CN116628470B - Voltage source data real-time supervision system and method based on artificial intelligence - Google Patents
Voltage source data real-time supervision system and method based on artificial intelligence Download PDFInfo
- Publication number
- CN116628470B CN116628470B CN202310378618.0A CN202310378618A CN116628470B CN 116628470 B CN116628470 B CN 116628470B CN 202310378618 A CN202310378618 A CN 202310378618A CN 116628470 B CN116628470 B CN 116628470B
- Authority
- CN
- China
- Prior art keywords
- application
- voltage source
- parameter
- target
- characteristic
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 17
- 238000004458 analytical method Methods 0.000 claims abstract description 68
- 238000012544 monitoring process Methods 0.000 claims abstract description 61
- 238000010276 construction Methods 0.000 claims abstract description 11
- 230000004044 response Effects 0.000 claims description 61
- 230000002159 abnormal effect Effects 0.000 claims description 46
- 238000004364 calculation method Methods 0.000 claims description 19
- 238000011161 development Methods 0.000 claims description 12
- 108010053481 Antifreeze Proteins Proteins 0.000 claims description 8
- 230000007774 longterm Effects 0.000 claims description 7
- 238000011835 investigation Methods 0.000 claims description 6
- 238000012163 sequencing technique Methods 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 5
- 238000013461 design Methods 0.000 description 5
- 230000009471 action Effects 0.000 description 3
- 238000005259 measurement Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008520 organization Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/10—Pre-processing; Data cleansing
- G06F18/15—Statistical pre-processing, e.g. techniques for normalisation or restoring missing data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Physics & Mathematics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Computation (AREA)
- Bioinformatics & Cheminformatics (AREA)
- General Engineering & Computer Science (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Evolutionary Biology (AREA)
- Business, Economics & Management (AREA)
- Economics (AREA)
- Health & Medical Sciences (AREA)
- Public Health (AREA)
- Probability & Statistics with Applications (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The application relates to the technical field of voltage source data supervision, in particular to a voltage source data real-time supervision system and method based on artificial intelligence, comprising a historical state database module, a feature set construction module, an application characteristic value analysis module, a multi-element target parameter determination module and a reference priority analysis module; the historical state database module is used for acquiring historical state data recorded in a period from the completion of the specification setting of the voltage source to the implementation of the application corresponding monitoring; the feature set construction module is used for constructing a feature set of an application environment where the reference voltage source parameter data are located; the application characteristic value analysis module is used for analyzing application characteristic values corresponding to the parameter data of the reference voltage source; the multi-element target parameter determining module is used for extracting a plurality of reference voltage source parameters with the same application environment as multi-element target parameters; the reference priority analysis module is used for analyzing the reference priority of the same application environment in the target feature set, wherein the reference priority comprises multiple target parameters applied to the specification setting of the reference voltage source.
Description
Technical Field
The application relates to the technical field of voltage source data supervision, in particular to a voltage source data real-time supervision system and method based on artificial intelligence.
Background
Whether it be an automobile, microwave oven or cell phone, all electronic devices must interact with the "real" world in some way. For this reason, the electronic device must be able to map real world measurements to measurable quantities in the electronic world; of course, to measure the voltage, a measurement standard is required, the standard is the reference voltage, and it is necessary for the system designer to manually analyze and determine what kind of reference voltage source is used, when considering various parameter changes in the specification setting of the reference voltage source, the required manual analysis cost will increase, and the difficulty and error rate of the specification setting of the reference voltage source will also increase; and different manual decisions may deviate from the design of the same circuit in terms of priority in view of parameter settings.
Disclosure of Invention
The application aims to provide a voltage source data real-time supervision system and method based on artificial intelligence so as to solve the problems in the background technology.
In order to solve the technical problems, the application provides the following technical scheme: the voltage source data real-time supervision method based on artificial intelligence comprises the following analysis steps:
step S1: acquiring historical state data recorded in a monitoring period corresponding to the implementation of the voltage source specification setting, wherein the monitoring period comprises a development setting period corresponding to the voltage source specification setting and an application monitoring period corresponding to the implementation of the application process, and the historical state data comprises reference voltage source parameter data of the development setting period and product abnormal response data recorded in the application monitoring period; based on the historical state data, constructing a feature set of an application environment in which the reference voltage source parameter data are located;
step S2: based on the feature set, analyzing application characteristic values corresponding to each parameter data of the reference voltage source;
step S3: comparing and analyzing feature sets corresponding to different reference voltage source parameters, extracting a plurality of reference voltage source parameters with the same application environment as a plurality of target parameters, and outputting the feature sets corresponding to the plurality of target parameters as target feature sets;
step S4: and acquiring application characteristic values corresponding to the multiple target parameters, and analyzing the reference priority of the multiple target parameters applied to the specification setting of the voltage source in the same application environment in the target characteristic set.
Further, in step S1, a feature set of an application environment where the reference voltage source parameter data is located is constructed, which includes the following analysis steps:
parameters which need to be considered in the development and setting period of the reference voltage source are obtained, wherein the parameters comprise initial precision, temperature coefficient, thermal hysteresis, long-term stability and low-frequency noise;
extracting reference voltage source data corresponding to any parameter value set in the historical data and other parameter value sets which are the same as target voltage source data, and acquiring physical environment characteristics of an application monitoring period of the target voltage source data, wherein the physical environment characteristics refer to phase characteristics of stable response generated by reference voltage source application after parameter setting is completed; the phase characteristics of the stable response are attribute characteristics of the corresponding phase when the abnormal response frequency of the target voltage source data is lowest in the application;
acquiring application environments corresponding to the phase characteristics meeting the stable response, wherein the application environments refer to application scenes in which the phase characteristics requirements of the same target voltage source data corresponding to the stable response exist;
constructing a feature set A, A { x, y, z } taking target voltage source data as a root node, physical environment features as a first child node and an application environment as a second child node; wherein x represents the corresponding target voltage source data after any parameter is set, y represents the physical environment characteristic corresponding to the target voltage source data, and z represents the application environment corresponding to the stage characteristic meeting the stable response; any parameter setting means that the parameter value settings are the same and the remaining parameter value settings are different.
The feature set is constructed because the initial design of the reference voltage source often needs to be manually combined with the application scene of the product and the specificity of the subsequent actual application scene, and the design of different parameters is used for solving different actual problems, so when the physical environment features corresponding to the different parameters are distinguished, the application environments corresponding to the different parameters are extracted through artificial intelligence on the premise of controlling the variables to be distinguished; the data can be effectively input into the system to effectively analyze the real-time data of the reference voltage source.
Further, the step S2 includes the following analysis steps:
acquiring product abnormal response data in an application monitoring period to which an ith parameter belongs, wherein the product abnormal response data comprises characteristics of abnormal response events and the occurrence number of the abnormal response events; the characteristics of the abnormal response event refer to the phase characteristics of the abnormal event which occur in the same kind of attribute as the physical environment characteristics;
the characteristic of the abnormal response event in the application monitoring period after the ith parameter setting is obtained is thatThe target event feature, when the target event feature is the same as the physical environment feature y corresponding to the first child node in the feature set to which the ith parameter belongs, the output feature value is U i The method comprises the steps of carrying out a first treatment on the surface of the When the target event feature is different from the physical environment feature y corresponding to the first child node in the i-th parameter corresponding feature set, outputting a feature value of V i The method comprises the steps of carrying out a first treatment on the surface of the Using the formula:
W i ＝U i *(g i1 /G i )+V i *(g i2 /G i )
calculating a first characteristic value W after the ith parameter setting in the application monitoring period i The method comprises the steps of carrying out a first treatment on the surface of the Wherein U is i >V i ，
g i1 The number of the events which exist when the target event characteristics are the same as the physical environment characteristics y corresponding to the first child node in the characteristic set to which the ith parameter belongs is represented;
g i2 representing the number of events in which the target event features and the physical environment features y corresponding to the first child node in the feature set to which the i-th parameter belongs are different;
G i indicating the total number of abnormal response events in the application monitoring period after the ith parameter is set;
the first characteristic value is a numerical value showing the characteristic of the parameter itself in the actual application by analyzing the physical environment characteristic and other physical environment characteristics corresponding to the parameter setting, and the larger the first characteristic value is, the larger the difficulty of setting and analyzing the analyzed parameter is;
the specific values of the other parameters corresponding to the i-th parameter after setting are obtained as oriented parameter values, the setting parameters are target parameters, the historical data corresponding to any identical oriented parameter values and different target parameter values are obtained as investigation parameter data, the abnormal response data of the investigation parameter data in the application monitoring period are obtained, and the formula is utilized:
Q i ＝|r i1 -r i2 |/r i0
calculating a second characteristic value Q after the ith parameter setting in the application monitoring period i ，
Wherein r is i1 To indicate that the application requirement is not satisfiedThe number of abnormal response events in the application monitoring period when the target parameter is set, r i2 Representing the occurrence number of abnormal response events in the application monitoring period when the target parameter setting corresponding to the application requirement is met, r i0 R represents i1 And r i2 Average value of (2); meeting the application requirement refers to setting a parameter value when the occurrence number of the abnormal response events is smaller than the abnormal event threshold value after setting the target parameter;
the second characteristic value reflects the deviation degree of the influence on the system under the condition of the same parameter setting and non-setting, and the larger the second characteristic value is, the larger the influence on the system is caused by the fact that the parameter setting is not finished, and the more important the parameter is;
using the formula: p (P) i ＝e 1 *W i +e 2 *Q i The method comprises the steps of carrying out a first treatment on the surface of the Calculating an application characteristic value P corresponding to the ith parameter of the reference voltage source i The method comprises the steps of carrying out a first treatment on the surface of the Wherein e 1 A reference coefficient, e, representing a first characteristic value 2 A reference coefficient representing a second characteristic value; e, e 1 +e 2 ＝1，0<e 1 、e 2 <1。
Further, step S3 includes the following analysis steps:
acquiring a feature set Ai { x, y, z } corresponding to the ith parameter;
extracting application environments in feature sets of m parameters as application environments to be analyzed, performing intersection analysis on the application environments to be analyzed to generate a first set, wherein the intersection analysis generates the first set as { z } 1 ∩z 2 ,z 1 ∩z 2 ∩z 3 ,......,z m-1 ∩z m -a }; wherein z is 1 、z 2 、......、z m Express application environments to be analyzed corresponding to the 1 st, 2 nd..third..m. parameters; intersection analysis is a combination of any parameter corresponding to the application environment to be analyzed; the first set is a set formed by all combinations;
extracting parameters corresponding to the intersection analysis result which is not the empty set as multiple target parameters;
and outputting the feature set corresponding to the multiple target parameters as a target feature set.
The analysis target feature set indicates that a plurality of parameters to be set exist in the same application environment.
Further, the step S4 includes the following analysis steps:
acquiring a j-th multi-element target parameter contained in the same application environment, and extracting an application characteristic value corresponding to the multi-element target parameter;
when the application characteristic values are different, sorting the multiple target parameters from large to small according to the numerical values of the application characteristic values to generate reference priority;
when the application characteristic values are the same, acquiring a characteristic set to which the same application characteristic value corresponds to a multi-element target parameter, and extracting a duration proportion of an existing application monitoring period of physical environment characteristics in the characteristic set, wherein the duration proportion refers to a ratio of response duration corresponding to the physical environment characteristics to total duration of the application monitoring period; and sequencing the multiple target parameters corresponding to the same application characteristic value from large to small according to the duration proportion value to generate the reference priority.
Priority when multiple parameters are required to be set in the same application environment are analyzed, and the system analysis parameter organization and resource reasonable allocation by artificial intelligence are facilitated.
The voltage source data real-time supervision system comprises a historical state database module, a feature set construction module, an application characteristic value analysis module, a multi-element target parameter determination module and a reference priority analysis module;
the historical state database module is used for acquiring historical state data recorded in a period from the completion of the specification setting of the voltage source to the implementation of the application corresponding monitoring;
the characteristic set construction module is used for constructing a characteristic set of an application environment where the reference voltage source parameter data are based on the historical state data;
the application characteristic value analysis module is used for analyzing application characteristic values corresponding to the parameter data of the reference voltage source;
the multi-element target parameter determining module is used for carrying out comparison analysis on feature sets corresponding to different reference voltage source parameters, and extracting a plurality of reference voltage source parameters with the same application environment as multi-element target parameters;
the reference priority analysis module is used for acquiring application characteristic values corresponding to the multiple target parameters, and analyzing the reference priority of the same application environment in the target feature set, which is applied to the specification setting of the reference voltage source, of the multiple target parameters.
Further, the feature set construction module comprises a reference data determination unit, a target voltage source data determination unit, a physical environment feature determination unit, an application environment determination unit and a feature set output unit;
the reference data determining unit is used for obtaining parameters which are required to be considered by the reference voltage source in a development and setting period, wherein the parameters comprise initial precision, temperature coefficient, thermal hysteresis, long-term stability and low-frequency noise;
the target voltage source data determining unit is used for extracting reference voltage source data corresponding to any parameter value set in the historical data which is the same and the other parameter value sets are different as target voltage source data;
the physical environment characteristic determining unit is used for obtaining physical environment characteristics of the application monitoring period where the target voltage source data are located;
the application environment determining unit is used for obtaining an application environment corresponding to the phase characteristics meeting the stable response;
the feature set output unit is used for constructing a feature set which takes target voltage source data as a root node, physical environment features as a first sub-node and application environment as a second sub-node.
Further, the application characteristic value analysis module comprises a first characteristic value calculation unit, a second characteristic value calculation unit and an application characteristic value calculation unit;
the first characteristic value calculation unit is used for calculating a first characteristic value based on the number of the events when the target event features correspond to the physical environment features in the feature set;
the second characteristic value calculation unit is used for calculating a second characteristic value based on the number of events when the target parameter corresponds to the physical environment characteristic in the characteristic set;
the application characteristic value calculation unit is used for calculating an output application characteristic value based on the first characteristic value and the second characteristic value.
Further, the reference priority analysis module comprises a parameter sequencing unit, a duration proportion analysis unit and a priority output unit;
the parameter sorting unit is used for sorting the multiple target parameters from large to small according to the magnitude of the application characteristic value;
the time length proportion analysis unit is used for analyzing the time length proportion of the existing application monitoring period of the physical environment characteristics in the characteristic set when the application characteristic values are the same, so as to determine the sequence;
the priority output unit is used for outputting the reference priority based on the parameter ranking result and the ranking result determined by the duration proportion analysis unit.
Compared with the prior art, the application has the following beneficial effects: according to the application, the historical state data recorded in the corresponding monitoring period from the completion of the specification setting of the voltage source to the implementation and application is divided through artificial intelligence, the parameters required to be considered in the reference voltage source setting are taken as root nodes to construct a feature set, and the application environments corresponding to different parameters are extracted and distinguished through artificial intelligence on the premise of controlling variables; the data can be effectively input into the system to effectively analyze the real-time data of the reference voltage source; the system can rapidly position the parameter data and the corresponding physical environment characteristics and application scenes; in addition, after the feature set is analyzed, the application characteristic values of different parameters are digitized, and the setting priority of the parameters under the condition that various parameters exist in the historical data are considered is analyzed; the system analysis parameters are organized by the artificial intelligence, and the resources are reasonably allocated; manual calculation force is reduced, so that system analysis is more intelligent.
Drawings
The accompanying drawings are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate the application and together with the embodiments of the application, serve to explain the application. In the drawings:
FIG. 1 is a schematic diagram of a voltage source data real-time supervision system based on artificial intelligence.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Referring to fig. 1, the present application provides the following technical solutions: the voltage source data real-time supervision method based on artificial intelligence comprises the following analysis steps:
step S1: acquiring historical state data recorded in a monitoring period corresponding to the implementation of the voltage source specification setting, wherein the monitoring period comprises a development setting period corresponding to the voltage source specification setting and an application monitoring period corresponding to the implementation of the application process, and the historical state data comprises reference voltage source parameter data of the development setting period and product abnormal response data recorded in the application monitoring period; based on the historical state data, constructing a feature set of an application environment in which the reference voltage source parameter data are located;
step S2: based on the feature set, analyzing application characteristic values corresponding to each parameter data of the reference voltage source; the application characteristic value refers to the importance degree, stability and precision of the data of different parameters of the reference voltage source;
step S3: comparing and analyzing feature sets corresponding to different reference voltage source parameters, extracting a plurality of reference voltage source parameters with the same application environment as a plurality of target parameters, and outputting the feature sets corresponding to the plurality of target parameters as target feature sets;
step S4: and acquiring application characteristic values corresponding to the multiple target parameters, and analyzing the reference priority of the multiple target parameters applied to the specification setting of the voltage source in the same application environment in the target characteristic set.
In step S1, a feature set of an application environment where the reference voltage source parameter data is located is constructed, which includes the following analysis steps:
parameters which need to be considered in the development and setting period of the reference voltage source are obtained, wherein the parameters comprise initial precision, temperature coefficient, thermal hysteresis, long-term stability and low-frequency noise;
extracting reference voltage source data corresponding to any parameter value set in the historical data and other parameter value sets which are the same as target voltage source data, and acquiring physical environment characteristics of an application monitoring period of the target voltage source data, wherein the physical environment characteristics refer to phase characteristics of stable response generated by reference voltage source application after parameter setting is completed; the phase characteristics of the stable response are attribute characteristics of the corresponding phase when the abnormal response frequency of the target voltage source data is lowest in the application;
acquiring application environments corresponding to the phase characteristics meeting the stable response, wherein the application environments refer to application scenes in which the phase characteristics requirements of the same target voltage source data corresponding to the stable response exist;
constructing a feature set A, A { x, y, z } taking target voltage source data as a root node, physical environment features as a first child node and an application environment as a second child node; wherein x represents the corresponding target voltage source data after any parameter is set, y represents the physical environment characteristic corresponding to the target voltage source data, and z represents the application environment corresponding to the stage characteristic meeting the stable response; any parameter setting means that the parameter value settings are the same and the remaining parameter value settings are different.
If the factor considered when setting the standard of the reference voltage source is a temperature coefficient, and the stage with the lowest abnormal response frequency in the practical application after the setting of the reference voltage source is that the system experiences low temperature, the physical environment characteristic corresponding to the temperature coefficient is a low-temperature attribute characteristic; the corresponding application environment may be a factory automation control application and wherein the environment may deviate from a scenario corresponding to a comfortable room temperature setting.
The feature set is constructed because the initial design of the reference voltage source often needs to be manually combined with the application scene of the product and the specificity of the subsequent actual application scene, and the design of different parameters is used for solving different actual problems, so when the physical environment features corresponding to the different parameters are distinguished, the application environments corresponding to the different parameters are extracted through artificial intelligence on the premise of controlling the variables to be distinguished; the data can be effectively input into the system to effectively analyze the real-time data of the reference voltage source.
The step S2 includes the following analysis steps:
acquiring product abnormal response data in an application monitoring period to which an ith parameter belongs, wherein the product abnormal response data comprises characteristics of abnormal response events and the occurrence number of the abnormal response events; the characteristics of the abnormal response event refer to the phase characteristics of the abnormal event which occur in the same kind of attribute as the physical environment characteristics; if the physical environment feature corresponding to the analysis setting parameter is a low-temperature attribute feature, the stage feature of the same type attribute as the physical environment feature, i.e. the low-temperature attribute feature, can be a high-temperature attribute feature, a low-noise attribute feature, a long-term drift attribute feature, and the like;
acquiring an abnormal response event characteristic as a target event characteristic in an application monitoring period after setting an ith parameter, and outputting a characteristic value as U when the target event characteristic is the same as a physical environment characteristic y corresponding to a first child node in a characteristic set to which the ith parameter belongs i The method comprises the steps of carrying out a first treatment on the surface of the When the target event feature is different from the physical environment feature y corresponding to the first child node in the i-th parameter corresponding feature set, outputting a feature value of V i The method comprises the steps of carrying out a first treatment on the surface of the Using the formula:
W i ＝U i *(g i1 /G i )+V i *(g i2 /G i )
calculating a first characteristic value W after the ith parameter setting in the application monitoring period i The method comprises the steps of carrying out a first treatment on the surface of the Wherein U is i >V i ，
g i1 The number of the events which exist when the target event characteristics are the same as the physical environment characteristics y corresponding to the first child node in the characteristic set to which the ith parameter belongs is represented;
g i2 representing the number of events in which the target event features and the physical environment features y corresponding to the first child node in the feature set to which the i-th parameter belongs are different;
G i indicating the total number of abnormal response events in the application monitoring period after the ith parameter is set;
the first characteristic value is a numerical value showing the characteristic of the parameter itself in the actual application by analyzing the physical environment characteristic and other physical environment characteristics corresponding to the parameter setting, and the larger the first characteristic value is, the larger the difficulty of setting and analyzing the analyzed parameter is;
the specific values of the other parameters corresponding to the i-th parameter after setting are obtained as oriented parameter values, the setting parameters are target parameters, the historical data corresponding to any identical oriented parameter values and different target parameter values are obtained as investigation parameter data, the abnormal response data of the investigation parameter data in the application monitoring period are obtained, and the formula is utilized:
Q i ＝|r i1 -r i2 |/r i0
calculating a second characteristic value Q after the ith parameter setting in the application monitoring period i ，
Wherein r is i1 Indicating the occurrence number of abnormal response events in the application monitoring period when the target parameter setting corresponding to the application requirement is not met, r i2 Representing the occurrence number of abnormal response events in the application monitoring period when the target parameter setting corresponding to the application requirement is met, r i0 R represents i1 And r i2 Average value of (2); meeting the application requirement refers to setting a parameter value when the occurrence number of the abnormal response events is smaller than the abnormal event threshold value after setting the target parameter;
the second characteristic value reflects the deviation degree of the influence on the system under the condition of the same parameter setting and non-setting, and the larger the second characteristic value is, the larger the influence on the system is caused by the fact that the parameter setting is not finished, and the more important the parameter is;
using the formula: p (P) i ＝e 1 *W i +e 2 *Q i The method comprises the steps of carrying out a first treatment on the surface of the Calculating an application characteristic value P corresponding to the ith parameter of the reference voltage source i The method comprises the steps of carrying out a first treatment on the surface of the Wherein e 1 A reference coefficient, e, representing a first characteristic value 2 A reference coefficient representing a second characteristic value; e, e 1 +e 2 ＝1，0<e 1 、e 2 <1。
Step S3 comprises the following analysis steps:
acquiring a feature set Ai { x, y, z } corresponding to the ith parameter;
extracting application environments in the feature set of m parameters as application environments to be analyzed, and waiting for analysisAnalyzing the application environment to generate a first set by intersection analysis, wherein the first set is { z }, and 1 ∩z 2 ,z 1 ∩z 2 ∩z 3 ,......,z m-1 ∩z m -a }; wherein z is 1 、z 2 、......、z m Express application environments to be analyzed corresponding to the 1 st, 2 nd..third..m. parameters; intersection analysis is a combination of any parameter corresponding to the application environment to be analyzed; the first set is a set formed by all combinations;
if there are 3 parameters, intersection analysis can be performed as: z 1 ∩z 2 ，z 1 ∩z 3 ，z 2 ∩z 3 ，z 1 ∩z 2 ∩z 3 ；
Extracting parameters corresponding to the intersection analysis result which is not the empty set as multiple target parameters;
and outputting the feature set corresponding to the multiple target parameters as a target feature set.
The analysis target feature set indicates that a plurality of parameters to be set exist in the same application environment.
The step S4 includes the following analysis steps:
acquiring a j-th multi-element target parameter contained in the same application environment, and extracting an application characteristic value corresponding to the multi-element target parameter;
when the application characteristic values are different, sorting the multiple target parameters from large to small according to the numerical values of the application characteristic values to generate reference priority;
when the application characteristic values are the same, acquiring a characteristic set to which the same application characteristic value corresponds to a multi-element target parameter, and extracting a duration proportion of an existing application monitoring period of physical environment characteristics in the characteristic set, wherein the duration proportion refers to a ratio of response duration corresponding to the physical environment characteristics to total duration of the application monitoring period; and sequencing the multiple target parameters corresponding to the same application characteristic value from large to small according to the duration proportion value to generate the reference priority.
As shown in the examples: when the application characteristic values are all 0.5, and the multi-element target parameters are respectively low-frequency noise and thermal stagnation, extracting the physical environment characteristics corresponding to the low-frequency noise as low-noise characteristics, and the physical environment characteristics corresponding to the thermal stagnation as cycle height Wen Tezheng; and the duration of the low-frequency noise corresponding to the application monitoring period is 2h, the duration of the thermal hysteresis corresponding to the application monitoring period is 3h, and the total duration of the application monitoring period is 12h, 3/12>2/12, and the reference priority of the output thermal hysteresis parameter setting is larger than the low-frequency noise.
Priority when multiple parameters are required to be set in the same application environment are analyzed, and the system analysis parameter organization and resource reasonable allocation by artificial intelligence are facilitated.
The voltage source data real-time supervision system comprises a historical state database module, a feature set construction module, an application characteristic value analysis module, a multi-element target parameter determination module and a reference priority analysis module;
the historical state database module is used for acquiring historical state data recorded in a period from the completion of the specification setting of the voltage source to the implementation of the application corresponding monitoring;
the characteristic set construction module is used for constructing a characteristic set of an application environment where the reference voltage source parameter data are based on the historical state data;
the application characteristic value analysis module is used for analyzing application characteristic values corresponding to the parameter data of the reference voltage source;
the multi-element target parameter determining module is used for carrying out comparison analysis on feature sets corresponding to different reference voltage source parameters, and extracting a plurality of reference voltage source parameters with the same application environment as multi-element target parameters;
the reference priority analysis module is used for acquiring application characteristic values corresponding to the multiple target parameters, and analyzing the reference priority of the same application environment in the target feature set, which is applied to the specification setting of the reference voltage source, of the multiple target parameters.
The feature set construction module comprises a reference data determination unit, a target voltage source data determination unit, a physical environment feature determination unit, an application environment determination unit and a feature set output unit;
the reference data determining unit is used for obtaining parameters which are required to be considered by the reference voltage source in a development and setting period, wherein the parameters comprise initial precision, temperature coefficient, thermal hysteresis, long-term stability and low-frequency noise;
the target voltage source data determining unit is used for extracting reference voltage source data corresponding to any parameter value set in the historical data which is the same and the other parameter value sets are different as target voltage source data;
the physical environment characteristic determining unit is used for obtaining physical environment characteristics of the application monitoring period where the target voltage source data are located;
the application environment determining unit is used for obtaining an application environment corresponding to the phase characteristics meeting the stable response;
the feature set output unit is used for constructing a feature set which takes target voltage source data as a root node, physical environment features as a first sub-node and application environment as a second sub-node.
The application characteristic value analysis module comprises a first characteristic value calculation unit, a second characteristic value calculation unit and an application characteristic value calculation unit;
the first characteristic value calculation unit is used for calculating a first characteristic value based on the number of the events when the target event features correspond to the physical environment features in the feature set;
the second characteristic value calculation unit is used for calculating a second characteristic value based on the number of events when the target parameter corresponds to the physical environment characteristic in the characteristic set;
the application characteristic value calculation unit is used for calculating an output application characteristic value based on the first characteristic value and the second characteristic value.
The reference priority analysis module comprises a parameter sequencing unit, a duration proportion analysis unit and a priority output unit;
the parameter sorting unit is used for sorting the multiple target parameters from large to small according to the magnitude of the application characteristic value;
the time length proportion analysis unit is used for analyzing the time length proportion of the existing application monitoring period of the physical environment characteristics in the characteristic set when the application characteristic values are the same, so as to determine the sequence;
the priority output unit is used for outputting the reference priority based on the parameter ranking result and the ranking result determined by the duration proportion analysis unit.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, 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.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present application, and the present application is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present application has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (5)
1. The voltage source data real-time supervision method based on artificial intelligence is characterized by comprising the following analysis steps:
step S1: acquiring historical state data recorded in a monitoring period corresponding to the implementation of the voltage source specification, wherein the monitoring period comprises a development setting period corresponding to the voltage source specification and an application monitoring period corresponding to the implementation of the application process, and the historical state data comprises reference voltage source parameter data of the development setting period and product abnormal response data recorded in the application monitoring period; based on the historical state data, constructing a feature set of an application environment in which the reference voltage source parameter data are located;
in the step S1, a feature set of an application environment where the reference voltage source parameter data is located is constructed, which includes the following analysis steps:
parameters which need to be considered in the development and setting period of the reference voltage source are obtained, wherein the parameters comprise initial precision, temperature coefficient, thermal hysteresis, long-term stability and low-frequency noise;
extracting reference voltage source data corresponding to any parameter value set in the historical data and other parameter value sets which are the same as target voltage source data, and acquiring physical environment characteristics of an application monitoring period of the target voltage source data, wherein the physical environment characteristics are phase characteristics of stable response generated by reference voltage source application after parameter setting is completed; the phase characteristic of the stable response is the attribute characteristic of the corresponding phase when the abnormal response frequency of the target voltage source data is lowest in the application;
acquiring application environments corresponding to the phase characteristics meeting the stable response, wherein the application environments refer to application scenes in which the phase characteristic requirements of the same target voltage source data corresponding to the stable response exist;
constructing a feature set A, A { x, y, z } taking target voltage source data as a root node, physical environment features as a first child node and an application environment as a second child node; wherein x represents the corresponding target voltage source data after any parameter is set, y represents the physical environment characteristic corresponding to the target voltage source data, and z represents the application environment corresponding to the stage characteristic meeting the stable response; any parameter setting means that the parameter values are the same, and the rest parameter values are different;
step S2: based on the feature set, analyzing application characteristic values corresponding to each parameter data of the reference voltage source;
the step S2 includes the following analysis steps:
acquiring product abnormal response data in an application monitoring period to which an ith parameter belongs, wherein the product abnormal response data comprises characteristics of abnormal response events and the occurrence number of the abnormal response events; the characteristics of the abnormal response event refer to the phase characteristics of the abnormal event which occur in the same type of attribute as the physical environment characteristics;
acquiring an abnormal response event characteristic as a target event characteristic in an application monitoring period after setting an ith parameter, and when the target event characteristic and a first sub-component in a characteristic set to which the ith parameter belongsWhen the physical environment characteristics y corresponding to the nodes are the same, the output characteristic value is U i The method comprises the steps of carrying out a first treatment on the surface of the When the target event feature is different from the physical environment feature y corresponding to the first child node in the i-th parameter corresponding feature set, outputting a feature value of V i The method comprises the steps of carrying out a first treatment on the surface of the Using the formula:
W i ＝U i *(g i1 /G i )+V i *(g i2 /G i )
calculating a first characteristic value W after the ith parameter setting in the application monitoring period i The method comprises the steps of carrying out a first treatment on the surface of the Wherein U is i >V i ，
g i1 The number of the events which exist when the target event characteristics are the same as the physical environment characteristics y corresponding to the first child node in the characteristic set to which the ith parameter belongs is represented;
g i2 representing the number of events in which the target event features and the physical environment features y corresponding to the first child node in the feature set to which the i-th parameter belongs are different;
G i indicating the total number of abnormal response events in the application monitoring period after the ith parameter is set;
the specific values of the other parameters corresponding to the i-th parameter after setting are obtained as oriented parameter values, the setting parameters are target parameters, the historical data corresponding to any identical oriented parameter values and different target parameter values are obtained as investigation parameter data, the abnormal response data of the investigation parameter data in the application monitoring period are obtained, and the formula is utilized:
Q i ＝|r i1 -r i2 |/r i0
calculating a second characteristic value Q after the ith parameter setting in the application monitoring period i ，
Wherein r is i1 Indicating the occurrence number of abnormal response events in the application monitoring period when the target parameter setting corresponding to the application requirement is not met, r i2 Representing the occurrence number of abnormal response events in the application monitoring period when the target parameter setting corresponding to the application requirement is met, r i0 R represents i1 And r i2 Average value of (2); the meeting of the application requirement means that the occurrence number of the abnormal response events after the setting of the target parameters is smaller than the threshold value of the abnormal eventA parameter value set at the time;
using the formula: p (P) i ＝e 1 *W i +e 2 *Q i The method comprises the steps of carrying out a first treatment on the surface of the Calculating an application characteristic value P corresponding to the ith parameter of the reference voltage source i The method comprises the steps of carrying out a first treatment on the surface of the Wherein e 1 A reference coefficient, e, representing a first characteristic value 2 A reference coefficient representing a second characteristic value; e, e 1 +e 2 ＝1，0<e 1 、e 2 <1；
Step S3: comparing and analyzing feature sets corresponding to different reference voltage source parameters, extracting a plurality of reference voltage source parameters with the same application environment as a plurality of target parameters, and outputting the feature sets corresponding to the plurality of target parameters as target feature sets;
the step S3 includes the following analysis steps:
acquiring a feature set Ai { x, y, z } corresponding to the ith parameter;
extracting application environments in feature sets of m parameters as application environments to be analyzed, performing intersection analysis on the application environments to be analyzed to generate a first set, wherein the intersection analysis generates a first set which is { z } 1 ∩z 2 ,z 1 ∩z 2 ∩z 3 ,......,z m-1 ∩z m -a }; wherein z is 1 、z 2 、......、z m Express application environments to be analyzed corresponding to the 1 st, 2 nd..third..m. parameters; the intersection analysis is a combination of any parameters corresponding to the application environment to be analyzed; the first set is a set formed by all combinations;
extracting parameters corresponding to the intersection analysis result which is not the empty set as multiple target parameters;
and outputting a feature set corresponding to the multiple target parameters as a target feature set;
step S4: acquiring application characteristic values corresponding to the multiple target parameters, and analyzing the reference priority of the multiple target parameters applied to the specification setting of the reference voltage source in the same application environment in the target characteristic set;
the step S4 includes the following analysis steps:
acquiring a j-th multi-element target parameter contained in the same application environment, and extracting an application characteristic value corresponding to the multi-element target parameter;
when the application characteristic values are different, sorting the multiple target parameters from large to small according to the numerical values of the application characteristic values to generate reference priority;
when the application characteristic values are the same, acquiring a characteristic set to which the same application characteristic value corresponds to a multi-element target parameter, and extracting a duration proportion of the existing application monitoring period of the physical environment characteristic in the characteristic set, wherein the duration proportion refers to a ratio of a response duration corresponding to the physical environment characteristic to a total duration of the application monitoring period; and sequencing the multiple target parameters corresponding to the same application characteristic value from large to small according to the duration proportion value to generate the reference priority.
2. The voltage source data real-time supervision system applying the voltage source data real-time supervision method based on artificial intelligence as claimed in claim 1, which is characterized by comprising a historical state database module, a feature set construction module, an application characteristic value analysis module, a multi-element target parameter determination module and a reference priority analysis module;
the historical state database module is used for acquiring historical state data recorded in a period from the completion of setting the voltage source specification to the implementation of application corresponding monitoring;
the characteristic set construction module is used for constructing a characteristic set of an application environment where the reference voltage source parameter data are based on the historical state data;
the application characteristic value analysis module is used for analyzing application characteristic values corresponding to the parameter data of the reference voltage source;
the multi-element target parameter determining module is used for comparing and analyzing feature sets corresponding to different reference voltage source parameters, and extracting a plurality of reference voltage source parameters with the same application environment as multi-element target parameters;
the reference priority analysis module is used for acquiring application characteristic values corresponding to the multiple target parameters, and analyzing the reference priority of the same application environment in the target characteristic set, which is applied to the specification setting of the reference voltage source, of the multiple target parameters.
3. The method for monitoring and controlling voltage source data in real time according to claim 2, wherein: the feature set construction module comprises a reference data determination unit, a target voltage source data determination unit, a physical environment feature determination unit, an application environment determination unit and a feature set output unit;
the reference data determining unit is used for obtaining parameters which are required to be considered by the reference voltage source in a development and setting period, wherein the parameters comprise initial precision, temperature coefficient, thermal hysteresis, long-term stability and low-frequency noise;
the target voltage source data determining unit is used for extracting reference voltage source data corresponding to any parameter value set in the historical data which are the same and the other parameter value sets are different as target voltage source data;
the physical environment characteristic determining unit is used for obtaining physical environment characteristics of the application monitoring period where the target voltage source data are located;
the application environment determining unit is used for obtaining an application environment corresponding to the phase characteristics meeting the stable response;
the feature set output unit is used for constructing a feature set which takes target voltage source data as a root node, physical environment features as a first sub-node and application environment as a second sub-node.
4. A method of real-time supervision of voltage source data according to claim 3, wherein: the application characteristic value analysis module comprises a first characteristic value calculation unit, a second characteristic value calculation unit and an application characteristic value calculation unit;
the first characteristic value calculation unit is used for calculating a first characteristic value based on the number of the events when the target event features correspond to the physical environment features in the feature set;
the second characteristic value calculation unit is used for calculating a second characteristic value based on the number of events when the target parameter corresponds to the physical environment characteristic in the characteristic set;
the application characteristic value calculation unit is configured to calculate an output application characteristic value based on the first characteristic value and the second characteristic value.
5. The method for monitoring and controlling voltage source data in real time according to claim 4, wherein: the reference priority analysis module comprises a parameter sequencing unit, a duration proportion analysis unit and a priority output unit;
the parameter sorting unit is used for sorting the multiple target parameters from large to small according to the magnitude of the application characteristic value;
the time length proportion analysis unit is used for analyzing the time length proportion of the existing application monitoring period of the physical environment characteristics in the characteristic set when the application characteristic values are the same, so as to determine the sequence;
the priority output unit is used for outputting the reference priority based on the parameter ranking result and the ranking result determined by the duration proportion analysis unit.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310378618.0A CN116628470B (en) | 2023-04-11 | 2023-04-11 | Voltage source data real-time supervision system and method based on artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310378618.0A CN116628470B (en) | 2023-04-11 | 2023-04-11 | Voltage source data real-time supervision system and method based on artificial intelligence |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116628470A CN116628470A (en) | 2023-08-22 |
| CN116628470B true CN116628470B (en) | 2023-11-10 |
Family
ID=87635468
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310378618.0A Active CN116628470B (en) | 2023-04-11 | 2023-04-11 | Voltage source data real-time supervision system and method based on artificial intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116628470B (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2014109557A (en) * | 2012-12-04 | 2014-06-12 | Mitsubishi Heavy Ind Ltd | Voltage monitoring device and voltage monitoring method |
| CA3072045A1 (en) * | 2017-08-02 | 2019-02-07 | Strong Force Iot Portfolio 2016, Llc | Methods and systems for detection in an industrial internet of things data collection environment with large data sets |
| CN112366337A (en) * | 2020-12-04 | 2021-02-12 | 上海燃锐新能源汽车技术有限公司 | Starting method and device of fuel cell engine system in low-temperature environment |
| CN113935562A (en) * | 2020-07-14 | 2022-01-14 | 东南大学 | Intelligent rating and automatic early warning method for health condition of power equipment |
| CN215866985U (en) * | 2021-07-30 | 2022-02-18 | 常州满旺半导体科技有限公司 | Detection apparatus for voltage self-zeroing circuit |
| KR20220072006A (en) * | 2020-11-23 | 2022-06-02 | 이유미 | Device, method and program for thermal environment analysis VR simulation |
| CN115471796A (en) * | 2022-11-14 | 2022-12-13 | 河北电力工程监理有限公司 | Power grid engineering supervision system and method based on machine vision |
| CN115833395A (en) * | 2022-12-26 | 2023-03-21 | 国网河北省电力有限公司电力科学研究院 | Analysis method and device for running state of power distribution network and online monitoring system |
-
2023
- 2023-04-11 CN CN202310378618.0A patent/CN116628470B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2014109557A (en) * | 2012-12-04 | 2014-06-12 | Mitsubishi Heavy Ind Ltd | Voltage monitoring device and voltage monitoring method |
| CA3072045A1 (en) * | 2017-08-02 | 2019-02-07 | Strong Force Iot Portfolio 2016, Llc | Methods and systems for detection in an industrial internet of things data collection environment with large data sets |
| CN113935562A (en) * | 2020-07-14 | 2022-01-14 | 东南大学 | Intelligent rating and automatic early warning method for health condition of power equipment |
| KR20220072006A (en) * | 2020-11-23 | 2022-06-02 | 이유미 | Device, method and program for thermal environment analysis VR simulation |
| CN112366337A (en) * | 2020-12-04 | 2021-02-12 | 上海燃锐新能源汽车技术有限公司 | Starting method and device of fuel cell engine system in low-temperature environment |
| CN215866985U (en) * | 2021-07-30 | 2022-02-18 | 常州满旺半导体科技有限公司 | Detection apparatus for voltage self-zeroing circuit |
| CN115471796A (en) * | 2022-11-14 | 2022-12-13 | 河北电力工程监理有限公司 | Power grid engineering supervision system and method based on machine vision |
| CN115833395A (en) * | 2022-12-26 | 2023-03-21 | 国网河北省电力有限公司电力科学研究院 | Analysis method and device for running state of power distribution network and online monitoring system |
Non-Patent Citations (1)
| Title |
|---|
| 电气控制过程中的常见问题及解决策略;王丽丽;《黑河学院学报》;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116628470A (en) | 2023-08-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109002904B (en) | Hospital outpatient quantity prediction method based on Prophet-ARMA | |
| US20150120263A1 (en) | Computer-Implemented Systems and Methods for Testing Large Scale Automatic Forecast Combinations | |
| CN111310981A (en) | Reservoir water level trend prediction method based on time series | |
| CN113222403B (en) | Big data-based power regulation method and device, storage medium and electronic equipment | |
| CN112231917A (en) | Space digital twin modeling method and device, computer equipment and storage medium | |
| CN113422693A (en) | Model construction method and recognition method of Internet of things equipment and computer equipment | |
| CN117556366B (en) | Data abnormality detection system and method based on data screening | |
| TW202133061A (en) | Demand forecasting method and demand forecasting apparatus | |
| CN115204491A (en) | Production line working condition prediction method and system based on digital twinning and LSTM | |
| CN113554302A (en) | Production management method and system based on MES intelligent manufacturing | |
| CN110766236A (en) | Power equipment state trend prediction method based on statistical analysis and deep learning | |
| Markoska et al. | Towards smart buildings performance testing as a service | |
| CN116628470B (en) | Voltage source data real-time supervision system and method based on artificial intelligence | |
| CN116629010B (en) | Degradation model confirmation and test design method based on random process | |
| Schachinger et al. | An advanced data analytics framework for energy efficiency in buildings | |
| CN108520311B (en) | Haze prediction model establishing method and system combining SOFM (software on a programmable) network and BP (back propagation) neural network | |
| CN115859891A (en) | Method for determining simulation parameters of electrolytic aluminum electrolysis cell | |
| CN106372811A (en) | Urban power grid operation index screening method and system | |
| CN113919449B (en) | Resident electric power data clustering method and device based on precise fuzzy clustering algorithm | |
| CN116186950A (en) | Processing method, system, device and storage medium for gas pipe network simulation | |
| CN113904933B (en) | Synchronous optimization method for performance and reliability of digital network control system | |
| CN115617670A (en) | Software test management method, storage medium and system | |
| CN114648060A (en) | Fault signal standardization processing and classification method based on machine learning | |
| CN111143482B (en) | Service data processing method and device of energy Internet of things and electronic equipment | |
| CN113884756A (en) | Electric energy metering edge acquisition device and method |
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 | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A real-time monitoring system and method for voltage source data based on artificial intelligence Granted publication date: 20231110 Pledgee: Bank of Nanjing Co.,Ltd. Changzhou Branch Pledgor: Changzhou manwang Semiconductor Technology Co.,Ltd. Registration number: Y2024980010098 |
|
| CP03 | Change of name, title or address | ||
| CP03 | Change of name, title or address |
Address after: 213000, 5th Floor, Building 1, Fubei Industrial Park, Tianning District, Changzhou City, Jiangsu Province Patentee after: Jiangsu Manwang Semiconductor Technology Co.,Ltd. Country or region after: China Address before: 213000, 5th Floor, Building 1, Fubei Industrial Park, Tianning District, Changzhou City, Jiangsu Province Patentee before: Changzhou manwang Semiconductor Technology Co.,Ltd. Country or region before: China |