CN117082108A - Internet of things communication method for intelligent low-voltage circuit breaker - Google Patents
Internet of things communication method for intelligent low-voltage circuit breaker Download PDFInfo
- Publication number
- CN117082108A CN117082108A CN202311335166.4A CN202311335166A CN117082108A CN 117082108 A CN117082108 A CN 117082108A CN 202311335166 A CN202311335166 A CN 202311335166A CN 117082108 A CN117082108 A CN 117082108A
- Authority
- CN
- China
- Prior art keywords
- circuit breaker
- low
- voltage circuit
- data
- internet
- 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
- 238000004891 communication Methods 0.000 title claims abstract description 59
- 238000000034 method Methods 0.000 title claims abstract description 57
- 230000005540 biological transmission Effects 0.000 claims description 67
- 238000004422 calculation algorithm Methods 0.000 claims description 54
- 230000006870 function Effects 0.000 claims description 43
- 238000003745 diagnosis Methods 0.000 claims description 36
- 238000004364 calculation method Methods 0.000 claims description 24
- 238000012937 correction Methods 0.000 claims description 24
- 238000012545 processing Methods 0.000 claims description 22
- 238000007405 data analysis Methods 0.000 claims description 21
- 238000009499 grossing Methods 0.000 claims description 15
- 238000001914 filtration Methods 0.000 claims description 11
- 238000007781 pre-processing Methods 0.000 claims description 11
- 238000005457 optimization Methods 0.000 claims description 10
- 238000004088 simulation Methods 0.000 claims description 10
- 238000010187 selection method Methods 0.000 claims description 6
- 238000009434 installation Methods 0.000 claims description 5
- 230000008569 process Effects 0.000 claims description 5
- 238000013475 authorization Methods 0.000 claims description 4
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 125000004122 cyclic group Chemical group 0.000 claims description 4
- 239000000284 extract Substances 0.000 claims description 4
- 238000001514 detection method Methods 0.000 claims description 3
- 230000008713 feedback mechanism Effects 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 description 9
- 238000004458 analytical method Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 230000003044 adaptive effect Effects 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 239000013307 optical fiber Substances 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000007667 floating Methods 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000013024 troubleshooting Methods 0.000 description 1
- 238000011144 upstream manufacturing Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- 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
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
-
- 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
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention discloses an intelligent low-voltage circuit breaker internet of things communication method, which relates to the technical field of low-voltage circuit breaker internet of things communication and solves the problem of insufficient remote overload protection control capability of a low-voltage circuit breaker.
Description
Technical Field
The invention relates to the technical field of communication of the Internet of things of low-voltage circuit breakers, in particular to an intelligent communication method of the Internet of things of the low-voltage circuit breakers.
Background
The intelligent low-voltage circuit breaker internet of things communication principle is that the low-voltage circuit breaker is combined with the internet of things technology to realize remote monitoring and control of the state of the circuit breaker, specifically, the intelligent low-voltage circuit breaker is connected with a cloud platform or a local area network through the embedded system, a sensor, a communication module and other technologies, so that information exchange and data sharing among devices are realized, and the intelligent low-voltage circuit breaker internet of things communication function is mainly realized in the following aspects: 1. remote monitoring: through the internet of things technology, the running state, the electrical parameters, the fault information and the like of the low-voltage circuit breaker can be monitored remotely at any time and any place, and the running reliability and the running safety of equipment are effectively improved; 2. remote control: the intelligent low-voltage circuit breaker can also realize remote control and management of equipment, for example, the equipment can be subjected to switching operation, current size adjustment and the like through a cloud platform or an APP; data analysis: the law and trend behind the data can be deeply mined by collecting a large amount of data generated by the low-voltage circuit breaker and by means of artificial intelligence and big data analysis technology, so that a reference basis is provided for enterprise decision.
In the prior art, the intelligent low-voltage circuit breaker internet of things communication method has a plurality of defects, on one hand, an internet of things platform cannot rapidly and accurately identify intelligent low-voltage circuit breaker equipment and acquire relevant information of the intelligent low-voltage circuit breaker equipment, when the internet of things platform acquires working data of the low-voltage circuit breaker, information receiving errors easily occur, on the other hand, overload diagnosis is not timely and accurate enough, the working circuit of the low-voltage circuit breaker is damaged, remote control of the low-voltage circuit breaker is not intelligent enough, and overload protection cannot be timely implemented, so that the intelligent low-voltage circuit breaker internet of things communication method is provided, and aims to improve the remote overload protection control capability of the low-voltage circuit breaker.
Disclosure of Invention
Aiming at the defects of the technology, the invention discloses an intelligent low-voltage circuit breaker internet of things communication method, wherein an identification code generation module, an identification code authentication module and an identification code access module are used for realizing the distribution and the use of identification codes, so that the problem that an intelligent low-voltage circuit breaker device cannot be quickly and accurately identified by an internet of things platform is solved, error-free data reception is realized by an intelligent wireless communication network by adopting an optimized path algorithm, the problem that information reception errors occur easily when the low-voltage circuit breaker working data are acquired by the internet of things platform is solved, and a cloud server is used for analyzing the low-voltage circuit breaker working data through a data preprocessing unit, a data analysis processing unit and an overload diagnosis unit, so that the overload diagnosis of the low-voltage circuit breaker is realized, the problem that the overload diagnosis is not timely and accurate is solved, and the overload protection problem cannot be timely implemented by a cloud remote control center through a control signal output module and an overload protection control module.
Analysis in view of the above, the invention provides an intelligent low-voltage circuit breaker internet of things communication method, which comprises the following steps:
the method comprises the steps that firstly, a low-voltage circuit breaker adopts a sensor group to collect working data of the low-voltage circuit breaker in real time, wherein the working data of the low-voltage circuit breaker comprise voltage, current and temperature;
secondly, registering and accessing the intelligent low-voltage circuit breaker equipment and the internet of things platform by adopting an identification code;
in the second step, the allocation and use of the identification code comprise an identification code generating module, an identification code authenticating module and an identification code accessing module, wherein the output end of the identification code generating module is connected with the input end of the identification code authenticating module, and the output end of the identification code authenticating module is connected with the input end of the identification code accessing module;
step three, the internet of things platform receives working data of the low-voltage circuit breaker by adopting an intelligent wireless communication network, wherein the intelligent wireless communication network comprises a data input module, a data transmission module and a data receiving module;
in the third step, the data input module adopts an API cloud platform protocol to input the working data of the low-voltage circuit breaker to the data transmission module, the data transmission module adopts an optimization path algorithm to optimize the working data transmission path of the low-voltage circuit breaker to realize the transmission of the working data of the low-voltage circuit breaker without errors, the data receiving module adopts a GPRS communication interface to receive the working data of the low-voltage circuit breaker, the output end of the data input module is connected with the input end of the data transmission module, the output end of the data transmission module is connected with the input end of the data receiving module,
fourthly, the Internet of things platform adopts a cloud server to analyze working data of the low-voltage circuit breaker and diagnose overload of the low-voltage circuit breaker, and the cloud server comprises a data preprocessing unit, a data analysis processing unit and an overload diagnosis unit;
in the fourth step, the output end of the data preprocessing unit is connected with the input end of the data analysis processing unit, and the output end of the data analysis processing unit is connected with the input end of the overload diagnosis unit;
and fifthly, the internet of things platform realizes overload protection of the working circuit of the low-voltage circuit breaker through a cloud remote control center, wherein the cloud remote control center comprises a control signal output module and an overload protection control module, and the output end of the control signal output module is connected with the input end of the overload protection control module.
According to the invention, the identification code generation module generates the unique identification code of the low-voltage circuit breaker by adopting an SHA hash function algorithm, the SHA hash function algorithm combines the self data of the low-voltage circuit breaker into a data block according to data splicing and byte sequence, the self data of the low-voltage circuit breaker comprises the model number, the serial number and the installation date of the low-voltage circuit breaker, the data block generates a hash value through the SHA hash function, the SHA hash function algorithm converts the hash value into a 16-system character string serving as the unique identification code of the low-voltage circuit breaker by adopting a conversion function, and the unique identification code of the low-voltage circuit breaker is written into and stored in the low-voltage circuit breaker through a nonvolatile memory.
As a further technical scheme of the invention, the identification code authentication module adopts a safety authentication protocol to realize the identity authentication and authentication of the identification code, the safety authentication protocol realizes that the identification code sends an authentication request to the Internet of things platform through the low-voltage circuit breaker identifier, the Internet of things platform returns an authorization code to the identification code through the identity authentication, and the identification code access module adopts a GPRS communication interface to bind with the Internet of things platform, so that the low-voltage circuit breaker is accessed to the Internet of things platform.
As a further technical scheme of the invention, the working method of the optimization path algorithm comprises the following steps:
determining a shortest path through a distance weight between an internet of things platform node and a low-voltage circuit breaker node by an optimization path algorithm, iteratively calculating the distance weight between the internet of things platform node and the low-voltage circuit breaker node by adopting an objective function, and selecting a path with the minimum distance weight as an optimal transmission path by the optimization path algorithm according to weight comparison, wherein the distance weight calculation formula is as follows:
（1）
in the case of the formula (1),distance weight between platform node of Internet of things and low-voltage circuit breaker node>Distance between platform node of Internet of things and low-voltage circuit breaker node, < >>For intelligent wireless communication network transmission rate, +.>Iterative calculation times are carried out for the objective function;
step two, the optimized path algorithm transmits the working data of the low-voltage circuit breaker to a cloud server of the internet of things platform according to an optimal transmission path in a dynamic routing transmission mode, and the dynamic routing transmission mode exchanges information between the internet of things platform node and the low-voltage circuit breaker node through a BGP dynamic routing protocol;
step three, an optimization path algorithm adopts forward correction transmission to perform error detection and correction in the low-voltage circuit breaker working data transmission process, the forward correction transmission encodes the low-voltage circuit breaker working data through convolutional code encoding to generate redundant data, and a convolutional code encoding calculation formula is as follows:
（2）
in the formula (2) of the present invention,for redundant data +.>For the input low-voltage circuit breaker operating data sequence, < >>For the input low-voltage circuit breaker operating data sequence subscript +.>Convolution kernel size encoded for a convolutional code, < >>The length of the coding constraint for convolutional code coding,is a coefficient of a convolutional code;
the forward correction transmission adopts cyclic redundancy check to detect errors of the transmitted low-voltage breaker working data, the forward correction transmission adopts BCH check codes to add redundancy bits into the original data to realize error correction, and the calculation formula for realizing error correction by the forward correction transmission is as follows:
（3）
in the formula (3) of the present invention,for error corrected low voltage circuit breaker operating data, < >>Redundancy check length for BCH check, +.>Is the number of redundant bits.
As a further technical scheme of the invention, the data preprocessing unit adopts a digital filtering algorithm to carry out smoothing treatment on the working data of the low-voltage circuit breaker to remove noise of the working data of the low-voltage circuit breaker, the digital filtering algorithm carries out weighted summation on the working data of the low-voltage circuit breaker through a weighted summation function to realize the smoothing treatment on the working data of the low-voltage circuit breaker, and the weighted summation function has a calculation formula as follows:
（4）
in the formula (4) of the present invention,for smoothing the processed low-voltage circuit breaker operating data, < >>For smoothing the pre-processed low-voltage breaker operating data, < >>Weighting values for the low-voltage circuit breaker operating data before smoothing +.>Is the filtering order;
the data analysis processing unit defines a working data analysis format of the low-voltage circuit breaker according to a GPRS communication protocol, and extracts overload diagnosis influence factors influencing overload of the low-voltage circuit breaker by adopting numerical characteristic selection, wherein the overload diagnosis influence factors comprise instantaneous overload capacity of the low-voltage circuit breaker, rated current of the low-voltage circuit breaker and thermal stability of the low-voltage circuit breaker.
As a further technical scheme of the invention, the overload diagnosis unit adopts a self-adaptive overload threshold selection method to set an overload diagnosis threshold according to an overload diagnosis influence factor, the self-adaptive overload threshold selection method dynamically adjusts the overload diagnosis threshold through a feedback mechanism, and the overload diagnosis unit compares the input voltage, the input current and the working temperature of the low-voltage circuit breaker with the overload diagnosis threshold through analog comparison to realize overload state judgment of the low-voltage circuit breaker.
As a further technical scheme of the invention, the control signal output module adopts a state space model with discrete time to represent the switch control of an output circuit of the low-voltage circuit breaker, the control signal output module outputs a circuit switch control instruction through a simulation prediction control algorithm, the simulation prediction control algorithm learns the dynamic characteristics of the state space model with discrete time according to working data of the low-voltage circuit breaker, the simulation prediction control algorithm adopts a state prediction function to calculate an optimal control input signal within the discrete time, and a calculation formula of the optimal control input signal is as follows:
（5）
in the formula (5) of the present invention,for optimal control input signal +.>A state feedback gain matrix for a state prediction function, < ->Is discrete time +.>State space model delay for discrete time, +.>For the low-voltage circuit breaker voltage state quantity, +.>Is the low voltage circuit breaker current state quantity.
As a further technical scheme of the invention, the overload protection module adopts an intelligent wireless communication network to transmit an optimal control input signal to the low-voltage circuit breaker, the low-voltage circuit breaker breaks internal contacts of the low-voltage circuit breaker through an electromagnetic overload protection circuit, the electromagnetic overload protection circuit processes the control input signal through fuzzy logic control, and the electromagnetic overload protection circuit executes the breaking operation of a working circuit of the low-voltage circuit breaker through a vacuum circuit breaker.
The invention has positive and beneficial effects different from the prior art:
the invention discloses an intelligent low-voltage circuit breaker internet of things communication method, which is characterized in that an identification code generation module, an identification code authentication module and an identification code access module are used for realizing the distribution and the use of identification codes, an internet of things platform can rapidly and accurately identify intelligent low-voltage circuit breaker equipment and acquire relevant information thereof, an intelligent wireless communication network adopts an optimized path algorithm to realize error-free data reception, a cloud server is used for analyzing working data of a low-voltage circuit breaker through a data preprocessing unit, a data analysis processing unit and an overload diagnosis unit, so that overload diagnosis of the low-voltage circuit breaker is realized, and a cloud remote control center is used for realizing overload protection of a working circuit of the low-voltage circuit breaker through a control signal output module and an overload protection control module.
Drawings
For a clearer description of embodiments of the invention or of solutions in the prior art, the drawings that are necessary for the description of the embodiments or of the prior art will be briefly described, it being apparent that the drawings in the description below are only some embodiments of the invention, from which, without inventive faculty, other drawings can be obtained for a person skilled in the art, in which:
FIG. 1 is a flow chart of an Internet of things communication method of an intelligent low-voltage circuit breaker;
FIG. 2 is a workflow diagram of the optimized path algorithm of the present invention;
FIG. 3 is a schematic diagram of the distribution and use of identification codes according to the present invention;
fig. 4 is a schematic structural diagram of a cloud server according to the present invention;
fig. 5 is a schematic structural diagram of the cloud remote control center of the present invention.
Detailed Description
The following description of the embodiments of the present disclosure will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the disclosure. It should be understood that the description is only illustrative and is not intended to limit the scope of the invention. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the present invention.
As shown in fig. 1-5, an internet of things communication method for an intelligent low-voltage circuit breaker includes the following steps:
the method comprises the steps that firstly, a low-voltage circuit breaker adopts a sensor group to collect working data of the low-voltage circuit breaker in real time, wherein the working data of the low-voltage circuit breaker comprise voltage, current and temperature;
secondly, registering and accessing the intelligent low-voltage circuit breaker equipment and the internet of things platform by adopting an identification code;
in the second step, the allocation and use of the identification code comprise an identification code generating module, an identification code authenticating module and an identification code accessing module, wherein the output end of the identification code generating module is connected with the input end of the identification code authenticating module, and the output end of the identification code authenticating module is connected with the input end of the identification code accessing module;
step three, the internet of things platform receives working data of the low-voltage circuit breaker by adopting an intelligent wireless communication network, wherein the intelligent wireless communication network comprises a data input module, a data transmission module and a data receiving module;
in the third step, the data input module adopts an API cloud platform protocol to input the working data of the low-voltage circuit breaker to the data transmission module, the data transmission module adopts an optimization path algorithm to optimize the working data transmission path of the low-voltage circuit breaker to realize the transmission of the working data of the low-voltage circuit breaker without errors, the data receiving module adopts a GPRS communication interface to receive the working data of the low-voltage circuit breaker, the output end of the data input module is connected with the input end of the data transmission module, the output end of the data transmission module is connected with the input end of the data receiving module,
fourthly, the Internet of things platform adopts a cloud server to analyze working data of the low-voltage circuit breaker and diagnose overload of the low-voltage circuit breaker, and the cloud server comprises a data preprocessing unit, a data analysis processing unit and an overload diagnosis unit;
in the fourth step, the output end of the data preprocessing unit is connected with the input end of the data analysis processing unit, and the output end of the data analysis processing unit is connected with the input end of the overload diagnosis unit;
and fifthly, the internet of things platform realizes overload protection of the working circuit of the low-voltage circuit breaker through a cloud remote control center, wherein the cloud remote control center comprises a control signal output module and an overload protection control module, and the output end of the control signal output module is connected with the input end of the overload protection control module.
In a specific embodiment, the sensor group is an integral body formed by a plurality of sensors and is used for collecting working data of the low-voltage circuit breaker in real time, and the sensor group comprises the following sensors: 1. a current sensor: the current measuring device is used for measuring the current passing through the low-voltage circuit breaker, and usually adopts a clamp type current transformer or a Hall current sensor and the like; 2. a voltage sensor: the voltage measuring device is used for measuring the voltage of the upstream and downstream of the low-voltage circuit breaker, and a voltage dividing type or optocoupler isolated voltage converter and the like are usually adopted; 3. temperature sensor: the temperature sensor is used for measuring the temperature change in the low-voltage circuit breaker so as to timely find and process the problems of overload, short circuit and the like, and the temperature sensor can adopt a thermistor, a thermocouple, a semiconductor temperature sensor and the like. The working state of the low-voltage breaker equipment can be comprehensively monitored through the sensors of the various types, and the working state is fed back to the Internet of things platform for analysis and processing. Therefore, equipment faults can be found and prevented in time, and the safety and reliability of equipment operation are improved.
The internet of things platform adopts intelligent wireless communication network to realize receiving low-voltage circuit breaker work data and has the following advantages: 1. the transmission distance is far: the wireless communication can carry out information transmission through electromagnetic waves in the air under the condition that cables or optical fibers are not required to be laid, so that a wider area can be covered; 2. the transmission speed is high: along with the development of mobile communication and Internet of things technologies, the transmission speed of the intelligent wireless communication network is also continuously improved, and the requirements of large-scale data real-time acquisition and transmission can be met; 3. the installation and maintenance are convenient: because the wireless communication device does not need to lay complex cables and optical fibers, the installation and maintenance are relatively easy; 4. the cost is low: compared with wired transmission equipment, the wireless communication equipment has lower cost and can be flexibly deployed and expanded according to the needs.
In a further embodiment, the identification code generation module generates a unique identification code of the low-voltage circuit breaker by adopting an SHA hash function algorithm, the SHA hash function algorithm combines the self data of the low-voltage circuit breaker into a data block according to data splicing and byte sequence, the self data of the low-voltage circuit breaker comprises a model number, a serial number and an installation date of the low-voltage circuit breaker, the data block generates a hash value through the SHA hash function, the SHA hash function algorithm converts the hash value into a 16-system character string serving as the unique identification code of the low-voltage circuit breaker by adopting a conversion function, and the unique identification code of the low-voltage circuit breaker is written into and stored in the low-voltage circuit breaker through a nonvolatile memory.
In a further embodiment, the identification code authentication module adopts a safety authentication protocol to realize identity authentication and authentication of the identification code, the safety authentication protocol realizes that the identification code sends an authentication request to the internet of things platform through the low-voltage circuit breaker identifier, the internet of things platform returns an authorization code to the identification code through identity authentication, and the identification code access module adopts a GPRS communication interface to bind with the internet of things platform, so that the low-voltage circuit breaker is accessed to the internet of things platform.
In a specific embodiment, the unique identifier (Unique Identifier) of the low voltage circuit breaker may be written to by a Non-Volatile Memory (Non-Volatile Memory), which is a storage device capable of holding data in the event of a power failure or power failure, in the low voltage circuit breaker, the unique identifier is typically used to identify and track each specific circuit breaker to implement management and monitoring thereof, the unique identifier may be a unique number, letter combination or other form of identifier, by writing the unique identifier into the Non-Volatile Memory, it may be ensured that the circuit breaker is still capable of retaining the information even after the power failure or power failure, so that after re-powering up or restoration, the system may read and use the unique identifier to perform various operations, such as querying, configuring, troubleshooting, and the like, the Non-Volatile Memory is typically implemented using Flash Memory (Flash Memory) or EEPROM (Electrically Erasable Programmable Read-Only Memory) and the like, which has a fast read-write speed, a high data reliability and a long-term data storage capability, and requires the data to be written to, and requires proper security and authorization, and the data to be read and read, and read the unique identifier and read security must be properly and verify the security.
The GPRS communication interface has the following characteristics: 1. high speed transmission: GPRS can provide higher data transmission rate, up to 115.2 kbps, and can transmit a large amount of data faster than traditional short message and voice communication; 2. the delay is low: the GPRS adopts a packet switching technology, and can immediately send data packets when the network is idle, so that the transmission delay is reduced; 3. the real-time performance is good: the GPRS supports instant connection and disconnection, so that the method has advantages in application scenes needing real-time response; 4. the coverage range is wide: the GPRS coverage area is relatively wide, and the GPRS can be used in cities, villages and some remote areas; 5. the cost is relatively low: GPRS devices are lower cost and the operator-provided traffic costs are relatively lower compared to other wireless communication technologies; in general, the GPRS communication interface is a mature and widely applied wireless communication technology, and is suitable for the application scene of the Internet of things, which needs medium speed, has low real-time requirements and has wider coverage range.
In a further embodiment, the working method of the optimized path algorithm is as follows:
determining a shortest path through a distance weight between an internet of things platform node and a low-voltage circuit breaker node by an optimization path algorithm, iteratively calculating the distance weight between the internet of things platform node and the low-voltage circuit breaker node by adopting an objective function, and selecting a path with the minimum distance weight as an optimal transmission path by the optimization path algorithm according to weight comparison, wherein the distance weight calculation formula is as follows:
（1）
in the case of the formula (1),distance weight between platform node of Internet of things and low-voltage circuit breaker node>Distance between platform node of Internet of things and low-voltage circuit breaker node, < >>For intelligent wireless communication network transmission rate, +.>Iterative calculation times are carried out for the objective function;
step two, the optimized path algorithm transmits the working data of the low-voltage circuit breaker to a cloud server of the internet of things platform according to an optimal transmission path in a dynamic routing transmission mode, and the dynamic routing transmission mode exchanges information between the internet of things platform node and the low-voltage circuit breaker node through a BGP dynamic routing protocol;
step three, an optimization path algorithm adopts forward correction transmission to perform error detection and correction in the low-voltage circuit breaker working data transmission process, the forward correction transmission encodes the low-voltage circuit breaker working data through convolutional code encoding to generate redundant data, and a convolutional code encoding calculation formula is as follows:
（2）
in the formula (2) of the present invention,for redundant data +.>For the input low-voltage circuit breaker operating data sequence, < >>For the input low-voltage circuit breaker operating data sequence subscript +.>Convolution kernel size encoded for a convolutional code, < >>The length of the coding constraint for convolutional code coding,is a coefficient of a convolutional code;
the forward correction transmission adopts cyclic redundancy check to detect errors of the transmitted low-voltage breaker working data, the forward correction transmission adopts BCH check codes to add redundancy bits into the original data to realize error correction, and the calculation formula for realizing error correction by the forward correction transmission is as follows:
（3）
in the formula (3) of the present invention,for error corrected low voltage circuit breaker operating data, < >>Redundancy check length for BCH check, +.>Is the number of redundant bits.
In a specific embodiment, a dynamic routing transmission mode exchanges information between an internet of things platform node and a low-voltage breaker node through a BGP (Border Gateway Protocol) dynamic routing protocol, wherein the BGP dynamic routing protocol is a protocol for routing between Autonomous Systems (AS) in the internet, and can help exchange network prefix information between different autonomous systems.
The optimal path algorithm can select a path with the minimum distance weight as an optimal transmission path according to weight comparison, the algorithm can help a network node to select the optimal path in a plurality of optional paths so as to improve the efficiency and performance of data transmission, and in the process of selecting the path by using the weight comparison, the optimal path algorithm adopts an objective function to iteratively calculate the distance weight between the platform node of the Internet of things and the low-voltage circuit breaker node, and the statistical table of the distance weight calculation results between the platform node of the Internet of things and the low-voltage circuit breaker node is shown in table 1:
TABLE 1 statistical table of distance weight calculation results
As shown in table 1, four test groups are set, the distance weights between the internet of things platform node and the low-voltage circuit breaker node are calculated by adopting two methods, the method 1 deduces the distance weights between the internet of things platform node and the low-voltage circuit breaker node by utilizing a statistical analysis method on historical data or sample data, the method 2 iteratively calculates the distance weights between the internet of things platform node and the low-voltage circuit breaker node by adopting an objective function for optimizing a path algorithm, the error of the method 1 is larger than that of the method 2, and the method 1 has the outstanding technical effect of iteratively calculating the distance weights between the internet of things platform node and the low-voltage circuit breaker node by adopting the objective function.
In a further embodiment, the data preprocessing unit performs smoothing processing on the low-voltage circuit breaker working data by adopting a digital filtering algorithm to remove noise of the low-voltage circuit breaker working data, the digital filtering algorithm performs weighted summation on the low-voltage circuit breaker working data by using a weighted summation function to realize the smoothing processing of the low-voltage circuit breaker working data, and a calculation formula of the weighted summation function is as follows:
（4）
in the formula (4) of the present invention,for smoothing the processed low-voltage circuit breaker operating data, < >>For smoothing the pre-processed low-voltage breaker operating data, < >>Weighting values for the low-voltage circuit breaker operating data before smoothing +.>Is the filtering order;
the data analysis processing unit defines a working data analysis format of the low-voltage circuit breaker according to a GPRS communication protocol, and extracts overload diagnosis influence factors influencing overload of the low-voltage circuit breaker by adopting numerical characteristic selection, wherein the overload diagnosis influence factors comprise instantaneous overload capacity of the low-voltage circuit breaker, rated current of the low-voltage circuit breaker and thermal stability of the low-voltage circuit breaker.
In a further embodiment, the overload diagnosis unit sets an overload diagnosis threshold according to the overload diagnosis influence factor by adopting an adaptive overload threshold selection method, the adaptive overload threshold selection method dynamically adjusts the overload diagnosis threshold through a feedback mechanism, and the overload diagnosis unit compares the input voltage, the input current and the working temperature of the low-voltage circuit breaker with the overload diagnosis threshold through analog comparison to realize overload state judgment of the low-voltage circuit breaker.
In a specific embodiment, the data analysis processing unit may define a low-voltage circuit breaker working data analysis format according to a GPRS communication protocol, where the following aspects need to be considered when defining the analysis format: 1.
data frame structure: determining the structure of a data frame, wherein the structure comprises a start identifier, a length field, a data field, a check field and the like, and the definition of the fields accords with the specification of a GPRS communication protocol; 2. data type and coding mode: determining the type and coding of each data field, for example, the breaker status may be represented using a boolean type, the current value may be represented using a floating point type, and for different types of data, an appropriate coding may be selected, such as binary, decimal, hexadecimal, etc.; 3. byte order: determining byte order (big endian or little endian) to ensure proper parsing of data during network transmission; 4. checking mechanism: a check field is defined to verify whether the received data is complete and correct, and common check mechanisms include Cyclic Redundancy Check (CRC) or simple Checksum (Checksum), etc.; 5. special case treatment: in consideration of the fact that an exception or a special situation may exist in the actual situation, a corresponding processing mode needs to be defined, for example, if a certain field is missing or wrong, a default value or error reporting processing can be adopted. After the analysis format of the working data of the low-voltage circuit breaker is defined through the steps, the analysis and processing can be carried out according to the defined format when the original data is received, and the analysis processing unit can extract the data field by field according to the protocol specification, and carry out corresponding conversion and verification to finally obtain the available working data.
The digital filtering algorithm performs weighted summation on the low-voltage circuit breaker working data through a weighted summation function, and taking the low-voltage circuit breaker working voltage data as an example, the statistical table of the weighted summation calculation result of the low-voltage circuit breaker working voltage data is shown in table 2:
table 2 statistics of the results of the low voltage circuit breaker operating data weighted summation calculations
As shown in table 2, four test groups are set, and the weighted summation value of the working voltage data of the low-voltage circuit breaker is calculated by adopting two methods, wherein the weighted summation value of the working voltage data of the low-voltage circuit breaker is calculated by adopting a first method and a second method, and the weighted summation is carried out on the working data of the low-voltage circuit breaker by adopting a weighted summation function through a second digital filtering algorithm.
In a further embodiment, the control signal output module adopts a state space model of discrete time to represent the control of the output circuit switch of the low-voltage circuit breaker, the control signal output module outputs a control instruction of the circuit switch through a simulation prediction control algorithm, the simulation prediction control algorithm learns the dynamic characteristics of the state space model of discrete time according to the working data of the low-voltage circuit breaker, and the simulation prediction control algorithm adopts a state prediction function to calculate an optimal control input signal in the discrete time, wherein the calculation formula of the optimal control input signal is as follows:
（5）
in the formula (5) of the present invention,for optimal control input signal +.>A state feedback gain matrix for a state prediction function, < ->Is discrete time +.>State space model delay for discrete time, +.>For the low-voltage circuit breaker voltage state quantity, +.>Is the low voltage circuit breaker current state quantity.
In a specific embodiment, a state space model of discrete time may be used to represent the output circuit switch control of a low voltage circuit breaker, the following being a simplified example: 1. state Variables (State Variables): state variable 1: the switching state of the circuit breaker (e.g., 0 for closed, 1 for open); state variable 2: outputting a current value of the circuit; 2. input Variables (Input Variables): input variable 1: a control signal (e.g., 0 for closing a circuit breaker, 1 for opening a circuit breaker); 3. output variable: output variable 1: the State of the output circuit (e.g., 0 represents open, 1 represents closed), 4, state Equation: when the input signal is 0, the circuit breaker remains in the off state, and the output current is 0: breaker status update: state variable 1=0; output current update: state variable 2=0; when the input signal is 1, the circuit breaker is opened, and the output current is updated according to the actual situation, and the state of the circuit breaker is updated: state variable 1=1, output current update: determining according to actual conditions; 5. output Equation (Output Equation): the state of the output circuit is equal to the switching state of the circuit breaker, and the output variable 1=the state variable 1, and a state space model of the switching control of the low-voltage circuit breaker output circuit under discrete time can be established through the definition and the equation. In the model, the input signal controls the switching state of the circuit breaker, and the state of the output circuit is consistent with the switching state of the circuit breaker, so that parameters and equations in the model can be further improved and adjusted according to actual requirements and system characteristics. The simulation prediction control algorithm calculates an optimal control input signal in discrete time by adopting a state prediction function, and a calculation result statistical table of the optimal control input signal is shown in table 3:
table 3 calculation result statistics table of optimum control input signals
As shown in table 3, four test groups are set, two methods are adopted to calculate the optimal control input signal, the method 3 obtains the optimal control input signal through the harmonic averaging of the accuracy and the recall, the method 4 simulates the predictive control algorithm to calculate the optimal control input signal in discrete time by adopting the state predictive function, the error of the method 3 is larger than that of the method 4, and the simulated predictive control algorithm has outstanding technical effects of calculating the optimal control input signal in discrete time by adopting the state predictive function.
In a further embodiment, the overload protection module transmits an optimal control input signal to the low-voltage circuit breaker through an intelligent wireless communication network, the low-voltage circuit breaker breaks internal contacts of the low-voltage circuit breaker through an electromagnetic overload protection circuit, the electromagnetic overload protection circuit processes the control input signal through fuzzy logic control, and the electromagnetic overload protection circuit performs a breaking operation of a working circuit of the low-voltage circuit breaker through a vacuum circuit breaker.
While specific embodiments of the present invention have been described above, it will be understood by those skilled in the art that these specific embodiments are by way of example only, and that various omissions, substitutions, and changes in the form and details of the methods and systems described above may be made by those skilled in the art without departing from the spirit and scope of the invention. For example, it is within the scope of the present invention to combine the above-described method steps to perform substantially the same function in substantially the same way to achieve substantially the same result. Accordingly, the scope of the invention is limited only by the following claims.
Claims (8)
1. An intelligent low-voltage circuit breaker internet of things communication method is characterized in that: the method comprises the following steps:
the method comprises the steps that firstly, a low-voltage circuit breaker adopts a sensor group to collect working data of the low-voltage circuit breaker in real time, wherein the working data of the low-voltage circuit breaker comprise voltage, current and temperature;
secondly, registering and accessing the intelligent low-voltage circuit breaker equipment and the internet of things platform by adopting an identification code;
in the second step, the allocation and use of the identification code comprise an identification code generating module, an identification code authenticating module and an identification code accessing module, wherein the output end of the identification code generating module is connected with the input end of the identification code authenticating module, and the output end of the identification code authenticating module is connected with the input end of the identification code accessing module;
step three, the internet of things platform receives working data of the low-voltage circuit breaker by adopting an intelligent wireless communication network, wherein the intelligent wireless communication network comprises a data input module, a data transmission module and a data receiving module;
in the third step, the data input module adopts an API cloud platform protocol to input the working data of the low-voltage circuit breaker to the data transmission module, the data transmission module adopts an optimization path algorithm to optimize the working data transmission path of the low-voltage circuit breaker to realize the transmission of the working data of the low-voltage circuit breaker without errors, the data receiving module adopts a GPRS communication interface to receive the working data of the low-voltage circuit breaker, the output end of the data input module is connected with the input end of the data transmission module, the output end of the data transmission module is connected with the input end of the data receiving module,
fourthly, the Internet of things platform adopts a cloud server to analyze working data of the low-voltage circuit breaker and diagnose overload of the low-voltage circuit breaker, and the cloud server comprises a data preprocessing unit, a data analysis processing unit and an overload diagnosis unit;
in the fourth step, the output end of the data preprocessing unit is connected with the input end of the data analysis processing unit, and the output end of the data analysis processing unit is connected with the input end of the overload diagnosis unit;
and fifthly, the internet of things platform realizes overload protection of the working circuit of the low-voltage circuit breaker through a cloud remote control center, wherein the cloud remote control center comprises a control signal output module and an overload protection control module, and the output end of the control signal output module is connected with the input end of the overload protection control module.
2. The intelligent low-voltage circuit breaker internet of things communication method according to claim 1, wherein the method comprises the following steps: the identification code generation module generates a unique identification code of the low-voltage circuit breaker by adopting an SHA hash function algorithm, the SHA hash function algorithm combines the self data of the low-voltage circuit breaker into a data block according to data splicing and byte sequence, the self data of the low-voltage circuit breaker comprises a model number, a serial number and an installation date of the low-voltage circuit breaker, the data block generates a hash value through the SHA hash function, the SHA hash function algorithm converts the hash value into a 16-system character string serving as the unique identification code of the low-voltage circuit breaker by adopting a conversion function, and the unique identification code of the low-voltage circuit breaker is written into a nonvolatile memory and stored in the low-voltage circuit breaker.
3. The intelligent low-voltage circuit breaker internet of things communication method according to claim 1, wherein the method comprises the following steps: the identification code authentication module adopts a safety authentication protocol to realize the identity authentication and authentication of the identification code, the safety authentication protocol realizes that the identification code sends an authentication request to the internet of things platform through the low-voltage circuit breaker identifier, the internet of things platform returns an authorization code to the identification code through identity authentication, and the identification code access module adopts a GPRS communication interface to bind with the internet of things platform, so that the low-voltage circuit breaker is accessed to the internet of things platform.
4. The intelligent low-voltage circuit breaker internet of things communication method according to claim 1, wherein the method comprises the following steps: the working method of the optimized path algorithm comprises the following steps:
step one, determining a shortest path through a distance weight between an internet of things platform node and a low-voltage circuit breaker node by using an optimized path algorithm, iteratively calculating the distance weight between the internet of things platform node and the low-voltage circuit breaker node by using an objective function, and selecting a path with the minimum distance weight as an optimal transmission path by using the optimized path algorithm according to weight comparison, wherein the distance weight calculation formula is as follows:
（1）
in the case of the formula (1),distance weight between platform node of Internet of things and low-voltage circuit breaker node>Distance between platform node of Internet of things and low-voltage circuit breaker node, < >>For intelligent wireless communication network transmission rate, +.>Iterative calculation times are carried out for the objective function;
step two, the optimized path algorithm transmits the working data of the low-voltage circuit breaker to a cloud server of the internet of things platform according to an optimal transmission path through a dynamic routing transmission mode, and the dynamic routing transmission mode exchanges information between the internet of things platform node and the low-voltage circuit breaker node through a BGP dynamic routing protocol;
step three, the optimized path algorithm adopts forward correction transmission to perform error detection and correction in the low-voltage circuit breaker working data transmission process, the forward correction transmission encodes the low-voltage circuit breaker working data through convolutional code encoding to generate redundant data, and a convolutional code encoding calculation formula is as follows:
（2）
in the formula (2) of the present invention,for redundant data +.>For the input low-voltage circuit breaker operating data sequence, < >>For the input low-voltage circuit breaker operating data sequence subscript +.>Convolution kernel size encoded for a convolutional code, < >>Coding constraint length for convolutional code coding, +.>Is a coefficient of a convolutional code;
the forward correction transmission adopts cyclic redundancy check to detect errors of the transmitted low-voltage breaker working data, the forward correction transmission adopts BCH check codes to add redundancy bits into the original data to realize error correction, and the calculation formula for realizing error correction by the forward correction transmission is as follows:
（3）
in the formula (3) of the present invention,for error corrected low voltage circuit breaker operating data, < >>Redundancy check length for BCH check, +.>Is the number of redundant bits.
5. The intelligent low-voltage circuit breaker internet of things communication method according to claim 1, wherein the method comprises the following steps: the data preprocessing unit carries out smoothing treatment on the working data of the low-voltage circuit breaker by adopting a digital filtering algorithm to remove noise of the working data of the low-voltage circuit breaker, and the digital filtering algorithm carries out weighted summation on the working data of the low-voltage circuit breaker by a weighted summation function to realize the smoothing treatment on the working data of the low-voltage circuit breaker, wherein the weighted summation function has a calculation formula as follows:
（4）
in the formula (4) of the present invention,for smoothing the processed low-voltage circuit breaker operating data, < >>For smoothing the pre-processed low-voltage breaker operating data, < >>Weighting values for the low-voltage circuit breaker operating data before smoothing +.>Is the filtering order;
the data analysis processing unit defines a working data analysis format of the low-voltage circuit breaker according to a GPRS communication protocol, and extracts overload diagnosis influence factors influencing overload of the low-voltage circuit breaker by adopting numerical characteristic selection, wherein the overload diagnosis influence factors comprise instantaneous overload capacity of the low-voltage circuit breaker, rated current of the low-voltage circuit breaker and thermal stability of the low-voltage circuit breaker.
6. The intelligent low-voltage circuit breaker internet of things communication method according to claim 1, wherein the method comprises the following steps: the overload diagnosis unit sets an overload diagnosis threshold according to an overload diagnosis influence factor by adopting a self-adaptive overload threshold selection method, the self-adaptive overload threshold selection method dynamically adjusts the overload diagnosis threshold through a feedback mechanism, and the overload diagnosis unit compares the input voltage, the input current and the working temperature of the low-voltage circuit breaker with the overload diagnosis threshold through analog comparison to realize overload state judgment of the low-voltage circuit breaker.
7. The intelligent low-voltage circuit breaker internet of things communication method according to claim 1, wherein the method comprises the following steps: the control signal output module adopts a state space model with discrete time to represent the control of an output circuit switch of the low-voltage circuit breaker, the control signal output module outputs a circuit switch control instruction through a simulation prediction control algorithm, the simulation prediction control algorithm learns the dynamic characteristics of the state space model with discrete time according to working data of the low-voltage circuit breaker, the simulation prediction control algorithm adopts a state prediction function to calculate an optimal control input signal in the discrete time, and a calculation formula of the optimal control input signal is as follows:
（5）
in the formula (5) of the present invention,for optimal control input signal +.>A state feedback gain matrix for a state prediction function, < ->Is discrete time +.>State space model delay for discrete time, +.>For the low-voltage circuit breaker voltage state quantity, +.>Is the current state quantity of the low-voltage circuit breaker。
8. The intelligent low-voltage circuit breaker internet of things communication method according to claim 1, wherein the method comprises the following steps: the overload protection module adopts an intelligent wireless communication network to transmit an optimal control input signal to the low-voltage circuit breaker, the low-voltage circuit breaker breaks an internal contact of the low-voltage circuit breaker through an electromagnetic overload protection circuit, the electromagnetic overload protection circuit processes the control input signal through fuzzy logic control, and the electromagnetic overload protection circuit executes the breaking operation of a working circuit of the low-voltage circuit breaker through a vacuum circuit breaker.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311335166.4A CN117082108B (en) | 2023-10-16 | 2023-10-16 | Internet of things communication method for intelligent low-voltage circuit breaker |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311335166.4A CN117082108B (en) | 2023-10-16 | 2023-10-16 | Internet of things communication method for intelligent low-voltage circuit breaker |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117082108A true CN117082108A (en) | 2023-11-17 |
| CN117082108B CN117082108B (en) | 2023-12-26 |
Family
ID=88706415
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311335166.4A Active CN117082108B (en) | 2023-10-16 | 2023-10-16 | Internet of things communication method for intelligent low-voltage circuit breaker |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117082108B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109066968A (en) * | 2018-07-07 | 2018-12-21 | 南京中环自动化设备有限公司 | Intelligent low-voltage circuit breaker system and its application method |
| US20200365346A1 (en) * | 2019-05-18 | 2020-11-19 | Amber Solutions, Inc. | Intelligent circuit breakers with solid-state bidirectional switches |
| CN113726014A (en) * | 2021-09-01 | 2021-11-30 | 广东省珩祥安全科技有限公司 | Power utilization monitoring method and system based on circuit breaker |
| CN114137857A (en) * | 2020-09-03 | 2022-03-04 | 浙江正泰电器股份有限公司 | Remote monitoring system and thing networking solid state relay |
| CN114137858A (en) * | 2020-09-03 | 2022-03-04 | 浙江正泰电器股份有限公司 | Remote monitoring system and Internet of things electromagnetic relay thereof |
| CN115102277A (en) * | 2022-06-06 | 2022-09-23 | 北京国电通网络技术有限公司 | Internet of things low-voltage intelligent circuit breaker and internet of things system thereof |
-
2023
- 2023-10-16 CN CN202311335166.4A patent/CN117082108B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109066968A (en) * | 2018-07-07 | 2018-12-21 | 南京中环自动化设备有限公司 | Intelligent low-voltage circuit breaker system and its application method |
| US20200365346A1 (en) * | 2019-05-18 | 2020-11-19 | Amber Solutions, Inc. | Intelligent circuit breakers with solid-state bidirectional switches |
| CN114137857A (en) * | 2020-09-03 | 2022-03-04 | 浙江正泰电器股份有限公司 | Remote monitoring system and thing networking solid state relay |
| CN114137858A (en) * | 2020-09-03 | 2022-03-04 | 浙江正泰电器股份有限公司 | Remote monitoring system and Internet of things electromagnetic relay thereof |
| CN113726014A (en) * | 2021-09-01 | 2021-11-30 | 广东省珩祥安全科技有限公司 | Power utilization monitoring method and system based on circuit breaker |
| CN115102277A (en) * | 2022-06-06 | 2022-09-23 | 北京国电通网络技术有限公司 | Internet of things low-voltage intelligent circuit breaker and internet of things system thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117082108B (en) | 2023-12-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN1981446B (en) | Apparatus and method for improving reliability of collected sensor data over a network | |
| US20120239320A1 (en) | Reliability calculation for substation automation systems | |
| CN111697566B (en) | Reliability assessment method for active power distribution network information physical system considering information failure | |
| CN111147566B (en) | Platform area ubiquitous Internet of things dual-mode networking system and method based on open network protocol | |
| WO2013148215A1 (en) | Photovoltaic system data handling methods and apparatus | |
| CN113156869B (en) | Remote maintenance system and method for electric power Internet of things terminal equipment | |
| CN113258995A (en) | Fault prediction method, device and computer readable storage medium | |
| CN110752966A (en) | Network protocol security test method and device, electronic equipment and storage medium | |
| CN108879956A (en) | The method that active judgement is carried out to the system failure based on equipment running status and is repaired | |
| CN115484131A (en) | Internet of things gateway and equipment data storage system for same | |
| CN117082108B (en) | Internet of things communication method for intelligent low-voltage circuit breaker | |
| CN114814467A (en) | Power distribution network fault positioning method | |
| Garcia et al. | Covert channel communication through physical interdependencies in cyber-physical infrastructures | |
| CN110537347B (en) | Method and central computer for detecting and determining the probability of failure of a radio network | |
| CN116540029A (en) | Active power distribution network fault section positioning method and device based on node distortion correction | |
| Rana et al. | Microgrid state estimation and control using Kalman filter and semidefinite programming technique | |
| CN111444472B (en) | Transformer substation equipment fault identification method and system considering comprehensive information | |
| CN111025135B (en) | Cloud platform-based test method for on-site FTU coordination control capability | |
| CN110336606B (en) | Power optical network fault diagnosis method based on parameter estimation and service identification | |
| CN111083701A (en) | Hardware identity authentication method in software-defined wireless sensor network | |
| CN113839921B (en) | Data processing method, device, computer equipment and storage medium | |
| CN115952925B (en) | Distribution terminal optimal configuration method considering extreme weather | |
| CN113067763B (en) | High-reliability mountain area distribution network communication system and communication method thereof | |
| Long et al. | Distribution Network Differential Protection Method Based on Dynamic Time Warping Algorithm | |
| CN117118616B (en) | Quantum key distribution network construction method and device based on power distribution network |
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 |