based on the above, ...

Images