CN112462715A - Equipment state identification method and identification terminal based on industrial Internet - Google Patents

Equipment state identification method and identification terminal based on industrial Internet Download PDF

Info

Publication number
CN112462715A
CN112462715A CN202011384566.0A CN202011384566A CN112462715A CN 112462715 A CN112462715 A CN 112462715A CN 202011384566 A CN202011384566 A CN 202011384566A CN 112462715 A CN112462715 A CN 112462715A
Authority
CN
China
Prior art keywords
identification
state
determining
script
intelligent
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
CN202011384566.0A
Other languages
Chinese (zh)
Inventor
林细兵
Original Assignee
林细兵
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 林细兵 filed Critical 林细兵
Priority to CN202011384566.0A priority Critical patent/CN112462715A/en
Publication of CN112462715A publication Critical patent/CN112462715A/en
Withdrawn legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00Programme-control systems
    • G05B19/02Programme-control systems electric
    • G05B19/418Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
    • G05B19/41845Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by system universality, reconfigurability, modularity
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00Program-control systems
    • G05B2219/30Nc systems
    • G05B2219/31From computer integrated manufacturing till monitoring
    • G05B2219/31395Process management, specification, process and production data, middle level
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

The application relates to an equipment state identification method and an identification terminal based on an industrial internet. When the scheme is applied, the global identification factor is determined based on the state identification report and the interaction list, the state identification report and the interaction list can be determined through the first intelligent device and the second intelligent device corresponding to the interactive production data, and when the first intelligent device and the second intelligent device are identified according to the global identification factor, the interactive production data are not directly subjected to feature analysis and processing. Therefore, when the interactive production data are overlarge, the state identification report and the interactive list can be analyzed, so that the state of different intelligent devices corresponding to the interactive production data can be indirectly identified, and the time cost can be effectively controlled. Under the working conditions with strict timeliness requirements, the state of the intelligent equipment can be rapidly and accurately identified through the method.

Description

Equipment state identification method and identification terminal based on industrial Internet
Technical Field
The application relates to the technical field of industrial internet, in particular to an equipment state identification method and an identification terminal based on the industrial internet.
Background
With the development of the technology of the internet of things, the application of a digital factory is more and more extensive. In a digital plant, different types of intelligent devices interact and cooperate through industrial internet technology, so that the stable and reliable operation of the whole digital plant is ensured. However, because of the high degree of device interaction in the digital factory, if an abnormality occurs in a certain intelligent device, the whole digital factory may be crashed. For this reason, it is very important how to identify the state of the smart device. In the prior art, state recognition is mostly realized by performing feature analysis and processing on operating parameters and interactive data of the intelligent device, and the mode usually needs to pay more time cost.
Disclosure of Invention
The application provides an equipment state identification method and an identification terminal based on an industrial internet, which aim to solve the technical problem that the time cost for identifying the state of equipment is too high in the prior art.
In a first aspect, a device status identification method based on an industrial internet is applied to an identification terminal communicating with a plurality of intelligent devices, and the identification terminal and the plurality of intelligent devices form a device status identification system, and the method at least includes:
judging whether interactive production data exist in a digital production network formed by all intelligent equipment in the equipment state identification system; wherein the interactive production data is the production data sent by one intelligent device to another intelligent device in the digital production network;
when the interactive production data exist in the digital production network, acquiring a first state identification report and a first interactive list of first intelligent equipment which sends the interactive production data, and acquiring a second state identification report and a second interactive list of second intelligent equipment which receives the interactive production data;
determining a first state identification factor of the first intelligent device according to the first state identification report, and determining a second state identification factor of the first intelligent device according to the first interaction list; determining a first global identification factor for the first smart device based on the first state identification factor and the second state identification factor;
determining data conversion logic information between the first intelligent device and the second intelligent device, determining a third state identification factor of the second intelligent device according to the data conversion logic information and the second interactive list, and determining a fourth state identification factor of the second intelligent device according to the second state identification report; determining a second global identification factor for the second smart device based on the third state identification factor and the fourth state identification factor;
determining a first data conversion loss value of the first intelligent device and a second data conversion loss value of the second intelligent device from the data conversion logic information; weighting the first global identification factor and the second global identification factor based on the first data conversion loss value and the second data conversion loss value to obtain a third global identification factor;
determining a first identification interval according to a first state identification report of the first intelligent device and determining a second identification interval according to a second state identification report of the second intelligent device; and identifying the device states of the first intelligent device and the second intelligent device based on the relative position relation between the third global identification factor and the first identification interval as well as the second identification interval.
Optionally, the step of determining the device states of the first smart device and the second smart device based on the relative position relationship between the third global identification factor and the first identification interval and the relative position relationship between the third global identification factor and the second identification interval further includes:
judging whether the first identification interval and the second identification interval are overlapped;
if the first identification interval and the second identification interval are overlapped; when the third global identification factor falls into the first identification interval, determining that the equipment state of the first intelligent equipment is an abnormal state and the equipment state of the second intelligent equipment is a normal state; when the third global identification factor falls into the second identification interval, determining that the equipment state of the second intelligent equipment is an abnormal state and the equipment state of the first intelligent equipment is a normal state; when the third global identification factor falls into an overlapping interval of the first identification interval and the second identification interval, determining that the equipment states of the first intelligent equipment and the second intelligent equipment are both abnormal states;
if the first identification interval and the second identification interval do not overlap; when the third global identification factor falls into the first identification interval, determining that the equipment state of the first intelligent equipment is an abnormal state and the equipment state of the second intelligent equipment is a normal state; when the third global identification factor falls into the second identification interval, determining that the equipment state of the second intelligent equipment is an abnormal state and the equipment state of the first intelligent equipment is a normal state; and when the third global identification factor does not fall into the first identification interval or the second identification interval, determining that the equipment states of the first intelligent equipment and the second intelligent equipment are normal states.
Optionally, the first status identification report of the first smart device is determined by the following sub-steps:
determining a target operation log with the equipment identifier of the first intelligent equipment from an operation log set corresponding to a preset state recognition thread; the state identification thread is used for carrying out state identification on the intelligent equipment when the intelligent equipment is in an idle working condition or obtaining a state identification result of the intelligent equipment from a third-party state identification equipment;
generating a first log feature set for representing the log information continuity of the target running log and a second log feature set for representing the log information category distribution of the target running log according to the target running log; the first log feature set and the second log feature set respectively comprise a plurality of feature vectors with different dimensions;
extracting an initial characteristic value of each characteristic vector of the target running log in the first log characteristic set, and determining a characteristic vector with a minimum dimension in the second log characteristic set as a target characteristic vector;
determining a current mapping value of the initial characteristic value in the target characteristic vector, and determining a mapping list between the first log characteristic set and the second log characteristic set according to the initial characteristic value and the current mapping value; determining a target vector value in the target characteristic vector values by taking the current mapping value as a reference vector value, mapping the target vector value to the characteristic vector corresponding to the initial characteristic value according to the mapping list, and determining a target characteristic value corresponding to the target vector value in the characteristic vector corresponding to the initial characteristic value;
determining a state identification result of the first intelligent device according to the difference value of the initial characteristic value and the target characteristic value; and generating a first state identification report of the first intelligent device based on all the determined state identification results.
Optionally, the first interaction list of the first smart device is specifically determined by the following sub-steps:
acquiring communication protocol information of the first intelligent device, and determining a target protocol field for representing a communication interaction object of the first intelligent device from the communication protocol information;
extracting at least a plurality of sub-target fields from the target protocol field and determining the field characteristics corresponding to each sub-target field; wherein the field features are used for characterizing the object identification of the communication interaction object;
analyzing each field characteristic to obtain object identification information corresponding to each field characteristic; determining interaction time period information of communication interaction between each communication interaction object and the first intelligent equipment according to the object identification information; and determining a first interaction list of the first intelligent device based on the object identification information and the interaction period information corresponding to each communication interaction object.
Optionally, the step of determining a first state identification factor of the first intelligent device according to the first state identification report, and determining a second state identification factor of the first intelligent device according to the first interaction list specifically includes:
listing all state recognition results in the first state recognition report, and determining the generation time of each state recognition result; determining the time length between the starting time and the current time as the state recognition time length by taking the current time as the ending time and the generation time farthest from the current time as the starting time;
determining a time weight value of each generation moment relative to the state identification duration; the time weight value corresponding to the generation time closer to the current time is larger;
determining the proportion of a target state identification result used for representing the abnormal state of the first intelligent device in all state identification results from all state identification results;
weighting the time weight value corresponding to each target state identification result according to the occupation ratio to obtain a target weight value; weighting and summing the target weight values to obtain a first state identification factor of the first intelligent device;
determining a target state identification factor of a third intelligent device interacting with the first intelligent device in a state identification period corresponding to the state identification duration from the first interaction list, wherein the target state identification factor is determined according to the step corresponding to the first state identification factor;
and determining the mean value of all the determined target state identification factors as the second state identification factor of the first intelligent equipment.
Optionally, the step of determining the first global identification factor of the first smart device based on the first state identification factor and the second state identification factor specifically includes:
determining a target generation time corresponding to a target state recognition result closest to the current time in the first state recognition report;
determining a difference between the current time and the target generation time;
determining a proportional value of the difference value and the state identification duration value;
weighting the first state identification factor and the second state identification factor by respectively adopting the proportion value and the target proportion value to obtain a first global identification factor of the first intelligent device; wherein a sum of the proportional value and the target proportional value is one.
Optionally, the step of determining the data conversion logic information between the first intelligent device and the second intelligent device specifically includes:
calling a first data conversion thread of the first intelligent device and a second data conversion thread of the second intelligent device respectively, and extracting a first thread script of the first data conversion thread and a second thread script of the second data conversion thread;
determining data mapping information of the first thread script relative to the second thread script and multiple groups of same script information in the first thread script and the second thread script;
judging whether a compatibility adjustment identifier exists between the first thread script and the second thread script; when the compatibility adjustment identification exists between the first thread script and the second thread script, determining a compatible script group and an incompatible script group corresponding to the first thread script and the second thread script; at least part of script information in the multiple groups of script information is under the compatible script group, and at least part of script information in the multiple groups of script information is under the incompatible script group;
determining information capacity difference between each script information of the multiple groups of script information under the incompatible script grouping and each script information of the multiple groups of script information under the compatible script grouping according to the script information of the multiple groups of script information under the compatible script grouping and the information capacity of the script information; adjusting the script information under the compatible script grouping and the script information under the incompatible script grouping according to the information capacity difference; the number of the script information under the adjusted compatible script group is the same as the number of the script information under the adjusted incompatible script group;
and determining data conversion logic information between the first intelligent device and the second intelligent device according to the one-to-one correspondence relationship between the script information under the adjusted compatible script group and the script information under the adjusted incompatible script group.
In a second aspect, an identification terminal is provided, which includes: the system comprises a processor, a memory and a network interface, wherein the memory and the network interface are connected with the processor; the network interface is connected with a nonvolatile memory in the identification terminal; when the processor is operated, the computer program is called from the nonvolatile memory through the network interface, and the computer program is operated through the memory so as to execute the method.
In a third aspect, a readable storage medium applied to a computer is provided, and a computer program is burned in the readable storage medium, and when the computer program runs in a memory of an identification terminal, the method is implemented.
When the device state identification method and the identification terminal based on the industrial internet are applied, the global identification factor is determined based on the state identification report and the interaction list, the state identification report and the interaction list can be determined through the first intelligent device and the second intelligent device corresponding to the interactive production data, and when the first intelligent device and the second intelligent device are identified according to the global identification factor, the interactive production data are not directly subjected to characteristic analysis and processing, so that when the interactive production data are overlarge, the state identification report and the interaction list can be analyzed, so that the indirect identification of the states of different intelligent devices corresponding to the interactive production data is realized, and the time cost can be effectively controlled. Under the working conditions with strict timeliness requirements, the state of the intelligent equipment can be rapidly and accurately identified through the method.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
Fig. 1 is a schematic diagram of an industrial internet-based device status identification system according to an exemplary embodiment of the present application.
Fig. 2 is a flowchart illustrating an industrial internet-based device status identification method according to an exemplary embodiment of the present application.
Fig. 3 is a block diagram illustrating an embodiment of an apparatus for identifying a device status based on an industrial internet according to an exemplary embodiment of the present application.
Fig. 4 is a hardware configuration diagram of an identification terminal where the apparatus of the present application is located.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
In order to solve the problems, the invention discloses an equipment state identification method and a terminal based on an industrial internet.
For convenience of describing the device state identification method, the application scenario of the device state identification method is first explained in the present application. Referring to fig. 1, a communication architecture of an industrial internet-based device status recognition system 100 according to the present invention is shown. As can be seen from fig. 1, the device status recognition system 100 includes a recognition terminal 200 and a plurality of smart devices 300 that communicate with each other. The plurality of intelligent devices 300 may be different types of production devices in the same digital factory, and are not limited herein.
On the basis of the above, please refer to fig. 2, which is a flowchart of an apparatus status identification method based on the industrial internet according to the present invention, and the method can be applied to the identification terminal 200 in fig. 1, and specifically can include the following steps.
Step1, judging whether interactive production data exist in a digital production network formed by all intelligent equipment in the equipment state identification system; wherein the interactive production data is production data sent by one intelligent device to another intelligent device in the digital production network.
Step2, when the interactive production data exist in the digital production network, acquiring a first state identification report and a first interactive list of a first intelligent device sending the interactive production data, and acquiring a second state identification report and a second interactive list of a second intelligent device receiving the interactive production data.
Step3, determining a first state identification factor of the first intelligent device according to the first state identification report, and determining a second state identification factor of the first intelligent device according to the first interaction list; determining a first global identification factor for the first smart device based on the first state identification factor and the second state identification factor.
Step4, determining data conversion logic information between the first intelligent device and the second intelligent device, determining a third state identification factor of the second intelligent device according to the data conversion logic information and the second interactive list, and determining a fourth state identification factor of the second intelligent device according to the second state identification report; determining a second global identification factor for the second smart device based on the third state identification factor and the fourth state identification factor.
Step5, determining a first data conversion loss value of the first intelligent device and a second data conversion loss value of the second intelligent device from the data conversion logic information; and weighting the first global identification factor and the second global identification factor based on the first data conversion loss value and the second data conversion loss value to obtain a third global identification factor.
Step6, determining a first identification interval according to the first state identification report of the first intelligent device and determining a second identification interval according to the second state identification report of the second intelligent device; and identifying the device states of the first intelligent device and the second intelligent device based on the relative position relation between the third global identification factor and the first identification interval as well as the second identification interval.
In this embodiment, the value range of the identification factor may be 0-1.
When the method described in Step1-Step6 is applied, the global identification factor is determined based on the state identification report and the interaction list, and the state identification report and the interaction list can be determined by the first intelligent device and the second intelligent device corresponding to the interactive production data, and when the first intelligent device and the second intelligent device are identified according to the global identification factor, the interactive production data are not directly subjected to characteristic analysis and processing, so that when the interactive production data are overlarge, the state identification report and the interaction list can be analyzed to realize indirect identification of states of different intelligent devices corresponding to the interactive production data, and the time cost can be effectively controlled. Under the working conditions with strict timeliness requirements, the state of the intelligent equipment can be rapidly and accurately identified through the method.
In a more specific embodiment, the determining the device states of the first smart device and the second smart device based on the relative position relationship between the third global identification factor and the first identification interval and the second identification interval described in Step6 further includes the following steps.
Step611, determining whether the first identification interval and the second identification interval overlap.
Step612, if the first identification interval and the second identification interval are overlapped; when the third global identification factor falls into the first identification interval, determining that the equipment state of the first intelligent equipment is an abnormal state and the equipment state of the second intelligent equipment is a normal state; when the third global identification factor falls into the second identification interval, determining that the equipment state of the second intelligent equipment is an abnormal state and the equipment state of the first intelligent equipment is a normal state; and when the third global identification factor falls into an overlapping interval of the first identification interval and the second identification interval, determining that the equipment states of the first intelligent equipment and the second intelligent equipment are both abnormal states.
Step613, if the first identification interval and the second identification interval do not overlap; when the third global identification factor falls into the first identification interval, determining that the equipment state of the first intelligent equipment is an abnormal state and the equipment state of the second intelligent equipment is a normal state; when the third global identification factor falls into the second identification interval, determining that the equipment state of the second intelligent equipment is an abnormal state and the equipment state of the first intelligent equipment is a normal state; and when the third global identification factor does not fall into the first identification interval or the second identification interval, determining that the equipment states of the first intelligent equipment and the second intelligent equipment are normal states.
When the contents described in Step611-Step613 are applied, the overlapping condition of the first identification interval and the second identification interval can be determined first, so that the device states of the first smart device and the second smart device can be determined according to different overlapping determination results. Therefore, different device states of the first intelligent device and the second intelligent device can be identified based on different relative position relations between the third global identification factor and the first identification interval and between the third global identification factor and the second identification interval, and comprehensiveness of device state identification is improved.
In one possible embodiment, only the first status identification report and the first interaction list of the first smart device sending the interactive production data are obtained in Step2, since the first status identification report and the first interaction list are obtained in a similar manner as the second status identification report and the second interaction list.
Further, the first status identification report of the first smart device may be determined by the following sub-steps.
Step211, determining a target operation log with the equipment identifier of the first intelligent equipment from an operation log set corresponding to a preset state identification thread; the state identification thread is used for carrying out state identification on the intelligent equipment when the intelligent equipment is in an idle working condition or obtaining a state identification result of the intelligent equipment from a third-party state identification device.
It will be appreciated that the state identification thread is only started in the following two cases.
(1) And starting the intelligent equipment when the intelligent equipment is in an idle working condition.
(2) The method is started when the identification result sending request of the third party state identification equipment is identified.
It will be appreciated that in both cases, the state identification requires less time-efficiency, which may allow for greater time costs. However, under some working conditions with higher requirements on timeliness, the state identification technology provided by the scheme needs to be adopted.
Accordingly, the device state recognition results in the two cases can be used as the recognition basis of the scheme. Therefore, the historical state recognition result can be directly analyzed, so that the time cost is greatly saved, and the timeliness of equipment state recognition is improved.
Step212, generating a first log feature set for representing the continuity of the log information of the target running log and a second log feature set for representing the category distribution of the log information of the target running log according to the target running log; the first log feature set and the second log feature set respectively comprise a plurality of feature vectors with different dimensions.
Step213, extracting an initial characteristic value of each characteristic vector of the target running log in the first log characteristic set, and determining a characteristic vector with the smallest dimension in the second log characteristic set as a target characteristic vector.
Step214, determining a current mapping value of the initial characteristic value in the target characteristic vector, and determining a mapping list between the first log characteristic set and the second log characteristic set according to the initial characteristic value and the current mapping value; determining a target vector value in the target feature vector values by taking the current mapping value as a reference vector value, mapping the target vector value to the feature vector corresponding to the initial feature value according to the mapping list, and determining a target feature value corresponding to the target vector value in the feature vector corresponding to the initial feature value.
Step215, determining a state identification result of the first intelligent device according to the difference value of the initial characteristic value and the target characteristic value; and generating a first state identification report of the first intelligent device based on all the determined state identification results.
It can be understood that through the contents described in steps S211 to S215, a target operation log in which the device identifier of the first smart device is added can be determined from the operation log set corresponding to the state recognition thread, and the target operation log is subjected to feature analysis and mapping conversion, so as to determine a plurality of state recognition results. In this way, the first state recognition report can be completely and accurately determined based on the plurality of state recognition results.
Optionally, the first interaction list of the first smart device may be specifically determined by the following sub-steps.
Step221, acquiring communication protocol information of the first intelligent device, and determining a target protocol field for representing a communication interaction object of the first intelligent device from the communication protocol information.
Step222, extracting at least a plurality of sub-target fields from the target protocol field and determining field characteristics corresponding to each sub-target field; wherein the field characteristics are used for characterizing the object identification of the communication interaction object.
Step223, analyzing each field characteristic to obtain object identification information corresponding to each field characteristic; determining interaction time period information of communication interaction between each communication interaction object and the first intelligent equipment according to the object identification information; and determining a first interaction list of the first intelligent device based on the object identification information and the interaction period information corresponding to each communication interaction object.
Through Step221-Step223, the communication protocol information of the first intelligent device can be analyzed, so that the first interaction list of the first intelligent device can be completely and accurately determined. The first interactive list comprises the object identification information and the interactive time period information of the communication interactive object, and can provide accurate identification basis and data basis for subsequent state identification.
In an alternative embodiment, the determining of the first state identification factor of the first smart device according to the first state identification report and the determining of the second state identification factor of the first smart device according to the first interaction list described in Step3 may specifically include the following sub-steps.
Step311, listing all state recognition results in the first state recognition report, and determining the generation time of each state recognition result; and determining the time length between the starting time and the current time as the state recognition time length by taking the current time as the ending time and the generation time farthest from the current time as the starting time.
Step312, determining a time weight value of each generation time relative to the state identification duration; wherein the time weight value corresponding to the generation time closer to the current time is larger.
And Step313, determining the proportion of the target state identification result used for representing the abnormal state of the first intelligent device in all the state identification results.
Step314, weighting the time weight value corresponding to each target state identification result according to the occupation ratio to obtain a target weight value; and carrying out weighted summation on the target weight values to obtain a first state identification factor of the first intelligent equipment.
In Step314, the first state identification factor may be understood as a direct state identification factor of the first smart device.
And Step315, determining a target state identification factor of a third intelligent device interacting with the first intelligent device in a state identification time period corresponding to the state identification duration from the first interaction list, wherein the target state identification factor is determined according to the Step corresponding to the first state identification factor.
And Step316, determining the average value of all the determined target state identification factors as a second state identification factor of the first intelligent device.
In Step316, the second state identification factor may be understood as an indirect state identification factor of the first smart device.
It is understood that based on the above steps, the direct state identification factor and the indirect state identification factor of the first smart device can be determined respectively, so as to take the state identification result of the first smart device and a third smart device interacting with the first smart device into account to ensure the accuracy and reliability of the first state identification factor and the second state identification factor.
Further, at Step3, the Step of determining the first global identification factor of the first smart device based on the first state identification factor and the second state identification factor specifically includes the following steps.
Step321, determining a target generation time corresponding to the target state identification result closest to the current time in the first state identification report.
Step322, determining a difference value between the current time and the target generation time.
And Step323, determining a proportional value of the difference value and the state identification duration value.
Step324, weighting the first state identification factor and the second state identification factor by respectively adopting the proportion value and the target proportion value to obtain a first global identification factor of the first intelligent device; wherein a sum of the proportional value and the target proportional value is one.
When the steps described in steps 321 to 324 are applied, the scale values for weighting the first state recognition factor and the second state recognition factor can be determined at the target generation time corresponding to the target state recognition result, taking into account the timeliness of the state recognition of the first smart device. Therefore, the first global identification factor of the first intelligent device can be accurately determined.
In one possible example, the determining of the data conversion logic information between the first smart device and the second smart device described in Step4 may be implemented in the following manner.
Step411, respectively invoking a first data conversion thread of the first intelligent device and a second data conversion thread of the second intelligent device, and extracting a first thread script of the first data conversion thread and a second thread script of the second data conversion thread.
Step412, determining data mapping information of the first thread script relative to the second thread script and multiple sets of same script information in the first thread script and the second thread script.
Step413, judging whether a compatibility adjustment identifier exists between the first thread script and the second thread script; when the compatibility adjustment identification exists between the first thread script and the second thread script, determining a compatible script group and an incompatible script group corresponding to the first thread script and the second thread script; at least part of script information in the multiple sets of script information is located under the compatible script packet, and at least part of script information in the multiple sets of script information is located under the incompatible script packet.
Step414, determining the information capacity difference between each script information of the multiple groups of script information under the incompatible script grouping and each script information of the multiple groups of script information under the compatible script grouping according to the script information of the multiple groups of script information under the compatible script grouping and the information capacity thereof; adjusting the script information under the compatible script grouping and the script information under the incompatible script grouping according to the information capacity difference; and the number of the script information under the adjusted compatible script group is the same as the number of the script information under the adjusted incompatible script group.
Step415, determining data conversion logic information between the first intelligent device and the second intelligent device according to the one-to-one correspondence relationship between the script information under the adjusted compatible script packet and the script information under the adjusted incompatible script packet.
When the contents described in steps 411 to 415 are applied, the first thread script of the first intelligent device and the second thread script of the second intelligent device can be analyzed, so that the data conversion logic information between the first intelligent device and the second intelligent device is determined completely and faultlessly.
In an alternative embodiment, determining the third state identification factor of the second smart device according to the data conversion logic information and the second interaction list, which is described in Step4, specifically includes the following steps.
(1) Screening a plurality of fourth intelligent devices in the second interactive list according to the data conversion logic information to obtain at least a plurality of fifth intelligent devices; wherein the fourth smart device is a smart device that has an interaction with the second smart device within the state identification period.
(2) Determining a fifth state identification factor of each fifth intelligent device according to the step corresponding to the determination of the first intelligent device; wherein the fifth state identification factor is a direct state identification factor of the fifth smart device.
(3) Determining a third state identification factor of the second intelligent device according to the fifth state identification factor; wherein the third state identification factor is an indirect state identification factor of the second smart device.
It is understood that, with the contents described in (1) - (3), the data conversion logic information can be taken into account in determining the third state identification factor, thereby ensuring the accuracy and reliability of the third state identification factor.
In Step4, the fourth state recognition factor can be understood as the direct state recognition factor of the second smart device. Accordingly, the fourth state recognition factor and the second global recognition factor are determined in a similar manner to the first state recognition factor and the first global recognition factor, and therefore will not be further described herein.
In an alternative embodiment, the determining the first data conversion loss value of the first smart device and the second data conversion loss value of the second smart device from the data conversion logic information described in Step5 may be specifically implemented by the following steps.
Step511, determining a current information structure field of the data conversion logic information, and a first information structure field of the first intelligent device and a second information structure field of the second intelligent device.
Step512, determining the first data conversion loss value according to the field similarity of the first information structure field and the current information structure field.
Step513, determining the second data conversion loss value according to the field similarity between the second information structure field and the current information structure field.
When the contents described in steps 511 to 513 are applied, the first data conversion loss value and the second data conversion loss value can be accurately determined.
In an alternative embodiment, the weighting of the first global identification factor and the second global identification factor based on the first data transition loss value and the second data transition loss value as described in Step5 results in a third global identification factor.
Step521, performing normalization processing on the first data conversion loss value and the second data conversion loss value to obtain a first loss coefficient corresponding to the first data conversion loss value and a second loss coefficient corresponding to the second data conversion loss value; wherein the first loss tangent and the second loss tangent are both positive numbers less than one.
Step522, determining a first product value of the first loss factor and the first global identification factor and a second product value of the second loss factor and the second global identification factor.
Step523, determining the third global identification factor according to the first product value and the second product value.
It can be understood that through the steps, the third global identification factor can be accurately determined.
On the basis of the above, please refer to fig. 3, which is a functional block diagram of an apparatus status identification device 600 according to an embodiment of the present invention. The device state recognition apparatus 600 is applied to a recognition terminal communicating with a plurality of intelligent devices, the recognition terminal and the plurality of intelligent devices form a device state recognition system, and the device state recognition apparatus 600 specifically includes the following functional modules.
A1. An apparatus 600 for recognizing device status comprises the following functional modules:
the data judgment module 601 is used for judging whether interactive production data exist in a digital production network formed by all intelligent devices in the device state identification system; wherein the interactive production data is the production data sent by one intelligent device to another intelligent device in the digital production network;
an equipment determining module 602, configured to, when it is determined that the interactive production data exists in the digital production network, obtain a first state identification report and a first interaction list of a first intelligent device that sends the interactive production data, and obtain a second state identification report and a second interaction list of a second intelligent device that receives the interactive production data;
a factor determining module 603, configured to determine a first state identification factor of the first smart device according to the first state identification report, and determine a second state identification factor of the first smart device according to the first interaction list; determining a first global identification factor for the first smart device based on the first state identification factor and the second state identification factor;
an information determining module 604, configured to determine data conversion logic information between the first smart device and the second smart device, determine a third state identification factor of the second smart device according to the data conversion logic information and the second interactive list, and determine a fourth state identification factor of the second smart device according to the second state identification report; determining a second global identification factor for the second smart device based on the third state identification factor and the fourth state identification factor;
a loss determining module 605, configured to determine a first data conversion loss value of the first smart device and a second data conversion loss value of the second smart device from the data conversion logic information; weighting the first global identification factor and the second global identification factor based on the first data conversion loss value and the second data conversion loss value to obtain a third global identification factor;
a state identification module 606, configured to determine a first identification interval according to the first state identification report of the first smart device and determine a second identification interval according to the second state identification report of the second smart device; and identifying the device states of the first intelligent device and the second intelligent device based on the relative position relation between the third global identification factor and the first identification interval as well as the second identification interval.
A2. The apparatus of a1, the state identification module 606, is specifically configured to:
judging whether the first identification interval and the second identification interval are overlapped;
if the first identification interval and the second identification interval are overlapped; when the third global identification factor falls into the first identification interval, determining that the equipment state of the first intelligent equipment is an abnormal state and the equipment state of the second intelligent equipment is a normal state; when the third global identification factor falls into the second identification interval, determining that the equipment state of the second intelligent equipment is an abnormal state and the equipment state of the first intelligent equipment is a normal state; when the third global identification factor falls into an overlapping interval of the first identification interval and the second identification interval, determining that the equipment states of the first intelligent equipment and the second intelligent equipment are both abnormal states;
if the first identification interval and the second identification interval do not overlap; when the third global identification factor falls into the first identification interval, determining that the equipment state of the first intelligent equipment is an abnormal state and the equipment state of the second intelligent equipment is a normal state; when the third global identification factor falls into the second identification interval, determining that the equipment state of the second intelligent equipment is an abnormal state and the equipment state of the first intelligent equipment is a normal state; and when the third global identification factor does not fall into the first identification interval or the second identification interval, determining that the equipment states of the first intelligent equipment and the second intelligent equipment are normal states.
A3. The apparatus of a1, the device determining module 602, is specifically configured to:
determining a target operation log with the equipment identifier of the first intelligent equipment from an operation log set corresponding to a preset state recognition thread; the state identification thread is used for carrying out state identification on the intelligent equipment when the intelligent equipment is in an idle working condition or obtaining a state identification result of the intelligent equipment from a third-party state identification equipment;
generating a first log feature set for representing the log information continuity of the target running log and a second log feature set for representing the log information category distribution of the target running log according to the target running log; the first log feature set and the second log feature set respectively comprise a plurality of feature vectors with different dimensions;
extracting an initial characteristic value of each characteristic vector of the target running log in the first log characteristic set, and determining a characteristic vector with a minimum dimension in the second log characteristic set as a target characteristic vector;
determining a current mapping value of the initial characteristic value in the target characteristic vector, and determining a mapping list between the first log characteristic set and the second log characteristic set according to the initial characteristic value and the current mapping value; determining a target vector value in the target characteristic vector values by taking the current mapping value as a reference vector value, mapping the target vector value to the characteristic vector corresponding to the initial characteristic value according to the mapping list, and determining a target characteristic value corresponding to the target vector value in the characteristic vector corresponding to the initial characteristic value;
determining a state identification result of the first intelligent device according to the difference value of the initial characteristic value and the target characteristic value; and generating a first state identification report of the first intelligent device based on all the determined state identification results.
A4. The apparatus of a3, the device determining module 602, is specifically configured to:
acquiring communication protocol information of the first intelligent device, and determining a target protocol field for representing a communication interaction object of the first intelligent device from the communication protocol information;
extracting at least a plurality of sub-target fields from the target protocol field and determining the field characteristics corresponding to each sub-target field; wherein the field features are used for characterizing the object identification of the communication interaction object;
analyzing each field characteristic to obtain object identification information corresponding to each field characteristic; determining interaction time period information of communication interaction between each communication interaction object and the first intelligent equipment according to the object identification information; and determining a first interaction list of the first intelligent device based on the object identification information and the interaction period information corresponding to each communication interaction object.
A5. The apparatus of a1, the factor determining module 603, is specifically configured to:
listing all state recognition results in the first state recognition report, and determining the generation time of each state recognition result; determining the time length between the starting time and the current time as the state recognition time length by taking the current time as the ending time and the generation time farthest from the current time as the starting time;
determining a time weight value of each generation moment relative to the state identification duration; the time weight value corresponding to the generation time closer to the current time is larger;
determining the proportion of a target state identification result used for representing the abnormal state of the first intelligent device in all state identification results from all state identification results;
weighting the time weight value corresponding to each target state identification result according to the occupation ratio to obtain a target weight value; weighting and summing the target weight values to obtain a first state identification factor of the first intelligent device;
determining a target state identification factor of a third intelligent device interacting with the first intelligent device in a state identification period corresponding to the state identification duration from the first interaction list, wherein the target state identification factor is determined according to the step corresponding to the first state identification factor;
and determining the mean value of all the determined target state identification factors as the second state identification factor of the first intelligent equipment.
A6. The apparatus of a5, the factor determining module 603, is specifically configured to:
determining a target generation time corresponding to a target state recognition result closest to the current time in the first state recognition report;
determining a difference between the current time and the target generation time;
determining a proportional value of the difference value and the state identification duration value;
weighting the first state identification factor and the second state identification factor by respectively adopting the proportion value and the target proportion value to obtain a first global identification factor of the first intelligent device; wherein a sum of the proportional value and the target proportional value is one.
A7. The apparatus of a1, the information determining module 604 is specifically configured to:
calling a first data conversion thread of the first intelligent device and a second data conversion thread of the second intelligent device respectively, and extracting a first thread script of the first data conversion thread and a second thread script of the second data conversion thread;
determining data mapping information of the first thread script relative to the second thread script and multiple groups of same script information in the first thread script and the second thread script;
judging whether a compatibility adjustment identifier exists between the first thread script and the second thread script; when the compatibility adjustment identification exists between the first thread script and the second thread script, determining a compatible script group and an incompatible script group corresponding to the first thread script and the second thread script; at least part of script information in the multiple groups of script information is under the compatible script group, and at least part of script information in the multiple groups of script information is under the incompatible script group;
determining information capacity difference between each script information of the multiple groups of script information under the incompatible script grouping and each script information of the multiple groups of script information under the compatible script grouping according to the script information of the multiple groups of script information under the compatible script grouping and the information capacity of the script information; adjusting the script information under the compatible script grouping and the script information under the incompatible script grouping according to the information capacity difference; the number of the script information under the adjusted compatible script group is the same as the number of the script information under the adjusted incompatible script group;
and determining data conversion logic information between the first intelligent device and the second intelligent device according to the one-to-one correspondence relationship between the script information under the adjusted compatible script group and the script information under the adjusted incompatible script group.
A8. The apparatus of a7, the information determining module 604 is specifically configured to:
screening a plurality of fourth intelligent devices in the second interactive list according to the data conversion logic information to obtain at least a plurality of fifth intelligent devices; wherein the fourth smart device is a smart device that has an interaction with the second smart device within the state identification period;
determining a fifth state identification factor of each fifth intelligent device according to the step corresponding to the determination of the first intelligent device; wherein the fifth state identification factor is a direct state identification factor of the fifth smart device;
determining a third state identification factor of the second intelligent device according to the fifth state identification factor; wherein the third state identification factor is an indirect state identification factor of the second smart device.
A9. The apparatus of a1, the loss determining module 605, is specifically configured to:
determining a current information structure field of data conversion logic information, a first information structure field of the first intelligent device and a second information structure field of the second intelligent device;
determining the first data conversion loss value according to the field similarity of the first information structure field and the current information structure field;
and determining the second data conversion loss value according to the field similarity of the second information structure field and the current information structure field.
A10. The apparatus of a9, the loss determining module 605, is specifically configured to:
normalizing the first data conversion loss value and the second data conversion loss value to obtain a first loss coefficient corresponding to the first data conversion loss value and a second loss coefficient corresponding to the second data conversion loss value; wherein the first loss factor and the second loss factor are both positive numbers less than one;
determining a first product value of the first loss factor and the first global identification factor and a second product value of the second loss factor and the second global identification factor;
determining the third global identification factor based on the first and second product values.
On the basis, the equipment state identification system is further provided, and the specific content is as follows.
B1. An equipment state identification system based on an industrial internet comprises an identification terminal and a plurality of intelligent equipment which are communicated with each other, wherein production data interaction exists among the intelligent equipment;
the identification terminal is used for judging whether interactive production data exist in a digital production network formed by all intelligent equipment in the equipment state identification system; wherein the interactive production data is the production data sent by one intelligent device to another intelligent device in the digital production network;
the identification terminal is used for acquiring a first state identification report and a first interactive list of first intelligent equipment for sending the interactive production data and acquiring a second state identification report and a second interactive list of second intelligent equipment for receiving the interactive production data when the interactive production data are determined to exist in the digital production network;
the identification terminal is used for determining a first state identification factor of the first intelligent device according to the first state identification report and determining a second state identification factor of the first intelligent device according to the first interactive list; determining a first global identification factor for the first smart device based on the first state identification factor and the second state identification factor;
the identification terminal is used for determining data conversion logic information between the first intelligent device and the second intelligent device, determining a third state identification factor of the second intelligent device according to the data conversion logic information and the second interactive list, and determining a fourth state identification factor of the second intelligent device according to the second state identification report; determining a second global identification factor for the second smart device based on the third state identification factor and the fourth state identification factor;
the identification terminal is used for determining a first data conversion loss value of the first intelligent device and a second data conversion loss value of the second intelligent device from the data conversion logic information; weighting the first global identification factor and the second global identification factor based on the first data conversion loss value and the second data conversion loss value to obtain a third global identification factor;
the identification terminal is used for determining a first identification interval according to the first state identification report of the first intelligent device and determining a second identification interval according to the second state identification report of the second intelligent device; and identifying the device states of the first intelligent device and the second intelligent device based on the relative position relation between the third global identification factor and the first identification interval as well as the second identification interval.
B2. The system of B1, the identification terminal, further configured to:
judging whether the first identification interval and the second identification interval are overlapped;
if the first identification interval and the second identification interval are overlapped; when the third global identification factor falls into the first identification interval, determining that the equipment state of the first intelligent equipment is an abnormal state and the equipment state of the second intelligent equipment is a normal state; when the third global identification factor falls into the second identification interval, determining that the equipment state of the second intelligent equipment is an abnormal state and the equipment state of the first intelligent equipment is a normal state; when the third global identification factor falls into an overlapping interval of the first identification interval and the second identification interval, determining that the equipment states of the first intelligent equipment and the second intelligent equipment are both abnormal states;
if the first identification interval and the second identification interval do not overlap; when the third global identification factor falls into the first identification interval, determining that the equipment state of the first intelligent equipment is an abnormal state and the equipment state of the second intelligent equipment is a normal state; when the third global identification factor falls into the second identification interval, determining that the equipment state of the second intelligent equipment is an abnormal state and the equipment state of the first intelligent equipment is a normal state; and when the third global identification factor does not fall into the first identification interval or the second identification interval, determining that the equipment states of the first intelligent equipment and the second intelligent equipment are normal states.
B3. The system of B1, the identification terminal, further configured to:
determining a target operation log with the equipment identifier of the first intelligent equipment from an operation log set corresponding to a preset state recognition thread; the state identification thread is used for carrying out state identification on the intelligent equipment when the intelligent equipment is in an idle working condition or obtaining a state identification result of the intelligent equipment from a third-party state identification equipment;
generating a first log feature set for representing the log information continuity of the target running log and a second log feature set for representing the log information category distribution of the target running log according to the target running log; the first log feature set and the second log feature set respectively comprise a plurality of feature vectors with different dimensions;
extracting an initial characteristic value of each characteristic vector of the target running log in the first log characteristic set, and determining a characteristic vector with a minimum dimension in the second log characteristic set as a target characteristic vector;
determining a current mapping value of the initial characteristic value in the target characteristic vector, and determining a mapping list between the first log characteristic set and the second log characteristic set according to the initial characteristic value and the current mapping value; determining a target vector value in the target characteristic vector values by taking the current mapping value as a reference vector value, mapping the target vector value to the characteristic vector corresponding to the initial characteristic value according to the mapping list, and determining a target characteristic value corresponding to the target vector value in the characteristic vector corresponding to the initial characteristic value;
determining a state identification result of the first intelligent device according to the difference value of the initial characteristic value and the target characteristic value; and generating a first state identification report of the first intelligent device based on all the determined state identification results.
B4. The system of B3, the identification terminal, further configured to:
acquiring communication protocol information of the first intelligent device, and determining a target protocol field for representing a communication interaction object of the first intelligent device from the communication protocol information;
extracting at least a plurality of sub-target fields from the target protocol field and determining the field characteristics corresponding to each sub-target field; wherein the field features are used for characterizing the object identification of the communication interaction object;
analyzing each field characteristic to obtain object identification information corresponding to each field characteristic; determining interaction time period information of communication interaction between each communication interaction object and the first intelligent equipment according to the object identification information; and determining a first interaction list of the first intelligent device based on the object identification information and the interaction period information corresponding to each communication interaction object.
B5. The system of B1, the identification terminal, further configured to:
listing all state recognition results in the first state recognition report, and determining the generation time of each state recognition result; determining the time length between the starting time and the current time as the state recognition time length by taking the current time as the ending time and the generation time farthest from the current time as the starting time;
determining a time weight value of each generation moment relative to the state identification duration; the time weight value corresponding to the generation time closer to the current time is larger;
determining the proportion of a target state identification result used for representing the abnormal state of the first intelligent device in all state identification results from all state identification results;
weighting the time weight value corresponding to each target state identification result according to the occupation ratio to obtain a target weight value; weighting and summing the target weight values to obtain a first state identification factor of the first intelligent device;
determining a target state identification factor of a third intelligent device interacting with the first intelligent device in a state identification period corresponding to the state identification duration from the first interaction list, wherein the target state identification factor is determined according to the step corresponding to the first state identification factor;
and determining the mean value of all the determined target state identification factors as the second state identification factor of the first intelligent equipment.
B6. The system of B5, the identification terminal, further configured to:
determining a target generation time corresponding to a target state recognition result closest to the current time in the first state recognition report;
determining a difference between the current time and the target generation time;
determining a proportional value of the difference value and the state identification duration value;
weighting the first state identification factor and the second state identification factor by respectively adopting the proportion value and the target proportion value to obtain a first global identification factor of the first intelligent device; wherein a sum of the proportional value and the target proportional value is one.
B7. The system of B1, the identification terminal, further configured to:
calling a first data conversion thread of the first intelligent device and a second data conversion thread of the second intelligent device respectively, and extracting a first thread script of the first data conversion thread and a second thread script of the second data conversion thread;
determining data mapping information of the first thread script relative to the second thread script and multiple groups of same script information in the first thread script and the second thread script;
judging whether a compatibility adjustment identifier exists between the first thread script and the second thread script; when the compatibility adjustment identification exists between the first thread script and the second thread script, determining a compatible script group and an incompatible script group corresponding to the first thread script and the second thread script; at least part of script information in the multiple groups of script information is under the compatible script group, and at least part of script information in the multiple groups of script information is under the incompatible script group;
determining information capacity difference between each script information of the multiple groups of script information under the incompatible script grouping and each script information of the multiple groups of script information under the compatible script grouping according to the script information of the multiple groups of script information under the compatible script grouping and the information capacity of the script information; adjusting the script information under the compatible script grouping and the script information under the incompatible script grouping according to the information capacity difference; the number of the script information under the adjusted compatible script group is the same as the number of the script information under the adjusted incompatible script group;
and determining data conversion logic information between the first intelligent device and the second intelligent device according to the one-to-one correspondence relationship between the script information under the adjusted compatible script group and the script information under the adjusted incompatible script group.
B8. The system of B7, the identification terminal, further configured to:
screening a plurality of fourth intelligent devices in the second interactive list according to the data conversion logic information to obtain at least a plurality of fifth intelligent devices; wherein the fourth smart device is a smart device that has an interaction with the second smart device within the state identification period;
determining a fifth state identification factor of each fifth intelligent device according to the step corresponding to the determination of the first intelligent device; wherein the fifth state identification factor is a direct state identification factor of the fifth smart device;
determining a third state identification factor of the second intelligent device according to the fifth state identification factor; wherein the third state identification factor is an indirect state identification factor of the second smart device.
B9. The system of B1, the identification terminal, further configured to:
determining a current information structure field of data conversion logic information, a first information structure field of the first intelligent device and a second information structure field of the second intelligent device;
determining the first data conversion loss value according to the field similarity of the first information structure field and the current information structure field;
and determining the second data conversion loss value according to the field similarity of the second information structure field and the current information structure field.
B10. The system of B9, the identification terminal, further configured to:
normalizing the first data conversion loss value and the second data conversion loss value to obtain a first loss coefficient corresponding to the first data conversion loss value and a second loss coefficient corresponding to the second data conversion loss value; wherein the first loss factor and the second loss factor are both positive numbers less than one;
determining a first product value of the first loss factor and the first global identification factor and a second product value of the second loss factor and the second global identification factor;
determining the third global identification factor based on the first and second product values.
On the basis of the above, as shown in fig. 4, there is also provided an identification terminal 200, including: a processor 801, and a memory 802 and a network interface 803 connected to the processor 801; the network interface 803 is connected with a nonvolatile memory 804 in the identification terminal 200; the processor 801, when running, retrieves a computer program from the non-volatile storage 804 via the network interface 803 and runs the computer program via the memory 802 to perform the above-described method.
On the basis, a readable storage medium applied to a computer is further provided, and a computer program is burned in the readable storage medium, and when the computer program runs in the memory 802 of the identification terminal 200, the method is implemented.
For the device embodiments, since they substantially correspond to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, wherein the modules described as separate parts may or may not be physically separate, and the parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the application. One of ordinary skill in the art can understand and implement it without inventive effort.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Claims (8)

1. An equipment state identification method based on industrial internet is characterized in that the method is applied to an identification terminal which is communicated with a plurality of intelligent equipment, the identification terminal and the intelligent equipment form an equipment state identification system, and the method at least comprises the following steps:
judging whether interactive production data exist in a digital production network formed by all intelligent equipment in the equipment state identification system; wherein the interactive production data is the production data sent by one intelligent device to another intelligent device in the digital production network;
when the interactive production data exist in the digital production network, acquiring a first state identification report and a first interactive list of first intelligent equipment which sends the interactive production data, and acquiring a second state identification report and a second interactive list of second intelligent equipment which receives the interactive production data;
determining a first state identification factor of the first intelligent device according to the first state identification report, and determining a second state identification factor of the first intelligent device according to the first interaction list; determining a first global identification factor for the first smart device based on the first state identification factor and the second state identification factor;
determining data conversion logic information between the first intelligent device and the second intelligent device, determining a third state identification factor of the second intelligent device according to the data conversion logic information and the second interactive list, and determining a fourth state identification factor of the second intelligent device according to the second state identification report; determining a second global identification factor for the second smart device based on the third state identification factor and the fourth state identification factor;
wherein:
determining a third state identification factor of the second intelligent device according to the data conversion logic information and the second interactive list, specifically including: screening a plurality of fourth intelligent devices in the second interactive list according to the data conversion logic information to obtain at least a plurality of fifth intelligent devices; wherein the fourth smart device is a smart device that has an interaction with the second smart device within the state identification period; determining a fifth state identification factor of each fifth intelligent device according to the step corresponding to the determination of the first intelligent device; wherein the fifth state identification factor is a direct state identification factor of the fifth smart device; determining a third state identification factor of the second intelligent device according to the fifth state identification factor; wherein the third state identification factor is an indirect state identification factor of the second smart device;
determining a first data conversion loss value of the first intelligent device and a second data conversion loss value of the second intelligent device from the data conversion logic information; weighting the first global identification factor and the second global identification factor based on the first data conversion loss value and the second data conversion loss value to obtain a third global identification factor;
determining a first identification interval according to a first state identification report of the first intelligent device and determining a second identification interval according to a second state identification report of the second intelligent device; and identifying the device states of the first intelligent device and the second intelligent device based on the relative position relation between the third global identification factor and the first identification interval as well as the second identification interval.
2. The method of claim 1, wherein the step of determining the device states of the first smart device and the second smart device based on the relative positional relationships of the third global identification factor to the first identification interval and to the second identification interval further comprises:
judging whether the first identification interval and the second identification interval are overlapped;
if the first identification interval and the second identification interval are overlapped; when the third global identification factor falls into the first identification interval, determining that the equipment state of the first intelligent equipment is an abnormal state and the equipment state of the second intelligent equipment is a normal state; when the third global identification factor falls into the second identification interval, determining that the equipment state of the second intelligent equipment is an abnormal state and the equipment state of the first intelligent equipment is a normal state; when the third global identification factor falls into an overlapping interval of the first identification interval and the second identification interval, determining that the equipment states of the first intelligent equipment and the second intelligent equipment are both abnormal states;
if the first identification interval and the second identification interval do not overlap; when the third global identification factor falls into the first identification interval, determining that the equipment state of the first intelligent equipment is an abnormal state and the equipment state of the second intelligent equipment is a normal state; when the third global identification factor falls into the second identification interval, determining that the equipment state of the second intelligent equipment is an abnormal state and the equipment state of the first intelligent equipment is a normal state; and when the third global identification factor does not fall into the first identification interval or the second identification interval, determining that the equipment states of the first intelligent equipment and the second intelligent equipment are normal states.
3. The method of claim 1, wherein the first status identification report of the first smart device is determined by the substeps of:
determining a target operation log with the equipment identifier of the first intelligent equipment from an operation log set corresponding to a preset state recognition thread; the state identification thread is used for carrying out state identification on the intelligent equipment when the intelligent equipment is in an idle working condition or obtaining a state identification result of the intelligent equipment from a third-party state identification equipment;
generating a first log feature set for representing the log information continuity of the target running log and a second log feature set for representing the log information category distribution of the target running log according to the target running log; the first log feature set and the second log feature set respectively comprise a plurality of feature vectors with different dimensions;
extracting an initial characteristic value of each characteristic vector of the target running log in the first log characteristic set, and determining a characteristic vector with a minimum dimension in the second log characteristic set as a target characteristic vector;
determining a current mapping value of the initial characteristic value in the target characteristic vector, and determining a mapping list between the first log characteristic set and the second log characteristic set according to the initial characteristic value and the current mapping value; determining a target vector value in the target characteristic vector values by taking the current mapping value as a reference vector value, mapping the target vector value to the characteristic vector corresponding to the initial characteristic value according to the mapping list, and determining a target characteristic value corresponding to the target vector value in the characteristic vector corresponding to the initial characteristic value;
determining a state identification result of the first intelligent device according to the difference value of the initial characteristic value and the target characteristic value; and generating a first state identification report of the first intelligent device based on all the determined state identification results.
4. The method of claim 3, wherein the first interactive manifest of the first smart device is determined by the substeps of:
acquiring communication protocol information of the first intelligent device, and determining a target protocol field for representing a communication interaction object of the first intelligent device from the communication protocol information;
extracting at least a plurality of sub-target fields from the target protocol field and determining the field characteristics corresponding to each sub-target field; wherein the field features are used for characterizing the object identification of the communication interaction object;
analyzing each field characteristic to obtain object identification information corresponding to each field characteristic; determining interaction time period information of communication interaction between each communication interaction object and the first intelligent equipment according to the object identification information; and determining a first interaction list of the first intelligent device based on the object identification information and the interaction period information corresponding to each communication interaction object.
5. The method of claim 1, wherein the steps of determining a first state identification factor for the first smart device based on the first state identification report and determining a second state identification factor for the first smart device based on the first interaction manifest comprise:
listing all state recognition results in the first state recognition report, and determining the generation time of each state recognition result; determining the time length between the starting time and the current time as the state recognition time length by taking the current time as the ending time and the generation time farthest from the current time as the starting time;
determining a time weight value of each generation moment relative to the state identification duration; the time weight value corresponding to the generation time closer to the current time is larger;
determining the proportion of a target state identification result used for representing the abnormal state of the first intelligent device in all state identification results from all state identification results;
weighting the time weight value corresponding to each target state identification result according to the occupation ratio to obtain a target weight value; weighting and summing the target weight values to obtain a first state identification factor of the first intelligent device;
determining a target state identification factor of a third intelligent device interacting with the first intelligent device in a state identification period corresponding to the state identification duration from the first interaction list, wherein the target state identification factor is determined according to the step corresponding to the first state identification factor;
and determining the mean value of all the determined target state identification factors as the second state identification factor of the first intelligent equipment.
6. The method of claim 5, wherein the step of determining the first global identification factor for the first smart device based on the first state identification factor and the second state identification factor comprises:
determining a target generation time corresponding to a target state recognition result closest to the current time in the first state recognition report;
determining a difference between the current time and the target generation time;
determining a proportional value of the difference value and the state identification duration value;
weighting the first state identification factor and the second state identification factor by respectively adopting the proportion value and the target proportion value to obtain a first global identification factor of the first intelligent device; wherein a sum of the proportional value and the target proportional value is one.
7. The method of claim 1, wherein the step of determining data conversion logic information between the first smart device and the second smart device specifically comprises:
calling a first data conversion thread of the first intelligent device and a second data conversion thread of the second intelligent device respectively, and extracting a first thread script of the first data conversion thread and a second thread script of the second data conversion thread;
determining data mapping information of the first thread script relative to the second thread script and multiple groups of same script information in the first thread script and the second thread script;
judging whether a compatibility adjustment identifier exists between the first thread script and the second thread script; when the compatibility adjustment identification exists between the first thread script and the second thread script, determining a compatible script group and an incompatible script group corresponding to the first thread script and the second thread script; at least part of script information in the multiple groups of script information is under the compatible script group, and at least part of script information in the multiple groups of script information is under the incompatible script group;
determining information capacity difference between each script information of the multiple groups of script information under the incompatible script grouping and each script information of the multiple groups of script information under the compatible script grouping according to the script information of the multiple groups of script information under the compatible script grouping and the information capacity of the script information; adjusting the script information under the compatible script grouping and the script information under the incompatible script grouping according to the information capacity difference; the number of the script information under the adjusted compatible script group is the same as the number of the script information under the adjusted incompatible script group;
and determining data conversion logic information between the first intelligent device and the second intelligent device according to the one-to-one correspondence relationship between the script information under the adjusted compatible script group and the script information under the adjusted incompatible script group.
8. An identification terminal, comprising:
a processor, and
a memory and a network interface connected with the processor;
the network interface is connected with a nonvolatile memory in the identification terminal;
the processor, when running, retrieves a computer program from the non-volatile memory via the network interface and runs the computer program via the memory to perform the method of any of claims 1-7.
CN202011384566.0A 2020-03-30 2020-03-30 Equipment state identification method and identification terminal based on industrial Internet Withdrawn CN112462715A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011384566.0A CN112462715A (en) 2020-03-30 2020-03-30 Equipment state identification method and identification terminal based on industrial Internet

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202010237403.3A CN111443669B (en) 2020-03-30 2020-03-30 Equipment state identification method and identification terminal applied to industrial Internet
CN202011384566.0A CN112462715A (en) 2020-03-30 2020-03-30 Equipment state identification method and identification terminal based on industrial Internet

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
CN202010237403.3A Division CN111443669B (en) 2020-03-30 2020-03-30 Equipment state identification method and identification terminal applied to industrial Internet

Publications (1)

Publication Number Publication Date
CN112462715A true CN112462715A (en) 2021-03-09

Family

ID=71653982

Family Applications (3)

Application Number Title Priority Date Filing Date
CN202010237403.3A Active CN111443669B (en) 2020-03-30 2020-03-30 Equipment state identification method and identification terminal applied to industrial Internet
CN202011384566.0A Withdrawn CN112462715A (en) 2020-03-30 2020-03-30 Equipment state identification method and identification terminal based on industrial Internet
CN202011384568.XA Withdrawn CN112462716A (en) 2020-03-30 2020-03-30 Equipment state identification method and system based on industrial Internet

Family Applications Before (1)

Application Number Title Priority Date Filing Date
CN202010237403.3A Active CN111443669B (en) 2020-03-30 2020-03-30 Equipment state identification method and identification terminal applied to industrial Internet

Family Applications After (1)

Application Number Title Priority Date Filing Date
CN202011384568.XA Withdrawn CN112462716A (en) 2020-03-30 2020-03-30 Equipment state identification method and system based on industrial Internet

Country Status (1)

Country Link
CN (3) CN111443669B (en)

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH08275389A (en) * 1995-03-31 1996-10-18 Mitsubishi Electric Corp Dc power device
US20070006065A1 (en) * 2005-07-01 2007-01-04 Microsoft Corporation Conditional event timing for interactive multimedia presentations
CN103544389B (en) * 2013-10-18 2018-07-10 丽水学院 Autocrane method for diagnosing faults based on fault tree and fuzzy neural network
CN104181896A (en) * 2014-08-29 2014-12-03 四川九成信息技术有限公司 Industrial control collecting state monitoring system based on Internet of Things
CN107611945B (en) * 2017-09-25 2020-05-29 国网河南省电力公司电力科学研究院 Equipment state sensing type 110kV line protection system and implementation method

Also Published As

Publication number Publication date
CN112462716A (en) 2021-03-09
CN111443669B (en) 2021-06-22
CN111443669A (en) 2020-07-24

Similar Documents

Publication Publication Date Title
CN111339363B (en) Image recognition method and device and server
CN110782240B (en) Business data processing method and device, computer equipment and storage medium
CN105590225A (en) Sales stage identification method and device based on client problems
CN111443669B (en) Equipment state identification method and identification terminal applied to industrial Internet
CN112070508B (en) Block chain payment processing method based on block chain finance and block chain payment platform
CN108881275B (en) Method and system for analyzing access compliance of user
CN111740494B (en) Data management method based on edge computing and cloud computing and edge computing platform
CN111459104B (en) Data tracking method based on industrial Internet and electronic equipment
CN113114788A (en) Service resource sharing method applied to cloud computing and digitization and cloud server
CN111935089A (en) Data processing method based on big data and edge calculation and artificial intelligence server
CN113568899A (en) Data optimization method based on big data and cloud server
CN109615919A (en) Virtual parking area user management method, server and computer readable storage medium
CN111459441B (en) Information display method and device and electronic equipment
CN114139210B (en) Big data security threat processing method and system based on intelligent service
CN111641612B (en) Data security protection method of edge computing network and communication master control device
CN113434192B (en) SDK platform-based packaging method and device and computer equipment
US20190391952A1 (en) Method and Apparatus for Device Identification Using a Serial Port
CN112600282B (en) Intelligent solar luggage charging and discharging control method and system
US20220230028A1 (en) Determination method, non-transitory computer-readable storage medium, and information processing device
CN111581512A (en) Webpage visitor number statistical method and device
CN114924973A (en) Automatic test method, device, equipment and storage medium of business system
CN114756399A (en) Fault detection method and related device
CN112532645A (en) Internet of things equipment operation data monitoring method and system and electronic equipment
CN115185848A (en) Method and device for determining number of test cases
CN114817064A (en) Automatic judgment method and device for safety test result

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
WW01 Invention patent application withdrawn after publication

Application publication date: 20210309

WW01 Invention patent application withdrawn after publication