CN111915846B - Intelligent cloud lightning protection operation and maintenance system based on cloud computing - Google Patents

Intelligent cloud lightning protection operation and maintenance system based on cloud computing Download PDF

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CN111915846B
CN111915846B CN202010801589.0A CN202010801589A CN111915846B CN 111915846 B CN111915846 B CN 111915846B CN 202010801589 A CN202010801589 A CN 202010801589A CN 111915846 B CN111915846 B CN 111915846B
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殷存泽
杨建航
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Anhui Yizong Electronic Technology Co ltd
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Abstract

The invention discloses an intelligent cloud lightning protection operation and maintenance system based on cloud computing, which is used for solving the problems of single protection means, insufficient reference data and weak autonomous troubleshooting capability of the existing lightning protection operation and maintenance system and comprises a cloud computing platform, an environment monitoring module, a lightning protection monitoring module, an algorithm auxiliary module, a power supply module, an alarm driving module, a human-computer interaction module, a data query module and a data storage module; the invention is provided with the algorithm auxiliary module, and the design takes the existing historical data as the basis to construct the auxiliary model, so that the overall lightning protection effect of the system can be improved; the lightning protection system is provided with the environment monitoring module, and the lightning generation coefficient is calculated by using the environment monitoring module, so that the lightning protection effect of the whole system is better, and meanwhile, the energy is saved; the invention is provided with the man-machine interaction module, and the safety factor of the surge protector can be inquired through the intelligent terminal, so that the autonomous troubleshooting capability of the system is improved.

Description

Intelligent cloud lightning protection operation and maintenance system based on cloud computing
Technical Field
The invention belongs to the technical field of lightning stroke protection, and particularly relates to an intelligent cloud lightning protection operation and maintenance system based on cloud computing.
Background
With the rapid development of electronic information technology, economic losses and social influences caused by thunderstorm disasters are increasing. Lightning is known to be extremely destructive, with voltages up to millions of volts and transient currents up to hundreds of thousands of amperes. The destructive consequences of a lightning strike are mainly reflected in three areas: 1) equipment destruction, casualties; 2) reduced life of the equipment or components; 3) the transmitted or stored signals and data are interfered or lost, and even the electronic equipment generates misoperation to temporarily break down or stop the whole system. The operation and maintenance monitoring system is damaged by lightning stroke, and the system breakdown event is frequent. Meanwhile, people cannot judge which monitoring equipment is struck by lightning in advance, so that the implementation difficulty of coping strategies is increased.
Because of the unpredictability of lightning stroke, people cannot predict which equipment and lines are struck by lightning in advance, and the lightning stroke position and the damage degree are determined only through investigation and monitoring when the lightning stroke event occurs most of the time, so that the timely receiving and transmitting of monitoring information can be influenced, and the investigation is mostly carried out manually, and the automation cannot be realized. Therefore, not only multiple protection of the operation and maintenance system is required to avoid the damage of lightning stroke to the operation and maintenance system, but also the autonomous troubleshooting capability of the operation and maintenance system needs to be improved.
Disclosure of Invention
In order to solve the problems of the existing lightning protection operation and maintenance system, the invention relates to an intelligent cloud lightning protection operation and maintenance system based on cloud computing, which comprises a cloud computing platform, a human-computer interaction module, an alarm driving module, an environment monitoring module, a lightning protection monitoring module and an algorithm auxiliary module; the invention adds the algorithm auxiliary module, and the design constructs the auxiliary model based on the existing historical data, so that the overall lightning protection effect of the system can be improved; the environment monitoring module is arranged, the climate environment of the monitoring area is monitored by the environment monitoring module, the lightning generation coefficient of the monitoring area is calculated according to a formula, and a corresponding instruction is sent to the designated module according to the comparison between the lightning generation coefficient and the preset threshold value, so that the lightning protection effect of the whole system is better, the energy is saved, and the protection means of the system is increased; the alarm driving module is arranged, and the alarm driving module sends an alarm to the intelligent terminal after receiving the instruction sent by the cloud computing platform, so that the early warning function of the system is realized; the data storage module is arranged, and the design aims to make up for the defect of the storage capacity of the cloud computing platform, so that the system is more complete and stable; according to the invention, the man-machine interaction module is arranged, so that a user can modify the preset threshold value and inquire the safety factor of the surge protector through the intelligent terminal, and the autonomous troubleshooting capability of the system is improved.
The purpose of the invention can be realized by the following technical scheme: an intelligent cloud lightning protection operation and maintenance system based on cloud computing comprises a cloud computing platform, a human-computer interaction module, an alarm driving module, an environment monitoring module, a lightning protection monitoring module and an algorithm auxiliary module;
the environment monitoring module is used for monitoring the environmental information of a monitoring area where the operation and maintenance system is located, the environment monitoring module comprises a temperature monitoring node, a humidity monitoring node, a wind power monitoring node and a cloud layer height node, and the specific monitoring steps are as follows:
the method comprises the following steps: monitoring environmental information of a monitoring area in real time by using a temperature monitoring node, a humidity monitoring node and a wind power monitoring node, acquiring cloud layer height data of the monitoring area from a meteorological platform through a cloud layer height node, and transmitting the environmental monitoring data to a cloud computing platform, wherein the environmental monitoring data comprises temperature, humidity, wind speed and cloud layer height;
step two: after the cloud computing platform receives the environment monitoring data, the temperature, the humidity, the wind speed and the cloud layer height are respectively marked as Wt1、St1、Ft1And Yt1T1 is the environment monitoring time;
step three: obtaining lightning production coefficient L of monitoring area by formulat1The calculation formula is
Figure BDA0002627581630000031
Figure BDA0002627581630000032
Wherein alpha, beta, gamma and delta are specific proportionality coefficients;
step four: when lightning produces coefficient Lt1When the environmental monitoring data, the environmental monitoring time and the lightning generation coefficient are less than or equal to the set threshold value, the cloud computing platform sends the environmental monitoring data, the environmental monitoring time and the lightning generation coefficient to a K1 memory of the data storage module; when lightning produces coefficient Lt1When the lightning generation instruction is larger than the set threshold value, the cloud computing platform sends the lightning generation instruction toThe lightning protection monitoring module is used for simultaneously transmitting the environment monitoring data, the environment monitoring time and the lightning generation coefficient to a K1 memory of the data storage module by the cloud computing platform;
the lightning protection monitoring module is used for monitoring real-time data of the surge protector, the lightning protection monitoring module is linearly connected with the surge protector, the lightning protection monitoring module comprises a lightning stroke counter, a leakage current monitoring node, a full current monitoring node and a resistive current monitoring node, and the specific monitoring steps are as follows:
z1: after receiving a lightning generation instruction sent by a cloud computing platform, a lightning protection monitoring module monitors the lightning stroke frequency, the leakage current, the full current and the resistive current of a surge protector every other minute and sends lightning monitoring data to the cloud computing platform, wherein the lightning monitoring data comprises the lightning stroke frequency, the leakage current, the full current and the resistive current;
z2: after the cloud computing platform receives the lightning monitoring data, marking the total lightning stroke, the average leakage current value, the effective full current value and the peak resistive current value as J respectivelyt2、ILt2、IXt2And IRt2T2 is lightning monitoring time;
z3: using formulas
Figure BDA0002627581630000033
i represents the serial number of the surge protector in the operation and maintenance system, and obtains the safety factor S of the surge protectori,t2Wherein delta, epsilon,
Figure BDA0002627581630000034
Is a specific proportionality coefficient;
z4: when the safety factor Si,t2When the lightning monitoring data is less than or equal to the set threshold value, the cloud computing platform monitors the lightning monitoring data, the lightning monitoring time and the safety factor Si,t2Sending the data to a data storage module K2 for storage; when the safety factor Si,t2When the lightning monitoring data is larger than the set threshold value, the cloud computing platform sends a danger instruction to the alarm driving module, and simultaneously, the lightning monitoring data, the lightning monitoring time and the safety factor S are usedi,t2Sending the data to a data storage module K2 for storage;
the algorithm auxiliary module is trained through monitoring data of the environment monitoring module to construct an auxiliary prediction model, the algorithm auxiliary module comprises a data processing unit and a model training unit, and the specific construction steps are as follows:
v1: the algorithm auxiliary module sends a data request instruction to the cloud computing platform at regular time, the cloud computing platform sends a storage opening instruction to the data storage module after receiving the data request instruction, and the data storage module sends the environmental monitoring data, the environmental monitoring time and the lightning monitoring coefficient stored in the K1 storage to the data processing unit after receiving the storage opening instruction;
v2: after receiving environment monitoring data, environment monitoring time and lightning monitoring coefficients, a data processing unit preprocesses the data, wherein the preprocessing comprises abnormal value smoothing and data normalization; taking environment monitoring data and environment monitoring time as input parameters of a model training unit and a lightning generation coefficient Lt1As an output parameter of the model training unit, and the model is trained by assigning the output parameter to 0 or 1, wherein 0 represents the lightning production coefficient Lt1Less than or equal to a preset threshold value, 1 represents a lightning production coefficient Lt1Greater than a preset threshold;
v3: taking the latest 24h of environment monitoring data and environment detection time stored in a K1 memory as input parameters of a model training unit, and performing secondary training on the model by using the latest 24h of environment monitoring data and a model output result of an environment monitoring module when the output data of the model is 0; when the output data of the model is 1, performing secondary training on the model by using the latest 24h environmental monitoring data of the environmental monitoring module and the model output result, and sending a lightning generation instruction to the lightning protection monitoring module through the cloud computing platform.
Preferably, the system further comprises a data query module, the data query module is configured to query the data in the data storage module through keywords, the keywords include time and number of the surge protector, and the specific query steps are as follows:
b1: a user inputs keywords to the human-computer interaction module through the intelligent terminal, and the human-computer interaction module sends a data query instruction and the keywords to the data query module through the cloud computing platform;
b2: after the data query module receives the data query instruction and the keywords, searching the keywords in the data storage module through the keywords and acquiring corresponding data;
b3: the data storage module sends the data searched according to the keywords to the man-machine interaction module through the cloud computing platform, and a user can check the data through the intelligent terminal.
Preferably, the data storage module comprises a K1 memory, a K2 memory and a K3 memory, wherein the K1 memory is used for storing environment monitoring data, environment monitoring time and lightning production coefficients, the K2 memory is used for storing lightning monitoring data, lightning monitoring time and safety factors, the K3 memory is used for storing other data in the working process of the system, and the other data comprise cache data generated during the running of the system and instruction records sent by a cloud computing platform; the system is also provided with a data backup module, wherein the data backup module is used for regularly backing up data of the data storage module, the data storage module and the data backup module are linearly connected with the cloud computing platform, and the data storage module is linearly connected with the data backup module.
Preferably, the human-computer interaction module is used for information transmission between a user and the cloud computing platform through the intelligent terminal, the human-computer interaction module is in linear connection with the cloud computing platform, the human-computer interaction module is in wireless connection with the intelligent terminal, and the intelligent terminal comprises an intelligent mobile phone, a notebook computer and an intelligent display.
Preferably, the alarm driving module sends an alarm according to a dangerous instruction sent by the cloud computing platform, the alarm driving module comprises a large-screen display unit and an audible and visual alarm unit, when the alarm driving module receives the dangerous instruction, the audible and visual alarm unit is driven to alarm, environment monitoring data, environment monitoring time, a thunder and lightning generation coefficient, thunder and lightning monitoring data, thunder and lightning monitoring time and safety coefficient are sent to the large-screen display unit, and the dangerous alarm information is sent to the man-machine interaction module, and a user uses the intelligent terminal to inquire about a damaged surge protector.
Preferably, the system further comprises a power supply module, the power supply module supplies power to each module, and the power supply module is in linear connection with the surge protector.
Preferably, the model training unit includes a neural network model, the neural network model is an error back propagation neural network, the error back propagation neural network includes an input layer, an intermediate layer, and an output layer, the input layer includes five data nodes, the intermediate layer includes eleven data nodes, and the output layer includes two data nodes.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention provides an intelligent cloud lightning protection operation and maintenance system based on cloud computing, an algorithm auxiliary module is added, an auxiliary model is constructed on the basis of the existing historical data, and the overall lightning protection effect of the system can be improved;
2. the environment monitoring module is arranged, the climate environment of the monitoring area is monitored by the environment monitoring module, the lightning generation coefficient of the monitoring area is calculated according to a formula, and a corresponding instruction is sent to the designated module according to the comparison between the lightning generation coefficient and the preset threshold value, so that the lightning protection effect of the whole system is better, the energy is saved, and the protection means of the system is increased;
3. the alarm driving module is arranged, and the alarm driving module sends an alarm to the intelligent terminal after receiving the instruction sent by the cloud computing platform, so that the early warning function of the system is realized; the data storage module is arranged, and the design aims to make up for the defect of the storage capacity of the cloud computing platform, so that the system is more complete and stable; according to the invention, the man-machine interaction module is arranged, so that a user can modify the preset threshold value and inquire the safety factor of the surge protector through the intelligent terminal, and the autonomous troubleshooting capability of the system is improved.
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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, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram 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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
As shown in fig. 1, an intelligent cloud lightning protection operation and maintenance system based on cloud computing comprises a cloud computing platform, a human-computer interaction module, an alarm driving module, an environment monitoring module, a lightning protection monitoring module, an algorithm auxiliary module, a data query module, a data storage module, a data backup module and a power supply module;
the environment monitoring module is used for monitoring the environmental information of a monitoring area where the operation and maintenance system is located, the environment monitoring module comprises a temperature monitoring node, a humidity monitoring node, a wind power monitoring node and a cloud layer height node, and the specific monitoring steps are as follows:
the method comprises the following steps: monitoring environmental information of a monitoring area in real time by using a temperature monitoring node, a humidity monitoring node and a wind power monitoring node, acquiring cloud layer height data of the monitoring area from a meteorological platform through a cloud layer height node, and transmitting the environmental monitoring data to a cloud computing platform, wherein the environmental monitoring data comprises temperature, humidity, wind speed and cloud layer height;
step two: after the cloud computing platform receives the environment monitoring data, the temperature, the humidity, the wind speed and the cloud layer height are respectively marked as Wt1、St1、Ft1And Yt1T1 is the environment monitoring time;
step three: obtaining lightning production coefficient L of monitoring area by formulat1The calculation formula is
Figure BDA0002627581630000071
Figure BDA0002627581630000072
Wherein alpha, beta, gamma and delta are specific proportionality coefficients;
step four: when lightning produces coefficient Lt1When the environmental monitoring data, the environmental monitoring time and the lightning generation coefficient are less than or equal to the set threshold value, the cloud computing platform sends the environmental monitoring data, the environmental monitoring time and the lightning generation coefficient to a K1 memory of the data storage module; when lightning produces coefficient Lt1When the lightning generation coefficient is larger than the set threshold value, the cloud computing platform sends a lightning generation instruction to the lightning protection monitoring module, and simultaneously sends environment monitoring data, environment monitoring time and the lightning generation coefficient to a K1 memory of the data storage module;
the lightning protection monitoring module is used for monitoring real-time data of the surge protector, the lightning protection monitoring module is linearly connected with the surge protector, the lightning protection monitoring module comprises a lightning stroke counter, a leakage current monitoring node, a full current monitoring node and a resistive current monitoring node, and the specific monitoring steps are as follows:
z1: after receiving a lightning generation instruction sent by a cloud computing platform, a lightning protection monitoring module monitors the lightning stroke frequency, the leakage current, the full current and the resistive current of a surge protector every other minute and sends lightning monitoring data to the cloud computing platform, wherein the lightning monitoring data comprises the lightning stroke frequency, the leakage current, the full current and the resistive current;
z2: after the cloud computing platform receives the lightning monitoring data, marking the total lightning stroke, the average leakage current value, the effective full current value and the peak resistive current value as J respectivelyt2、ILt2、IXt2And IRt2T2 is lightning monitoring time;
z3: using formulas
Figure BDA0002627581630000081
Figure BDA0002627581630000082
i represents the serial number of the surge protector in the operation and maintenance system, and obtains the safety factor S of the surge protectori,t2Wherein delta, epsilon,
Figure BDA0002627581630000083
Is a specific proportionality coefficient;
z4: when the safety factor Si,t2When the lightning monitoring data is less than or equal to the set threshold value, the cloud computing platform monitors the lightning monitoring data, the lightning monitoring time and the safety factor Si,t2Sending the data to a data storage module K2 for storage; when the safety factor Si,t2When the lightning monitoring data is larger than the set threshold value, the cloud computing platform sends a danger instruction to the alarm driving module, and simultaneously, the lightning monitoring data, the lightning monitoring time and the safety factor S are usedi,t2Sending the data to a data storage module K2 for storage;
the algorithm auxiliary module is trained through monitoring data of the environment monitoring module to construct an auxiliary prediction model, the algorithm auxiliary module comprises a data processing unit and a model training unit, and the specific construction steps are as follows:
v1: the algorithm auxiliary module sends a data request instruction to the cloud computing platform at regular time, the cloud computing platform sends a storage opening instruction to the data storage module after receiving the data request instruction, and the data storage module sends the environmental monitoring data, the environmental monitoring time and the lightning monitoring coefficient stored in the K1 storage to the data processing unit after receiving the storage opening instruction;
v2: after receiving environment monitoring data, environment monitoring time and lightning monitoring coefficients, a data processing unit preprocesses the data, wherein the preprocessing comprises abnormal value smoothing and data normalization; taking environment monitoring data and environment monitoring time as input parameters of a model training unit and a lightning generation coefficient Lt1As an output parameter of the model training unit, and the model is trained by assigning the output parameter to 0 or 1, wherein 0 represents the lightning production coefficient Lt1Less than or equal to a preset threshold value, 1 represents a lightning production coefficient Lt1Greater than a preset threshold;
v3: taking the latest 24h of environment monitoring data and environment detection time stored in a K1 memory as input parameters of a model training unit, and performing secondary training on the model by using the latest 24h of environment monitoring data and a model output result of an environment monitoring module when the output data of the model is 0; when the output data of the model is 1, performing secondary training on the model by using the latest 24h environmental monitoring data of the environmental monitoring module and the model output result, and sending a lightning generation instruction to the lightning protection monitoring module through the cloud computing platform.
The data query module is used for querying data in the data storage module through keywords, the keywords comprise time and surge protector numbers, and the specific query steps are as follows:
b1: a user inputs keywords to the human-computer interaction module through the intelligent terminal, and the human-computer interaction module sends a data query instruction and the keywords to the data query module through the cloud computing platform;
b2: after the data query module receives the data query instruction and the keywords, searching the keywords in the data storage module through the keywords and acquiring corresponding data;
b3: the data storage module sends the data searched according to the keywords to the man-machine interaction module through the cloud computing platform, and a user can check the data through the intelligent terminal.
The data storage module comprises a K1 memory, a K2 memory and a K3 memory, wherein the K1 memory is used for storing environment monitoring data, environment monitoring time and lightning production coefficients, the K2 memory is used for storing the lightning monitoring data, the lightning monitoring time and safety factors, the K3 memory is used for storing other data in the working process of the system, and the other data comprise cache data generated during the operation of the system and instruction records sent by a cloud computing platform; the system is also provided with a data backup module, wherein the data backup module is used for regularly backing up data of the data storage module, the data storage module and the data backup module are linearly connected with the cloud computing platform, and the data storage module is linearly connected with the data backup module.
The human-computer interaction module is used for information transmission between a user and the cloud computing platform through the intelligent terminal, the human-computer interaction module is in linear connection with the cloud computing platform, the human-computer interaction module is in wireless connection with the intelligent terminal, and the intelligent terminal comprises an intelligent mobile phone, a notebook computer and an intelligent display.
Alarm drive module sends out the police dispatch newspaper according to the dangerous instruction that cloud computing platform sent, alarm drive module includes large-size screen display element and audible-visual alarm unit, and when alarm drive module received dangerous instruction, drive audible-visual alarm unit reported to the police to send environment monitoring data, environment monitoring time, thunder and lightning production coefficient, thunder and lightning monitoring data, thunder and lightning monitoring time and factor of safety to large-size screen display element, and send "dangerous warning" information to man-machine interaction module, the user uses intelligent terminal to inquire the surge protector of damage.
The system further comprises a power supply module, the power supply module supplies power to each module, and the power supply module is in linear connection with the surge protector.
The model training unit comprises a neural network model, the neural network model is an error back propagation neural network, the error back propagation neural network comprises an input layer, a middle layer and an output layer, the input layer comprises five data nodes, the middle layer comprises eleven data nodes, and the output layer comprises two data nodes.
The system still includes GIS intelligent monitoring module, GIS intelligent monitoring module shows the monitoring effect of specific area lightning protection operation and maintenance system in order to realize the multiple spot networking control through internet of things, specific area includes provincial level administrative area, city level administrative area and county level administrative area, GIS intelligent monitoring module includes controller, coordinate identification unit, data storage unit and management display element, the management display element includes map display node, data statistics node and data access node, and concrete monitoring step is:
m1: the management personnel import geographic coordinates of the intelligent cloud lightning protection operation and maintenance systems through the coordinate identification unit, and the controller acquires environment monitoring data, lightning monitoring data and safety factors of the surge protectors of the intelligent cloud lightning protection systems through the Internet of things technology and sends the environment monitoring data, the lightning monitoring data and the safety factors to the data storage module and the management display unit;
m2: after the data storage module receives the data, classified storage is carried out according to the receiving time and the geographic coordinates of the operation and maintenance system;
m3: after the management display unit receives the data, the map display unit marks on a map according to the geographic coordinates of the operation and maintenance system, and the specific marking steps are as follows:
w1: when the safety coefficient of the surge protector in the operation and maintenance system is larger than a preset threshold value, the operation and maintenance system is marked by using a triangle on a map, and the operation and maintenance system is marked by a formula
Figure BDA0002627581630000111
Obtaining the marking coefficient of the operation and maintenance system
Figure BDA0002627581630000112
When in use
Figure BDA0002627581630000113
When the triangle is filled with yellow, when
Figure BDA0002627581630000114
When the triangle is filled with orange color, when
Figure BDA0002627581630000115
Then, the triangle is filled with red;
w2: when the safety coefficient of a surge protector in the operation and maintenance system is smaller than or equal to a preset threshold value, marking the operation and maintenance system by using a circle on a map, and filling the circle into green;
m4: the data statistics node counts the number of safety factors of surge protectors in the intelligent cloud lightning protection operation and maintenance system, wherein the proportion that the safety factors are larger than a preset threshold value is F1, the proportion that the safety factors are smaller than or equal to the preset threshold value is F2, the result is displayed by a pie chart, the area represented by F1 is filled with red, and the area represented by F2 is filled with green;
m5: the data access node divides the geographic coordinates of the intelligent cloud lightning protection operation and maintenance system into two rows for display, the display sequence of the geographic coordinates of the operation and maintenance system is sorted according to the longitude, and a manager clicks the corresponding geographic coordinates to inquire the data of the operation and maintenance system;
the GIS intelligent monitoring module is used for intensively storing and displaying the lightning protection effect of the operation and maintenance system in the specific area, and the map display node, the data statistics node and the data access node are used for displaying the acquired data in a classified mode, so that the operation and maintenance system in the area can be accurately monitored, and the operation and maintenance system is maintained and rush-repaired.
The above formulas are all quantitative calculation, the formula is a formula obtained by acquiring a large amount of data and performing software simulation to obtain the latest real situation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The working principle of the invention is as follows: the environmental monitoring module monitors the climate environment of a monitoring area and sends the climate environment to the cloud computing platform for processing, the lightning production coefficient is calculated according to a formula, when the lightning production coefficient is larger than a set threshold value, the lightning protection monitoring module monitors the surge protector in real time and sends data to the cloud computing platform for calculating the safety coefficient of the surge protector, and corresponding instructions are generated by the cloud computing platform and sent to the human-computer interaction module and the alarm driving module;
the alarm driving module sends out an alarm according to the instruction sent by the cloud computing platform; the algorithm auxiliary module trains an error back propagation neural network by using historical data in the data storage module, takes monitoring data of the environment monitoring module in the last 24h as input of the model, and performs secondary training on the model by using the environment monitoring data of the environment monitoring module in the last 24h and an output result of the model when the output data of the model is 0; when the output data of the model is 1, performing secondary training on the model by using the environment monitoring data of the environment monitoring module in the last 24h and the output result of the model, and sending an instruction to the lightning protection monitoring module through the cloud computing platform; the user can check the lightning strike condition in the operation and maintenance system and the data stored in the memory through the man-machine interaction module.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.

Claims (7)

1. An intelligent cloud lightning protection operation and maintenance system based on cloud computing is characterized by comprising a cloud computing platform, a human-computer interaction module, an alarm driving module, an environment monitoring module, a lightning protection monitoring module and an algorithm auxiliary module;
the environment monitoring module is used for monitoring the environmental information of a monitoring area where the operation and maintenance system is located, the environment monitoring module comprises a temperature monitoring node, a humidity monitoring node, a wind power monitoring node and a cloud layer height node, and the specific monitoring steps are as follows:
the method comprises the following steps: monitoring environmental information of a monitoring area in real time by using a temperature monitoring node, a humidity monitoring node and a wind power monitoring node, acquiring cloud layer height data of the monitoring area from a meteorological platform through a cloud layer height node, and transmitting the environmental monitoring data to a cloud computing platform, wherein the environmental monitoring data comprises temperature, humidity, wind speed and cloud layer height;
step two: after the cloud computing platform receives the environment monitoring data, the temperature, the humidity, the wind speed and the cloud layer height are respectively marked as Wt1、St1、Ft1And Yt1T1 is the environment monitoring time;
step three: obtaining lightning production coefficient L of monitoring area by formulat1The calculation formula is
Figure FDA0002627581620000011
Figure FDA0002627581620000012
Wherein alpha, beta, gamma and delta are specific proportionality coefficients;
step four: when lightning produces coefficient Lt1When the environmental monitoring is less than or equal to the set threshold value, the cloud computing platform monitors the environmentThe measured data, the environment monitoring time and the lightning production coefficient are sent to a K1 memory of the data storage module; when lightning produces coefficient Lt1When the lightning generation coefficient is larger than the set threshold value, the cloud computing platform sends a lightning generation instruction to the lightning protection monitoring module, and simultaneously sends environment monitoring data, environment monitoring time and the lightning generation coefficient to a K1 memory of the data storage module;
the lightning protection monitoring module is used for monitoring real-time data of the surge protector, the lightning protection monitoring module is linearly connected with the surge protector, the lightning protection monitoring module comprises a lightning stroke counter, a leakage current monitoring node, a full current monitoring node and a resistive current monitoring node, and the specific monitoring steps are as follows:
z1: after receiving a lightning generation instruction sent by a cloud computing platform, a lightning protection monitoring module monitors the lightning stroke frequency, the leakage current, the full current and the resistive current of a surge protector every other minute and sends lightning monitoring data to the cloud computing platform, wherein the lightning monitoring data comprises the lightning stroke frequency, the leakage current, the full current and the resistive current;
z2: after the cloud computing platform receives the lightning monitoring data, marking the total lightning stroke, the average leakage current value, the effective full current value and the peak resistive current value as J respectivelyt2、ILt2、IXt2And IRt2T2 is lightning monitoring time;
z3: using formulas
Figure FDA0002627581620000021
i represents the serial number of the surge protector in the operation and maintenance system, and obtains the safety factor S of the surge protectori,t2Wherein delta, epsilon,
Figure FDA0002627581620000022
Is a specific proportionality coefficient;
z4: when the safety factor Si,t2When the lightning monitoring data is less than or equal to the set threshold value, the cloud computing platform monitors the lightning monitoring data, the lightning monitoring time and the safety factor Si,t2Sending the data to a data storage module K2 for storage; when the safety factor Si,t2When the lightning monitoring data is larger than the set threshold value, the cloud computing platform sends a danger instruction to the alarm driving module, and simultaneously, the lightning monitoring data, the lightning monitoring time and the safety factor S are usedi,t2Sending the data to a data storage module K2 for storage;
the algorithm auxiliary module is trained through monitoring data of the environment monitoring module to construct an auxiliary prediction model, the algorithm auxiliary module comprises a data processing unit and a model training unit, and the specific construction steps are as follows:
v1: the algorithm auxiliary module sends a data request instruction to the cloud computing platform at regular time, the cloud computing platform sends a storage opening instruction to the data storage module after receiving the data request instruction, and the data storage module sends the environmental monitoring data, the environmental monitoring time and the lightning monitoring coefficient stored in the K1 storage to the data processing unit after receiving the storage opening instruction;
v2: after receiving environment monitoring data, environment monitoring time and lightning monitoring coefficients, a data processing unit preprocesses the data, wherein the preprocessing comprises abnormal value smoothing and data normalization; taking environment monitoring data and environment monitoring time as input parameters of a model training unit and a lightning generation coefficient Lt1As an output parameter of the model training unit, and the model is trained by assigning the output parameter to 0 or 1, wherein 0 represents the lightning production coefficient Lt1Less than or equal to a preset threshold value, 1 represents a lightning production coefficient Lt1Greater than a preset threshold;
v3: taking the latest 24h of environment monitoring data and environment detection time stored in a K1 memory as input parameters of a model training unit, and performing secondary training on the model by using the latest 24h of environment monitoring data and a model output result of an environment monitoring module when the output data of the model is 0; when the output data of the model is 1, performing secondary training on the model by using the latest 24h environmental monitoring data of the environmental monitoring module and the model output result, and sending a lightning generation instruction to the lightning protection monitoring module through the cloud computing platform.
2. The cloud computing-based intelligent cloud lightning protection operation and maintenance system according to claim 1, further comprising a data query module, wherein the data query module is configured to query data in the data storage module through keywords, the keywords include time and surge protector numbers, and the specific query steps are as follows:
b1: a user inputs keywords to the human-computer interaction module through the intelligent terminal, and the human-computer interaction module sends a data query instruction and the keywords to the data query module through the cloud computing platform;
b2: after the data query module receives the data query instruction and the keywords, searching the keywords in the data storage module through the keywords and acquiring corresponding data;
b3: the data storage module sends the data searched according to the keywords to the man-machine interaction module through the cloud computing platform, and a user can check the data through the intelligent terminal.
3. The cloud computing-based intelligent cloud lightning protection operation and maintenance system according to claim 1, wherein the data storage module comprises a K1 memory, a K2 memory and a K3 memory, the K1 memory is used for storing environment monitoring data, environment monitoring time and lightning production coefficients, the K2 memory is used for storing lightning monitoring data, lightning monitoring time and safety factors, the K3 memory is used for storing other data in the working process of the system, and the other data comprises cache data generated in the running process of the system and instruction records sent by a cloud computing platform; the system is also provided with a data backup module, wherein the data backup module is used for regularly backing up data of the data storage module, the data storage module and the data backup module are linearly connected with the cloud computing platform, and the data storage module is linearly connected with the data backup module.
4. The cloud computing-based intelligent cloud lightning protection operation and maintenance system according to claim 1, wherein the human-computer interaction module is used for information transmission between a user and the cloud computing platform through an intelligent terminal, the human-computer interaction module is linearly connected with the cloud computing platform, the human-computer interaction module is wirelessly connected with the intelligent terminal, and the intelligent terminal comprises an intelligent mobile phone, a notebook computer and an intelligent display.
5. The intelligent cloud lightning protection operation and maintenance system based on cloud computing of claim 1, characterized in that, the alarm drive module sends out the police according to the danger instruction that cloud computing platform sent, the alarm drive module includes large-size screen display unit and audible and visual alarm unit, and when the alarm drive module received the danger instruction, drive audible and visual alarm unit and report to the police to send environment monitoring data, environment monitoring time, thunder and lightning production coefficient, thunder and lightning monitoring data, thunder and lightning monitoring time and factor of safety to large-size screen display unit, and send "danger warning" information to human-computer interaction module, the user used intelligent terminal to inquire the surge protector who damages.
6. The cloud computing-based intelligent cloud lightning protection operation and maintenance system according to claim 1, further comprising a power supply module, wherein the power supply module supplies power to each module, and the power supply module is linearly connected with the surge protector.
7. The intelligent cloud lightning protection operation and maintenance system based on cloud computing according to claim 1, wherein the model training unit comprises a neural network model, the neural network model is an error back propagation neural network, the error back propagation neural network comprises an input layer, an intermediate layer and an output layer, the input layer comprises five data nodes, the intermediate layer comprises eleven data nodes, and the output layer comprises two data nodes.
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