A fault alarm system for intelligent electric energy meters

Abstract

The present invention discloses a fault alarm system for an intelligent electric energy meter, which relates to the technical field of electric power instruments and meters, and solves the technical problem that the existing electric energy meter cannot provide fault diagnosis alarm and fault warning; the system includes a data acquisition module, which is used to collect the operation data of the intelligent electric energy meter and send it to the data storage and analysis module; a data storage and transmission module, which is used to send the stored operation data to the data analysis and processing module; a data analysis and processing module, which is used to perform fault analysis on the operation data and generate an alarm instruction according to the fault analysis result, and send the fault analysis result and the alarm instruction to the data storage and transmission module for storage; an instruction execution module, which is used to execute the alarm instruction. The data analysis and processing module includes a fault diagnosis unit, a data processing unit and an instruction generation unit. The present invention is reasonably designed and is convenient for fault alarm of the intelligent electric energy meter.

Description

Technical Field

[0001] The invention belongs to the technical field of electric power instruments and meters, relates to smart electric meter technology, and specifically is a fault alarm system for a smart electric energy meter. Background Art

[0002] Smart energy meters are composed of measurement units, data processing units, communication units, etc., and have functions such as energy metering, information storage and processing, real-time monitoring, automatic control, and information interaction. At present, due to poor electricity management by electricity users, household fires and personal electric shock accidents occur from time to time. In the prior art, the lines are mostly detected to collect electricity usage information in the homes of electricity users. When the current, voltage or other data in the circuit changes, the protection mechanism in the smart meter is activated to protect the circuit. However, its analysis method is too simple. It only triggers the circuit protection mechanism based on simple operating data such as voltage and current reaching the trigger standard. It does not conduct in-depth analysis of the operating data to determine the cause of the fault. After the circuit protection mechanism is triggered, the user is unclear about the cause of the fault. Therefore, a smart energy meter fault alarm system is needed to provide fault diagnosis alarm and fault warning services. Summary of the invention

[0003] The present invention provides a smart electric energy meter fault alarm system, which is used to solve the technical problem that the existing electric energy meters cannot perform fault diagnosis and alarm and fault early warning.

[0004] The purpose of the present invention can be achieved through the following technical solutions:

[0005] A smart electric energy meter fault alarm system, comprising:

[0006] The data storage and transmission module is used to store the operation data of the smart electric energy meter and send it to the data analysis and processing module; the operation data includes the vibration signal of the electric energy meter, the temperature signal of the electric energy meter, the current signal and the voltage signal;

[0007] The data analysis and processing module is used to perform fault analysis on the operation data and generate fault analysis results and alarm instructions. The specific process of generating fault analysis results and alarm instructions includes:

[0008] Preprocess the operation data to generate preprocessing signals. First, check and diagnose the preprocessing signals to diagnose the energy meter energy consumption fault and branch power theft fault. Then, perform in-depth diagnosis on the preprocessing signals to diagnose the energy meter over-temperature fault, impact fault, vibration fault and over-current fault. Then, generate the diagnosis results, and generate alarm instructions according to the diagnosis result-alarm instruction mapping, and send them to the instruction execution module.

[0009] The instruction execution module is used to execute the alarm instruction.

[0010] Furthermore, the operation data is preprocessed, and the specific process includes:

[0011] First, an operation data-time curve is generated according to the operation data, and the operation data-time curve includes an electric meter vibration signal-time curve, an electric meter temperature signal-time curve, a current signal-time curve and a voltage signal-time curve; then, an incoming power-time curve, an outgoing power-time curve, a branch power-time curve, an incoming electric energy consumption-time curve, an outgoing electric energy consumption-time curve and a branch electric energy consumption-time curve are generated according to the operation data-time curve.

[0012] Furthermore, the energy consumption fault of the energy meter is checked and diagnosed, and the specific process includes:

[0013] In the same coordinate system, the distance between the incoming power consumption-time curve and the outgoing power consumption-time curve at the same time is calculated respectively to generate a distance-time curve. Then, the distance-time curve is sampled to obtain a distance sampling data set and calculate the distance standard deviation. When the standard deviation is greater than or equal to the set threshold, it is determined that the energy meter has an energy consumption fault.

[0014] The specific process of diagnosing the power theft fault in the power meter branch is the same as the process of diagnosing the power meter energy consumption fault.

[0015] Furthermore, the over-temperature fault is diagnosed in depth, and the specific process includes:

[0016] Set a first set change rate and a second set change rate; set a first set temperature and a second set temperature, analyze the meter temperature signal-time curve, and when the meter temperature is greater than the first set temperature, determine that the meter over-temperature fault occurs; when the meter temperature is greater than the second set temperature for a continuous time exceeding the set time, determine that the meter over-temperature fault occurs.

[0017] Furthermore, the impact fault is diagnosed in depth, and the specific process includes:

[0018] The voltage signal-time curve is derived to obtain a voltage change rate-time curve; when the voltage change rate is greater than a first set change rate, it is determined that an impact fault occurs; when the voltage change rate is greater than a second set change rate for a time greater than a set time, it is determined that an impact fault occurs.

[0019] Furthermore, the vibration fault is diagnosed in depth. The specific process includes:

[0020] The vibration signal-time curve is subjected to discrete Fourier transform to obtain the meter vibration signal spectrum diagram, and then the meter vibration signal spectrum diagram is demodulated to obtain a demodulated spectrum. The demodulated spectrum is compared with the fault spectrum to determine whether the electric energy meter has a vibration fault.

[0021] Furthermore, the vibration fault includes excessive load, eddy current vibration of the turntable, loose electromagnetic coil, loose iron core and lack of oil in the meter turntable.

[0022] Furthermore, it also includes a data acquisition module, which is used to collect the operating data of the smart meter and send it to the data storage and transmission module.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] The present invention determines the fault of the electric energy meter and the branch power theft fault respectively by checking and diagnosing the incoming power consumption-time curve, the outgoing power consumption-time curve and the branch power consumption-time curve; the present invention formulates different processing methods and fault diagnosis methods according to the temperature signal-time curve of the electric meter, the voltage signal-time curve, the vibration signal-time curve of the electric meter, the branch power-time curve and the branch current-time curve, and meets the needs of fault diagnosis of the intelligent electric energy meter. When diagnosing the vibration signal of the electric meter, the frequency domain analysis method is used to analyze the vibration signal, and by comparing it with the fault spectrum, the mechanical fault inside the electric meter can be diagnosed; it can accurately diagnose various faults of the electric energy meter. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0027] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] The terms used herein are used to describe embodiments and are not intended to restrict and / or limit the present disclosure; it should be noted that the singular forms "a", "an", and "the" also include plural forms unless the context clearly indicates otherwise; and, although terms "first", "second", etc. may be used herein to describe various elements, the elements are not limited by these terms, which are only used to distinguish one element from another.

[0029] like Figure 1 As shown, a smart energy meter fault alarm system includes a data acquisition module for collecting operation data of the smart meter and sending it to a data storage and analysis module;

[0030] The operation data includes meter vibration signal, meter temperature signal, current signal and voltage signal. The current signal includes branch current signal and main current signal. The voltage signal includes incoming voltage signal, outgoing voltage signal and branch voltage signal. The corresponding data is collected through vibration sensor, temperature sensor, current sensor and voltage sensor.

[0031] A data storage and transmission module, used for sending the stored operation data to the data analysis and processing module;

[0032] A data analysis and processing module is used to perform fault analysis on the operation data and generate an alarm instruction according to the fault analysis result, and send the fault analysis result and the alarm instruction to the data storage and transmission module for storage;

[0033] The data analysis and processing module includes a fault diagnosis unit, a data processing unit and an instruction generation unit. The data processing unit is used to pre-process the operation data, and the specific process includes:

[0034] The operation data is preprocessed to obtain a preprocessed signal, wherein the preprocessing is to convert the meter vibration signal, meter temperature signal, current signal and voltage signal into a meter vibration signal-time curve, a meter temperature signal-time curve, a current signal-time curve and a voltage signal-time curve; and according to the current signal-time curve and the voltage signal-time curve, an incoming power-time curve, an outgoing power-time curve and a branch power-time curve are generated, thereby obtaining an incoming power consumption-time curve, an outgoing power consumption-time curve and a branch power consumption-time curve.

[0035] The fault diagnosis unit is used to perform fault diagnosis according to the operation data to obtain a fault analysis result; the specific process of the fault diagnosis unit performing fault diagnosis according to the operation data is as follows:

[0036] The preprocessing signal is checked and diagnosed, and the check and diagnosis preprocessing signal includes the incoming power consumption-time curve and the outgoing power consumption-time curve for checking and diagnosis. It should be noted that the power consumption of the smart power meter should be considered during the check and diagnosis. Ideally, the power consumption of the smart power meter is always consistent, that is, in the same coordinate system, the incoming power consumption-time curve is obtained by translating the outgoing power consumption-time curve upward. However, in the actual working process, the power consumption of the smart power meter is not always consistent. When the current is large, the power consumption is also large. The solution is to adjust the two; the adjustment is to calculate the distance between the incoming power consumption-time curve and the outgoing power consumption-time curve to obtain the spacing-time curve, and then sample the spacing to obtain the spacing sampling data set. The sampling frequency can be set according to actual conditions and is not specifically limited here. The largest and smallest intervals in the sampling data set are removed, and then the standard deviation of the remaining interval set is calculated. When the standard deviation is less than the set threshold, it is judged that the electric energy meter has no energy consumption fault. When the standard deviation is greater than or equal to the set threshold, it is judged that the electric energy meter has an energy consumption fault.

[0037] The verification and diagnosis preprocessing signal also includes the verification and diagnosis of the outgoing line power consumption-time curve and the branch power consumption-time curve. It should be noted that there are multiple branch power consumption-time curves that respectively represent the power consumption of each branch at the lower end of the power meter. All branch power consumption-time curves at the lower end of the power meter are integrated into a branch comprehensive power consumption-time curve, and the branch comprehensive power consumption-time curve is verified and diagnosed with the outgoing line power consumption-time curve. In theory, the branch comprehensive power consumption-time curve and the outgoing line power consumption-time curve are two overlapping curves in the same coordinate system, but in reality, each branch may have line loss and other conditions, so the calculated branch comprehensive power consumption is less than the outgoing line power consumption. The solution is to adjust the branch comprehensive power consumption-time curve and the outgoing line power consumption-time curve, and the adjustment process is consistent with the above. When the standard deviation is less than the set threshold, it is judged that there is no power theft fault in the branch, and when the standard deviation is greater than or equal to the set threshold, it is judged that there is a power theft fault in the branch;

[0038] After checking the diagnostic preprocessing signal, perform deep diagnosis of the preprocessing signal, including deep diagnosis of the meter temperature signal-time curve, setting a first set temperature and a second set temperature, when the meter temperature signal-time curve has a point greater than the first set temperature, immediately determine that the meter has an over-temperature fault, when there is a section or several sections of the meter temperature signal-time curve that continuously exceeds the second set temperature but does not reach the first set temperature, obtain the time when the temperature is continuously greater than the second set temperature through the meter temperature signal-time curve, when the time when the temperature is continuously greater than the second set temperature is less than the set time, determine that the meter has no over-temperature fault, and when the time when the temperature is continuously greater than the second set temperature is greater than or equal to the set threshold, determine that the meter has an over-temperature fault;

[0039] The pre-processing signal deep diagnosis also includes deep diagnosis of voltage signal-time curve, and the process is: deriving the voltage signal-time curve to obtain the voltage change rate-time curve. It should be noted that no matter the incoming line voltage, the outgoing line voltage or the voltage of each branch, it should be the standard voltage in theory during normal operation, such as 220V for household electricity and 380V for industrial electricity. However, the change of the power grid load will bring a certain impact to the incoming line voltage, and the load change on the line will also impact the outgoing line voltage and the voltage of each branch, thereby bringing about a change in the voltage signal, which generally lasts for a short time and the impact amplitude is relatively small. The fault voltage change rate and the standard voltage change rate are set. Therefore, when the voltage change rate at a certain moment is greater than the first set change rate, it means that the impact is too large and an impact fault occurs. When the voltage change rate at a certain moment is less than the first set change rate, it means that the impact is small and has no effect on the circuit and the electric energy meter. In addition, when the voltage change rate exceeds the second set change rate within a set time period, it means that the impact time is too long and an impact fault occurs. When the voltage change rate does not exceed the standard voltage change rate within a set time period, it means that the impact time is not enough to cause a fault.

[0040] The pre-processing signal deep diagnosis also includes deep diagnosis of the vibration signal-time curve of the electric meter, the vibration signal-time curve is subjected to discrete Fourier transformation to obtain the vibration signal spectrum of the electric meter, and then the vibration signal spectrum of the electric meter is demodulated to obtain a demodulated spectrum, the demodulation process includes envelope analysis, and then the demodulated spectrum is compared and analyzed, the comparative analysis is to compare the demodulated spectrum with the corresponding fault spectrum, find the fault spectrum that best matches the demodulated spectrum, and thus judge the fault. It should be noted that the fault spectrum is obtained by analyzing the vibration signal before the fault occurs after the previous fault occurs, and after neural network learning. It is emphasized here that the data acquisition module also collects the equipment information of the electric energy meter, and the equipment information includes brand, model, factory date and installation date. The vibration faults of the electric energy meter include excessive load, turntable eddy current vibration, loose electromagnetic coil, loose iron core, insufficient oil in the electric meter turntable and improper turntable installation position, etc. Long-term vibration will cause inaccurate measurement of the electric energy meter and reduce the life of the electric energy meter.

[0041] The deep diagnosis preprocessing signal also includes a deep diagnosis branch power-time curve and a branch current-time curve. The sum of the rated powers of all the equipment carried by the branch and the sum of the rated currents of all the equipment are calculated and used as the basis for verification and diagnosis of the branch power curve and the branch current curve. When there is a part in the branch power-time curve that continuously exceeds the sum of the rated powers, its duration is calculated. When the duration is greater than a set threshold, it is determined that an overload fault exists in the branch. When there is a part in the branch current-time curve that continuously exceeds the sum of the rated powers, its duration is calculated. When the duration is greater than a set threshold, it is determined that an overcurrent fault exists in the branch.

[0042] The instruction generation unit is used to generate an alarm instruction according to the fault analysis result, and the alarm instruction includes a trip instruction and an alarm instruction.

[0043] After a deep diagnosis of the preprocessed signal, a fault analysis result is obtained and sent to the instruction generation unit.

[0044] The instruction generation unit stores a mapping of fault analysis results to warning instructions, generates warning instructions according to the fault analysis results, and sends the warning instructions to the instruction execution module.

[0045] The instruction execution module includes an audible and visual alarm module and a tripping module; the audible and visual alarm module is used to execute the alarm instruction; the tripping module is used to execute the tripping instruction; the instruction execution module also includes a display screen for displaying the fault analysis results; the alarm instruction includes a voice broadcast of the fault analysis results and recommended measures.

[0046] Working principle of the present invention: The present invention collects operation data and then pre-processes the operation data to obtain the meter vibration signal-time curve, meter temperature signal-time curve, current signal-time curve and voltage signal-time curve, and then obtains the incoming power-time curve, outgoing power-time curve, branch power-time curve, incoming power consumption-time curve, outgoing power consumption-time curve, branch power consumption-time curve. Then, different processing methods are used according to the particularity of different models to diagnose the type of fault and obtain the result of diagnostic analysis.

[0047] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0048] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A smart electric energy meter fault alarm system, characterized in that: include: A data storage and transmission module is used to store the operation data of the smart energy meter and send it to the data analysis and processing module; The operation data includes the meter vibration signal, meter temperature signal, current signal and voltage signal; The data analysis and processing module is used to perform fault analysis on the operation data and generate fault analysis results and alarm instructions. The specific process of generating fault analysis results and alarm instructions includes: Preprocess the operation data to generate preprocessing signals. First, check and diagnose the preprocessing signals to diagnose the energy meter energy consumption fault and branch power theft fault. Then, perform in-depth diagnosis on the preprocessing signals to diagnose the energy meter over-temperature fault, impact fault, vibration fault and over-current fault. Then, generate the diagnosis results, and generate alarm instructions according to the diagnosis result-alarm instruction mapping, and send them to the instruction execution module. An instruction execution module, used for executing alarm instructions; Preprocess the running data. The specific process includes: Firstly, an operation data-time curve is generated according to the operation data, wherein the operation data-time curve includes an electric meter vibration signal-time curve, an electric meter temperature signal-time curve, a current signal-time curve and a voltage signal-time curve; then, an incoming power-time curve, an outgoing power-time curve, a branch power-time curve, an incoming power consumption-time curve, an outgoing power consumption-time curve and a branch power consumption-time curve are generated according to the operation data-time curve; Check and diagnose the energy consumption fault of the energy meter. The specific process includes: In the same coordinate system, the distance between the incoming power consumption-time curve and the outgoing power consumption-time curve at the same time is calculated respectively to generate a distance-time curve. Then, the distance-time curve is sampled to obtain a distance sampling data set and calculate the distance standard deviation. When the standard deviation is greater than or equal to the set threshold, it is determined that the energy meter has an energy consumption fault. The specific process of diagnosing the electricity theft fault in the electric energy meter branch is the same as the process of diagnosing the energy consumption fault in the electric energy meter; In-depth diagnosis of over-temperature faults, the specific process includes: Set a first set temperature and a second set temperature, analyze the meter temperature signal-time curve, and when the meter temperature is greater than the first set temperature, determine that the meter over-temperature fault occurs; when the meter temperature is greater than the second set temperature for a continuous period exceeding the set time, determine that the meter over-temperature fault occurs; In-depth diagnosis of impact faults, the specific process includes: A first set change rate and a second set change rate are set, and the voltage signal-time curve is derived to obtain a voltage change rate-time curve; when the voltage change rate is greater than the first set change rate, it is determined that an impact fault occurs; when the voltage change rate is greater than the second set change rate for a period of time greater than the set time, it is determined that an impact fault occurs; In-depth diagnosis of vibration faults, the specific process includes: The vibration signal-time curve is subjected to discrete Fourier transform to obtain the meter vibration signal spectrum diagram, and then the meter vibration signal spectrum diagram is demodulated to obtain a demodulated spectrum. The demodulated spectrum is compared with the fault spectrum to determine whether the electric energy meter has a vibration fault.

2. The intelligent electric energy meter fault alarm system according to claim 1, characterized in that: The vibration faults include excessive load, eddy current vibration of the turntable, loose electromagnetic coil, loose iron core and lack of oil in the meter turntable.

3. The intelligent electric energy meter fault alarm system according to claim 1, characterized in that: It also includes a data acquisition module, which is used to collect the operating data of the smart meter and send it to the data storage and transmission module.

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