CN112255480A - Hall effect based electric appliance characteristic identification method and safety early warning system thereof - Google Patents
Hall effect based electric appliance characteristic identification method and safety early warning system thereof Download PDFInfo
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- 230000005355 Hall effect Effects 0.000 title claims description 45
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- G—PHYSICS
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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Abstract
The invention provides a safety early warning system based on a current fingerprint technology, which comprises: the device comprises an electricity detection sensor, a main control module and a manual updating module. The electricity utilization detection sensor is used for detecting a current signal of a current circuit; the main control module is used for matching the current signal with reference current signals of all pre-stored electric appliances in an electric appliance feature library and judging whether the matching can be successful or not; when the matching is judged to be successful, defining the pre-stored electric appliance which is successfully matched as the electric appliance connected with the current circuit; and the manual updating module is used for manually acquiring the current electric appliance and the corresponding current signal data and updating the current electric appliance and the corresponding current signal data to the electric appliance feature library. Compared with the prior art, the invention can realize the purposes of identifying the current power utilization electric appliances of each circuit according to the current fingerprint technology and carrying out corresponding safety power utilization early warning prediction by utilizing background data analysis.
Description
Technical Field
The invention relates to the technical field of circuit measurement of electrical variables, in particular to an electrical appliance characteristic identification method based on a Hall effect and a safety early warning system thereof.
Background
Along with the development of science and technology, more and more various types of electric equipment go deep into each family, company, enterprise, along with intelligent process, the type of electric equipment is more and more, and every electric equipment's operating condition also exists differently, can be along with the incessant switching of environment, time's change even.
The existing electric equipment starts to develop intelligently, and can be or is applied to intelligent functional environments such as bidirectional multi-rate metering and the like, which represents that an energy-saving intelligent power grid is finally developed to a user intelligent terminal in the future, however, the existing problems are that after a corresponding module is installed, the type of the electric equipment needs to be manually selected and configured, firstly, the user cannot flexibly adjust the electric equipment in subsequent use, secondly, special operation and maintenance personnel need to be dispatched to install, debug and pre-install, and the supervision cost is increased while the personnel cost is increased.
On the other hand, some electric devices are not safely turned off, which causes the electric devices to generate heat due to the continuous power-on state, thereby invisibly increasing the risk of fire; that is, for the safety of electricity, the surveillance camera cannot handle. Therefore, it is urgently needed to develop a corresponding technology to solve the existing problems.
Disclosure of Invention
In order to solve the problems, the invention provides an electric appliance characteristic identification method based on the Hall effect and a safety early warning system thereof, which can realize the purposes of identifying the current electric appliances of each circuit according to the Hall effect and carrying out corresponding safety electric appliance early warning prediction by utilizing background data analysis.
In order to achieve the purpose, the invention provides an electrical appliance characteristic identification method based on a Hall effect, which comprises the following steps:
s110: the Hall sensor detects a current signal of a current circuit;
s120: matching the current signal with a reference current signal of each pre-stored electrical appliance in an electrical appliance feature library, and judging whether the matching is successful; if yes, go to step S130; if not, go to step S140;
s130: defining the successfully matched pre-stored electric appliance as the electric appliance connected with the current circuit;
s140: and manually acquiring the current electric appliance and the corresponding current signal data, and updating the current electric appliance and the corresponding current signal data to the electric appliance feature library.
Preferably, the S120 process:
matching the current signal with a reference current signal of each pre-stored electrical appliance in an electrical appliance feature library;
judging whether the current signal is successfully superposed and matched with a certain reference current signal or two or more reference current signals;
if the matching is successful, the judgment result is yes; otherwise, the judgment result is negative.
Preferably, the forming process of the electrical appliance feature library is as follows:
collecting current signals flowing through a plurality of electrical appliances and respectively using the current signals as training samples;
constructing a current signal-time coordinate graph for training different electrical appliances by taking time as an X axis and current as a Y axis;
and respectively inputting the constructed current signal-time coordinate graph and time coordinate graph of different electrical appliances into a neural network for training until the electrical appliance characteristic library is formed by training.
Preferably, the current signal is: current, hall potential difference.
Preferably, the hall sensor is connected to the current circuit by a fastening device to detect and acquire a current signal.
In order to achieve the above object, the present invention further provides a safety pre-warning system based on hall effect, which comprises: the device comprises a Hall sensor, a master control module and a manual updating module;
the Hall sensor is used for detecting a current signal of a current circuit; the main control module is electrically connected with the Hall sensor and is used for matching the current signal with reference current signals of all pre-stored electric appliances in an electric appliance feature library and judging whether the matching can be successful or not; when the matching is judged to be successful, defining the pre-stored electric appliance which is successfully matched as the electric appliance connected with the current circuit; and the manual updating module is electrically connected with the main control module and used for manually acquiring the current electric appliance and the corresponding current signal data and updating the current electric appliance and the corresponding current signal data to the electric appliance feature library.
Preferably, the safety precaution system based on hall effect further includes: a background; the background is used for acquiring the habit of using the electric appliance by a user corresponding to the current circuit according to the current signal of the current circuit, and judging whether the abnormal use condition exists according to the habit of using the electric appliance by the user.
Preferably, the abnormal use condition includes: access of dangerous electrical equipment, abnormal electricity utilization behaviors and/or electrical faults.
Preferably, the background is further configured to analyze current signals of the plurality of circuits, and predict corresponding fire information according to big data analysis.
Compared with the prior art, the invention has the beneficial effects that: the purposes of identifying the current power utilization electric appliances of each circuit according to the Hall effect and carrying out corresponding safety power utilization early warning prediction by utilizing background data analysis can be achieved.
Drawings
FIG. 1 is a schematic flow chart of an electrical appliance characteristic identification method based on Hall effect according to the present invention;
FIG. 2 is a block diagram of a first embodiment of a Hall-effect based security early warning system of the present invention;
fig. 3 is a block diagram of a second embodiment or a third embodiment of the hall effect based security early warning system according to the present invention.
Detailed Description
The technical solution 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. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides an electrical appliance characteristic identification method based on a Hall effect. The application scenarios of the Hall effect-based electric appliance feature identification method are not limited, for example: schools, factories, entertainment venues, homes, etc. The identification of the Hall effect refers to the extraction of current characteristics, which is similar to the conventional fingerprint identification technology, but the types of the extracted characteristics are different. The principle of the Hall effect is as follows: when a current passes through the semiconductor perpendicular to an external magnetic field, carriers are deflected, and an additional electric field is generated perpendicular to the direction of the current and the magnetic field, so that a potential difference is generated between two ends of the semiconductor, namely the hall effect, and the potential difference is also called as a hall potential difference. By further combining current characteristic data (current, Hall potential difference and the like) of various electric equipment in use, the method judges that: the electric equipment connected to the line has certain types (such as an air conditioner, a computer and a battery car) and the working state (such as a working gear and whether the electric equipment is abnormal or not).
Referring to fig. 1, fig. 1 is a schematic flow chart of an electrical appliance feature identification method based on hall effect according to the present invention. The Hall effect-based electric appliance feature identification method comprises the following steps:
s110: the hall sensor detects a current signal of the present circuit.
In this embodiment, the hall sensor is connected to the current circuit by using the fastening device to detect and acquire the current signal, so that the circuit does not need to be invaded to acquire the corresponding current signal. The hall sensor may be of a conventional type, and will not be described in detail herein. The sampling frequency of the Hall sensor for detecting and acquiring the current signal is preferably set to be 10k, the sampling frequency can be set collectively according to actual requirements, and the conventional sampling frequency is within the protection scope of the invention. The current signal may be a current, a hall potential difference, or other signals.
S120: matching the current signal with a reference current signal of each pre-stored electrical appliance in an electrical appliance feature library, and judging whether the matching is successful; if yes, go to step S130; if not, the process proceeds to step S140.
In this embodiment, the S120 process: 1. matching the current signal with a reference current signal of each pre-stored electrical appliance in an electrical appliance feature library; 2. judging whether the current signal is successfully superposed and matched with a certain reference current signal or two or more reference current signals; 3. if the matching is successful, the judgment result is yes; otherwise, the judgment result is negative. Wherein, the forming process of the electrical appliance characteristic library comprises the following steps: collecting current signals flowing through a plurality of electrical appliances and respectively using the current signals as training samples; constructing a current signal-time coordinate graph for training different electrical appliances by taking time as an X axis and current as a Y axis; and respectively inputting the constructed current signal-time coordinate graph and time coordinate graph of different electrical appliances into a neural network for training until the electrical appliance characteristic library is formed by training.
The present embodiment describes the process of step S120 in detail by using a specific example. For example: the current signal obtained at present is a first Hall potential difference signal; matching the first Hall potential difference signal with reference Hall potential difference signals of all pre-stored electric appliances in an electric appliance feature library, wherein the matching result is that the first Hall potential difference signal is consistent with the superposition result of the air conditioner Hall potential difference signal and the electric lamp Hall potential difference signal; therefore, the electric appliances connected with the current circuit are air conditioners and electric lamps. If the matching result shows that the first Hall potential difference signal is similar to the Hall potential difference signal part of the electric lamp, the residual Hall potential difference signal belongs to the superposition of a certain unknown electric appliance signal, and therefore the electric lamp connected with the current circuit and the certain unknown electric appliance are obtained.
S130: and defining the successfully matched pre-stored electric appliance as the electric appliance connected with the current circuit.
In this embodiment, the connected electrical appliance obtained through analysis is fed back to the background and the like for processing.
S140: and manually acquiring the current electric appliance and the corresponding current signal data, and updating the current electric appliance and the corresponding current signal data to the electric appliance feature library.
In this embodiment, if the unknown electrical appliance is analyzed, a corresponding manager may be notified to go to the current circuit for detection, obtain the affiliation of the unknown electrical appliance and the current signal thereof, and further update the current signal to the electrical appliance feature library. Thereby facilitating the subsequent analysis and development of the hall effect technology.
The invention further provides a first embodiment of the safety early warning system based on the Hall effect. The application scenarios of the safety early warning system based on the hall effect are not limited, for example: schools, factories, entertainment venues, homes, etc. The principle of the Hall effect is as follows: when a current passes through the semiconductor perpendicular to an external magnetic field, carriers are deflected, and an additional electric field is generated perpendicular to the direction of the current and the magnetic field, so that a potential difference is generated between two ends of the semiconductor, namely the hall effect, and the potential difference is also called as a hall potential difference. By further combining current characteristic data (current, Hall potential difference and the like) of various electric equipment in use, the method judges that: the electric equipment connected to the line has certain types (such as an air conditioner, a computer and a battery car) and the working state (such as a working gear and whether the electric equipment is abnormal or not).
Referring to fig. 2, fig. 2 is a block diagram of a first embodiment of a safety precaution system based on hall effect according to the present invention. The safety early warning system based on the Hall effect comprises: the hall sensor 100, the main control module 200 and the manual updating module 300. The hall sensor 100 is used for detecting a current signal of a present circuit. The main control module 200 is electrically connected with the hall sensor 100 and is used for matching the current signal with a reference current signal of each pre-stored electrical appliance in an electrical appliance feature library and judging whether the matching is successful; and when the matching is judged to be successful, defining the pre-stored electric appliance which is successfully matched as the electric appliance connected with the current circuit. The manual update module 300 is electrically connected to the main control module 200, and is configured to manually obtain current electrical appliances and corresponding current signal data, and update the current electrical appliances and the current signal data to the electrical appliance feature library.
In this embodiment, the hall sensor 100 is connected to the current circuit by a fastening device to detect and obtain the current signal, so that the circuit does not need to be invaded to obtain the corresponding current signal. The sampling frequency of the hall sensor 100 for detecting and acquiring the current signal is preferably set to 10k, and the sampling frequency can be collectively set according to actual requirements, and the conventional sampling frequency is within the protection scope of the present invention. The current signal may be a current, a hall potential difference, or other signals.
In this embodiment, the processing procedure of the main control module 200 includes: 1. matching the current signal with a reference current signal of each pre-stored electrical appliance in an electrical appliance feature library; 2. judging whether the current signal is successfully superposed and matched with a certain reference current signal or two or more reference current signals; 3. if the matching is successful, the judgment result is yes; otherwise, the judgment result is negative. Wherein, the forming process of the electrical appliance characteristic library comprises the following steps: collecting current signals flowing through a plurality of electrical appliances and respectively using the current signals as training samples; constructing a current signal-time coordinate graph for training different electrical appliances by taking time as an X axis and current as a Y axis; and respectively inputting the constructed current signal-time coordinate graph and time coordinate graph of different electrical appliances into a neural network for training until the electrical appliance characteristic library is formed by training.
The present embodiment describes the process of the main control module 200 in detail by using a specific example. For example: the current signal obtained at present is a first Hall potential difference signal; matching the first Hall potential difference signal with reference Hall potential difference signals of all pre-stored electric appliances in an electric appliance feature library, wherein the matching result is that the first Hall potential difference signal is consistent with the superposition result of the air conditioner Hall potential difference signal and the electric lamp Hall potential difference signal; therefore, the electric appliances connected with the current circuit are air conditioners and electric lamps. If the matching result shows that the first Hall potential difference signal is similar to the Hall potential difference signal part of the electric lamp, the residual Hall potential difference signal belongs to the superposition of a certain unknown electric appliance signal, and therefore the electric lamp connected with the current circuit and the certain unknown electric appliance are obtained.
In this embodiment, if the main control module 200 analyzes that there is an unknown electrical appliance, the manual update module 300 may notify a corresponding administrator to go to the current circuit for detection, obtain the attribution of the unknown electrical appliance and its current signal, and further manually update the current signal to the electrical appliance feature library. Thereby facilitating the subsequent analysis and development of the hall effect technology.
The invention also provides a second embodiment of the safety early warning application based on the Hall effect. Referring to fig. 3, fig. 3 is a block diagram of a second embodiment of the safety precaution system based on hall effect according to the present invention. The second embodiment of the safety precaution system based on hall effect is improved on the basis of the first embodiment, and the improvement is that the safety precaution system based on hall effect further comprises: a background 400. The background 400 is configured to obtain a habit of using an electrical appliance by a user corresponding to a current circuit according to a current signal of the current circuit, and determine whether an abnormal use condition exists according to the habit of using the electrical appliance by the user.
In this embodiment, the abnormal use condition includes: access of dangerous electrical equipment, abnormal electricity utilization behaviors and/or electrical faults. Because the electric appliances corresponding to the current circuit are relatively fixed, and the use time, the use frequency and the like of each electric appliance are also relatively fixed, data analysis is performed through the background 400, if the electric appliances are used in a non-use time period, it is probably inferred that the user forgets to turn off the electric appliances, and at the moment, the background 400 can send corresponding short messages to remind the user terminal or the administrator terminal to perform verification processing. If other current signals appear in the non-use time period, the user side is connected with other used electric appliances in the current circuit, and whether the used electric appliances are dangerous equipment such as an electric vehicle needs to be judged and verified at the moment; if the equipment is dangerous equipment, the administrator or the user side needs to be informed to process in time. If the current information of the corresponding electric appliance does not appear in a fixed use time period, further verification is needed to verify whether the electric appliance fails and cannot be used. Through the implementation mode, the safety early warning system based on the Hall effect can be further improved, and the safety of a user is guaranteed.
The invention also provides a third embodiment of the safety early warning application based on the Hall effect. Referring to fig. 3, fig. 3 is a block diagram of a third embodiment of the safety precaution system based on hall effect according to the present invention. The third embodiment of the safety early warning system based on the hall effect is improved on the basis of the second embodiment, and the improvement is that the background 400 is also used for analyzing current signals of a plurality of circuits and predicting corresponding fire information according to big data analysis.
In this embodiment, the prediction of the fire information may be performed by: firstly, acquiring current signals of a plurality of circuits in a certain administration area within a certain time period, and acquiring alarm historical data and population density data of corresponding alarm equipment; analyzing the degree of association between the fire and population density and the use of electric appliances according to the acquired signals and data; estimating the probability of the next fire occurrence according to the correlation; and further performing regular fixed-point investigation according to the calculated probability. Through the embodiment, the future fire hazard can be predicted and the warning can be given based on the existing fire data, so that the loss of personal and property and the loss of social resources are reduced.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (9)
1. The Hall effect based electric appliance characteristic identification method is characterized by comprising the following steps of:
s110: the Hall sensor detects a current signal of a current circuit;
s120: matching the current signal with a reference current signal of each pre-stored electrical appliance in an electrical appliance feature library, and judging whether the matching is successful; if yes, go to step S130; if not, go to step S140;
s130: defining the successfully matched pre-stored electric appliance as the electric appliance connected with the current circuit;
s140: and manually acquiring the current electric appliance and the corresponding current signal data, and updating the current electric appliance and the corresponding current signal data to the electric appliance feature library.
2. The hall effect based appliance feature identification method according to claim 1, wherein the S120 process:
matching the current signal with a reference current signal of each pre-stored electrical appliance in an electrical appliance feature library;
judging whether the current signal is successfully superposed and matched with a certain reference current signal or two or more reference current signals;
if the matching is successful, the judgment result is yes; otherwise, the judgment result is negative.
3. The Hall effect based appliance feature identification method according to claim 1, wherein the forming process of the appliance feature library is as follows:
collecting current signals flowing through a plurality of electrical appliances and respectively using the current signals as training samples;
constructing a current signal-time coordinate graph for training different electrical appliances by taking time as an X axis and current as a Y axis;
and respectively inputting the constructed current signal-time coordinate graph and time coordinate graph of different electrical appliances into a neural network for training until the electrical appliance characteristic library is formed by training.
4. The Hall effect based appliance feature identification method according to claim 1, wherein the current signal is: current, hall potential difference.
5. The Hall Effect based electrical appliance characteristic identification method according to any one of claims 1 to 4, wherein the Hall sensor is connected into the current circuit by a buckling device to detect and acquire a current signal.
6. Safety precaution system based on hall effect, its characterized in that, safety precaution system based on hall effect includes: the device comprises a Hall sensor, a master control module and a manual updating module;
the Hall sensor is used for detecting a current signal of a current circuit; the main control module is electrically connected with the Hall sensor and is used for matching the current signal with reference current signals of all pre-stored electric appliances in an electric appliance feature library and judging whether the matching can be successful or not; when the matching is judged to be successful, defining the pre-stored electric appliance which is successfully matched as the electric appliance connected with the current circuit; and the manual updating module is electrically connected with the main control module and used for manually acquiring the current electric appliance and the corresponding current signal data and updating the current electric appliance and the corresponding current signal data to the electric appliance feature library.
7. The hall effect based security pre-warning system of claim 6, further comprising: a background; the background is used for acquiring the habit of using the electric appliance by a user corresponding to the current circuit according to the current signal of the current circuit, and judging whether the abnormal use condition exists according to the habit of using the electric appliance by the user.
8. The hall effect based safety precaution system of claim 7, wherein the abnormal use condition includes: access of dangerous electrical equipment, abnormal electricity utilization behaviors and/or electrical faults.
9. The hall effect based security early warning system of claim 7, wherein the background is further configured to analyze the current signals of the plurality of circuits and predict corresponding fire information according to big data analysis.
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