An abnormality diagnosis method, device, electronic device, and storage medium

Abstract

Embodiments of the present application provide an exception diagnosis method and device, electronic equipment and storage medium. The exception diagnosis method is applied to the electronic equipment, and the electronic equipment is installed with upper software providing services for a device to be diagnosed. The exception diagnosis method comprises: obtaining each event reported by the device to be diagnosed, and obtaining a work log about the device to be diagnosed generated by the upper software; analyzing event information of each event and log content of the work log to obtain an exception message of the device to be diagnosed; and displaying exception message distribution information of the device to be diagnosed according to the exception message. The exception diagnosis method provided by the embodiments of the present application can reduce the difficulty of diagnosing the device to be diagnosed, and improve the efficiency of diagnosing the device to be diagnosed.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to an anomaly diagnosis method, apparatus, electronic device, and storage medium. Background Technology

[0002] During operation, equipment may experience anomalies due to various reasons, such as packet loss, abnormal data packets, abnormal I / O triggering, and device disconnection. In related technologies, the client software used to operate the device under diagnosis can serve as the upper-layer software for that device. When diagnosing anomalies in the device, technicians typically need to examine each log entry in the upper-layer software's logs to identify any abnormal entries and determine the specific anomaly.

[0003] However, during the operation of the device under diagnosis, a large amount of operational logs are typically generated. Due to the large volume of these logs and the difficulty in reading and understanding them, anomaly diagnosis using related technologies is both challenging and inefficient. Summary of the Invention

[0004] The purpose of this application is to provide an anomaly diagnosis method, apparatus, electronic device, and storage medium to reduce the difficulty and improve the efficiency of anomaly diagnosis. The specific technical solution is as follows:

[0005] In a first aspect, embodiments of this application provide an anomaly diagnosis method applied to an electronic device, wherein the electronic device is equipped with upper-layer software that provides services for the device to be diagnosed; the method includes:

[0006] Obtain all events reported by the device under diagnosis, and obtain the work log of the device under diagnosis generated by the upper layer software;

[0007] The event information of each event and the log content of the work log are parsed to obtain the abnormal message of the device to be diagnosed; wherein, the abnormal message includes: abnormal events in each event, and / or, abnormal log entries in the work log; the event information of each event includes: event type and timestamp; the log content of each log entry in the work log includes: log type and system time;

[0008] Based on the abnormal messages, display the distribution information of abnormal messages of the device to be diagnosed.

[0009] Optionally, in one specific implementation, parsing the event information of each event and the log content of the work log to obtain the abnormal message of the device to be diagnosed includes:

[0010] According to each preset cycle, each event reported by the device under diagnosis and each newly added log entry in the work log within the preset cycle are read, and each read event and each log entry are parsed to obtain the abnormal message of the device under diagnosis.

[0011] Optionally, in one specific implementation, displaying the distribution information of abnormal messages of the device to be diagnosed based on the abnormal messages includes:

[0012] In a first coordinate system with system time as the first coordinate axis and the number of message entries as the second coordinate axis, a polyline connecting each target point is displayed, and a specified point among the target points is highlighted.

[0013] For each target point, the coordinates of the target point on the first coordinate axis are: the time period represented by the target point; the coordinates of the target point on the second coordinate axis are: the sum of the number of events reported by the device to be diagnosed and the number of newly added log entries in the work log within the preset period represented by the target point; the designated point is: the target point corresponding to the preset period in which abnormal messages exist.

[0014] Optionally, in one specific implementation, the method further includes:

[0015] In a second coordinate system with system time as the first coordinate axis and message type as the second coordinate axis, display the distribution points of each event and / or each log.

[0016] Specifically, for each event distribution point, the coordinate of the event distribution point on the first coordinate axis is: the system time corresponding to the timestamp of the event represented by the event distribution point; the coordinate of the event distribution point on the second coordinate axis is: the event type of the event represented by the event distribution point; for each log distribution point, the coordinate of the log distribution point on the first coordinate axis is: the system time of the log entry represented by the log distribution point; the coordinate of the log distribution point on the second coordinate axis is: the log type of the log entry represented by the log distribution point.

[0017] Optionally, in one specific implementation, the event includes an I / O event, and the method further includes:

[0018] Based on the various IO events reported by the device under diagnosis, display the IO waveform diagrams of each IO channel of the device under diagnosis, and highlight abnormal waveforms in each IO waveform diagram; wherein, the IO waveform diagram of each IO channel is plotted with system time as the first coordinate axis.

[0019] Optionally, in one specific implementation, the method further includes:

[0020] After each event is acquired, a specified entry about that event is added to a preset table;

[0021] After each log entry is obtained, a specified entry about that log entry is added to the preset table;

[0022] The specified entry includes at least one of system time, type, device identifier, and specific content.

[0023] Secondly, embodiments of this application provide an anomaly diagnostic device applied to an electronic device, wherein the electronic device is equipped with upper-layer software that provides services to the device under diagnosis; the device includes:

[0024] The event acquisition module is used to acquire various events reported by the device under diagnosis and to acquire the work logs about the device under diagnosis generated by the upper-layer software.

[0025] The information parsing module is used to parse the event information of each event and the log content of the work log to obtain the abnormal message of the device to be diagnosed; wherein, the abnormal message includes: abnormal events in each event, and / or, abnormal log entries in the work log; the event information of each event includes: event type and timestamp; the log content of each log entry in the work log includes: log type and system time;

[0026] The information display module is used to display the distribution information of abnormal messages of the device to be diagnosed based on the abnormal messages.

[0027] Optionally, in one specific implementation, the information parsing module is specifically used for:

[0028] According to each preset cycle, each event reported by the device under diagnosis and each newly added log entry in the work log within the preset cycle are read, and each event and log entry read are parsed to obtain the abnormal message of the device under diagnosis.

[0029] Optionally, in one specific implementation, the information display module is specifically used for:

[0030] In a first coordinate system with system time as the first coordinate axis and the number of message entries as the second coordinate axis, a polyline connecting each target point is displayed, and a specified point among the target points is highlighted.

[0031] Wherein, for each target point, the coordinates of the target point on the first coordinate axis are: the time period represented by the target point; the coordinates of the target point on the second coordinate axis are: the sum of the number of events reported by the device to be diagnosed and the number of newly added log entries in the work log within the preset period represented by the target point; the designated point is: the target point corresponding to the preset period in which abnormal messages exist;

[0032] Optionally, in one specific implementation, the apparatus further includes:

[0033] The distribution point display module is used to display the distribution points of each event and / or each log in a second coordinate system with system time as the first coordinate axis and message type as the second coordinate axis.

[0034] Specifically, for each event distribution point, its coordinate on the first coordinate axis is the system time corresponding to the timestamp of the event represented by that event distribution point; its coordinate on the second coordinate axis is the event type of the event represented by that event distribution point; for each log distribution point, its coordinate on the first coordinate axis is the system time of the log entry represented by that log distribution point; its coordinate on the second coordinate axis is the log type of the log entry represented by that log distribution point.

[0035] Optionally, in one specific implementation, the event includes an I / O event, and the device further includes:

[0036] The waveform display module is used to display the IO waveforms of each IO channel of the device under diagnosis based on the IO events reported by the device under diagnosis, and to highlight abnormal waveforms in each IO waveform; wherein, the IO waveform of each IO channel is plotted with system time as the first coordinate axis;

[0037] Optionally, in one specific implementation, the apparatus further includes:

[0038] The event entry addition module is used to add a specified entry about each event to a preset table after each event is acquired.

[0039] The log entry adding module is used to add a specified entry about each log entry to the preset table after each log entry is obtained.

[0040] The specified entry includes at least one of system time, type, device identifier, and specific content.

[0041] Thirdly, embodiments of this application provide an electronic device, including:

[0042] Memory, used to store computer programs;

[0043] The processor, when executing a program stored in memory, implements any of the above-described anomaly diagnosis methods.

[0044] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements any of the above-described anomaly diagnosis methods.

[0045] This application also provides a computer program product containing instructions that, when run on a computer, cause the computer to perform any of the above-described anomaly diagnosis methods.

[0046] Beneficial effects of the embodiments in this application:

[0047] As can be seen from the above, by applying the solution provided in this application embodiment, an upper-layer software that provides services to the device under diagnosis can be installed on the electronic device. The device under diagnosis can report various events occurring within it to the electronic device, and the upper-layer software can generate logs about the device under diagnosis. During defect diagnosis, the electronic device can obtain the various events reported by the device under diagnosis and the working logs about the device under diagnosis generated by the upper-layer software. The event information of each event may include: event type and timestamp; the log content of each log entry in the working log may include: log type and system time; abnormal events in each event, and / or, abnormal log entries in the working log can be used as abnormal messages. The electronic device can parse the event information of each obtained event and the log content of the obtained working log to obtain the abnormal messages of the device under diagnosis, and then, based on the abnormal messages, display the abnormal message distribution information of the device under diagnosis.

[0048] Therefore, since abnormal information can include abnormal log entries in the work log, technicians no longer need to check each log entry in the work log to identify the abnormal log entries when performing abnormal diagnosis on the device under diagnosis. Instead, they can more intuitively and directly identify the abnormal log entries in each log entry by looking at the abnormal message distribution information of the device under diagnosis displayed by the electronic device. It is evident that the solution provided in this application can reduce the difficulty and improve the efficiency of abnormal diagnosis for the device under diagnosis.

[0049] Furthermore, since the abnormal information can also include abnormal events from various events reported by the device under diagnosis, technicians can identify abnormal log entries and abnormal events from various log entries and events by using the abnormal message distribution information displayed by the electronic device. Based on these abnormal log entries and events, technicians can then perform anomaly diagnosis on the device. Therefore, compared to determining the abnormality of the device based on abnormal log entries, the solution provided in this application can improve the accuracy of anomaly diagnosis.

[0050] Of course, implementing any product or method of this application does not necessarily require achieving all of the advantages described above at the same time. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other embodiments can be obtained based on these drawings.

[0052] Figure 1 A flowchart illustrating an anomaly diagnosis method provided in an embodiment of this application;

[0053] Figure 2 Another flowchart illustrating the anomaly diagnosis method provided in the embodiments of this application;

[0054] Figure 3 This is another flowchart illustrating the anomaly diagnosis method provided in the embodiments of this application;

[0055] Figure 4 A schematic diagram of a polyline connecting various target points in a first coordinate system, provided as an embodiment of this application;

[0056] Figure 5 A schematic diagram of log distribution points in a second coordinate system provided in an embodiment of this application;

[0057] Figure 6 The IO waveform diagrams of each IO channel of a data acquisition card and a camera provided in this application embodiment;

[0058] Figure 7 This application provides an example of highlighting a specified log entry in a preset table as shown in Table 1.

[0059] Figure 8 This is a schematic diagram of the structure of an abnormality diagnosis device provided in an embodiment of this application;

[0060] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0061] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art based on this application are within the scope of protection of this application.

[0062] In related technologies, the client software used to operate the device under diagnosis can be used as the upper-level software of the device under diagnosis. When performing abnormal diagnosis on the device under diagnosis, technicians usually need to check each log entry in the work log of the device under diagnosis recorded by the upper-level software of the device under diagnosis, identify the abnormal log entries in each log entry, and then determine the abnormal situation of the device under diagnosis based on the abnormal log entries.

[0063] However, during the operation of the device under diagnosis, a large amount of operational logs are typically generated. Due to the large volume of these logs and the difficulty in reading and understanding them, anomaly diagnosis using related technologies is both challenging and inefficient.

[0064] Based on this, the embodiments of this application provide an anomaly diagnosis method.

[0065] This method is applicable to various scenarios requiring anomaly diagnosis of equipment, such as diagnosing anomalies in independent devices, or detecting defects in devices within a system composed of multiple devices. Therefore, this application does not specifically limit the application scenarios of this method.

[0066] Furthermore, this method can be applied to various electronic devices capable of data processing and equipped with upper-layer software that provides services to the device under diagnosis, such as mobile phones, laptops, and desktop computers. The electronic device can be a standalone device or a cluster of multiple electronic devices; this embodiment of the invention does not specifically limit its use, and will be referred to as an electronic device.

[0067] One of the abnormality diagnosis methods provided in this application embodiment may include the following steps:

[0068] Obtain all events reported by the device under diagnosis, and obtain the work log of the device under diagnosis generated by the upper layer software;

[0069] The event information of each event and the log content of the work log are parsed to obtain the abnormal message of the device to be diagnosed; wherein, the abnormal message includes: abnormal events in each event, and / or, abnormal log entries in the work log; the event information of each event includes: event type and timestamp; the log content of each log entry in the work log includes: log type and system time;

[0070] Based on the abnormal messages, display the distribution information of abnormal messages of the device to be diagnosed.

[0071] As can be seen from the above, by applying the solution provided in this application embodiment, an upper-layer software that provides services to the device under diagnosis can be installed on the electronic device. The device under diagnosis can report various events occurring within it to the electronic device, and the upper-layer software can generate logs about the device under diagnosis. During defect diagnosis, the electronic device can obtain the various events reported by the device under diagnosis and the working logs about the device under diagnosis generated by the upper-layer software. The event information of each event may include: event type and timestamp; the log content of each log entry in the working log may include: log type and system time; abnormal events in each event, and / or, abnormal log entries in the working log can be used as abnormal messages. The electronic device can parse the event information of each obtained event and the log content of the obtained working log to obtain the abnormal messages of the device under diagnosis, and then, based on the abnormal messages, display the abnormal message distribution information of the device under diagnosis.

[0072] Therefore, since abnormal information can include abnormal log entries in the work log, technicians no longer need to check each log entry in the work log to identify the abnormal log entries when performing abnormal diagnosis on the device under diagnosis. Instead, they can more intuitively and directly identify the abnormal log entries in each log entry by looking at the abnormal message distribution information of the device under diagnosis displayed by the electronic device. It is evident that the solution provided in this application can reduce the difficulty and improve the efficiency of abnormal diagnosis for the device under diagnosis.

[0073] Furthermore, since the abnormal information can also include abnormal events from various events reported by the device under diagnosis, technicians can identify abnormal log entries and abnormal events from various log entries and events by using the abnormal message distribution information displayed by the electronic device. Based on these abnormal log entries and events, technicians can then perform anomaly diagnosis on the device. Therefore, compared to determining the abnormality of the device based on abnormal log entries, the solution provided in this application can improve the accuracy of anomaly diagnosis.

[0074] The following, with reference to the accompanying drawings, provides a detailed description of an abnormality diagnosis method provided in an embodiment of this application.

[0075] Figure 1 This is a schematic flowchart of an anomaly diagnosis method provided in an embodiment of this application, such as... Figure 1 As shown, the method may include the following steps S101-S103.

[0076] S101: Obtain all events reported by the device under diagnosis and obtain the work logs about the device under diagnosis generated by the upper-layer software.

[0077] Users can operate the device under diagnosis through client software, such as controlling the device to perform specified actions. This client software can act as upper-layer software for the device under diagnosis. This upper-layer software can be installed on the device under diagnosis itself or on other devices that communicate with it. To enable the electronic device to provide services to the device under diagnosis, upper-layer software providing these services can be installed on the electronic device.

[0078] For example, the device to be diagnosed can be an industrial production device. In order for the electronic device to control various industrial production devices, upper-level software that can control various industrial production devices can be installed on the electronic device.

[0079] For example, the electronic device can be an industrial control computer, and the device to be diagnosed can be an industrial camera and an image acquisition card. In order for the industrial control computer to control the industrial camera and acquire images captured by the industrial camera through the image acquisition card, upper-level software for implementing the above operations can be installed on the industrial control computer.

[0080] Optionally, the aforementioned upper-layer software can be a software development kit (SDK) used to develop the device to be diagnosed.

[0081] The device under test can send various events occurring within it to the electronic device. The upper-layer software installed on the electronic device that provides services to the device under test can generate a work log about the device under test based on the services it provides. When performing anomaly detection on the device under test, the electronic device can obtain the various events reported by the device under test and the work log about the device under test generated by the upper-layer software.

[0082] The format of events reported by the device under diagnosis to the electronic device, and the format of the work logs generated by the upper-layer software about the device under diagnosis, can be set by those skilled in the art according to the specific application. This application embodiment does not impose specific limitations.

[0083] Optionally, the event information for each event reported by the device under diagnosis to the electronic device may include the event's timestamp, event type, event channel, and event description.

[0084] Optionally, the event types reported by the device under diagnosis to the electronic device can be divided into regular events, abnormal events, and IO (Input / Output) events. The event channel can be an IO channel for IO events, and the timestamp can be determined based on the startup time of the device under diagnosis.

[0085] For example, if the device to be diagnosed receives image data A through IO channel 1 10 seconds after startup, the timestamp in the event information of the event reported by the device to the electronic device can be 10 seconds, the event type can be IO event, the event channel can be IO channel 1, and the event description can be receiving image data A.

[0086] Optionally, the log content for each log entry in the working log of the device to be diagnosed generated by the upper-layer software may include system time, log type, code location, log information, and solution.

[0087] Optionally, the above log types can be divided into debug logs, regular logs, warning logs, and error logs. The above solutions can be solutions for device anomalies corresponding to error logs. The above system time can be the local time when the log entry was generated.

[0088] In addition, the time for the electronic device to acquire the various events reported by the device under diagnosis, and the time for acquiring the work logs about the device under diagnosis generated by the upper-layer software, can be set by those skilled in the art according to the specific application situation, and this application embodiment does not impose specific limitations.

[0089] Optionally, the device under test can report various events occurring within it to the electronic device in real time, and the electronic device can obtain the various events reported by the device under test in real time.

[0090] Optionally, when the electronic device begins to perform abnormal diagnosis on the device under diagnosis, it can send an event reporting command to the device under diagnosis to prompt the device under diagnosis to report events. Then, after receiving the event reporting command, the device under diagnosis can respond to the event reporting command and report the various events that occurred inside it to the electronic device in real time. The electronic device can obtain the various events reported by the device under diagnosis in real time.

[0091] Optionally, the device under test can also report various events that occur within it to the electronic device at a specified period, and then the electronic device can obtain the various events reported by the device under test at a specified period.

[0092] Optionally, the electronic device can acquire working logs about the device under diagnosis generated by the upper-level software in real time.

[0093] Optionally, the electronic device can acquire the working logs about the device to be diagnosed generated by the upper-layer software according to the target cycle.

[0094] Optionally, the electronic device may obtain the working logs about the device under diagnosis generated by the upper-layer software within a specified time range when it begins to perform abnormal diagnosis on the device under diagnosis.

[0095] Optionally, the electronic device can obtain various events reported by the device under diagnosis and the work logs generated by the upper-layer software about the device under diagnosis through multi-process read-only mode, so as not to affect the normal operation of the device under diagnosis and its upper-layer software while performing abnormal diagnosis on the device under diagnosis.

[0096] S102: Parse the event information and log content of each event to obtain the abnormal message of the device to be diagnosed.

[0097] The exception messages include: exception events in each event, and / or exception log entries in the work log; the event information for each event includes: event type and timestamp; the log content for each log entry in the work log includes: log type and system time.

[0098] For each event, the event information may include: event type and timestamp; the electronic device parses the event information of each acquired event to identify abnormal events at each time. For each log entry in the work log, the log content of the log entry may include: log type and system time; the electronic device parses the log content of the acquired work log regarding the device under diagnosis to identify abnormal log entries in the work log. Therefore, the abnormal events identified by the electronic device in each event, and / or the abnormal log entries in the work log, can serve as abnormal messages regarding the device under diagnosis.

[0099] Optionally, the above event types may include: normal events and abnormal events; the above log types may include: normal logs, error logs, and warning logs. Furthermore, when parsing the event information of each event, the electronic device can identify events with the event type of abnormal event included in the event information as abnormal events; and when parsing the log content of the work log, it can identify log entries with the log type of error log included in the built-in content as abnormal log entries.

[0100] Optionally, to improve the real-time performance of anomaly diagnosis, the electronic device can read all events reported by the device under diagnosis in real time, and read all newly added log entries in the work log in real time, and perform real-time parsing of each event and log entry to obtain the anomaly message of the device under diagnosis.

[0101] Alternatively, in one specific implementation, such as Figure 2 As shown, step S102 above: parsing the event information of each event and the log content of the work log to obtain the abnormal message of the device to be diagnosed, may include the following step S201.

[0102] S201: According to each preset cycle, read each event reported by the device under diagnosis and each newly added log entry in the work log within the preset cycle, and parse each event and each log entry to obtain the abnormal message of the device under diagnosis.

[0103] The aforementioned preset period can be set by those skilled in the art according to specific application conditions, and this application embodiment does not impose specific limitations.

[0104] For example, the preset period can be 1 second. Then, the electronic device can read each event reported by the device under diagnosis and each new log entry added in the work log within the 1 second after each preset period ends, that is, at each 1-second interval, and parse each event and each log entry to obtain the abnormal message of the device under diagnosis.

[0105] However, the data reading capability of electronic devices can be limited. Therefore, if there are many events reported by the device under diagnosis and many new log entries added to the work log within a preset period, the electronic device may not be able to read all the events reported by the device under diagnosis and all the new log entries added to the work log within that preset period at once. Optionally, the electronic device can read each event from the unparsed events according to a first read quantity, and read each log entry from the unparsed work log according to a second read quantity, according to each preset period.

[0106] The first and second read counts can be set by those skilled in the art according to specific application conditions (such as the data reading capability of electronic devices), and this application embodiment does not impose specific limitations.

[0107] For example, the first read count can be 20, and the second read count can be 10. For a certain preset period, there are 21 unparsed events and 9 unparsed work logs. Therefore, for this preset period, the electronic device can read 20 events from the 21 unparsed events and read the 9 unparsed work logs.

[0108] S103: Based on the abnormal messages, display the distribution information of abnormal messages of the device to be diagnosed.

[0109] After receiving abnormal messages from the device under diagnosis, the electronic device can display the distribution information of the abnormal messages from the device under diagnosis based on the received abnormal messages.

[0110] Optionally, the above-mentioned abnormal message distribution information may include the distribution time and / or the distribution location of the abnormal messages.

[0111] For example, the aforementioned abnormal message distribution information may include the distribution time of the abnormal messages. Furthermore, the electronic device can determine the system time corresponding to the abnormal event in each event based on the timestamp included in the event information of the abnormal events in each event, and use this as the distribution time of the abnormal event in each event; the system time included in the log content of the abnormal log entries in the work log is determined as the distribution time of the abnormal log entries in the work log. Then, the distribution time of the abnormal events in each event, and / or the distribution time of the abnormal log entries in the work log, are displayed as the abnormal message distribution information of the device to be diagnosed.

[0112] For example, the above-mentioned abnormal message distribution information may include the distribution location of the abnormal messages. Then, the electronic device can display the acquired events and work logs, highlight the abnormal events in the displayed events, and highlight the abnormal log entries in the displayed work logs, thereby realizing the display of the distribution location of the abnormal messages of the device to be diagnosed.

[0113] Optionally, the above-mentioned abnormal message distribution information may also include the number of abnormal messages within a preset time period.

[0114] Alternatively, in one specific implementation, such as Figure 3 As shown, corresponding to step S201 above, step S103 above may include the following step S301.

[0115] S301: In a first coordinate system with system time as the first coordinate axis and the number of message entries as the second coordinate axis, display a polyline connecting each target point and highlight a specified point among each target point.

[0116] For each target point, the coordinates of the target point on the first coordinate axis are: the time period represented by the target point; the coordinates of the target point on the second coordinate axis are: the sum of the number of events reported by the device to be diagnosed and the number of new log entries in the work log within the preset period represented by the target point; the designated point is: the target point corresponding to the preset period in which abnormal messages exist.

[0117] In other words, if the abnormal messages of the device under diagnosis are determined according to a preset period, then when displaying the distribution information of the abnormal messages of the device under diagnosis, for each preset period, the coordinates on the first coordinate axis are set as the time of the preset period, and the coordinates on the second coordinate axis are set as the sum of the number of events reported by the device under diagnosis and the number of new log entries added in the work log within the preset period. In a first coordinate system with system time as the first coordinate axis and the number of message entries as the second coordinate axis, target points representing the preset period are determined, and the target points corresponding to the preset periods with abnormal messages are determined as designated points. Then, a polyline connecting each target point is displayed in the first coordinate system, and the designated points among each target point are highlighted. Thus, the polyline connecting each target point and each designated point in the displayed first coordinate system contain the distribution information of the abnormal messages of the device under diagnosis.

[0118] The time for each preset period can be any point in time included within that preset period. For example, the time for each period can be the end time of that period. This application does not specifically limit the time for each preset period.

[0119] For example, when highlighting a specific point among the target points using black dots, a polyline connecting the target points can be displayed in a first coordinate system with system time as the horizontal axis and the number of message entries as the vertical axis, highlighting the specific point among the target points. This can result in the following: Figure 4 The diagram shown.

[0120] Therefore, since abnormal information can include abnormal log entries in the work log, technicians no longer need to check each log entry in the work log to identify the abnormal log entries when performing abnormal diagnosis on the device under diagnosis. Instead, they can more intuitively and directly identify the abnormal log entries in each log entry by looking at the abnormal message distribution information of the device under diagnosis displayed by the electronic device. It is evident that the solution provided in this application can reduce the difficulty and improve the efficiency of abnormal diagnosis for the device under diagnosis.

[0121] Furthermore, since the abnormal information can also include abnormal events from various events reported by the device under diagnosis, technicians can identify abnormal log entries and abnormal events from various log entries and events by using the abnormal message distribution information displayed by the electronic device. Based on these abnormal log entries and events, technicians can then perform anomaly diagnosis on the device. Therefore, compared to determining the abnormality of the device based on abnormal log entries, the solution provided in this application can improve the accuracy of anomaly diagnosis.

[0122] Optionally, in one specific implementation, the anomaly diagnosis method provided in this application embodiment may further include the following step 11.

[0123] Step 11: In a second coordinate system with system time as the first coordinate axis and message type as the second coordinate axis, display the distribution points of each event and / or each log distribution point.

[0124] For each event distribution point, the coordinate of the event distribution point on the first coordinate axis is: the system time corresponding to the timestamp of the event represented by the event distribution point; the coordinate of the event distribution point on the second coordinate axis is: the event type of the event represented by the event distribution point; for each log distribution point, the horizontal coordinate of the log distribution point is: the system time of the log entry represented by the log distribution point; the vertical coordinate of the log distribution point is: the log type of the log entry represented by the log distribution point.

[0125] When performing anomaly diagnosis on the device to be diagnosed, for each acquired event, the system time corresponding to the event's timestamp can be used as the coordinate on the first coordinate axis, and the event type as the coordinate on the second coordinate axis. In a second coordinate system with system time as the first coordinate axis and message type as the second coordinate axis, the event distribution point representing the event can be determined. Similarly, for each log entry in the acquired work log, the system time of the log entry can be used as the coordinate on the first coordinate axis, and the log type as the coordinate on the second coordinate axis. In a second coordinate system with system time as the first coordinate axis and message type as the second coordinate axis, the log distribution point representing the log entry can be determined. Furthermore, each event distribution point and / or each log distribution point can be displayed in the second coordinate system with system time as the first coordinate axis and message type as the second coordinate axis.

[0126] Optionally, the electronic device may respond to a message distribution viewing request for a specified time period by displaying each event distribution point and / or each log distribution point in a second coordinate system with system time as the first coordinate axis and message type as the second coordinate axis.

[0127] For example, log types may include error logs, warning logs, general logs, and debug logs. When an electronic device responds to a request to view the message distribution over a time period from time 1 to time 7, the effect of displaying each log distribution point in a second coordinate system with system time as the first axis and message type as the second axis can be as follows: Figure 5 As shown.

[0128] Optionally, users can send a message distribution viewing request for a specified time period to the electronic device by selecting a specified time period in the first coordinate system mentioned above.

[0129] Optionally, the electronic device may also respond to a request to view the content of a specified event or a specified log entry, and display the specific content of that specified event or log entry.

[0130] For example, such as Figure 5 As shown, a user can send a content viewing request for a specified log entry to an electronic device by moving the mouse cursor to log distribution point A representing that entry, or by clicking on log distribution point A representing that entry. The electronic device can accept the content viewing request and respond to the request by displaying the content in the specified log entry. Figure 5 The system time for the specified log entry is t6, and the log information F for the specified log entry is displayed.

[0131] Optionally, users can also change the time range of the specified time period by dragging the first coordinate axis of the second coordinate system.

[0132] Based on this, technicians can determine the specific distribution of abnormal messages according to the event distribution points and / or log distribution points displayed in the second coordinate system, and determine the abnormality of the device to be diagnosed based on the specific distribution of abnormal messages. Therefore, applying this specific implementation method can further improve the efficiency and accuracy of device anomaly diagnosis.

[0133] Optionally, in one specific implementation, the above-mentioned events may include IO events. Furthermore, the anomaly diagnosis method provided in this application embodiment may also include the following step 21.

[0134] Step 21: Based on the IO events reported by the device under diagnosis, display the IO waveforms of each IO channel of the device under diagnosis, and highlight abnormal waveforms in each IO waveform.

[0135] The IO waveform of each IO channel can be plotted with system time as the first coordinate axis.

[0136] Each I / O event can include information indicating whether it is an input or output event. When diagnosing anomalies in a device, the electronic device can use system time as the primary coordinate axis, with high and low levels representing input and output events respectively. Based on the I / O events reported by the device, the electronic device can determine the I / O waveforms for each I / O channel. For each determined I / O waveform, the electronic device can also identify and highlight any abnormal waveforms within it.

[0137] For example, the device to be diagnosed may include a data acquisition card and a camera. The data acquisition card has I / O channels including channel 1, channel 2, and channel 3, and the camera has I / O channels including channel 4, channel 5, and channel 6. Then, using system time as the first coordinate axis, based on the acquired I / O events reported by the device to be diagnosed, the determined I / O waveforms of each I / O channel of the device to be diagnosed can be as follows: Figure 6 As shown.

[0138] Based on this, by applying this specific implementation method, when technicians perform anomaly diagnosis on the device under diagnosis, they can determine the triggering status of each IO channel of the device under diagnosis based on the IO waveform diagram of each IO channel. Then, the triggering status of each IO channel and the abnormal waveforms highlighted in each IO waveform diagram can be used as the basis for anomaly diagnosis of the device under diagnosis, thereby further improving the efficiency of anomaly diagnosis of the device under diagnosis.

[0139] Optionally, in one specific implementation, the anomaly diagnosis method provided in this application embodiment may further include the following steps 31-32.

[0140] Step 31: After each event is acquired, add a specified entry for that event to the preset table.

[0141] Step 32: After each log entry is obtained, add a specified entry for that log entry to the preset table.

[0142] The specified entries include at least one of system time, type, device identifier, and specific content.

[0143] In other words, when performing anomaly diagnosis on the device under diagnosis, a preset table can be set up. Each time the electronic device acquires an event, a specified entry for that event can be added to the preset table; similarly, each time a log entry is acquired, a specified entry for that log entry can be added to the preset table. Furthermore, technicians can view the various events and operational logs related to the device under diagnosis by consulting this preset table.

[0144] For example, when the device to be diagnosed includes an industrial camera 1 and a data acquisition card 1, and the specified entries include system time, type, device identifier, and specific content, the preset table can be as shown in Table 1. After acquiring each event or log entry, the electronic device can add the system time, type, device identifier, and specific content of that event or log entry to Table 1. Furthermore, when technicians perform anomaly diagnosis on the industrial camera 1, by referring to Table 1, they can understand that the upper-level software generated a warning log for the industrial camera 1 at system time t9, and the specific content of this warning log is log information I; and that an abnormal event occurred on the industrial camera 1 at system time t10, and the specific content of this abnormal event is event description G.

[0145] Table 1:

[0146] System Time type Equipment identification Specific content Time t1 IO events Industrial Camera 1 Event Description A Time t2 Debug logs Capture Card 1 Log information B Time t3 Regular logs Industrial Camera 1 Log information C Time t4 routine events Capture Card 1 Event Description D Time t5 Regular logs Industrial Camera 1 Log information E Time t6 Regular logs Industrial Camera 1 Log information F Time T7 routine events Capture Card 1 Event Description G Time T8 Regular logs Industrial Camera 1 Log information H Time T9 Warning Log Industrial Camera 1 Log Information I Time T10 Abnormal events Industrial Camera 1 Event Description G Time T11 Warning Log Capture Card 1 Log information K Time t12 Error Log Capture Card 1 Log information L

[0147] Optionally, the electronic device may also, in response to a viewing request for a specified event and / or a specified log entry, locate the specified event and / or the specified log entry corresponding to the viewing request in a preset table.

[0148] Optionally, the above-mentioned viewing request for a specified event may include at least one of the contents of a specified entry for the specified event, and the above-mentioned viewing request for a specified log entry may include at least one of the contents of a specified entry for the specified log entry.

[0149] Optionally, users can also send a viewing request for a specified event and / or a specified log entry to the electronic device by clicking a target point in the first coordinate system of the above embodiments, clicking a specified point in the first coordinate system of the above embodiments, clicking an event distribution point in the second coordinate system of the above embodiments, clicking a log distribution point in the second coordinate system of the above embodiments, or selecting a waveform segment in the above IO waveform diagram.

[0150] For example, such as Figure 5 As shown, a user can send a viewing request for a specific log entry to the electronic device by clicking log distribution point A in the second coordinate system. The electronic device can respond to this viewing request by locating and highlighting the specified log entry corresponding to the viewing request in a preset table as shown in Table 1. Furthermore, the effect of the electronic device locating and highlighting the specified log entry corresponding to the viewing request in the preset table as shown in Table 1 is as follows: Figure 7 As shown.

[0151] Optionally, in the above specific implementations, the time range of the first coordinate axis can be determined based on the current time and a preset duration; or, the time range of the first coordinate axis can be determined based on the current time and the start time of abnormal diagnosis of the device to be diagnosed.

[0152] For example, the start time of the time range of the first coordinate axis can be the difference between the current time and a preset duration, and the end time can be the current time.

[0153] For example, the start time of the time range of the first coordinate axis can be the start time of abnormal diagnosis of the device to be diagnosed, and the end time can be the current time.

[0154] It is worth noting that the time range of each of the above-mentioned first coordinate axes can be adjusted by the user and can be set by those skilled in the art according to the specific application. This application embodiment does not impose specific limitations here.

[0155] like Figure 8 As shown in the figure, this application embodiment also provides an anomaly diagnosis device applied to an electronic device, wherein the electronic device is equipped with upper-layer software that provides services for the device to be diagnosed; the anomaly diagnosis device may include the following modules.

[0156] The event acquisition module 801 is used to acquire various events reported by the device under diagnosis and to acquire the work log of the device under diagnosis generated by the upper layer software.

[0157] The information parsing module 802 is used to parse the event information of each event and the log content of the work log to obtain the abnormal message of the device to be diagnosed; wherein, the abnormal message includes: abnormal events in each event, and / or, abnormal log entries in the work log; the event information of each event includes: event type and timestamp; the log content of each log entry in the work log includes: log type and system time;

[0158] The information display module 803 is used to display the distribution information of abnormal messages of the device to be diagnosed based on the abnormal messages.

[0159] As can be seen from the above, by applying the solution provided in this application embodiment, an upper-layer software that provides services to the device under diagnosis can be installed on the electronic device. The device under diagnosis can report various events occurring within it to the electronic device, and the upper-layer software can generate logs about the device under diagnosis. During defect diagnosis, the electronic device can obtain the various events reported by the device under diagnosis and the working logs about the device under diagnosis generated by the upper-layer software. The event information of each event may include: event type and timestamp; the log content of each log entry in the working log may include: log type and system time; abnormal events in each event, and / or, abnormal log entries in the working log can be used as abnormal messages. The electronic device can parse the event information of each obtained event and the log content of the obtained working log to obtain the abnormal messages of the device under diagnosis, and then, based on the abnormal messages, display the abnormal message distribution information of the device under diagnosis.

[0160] Therefore, since abnormal information can include abnormal log entries in the work log, technicians no longer need to check each log entry in the work log to identify the abnormal log entries when performing abnormal diagnosis on the device under diagnosis. Instead, they can more intuitively and directly identify the abnormal log entries in each log entry by looking at the abnormal message distribution information of the device under diagnosis displayed by the electronic device. It is evident that the solution provided in this application can reduce the difficulty and improve the efficiency of abnormal diagnosis for the device under diagnosis.

[0161] Furthermore, since the abnormal information can also include abnormal events from various events reported by the device under diagnosis, technicians can identify abnormal log entries and abnormal events from various log entries and events by using the abnormal message distribution information displayed by the electronic device. Based on these abnormal log entries and events, technicians can then perform anomaly diagnosis on the device. Therefore, compared to determining the abnormality of the device based on abnormal log entries, the solution provided in this application can improve the accuracy of anomaly diagnosis.

[0162] Optionally, in one specific implementation, the information parsing module is specifically used for:

[0163] According to each preset cycle, each event reported by the device under diagnosis and each newly added log entry in the work log within the preset cycle are read, and each event and log entry read are parsed to obtain the abnormal message of the device under diagnosis.

[0164] Optionally, in one specific implementation, the information display module is specifically used for:

[0165] In a first coordinate system with system time as the first coordinate axis and the number of message entries as the second coordinate axis, a polyline connecting each target point is displayed, and a specified point among the target points is highlighted.

[0166] Wherein, for each target point, the coordinates of the target point on the first coordinate axis are: the time period represented by the target point; the coordinates of the target point on the second coordinate axis are: the sum of the number of events reported by the device to be diagnosed and the number of newly added log entries in the work log within the preset period represented by the target point; the designated point is: the target point corresponding to the preset period in which abnormal messages exist;

[0167] Optionally, in one specific implementation, the apparatus further includes:

[0168] The distribution point display module is used to display the distribution points of each event and / or each log in a second coordinate system with system time as the first coordinate axis and message type as the second coordinate axis.

[0169] Specifically, for each event distribution point, its coordinate on the first coordinate axis is the system time corresponding to the timestamp of the event represented by that event distribution point; its coordinate on the second coordinate axis is the event type of the event represented by that event distribution point; for each log distribution point, its coordinate on the first coordinate axis is the system time of the log entry represented by that log distribution point; its coordinate on the second coordinate axis is the log type of the log entry represented by that log distribution point.

[0170] Optionally, in one specific implementation, the event includes an I / O event, and the device further includes:

[0171] The waveform display module is used to display the IO waveforms of each IO channel of the device under diagnosis based on the IO events reported by the device under diagnosis, and to highlight abnormal waveforms in each IO waveform; wherein, the IO waveform of each IO channel is plotted with system time as the first coordinate axis;

[0172] Optionally, in one specific implementation, the apparatus further includes:

[0173] The event entry addition module is used to add a specified entry about each event to a preset table after each event is acquired.

[0174] The log entry adding module is used to add a specified entry about each log entry to the preset table after each log entry is obtained.

[0175] The specified entry includes at least one of system time, type, device identifier, and specific content.

[0176] This application also provides an electronic device, such as... Figure 9 As shown, it includes:

[0177] Memory 901 is used to store computer programs;

[0178] When the processor 902 executes the program stored in the memory 901, it implements any of the abnormal diagnosis methods provided in the embodiments of this application.

[0179] Furthermore, the aforementioned electronic device may also include a communication bus and / or a communication interface, with the processor 902, communication interface, and memory 901 communicating with each other via the communication bus.

[0180] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not indicate that there is only one bus or one type of bus.

[0181] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0182] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0183] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0184] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the steps of any of the above-described abnormality diagnosis methods.

[0185] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to perform any of the abnormality diagnosis methods described above.

[0186] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a solid-state drive (SSD), etc.

[0187] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0188] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments, electronic device embodiments, computer-readable storage medium embodiments, and computer program product embodiments are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0189] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. An abnormality diagnosis method characterized by comprising: The method is applied to an electronic device, and the electronic device is installed with upper software providing service for a device to be diagnosed. Obtaining each event reported by the device to be diagnosed and a working log of the device to be diagnosed generated by the upper software through a multi-process read-only mode; Analyzing event information of the events and log content of the working log to obtain an abnormal message of the device to be diagnosed; wherein the abnormal message includes an abnormal event in the events and / or an abnormal log entry in the working log; event information of each event includes an event type and a timestamp; log content of each log entry in the working log includes a log type and a system time; the event type includes a normal event and an abnormal event; and the log type includes a normal log, an abnormal log and a warning log; Displaying abnormal message distribution information of the device to be diagnosed according to the abnormal message; wherein the abnormal message distribution information includes distribution time of the abnormal message and / or distribution position of the abnormal message; Displaying each event distribution point and / or each log distribution point in a second coordinate system with a system time as a first coordinate axis and a message type as a second coordinate axis; wherein for each event distribution point, a coordinate of the event distribution point on the first coordinate axis is a system time corresponding to a timestamp of an event represented by the event distribution point; and a coordinate of the event distribution point on the second coordinate axis is an event type of the event represented by the event distribution point; for each log distribution point, a coordinate of the log distribution point on the first coordinate axis is a system time of a log entry represented by the log distribution point; and a coordinate of the log distribution point on the second coordinate axis is a log type of the log entry represented by the log distribution point.

2. The method of claim 1, wherein, The analyzing of the event information of the events and the log content of the working log to obtain the abnormal message of the device to be diagnosed includes: Reading each event reported by the device to be diagnosed and each log entry newly added in the working log in each preset period, and analyzing the read events and log entries to obtain the abnormal message of the device to be diagnosed.

3. The method of claim 2, wherein, The displaying of the abnormal message distribution information of the device to be diagnosed according to the abnormal message includes: Displaying a polyline connecting each target point in a first coordinate system with a system time as a first coordinate axis and a message entry number as a second coordinate axis, and highlighting a specified point in the target points; wherein for each target point, a coordinate of the target point on the first coordinate axis is a time of the preset period represented by the target point, and a coordinate of the target point on the second coordinate axis is a sum of a number of events reported by the device to be diagnosed and a number of log entries newly added in the working log in the preset period represented by the target point; and the specified point is a target point corresponding to a preset period with an abnormal message.

4. The method of claim 1, wherein, The events include IO events, and the method further includes: According to the acquired IO events reported by the to-be-diagnosed device, an IO waveform graph of each IO channel of the to-be-diagnosed device is displayed, and an abnormal waveform is highlighted in each IO waveform graph; wherein the IO waveform graph of each IO channel takes system time as a first coordinate axis.

5. The method according to any one of claims 1 to 4, characterized in that, The method further comprises: adding a specified entry about the event in a preset table after each event is acquired; adding a specified entry about the log entry in the preset table after each log entry is acquired; wherein the specified entry comprises at least one of system time, type, device identification and specific content.

6. An abnormality diagnosing apparatus characterized by comprising: The device is applied to an electronic device, wherein the electronic device is installed with upper-layer software providing services for a to-be-diagnosed device; the device comprises: an event acquisition module, configured to acquire, through a multi-process read-only mode, each event reported by the to-be-diagnosed device and a working log about the to-be-diagnosed device generated by the upper-layer software; an information analysis module, configured to analyze event information of the events and log content of the working log to obtain abnormal messages of the to-be-diagnosed device; wherein the abnormal messages comprise abnormal events in the events and / or abnormal log entries in the working log; the event information of each event comprises event type and timestamp; the log content of each log entry in the working log comprises log type and system time, the event type comprises normal event and abnormal event, and the log type comprises normal log, abnormal log and warning log; an information display module, configured to display abnormal message distribution information of the to-be-diagnosed device according to the abnormal messages, wherein the abnormal message distribution information comprises distribution time of abnormal messages and / or distribution position of abnormal messages; a distribution point display module, configured to display each event distribution point and / or each log distribution point in a second coordinate system taking system time as a first coordinate axis and message type as a second coordinate axis; wherein for each event distribution point, the coordinate of the event distribution point on the first coordinate axis is the system time corresponding to the timestamp of the event represented by the event distribution point, and the coordinate of the event distribution point on the second coordinate axis is the event type of the event represented by the event distribution point; for each log distribution point, the coordinate of the log distribution point on the first coordinate axis is the system time of the log entry represented by the log distribution point, and the coordinate of the log distribution point on the second coordinate axis is the log type of the log entry represented by the log distribution point.

7. The device of claim 6, wherein: the information analysis module is specifically configured to: read, according to each preset period, each event reported by the to-be-diagnosed device and each newly added log entry in the working log in the preset period, and analyze the read events and log entries to obtain abnormal messages of the to-be-diagnosed device; and / or, the information display module is specifically configured to: In a first coordinate system with a system time as a first coordinate axis and a message entry quantity as a second coordinate axis, a polyline connecting each target point is displayed, and a specified point in the target points is highlighted; Wherein, for each target point, the coordinate of the target point on the first coordinate axis is the time represented by the target point in the preset period, and the coordinate of the target point on the second coordinate axis is the sum of the number of events reported by the device to be diagnosed and the number of log entries added in the work log in the period represented by the target point; the specified point is the target point corresponding to the preset period of abnormal messages; And / or, The events include IO events, and the device further includes: a waveform diagram display module configured to display IO waveform diagrams of each IO channel of the device to be diagnosed according to each IO event reported by the device to be diagnosed, and highlight abnormal waveforms in each IO waveform diagram; wherein the IO waveform diagram of each IO channel takes system time as a first coordinate axis; And / or, The device further includes: an event entry adding module configured to add a specified entry about each event in a preset table after obtaining the event; a log entry adding module configured to add a specified entry about each log entry in the preset table after obtaining the log entry; Wherein, the specified entry includes at least one of system time, type, device identifier and specific content.

8. An electronic device, comprising: including: a memory configured to store a computer program; a processor configured to execute the program stored in the memory to implement the method of any one of claims 1-5.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the method of any one of claims 1-5.

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