CN113660552A - Intelligent early warning system and method for power cable - Google Patents
Intelligent early warning system and method for power cable Download PDFInfo
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- H—ELECTRICITY
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- H04Q—SELECTING
- H04Q9/00—Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom
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- 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
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- H04Q2209/823—Arrangements in the sub-station, i.e. sensing device where the sensing device takes the initiative of sending data where the data is sent when the measured values exceed a threshold, e.g. sending an alarm
Abstract
The invention discloses an intelligent early warning system and method for a power cable, wherein the system comprises: the system comprises an acquisition terminal, a wireless gateway and a server side; the system comprises an acquisition terminal, a server and a wireless gateway, wherein the acquisition terminal is used for acquiring data of cable environment data according to a preset time interval, processing, storing and uploading the acquired data, monitoring and adjusting the state of a cable according to the acquired data and transmitting the acquired data to the server through the wireless gateway; the wireless gateway is used for routing the acquired data to a corresponding server; the server is used for collecting the collected data sent by the wireless gateway, analyzing the collected data through a big data analysis technology, predicting cable hidden dangers according to analysis results, early warning fault occurrence and positioning fault positions through prefabricated cable geographic position information; the invention solves the early warning problem of the power cable by big data and applying an intelligent means.
Description
Technical Field
The invention relates to the technical field of computers, in particular to an intelligent early warning system and method for a power cable.
Background
The distribution cable is one of the core assets of a power supply company, is wide in distribution, large in quantity, secret in operation environment and high in management difficulty. A power company invests a large amount of manpower, financial resources and material resources every year, patrols and inspects cables and environments in a cable trench well, is limited by monitoring means, is high in monitoring information acquisition cost and low in efficiency, cannot realize real-time monitoring, and cannot predict and prevent in time.
How to use advanced technical means to realize low-cost and high-efficiency management is a problem to be solved urgently.
Disclosure of Invention
The invention aims to provide an intelligent early warning system and method for a power cable, and aims to solve the problems in the prior art.
The invention provides an intelligent early warning system for a power cable, which specifically comprises: the system comprises an acquisition terminal, a wireless gateway and a server side;
the system comprises an acquisition terminal, a server and a wireless gateway, wherein the acquisition terminal is used for acquiring data of cable environment data according to a preset time interval, processing, storing and uploading the acquired data, monitoring and adjusting the state of a cable according to the acquired data and transmitting the acquired data to the server through the wireless gateway;
and the wireless gateway is used for routing the acquired data to the corresponding server.
And the server is used for collecting the collected data sent by the wireless gateway, analyzing the collected data through a big data analysis technology, predicting the hidden cable danger according to an analysis result, early warning the occurrence of a fault, and positioning the fault position through the geographical position information of the prefabricated cable.
Further, the acquisition terminal specifically includes:
the cable joint temperature monitoring terminal is used for monitoring the temperature of a cable through an RFID label temperature sensor and setting a cable temperature alarm value, wherein the RFID label temperature sensor is arranged on a cable joint in a bundling mode;
the environment temperature and humidity monitoring terminal is used for monitoring environment temperature and environment humidity and setting an environment temperature alarm value and an environment humidity alarm value;
and the cable immersion monitoring terminal is used for monitoring the liquid level height.
Further, the wireless gateway specifically includes:
the RFID radio frequency chip is used for receiving the acquired data of the acquisition terminal;
the NB communication module is used for realizing communication from the wireless gateway to the server and routing the acquired data to the corresponding server;
the MCU is used for realizing hardware management and low-power consumption power management of the wireless gateway;
and the lithium battery pack is used for providing power support for the wireless gateway.
Further, the server specifically includes:
the public cloud platform is used for providing cloud services;
the national network cloud platform is used for providing cloud service by additionally arranging an application server and a database server;
and the intelligent analysis monitoring module is used for adjusting the early warning threshold value through big data analysis capability and learning capability, and performing trend analysis, comparative analysis and historical iterative analysis according to the acquired data, the electricity utilization time period, the geographic position and the information of the natural environment.
The invention provides an intelligent early warning method for a power cable, which specifically comprises the following steps:
the method comprises the steps that data acquisition is carried out on cable environment data according to preset time intervals through an acquisition terminal, the acquired data are processed, stored and uploaded, self-state monitoring and adjustment are achieved, and the acquired data are transmitted to a server side through a wireless gateway;
and receiving the acquired data through a wireless gateway, and sending the acquired data to a server.
Collecting the collected data sent by the wireless gateway through a server, analyzing the collected data by utilizing a big data analysis technology, predicting hidden cable hazards, early warning the occurrence of faults, and positioning fault positions in time through prefabricated cable geographical position information;
further, data acquisition is carried out on the cable environment data through an acquisition terminal according to a preset time interval, and the method specifically comprises the following steps:
monitoring the temperature of the cable through an RFID label temperature sensor on a cable joint temperature monitoring terminal, and setting a cable temperature alarm value, wherein the RFID label temperature sensor is arranged on the cable joint in a bundling manner;
monitoring the ambient temperature and the ambient humidity through an ambient temperature and humidity monitoring terminal, and setting an ambient temperature alarm value and an ambient humidity alarm value;
and monitoring the liquid level height through a cable immersion monitoring terminal.
Further, receiving the collected data through a wireless gateway specifically includes:
receiving and sending wireless data through an RFID radio frequency chip;
receiving and acquiring terminal data through an NB communication module, and routing the terminal data to a corresponding server;
the hardware management and the low-power consumption power supply management of the wireless gateway are realized through the MCU;
and the power support is provided for the wireless gateway through the lithium battery pack.
Further, the collected data sent by the wireless gateway is collected through the server, and the collected data is analyzed by using a big data analysis technology, which specifically comprises the following steps:
providing cloud services through a public cloud platform;
additionally arranging an application server and a database server through a national network cloud platform;
the early warning threshold value is adjusted by using big data analysis capability and learning capability through intelligent analysis monitoring software, and trend analysis, comparative analysis and historical iterative analysis are carried out on the information such as the collected data, the electricity consumption time interval, the geographic position, the natural environment and the like.
The invention provides an intelligent early warning device for a power cable, which comprises: the intelligent early warning system comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the computer program realizes the steps of the intelligent early warning method for the power cable when being executed by the processor.
The invention provides a computer readable storage medium, wherein an implementation program for information transmission is stored on the computer readable storage medium, and the steps of the intelligent early warning method for the power cable are realized when the program is executed by a processor.
By adopting the embodiment of the invention, the acquisition terminal is used for acquiring the data of the cable environment data according to the preset time interval, processing, storing and uploading the acquired data, the server side is used for analyzing the acquired data through a big data analysis technology, predicting the hidden danger of the cable according to the analysis result and early warning the occurrence of the fault, and the fault position is positioned through the prefabricated cable geographical position information.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a block diagram of a power cable intelligent warning system according to an embodiment of the present invention;
fig. 2 is an application scenario of the intelligent early warning system for power cables according to the embodiment of the present invention;
FIG. 3 is a flow chart of a power cable intelligent warning method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an apparatus according to a first embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise. Furthermore, the terms "mounted," "connected," and "connected" are to be construed broadly and may, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
System embodiment
According to an embodiment of the present invention, an intelligent early warning system for a power cable is provided, fig. 1 is a structural diagram of the intelligent early warning system for a power cable according to an embodiment of the present invention, and as shown in fig. 1, the intelligent early warning system for a power cable according to an embodiment of the present invention specifically includes: the system comprises an acquisition terminal 10, a wireless gateway 12 and a server 14;
the acquisition terminal 10 is used for carrying out data acquisition on cable environment data according to a preset time interval, processing, storing and uploading the acquired data, monitoring and adjusting the cable state according to the acquired data, transmitting the acquired data to a server through a wireless gateway, and specifically comprising:
cable joint temperature monitoring terminal for through RFID label temperature sensor monitoring cable temperature, set up cable temperature alarm value, wherein, RFID label temperature sensor installs in cable joint in order to tie up the mode, does not destroy the cable top layer, under the live working condition, by professional installation of going into the well, guarantees to implement the security, set up cable joint temperature monitoring terminal temperature measurement scope and do: 0-100 ℃, and the temperature alarm setting range is as follows: 00-100 ℃;
environment humiture monitor terminal for monitoring ambient temperature and ambient humidity set up ambient temperature alarm value and ambient humidity alarm value, temperature measurement scope: -40-80 ℃, ambient temperature measurement accuracy: ± 1%, humidity measurement range: 0-99.9% RH, ambient humidity measurement accuracy: +/-2%, and the temperature alarm setting range: -40-100 ℃, humidity alarm setting range: 0 to 100% RH.
And the cable immersion monitoring terminal is used for monitoring the liquid level height.
The wireless gateway 12 is configured to route the acquired data to a corresponding server, where the wireless gateway 12 specifically includes: the RFID radio frequency chip is used for receiving the acquired data of the acquisition terminal; the NB communication module is used for realizing communication from the wireless gateway to the server side and routing the terminal data to the corresponding server through TCP, HTTP, MQTT and T-link protocols; the MCU is used for realizing hardware management and low-power consumption power management of the wireless gateway; the lithium battery pack is used for providing power support for the wireless gateway, the wireless gateway shell is of a waterproof grade above IP65, the moisture-proof and waterproof performance is reliable, the battery is prevented from being affected with damp and spontaneous combustion or explosion, and the equipment is safe and reliable.
The server 14 is configured to collect the collected data sent by the wireless gateway, analyze the collected data through a big data analysis technology, predict a cable hidden trouble according to an analysis result, perform early warning on a fault, and locate a fault position through prefabricated cable geographical position information, where the server 14 specifically includes: the public cloud platform is used for providing cloud services; the national network cloud platform is used for providing cloud service by additionally arranging an application server and a database server, so that the system operation and data safety are effectively ensured; and the intelligent analysis monitoring module is used for adjusting the early warning threshold value through big data analysis capability and learning capability, and performing trend analysis, comparative analysis and historical iterative analysis according to the acquired data, the electricity utilization time period, the geographic position and the information of the natural environment.
And (3) trend analysis: the temperature and humidity changes of the power pipeline are analyzed by taking time as a main line, and taking the power utilization time period as the main line according to the temperature, humidity and water level information of the monitoring point. The fluctuation early warning threshold value of the trend analysis is based on a power voltage measurement coefficient of a laboratory, and combines the actual fluctuation change of the on-site trend to carry out abnormal early warning and intelligent learning. In the later period, by large data volume accumulation, analysis labels can be added by taking time as a main line, such as: changes in four seasons, weather changes, daily electricity consumption peak changes, etc. Such as: and (2) continuously monitoring the No. 1 well cable joint A for three years to form a cable skin temperature trend curve, an environment temperature and humidity curve, a water immersion curve and a weather change curve, wherein the dynamic threshold value of the point A changes along with the trend curve, the temperature of a certain point A is separated from the cable skin temperature curve, the temperature of the trend curve is 60 ℃ in the current day, the temperature of the trend curve is 65 ℃ in the current day, the trend temperature of the period in the history is 30 ℃ through weather analysis, and the weather temperature of the current day is 25 ℃, and then triggering alarm.
And (3) benchmarking analysis: if the state is a main line, analyzing the data difference of the adjacent state, the same scene state and the same attribute label, and analyzing the abnormal detection point condition which does not conform to the large rule event by comparing and analyzing the synchronous data rule and state. The initial comparison analysis algorithm is based on field monitoring data and carries out comparison analysis on labels with the same attributes, such as the same line, the same type of position, the same time, the same weather and the like. Such as: the cable joint A, B, C of the No. 1 well to the No. 5 well on the same line is continuously monitored for three years, each point has a respective trend curve, the temperature in the No. 1 well at a certain day is 40 ℃, the temperatures in other wells are 30 ℃, and the joints ABC in the No. 1 well all accord with the temperature curves, the system gives an alarm, an inspector arrives at the site, the asphalt pavement pouring construction is carried out near the No. 1 well, the cable in the well is not abnormal, the system inspects logs, and the alarm is eliminated; for another example, the alarm is triggered by the temperature of the 2# well joint ABC at the time point AB being 60 ℃ and the temperature of the point C being 70 ℃.
And in the later stage, the intelligent level of the platform can be increased by customizing the contrast factor tag and adding an analysis algorithm. The comparison and analysis is also a process for refining the knowledge of the inspection personnel, and is a verification process based on personnel experience and mass data.
And historical iterative analysis, namely, performing iterative summary on related historical data by taking the occurrence of abnormal faults as a basis and combining the occurrence of historical data abnormal events, wherein the historical data iterative algorithm is based on a factor algorithm, judges the reason for causing the historical data abnormal based on the abnormal event result, extracts historical abnormal data points, and summarizes data analysis labels such as data label association and summarized data threshold values. The iterative analysis of historical data is the core of the learning growth of an intelligent algorithm. Such as: the alarm of the 1# well A occurs twice in summer, the alarm is 65 ℃ and the alarm is 70 ℃, the fault occurs, the system starts to automatically monitor the well A, the alarm time is about 3 pm, the air temperature is over 45 ℃, the patrol personnel record and ground monitoring are combined, the reflection of light of a nearby new building glass curtain wall is found and just falls on the well, the system automatically records the well, and the threshold value is prefabricated again. Through system learning, similar situations occur in the 3# well, and the system automatically prefabricates the threshold again.
As shown in fig. 2, for an application scenario in one or more embodiments of the present disclosure, an acquisition terminal is installed in a downhole to acquire downhole cable data, an indoor temperature and humidity sensor 22 is used to acquire the temperature and humidity data in the well, an RFID tag temperature sensor 23 is used to acquire the temperature data of a cable connector, the RFID tag temperature sensor is installed in a cable connector 25 in a bundling manner, without damaging a surface layer of a cable 24, and is installed in the well by a professional under a live working condition to ensure implementation safety, the transformer 26 is used to acquire a water immersion condition of the cable, and an RFID reader/writer 21 of a gateway transmits the acquired data to the gateway.
Method embodiment
An intelligent early warning method for a power cable is provided, fig. 3 is a flow chart of the intelligent early warning method for the power cable according to the embodiment of the present invention, and as shown in fig. 3, the intelligent early warning method for the power cable according to the embodiment of the present invention specifically includes:
step S301, data acquisition is carried out on cable environment data according to preset time intervals through an acquisition terminal, the acquired data are processed, stored and uploaded, self state monitoring and adjustment are achieved, the acquired data are transmitted to a server through a wireless gateway, and the step S301 specifically comprises the following steps: through cable joint temperature monitoring terminal for through RFID label temperature sensor monitoring cable temperature, set up cable temperature alarm value, wherein, RFID label temperature sensor installs in cable joint with tying up the mode, does not destroy the cable top layer, under the electrified operation condition, by professional installation of going into the well, guarantees to implement the security, and it is to set up cable joint temperature monitoring terminal temperature measurement range: 0-100 ℃, and the temperature alarm setting range is as follows: 00-100 ℃; through environment humiture monitor terminal, monitoring ambient temperature and ambient humidity set up ambient temperature alarm value and ambient humidity alarm value, temperature measurement scope: -40-80 ℃, ambient temperature measurement accuracy: ± 1%, humidity measurement range: 0-99.9% RH, ambient humidity measurement accuracy: +/-2%, and the temperature alarm setting range: -40-100 ℃, humidity alarm setting range: 0 to 100% RH; and monitoring the liquid level height through a cable immersion monitoring terminal.
Step S302, receiving the collected data through a wireless gateway, and sending the collected data to a server, wherein the step S302 specifically comprises: receiving the collected data of the collecting terminal through the RFID radio frequency chip; the communication from the wireless gateway to the server side is realized through an NB communication module, and the terminal data is routed to a corresponding server through TCP, HTTP, MQTT and T-link protocols; the hardware management and the low-power consumption power supply management of the wireless gateway are realized through the MCU; through the lithium cell group, for wireless gateway provides electric power support, wireless gateway shell is the waterproof grade more than IP65, and dampproofing waterproof performance is reliable, avoids the battery to wet spontaneous combustion or explosion, equipment safe and reliable.
Step S303, collecting the collected data sent by the wireless gateway through a server, analyzing the collected data by utilizing a big data analysis technology, predicting hidden cable troubles, early warning the occurrence of faults, and positioning the fault positions in time through the geographical position information of the prefabricated cable; step S303 specifically includes: providing cloud services through a public cloud platform; an application server and a database server are additionally arranged on the national network cloud platform for providing cloud service, so that the system operation and data safety are effectively ensured; the early warning threshold value is adjusted by using big data analysis capability and learning capability through intelligent analysis monitoring software, and trend analysis, comparative analysis and historical iterative analysis are carried out on the information such as the collected data, the electricity consumption time interval, the geographic position, the natural environment and the like.
And (3) trend analysis: the temperature and humidity changes of the power pipeline are analyzed by taking time as a main line, and taking the power utilization time period as the main line according to the temperature, humidity and water level information of the monitoring point. The fluctuation early warning threshold value of the trend analysis is based on a power voltage measurement coefficient of a laboratory, and combines the actual fluctuation change of the on-site trend to carry out abnormal early warning and intelligent learning. In the later period, by large data volume accumulation, analysis labels can be added by taking time as a main line, such as: changes in four seasons, weather changes, daily electricity consumption peak changes, etc. Such as: and (2) continuously monitoring the No. 1 well cable joint A for three years to form a cable skin temperature trend curve, an environment temperature and humidity curve, a water immersion curve and a weather change curve, wherein the dynamic threshold value of the point A changes along with the trend curve, the temperature of a certain point A is separated from the cable skin temperature curve, the temperature of the trend curve is 60 ℃ in the current day, the temperature of the trend curve is 65 ℃ in the current day, the trend temperature of the period in the history is 30 ℃ through weather analysis, and the weather temperature of the current day is 25 ℃, and then triggering alarm.
And (3) benchmarking analysis: if the state is a main line, analyzing the data difference of the adjacent state, the same scene state and the same attribute label, and analyzing the abnormal detection point condition which does not conform to the large rule event by comparing and analyzing the synchronous data rule and state. The initial comparison analysis algorithm is based on field monitoring data and carries out comparison analysis on labels with the same attributes, such as the same line, the same type of position, the same time, the same weather and the like. Such as: the cable joint A, B, C of the No. 1 well to the No. 5 well on the same line is continuously monitored for three years, each point has a respective trend curve, the temperature in the No. 1 well at a certain day is 40 ℃, the temperatures in other wells are 30 ℃, and the joints ABC in the No. 1 well all accord with the temperature curves, the system gives an alarm, an inspector arrives at the site, the asphalt pavement pouring construction is carried out near the No. 1 well, the cable in the well is not abnormal, the system inspects logs, and the alarm is eliminated; for another example, the alarm is triggered by the temperature of the 2# well joint ABC at the time point AB being 60 ℃ and the temperature of the point C being 70 ℃.
And in the later stage, the intelligent level of the platform can be increased by customizing the contrast factor tag and adding an analysis algorithm. The comparison and analysis is also a process for refining the knowledge of the inspection personnel, and is a verification process based on personnel experience and mass data.
And historical iterative analysis, namely, performing iterative summary on related historical data by taking the occurrence of abnormal faults as a basis and combining the occurrence of historical data abnormal events, wherein the historical data iterative algorithm is based on a factor algorithm, judges the reason for causing the historical data abnormal based on the abnormal event result, extracts historical abnormal data points, and summarizes data analysis labels such as data label association and summarized data threshold values. The iterative analysis of historical data is the core of the learning growth of an intelligent algorithm. Such as: the alarm of the 1# well A occurs twice in summer, the alarm is 65 ℃ and the alarm is 70 ℃, the fault occurs, the system starts to automatically monitor the well A, the alarm time is about 3 pm, the air temperature is over 45 ℃, the patrol personnel record and ground monitoring are combined, the reflection of light of a nearby new building glass curtain wall is found and just falls on the well, the system automatically records the well, and the threshold value is prefabricated again. Through system learning, similar situations occur in the 3# well, and the system automatically prefabricates the threshold again.
Apparatus embodiment one
An embodiment of the present invention provides an intelligent early warning device for a power cable, as shown in fig. 4, including: a memory 40, a processor 42 and a computer program stored on the memory 40 and executable on the processor 42, which computer program when executed by the processor 42 performs the steps as described in the method embodiments.
Device embodiment II
An embodiment of the present invention provides a computer-readable storage medium, on which an implementation program for information transmission is stored, and when executed by the processor 42, the program implements the steps as described in the method embodiment.
The computer-readable storage medium of this embodiment includes, but is not limited to: ROM, RAM, magnetic or optical disks, and the like.
It should be noted that the embodiment of the storage medium in this specification and the embodiment of the method in this specification are based on the same inventive concept, and therefore, specific implementation of this embodiment may refer to implementation of the corresponding method described above, and repeated details are not described here.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
In the 30 s of the 20 th century, improvements in a technology could clearly be distinguished between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the units may be implemented in the same software and/or hardware or in multiple software and/or hardware when implementing the embodiments of the present description.
One skilled in the art will recognize that one or more embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The description has been presented with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the description. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
One or more embodiments of the present description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of this document and is not intended to limit this document. Various modifications and changes may occur to those skilled in the art from this document. Any modifications, equivalents, improvements, etc. which come within the spirit and principle of the disclosure are intended to be included within the scope of the claims of this document.
Claims (10)
1. A power cable intelligent early warning system, characterized in that, the system includes: the system comprises an acquisition terminal, a wireless gateway and a server side;
the system comprises an acquisition terminal, a server and a wireless gateway, wherein the acquisition terminal is used for acquiring data of cable environment data according to a preset time interval, processing, storing and uploading the acquired data, monitoring and adjusting the state of a cable according to the acquired data and transmitting the acquired data to the server through the wireless gateway;
the wireless gateway is used for routing the acquired data to a corresponding server;
and the server is used for collecting the collected data sent by the wireless gateway, analyzing the collected data through a big data analysis technology, predicting the hidden cable danger according to an analysis result, early warning the occurrence of a fault, and positioning the fault position through the geographical position information of the prefabricated cable.
2. The system according to claim 1, wherein the acquisition terminal specifically comprises:
the cable joint temperature monitoring terminal is used for monitoring the temperature of a cable through an RFID label temperature sensor and setting a cable temperature alarm value, wherein the RFID label temperature sensor is arranged on a cable joint in a bundling mode;
the environment temperature and humidity monitoring terminal is used for monitoring environment temperature and environment humidity and setting an environment temperature alarm value and an environment humidity alarm value;
and the cable immersion monitoring terminal is used for monitoring the liquid level height.
3. The system according to claim 1, wherein the wireless gateway specifically comprises:
the RFID radio frequency chip is used for receiving the acquired data of the acquisition terminal;
the NB communication module is used for realizing communication from the wireless gateway to the server and routing the acquired data to the corresponding server;
the MCU is used for realizing hardware management and low-power consumption power management of the wireless gateway;
and the lithium battery pack is used for providing power support for the wireless gateway.
4. The system according to claim 1, wherein the server specifically comprises:
the public cloud platform is used for providing cloud services;
the national network cloud platform is used for providing cloud service by additionally arranging an application server and a database server;
and the intelligent analysis monitoring module is used for adjusting the early warning threshold value through big data analysis capability and learning capability, and performing trend analysis, comparative analysis and historical iterative analysis according to the acquired data, the electricity utilization time period, the geographic position and the information of the natural environment.
5. A power cable intelligent early warning method is characterized by comprising the following steps:
the method comprises the steps that data acquisition is carried out on cable environment data according to preset time intervals through an acquisition terminal, the acquired data are processed, stored and uploaded, self-state monitoring and adjustment are achieved, and the acquired data are transmitted to a server side through a wireless gateway;
receiving the acquired data through a wireless gateway and sending the acquired data to a server;
the collected data sent by the wireless gateway are collected through a server, the collected data are analyzed through a big data analysis technology, cable hidden dangers are predicted, faults are early warned, and fault positions are timely located through prefabricated cable geographic position information.
6. The method according to claim 5, wherein the data acquisition of the cable environment data by the acquisition terminal at predetermined time intervals specifically comprises:
monitoring the temperature of the cable through an RFID label temperature sensor on a cable joint temperature monitoring terminal, and setting a cable temperature alarm value, wherein the RFID label temperature sensor is arranged on the cable joint in a bundling manner;
monitoring the ambient temperature and the ambient humidity through an ambient temperature and humidity monitoring terminal, and setting an ambient temperature alarm value and an ambient humidity alarm value;
and monitoring the liquid level height through a cable immersion monitoring terminal.
7. The method according to claim 5, wherein the receiving the collected data by the wireless gateway specifically comprises:
receiving the acquired data of the acquisition terminal through the RFID radio frequency chip;
the communication from the wireless gateway to the server side is realized through an NB communication module, and the acquired data is routed to a corresponding server;
the hardware management and the low-power consumption power supply management of the wireless gateway are realized through the MCU;
and the power support is provided for the wireless gateway through the lithium battery pack.
8. The method according to claim 5, wherein the collecting data sent by the wireless gateway is collected by a server, and the analyzing of the collecting data is performed by using a big data analysis technology, specifically comprising:
providing cloud services through a public cloud platform;
an application server and a database server are additionally arranged through a national network cloud platform and used for providing cloud services;
the early warning threshold value is adjusted by using big data analysis capability and learning capability through intelligent analysis monitoring software, and trend analysis, comparative analysis and historical iterative analysis are carried out on the information such as the collected data, the power consumption time interval, the geographic position, the natural environment and the like.
9. The utility model provides a power cable intelligence early warning device which characterized in that includes: memory, processor and computer program stored on the memory and executable on the processor, the computer program when executed by the processor implementing the steps of the power cable smart warning method as claimed in any one of claims 5 to 8.
10. A computer-readable storage medium, on which an information transfer implementation program is stored, which when executed by a processor implements the steps of the power cable smart warning method as claimed in any one of claims 5 to 8.
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