Eye diagram abnormal waveform detection method, device, computer equipment, and storage medium

Abstract

The present disclosure relates to an eye diagram abnormal waveform detection method, device, computer equipment, storage medium and computer program product. The method comprises: obtaining eye diagram data and abnormal waveform features; setting an initial template according to the abnormal waveform features or custom requirements; setting an overlay depth in the initial template to obtain a target template, wherein the overlay depth represents the threshold value of the number of waveforms allowed to exist in the template pixel points; using the target template to detect the waveform in the eye diagram data and determine the abnormal waveform detection result of the eye diagram data. The design of the overlay depth allows the eye diagram template to have room for adjustment in terms of sensitivity, thereby meeting the demand for accurate detection of sporadic signals in the time domain. The use of this method can solve the problem of difficulty in accurately detecting sporadic signals in the time domain.

Description

Technical Field

[0001] The present disclosure relates to the technical field of digital signal processing, and in particular to a method, device, computer equipment, and storage medium for detecting abnormal eye diagram waveforms. Background Art

[0002] With the development of digital signal processing technology, eye diagram data processing technology has emerged. The eye diagram records and counts the information before the violation time point. The eye diagram of high-speed serial signals contains almost all the prior information. By comparing the known information with the illegal eye diagram information, information that cannot be observed in the time domain can be obtained in the comparison. In the process of measuring time domain signals, the information before the measurement time point is not easy to be retained due to many reasons such as storage depth and settings. In specific scenarios, if it is necessary to compare the previous characteristics of the signal with the current signal characteristics, it is difficult to locate the problem using only the time domain observation method. Due to the sporadic nature of the waveform, it takes a lot of time to use human observation to observe the moment when the waveform in the eye diagram is wrong, and the correctness of the observation results cannot be guaranteed.

[0003] Due to occasional reasons, the characteristics of the target waveform are not easy to observe, and it is difficult to find the trigger conditions. The template trigger function currently used will respond to the signal when the signal touches the template. The influence of small noise or jitter cannot be ignored, resulting in an overly sensitive response at the edge of the set template, making the effect of detecting abnormal waveforms unsatisfactory. Summary of the invention

[0004] Based on this, it is necessary to provide an eye diagram abnormal waveform detection method, device, computer equipment, computer readable storage medium and computer program product that can solve the problem of difficulty in accurately detecting sporadic signals in the time domain in response to the above technical problems.

[0005] In a first aspect, the present disclosure provides a method for detecting abnormal eye diagram waveforms. The method comprises:

[0006] Obtain eye diagram data and abnormal waveform characteristics;

[0007] According to the abnormal waveform characteristics or custom requirements, an initial template is set;

[0008] Setting a stacking depth in the initial template to obtain a target template, wherein the stacking depth represents a threshold value of the number of waveforms allowed to exist in the template pixel points;

[0009] The target template is used to detect the waveform in the eye diagram data to determine an abnormal waveform detection result of the eye diagram data.

[0010] In one embodiment, the method further comprises:

[0011] When the abnormal waveform detection result includes the presence of an abnormal waveform, the type of the abnormal waveform is determined according to the abnormal waveform detection result to obtain a type determination result.

[0012] In one embodiment, the method further comprises:

[0013] When the abnormal waveform detection result includes the presence of an abnormal waveform, corresponding abnormal processing is performed according to the abnormal waveform detection result, and the abnormal processing includes at least one of the following processing: stop upon failure, save current frame, buzzer, screenshot, no response.

[0014] In one embodiment, the method further comprises:

[0015] Get time data and voltage data;

[0016] Drawing a target area in the initial template according to the time data and the voltage data to obtain an area template;

[0017] The stacking depth is set in the region template to obtain a target template, wherein the edge stacking depth of the target template is greater than the internal stacking depth.

[0018] In one embodiment, the initial template includes a loaded template or a drawn template.

[0019] In one embodiment, the type determination result includes:

[0020] When the waveform in the eye diagram data collides with or penetrates the peripheral template in the target template, determining the type of the abnormal waveform is a signal over-amplitude;

[0021] When the waveform in the eye diagram data collides with the internal template in the target template, determining that the type of the abnormal waveform is excessive jitter;

[0022] When the waveform in the eye diagram data passes through the internal template in the target template, it is determined that the type of the abnormal waveform is a clock error.

[0023] In a second aspect, the present disclosure further provides a device for detecting abnormal eye diagram waveforms. The device comprises:

[0024] A first data acquisition module, used to acquire eye diagram data and abnormal waveform characteristics;

[0025] An initial template module, used to set an initial template according to the abnormal waveform characteristics or custom requirements;

[0026] A target template module, used to set a stacking depth in the initial template to obtain a target template, wherein the stacking depth represents a threshold value of the number of waveforms allowed to exist in the template pixel points;

[0027] The detection module is used to detect the waveform in the eye diagram data using the target template to determine the abnormal waveform detection result of the eye diagram data.

[0028] In one embodiment, the device further comprises:

[0029] The type judgment module is used to judge the type of the abnormal waveform according to the abnormal waveform detection result when the abnormal waveform detection result includes the existence of an abnormal waveform, so as to obtain a type judgment result.

[0030] In one embodiment, the device further comprises:

[0031] The exception handling module is used to perform corresponding exception handling according to the abnormal waveform detection result when the abnormal waveform detection result includes the existence of an abnormal waveform. The exception handling includes at least one of the following processing: stop upon failure, save current frame, buzzer, screenshot, and no response.

[0032] In one embodiment, the device further comprises:

[0033] A second data acquisition module, used to acquire time data and voltage data;

[0034] A region template module, used for drawing a target region in the initial template according to the time data and the voltage data to obtain a region template;

[0035] The target template module is used to set the stacking depth in the area template to obtain the target template, wherein the edge stacking depth of the target template is greater than the internal stacking depth.

[0036] In one embodiment, the type determination module is used to:

[0037] When the waveform in the eye diagram data collides with or penetrates the peripheral template in the target template, determining the type of the abnormal waveform is a signal over-amplitude;

[0038] When the waveform in the eye diagram data collides with the internal template in the target template, determining that the type of the abnormal waveform is excessive jitter;

[0039] When the waveform in the eye diagram data passes through the internal template in the target template, it is determined that the type of the abnormal waveform is a clock error.

[0040] In a third aspect, the present disclosure further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0041] Obtain eye diagram data and abnormal waveform characteristics;

[0042] According to the abnormal waveform characteristics or custom requirements, an initial template is set;

[0043] Setting a stacking depth in the initial template to obtain a target template, wherein the stacking depth represents a threshold value of the number of waveforms allowed to exist in the template pixel points;

[0044] The target template is used to detect the waveform in the eye diagram data to determine an abnormal waveform detection result of the eye diagram data.

[0045] In a fourth aspect, the present disclosure further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0046] Obtain eye diagram data and abnormal waveform characteristics;

[0047] According to the abnormal waveform characteristics or custom requirements, an initial template is set;

[0048] Setting a stacking depth in the initial template to obtain a target template, wherein the stacking depth represents a threshold value of the number of waveforms allowed to exist in the template pixel points;

[0049] The target template is used to detect the waveform in the eye diagram data to determine an abnormal waveform detection result of the eye diagram data.

[0050] In a fifth aspect, the present disclosure further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0051] Obtain eye diagram data and abnormal waveform characteristics;

[0052] According to the abnormal waveform characteristics or custom requirements, an initial template is set;

[0053] Setting a stacking depth in the initial template to obtain a target template, wherein the stacking depth represents a threshold value of the number of waveforms allowed to exist in the template pixel points;

[0054] The target template is used to detect the waveform in the eye diagram data to determine an abnormal waveform detection result of the eye diagram data.

[0055] The above-mentioned eye diagram abnormal waveform detection method, device, computer equipment, storage medium and computer program product, by setting the overlay depth in the eye diagram template, make the pixel points of the eye diagram template have a threshold value for the response to the abnormal waveform, so that the eye diagram template can detect the abnormal waveform while not being too sensitive, and can solve the problem of difficulty in accurately detecting sporadic signals in the time domain. The design of the overlay depth allows the eye diagram template to have room for adjustment in terms of sensitivity, thereby meeting the demand for accurate detection of sporadic signals in the time domain. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0057] Figure 1 A diagram showing an application environment of a method for detecting abnormal eye diagram waveforms in an embodiment;

[0058] Figure 2 A schematic diagram of a flow chart of a method for detecting abnormal eye diagram waveforms in one embodiment;

[0059] Figure 3 A schematic diagram of a flow chart of a method for detecting abnormal eye diagram waveforms in another embodiment;

[0060] Figure 4 A schematic diagram of a template of a method for detecting abnormal eye diagram waveforms in an embodiment;

[0061] Figure 5 A schematic diagram of a template of a method for detecting abnormal eye diagram waveforms in another embodiment;

[0062] Figure 6 A schematic diagram of a template of a method for detecting abnormal eye diagram waveforms in another embodiment;

[0063] Figure 7 A schematic diagram of a template of a method for detecting abnormal eye diagram waveforms in another embodiment;

[0064] Figure 8 is a structural block diagram of an abnormal eye diagram waveform detection device in one embodiment;

[0065] Fig. 9 is a structural block diagram of an abnormal eye pattern waveform detection device in another embodiment;

[0066] Fig.10 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solution and advantages of the present disclosure more clear, the present disclosure is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present disclosure and are not used to limit the present disclosure.

[0068] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0069] The eye diagram abnormal waveform detection method provided by the embodiment of the present disclosure can be applied to Figure 1 In the application environment shown. The server 104 has a data receiving end, which can be used to receive data (including eye diagram data and related data). The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The server 104 obtains eye diagram data and abnormal waveform characteristics. The server 104 sets an initial template according to the abnormal waveform characteristics or custom requirements. The server 104 sets the superposition depth in the initial template to obtain a target template, and the superposition depth represents the threshold value of the number of waveforms allowed to exist in the template pixel points. The server 104 uses the target template to detect the waveform in the eye diagram data and determine the abnormal waveform detection result of the eye diagram data. The server 104 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0070] In one embodiment, Figure 2 As shown, a method for detecting abnormal eye waveform is provided. Figure 1 The application environment in the example is used to illustrate the following steps:

[0071] S202, obtaining eye diagram data and abnormal waveform characteristics.

[0072] The eye diagram may refer to a historical image superimposed by an oscilloscope. The eye diagram data may refer to data that can be used to draw an eye diagram, which is data to be processed. The abnormal waveform feature may refer to a feature of an abnormal waveform.

[0073] Specifically, eye diagram data and abnormal waveform features are obtained. The eye diagram data is data to be processed, which is used to draw an eye diagram and perform abnormal waveform detection. The abnormal waveform may refer to a waveform that is different from the expected waveform, or may refer to a target waveform that needs to be found. The specific abnormal waveform may be defined according to the specific application scenario. The abnormal waveform generally refers to a waveform that is different from most waveforms in the eye diagram, for example, it may be a waveform that does not overlap with more than 90% of the waveforms in the eye diagram. The abnormal waveform features may refer to the features of the abnormal waveform determined according to actual needs.

[0074] S204: Setting an initial template according to the abnormal waveform characteristics or customized requirements.

[0075] The customized requirement may refer to the setting requirement of the initial template customized by the user. The initial template may refer to a geometric figure with a determined position and size in the eye diagram.

[0076] Specifically, the initial template can be used to detect abnormal waveforms in the eye diagram. According to the abnormal waveform characteristics or the custom requirements, an initial template capable of detecting abnormal waveforms is set. When the initial template is set according to the custom requirements, the user can set any initial template setting requirements, which is based on the specific usage requirements. The initial template has a certain position, size and geometric shape on the eye diagram. The initial template may include one or more geometric figures.

[0077] S206, setting a stacking depth in the initial template to obtain a target template, wherein the stacking depth represents a threshold value of the number of waveforms allowed to exist in the template pixel points.

[0078] The template pixel point may refer to the pixel point of the template. The waveform quantity threshold may refer to the quantity threshold of the superimposed waveform.

[0079] Specifically, the template pixels may correspond to the oscilloscope pixels. Figure 1 Generally, it is an image formed by the superposition of multiple waveform images. The waveform passing through a certain pixel in the eye diagram can be superimposed. The superposition depth may refer to the maximum value of the superimposed waveform allowed to exist in the template pixel before the abnormal waveform response is triggered. The area contained in the initial template can be considered to be composed of many pixels. A superposition depth can be set for each pixel. The density of the template pixels is related to the resolution of the template. Generally, the higher the resolution of the template, the higher the detection accuracy of the template. The superposition depth can be set at the pixel points of the initial template. The specific value of the superposition depth can be set according to actual needs, and can be set manually or automatically by a preset program. The superposition depth is generally a positive integer greater than 0. According to actual needs, the superposition depth can also be set to 0. The initial template with the superposition depth set can be called the target template.

[0080] S208, using the target template to detect the waveform in the eye diagram data, and determining an abnormal waveform detection result of the eye diagram data.

[0081] The abnormal waveform detection result may refer to a detection result related to an abnormal waveform in an eye diagram.

[0082] Specifically, the target template is used to detect the waveform in the eye diagram data. In abnormal waveform detection, generally, only when the number of waveforms at a pixel point in the regional template exceeds the superposition depth corresponding to the pixel point, will the response of detecting the abnormal waveform be triggered, and it is determined that an abnormal waveform has appeared at the pixel point. Of course, in some special cases, other trigger mechanisms can also be added, such as setting a certain response mechanism to be triggered when the number of waveforms detected at a certain pixel point is greater than 0. Then the specific information of the abnormal waveform is detected, and the specific information may include the position, occurrence time, waveform shape, quantity and other information of the abnormal waveform in the eye diagram. Whether an abnormal waveform exists and the specific information of the abnormal waveform can be determined as the abnormal waveform detection result.

[0083] In the above-mentioned eye diagram abnormal waveform detection method, by setting the overlay depth in the eye diagram template, the pixel points of the eye diagram template have a threshold for the response to the abnormal waveform, so that the eye diagram template can detect the abnormal waveform while not being too sensitive, and can solve the problem of difficulty in accurately detecting sporadic signals in the time domain. The design of the overlay depth allows the eye diagram template to have room for adjustment in terms of sensitivity, thereby meeting the demand for accurate detection of sporadic signals in the time domain.

[0084] In one embodiment, the method further comprises:

[0085] When the abnormal waveform detection result includes the presence of an abnormal waveform, the type of the abnormal waveform is determined according to the abnormal waveform detection result to obtain a type determination result.

[0086] Specifically, when the abnormal waveform detection result includes the presence of an abnormal waveform, the abnormal waveform can be classified according to actual needs based on the specific information in the abnormal waveform detection result. For example, the abnormal waveform can be classified according to the position, appearance time, waveform shape, or quantity of the abnormal waveform in the eye diagram. A plurality of abnormal waveform types can be preset, and when an abnormal waveform appears, the abnormal waveform is classified into a corresponding type. The type of the abnormal waveform is determined to facilitate subsequent processing of the abnormal waveform.

[0087] In this embodiment, by determining the type of the abnormal waveform according to the abnormal waveform detection result and obtaining a type determination result, the abnormal waveform can be more effectively classified to facilitate subsequent processing.

[0088] In one embodiment, the method further comprises:

[0089] When the abnormal waveform detection result includes the presence of an abnormal waveform, corresponding abnormal processing is performed according to the abnormal waveform detection result, and the abnormal processing includes at least one of the following processing: stop upon failure, save current frame, buzzer, screenshot, no response.

[0090] Among them, stop on failure may mean that the program stops running. Save current frame may mean saving a set of waveform data currently analyzed. Buzzer may mean that the buzzer sounds. Screenshot may mean taking a screenshot of the screen and saving it. No response may mean not performing any exception processing.

[0091] Specifically, when the abnormal waveform detection result includes the presence of an abnormal waveform, corresponding abnormal processing is performed according to the abnormal waveform detection result. The abnormal processing includes at least one of the following processing: stop upon failure, save current frame, buzzer, screenshot, no response. The abnormal processing is a processing content set in advance. In addition to stop upon failure, save current frame, buzzer, screenshot, no response, other processing contents can also be set as needed.

[0092] In this embodiment, by setting the processing content after detecting an abnormal waveform, it is possible to automatically process the abnormal waveform at the first time when it is detected, and achieve various processing effects actually needed, such as stopping the program, saving data, issuing an alarm, etc.

[0093] In one embodiment, Figure 3 As shown, the method also includes:

[0094] S302, acquiring time data and voltage data.

[0095] S304: Draw a target area in the initial template according to the time data and the voltage data to obtain a region template.

[0096] S306, setting a stacking depth in the region template to obtain a target template, wherein an edge stacking depth of the target template is greater than an internal stacking depth.

[0097] Among them, time data may refer to waveform time data related to detecting abnormal waveforms. Voltage data may refer to waveform voltage data related to detecting abnormal waveforms. Edge stacking depth may refer to the stacking depth of pixel points in the edge area of ​​the target template. Internal stacking depth may refer to the stacking depth of pixel points in the target area. Edge area may refer to the area inside the area where the target template is located except the target area.

[0098] Specifically, both the time data and the voltage data can be set according to actual needs. The time data can be used to determine the horizontal coordinate of a point on the initial template. The voltage data can be used to determine the vertical coordinate of a point on the initial template. According to the time data and the voltage data, the coordinates of some points on the initial template can be determined. According to the coordinates of the some points, a target area with a determined position, size and shape can be determined. The target area is included in the area where the initial template is located. The shape of the target area can be the same as that of the initial template, or it can be different from the shape of the initial template. The initial template after drawing the target area can be called an area template. The area template after setting the overlay depth can be called a target template. Due to the existence of the target area, the area template is divided into a target area and an edge area. When setting the overlay depth, the edge overlay depth is made greater than the internal overlay depth, even if the threshold of the trigger response of the edge area of ​​the target template is greater than the threshold of the trigger response of the target area, which is conducive to solving the problem that the template edge response is too sensitive when the eye diagram template detects abnormal waveforms.

[0099] In this embodiment, by drawing the target area in the initial template, the area where the template is located is divided into an edge area and a target area, and the overlay depth of the edge area is set greater than the overlay depth of the target area. This can avoid the problem of the template edge being too sensitive when triggering a response, which is conducive to accurately detecting sporadic signals in the time domain.

[0100] In one embodiment, Figure 4 As shown in the figure, an exemplary target template is provided. The area surrounded by the outer hexagon in the figure is the area where the target template is located, which is also the area where the initial template is located. The area surrounded by the inner hexagon is the target area. The numbers in the figure are the stacking depths, and each number corresponds to a pixel. The values ​​of some stacking depths in the figure are large, indicating that the corresponding pixels are easily affected by noise or jitter.

[0101] In one embodiment, the initial template includes a loaded template or a drawn template.

[0102] The loaded template may refer to a preset template or an automatically generated template. The drawn template may refer to a new template drawn according to usage requirements.

[0103] Specifically, the system or software may provide a preset template, which has a certain degree of versatility. When performing abnormal waveform detection, if a new template does not need to be drawn, the preset template can be directly loaded, or the program can automatically generate a template based on information such as the eye height and eye width of the eye diagram. Figure 5As shown, an eye diagram template composed of rectangles, triangles and hexagons is automatically generated by the program. According to actual use needs, a new template can also be drawn or a new template can be obtained by modifying the loaded template. The drawn template can have any desired shape.

[0104] In this embodiment, by making the initial template include a loaded template or a drawn template, various usage requirements for the template can be met, which is conducive to achieving the beneficial effect of accurately detecting sporadic signals in the time domain.

[0105] In one embodiment, the type determination result includes:

[0106] When the waveform in the eye diagram data collides with or penetrates the peripheral template in the target template, the type of the abnormal waveform is determined to be a signal excess amplitude.

[0107] When the waveform in the eye diagram data collides with the internal template in the target template, it is determined that the type of the abnormal waveform is excessive jitter.

[0108] When the waveform in the eye diagram data passes through the internal template in the target template, it is determined that the type of the abnormal waveform is a clock error.

[0109] The peripheral template may refer to a template at the top of the eye diagram or a template at the bottom of the eye diagram, and the internal template may refer to a template inside the eye diagram.

[0110] Specifically, for example Figure 6 As shown, the upper rectangle in the figure belongs to the template at the top of the eye diagram, the lower rectangle in the figure belongs to the template at the bottom of the eye diagram, and the middle rectangle in the figure belongs to the template inside the eye diagram. According to the location of the abnormal waveform, the abnormal waveform is divided into three types: signal over-amplitude, excessive jitter, and clock error. When the waveform in the eye diagram data collides with or penetrates the peripheral template in the target template, the type of the abnormal waveform is judged to be signal over-amplitude. When the waveform in the eye diagram data collides with the internal template in the target template, the type of the abnormal waveform is judged to be excessive jitter. When the waveform in the eye diagram data penetrates the internal template in the target template, the type of the abnormal waveform is judged to be a clock error. For example, when there is Figure 7 In the situation shown, it can be determined that the type of the abnormal waveform is signal over-amplitude.

[0111] In this embodiment, by classifying abnormal waveforms into three types: signal over-amplitude, excessive jitter, and clock error, the abnormal waveforms are automatically classified into corresponding types according to their locations, thereby achieving the beneficial effect of quickly and automatically completing the classification of abnormal waveforms and determining the location characteristics of the abnormal waveforms.

[0112] In one embodiment, a method for detecting abnormal eye diagram waveform is provided, the method comprising:

[0113] Obtain eye diagram data, abnormal waveform features, time data, and voltage data. Set an initial template according to the abnormal waveform features or custom requirements. Draw a target area in the initial template according to the time data and the voltage data to obtain a region template. Set an overlay depth in the region template to obtain a target template, wherein the edge overlay depth of the target template is greater than the internal overlay depth. Use the target template to detect the waveform in the eye diagram data to determine the abnormal waveform detection result of the eye diagram data.

[0114] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0115] Based on the same inventive concept, the embodiment of the present disclosure also provides an eye diagram abnormal waveform detection device for implementing the above-mentioned eye diagram abnormal waveform detection method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in one or more embodiments of the eye diagram abnormal waveform detection device provided below can refer to the limitations of the eye diagram abnormal waveform detection method above, and will not be repeated here.

[0116] Based on the description of the form page display method embodiment described above, the present disclosure also provides a form page display device. The device may include a system (including a distributed system), software (application), module, component, server, client, etc. using the method described in the embodiment of this specification and a device combined with necessary implementation hardware. Based on the same innovative concept, the device in one or more embodiments provided by the embodiment of the present disclosure is as described in the following embodiments. Since the implementation scheme and method of the device to solve the problem are similar, the implementation of the specific device in the embodiment of this specification can refer to the implementation of the aforementioned method, and the repetitions will not be repeated. As used below, the term "unit" or "module" can implement a combination of software and / or hardware of predetermined functions. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0117] In one embodiment, Figure 8 As shown, an eye diagram abnormal waveform detection device 800 is provided, comprising: a first data acquisition module 802, an initial template module 804, a target template module 806 and a detection module 808, wherein:

[0118] The first data acquisition module 802 is used to acquire eye diagram data and abnormal waveform characteristics.

[0119] The initial template module 804 is used to set the initial template according to the abnormal waveform characteristics or customized requirements.

[0120] The target template module 806 is used to set the stacking depth in the initial template to obtain the target template, and the stacking depth represents the threshold value of the number of waveforms allowed to exist in the template pixel points.

[0121] The detection module 808 is used to detect the waveform in the eye diagram data using the target template to determine the abnormal waveform detection result of the eye diagram data.

[0122] In one embodiment, the apparatus further comprises:

[0123] The type judgment module is used to judge the type of the abnormal waveform according to the abnormal waveform detection result when the abnormal waveform detection result includes the existence of an abnormal waveform, so as to obtain a type judgment result.

[0124] In one embodiment, the apparatus further comprises:

[0125] The exception handling module is used to perform corresponding exception handling according to the abnormal waveform detection result when the abnormal waveform detection result includes the existence of an abnormal waveform. The exception handling includes at least one of the following processing: stop upon failure, save current frame, buzzer, screenshot, and no response.

[0126] In one embodiment, Fig. 9 As shown, the device also includes:

[0127] The second data acquisition module 902 is used to acquire time data and voltage data.

[0128] The area template module 904 is used to draw a target area in the initial template according to the time data and the voltage data to obtain an area template.

[0129] The target template module 806 is used to set the stacking depth in the region template to obtain a target template, wherein the edge stacking depth of the target template is greater than the internal stacking depth.

[0130] In one embodiment, the type determination module is used to:

[0131] When the waveform in the eye diagram data collides with or penetrates the peripheral template in the target template, the type of the abnormal waveform is determined to be a signal excess amplitude.

[0132] When the waveform in the eye diagram data collides with the internal template in the target template, it is determined that the type of the abnormal waveform is excessive jitter.

[0133] When the waveform in the eye diagram data passes through the internal template in the target template, it is determined that the type of the abnormal waveform is a clock error.

[0134] Each module in the above-mentioned eye diagram abnormal waveform detection device can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0135] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig.10 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store eye diagram data and eye diagram related data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for detecting abnormal eye diagram waveforms is implemented.

[0136] Those skilled in the art will understand that Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the scheme of the present disclosure, and does not constitute a limitation on the computer device to which the scheme of the present disclosure is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0137] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0138] Obtain eye diagram data and abnormal waveform characteristics;

[0139] According to the abnormal waveform characteristics or custom requirements, an initial template is set;

[0140] Setting a stacking depth in the initial template to obtain a target template, wherein the stacking depth represents a threshold value of the number of waveforms allowed to exist in the template pixel points;

[0141] The target template is used to detect the waveform in the eye diagram data to determine an abnormal waveform detection result of the eye diagram data.

[0142] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0143] When the abnormal waveform detection result includes the presence of an abnormal waveform, the type of the abnormal waveform is determined according to the abnormal waveform detection result to obtain a type determination result.

[0144] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0145] When the abnormal waveform detection result includes the presence of an abnormal waveform, corresponding abnormal processing is performed according to the abnormal waveform detection result, and the abnormal processing includes at least one of the following processing: stop upon failure, save current frame, buzzer, screenshot, no response.

[0146] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0147] Get time data and voltage data;

[0148] Drawing a target area in the initial template according to the time data and the voltage data to obtain an area template;

[0149] The stacking depth is set in the region template to obtain a target template, wherein the edge stacking depth of the target template is greater than the internal stacking depth.

[0150] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0151] Get time data and voltage data;

[0152] Drawing a target area in the initial template according to the time data and the voltage data to obtain an area template;

[0153] The stacking depth is set in the region template to obtain a target template, wherein the edge stacking depth of the target template is greater than the internal stacking depth.

[0154] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0155] When the waveform in the eye diagram data collides with or penetrates the peripheral template in the target template, determining the type of the abnormal waveform is a signal over-amplitude;

[0156] When the waveform in the eye diagram data collides with the internal template in the target template, determining that the type of the abnormal waveform is excessive jitter;

[0157] When the waveform in the eye diagram data passes through the internal template in the target template, it is determined that the type of the abnormal waveform is a clock error.

[0158] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0159] Obtain eye diagram data and abnormal waveform characteristics;

[0160] According to the abnormal waveform characteristics or custom requirements, an initial template is set;

[0161] Setting a stacking depth in the initial template to obtain a target template, wherein the stacking depth represents a threshold value of the number of waveforms allowed to exist in the template pixel points;

[0162] The target template is used to detect the waveform in the eye diagram data to determine an abnormal waveform detection result of the eye diagram data.

[0163] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0164] When the abnormal waveform detection result includes the presence of an abnormal waveform, the type of the abnormal waveform is determined according to the abnormal waveform detection result to obtain a type determination result.

[0165] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0166] When the abnormal waveform detection result includes the presence of an abnormal waveform, corresponding abnormal processing is performed according to the abnormal waveform detection result, and the abnormal processing includes at least one of the following processing: stop upon failure, save current frame, buzzer, screenshot, no response.

[0167] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0168] Get time data and voltage data;

[0169] Drawing a target area in the initial template according to the time data and the voltage data to obtain an area template;

[0170] The stacking depth is set in the region template to obtain a target template, wherein the edge stacking depth of the target template is greater than the internal stacking depth.

[0171] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0172] When the waveform in the eye diagram data collides with or penetrates the peripheral template in the target template, determining the type of the abnormal waveform is a signal over-amplitude;

[0173] When the waveform in the eye diagram data collides with the internal template in the target template, determining that the type of the abnormal waveform is excessive jitter;

[0174] When the waveform in the eye diagram data passes through the internal template in the target template, it is determined that the type of the abnormal waveform is a clock error.

[0175] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0176] Obtain eye diagram data and abnormal waveform characteristics;

[0177] According to the abnormal waveform characteristics or custom requirements, an initial template is set;

[0178] Setting a stacking depth in the initial template to obtain a target template, wherein the stacking depth represents a threshold value of the number of waveforms allowed to exist in the template pixel points;

[0179] The target template is used to detect the waveform in the eye diagram data to determine an abnormal waveform detection result of the eye diagram data.

[0180] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0181] When the abnormal waveform detection result includes the presence of an abnormal waveform, the type of the abnormal waveform is determined according to the abnormal waveform detection result to obtain a type determination result.

[0182] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0183] When the abnormal waveform detection result includes the presence of an abnormal waveform, corresponding abnormal processing is performed according to the abnormal waveform detection result, and the abnormal processing includes at least one of the following processing: stop upon failure, save current frame, buzzer, screenshot, no response.

[0184] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0185] Get time data and voltage data;

[0186] Drawing a target area in the initial template according to the time data and the voltage data to obtain an area template;

[0187] The stacking depth is set in the region template to obtain a target template, wherein the edge stacking depth of the target template is greater than the internal stacking depth.

[0188] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0189] When the waveform in the eye diagram data collides with or penetrates the peripheral template in the target template, determining the type of the abnormal waveform is a signal over-amplitude;

[0190] When the waveform in the eye diagram data collides with the internal template in the target template, determining that the type of the abnormal waveform is excessive jitter;

[0191] When the waveform in the eye diagram data passes through the internal template in the target template, it is determined that the type of the abnormal waveform is a clock error.

[0192] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties.

[0193] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided by the present disclosure can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided by the present disclosure may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited thereto. The processor involved in each embodiment provided by the present disclosure may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited thereto.

[0194] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0195] The above-described embodiments only express several implementation methods of the present disclosure, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present disclosure, and these all belong to the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the attached claims.

Claims

1. A method for detecting abnormal eye diagram waveform, characterized in that: The method comprises: Obtain eye diagram data and abnormal waveform characteristics; According to the abnormal waveform characteristics or custom requirements, an initial template is set; Get time data and voltage data; Drawing a target area in the initial template according to the time data and the voltage data to obtain an area template; Setting a stacking depth in the area template to obtain a target template, wherein the edge stacking depth of the target template is greater than the internal stacking depth, and the stacking depth represents a threshold value of the number of waveforms allowed to exist in the template pixel points; The target template is used to detect the waveform in the eye diagram data to determine an abnormal waveform detection result of the eye diagram data.

2. The method according to claim 1, characterized in that The method further comprises: When the abnormal waveform detection result includes the presence of an abnormal waveform, the type of the abnormal waveform is determined according to the abnormal waveform detection result to obtain a type determination result.

3. The method according to claim 1, characterized in that The method further comprises: When the abnormal waveform detection result includes the presence of an abnormal waveform, a corresponding abnormal processing is performed, and the abnormal processing includes at least one of the following processing: stop upon failure, save current frame, buzzer, screenshot, no response.

4. The method according to claim 1, characterized in that: The initial template includes a loaded template or a drawn template.

5. The method according to claim 2, characterized in that: The type determination result includes: When the waveform in the eye diagram data collides with or penetrates the peripheral template in the target template, determining the type of the abnormal waveform is a signal over-amplitude; When the waveform in the eye diagram data collides with the internal template in the target template, determining that the type of the abnormal waveform is excessive jitter; When the waveform in the eye diagram data passes through the internal template in the target template, it is determined that the type of the abnormal waveform is a clock error.

6. A device for capturing abnormal eye diagram waveforms, characterized in that: The device comprises: A first data acquisition module, used to acquire eye diagram data and abnormal waveform characteristics; An initial template module, used to set an initial template according to the abnormal waveform characteristics or custom requirements; A second data acquisition module is used to acquire time data and voltage data; a region template module is used to draw a target region in the initial template according to the time data and the voltage data to obtain a region template; a target template module is used to set an overlay depth in the region template to obtain a target template, wherein the edge overlay depth of the target template is greater than the internal overlay depth, and the overlay depth represents a threshold value of the number of waveforms allowed to exist in the template pixel points; The detection module is used to detect the waveform in the eye diagram data using the target template to determine the abnormal waveform detection result of the eye diagram data.

7. The device according to claim 6, characterized in that The device also includes: The type judgment module is used to judge the type of the abnormal waveform according to the abnormal waveform detection result when the abnormal waveform detection result includes the existence of an abnormal waveform, so as to obtain a type judgment result.

8. The device according to claim 6, characterized in that The device also includes: The exception handling module is used to perform corresponding exception handling according to the abnormal waveform detection result when the abnormal waveform detection result includes the existence of an abnormal waveform. The exception handling includes at least one of the following processing: stop upon failure, save current frame, buzzer, screenshot, and no response.

9. The device according to claim 7, characterized in that The type determination module is used for: When the waveform in the eye diagram data collides with or penetrates the peripheral template in the target template, determining the type of the abnormal waveform is a signal over-amplitude; When the waveform in the eye diagram data collides with the internal template in the target template, determining that the type of the abnormal waveform is excessive jitter; When the waveform in the eye diagram data passes through the internal template in the target template, it is determined that the type of the abnormal waveform is a clock error.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

12. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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