CN117239942B - Ammeter with monitoring function - Google Patents
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Abstract
The invention relates to the technical field of voltage measuring instruments, in particular to an ammeter with a monitoring function. The ammeter provided by the invention uploads a voltage signal to the cloud server through the voltage sensor device in the voltage monitoring control module, the cloud server acquires a standard feature vector representing normal signal fluctuation in historical data, and judges whether the real-time voltage signal is an abnormal signal or not by comparing the standard feature vector with the real-time feature vector of the real-time voltage signal, and feeds back a first disconnection control signal. The surge protector is also used for detecting the amplitude of the real-time voltage signal and feeding back a second disconnection control signal. The relay receives the first breaking control signal and the second breaking control signal to conduct breaking operation. According to the invention, the real-time voltage signal is monitored through the voltage signal fluctuation and the amplitude, so that dangerous events can be effectively prevented in time.
Description
Technical Field
The invention relates to the technical field of voltage measuring instruments, in particular to an ammeter with a monitoring function.
Background
In the actual application process of the ammeter box, the components such as the ammeter in the box can be broken down or heat, and because the circuit in the ammeter box is complex, if the real-time voltage state is not monitored in time, the ammeter box can be triggered to fire, and dangerous events such as fire and electric leakage occur.
A surge protector is arranged on an existing ammeter with a monitoring function and used for detecting abnormal voltage in real time, so that an open circuit command is fed back in time, and dangerous events are prevented from happening. However, the voltage signal is a signal with obvious fluctuation, if abnormal fluctuation of the voltage occurs at a certain moment, the abnormal fluctuation still causes damage to an instrument line in the ammeter box, and the surge protector cannot recognize the abnormal fluctuation, so that the ammeter monitoring function is disabled, and disaster hidden danger is generated.
Disclosure of Invention
In order to solve the technical problem that the existing ammeter with the monitoring function cannot accurately monitor abnormal voltage, the invention aims to provide the ammeter with the monitoring function, and the adopted technical scheme is as follows:
the invention provides an ammeter with a monitoring function, which comprises an ammeter body and a voltage monitoring control module, wherein the inlet end of an inlet wire switch of the ammeter body is connected with the voltage monitoring control module, and the voltage monitoring control module comprises a voltage sensing device 11, a surge protector 1 and a relay 10; the voltage sensing device 11 detects a real-time voltage signal of the inlet wire end and sends the real-time voltage signal to the cloud server and the surge protector 1, the surge protector 1 analyzes the real-time voltage signal and sends a second disconnection control signal to the relay 10, and the relay 10 receives a first disconnection control signal sent by the cloud server or a second disconnection control signal sent by the surge protector 1 and performs disconnection operation;
the cloud server sending the first disconnection control signal under the conditions that:
counting the non-load normal voltage signals and the load normal voltage signals in a historical time period before the real-time moment; obtaining a plurality of first component signals of the non-load normal voltage signals and a plurality of second component signals of the load normal voltage signals; matching the first component signal and the second component signal to obtain a plurality of matched pairs; according to the difference of the corresponding position data points between the two signals in the matching pair, counting the positions of the mutation points, wherein the mutation points form a characteristic value sequence of the corresponding matching pair; taking the feature vectors of all the feature value sequences as standard feature vectors; acquiring a real-time characteristic vector of the real-time voltage signal, judging whether the real-time voltage signal is an abnormal signal according to the similarity between the real-time characteristic vector and the standard characteristic vector, and if the real-time voltage signal is the abnormal signal, sending a first disconnection control signal;
the conditions under which the surge protector 1 transmits the second open circuit control signal include:
and if the amplitude of the real-time voltage signal is detected to be an abnormal amplitude, sending a second disconnection control signal.
Further, the cloud server counts the non-load normal voltage signal and the load normal voltage signal in the historical time period before the real-time moment, including:
counting a historical normal voltage signal in a historical time period, and dividing the historical normal voltage signal into a historical non-load normal voltage signal and a historical load normal voltage signal; each historical normal voltage signal is the same as the real-time voltage signal in length; the number of the historical non-load normal voltage signals is the same as the number of the historical load normal voltage signals; splicing the historical normal voltage signals without load according to a time sequence to obtain the normal voltage signals without load; and splicing the historical load normal voltage signals according to a time sequence to obtain the load normal voltage signals.
Further, the cloud server obtains a plurality of IMF components of the non-load normal voltage signal as the first component signal by adopting an EMD decomposition algorithm, and samples the IMF components of the load normal voltage signal as the second component signal by adopting the EMD decomposition algorithm.
Further, in the cloud server, the method for acquiring the matching pair includes:
and respectively taking the first component signal and the second component signal as nodes on one side in a KM matching algorithm, taking cosine similarity as an edge weight between the nodes on two sides, and taking two nodes with the edge weight larger than a preset edge weight threshold as matching pairs.
Further, in the cloud server, the method for acquiring the mutation point position includes:
matching signal points between two signals in the matching pair by using a DTW algorithm to obtain a matching result of each signal point; each signal point is used as a signal point to be analyzed, and if the matching result of the signal point to be analyzed is matched with at least two other signal points, the corresponding signal point to be analyzed is marked as a mutation point; traversing all signal points to be analyzed to obtain all mutation points; the location of the discontinuity on the first component signal or the second component signal is taken as the discontinuity location.
Further, in the cloud server, the method for obtaining the standard feature vector includes:
taking the characteristic value sequence of each matched pair as one row of a first characteristic matrix to obtain the first characteristic matrix; and obtaining first eigenvectors of the first eigenvector matrix by utilizing an SVD (singular value decomposition) algorithm, wherein the first eigenvectors are ordered in descending order according to corresponding eigenvalues, and the preset number of first eigenvectors are selected as the standard eigenvectors.
Further, in the cloud server, the method for acquiring the real-time feature vector includes:
dividing the real-time voltage signals and forming a real-time voltage signal matrix, wherein the size of the real-time voltage signal matrix is the same as that of the first feature matrix; and obtaining second eigenvectors of the real-time voltage signal matrix by utilizing an SVD (singular value decomposition) algorithm, wherein the second eigenvectors are ordered in descending order according to corresponding eigenvalues, and the preset number of second eigenvectors are selected as the real-time eigenvectors.
Further, in the cloud server, the determining whether the real-time voltage signal is an abnormal signal according to the similarity between the real-time feature vector and the standard feature vector includes:
and respectively taking the real-time feature vector and the standard feature vector as nodes on one side in a KM matching algorithm, taking the DTW distance between vectors as an edge weight value, obtaining an optimal matching pair by using the KM matching algorithm, taking the average edge weight value of all the optimal matching pairs as a judging index, and judging the real-time voltage signal as an abnormal signal if the judging index is larger than a preset judging threshold value.
Further, the method for judging the abnormal amplitude value of the surge protector (1) comprises the following steps:
and if the amplitude of the real-time voltage signal is larger than a preset voltage threshold value, judging that the amplitude is abnormal.
Further, after the cloud server determines whether the real-time voltage signal is an abnormal signal, the cloud server further includes:
and if the real-time voltage signal is not an abnormal signal, averaging vectors in the optimal matching pair to obtain an update vector, and replacing the standard feature vector in the cloud server with the update vector.
The invention has the following beneficial effects:
according to the invention, a cloud computing function is added on the basis of monitoring voltage amplitude by the surge protector, a real-time voltage signal is sent to the cloud server through the voltage sensing device, the cloud server can analyze the non-load normal voltage signal and the load normal voltage information in a historical time period, and a standard feature vector is obtained by decomposing and matching component signals. The standard feature vector contains abrupt point information of signal transmission fluctuation and is obtained according to normal voltage data in a historical time period before real-time, so that the standard feature vector can be used as a standard for evaluating whether the real-time voltage signal is abnormal, the cloud server can transmit a first disconnection control signal to the relay by judging whether the real-time voltage signal is abnormal or not, and the relay can receive the first disconnection control signal transmitted by the cloud server and a second disconnection control signal transmitted by the surge protector to perform timely and accurate disconnection operation, so that dangerous events of an ammeter box are prevented.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a block diagram of a voltage monitoring control module according to an embodiment of the present invention.
Fig. 2 is a block diagram of an electric meter with a monitoring function according to an embodiment of the present invention.
Fig. 3 is a flowchart illustrating a method for sending a first disconnection control signal by a cloud server according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of DTW matching according to an embodiment of the present invention.
The reference numerals in the figures are: 1. a surge protector; 2. a wire inlet switch; 3. A leakage circuit breaker; 4. a transformer; 5. a voltage sensor; 6. an electricity meter; 7. an outlet switch; 8. an electrical fire monitoring detector; 9. an ammeter centralized meter reading device; 10. a relay; 11. a voltage sensing device.
Detailed Description
In order to further describe the technical means and effects adopted by the present invention to achieve the preset purpose, the following detailed description refers to the specific implementation, structure, characteristics and effects of an ammeter with monitoring function according to the present invention with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following specifically describes a specific scheme of the electric meter with a monitoring function provided by the invention with reference to the accompanying drawings.
The ammeter with the monitoring function in the embodiment of the invention comprises an ammeter body and a voltage monitoring control module, wherein the inlet wire end of an inlet wire switch of the ammeter body is connected with the voltage monitoring control module, and the voltage monitoring control module comprises a voltage sensing device 11, a surge protector 1 and a relay 10. Referring to fig. 1, a block diagram of a voltage monitoring control module according to an embodiment of the present invention is shown, in fig. 1, a left side of a voltage sensing device 11 is connected to a wire inlet end of an ammeter body, that is, the voltage sensing device can detect voltage through the wire inlet end of a wire inlet switch of the ammeter body and form a real-time voltage signal; the right side of the voltage sensing device 11 is connected with the surge protector 1, and the voltage sensing device 11 can transmit detected real-time voltage signals to the surge protector 1; the surge protector 1 is able to analyze the real-time voltage signal and send a second open-circuit control signal to the relay 10; the voltage sensing device 11 also needs to send the real-time voltage signal to a cloud server, and the cloud server sends a first disconnection control signal to the relay 10 by analyzing the real-time voltage signal; the relay 10 receives the first or second open control signal and performs an open operation. The ammeter in the embodiment of the invention increases the cloud computing analysis process on the basis of detecting the abnormal voltage by the traditional surge protector, namely, the relay 10 can simultaneously receive two breaking signals. When the amplitude of the real-time voltage signal has obvious abnormality, the abnormality can be detected directly through the local surge protector 1, a second open-circuit control signal is fed back to the relay 10, and the relay 10 executes open-circuit operation to protect the safety of the ammeter box; when the amplitude of the real-time voltage signal is not obviously abnormal, but the data fluctuation is abnormal, the surge protector 1 cannot feed back the second breaking control signal, the cloud server can send the first breaking control signal to the relay 10, the relay 10 can cut off the circuit through an internal electromagnetic mechanism or a semiconductor switch and the like, and the breaking operation is performed to protect the safety of the ammeter box.
The ammeter provided by the embodiment of the invention can analyze the abnormal state of the real-time voltage from two dimensions of the voltage amplitude and the voltage fluctuation, can realize effective monitoring of the real-time voltage and can prevent dangerous events from happening to the ammeter box.
It should be noted that, the voltage monitoring control module provided by the embodiment of the present invention may be applied to all electric meter bodies, for example, an electric meter box with fire monitoring function proposed in CN212624311U, please refer to fig. 2, which shows a structure diagram of an electric meter with monitoring function provided by an embodiment of the present invention, where the electric meter in fig. 2 includes a surge protector 1; a wire inlet switch 2; a leakage circuit breaker 3; a transformer 4; a voltage sensor 5; an electricity meter 6; an outlet switch 7; an electrical fire monitoring detector 8; an ammeter centralized meter-reading device 9; a relay 10; a voltage sensing device 11. In the electricity meter of fig. 2, the respective structures are wired inside the electricity meter, wherein the voltage sensing device 11, the surge protector 1 and the relay 10 constitute a voltage monitoring control module at the lower right corner. Inside the ammeter, the voltage sensing device 11 is connected to the incoming line switch 2 and the surge protector 1, the surge protector is connected to the voltage sensing device 11 and the relay 10, and the connection modes of other structures are already known to those skilled in the art, and are not described herein.
Referring to fig. 3, a flowchart illustrating a method for sending a first disconnection control signal by a cloud server according to an embodiment of the invention is shown, where the method includes:
step S1: counting the non-load normal voltage signals and the load normal voltage signals in a historical time period before the real-time moment; a plurality of first component signals of the non-load normal voltage signal are obtained, and a plurality of second component signals of the load normal voltage signal are obtained.
In order to judge whether the real-time voltage signal is an abnormal signal, the cloud server in the embodiment of the invention adopts a matching idea to obtain the fluctuation characteristics of the normal voltage signal, and the real-time voltage signal is compared with the real-time voltage signal to judge the abnormality of the real-time voltage signal. Considering that the electricity consumption data has a certain periodicity, the characteristics of the electricity consumption data in the continuous time period are consistent, so that the normal voltage data in the historical time period before the real-time moment is counted for analysis, and the accuracy of subsequent comparison judgment is ensured. Further consider that the voltage signal in the electricity data is divided into a loaded case and an unloaded case, and thus the non-loaded normal voltage signal and the loaded normal voltage signal are further divided.
Preferably, in one embodiment of the present invention, the counting, by the cloud server, the non-load normal voltage signal and the load normal voltage signal in the historical time period before the real-time moment includes:
counting a historical normal voltage signal in a historical time period, and dividing the historical normal voltage signal into a historical non-load normal voltage signal and a historical load normal voltage signal; to facilitate matching of subsequent processes, the number of historical non-load normal voltage signals is the same as the number of historical load normal voltage signals. Because the obtained historical normal voltage signal with no load or the historical normal voltage signal with no load can be data with multiple sections of the same length, the historical normal voltage signal with no load is spliced according to time sequence to obtain the normal voltage signal with no load for the convenience of subsequent data processing; and splicing the historical load normal voltage signals according to the time sequence to obtain the load normal voltage signals.
In one embodiment of the present invention, each voltage signal is 5 minutes in length, and the historical time period is set to a time period of thirty voltage signals before the real-time instant. If the number of the counted historical normal voltage signals of the non-load is larger than that of the historical normal voltage signals of the load, continuously counting the historical normal voltage signals of the load to the historical moment before the historical time period until the number of the two voltage signals is equal; if the number of the counted historical non-load normal voltage signals is smaller than that of the historical load normal voltage signals, deleting the historical non-load normal voltage signals which are in front in time sequence until the number of the two voltage signals is equal.
Normally, the voltage signal is periodically changed, but in special cases, the waveform of the voltage signal may be changed to some extent due to load change or other factors, for example, when the load is high, the waveform may become irregular or distorted although the voltage signal maintains the periodic change. All conventional periodic waveform comparison methods are difficult to accurately monitor and identify abnormal voltage fluctuation. Therefore, the voltage signals are required to be divided into two categories of load and non-load, the voltage signals are decomposed, one signal is decomposed into component signals with a plurality of frequencies, fluctuation of the signals is analyzed among different component signals, and the problem that monitoring effect is poor due to analysis periodicity is avoided. According to the embodiment of the invention, the non-load normal voltage signal and the load normal voltage signal are respectively decomposed to obtain a plurality of first component signals of the non-load normal voltage signal and a plurality of second component signals of the load normal voltage signal.
Preferably, in one embodiment of the present invention, the signal decomposition algorithm uses an EMD decomposition algorithm, that is, the cloud server uses the EMD decomposition algorithm to obtain a plurality of IMF components of the non-load normal voltage signal as a first component signal, and samples the EMD decomposition algorithm to obtain a plurality of IMF components of the load normal voltage signal as a second component signal. It should be noted that the EMD decomposition algorithm is a technical means well known to those skilled in the art, and will not be described herein.
Step S2: matching the first component signal and the second component signal to obtain a plurality of matched pairs; according to the difference of the corresponding position data points between the two signals in the matching pair, counting the positions of the mutation points, wherein the mutation points form a characteristic value sequence of the corresponding matching pair; and taking the eigenvectors of all eigenvalue sequences as standard eigenvectors.
Because the normal voltage signals have certain local differences in waveforms due to different load types, the integral change trend is similar because the normal voltage signals belong to the same, so that classification signals under different frequencies can be matched with each other, further common characteristics are obtained, and standard characteristic vectors with strong referential property are obtained.
Because the first classification signal and the second classification signal belong to different load categories, the first classification signal and the second classification signal are matched with each other, and a plurality of matched pairs are obtained, i.e. one matched pair comprises one first classification signal and one second classification signal.
Preferably, in one embodiment of the present invention, the method for acquiring the matching pair includes:
the first component signal and the second component signal are respectively used as nodes on one side in the KM matching algorithm, cosine similarity is used as an edge weight between the nodes on two sides, and two nodes with the edge weight larger than a preset edge weight threshold are used as matching pairs.
It should be noted that the KM matching algorithm and the cosine similarity are technical means well known to those skilled in the art, and are not described herein. In the embodiment of the invention, after the edge weight is normalized, the threshold value of the edge weight is set to be 0.7. It should be noted that, the obtaining of the matching pair is not a step of searching for the optimal matching relationship, and because two nodes with edge weights greater than the preset edge weight threshold are used as the matching pair, the situation that the same node appears in different matching pairs exists.
Because the two signals in the matching pair belong to the normal voltage signal but belong to different load types, the position of the mutation point can be counted by comparing the difference of the corresponding position data points between the two signals, the position of the mutation point can represent the position when the signal data between the two signals are transmitted in different changes, and therefore the position can be used as characteristic information, namely, the mutation point forms a characteristic value sequence of the corresponding matching pair, and because a plurality of matching pairs exist, characteristic vectors of all characteristic value sequences are used as standard characteristic vectors. That is, the standard feature vector contains feature position information on normal voltage data, and can be used as a basis for subsequent judgment of real-time voltage signal abnormality.
Preferably, in an embodiment of the present invention, in a cloud end server, a method for acquiring a mutation point position includes:
and matching the signal points between the two signals in the matching pair by using a DTW algorithm to obtain a matching result of each signal point. Each signal point is used as a signal point to be analyzed, and if the matching result of the signal point to be analyzed is matched with at least two other signal points, the corresponding signal point to be analyzed is marked as a mutation point; traversing all signal points to be analyzed to obtain all mutation points; the location of the discontinuity on the first component signal or the second component signal is taken as the location of the discontinuity. Referring to fig. 4, a DTW matching diagram is shown, in which an upper curve in fig. 4 is a first component signal, a lower curve in fig. 4 is a second component signal, dashed lines between two curves in fig. 4 indicate correspondence, and fig. 4 shows that after DTW matching, there are one-to-one and one-to-many cases in a matching relationship of signal points, and one-to-many signal points are points when two signals transmit different trend directions of data, for example, a 7 th signal point of an upper curve in fig. 4 corresponds to 8 th and 7 th points of a lower curve. Therefore, the signal points corresponding to one-to-many can be used as mutation points, and the mutation point positions can be obtained.
In one embodiment of the invention, the position difference between the matching relations of each signal point, namely the difference of the corresponding serial number values of the signal points on the curve, is obtained. If the signal points are in a one-to-one condition continuously, the difference of the sequence number values cannot be changed; if the signal points are in a one-to-many condition, the sequence number value differences will change, for example, the sequence number value differences of the first 6 signal points in fig. 4 are all 0, and the sequence number value differences of the 7 th signal point of the upper curve and the 8 th and 7 th points of the lower curve are 1 and 0. Therefore, the idea of encoding can be adopted to construct sequence number value difference sequences to obtain the running information of each sequence number value, in the embodiment of the invention, a binary group is constructed, wherein the first element in the binary group is sequence number value difference, and the second element is the number of continuous occurrences of the first element obtained by using the running code analysis. When the second element in the binary group is smaller than 2, the condition that the corresponding signal points are one-to-many is described, so that mutation point information is obtained.
Preferably, in one embodiment of the present invention, the method for obtaining the standard feature vector includes:
and taking the characteristic value sequence of each matching pair as one row of the first characteristic matrix to obtain the first characteristic matrix. The number of rows of the first feature matrix is the number of matched pairs, and the number of columns is the length of the longest feature value sequence. And obtaining first eigenvectors of the first eigenvector matrix by utilizing an SVD (singular value decomposition) algorithm, sorting the first eigenvectors in descending order according to the corresponding eigenvalues, and selecting a preset number of first eigenvectors as standard eigenvectors. It should be noted that, the SVD decomposition algorithm is a technical means well known to those skilled in the art, and will not be described herein. In the embodiment of the present invention, the preset number is set to 10, that is, the first ten first feature vectors are selected as standard feature vectors, that is, the standard feature vectors are a set of vectors.
Step S3: and obtaining a real-time characteristic vector of the real-time voltage signal, judging whether the real-time voltage signal is an abnormal signal according to the similarity between the real-time characteristic vector and the standard characteristic vector, and if the real-time voltage signal is the abnormal signal, sending a first disconnection control signal.
The cloud server in the step S1 and the cloud server in the step S2 obtain standard feature vectors for matching comparison, the real-time voltage signals are further converted into the real-time feature vectors with the same form as the characteristic feature vectors, the matching comparison process can be carried out, whether the real-time voltage signals are abnormal information or not is judged according to the similarity between the real-time feature vectors and the characteristic feature vectors, namely the greater the similarity is, the more the real-time voltage signals belong to the data distribution of the normal voltage signals; the smaller the similarity, the greater the probability that the abnormal fluctuation appears on the real-time voltage signal and is an abnormal signal. When the real-time voltage signal is judged to be an abnormal signal, the cloud server can send a first disconnection control signal.
Preferably, considering that the standard feature vector in one embodiment of the present invention is a set of vectors, the method for acquiring the real-time feature vector includes:
dividing the real-time voltage signals and forming a real-time voltage signal matrix, wherein the size of the real-time voltage signal matrix is required to be ensured to be the same as that of the first characteristic matrix in order to facilitate the comparison of the characteristic vectors; and obtaining second eigenvectors of the real-time voltage signal matrix by utilizing an SVD (singular value decomposition) algorithm, and ordering the second eigenvectors in a descending order according to the corresponding eigenvalues, wherein a preset number of second eigenvectors are selected as the real-time eigenvectors, namely the number of the second eigenvectors is the same as that of the first eigenvectors.
Because the implementation feature vector and the characterization feature vector are each a set of a plurality of vectors in one embodiment of the present invention, determining whether the real-time voltage signal is an abnormal signal according to the similarity between the real-time feature vector and the standard feature vector in one preferred embodiment of the present invention includes:
and respectively taking the real-time feature vector and the standard feature vector as nodes on one side in the KM matching algorithm, taking the DTW distance between the vectors as an edge weight value, obtaining an optimal matching pair by using the KM matching algorithm, taking the average edge weight value of all the optimal matching pairs as a discrimination index, and judging the real-time voltage signal as an abnormal signal if the discrimination index is larger than a preset discrimination threshold value. In one embodiment of the present invention, after normalizing the discrimination indicator, the discrimination threshold is set to 0.3.
Preferably, in an embodiment of the present invention, after the cloud server determines whether the real-time voltage signal is an abnormal signal, the method further includes:
if the real-time voltage signal is not an abnormal signal, averaging vectors in the optimal matching pair to obtain an update vector, and replacing a standard feature vector in the cloud server with the update vector. The method has the advantages that the characteristic vector in the cloud server is updated, the updated standard characteristic vector can be directly used as data for matching comparison in the subsequent monitoring process, and the characteristic vector is obtained without reckoning voltage signals in a historical time period.
Preferably, in one embodiment of the present invention, the method for judging the abnormal amplitude of the surge protector 1 includes: if the amplitude of the real-time voltage signal is greater than the preset voltage threshold, the MOV in the surge protector 1 will become a high resistance state, limit the current and determine that the amplitude is abnormal, and send a second open control signal to the relay 10. It should be noted that, the voltage threshold may be set according to the actual implementation, and is not limited herein.
It should be noted that, the structure with signal receiving and transmitting functions in the ammeter provided by the embodiment of the invention can directly adopt the signal receiving and transmitting module commonly used in the prior art, and the specific model is not limited.
In summary, the electric meter provided by the embodiment of the invention uploads the voltage signal to the cloud server through the voltage sensor device in the voltage monitoring control module, the cloud server obtains the standard feature vector representing the normal signal fluctuation in the historical data, and judges whether the real-time voltage signal is an abnormal signal or not by comparing the standard feature vector with the real-time feature vector of the real-time voltage signal, and feeds back the first disconnection control signal. The surge protector is also used for detecting the amplitude of the real-time voltage signal and feeding back a second disconnection control signal. The relay receives the first breaking control signal and the second breaking control signal to conduct breaking operation. According to the invention, the real-time voltage signal is monitored through the voltage signal fluctuation and the amplitude, so that dangerous events can be effectively prevented in time.
It should be noted that: the sequence of the embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
Claims (7)
1. The utility model provides an ammeter with monitor function, the ammeter includes ammeter body and voltage monitoring control module, its characterized in that, the inlet wire end of inlet wire switch of ammeter body links to each other with voltage monitoring control module, and voltage monitoring control module includes voltage sensing device (11), surge protector (1) and relay (10); the voltage sensing device (11) detects a real-time voltage signal of the inlet wire end and sends the real-time voltage signal to the cloud server and the surge protector (1), the surge protector (1) analyzes the real-time voltage signal and sends a second disconnection control signal to the relay (10), and the relay (10) receives the first disconnection control signal sent by the cloud server or the second disconnection control signal sent by the surge protector (1) and performs disconnection operation;
the cloud server sending the first disconnection control signal under the conditions that:
counting the non-load normal voltage signals and the load normal voltage signals in a historical time period before the real-time moment; obtaining a plurality of first component signals of the non-load normal voltage signals and a plurality of second component signals of the load normal voltage signals; matching the first component signal and the second component signal to obtain a plurality of matched pairs; according to the difference of the corresponding position data points between the two signals in the matching pair, counting the positions of the mutation points, wherein the mutation points form a characteristic value sequence of the corresponding matching pair; taking the feature vectors of all the feature value sequences as standard feature vectors; acquiring a real-time characteristic vector of the real-time voltage signal, judging whether the real-time voltage signal is an abnormal signal according to the similarity between the real-time characteristic vector and the standard characteristic vector, and if the real-time voltage signal is the abnormal signal, sending a first disconnection control signal;
the condition for the surge protector (1) to send the second disconnection control signal includes:
if the amplitude of the real-time voltage signal is detected to be an abnormal amplitude, a second disconnection control signal is sent;
the cloud server obtains a plurality of IMF components of the non-load normal voltage signal by adopting an EMD (empirical mode decomposition) algorithm as the first component signal, and samples the IMF components of the load normal voltage signal by adopting the EMD algorithm as the second component signal;
in the cloud server, the method for acquiring the matching pair comprises the following steps:
the first component signal and the second component signal are respectively used as nodes on one side in a KM matching algorithm, cosine similarity is used as an edge weight between the nodes on two sides, and two nodes with the edge weight larger than a preset edge weight threshold are used as matching pairs;
in the cloud server, the method for acquiring the mutation point position comprises the following steps:
matching signal points between two signals in the matching pair by using a DTW algorithm to obtain a matching result of each signal point; each signal point is used as a signal point to be analyzed, and if the matching result of the signal point to be analyzed is matched with at least two other signal points, the corresponding signal point to be analyzed is marked as a mutation point; traversing all signal points to be analyzed to obtain all mutation points; the location of the discontinuity on the first component signal or the second component signal is taken as the discontinuity location.
2. The utility meter with monitoring function according to claim 1, wherein the cloud server counts the non-load normal voltage signal and the load normal voltage signal in a historical period of time before the real-time instant, comprising:
counting a historical normal voltage signal in a historical time period, and dividing the historical normal voltage signal into a historical non-load normal voltage signal and a historical load normal voltage signal; each historical normal voltage signal is the same as the real-time voltage signal in length; the number of the historical non-load normal voltage signals is the same as the number of the historical load normal voltage signals; splicing the historical normal voltage signals without load according to a time sequence to obtain the normal voltage signals without load; and splicing the historical load normal voltage signals according to a time sequence to obtain the load normal voltage signals.
3. The electricity meter with a monitoring function according to claim 1, wherein the method for obtaining the standard feature vector in the cloud server comprises:
taking the characteristic value sequence of each matched pair as one row of a first characteristic matrix to obtain the first characteristic matrix; and obtaining first eigenvectors of the first eigenvector matrix by utilizing an SVD (singular value decomposition) algorithm, wherein the first eigenvectors are ordered in descending order according to corresponding eigenvalues, and the preset number of first eigenvectors are selected as the standard eigenvectors.
4. The electricity meter with a monitoring function according to claim 3, wherein the method for obtaining the real-time feature vector in the cloud server comprises:
dividing the real-time voltage signals and forming a real-time voltage signal matrix, wherein the size of the real-time voltage signal matrix is the same as that of the first feature matrix; and obtaining second eigenvectors of the real-time voltage signal matrix by utilizing an SVD (singular value decomposition) algorithm, wherein the second eigenvectors are ordered in descending order according to corresponding eigenvalues, and the preset number of second eigenvectors are selected as the real-time eigenvectors.
5. The electric meter with monitoring function according to claim 4, wherein the determining, in the cloud server, whether the real-time voltage signal is an abnormal signal according to the similarity between the real-time feature vector and the standard feature vector comprises:
and respectively taking the real-time feature vector and the standard feature vector as nodes on one side in a KM matching algorithm, taking the DTW distance between vectors as an edge weight value, obtaining an optimal matching pair by using the KM matching algorithm, taking the average edge weight value of all the optimal matching pairs as a judging index, and judging the real-time voltage signal as an abnormal signal if the judging index is larger than a preset judging threshold value.
6. An electricity meter with monitoring function according to claim 1, characterized in that the method for determining the abnormal amplitude of the surge protector (1) comprises:
and if the amplitude of the real-time voltage signal is larger than a preset voltage threshold value, judging that the amplitude is abnormal.
7. The electric meter with monitoring function according to claim 5, wherein the cloud server further comprises, after determining whether the real-time voltage signal is an abnormal signal:
and if the real-time voltage signal is not an abnormal signal, averaging vectors in the optimal matching pair to obtain an update vector, and replacing the standard feature vector in the cloud server with the update vector.
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