An intelligent lightning protection real-time online monitoring system

Abstract

The present invention discloses an intelligent lightning protection real-time online monitoring system, which relates to the technical field of lightning protection. The system includes a lightning arrester, a lightning monitoring device group, a lightning prediction device group and a cloud service platform. The lightning monitoring device group collects the lightning protection working information of the lightning arrester and sends the lightning protection working information to the cloud service platform; the cloud service platform records the lightning protection working information and predicts the state of the lightning arrester according to the lightning protection working information; the lightning prediction device group monitors the meteorological electric field information in the air near the protected device and predicts the degree of harm to the protected device caused by lightning strike according to the meteorological electric field information, and sends it to the cloud service platform as early warning information; the cloud service platform controls the operation of the lightning arrester according to the early warning information and issues an early warning. Through the above system, the lightning arrester can be detected in real time, the state of the lightning arrester can be predicted according to the lightning protection working information, and the degree of harm to the protected device caused by lightning strike can be predicted, saving manpower and material resources and improving the detection efficiency and prevention effect.

Description

Technical Field

[0001] The present invention relates to the technical field of lightning protection, and particularly relates to an intelligent lightning protection real-time online monitoring system. Background Art

[0002] In modern society, lightning arresters have been widely used in many systems such as power, communication, monitoring, and automation to protect these systems from lightning damage. However, lightning arresters protect the backend equipment by discharging surge currents and limiting voltages. Therefore, the core components have a limited number of times of withstanding surge current impacts and are extremely vulnerable to direct breakdown or gradual deterioration, eventually leading to damage. When damaged, a transient large current will pass through the component interior, and the product will generate high heat. At this time, if the front-end disconnecting device fails to disconnect the lightning arrester from the system in time, there is a risk of fire. However, if the lightning arrester is disconnected from the system, the system will lose its lightning protection function and is extremely vulnerable to lightning intrusion, resulting in system damage.

[0003] Traditional inspections and detections of lightning arresters are usually carried out more than once a year. Personnel need to carry equipment to the site to detect lightning protection products. Not only is the detection cycle long, but also a large amount of manpower and material resources are consumed, and the detection effect is poor. Summary of the Invention

[0004] The purpose of the present invention is to solve the problems in the above background art and propose an intelligent lightning protection real-time online monitoring system.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An embodiment of the present invention provides an intelligent lightning protection real-time online monitoring system, which includes a lightning arrester, and also includes a lightning monitoring device group, a lightning prediction device group, and a cloud service platform;

[0007] Wherein:

[0008] The lightning monitoring device group is used to collect the lightning protection working information of the lightning arrester and send the lightning protection working information to the cloud service platform;

[0009] The cloud service platform is used to record the lightning protection working information and predict the state of the lightning arrester according to the lightning protection working information;

[0010] The lightning prediction device group is used to monitor the meteorological electric field information in the air near the protected device and predict the degree of harm to the protected device caused by lightning strikes according to the meteorological electric field information, and send it to the cloud service platform as early warning information;

[0011] The cloud service platform is also used to control the operation of the lightning arrester according to the early warning information and give an early warning.

[0012] Optionally, the lightning monitoring device group includes a lightning monitoring device, an SPD monitoring device, a grounding monitoring device, an environmental monitoring module, and a first communication module; the lightning protection work information includes lightning current waveform information, SPD work information, grounding information, and environmental information;

[0013] Wherein:

[0014] The lightning monitoring device is used to collect the analog differential signal of lightning when the lightning arrester works, and restore the waveform of the analog differential signal to obtain the lightning current waveform information;

[0015] The SPD monitoring device is used to collect the number of SPD lightning discharges of the lightning arrester, as well as the working data of the SPD, the data of the backup circuit breaker, and the working environment data, as the SPD work information;

[0016] The grounding monitoring device is used to collect the connection information of the grounding downlead of the lightning arrester, the loop grounding resistance, and the metal loop connection information, as the grounding information;

[0017] The environmental monitoring module is used to collect the leakage current data, power frequency current, voltage, Rogowski coil data, integrator data, temperature, and zero-sequence current of the lightning arrester, as the environmental information;

[0018] The first communication module is used to communicate data with the cloud service platform.

[0019] Optionally, the lightning current waveform information includes the waveform, polarity, peak value, charge quantity, specific energy, time, and number of lightning current, or the polarity, peak value, energy, time, and number of the incoming surge on the line.

[0020] Optionally, the cloud service platform includes a data statistics module, a data processing module, and an alarm module; the lightning protection work information includes the target device identifier of the lightning arrester;

[0021] The data statistics module is used to count and record the lightning protection work information of the lightning arrester according to the target device identifier;

[0022] The data processing module is used to judge the status of the lightning arrester according to the lightning protection work information and predict the service life of the lightning arrester;

[0023] The alarm module is used to give an alarm when the data processing module judges that the status of the lightning arrester is abnormal;

[0024] The alarm module is also used to give an alarm when the data processing module predicts that the service life of the lightning arrester is less than the preset time value.

[0025] Optionally, the data processing module predicts the service life of the lightning arrester specifically as follows:

[0026]

[0027] where C is the rated lightning discharge times of the lightning arrester, C1 is the SPD lightning discharge times of the lightning arrester, C2 is the number of intrusion surge of the lightning arrester, I 1i is the peak value of the i-th lightning current, I 2i is the peak value of the i-th intrusion surge, I is the rated lightning discharge current of the lightning arrester, sgn[x] is the sign function, T is the rated working time of the lightning arrester, t is the actual working time of the lightning arrester, and α and β are preset exponential parameters.

[0028] Optionally, the lightning prediction device group includes an atmospheric electric field meter, a lightning strike prediction module, and a second communication module;

[0029] The atmospheric electric field meter is used to collect the electric field data in the atmosphere at a preset periodic duration;

[0030] The lightning strike prediction module is used to predict the probability of lightning occurrence in the next preset periodic duration according to the electric field data collected in the current preset periodic duration, calculate the lightning intensity according to the electric field intensity value, and predict the damage degree of the protected device being struck by lightning according to the probability of lightning phenomenon and the lightning intensity;

[0031] The second communication module is used to communicate data with the cloud service platform.

[0032] Optionally, the lightning strike prediction module includes a calculation sub-module, a prediction sub-module, and an evaluation sub-module; the electric field data is the charge change in the air within a preset periodic duration;

[0033] The calculation sub-module is used to calculate the electric field intensity in the current air according to the charge change to obtain the atmospheric electric field time series data in the current period;

[0034] The prediction sub-module is used to input the atmospheric electric field time series data into a pre-trained BP neural network to obtain the probability of lightning occurrence in the next preset periodic duration, and calculate the lightning intensity according to the electric field intensity value;

[0035] The evaluation sub-module is used to predict the damage degree of the protected device being struck by lightning according to the probability of lightning phenomenon and the lightning intensity.

[0036] An intelligent lightning protection real-time online monitoring system provided by an embodiment of the present invention includes a lightning arrester, and also includes a lightning monitoring device group, a lightning prediction device group, and a cloud service platform; wherein: the lightning monitoring device group is used to collect the lightning protection working information of the lightning arrester and send the lightning protection working information to the cloud service platform; the cloud service platform is used to record the lightning protection working information and predict the state of the lightning arrester according to the lightning protection working information; the lightning prediction device group is used to monitor the meteorological electric field information in the air near the protected device and predict the degree of harm to the protected device caused by lightning strikes according to the meteorological electric field information, and send it to the cloud service platform as a warning message; the cloud service platform is also used to control the operation of the lightning arrester according to the warning message and issue a warning. Through the above system, the lightning arrester can be detected in real time, the state of the lightning arrester can be predicted according to the lightning protection working information, and the degree of harm to the protected device caused by lightning strikes can be predicted, saving manpower and material resources and improving the detection efficiency and prevention effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present invention will be further described below with reference to the accompanying drawings.

[0038] Figure 1 It is a system block diagram of an intelligent lightning protection real-time online monitoring system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0040] An embodiment of the present invention provides an intelligent lightning protection real-time online monitoring system. Refer to Figure 1 , Figure 1 It is a system block diagram of an intelligent lightning protection real-time online monitoring system provided by an embodiment of the present invention, including a lightning arrester, and also including a lightning monitoring device group, a lightning prediction device group, and a cloud service platform;

[0041] Wherein:

[0042] The lightning monitoring device group is used to collect the lightning protection working information of the lightning arrester and send the lightning protection working information to the cloud service platform;

[0043] The cloud service platform is used to record the lightning protection working information and predict the state of the lightning arrester according to the lightning protection working information;

[0044] A group of lightning prediction devices is used to monitor the meteorological electric field information in the air near the protected device, predict the degree of lightning strike hazard to the protected device based on the meteorological electric field information, and send it to the cloud service platform as early warning information.

[0045] The cloud service platform is also used to control the lightning arrester to work according to the early warning information and give an early warning.

[0046] Based on an intelligent lightning protection real-time online monitoring system provided by an embodiment of the present invention, the lightning arrester can be detected in real time, the state of the lightning arrester can be predicted according to the lightning protection work information, and the degree of lightning strike hazard to the protected device can be predicted, saving manpower and material resources and improving the detection efficiency and prevention effect.

[0047] In one implementation, the protected device can be a core device in systems such as power, communication, monitoring, and automation. The lightning arrester can be deployed on the protected device to protect the protected device from lightning damage.

[0048] In one implementation, the group of lightning prediction devices can monitor the meteorological electric field information within a preset range, and can give early warnings to all protected devices and lightning arresters within the preset range.

[0049] In one embodiment, the lightning monitoring device group includes a lightning monitoring device, an SPD monitoring device, a grounding monitoring device, an environmental monitoring module, and a first communication module; the lightning protection work information includes lightning current waveform information, SPD work information, grounding information, and environmental information.

[0050] Among them:

[0051] The lightning monitoring device is used to collect the analog differential signal of lightning when the lightning arrester works, and restore the waveform of the analog differential signal to obtain the lightning current waveform information.

[0052] The SPD monitoring device is used to collect the number of times the SPD of the lightning arrester discharges lightning strikes, as well as the working data, backup circuit breaker data, and working environment data of the SPD as the SPD work information.

[0053] The grounding monitoring device is used to collect the connection information of the grounding downlead of the lightning arrester, the loop grounding resistance, and the metal loop connection information as the grounding information.

[0054] The environmental monitoring module is used to collect the leakage current data, power frequency current, voltage, Rogowski coil data, integrator data, temperature, and zero-sequence current of the lightning arrester as the environmental information.

[0055] The first communication module is used to communicate data with the cloud service platform.

[0056] In one embodiment, the lightning current waveform information includes the waveform, polarity, peak value, charge quantity, specific energy, time, and number of times of the lightning current, or the polarity, peak value, energy, time, and number of times of the inrush surge on the line.

[0057] In one implementation, the service life of the lightning arrester can be predicted based on the lightning current waveform information.

[0058] In one embodiment, the cloud service platform includes a data statistics module, a data processing module, and an alarm module; the lightning protection work information includes the target device identifier of the lightning arrester;

[0059] The data statistics module is used to statistically record the lightning protection work information of the lightning arrester according to the target device identifier;

[0060] The data processing module is used to judge the state of the lightning arrester according to the lightning protection work information and predict the service life of the lightning arrester;

[0061] The alarm module is used to give an alarm when the data processing module judges that the state of the lightning arrester is abnormal;

[0062] The alarm module is also used to give an alarm when the data processing module predicts that the service life of the lightning arrester is less than a preset time value.

[0063] In one implementation, the cloud service platform can generate a working chart of the lightning arrester according to the lightning protection work information of the lightning arrester recorded by the data statistics module, intuitively showing the working life cycle of the lightning arrester, which is convenient for data statistics and analysis.

[0064] In one implementation, the state of the lightning arrester is judged according to the SPD working information, grounding information, and environmental information.

[0065] In one embodiment, the specific method for the data processing module to predict the service life of the lightning arrester is as follows:

[0066]

[0067] Where C is the rated lightning discharge times of the lightning arrester, C1 is the SPD lightning discharge times of the lightning arrester, C2 is the inrush surge times of the lightning arrester, I 1i is the peak value of the i-th lightning current, I 2i is the peak value of the i-th inrush surge, I is the rated lightning discharge current of the lightning arrester, sgn[x] is the sign function, T is the rated working time of the lightning arrester, t is the actual working time of the lightning arrester, and α and β are preset exponential parameters.

[0068] Where

[0069]

[0070] In one implementation, when the peak value of the i-th lightning current is too large and the ratio of I 1i to I is greater than 0.7 times, the damage effect of this lightning current on the lightning arrester is enlarged, that is, the enlarged effect of this lightning strike can be compensated, and the predicted service life of the lightning arrester is reduced.

[0071] In one implementation, the rated lightning discharge times, rated lightning discharge current, and rated operating time of the lightning arrester can be obtained according to the model of the lightning arrester.

[0072] In one embodiment, the lightning prediction device group includes an atmospheric electric field meter, a lightning strike prediction module, and a second communication module;

[0073] The atmospheric electric field meter is used to collect the electric field data in the atmosphere according to a preset cycle duration;

[0074] The lightning strike prediction module is used to predict the probability of lightning occurrence in the next preset cycle duration according to the electric field data collected in the current preset cycle duration, calculate the lightning intensity according to the electric field intensity value, and predict the damage degree of the protected device by lightning according to the probability of lightning phenomenon and the lightning intensity;

[0075] The second communication module is used to perform data communication with the cloud service platform.

[0076] In one implementation, the lightning detection of the atmospheric electric field meter can use radio frequency technology, electric field detection technology, and radio frequency sensors to detect meteorological conditions and lightning signals, and calculate the lightning area range. Through an antenna (metal ball or metal wire) perpendicular to the electric field and parallel to the ground, the electric field in the atmosphere can be measured.

[0077] In one embodiment, the lightning strike prediction module includes an acquisition sub-module, a calculation sub-module, a prediction sub-module, and an evaluation sub-module; the electric field data is the charge change in the air within a preset cycle duration;

[0078] The calculation sub-module is used to calculate the current electric field intensity in the air according to the charge change to obtain the atmospheric electric field time series data in the current cycle;

[0079] The prediction sub-module is used to input the atmospheric electric field time series data into a pre-trained BP neural network to obtain the probability of lightning occurrence in the next preset cycle duration, and calculate the lightning intensity according to the electric field intensity value;

[0080] The evaluation sub-module is used to predict the damage degree of the protected device by lightning according to the probability of lightning phenomenon and the lightning intensity.

[0081] In one implementation, the formation of lightning is a process of charge accumulation, and the probability of lightning occurrence can be predicted by monitoring the electric field change in the atmosphere.

[0082] In one implementation, the charge variation Q(t) is a function of the charge at the test point changing with time. The potential between the test point and a preset reference point can be calculated by the following formula (3):

[0083]

[0084] Where H is the distance between the thundercloud and the ground, ε is the dielectric constant, L1 is the distance between the test point and the preset reference point, and I(t) is the current generated by the charge changing with time. The equivalent capacitance C:

[0085] C = C0 + C1 (4)

[0086] Where C0 is the equivalent capacitance of the atmospheric electric field instrument circuit, and C1 is the capacitance between the antenna of the atmospheric electric field instrument and the land,

[0087]

[0088] Where r is the radius of the antenna of the atmospheric electric field instrument, and L is the length of the antenna of the atmospheric electric field instrument.

[0089] In one implementation, the lightning intensity of the thundercloud can be calculated based on the potential E:

[0090]

[0091] Where τ is the time constant, τ0 is the standard value of the time constant, and E max is the maximum potential E within each period.

[0092] The above has described a detailed embodiment of the present invention, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the implementation scope of the present invention. Any equivalent changes and improvements made according to the scope of the present invention application should still fall within the patent coverage scope of the present invention.

Claims

1. An intelligent lightning protection real-time online monitoring system, including a lightning arrester, characterized in that, It also includes a lightning monitoring device group, a lightning prediction device group, and a cloud service platform; Among them: The lightning monitoring device group is used to collect the lightning protection working information of the lightning arrester and send the lightning protection working information to the cloud service platform; The cloud service platform is used to record the lightning protection working information and predict the status of the lightning arrester according to the lightning protection working information; The lightning prediction device group is used to monitor the meteorological electric field information in the air near the protected device and predict the degree of damage to the protected device caused by lightning strikes according to the meteorological electric field information, and send it to the cloud service platform as a warning message; The cloud service platform is also used to control the lightning arrester to work according to the warning message and give a warning; The lightning prediction device group includes an atmospheric electric field instrument, a lightning strike prediction module, and a second communication module; The atmospheric electric field instrument is used to collect the electric field data in the atmosphere according to a preset cycle duration; The lightning strike prediction module is used to predict the probability of lightning occurrence in the next preset cycle duration according to the electric field data collected in the current preset cycle duration, calculate the lightning intensity according to the electric field intensity value, and predict the degree of damage to the protected device caused by lightning strikes according to the probability of lightning occurrence and the lightning intensity; The second communication module is used to communicate data with the cloud service platform; The lightning strike prediction module includes a calculation sub-module, a prediction sub-module, and an evaluation sub-module; the electric field data is the charge change in the air within a preset cycle duration; The calculation sub-module is used to calculate the electric field intensity in the current air according to the charge change to obtain the atmospheric electric field time series data in the current cycle; The prediction sub-module is used to input the atmospheric electric field time series data into a pre-trained BP neural network to obtain the probability of lightning occurrence in the next preset cycle duration and calculate the lightning intensity according to the electric field intensity value; The evaluation sub-module is used to predict the degree of damage to the protected device caused by lightning strikes according to the probability of lightning occurrence and the lightning intensity.

2. The intelligent lightning protection real-time online monitoring system according to claim 1, wherein, The lightning monitoring device group includes a lightning monitoring device, an SPD monitoring device, a grounding monitoring device, an environment monitoring module, and a first communication module; the lightning protection working information includes lightning current waveform information, SPD working information, grounding information, and environment information; Among them: The lightning monitoring device is used to collect the analog differential signal of lightning when the lightning arrester works and restore the waveform of the analog differential signal to obtain the lightning current waveform information; The SPD monitoring device is used to collect the number of SPD lightning discharges of the lightning arrester, as well as the working data, backup circuit breaker data, and working environment data of the SPD as the SPD working information; The grounding monitoring device is used to collect the connection information of the grounding downlead of the lightning arrester, the loop grounding resistance, and the metal loop connection information as the grounding information; The environment monitoring module is used to collect the leakage current data, power frequency current, voltage, Rogowski coil data, integrator data, temperature, and zero-sequence current of the lightning arrester as the environment information; The first communication module is used to communicate data with the cloud service platform.

3. An intelligent lightning protection real-time online monitoring system according to claim 2, characterized in that, The lightning current waveform information includes the waveform, polarity, peak value, charge quantity, specific energy, time, and number of times of the lightning current, or the polarity, peak value, energy, time, and number of times of the incoming surge on the line.

4. An intelligent lightning protection real-time online monitoring system according to claim 3, characterized in that, The cloud service platform includes a data statistics module, a data processing module, and an alarm module; the lightning protection work information further includes the target device identifier of the lightning arrester; The data statistics module is used to statistically record the lightning protection work information of the lightning arrester according to the target device identifier; The data processing module is used to judge the state of the lightning arrester according to the lightning protection work information and predict the service life of the lightning arrester; The alarm module is used to give an alarm when the data processing module judges that the state of the lightning arrester is abnormal; The alarm module is further used to give an alarm when the data processing module predicts that the service life of the lightning arrester is less than the preset time value.

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