CN116578073A - Anomaly analysis method and system of sensor signal calibration control system - Google Patents
Anomaly analysis method and system of sensor signal calibration control system Download PDFInfo
- Publication number
- CN116578073A CN116578073A CN202310856626.1A CN202310856626A CN116578073A CN 116578073 A CN116578073 A CN 116578073A CN 202310856626 A CN202310856626 A CN 202310856626A CN 116578073 A CN116578073 A CN 116578073A
- Authority
- CN
- China
- Prior art keywords
- calibration
- control system
- operation log
- system operation
- prior
- 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.)
- Granted
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 150
- 239000013598 vector Substances 0.000 claims abstract description 112
- 238000012545 processing Methods 0.000 claims abstract description 106
- 238000000034 method Methods 0.000 claims description 67
- 230000005856 abnormality Effects 0.000 claims description 66
- 230000008569 process Effects 0.000 claims description 25
- 230000002159 abnormal effect Effects 0.000 claims description 19
- 238000013473 artificial intelligence Methods 0.000 claims description 13
- 238000003860 storage Methods 0.000 claims description 13
- 238000009826 distribution Methods 0.000 claims description 9
- 238000004590 computer program Methods 0.000 claims description 7
- 238000012423 maintenance Methods 0.000 claims description 4
- 238000005065 mining Methods 0.000 abstract description 9
- 238000004519 manufacturing process Methods 0.000 description 18
- 238000012544 monitoring process Methods 0.000 description 18
- 230000005540 biological transmission Effects 0.000 description 6
- 238000012795 verification Methods 0.000 description 6
- 238000001514 detection method Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 238000013139 quantization Methods 0.000 description 4
- 238000004891 communication Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 235000019580 granularity Nutrition 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0221—Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D18/00—Testing or calibrating apparatus or arrangements provided for in groups G01D1/00 - G01D15/00
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
-
- Y—GENERAL 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Automation & Control Theory (AREA)
- Quality & Reliability (AREA)
- General Engineering & Computer Science (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
According to the anomaly analysis method and the anomaly analysis system for the sensor signal calibration control system, through the acquisition of the plurality of sensor signal calibration processing reports of the calibration control system operation log to be subjected to anomaly analysis, calibration task text description vector mining, calibration link text description vector mining and calibration result feedback information mining can be respectively carried out for each sensor signal calibration processing report, so that whether the calibration control system operation log to be subjected to anomaly analysis is the anomaly operation log or not is determined according to comparison information respectively corresponding to three types of information when the operation log is subjected to comparison analysis, the anomaly analysis is realized through the three types of information of the operation log, whether the calibration control system operation log to be subjected to anomaly analysis is the anomaly operation log can be determined based on the most description layers, and the anomaly analysis accuracy and the reliability of the calibration control system for the sensor signal calibration control system are improved based on the anomaly analysis thought of the operation log.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an anomaly analysis method and system of a sensor signal calibration control system.
Background
The sensor is a detecting device, which can sense the measured information and convert the sensed information into electric signals or other information output in the required form according to a certain rule so as to meet the requirements of information transmission, processing, storage, display, recording, control and the like. The sensor has the characteristics of microminiaturization, digitalization, intellectualization, multifunction, systemization, networking and the like, and is a primary link for realizing automatic detection and automatic control.
During the acquisition and transmission of the sensor signal, errors in the sensor signal may be caused by a series of uncontrollable factors, and thus calibration of the sensor signal is indispensable. Calibration of the sensor signals is typically achieved based on a corresponding calibration control system, but the calibration control system is also unavoidably abnormal/faulty during operation.
Disclosure of Invention
In order to improve the technical problems in the related art, the invention provides an anomaly analysis method and an anomaly analysis system for a sensor signal calibration control system.
In a first aspect, an embodiment of the present invention provides an anomaly analysis method for a sensor signal calibration control system, applied to an artificial intelligence analysis system, where the method includes:
acquiring a calibration control system operation log to be subjected to anomaly analysis, wherein the calibration control system operation log to be subjected to anomaly analysis comprises X sensor signal calibration processing reports, and X is a positive integer;
acquiring calibration task text description vectors of the X sensor signal calibration processing reports and calibration link text description vectors of the X sensor signal calibration processing reports, and acquiring calibration result feedback information of a calibration control system operation log to be subjected to anomaly analysis;
performing calibration task description comparison on the calibration task text description vectors of the X sensor signal calibration processing reports and the prior calibration task text description vectors corresponding to the operation logs of the prior calibration control system to obtain calibration task description comparison information;
performing calibration link description comparison on the calibration link text description vectors of the X sensor signal calibration processing reports and the prior calibration link text description vectors corresponding to the operation logs of the prior calibration control systems to obtain calibration link description comparison information;
Performing calibration feedback comparison on the calibration result feedback information of the calibration control system operation log to be subjected to anomaly analysis and the prior calibration result feedback information of the plurality of prior calibration control system operation logs to obtain calibration feedback comparison information;
and determining an abnormality discrimination viewpoint of the calibration control system operation log to be subjected to abnormality analysis according to the calibration task description comparison information, the calibration link description comparison information and the calibration feedback comparison information, wherein the abnormality discrimination viewpoint is used for representing whether the calibration control system operation log to be subjected to abnormality analysis is an abnormal operation log or not.
In some optional embodiments, any one of the X sensor signal calibration process reports is considered a u-th sensor signal calibration process report, any one of the plurality of a priori calibration control system operation logs is considered a v-th a priori calibration control system operation log, the v-th a priori calibration control system operation log including Y a priori sensor signal calibration process reports, u, v, Y each being a positive integer;
the calibration task description comparison is performed on the calibration task text description vectors of the X sensor signal calibration processing reports and the prior calibration task text description vectors corresponding to the operation logs of the prior calibration control system, so as to obtain calibration task description comparison information, and the method comprises the following steps:
Respectively determining overall text description commonality coefficients between the calibration task text description vectors of the u-th sensor signal calibration processing report and the prior calibration task text description vectors corresponding to the Y prior sensor signal calibration processing reports, and taking the maximum overall text description commonality coefficient as the overall text description commonality coefficient of the u-th sensor signal calibration processing report and the v-th prior calibration control system operation log until determining the overall text description commonality coefficient of each sensor signal calibration processing report in the X sensor signal calibration processing reports and the v-th prior calibration control system operation log;
determining the overall text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the v priori calibration control system operation log according to the overall text description commonality coefficient between each sensor signal calibration processing report in the X sensor signal calibration processing reports and the v priori calibration control system operation log respectively until the overall text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the multiple priori calibration control system operation logs is determined;
And determining the calibration task description comparison information according to the overall text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the multiple prior calibration control system operation logs.
In some optional embodiments, any one of the X sensor signal calibration process reports is considered a u-th sensor signal calibration process report, any one of the plurality of a priori calibration control system operation logs is considered a v-th a priori calibration control system operation log, the v-th a priori calibration control system operation log including Y a priori sensor signal calibration process reports, u, v, Y each being a positive integer;
and comparing the calibration link text description vectors of the X sensor signal calibration processing reports with the prior calibration link text description vectors corresponding to the prior calibration control system operation logs to obtain calibration link description comparison information, wherein the method comprises the following steps:
determining phase text description commonality coefficients between the calibration link text description vectors of the u-th sensor signal calibration processing report and the prior calibration link text description vectors corresponding to the Y prior sensor signal calibration processing reports respectively, and taking the maximum phase text description commonality coefficient as the phase text description commonality coefficients of the u-th sensor signal calibration processing report and the v-th prior calibration control system operation log until determining the phase text description commonality coefficients of each sensor signal calibration processing report in the X sensor signal calibration processing reports and the v-th prior calibration control system operation log respectively;
Determining a phase text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the v priori calibration control system operation log according to the phase text description commonality coefficient between each sensor signal calibration processing report in the X sensor signal calibration processing reports and the v priori calibration control system operation log respectively until determining the phase text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the multiple priori calibration control system operation logs;
and determining the calibration link description comparison information according to the phase text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the multiple prior calibration control system operation logs.
In some optional embodiments, the performing calibration feedback comparison between the calibration result feedback information of the calibration control system operation log to be subjected to anomaly analysis and the prior calibration result feedback information of the multiple prior calibration control system operation logs to obtain calibration feedback comparison information includes:
determining calibration feedback commonality coefficients between the calibration result feedback information of the calibration control system operation log to be subjected to anomaly analysis and the prior calibration result feedback information of each prior calibration control system operation log respectively;
And determining the calibration feedback comparison information according to the calibration feedback commonality coefficient.
In some alternative embodiments, the method further comprises:
acquiring a plurality of prior calibration control system operation logs, wherein each prior calibration control system operation log comprises Y prior sensor signal calibration processing reports;
acquiring prior calibration task text description vectors of Y prior sensor signal calibration processing reports of each prior calibration control system operation log and prior calibration link text description vectors of the Y prior sensor signal calibration processing reports, and acquiring prior calibration result feedback information of each prior calibration control system operation log;
and correspondingly importing the prior calibration task text description vectors of the Y prior sensor signal calibration processing reports of each prior calibration control system operation log, the prior calibration link text description vectors of the Y prior sensor signal calibration processing reports and the prior calibration result feedback information of each prior calibration control system operation log into a cloud sharing server, wherein the cloud sharing server comprises prior calibration task text description vectors, prior calibration link text description vectors and prior calibration result feedback information corresponding to the prior calibration control system operation logs.
In some alternative embodiments, the method further comprises:
acquiring prior operation log keywords of each prior calibration control system operation log and distribution feature labels of prior calibration task text description vectors of each prior calibration control system operation log in the cloud sharing server;
generating a query catalog according to the prior operation log keywords of each prior calibration control system operation log and the distribution characteristic labels;
the calibration task description comparison is performed on the calibration task text description vectors of the X sensor signal calibration processing reports and the prior calibration task text description vectors corresponding to the operation logs of the prior calibration control system, so as to obtain calibration task description comparison information, and the method comprises the following steps:
acquiring the operation log keywords of the calibration control system operation log to be subjected to anomaly analysis, and determining an initial operation log keyword set from the query catalog according to the operation log keywords of the calibration control system operation log to be subjected to anomaly analysis;
determining a priori calibration task text description vector corresponding to the initial operation log keyword set according to a distribution feature tag associated with the initial operation log keyword set in the query catalog;
And carrying out calibration task description comparison on the calibration task text description vectors of the X sensor signal calibration processing reports and the prior calibration task text description vectors corresponding to the initial operation log keyword set to obtain calibration task description comparison information.
In some optional embodiments, the determining the abnormality discrimination point of the calibration control system operation log to be subjected to the abnormality analysis according to the calibration task description comparison information, the calibration link description comparison information and the calibration feedback comparison information includes:
acquiring the kind of the related sensing signals of the calibration control system operation log to be subjected to anomaly analysis, and determining a target sensing calibration event corresponding to the calibration control system operation log to be subjected to anomaly analysis according to the kind of the related sensing signals;
acquiring a first confidence factor corresponding to a calibration task text description vector, a second confidence factor corresponding to a calibration link text description vector and a third confidence factor corresponding to calibration result feedback information under the target sensing calibration event;
and determining an abnormality discrimination viewpoint of the calibration control system operation log to be subjected to abnormality analysis according to the first confidence factor, the calibration task description comparison information, the second confidence factor, the calibration link description comparison information, the third confidence factor and the calibration feedback comparison information.
In some alternative embodiments, the method further comprises:
if the abnormality discrimination point of the calibration control system operation log to be subjected to abnormality analysis reflects that the calibration control system operation log to be subjected to abnormality analysis is not the abnormality operation log, sharing the calibration control system operation log to be subjected to abnormality analysis;
if the abnormality discrimination viewpoint of the calibration control system operation log to be subjected to abnormality analysis reflects that the calibration control system operation log to be subjected to abnormality analysis is an abnormality label, generating an abnormality early warning message, wherein the abnormality early warning message is used for indicating maintenance of a sensor signal calibration control system corresponding to the calibration control system operation log to be subjected to abnormality analysis;
and if the calibration control system operation log corresponding to the maintained sensor signal calibration control system is obtained and is not an abnormal operation log, sharing the calibration control system operation log corresponding to the maintained sensor signal calibration control system.
In a second aspect, the present invention also provides an artificial intelligence analysis system, comprising a processor and a memory; the processor is in communication with the memory, and the processor is configured to read and execute a computer program from the memory to implement the method described above.
In a third aspect, the present invention also provides a computer-readable storage medium having stored thereon a program which, when executed by a processor, implements the method described above.
According to the embodiment of the invention, the calibration task text description vector mining, the calibration link text description vector mining and the calibration result feedback information mining can be respectively carried out for each sensor signal calibration processing report by acquiring a plurality of sensor signal calibration processing reports of the calibration control system operation log to be subjected to the anomaly analysis, so that when the operation log is compared and analyzed, the comparison and analysis can be carried out according to the three types of mined information, whether the calibration control system operation log to be subjected to the anomaly analysis is the anomaly operation log or not is determined according to the comparison information corresponding to the three types of information, and in view of the anomaly analysis realized through the three types of information of the operation log, whether the calibration control system operation log to be subjected to the anomaly analysis is the anomaly operation log can be determined based on the most description layers, thereby improving the anomaly analysis precision and the reliability of the calibration control system for the sensor signal based on the anomaly analysis thought of the operation log.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a flow chart of an anomaly analysis method of a sensor signal calibration control system according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the invention. Rather, they are merely examples of apparatus and methods consistent with aspects of the invention as detailed in the accompanying claims.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.
The method embodiments provided by the embodiments of the present invention may be implemented in an artificial intelligence analysis system, a computer device, or similar computing device. Taking the example of operation on an artificial intelligence analysis system, the artificial intelligence analysis system may include one or more processors (which may include, but is not limited to, a microprocessor MCU, a programmable logic device FPGA, etc. processing means) and memory for storing data, and optionally, transmission means for communication functions. It will be appreciated by those of ordinary skill in the art that the above-described structure is merely illustrative and is not intended to limit the structure of the artificial intelligence analysis system. For example, the artificial intelligence analysis system can also include more or fewer components than shown above, or have a different configuration than shown above.
The memory may be used to store a computer program, for example, a software program of application software and a module, such as a computer program corresponding to an anomaly analysis method of a sensor signal calibration control system in an embodiment of the present invention, and the processor executes the computer program stored in the memory, thereby performing various functional applications and data processing, that is, implementing the above-mentioned method. The memory may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid state memory. In some examples, the memory may further include memory remotely located with respect to the processor, the remote memory being connectable to the artificial intelligence analysis system through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission means is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communications provider of an artificial intelligence analysis system. In one example, the transmission means comprises a network adapter (Network Interface Controller, simply referred to as NIC) that can be connected to other network devices via a base station to communicate with the internet. In one example, the transmission device may be a Radio Frequency (RF) module, which is used to communicate with the internet wirelessly.
Based on this, referring to fig. 1, fig. 1 is a flowchart of an anomaly analysis method of a sensor signal calibration control system according to an embodiment of the present invention, where the method is applied to an artificial intelligence analysis system, and further may include S101-S106.
S101, an artificial intelligent analysis system acquires a calibration control system operation log to be subjected to anomaly analysis.
The calibration control system operation log to be subjected to anomaly analysis comprises X sensor signal calibration processing reports, wherein X is a positive integer.
In some examples, the calibration control system log to be subjected to anomaly analysis may be understood as a log of the operation of the sensor signal calibration control system when performing calibration control on the corresponding sensor signal.
Further, the sensor includes various types such as a resistive sensor, an inductive sensor, a capacitive sensor, a piezoelectric sensor, a magneto-electric sensor, a thermo-electric sensor, a photoelectric sensor, a digital sensor, an optical fiber sensor, an ultrasonic sensor, a thermal sensor, an analog sensor, and the like. The calibration control system for the sensor signals acquired by the different types of sensors can be selected adaptively as well, which is not shown here. Still further, the sensor signal calibration process report may be understood as a calibration process record in text form.
S102, acquiring calibration task text description vectors of the X sensor signal calibration processing reports and calibration link text description vectors of the X sensor signal calibration processing reports, and acquiring calibration result feedback information of a calibration control system operation log to be subjected to anomaly analysis.
In the embodiment of the invention, the calibration task text description vector and the calibration link text description vector are respectively used for representing the global report text characteristic and the local report text characteristic of the corresponding sensor signal calibration processing report. When the calibration control processing is performed on the sensor signal, the sensor signal calibration control system usually performs corresponding calibration task link splitting processing according to a complete calibration control task, and then performs orderly calibration control based on the split calibration task links so as to realize the processing of the sensor signal. Thus, the calibration task text description vector and the calibration link text description vector can reflect the characteristics of the sensor signal calibration process report from different granularities. As another example, the sensor signal calibration process report may include a record in text form of the initial sensor signal, calibration control parameters, calibration signals, etc.,
Further, the calibration result feedback information of the calibration control system operation log to be subjected to anomaly analysis can be understood as: after the calibration signal corresponding to the calibration control system operation log to be subjected to anomaly analysis is returned to the request end, the request end performs opinion feedback after use according to the calibration signal, and the opinion feedback can represent the signal calibration quality of the sensor signal calibration control system corresponding to the calibration control system operation log to be subjected to anomaly analysis.
S103, performing calibration task description comparison on the calibration task text description vectors of the X sensor signal calibration processing reports and the prior calibration task text description vectors corresponding to the prior calibration control system operation logs to obtain calibration task description comparison information.
And S104, performing calibration link description comparison on the calibration link text description vectors of the X sensor signal calibration processing reports and the prior calibration link text description vectors corresponding to the prior calibration control system operation logs to obtain calibration link description comparison information.
S105, performing calibration feedback comparison on the calibration result feedback information of the calibration control system operation log to be subjected to anomaly analysis and the prior calibration result feedback information of the plurality of prior calibration control system operation logs to obtain calibration feedback comparison information.
For S103-S105, the a priori calibration control system operation log may be a calibration control system operation log used as a reference for anomaly analysis, for example, an authenticated calibration control system operation log, or for example, a historical calibration control system operation log. Based on the above, the prior calibration task text description vector, the prior calibration link text description vector and the prior calibration result feedback information can also be respectively used as references of the calibration task text description vector, the calibration link text description vector and the calibration result feedback information.
S106, determining an abnormality judgment view of the calibration control system operation log to be subjected to abnormality analysis according to the calibration task description comparison information, the calibration link description comparison information and the calibration feedback comparison information.
In the embodiment of the invention, the calibration task description comparison, the calibration link description comparison and the calibration feedback comparison described in S103-S105 are three different steps for carrying out the abnormality analysis, and the feature dimensions concerned by the three different steps are different, so that the abnormality analysis of the operation log of the calibration control system can be comprehensively and comprehensively realized as much as possible, and whether the abnormality/fault exists in the sensor signal calibration control system or not is judged.
In S106, the anomaly discrimination viewpoint is used to characterize whether the calibration control system operation log to be subjected to anomaly analysis is an anomaly operation log. In the embodiment of the invention, the abnormal operation log can reflect the abnormality/fault of the sensor signal calibration control system corresponding to the operation log of the calibration control system to be subjected to abnormality analysis, and the abnormal point/fault point, such as hardware structure fault abnormality or software system fault abnormality, can be further determined through the dissimilarity of the calibration task description comparison, the calibration link description comparison and the calibration feedback comparison.
It can be seen that, through S101-S106, by acquiring a plurality of sensor signal calibration processing reports of the calibration control system operation log to be subjected to anomaly analysis, calibration task text description vector mining, calibration link text description vector mining, and calibration result feedback information mining can be performed for each sensor signal calibration processing report, so that when the operation log is compared and analyzed, it can be implemented according to three types of information mined, and according to comparison information corresponding to the three types of information, whether the calibration control system operation log to be subjected to anomaly analysis is an anomaly operation log is determined, and in view of implementing anomaly analysis through the three types of information of the operation log, whether the calibration control system operation log to be subjected to anomaly analysis is an anomaly operation log can be determined based on as many description levels, thereby improving anomaly analysis accuracy and reliability of the calibration control system for sensor signals based on the anomaly analysis concept of the operation log.
In some possible embodiments, any one of the X sensor signal calibration process reports is treated as a u-th sensor signal calibration process report, any one of the plurality of a priori calibration control system operation logs is treated as a v-th a priori calibration control system operation log comprising Y a priori sensor signal calibration process reports, u, v, Y being positive integers. On this basis, the calibration task text description vector of the calibration processing report of the X sensor signals in S103 is compared with the prior calibration task text description vectors corresponding to the operation logs of the multiple prior calibration control systems to obtain calibration task description comparison information, including S1031-S1033.
S1031, determining overall text description commonality coefficients between the calibration task text description vectors of the u-th sensor signal calibration processing report and the prior calibration task text description vectors corresponding to the Y prior sensor signal calibration processing reports respectively, and taking the maximum overall text description commonality coefficient as the overall text description commonality coefficient of the u-th sensor signal calibration processing report and the v-th prior calibration control system operation log until determining the overall text description commonality coefficient of each sensor signal calibration processing report in the X-th sensor signal calibration processing reports and the v-th prior calibration control system operation log respectively.
In the embodiment of the invention, the overall text description commonality coefficient can be understood as the similarity of text description vectors/text characteristics under the global level.
S1032, determining the overall text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the v priori calibration control system operation log according to the overall text description commonality coefficient between each sensor signal calibration processing report in the X sensor signal calibration processing reports and the v priori calibration control system operation log respectively until determining the overall text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the multiple priori calibration control system operation logs.
S1033, determining the calibration task description comparison information according to the overall text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the multiple prior calibration control system operation logs.
In the embodiment of the invention, when the calibration task description comparison information is determined, the realization of the integral text description commonality coefficient based on each sensor signal calibration processing report and each prior sensor signal calibration processing report can be realized, the integral text description commonality coefficient of each sensor signal calibration processing report and the v-th prior calibration control system operation log is determined through the maximum integral text description commonality coefficient, and the integral text description commonality coefficient between the calibration control system operation log to be subjected to abnormal analysis and a plurality of prior calibration control system operation logs is further determined, so that the omission of the integral text description commonality coefficient determination can be avoided, and the integrity of the calibration task description comparison information is ensured.
In some possible embodiments, any one of the X sensor signal calibration process reports is treated as a u-th sensor signal calibration process report, any one of the plurality of a priori calibration control system operation logs is treated as a v-th a priori calibration control system operation log comprising Y a priori sensor signal calibration process reports, u, v, Y being positive integers. On this basis, the calibration link text description vector of the calibration processing report of the X sensor signals in S104 is compared with the prior calibration link text description vectors corresponding to the operation logs of the multiple prior calibration control systems to obtain calibration link description comparison information, including S1041-S1043.
S1041, determining phase text description commonality coefficients between the calibration link text description vector of the u-th sensor signal calibration processing report and the prior calibration link text description vectors corresponding to the Y prior sensor signal calibration processing reports respectively, and taking the maximum phase text description commonality coefficient as the phase text description commonality coefficient of the u-th sensor signal calibration processing report and the v-th prior calibration control system operation log until determining the phase text description commonality coefficient of each sensor signal calibration processing report in the X-th sensor signal calibration processing reports and the v-th prior calibration control system operation log respectively.
In the embodiment of the invention, the stage text description commonality coefficient can be understood as the similarity of text description vectors/text characteristics under the local level.
S1042, determining a phase text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the v priori calibration control system operation log according to the phase text description commonality coefficient between each sensor signal calibration processing report in the X sensor signal calibration processing reports and the v priori calibration control system operation log respectively until determining the phase text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the multiple priori calibration control system operation logs.
S1043, determining the calibration link description comparison information according to the phase text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the multiple prior calibration control system operation logs.
In the embodiment of the invention, when determining the calibration link description comparison information, the method can be realized based on the phase text description commonality coefficient of each sensor signal calibration processing report and each prior sensor signal calibration processing report, and the phase text description commonality coefficient of each sensor signal calibration processing report and the v-th prior calibration control system operation log is determined through the maximum phase text description commonality coefficient, and the phase text description commonality coefficient between the calibration control system operation log to be subjected to abnormal analysis and a plurality of prior calibration control system operation logs is further determined, so that the omission of the determination of the phase text description commonality coefficient can be avoided, and the integrity of the calibration link description comparison information is ensured.
In other possible embodiments, the comparing the calibration result feedback information of the calibration control system operation log to be subjected to the anomaly analysis with the prior calibration result feedback information of the multiple prior calibration control system operation logs in S105 includes S1051 and S1052.
S1051, determining calibration feedback commonality coefficients between the calibration result feedback information of the calibration control system operation log to be subjected to anomaly analysis and the prior calibration result feedback information of each prior calibration control system operation log respectively.
The calibration feedback commonality coefficient can be understood as the similarity of text information among feedback information of different calibration results.
S1052, determining the calibration feedback comparison information according to the calibration feedback commonality coefficient.
It can be appreciated that by S1051 and S1052, calibration feedback comparison information can be accurately determined based on the quantized calibration feedback commonality coefficients.
In some alternative embodiments, the method further comprises S201-S203.
S201, acquiring a plurality of prior calibration control system operation logs, wherein each prior calibration control system operation log comprises Y prior sensor signal calibration processing reports.
S202, acquiring prior calibration task text description vectors of Y prior sensor signal calibration processing reports of each prior calibration control system operation log and prior calibration link text description vectors of the Y prior sensor signal calibration processing reports, and acquiring prior calibration result feedback information of each prior calibration control system operation log.
S203, the prior calibration task text description vectors of the Y prior sensor signal calibration processing reports of each prior calibration control system operation log, the prior calibration link text description vectors of the Y prior sensor signal calibration processing reports and the prior calibration result feedback information of each prior calibration control system operation log are correspondingly imported into the cloud sharing server.
The cloud sharing server comprises prior calibration task text description vectors, prior calibration link text description vectors and prior calibration result feedback information corresponding to the operation logs of the prior calibration control systems.
It can be appreciated that, by applying S201-S203, after the prior calibration control system running log, the prior sensor signal calibration processing report, the prior calibration task text description vector, the prior calibration link text description vector and the prior calibration result feedback information are obtained, the reference data information can be stored in the cloud sharing server, so that when the reference data information needs to be used, the reference data information can be called by the cloud sharing server, and the storage pressure of the artificial intelligent analysis system is reduced.
In other alternative embodiments, the method further comprises S301 and S302.
S301, acquiring prior running log keywords of each prior calibration control system running log and distribution feature labels of prior calibration task text description vectors of each prior calibration control system running log in the cloud sharing server.
S302, generating a query catalog according to the prior running log keywords of each prior calibration control system running log and the distribution characteristic labels.
The prior running log keywords are used for distinguishing different prior calibration control system running logs, the distributed feature labels are used for reflecting storage positions or storage addresses of prior calibration task text description vectors of the prior calibration control system running logs in the cloud sharing server, and based on the storage positions or storage addresses, query catalogues can be generated by combining the prior running log keywords and the distributed feature labels.
Based on S301 and S302, the calibration task text description vector of the X sensor signal calibration processing reports in S103 is compared with the prior calibration task text description vectors corresponding to the multiple prior calibration control system operation logs to obtain calibration task description comparison information, which includes S103a-S103c.
S103a, acquiring operation log keywords of the calibration control system operation log to be subjected to anomaly analysis, and determining an initial operation log keyword set from the query catalog according to the operation log keywords of the calibration control system operation log to be subjected to anomaly analysis;
s103b, calling a priori calibration task text description vector corresponding to the initial running log keyword set from a distribution feature tag associated with the initial running log keyword set in the query catalog.
And S103c, performing calibration task description comparison on the calibration task text description vectors of the X sensor signal calibration processing reports and the priori calibration task text description vectors corresponding to the initial operation log keyword set to obtain calibration task description comparison information.
By the design, based on the S103a-S103c, the prior calibration task text description vector can be quickly fetched, so that the timeliness of the calibration task description comparison is improved, and the calibration task description comparison information can be efficiently determined.
In some possible embodiments, the determining in S106 an abnormality determination view of the calibration control system operation log to be subjected to an abnormality analysis according to the calibration task description comparison information, the calibration link description comparison information, and the calibration feedback comparison information includes S1061-S1063.
S1061, acquiring the kind of the related sensing signal of the calibration control system operation log to be subjected to anomaly analysis, and determining a target sensing calibration event corresponding to the calibration control system operation log to be subjected to anomaly analysis according to the kind of the related sensing signal.
In the embodiment of the invention, the type of the sensor signals involved in the operation log of the calibration control system to be subjected to anomaly analysis can be understood as the type of the sensor signals to be calibrated by the sensor signal calibration control system, and the target sensor calibration event can be understood as the calibration scene of the sensor signals.
S1062, obtaining a first confidence factor corresponding to the calibration task text description vector, a second confidence factor corresponding to the calibration link text description vector and a third confidence factor corresponding to the calibration result feedback information under the target sensing calibration event.
In the embodiment of the invention, the confidence factor can be understood as an importance weight or a contribution coefficient, and is used for reflecting the importance of information in different dimensions.
S1063, determining an abnormality discrimination viewpoint of the calibration control system operation log to be subjected to abnormality analysis according to the first confidence factor, the calibration task description comparison information, the second confidence factor, the calibration link description comparison information, the third confidence factor and the calibration feedback comparison information.
In the embodiment of the invention, when determining the abnormality discrimination viewpoint, weighting processing can be performed according to the importance of the information of different dimensions, so as to obtain the abnormality discrimination viewpoint of the calibration control system operation log to be subjected to abnormality analysis. For example, the quantitative weighted summation of the calibration task description comparison information, the calibration link description comparison information and the calibration feedback comparison information can be realized through the first confidence factor, the second confidence factor and the third confidence factor, so that the quantitative abnormal judgment view (for example, the value range of the abnormal judgment view can be between 0 and 1) can be accurately and rapidly obtained.
In some alternative embodiments, the method further comprises: if the abnormality discrimination point of the calibration control system operation log to be subjected to abnormality analysis reflects that the calibration control system operation log to be subjected to abnormality analysis is not the abnormality operation log, sharing the calibration control system operation log to be subjected to abnormality analysis; if the abnormality discrimination viewpoint of the calibration control system operation log to be subjected to abnormality analysis reflects that the calibration control system operation log to be subjected to abnormality analysis is an abnormality label, generating an abnormality early warning message, wherein the abnormality early warning message is used for indicating maintenance of a sensor signal calibration control system corresponding to the calibration control system operation log to be subjected to abnormality analysis; and if the calibration control system operation log corresponding to the maintained sensor signal calibration control system is obtained and is not an abnormal operation log, sharing the calibration control system operation log corresponding to the maintained sensor signal calibration control system.
In the embodiment of the present invention, the abnormal judgment view may be analyzed according to a preset view quantization threshold, for example, the view quantization threshold is set to 0.5, if the quantization value corresponding to the abnormal judgment view is higher than 0.5, the calibration control system operation log to be subjected to the abnormal analysis is determined to be the abnormal operation log, and if the quantization value corresponding to the abnormal judgment view is not higher than 0.5, the calibration control system operation log to be subjected to the abnormal analysis is determined not to be the abnormal operation log. When the calibration control system operation log to be subjected to anomaly analysis is not the anomaly operation log, the calibration control system operation log to be subjected to anomaly analysis can be shared, otherwise, the corresponding sensor signal calibration control system can be subjected to maintenance processing, so that the correctness of sensor signal calibration control performed later is ensured.
In some independent embodiments, the sharing the calibration control system log to be subjected to anomaly analysis includes: when a shared access request aiming at the calibration control system operation log to be subjected to anomaly analysis is received, carrying out safety check on a target sensor production monitoring server corresponding to the shared access request; and on the premise that the target sensor production monitoring server passes the safety check, sharing the operation log of the calibration control system to be subjected to anomaly analysis to the target sensor production monitoring server.
Therefore, the calibration control system operation log sharing to be subjected to anomaly analysis can be realized on the premise of passing the safety check, so that the safety of operation log sharing is ensured.
In some independent embodiments, the security check is performed on the target sensor production monitoring server corresponding to the shared access request, including S401-S403.
S401, acquiring a first data wind control detection vector and a first vulnerability scanning text vector of a target sensor production monitoring server, and acquiring a second data wind control detection vector and a second vulnerability scanning text vector of a reference sensor production monitoring server.
S402, determining whether a wind control safety check conclusion of the target sensor production monitoring server and a wind control safety check conclusion of the reference sensor production monitoring server meet a commonality analysis condition according to the first data wind control detection vector and the second data wind control detection vector, and determining whether a vulnerability protection check conclusion of the target sensor production monitoring server and a vulnerability protection check conclusion of the reference sensor production monitoring server meet the commonality analysis condition according to the first vulnerability scanning text vector and the second vulnerability scanning text vector.
S403, if the wind control safety check conclusion of the target sensor production monitoring server and the wind control safety check conclusion of the reference sensor production monitoring server meet the commonality analysis conditions, and the vulnerability protection check conclusion of the target sensor production monitoring server and the vulnerability protection check conclusion of the reference sensor production monitoring server meet the commonality analysis conditions, judging that the target sensor production monitoring server passes the safety check.
In the embodiment of the invention, when the safety verification of the target sensor production monitoring server is carried out, the reference sensor production monitoring server can be utilized to judge the common analysis conditions (the similarity between different wind control safety verification conclusions and the similarity between different vulnerability protection verification conclusions) of the wind control safety verification conclusions and the vulnerability protection verification conclusions from two dimensions of data wind control and vulnerability scanning, so that the safety verification of the target sensor production monitoring server can be rapidly and accurately realized by utilizing the common analysis thought.
Further, there is also provided a computer-readable storage medium having stored thereon a program which, when executed by a processor, implements the above-described method.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. The apparatus and method embodiments described above are merely illustrative, for example, flow diagrams and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present invention may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a network device, or the like) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An anomaly analysis method for a sensor signal calibration control system, the method being applied to an artificial intelligence analysis system, the method comprising:
acquiring a calibration control system operation log to be subjected to anomaly analysis, wherein the calibration control system operation log to be subjected to anomaly analysis comprises X sensor signal calibration processing reports, and X is a positive integer;
acquiring calibration task text description vectors of the X sensor signal calibration processing reports and calibration link text description vectors of the X sensor signal calibration processing reports, and acquiring calibration result feedback information of a calibration control system operation log to be subjected to anomaly analysis;
performing calibration task description comparison on the calibration task text description vectors of the X sensor signal calibration processing reports and the prior calibration task text description vectors corresponding to the operation logs of the prior calibration control system to obtain calibration task description comparison information;
Performing calibration link description comparison on the calibration link text description vectors of the X sensor signal calibration processing reports and the prior calibration link text description vectors corresponding to the operation logs of the prior calibration control systems to obtain calibration link description comparison information;
performing calibration feedback comparison on the calibration result feedback information of the calibration control system operation log to be subjected to anomaly analysis and the prior calibration result feedback information of the plurality of prior calibration control system operation logs to obtain calibration feedback comparison information;
and determining an abnormality discrimination viewpoint of the calibration control system operation log to be subjected to abnormality analysis according to the calibration task description comparison information, the calibration link description comparison information and the calibration feedback comparison information, wherein the abnormality discrimination viewpoint is used for representing whether the calibration control system operation log to be subjected to abnormality analysis is an abnormal operation log or not.
2. The method of claim 1, wherein any one of the X sensor signal calibration process reports is treated as a u-th sensor signal calibration process report, any one of the plurality of a priori calibration control system operation logs is treated as a v-th a priori calibration control system operation log comprising Y a priori sensor signal calibration process reports, u, v, Y being positive integers;
The calibration task description comparison is performed on the calibration task text description vectors of the X sensor signal calibration processing reports and the prior calibration task text description vectors corresponding to the operation logs of the prior calibration control system, so as to obtain calibration task description comparison information, and the method comprises the following steps:
respectively determining overall text description commonality coefficients between the calibration task text description vectors of the u-th sensor signal calibration processing report and the prior calibration task text description vectors corresponding to the Y prior sensor signal calibration processing reports, and taking the maximum overall text description commonality coefficient as the overall text description commonality coefficient of the u-th sensor signal calibration processing report and the v-th prior calibration control system operation log until determining the overall text description commonality coefficient of each sensor signal calibration processing report in the X sensor signal calibration processing reports and the v-th prior calibration control system operation log;
determining the overall text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the v priori calibration control system operation log according to the overall text description commonality coefficient between each sensor signal calibration processing report in the X sensor signal calibration processing reports and the v priori calibration control system operation log respectively until the overall text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the multiple priori calibration control system operation logs is determined;
And determining the calibration task description comparison information according to the overall text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the multiple prior calibration control system operation logs.
3. The method of claim 1, wherein any one of the X sensor signal calibration process reports is treated as a u-th sensor signal calibration process report, any one of the plurality of a priori calibration control system operation logs is treated as a v-th a priori calibration control system operation log comprising Y a priori sensor signal calibration process reports, u, v, Y being positive integers;
and comparing the calibration link text description vectors of the X sensor signal calibration processing reports with the prior calibration link text description vectors corresponding to the prior calibration control system operation logs to obtain calibration link description comparison information, wherein the method comprises the following steps:
determining phase text description commonality coefficients between the calibration link text description vectors of the u-th sensor signal calibration processing report and the prior calibration link text description vectors corresponding to the Y prior sensor signal calibration processing reports respectively, and taking the maximum phase text description commonality coefficient as the phase text description commonality coefficients of the u-th sensor signal calibration processing report and the v-th prior calibration control system operation log until determining the phase text description commonality coefficients of each sensor signal calibration processing report in the X sensor signal calibration processing reports and the v-th prior calibration control system operation log respectively;
Determining a phase text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the v priori calibration control system operation log according to the phase text description commonality coefficient between each sensor signal calibration processing report in the X sensor signal calibration processing reports and the v priori calibration control system operation log respectively until determining the phase text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the multiple priori calibration control system operation logs;
and determining the calibration link description comparison information according to the phase text description commonality coefficient between the calibration control system operation log to be subjected to anomaly analysis and the multiple prior calibration control system operation logs.
4. A method according to claim 2 or 3, wherein said comparing the calibration result feedback information of the calibration control system operation log to be subjected to anomaly analysis with the prior calibration result feedback information of the plurality of prior calibration control system operation logs to obtain calibration feedback comparison information comprises:
determining calibration feedback commonality coefficients between the calibration result feedback information of the calibration control system operation log to be subjected to anomaly analysis and the prior calibration result feedback information of each prior calibration control system operation log respectively;
And determining the calibration feedback comparison information according to the calibration feedback commonality coefficient.
5. The method of claim 4, wherein the method further comprises:
acquiring a plurality of prior calibration control system operation logs, wherein each prior calibration control system operation log comprises Y prior sensor signal calibration processing reports;
acquiring prior calibration task text description vectors of Y prior sensor signal calibration processing reports of each prior calibration control system operation log and prior calibration link text description vectors of the Y prior sensor signal calibration processing reports, and acquiring prior calibration result feedback information of each prior calibration control system operation log;
and correspondingly importing the prior calibration task text description vectors of the Y prior sensor signal calibration processing reports of each prior calibration control system operation log, the prior calibration link text description vectors of the Y prior sensor signal calibration processing reports and the prior calibration result feedback information of each prior calibration control system operation log into a cloud sharing server, wherein the cloud sharing server comprises prior calibration task text description vectors, prior calibration link text description vectors and prior calibration result feedback information corresponding to the prior calibration control system operation logs.
6. The method of claim 5, wherein the method further comprises:
acquiring prior operation log keywords of each prior calibration control system operation log and distribution feature labels of prior calibration task text description vectors of each prior calibration control system operation log in the cloud sharing server;
generating a query catalog according to the prior operation log keywords of each prior calibration control system operation log and the distribution characteristic labels;
the calibration task description comparison is performed on the calibration task text description vectors of the X sensor signal calibration processing reports and the prior calibration task text description vectors corresponding to the operation logs of the prior calibration control system, so as to obtain calibration task description comparison information, and the method comprises the following steps:
acquiring the operation log keywords of the calibration control system operation log to be subjected to anomaly analysis, and determining an initial operation log keyword set from the query catalog according to the operation log keywords of the calibration control system operation log to be subjected to anomaly analysis;
determining a priori calibration task text description vector corresponding to the initial operation log keyword set according to a distribution feature tag associated with the initial operation log keyword set in the query catalog;
And carrying out calibration task description comparison on the calibration task text description vectors of the X sensor signal calibration processing reports and the prior calibration task text description vectors corresponding to the initial operation log keyword set to obtain calibration task description comparison information.
7. The method of claim 1, wherein determining an anomaly discrimination view of the calibration control system operation log to be subjected to anomaly analysis based on the calibration task description comparison information, the calibration link description comparison information, and the calibration feedback comparison information comprises:
acquiring the kind of the related sensing signals of the calibration control system operation log to be subjected to anomaly analysis, and determining a target sensing calibration event corresponding to the calibration control system operation log to be subjected to anomaly analysis according to the kind of the related sensing signals;
acquiring a first confidence factor corresponding to a calibration task text description vector, a second confidence factor corresponding to a calibration link text description vector and a third confidence factor corresponding to calibration result feedback information under the target sensing calibration event;
and determining an abnormality discrimination viewpoint of the calibration control system operation log to be subjected to abnormality analysis according to the first confidence factor, the calibration task description comparison information, the second confidence factor, the calibration link description comparison information, the third confidence factor and the calibration feedback comparison information.
8. The method of claim 1, wherein the method further comprises:
if the abnormality discrimination point of the calibration control system operation log to be subjected to abnormality analysis reflects that the calibration control system operation log to be subjected to abnormality analysis is not the abnormality operation log, sharing the calibration control system operation log to be subjected to abnormality analysis;
if the abnormality discrimination viewpoint of the calibration control system operation log to be subjected to abnormality analysis reflects that the calibration control system operation log to be subjected to abnormality analysis is an abnormality label, generating an abnormality early warning message, wherein the abnormality early warning message is used for indicating maintenance of a sensor signal calibration control system corresponding to the calibration control system operation log to be subjected to abnormality analysis;
and if the calibration control system operation log corresponding to the maintained sensor signal calibration control system is obtained and is not an abnormal operation log, sharing the calibration control system operation log corresponding to the maintained sensor signal calibration control system.
9. An artificial intelligence analysis system comprising a processor and a memory; the processor is communicatively connected to the memory, the processor being configured to read a computer program from the memory and execute the computer program to implement the method of any of claims 1-8.
10. A computer readable storage medium, characterized in that a program is stored thereon, which program, when being executed by a processor, implements the method of any of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310856626.1A CN116578073B (en) | 2023-07-13 | 2023-07-13 | Anomaly analysis method and system of sensor signal calibration control system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310856626.1A CN116578073B (en) | 2023-07-13 | 2023-07-13 | Anomaly analysis method and system of sensor signal calibration control system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116578073A true CN116578073A (en) | 2023-08-11 |
| CN116578073B CN116578073B (en) | 2023-10-03 |
Family
ID=87541733
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310856626.1A Active CN116578073B (en) | 2023-07-13 | 2023-07-13 | Anomaly analysis method and system of sensor signal calibration control system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116578073B (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120330596A1 (en) * | 2011-06-21 | 2012-12-27 | General Electric Company | Self-calibrating sensor, system, and computer program product |
| US20180174065A1 (en) * | 2016-12-15 | 2018-06-21 | Nec Laboratories America, Inc. | Content-Level Anomaly Detection for Heterogeneous Logs |
| CN109165234A (en) * | 2018-09-19 | 2019-01-08 | 北京云迹科技有限公司 | Robot exception analysis method and device |
| CN110132305A (en) * | 2019-04-28 | 2019-08-16 | 浙江吉利控股集团有限公司 | A kind of real-time calibration method and device |
| CN112000806A (en) * | 2020-08-25 | 2020-11-27 | 携程旅游信息技术（上海）有限公司 | Abnormal log monitoring and analyzing method, system, equipment and storage medium |
| CN112585433A (en) * | 2018-08-22 | 2021-03-30 | 罗伯特·博世有限公司 | Method for calibrating a sensor of a device and sensor system |
| CN114329454A (en) * | 2022-01-12 | 2022-04-12 | 云南云数据科技有限公司 | Threat analysis method and system based on application software big data |
| CN115860836A (en) * | 2022-12-07 | 2023-03-28 | 广东南粤分享汇控股有限公司 | E-commerce service pushing method and system based on user behavior big data analysis |
| CN116126945A (en) * | 2023-03-30 | 2023-05-16 | 创域智能(常熟)网联科技有限公司 | Sensor running state analysis method and system based on data analysis |
-
2023
- 2023-07-13 CN CN202310856626.1A patent/CN116578073B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120330596A1 (en) * | 2011-06-21 | 2012-12-27 | General Electric Company | Self-calibrating sensor, system, and computer program product |
| US20180174065A1 (en) * | 2016-12-15 | 2018-06-21 | Nec Laboratories America, Inc. | Content-Level Anomaly Detection for Heterogeneous Logs |
| CN112585433A (en) * | 2018-08-22 | 2021-03-30 | 罗伯特·博世有限公司 | Method for calibrating a sensor of a device and sensor system |
| CN109165234A (en) * | 2018-09-19 | 2019-01-08 | 北京云迹科技有限公司 | Robot exception analysis method and device |
| CN110132305A (en) * | 2019-04-28 | 2019-08-16 | 浙江吉利控股集团有限公司 | A kind of real-time calibration method and device |
| CN112000806A (en) * | 2020-08-25 | 2020-11-27 | 携程旅游信息技术（上海）有限公司 | Abnormal log monitoring and analyzing method, system, equipment and storage medium |
| CN114329454A (en) * | 2022-01-12 | 2022-04-12 | 云南云数据科技有限公司 | Threat analysis method and system based on application software big data |
| CN115860836A (en) * | 2022-12-07 | 2023-03-28 | 广东南粤分享汇控股有限公司 | E-commerce service pushing method and system based on user behavior big data analysis |
| CN116126945A (en) * | 2023-03-30 | 2023-05-16 | 创域智能(常熟)网联科技有限公司 | Sensor running state analysis method and system based on data analysis |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116578073B (en) | 2023-10-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109587001B (en) | Performance index abnormality detection method and device | |
| CN111178760B (en) | Risk monitoring method, risk monitoring device, terminal equipment and computer readable storage medium | |
| CN110888783A (en) | Monitoring method and device of micro-service system and electronic equipment | |
| CN112003838B (en) | Network threat detection method, device, electronic device and storage medium | |
| CN108985057B (en) | Webshell detection method and related equipment | |
| CN113489713B (en) | Network attack detection method, device, equipment and storage medium | |
| CN111866024B (en) | Network encryption traffic identification method and device | |
| CN112073393B (en) | Flow detection method based on cloud computing and user behavior analysis | |
| US20170293757A1 (en) | Systems and Methods for Enhancing Control System Security by Detecting Anomalies in Descriptive Characteristics of Data | |
| US20210224383A1 (en) | Abnormality detection device | |
| WO2017093783A1 (en) | Network security agent | |
| CN114079579B (en) | Malicious encryption traffic detection method and device | |
| US20180181871A1 (en) | Apparatus and method for detecting abnormal event using statistics | |
| EP3883190B1 (en) | Detection device, detection method, and detection program | |
| CN110162973B (en) | Webshell file detection method and device | |
| CN116578073B (en) | Anomaly analysis method and system of sensor signal calibration control system | |
| CN112380073B (en) | Fault position detection method and device and readable storage medium | |
| CN115932144B (en) | Chromatograph performance detection method, chromatograph performance detection device, chromatograph performance detection equipment and computer medium | |
| EP3631637B1 (en) | System, device and method for frozen period detection in sensor datasets | |
| CN116939661A (en) | SIM card abnormality detection method and system, electronic equipment and storage medium | |
| JP6574310B2 (en) | Evaluation information matching method, apparatus and server | |
| US20230246935A1 (en) | Detecting behavioral change of iot devices using novelty detection based behavior traffic modeling | |
| CN114650218B (en) | Data acquisition method, device, system and storage medium | |
| EP3937461A1 (en) | Data service tracker module for a communication system and method of determining a set of data couplings | |
| CN110098983B (en) | Abnormal flow detection method and device |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |