阅读说明：本技术 一种智能电能表故障报警系统 (Intelligent electric energy meter fault alarm system ) 是由 李屹 李桃 豆玉华 王堃 王力 陈旭 邓云峰 于 2021-09-01 设计创作，主要内容包括：本发明公开了一种智能电能表故障报警系统,涉及电力仪器仪表技术领域,解决了现有电能表不能故障诊断报警及故障预警的技术问题；系统包括数据采集模块,用于采集智能电表的运行数据并将其发送至数据存储分析模块；数据存储传输模块,用于将存储的运行数据发送至数据分析处理模块；数据分析处理模块,用于对运行数据其进行故障分析并根据故障分析结果生成告警指令,将故障分析结果和告警指令发送至数据存储传输模块存储；指令执行模块,用于执行告警指令。所述数据分析处理模块包括故障诊断单元、数据处理单元及指令生成单元。本发明设计合理,便于智能电能表故障报警。(The invention discloses an intelligent electric energy meter fault alarm system, relates to the technical field of electric instruments and meters, and solves the technical problems that the existing electric energy meter cannot carry out fault diagnosis alarm and fault early warning; the system comprises a data acquisition module, a data storage and analysis module and a data storage and analysis module, wherein the data acquisition module is used for acquiring the operating data of the intelligent electric meter and sending the operating data to the data storage and analysis module; the data storage and transmission module is used for sending the stored operating data to the data analysis and processing module; the data analysis processing module is used for carrying out fault analysis on the operating data, generating an alarm instruction according to a fault analysis result and sending the fault analysis result and the alarm instruction to the data storage and transmission module for storage; and the instruction execution module is used for executing the alarm instruction. The data analysis processing module comprises a fault diagnosis unit, a data processing unit and an instruction generating unit. The intelligent electric energy meter fault alarm system is reasonable in design and convenient for intelligent electric energy meter fault alarm.)

1. The utility model provides an intelligent ammeter fault alarm system which characterized in that includes:

the data storage and transmission module is used for storing the operating data of the intelligent electric energy meter and sending the operating data to the data analysis and processing module; the operation data comprises an ammeter vibration signal, an ammeter temperature signal, a current signal and a voltage signal;

the data analysis processing module is used for carrying out fault analysis on the operating data and generating a fault analysis result and an alarm instruction, and the specific process of generating the fault analysis result and the alarm instruction comprises the following steps:

preprocessing the operation data to generate a preprocessing signal, checking and diagnosing the preprocessing signal, and diagnosing energy consumption faults and branch circuit electricity stealing faults of the electric energy meter; then, carrying out deep diagnosis on the preprocessed signals, and diagnosing over-temperature faults, impact faults, vibration faults and over-current faults of the electric energy meter; then generating a diagnosis result, generating an alarm instruction according to the diagnosis result-alarm instruction mapping, and sending the alarm instruction to an instruction execution module;

and the instruction execution module is used for executing the alarm instruction.

2. The intelligent electric energy meter fault alarm system of claim 1, wherein the operation data is preprocessed, and the specific process comprises:

firstly, generating an operation data-time curve according to operation data, wherein the operation data-time curve comprises an ammeter vibration signal-time curve, an ammeter temperature signal-time curve, a current signal-time curve and a voltage signal-time curve; and generating an incoming line power-time curve, an outgoing line power-time curve, a branch line power-time curve, an incoming line electric energy consumption-time curve, an outgoing line electric energy consumption-time curve and a branch line electric energy consumption-time curve according to the operation data-time curve.

3. The intelligent electric energy meter fault alarm system according to claim 2, wherein the specific process of checking and diagnosing the energy consumption fault of the electric energy meter comprises the following steps:

respectively calculating the distance between an incoming line electric energy consumption-time curve and an outgoing line electric energy consumption-time curve at the same moment in the same coordinate system to generate a distance-time curve, then sampling the distance-time curve to obtain a distance sampling data set and calculate a distance standard deviation, and judging the energy consumption fault of the electric energy meter when the standard deviation is more than or equal to a set threshold value;

the specific process for diagnosing the electricity stealing faults of the branches of the electric energy meter is the same as the process for diagnosing the energy consumption faults of the electric energy meter.

4. The intelligent electric energy meter fault alarm system according to claim 2, wherein the deep diagnosis of the over-temperature fault comprises the following specific processes:

setting a first set temperature and a second set temperature, analyzing an ammeter temperature signal-time curve, and judging that an ammeter overtemperature fault occurs when the ammeter temperature is higher than the first set temperature; and when the continuous time that the temperature of the electric meter is greater than the second set temperature exceeds the set time, judging that the over-temperature fault of the electric meter occurs.

5. The intelligent electric energy meter fault alarm system as claimed in claim 2, wherein the deep diagnosis of the impact fault comprises the following specific processes:

setting a first set change rate and a second set change rate, and deriving a voltage signal-time curve to obtain a voltage change rate-time curve; when the voltage change rate is larger than a first set change rate, judging that an impact fault is generated; and when the time that the voltage change rate is greater than the second set change rate is greater than the set time, judging that the impact fault is generated.

6. The intelligent electric energy meter fault alarm system according to claim 1, wherein the deep diagnosis of the vibration fault comprises the following specific processes:

and obtaining an ammeter vibration signal spectrogram through discrete Fourier transformation of the vibration signal-time curve, demodulating the ammeter vibration signal spectrogram to obtain a demodulation map, comparing the demodulation map with a fault map, and judging whether the electric energy meter has a vibration fault.

7. The intelligent electric energy meter fault alarm system of claim 6, wherein the vibration fault comprises overload, rotating disc eddy current vibration, loose electromagnetic coil, loose iron core and low oil of rotating disc of electric meter.

8. The intelligent electric energy meter fault alarm system as claimed in claim 1, further comprising a data acquisition module for acquiring operation data of the intelligent electric energy meter and sending the operation data to the data storage and transmission module.

Technical Field

The invention belongs to the technical field of electric power instruments and meters, relates to an intelligent ammeter technology, and particularly relates to an intelligent ammeter fault alarm system.

Background

The intelligent electric energy meter is composed of a measuring unit, a data processing unit, a communication unit and the like, and has the functions of electric energy metering, information storage and processing, real-time monitoring, automatic control, information interaction and the like. At present, household fire and personal electric shock accidents happen frequently due to poor power utilization management of power utilization customers. In the prior art, circuits are mostly detected, electricity utilization information of electricity utilization customers is collected, and when current, voltage or other data in the circuits are changed, a protection mechanism in the intelligent electric meter acts to protect the circuits. However, the analysis method is too simple, the circuit protection mechanism is triggered only according to the fact that simple operation data such as voltage and current reach the trigger standard, deep analysis is not conducted on the operation data to judge the fault reason, and after the circuit protection mechanism is triggered, a user does not know the fault reason. Therefore, a fault alarm system of an intelligent electric energy meter is needed to provide services of fault diagnosis alarm and fault early warning.

Disclosure of Invention

The invention provides an intelligent electric energy meter fault alarm system which is used for solving the technical problems that the existing electric energy meter cannot carry out fault diagnosis alarm and fault early warning.

The purpose of the invention can be realized by the following technical scheme:

an intelligent electric energy meter fault alarm system, comprising:

the data storage and transmission module is used for storing the operating data of the intelligent electric energy meter and sending the operating data to the data analysis and processing module; the operation data comprises an ammeter vibration signal, an ammeter temperature signal, a current signal and a voltage signal;

the data analysis processing module is used for carrying out fault analysis on the operating data and generating a fault analysis result and an alarm instruction, and the specific process of generating the fault analysis result and the alarm instruction comprises the following steps:

preprocessing the operation data to generate a preprocessing signal, checking and diagnosing the preprocessing signal, and diagnosing energy consumption faults and branch circuit electricity stealing faults of the electric energy meter; then, carrying out deep diagnosis on the preprocessed signals, and diagnosing over-temperature faults, impact faults, vibration faults and over-current faults of the electric energy meter; then generating a diagnosis result, generating an alarm instruction according to the diagnosis result-alarm instruction mapping, and sending the alarm instruction to an instruction execution module;

and the instruction execution module is used for executing the alarm instruction.

Further, the operation data is preprocessed, and the specific process comprises the following steps:

firstly, generating an operation data-time curve according to operation data, wherein the operation data-time curve comprises an ammeter vibration signal-time curve, an ammeter temperature signal-time curve, a current signal-time curve and a voltage signal-time curve; and generating an incoming line power-time curve, an outgoing line power-time curve, a branch line power-time curve, an incoming line electric energy consumption-time curve, an outgoing line electric energy consumption-time curve and a branch line electric energy consumption-time curve according to the operation data-time curve.

Further, checking and diagnosing the energy consumption fault of the electric energy meter comprises the following specific processes:

respectively calculating the distance between an incoming line electric energy consumption-time curve and an outgoing line electric energy consumption-time curve at the same moment in the same coordinate system to generate a distance-time curve, then sampling the distance-time curve to obtain a distance sampling data set and calculate a distance standard deviation, and judging the energy consumption fault of the electric energy meter when the standard deviation is more than or equal to a set threshold value;

the specific process for diagnosing the electricity stealing faults of the branches of the electric energy meter is the same as the process for diagnosing the energy consumption faults of the electric energy meter.

Further, the deep diagnosis of the over-temperature fault comprises the following specific processes:

setting a first set rate of change and a second set rate of change; setting a first set temperature and a second set temperature, analyzing an ammeter temperature signal-time curve, and judging that an ammeter overtemperature fault occurs when the ammeter temperature is higher than the first set temperature; and when the continuous time that the temperature of the electric meter is greater than the second set temperature exceeds the set time, judging that the over-temperature fault of the electric meter occurs.

Further, the impact fault is deeply diagnosed, and the specific process comprises the following steps:

the voltage signal-time curve is subjected to derivation to obtain a voltage change rate-time curve; when the voltage change rate is larger than a first set change rate, judging that an impact fault is generated; and when the time that the voltage change rate is greater than the second set change rate is greater than the set time, judging that the impact fault is generated.

Further, the deep diagnosis of the vibration fault comprises the following specific processes:

and obtaining an ammeter vibration signal spectrogram through discrete Fourier transformation of the vibration signal-time curve, demodulating the ammeter vibration signal spectrogram to obtain a demodulation map, comparing the demodulation map with a fault map, and judging whether the electric energy meter has a vibration fault.

Further, the vibration faults include overload, vortex vibration of the rotating disc, loosening of the electromagnetic coil, loosening of the iron core and oil shortage of the rotating disc of the electric meter.

And the data acquisition module is used for acquiring the operating data of the intelligent electric meter and sending the operating data to the data storage and transmission module.

Compared with the prior art, the invention has the beneficial effects that:

the method respectively judges the faults of the electric energy meter and the branch circuit electricity stealing faults by checking and diagnosing an incoming line electric energy consumption-time curve, an outgoing line electric energy consumption-time curve and a branch circuit electric energy consumption-time curve; according to the method, different processing modes and fault diagnosis methods are respectively formulated according to an ammeter temperature signal-time curve, a voltage signal-time curve, an ammeter vibration signal-time curve, a branch power-time curve and a branch current-time curve, so that the fault diagnosis requirement of the intelligent ammeter is met. When the electric meter vibration signal is diagnosed, the vibration signal is analyzed by adopting a frequency domain analysis method, and the mechanical fault in the electric meter can be diagnosed by comparing the vibration signal with a fault map; the method can accurately diagnose faults of various aspects of the electric energy meter.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a schematic block diagram of the present invention.

Detailed Description

The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The terminology used herein is for the purpose of describing embodiments and is not intended to be limiting and/or limiting of the present disclosure; it should be noted that the singular forms "a," "an," and "the" include the plural forms as well, unless the context clearly indicates otherwise; also, although the 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.

As shown in fig. 1, the intelligent electric energy meter fault alarm system comprises a data acquisition module, a data storage and analysis module and a data processing module, wherein the data acquisition module is used for acquiring operation data of an intelligent electric energy meter and sending the operation data to the data storage and analysis module;

the operation data comprise ammeter vibration signals, ammeter temperature signals, current signals and voltage signals, the current signals comprise branch current signals and main circuit current signals, and the voltage signals comprise inlet wire voltage signals, outlet wire voltage signals and branch voltage signals. The method specifically comprises the step of collecting corresponding data through a vibration sensor, a temperature sensor, a current sensor and a voltage sensor.

The data storage and transmission module is used for sending the stored operating data to the data analysis and processing module;

the data analysis processing module is used for carrying out fault analysis on the operating data, generating an alarm instruction according to a fault analysis result and sending the fault analysis result and the alarm instruction to the data storage and transmission module for storage;

the data analysis processing module comprises a fault diagnosis unit, a data processing unit and an instruction generating unit. The data processing unit is used for preprocessing the running data, and the specific process comprises the following steps:

preprocessing the operation data to obtain a preprocessing signal, wherein the preprocessing is to make an ammeter vibration signal-time curve, an ammeter temperature signal-time curve, a current signal-time curve and a voltage signal-time curve from an ammeter vibration signal, an ammeter temperature signal, 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 line power-time curve, an outgoing line power-time curve and a branch power-time curve are prepared, so that an incoming line electric energy consumption-time curve, an outgoing line electric energy consumption-time curve and a branch electric energy consumption-time curve can be obtained.

The fault diagnosis unit is used for carrying out fault diagnosis according to the operation data to obtain a fault analysis result; the specific process of the fault diagnosis unit for carrying out fault diagnosis according to the operation data is as follows:

checking and diagnosing a preprocessed signal, wherein the checking and diagnosing preprocessed signal comprises an incoming line electric energy consumption-time curve and an outgoing line electric energy consumption-time curve for checking and diagnosing, and it needs to be stated that the electric energy consumed by the intelligent electric energy meter is considered during the checking and diagnosing, and the electric energy consumed by the intelligent electric energy meter is always consistent under an ideal condition, namely in the same coordinate system, the incoming line electric energy consumption-time curve is obtained by translating the outgoing line electric energy consumption-time curve upwards, but in an actual working process, the electric energy consumed by the intelligent electric energy meter is not always consistent, the electric energy consumed is larger when the current is larger, and the two are set in a solving way; and the setting is to calculate the distance between an incoming line electric energy consumption-time curve and an outgoing line electric energy consumption-time curve to obtain a distance-time curve, and then sample the distance to obtain a distance sampling data set. The sampling frequency can be set according to the actual self, no specific limitation is made, the maximum distance and the minimum distance in the sampling data set are removed, then the standard deviation calculation is carried out on the rest distance sets, when the standard deviation is smaller than a set threshold, the electric energy meter is judged to have no energy consumption fault, and when the standard deviation is larger than or equal to the set threshold, the electric energy meter is judged to have the energy consumption fault;

the checking, diagnosing and preprocessing signals further comprise checking and diagnosing an outgoing line electric energy consumption-time curve and a branch electric energy consumption-time curve, wherein a plurality of branch electric energy consumption-time curves respectively represent the electric energy consumption situation of each branch at the lower end of the electric energy meter, all branch electric energy consumption-time curves at the lower end of the electric energy meter are integrated into a branch comprehensive electric energy consumption-time curve, the branch comprehensive electric energy consumption-time curve and the outgoing line electric energy consumption-time curve are checked and diagnosed, theoretically, the branch comprehensive electric energy consumption-time curve and the outgoing line electric energy consumption-time curve are two coincident curves in the same coordinate system, but the branch comprehensive electric energy consumption is smaller than the outgoing line electric energy consumption in practice, and the solution is to set the branch comprehensive electric energy consumption-time curve and the outgoing line electric energy consumption-time curve, the setting process is consistent with the above. Judging whether the branch circuit has power stealing failure when the standard deviation is smaller than a set threshold value, and judging whether the branch circuit has power stealing failure when the standard deviation is larger than or equal to the set threshold value;

after the diagnosis preprocessing signal is checked, performing preprocessing signal deep diagnosis, including deeply diagnosing an electric meter temperature signal-time curve, setting a first set temperature and a second set temperature, immediately judging the overtemperature fault of the electric meter when the electric meter temperature signal-time curve has a point greater than the first set temperature, obtaining the time continuously greater than the second set temperature through the electric meter temperature signal-time curve when one or more continuous curves in the electric meter temperature signal-time curve exceed the second set temperature but do not reach the first set temperature, judging that the electric energy meter has no overtemperature fault when the time continuously greater than the second set temperature is less than the set time, and judging the overtemperature fault of the electric energy meter when the time continuously greater than the second set temperature is greater than or equal to a set threshold value;

the preprocessing signal deep diagnosis also comprises a deep diagnosis voltage signal-time curve, and the process is as follows: the voltage signal-time curve is derived to obtain a voltage change rate-time curve, it should be noted that, regardless of the incoming line voltage, the outgoing line voltage or the voltage of each branch circuit, the incoming line voltage, the outgoing line voltage or the voltage of each branch circuit should theoretically be a standard voltage during normal operation, such as 220V for household power and 380V for industrial power, but the change of the load of the power grid can bring certain impact to the incoming line voltage, the change of the load on the line can also impact the outgoing line voltage and the voltage of each branch circuit, so that the change of the voltage signal is brought, the general duration is short, and the impact amplitude is small. And setting a fault voltage change rate and a standard voltage change rate, so that when the voltage change rate at a certain moment is greater than a first set change rate, the situation that the impact fault is generated due to overlarge impact is indicated, and when the voltage change rate at a certain moment is less than the first set change rate, the situation that the impact is small is indicated, and the circuit and the electric energy meter are not influenced. And in addition, when the voltage change rates in a set time period exceed the second set change rate, the impact fault is generated due to overlong impact time. When the voltage change rate does not completely exceed the standard voltage change rate in a set time period, the surge time is not enough to generate a fault.

The preprocessing signal depth diagnosis further comprises a depth diagnosis ammeter vibration signal-time curve, the vibration signal-time curve is subjected to discrete Fourier transform to obtain an ammeter vibration signal spectrogram, then the ammeter vibration signal spectrogram is demodulated to obtain a demodulation map, the demodulation process comprises envelope analysis, then the demodulation map is compared and analyzed, and the comparison and analysis is to compare the demodulation map with a corresponding fault map to find a fault map which best meets the demodulation map, so that faults are judged. It should be noted that the failure map is obtained by analyzing the vibration signal before the failure occurs after the failure occurs and by learning through a neural network. It is emphasized here that the data acquisition module also acquires device information of the electric energy meter, including brand, model, date of delivery and date of installation. The vibration faults of the electric energy meter comprise overlarge load, rotary table vortex vibration, looseness of an electromagnetic coil, looseness of an iron core, less oil of a rotary table of the electric energy meter, improper installation position of the rotary table and the like, the metering of the electric energy meter is inaccurate due to long-time vibration, and the service life of the electric energy meter is shortened.

The deep diagnosis preprocessing signal also comprises a deep diagnosis branch power-time curve and a branch current-time curve, the sum of all rated powers of equipment carried by the branch is calculated, the sum of the rated currents of all the equipment is used as the basis for checking and diagnosing the branch power curve and the branch current curve, when the branch power-time curve has a part which continuously exceeds the sum of the rated powers, the duration time of the branch is calculated, when the duration time is greater than a set threshold value, the branch is judged to have the overload fault, when the branch circuit-time curve has a part which continuously exceeds the sum of the rated powers, the duration time of the branch circuit-time curve is calculated, and when the duration time is greater than the set threshold value, the branch is judged to have the overcurrent fault.

The instruction generating unit is used for generating an alarm instruction according to the fault analysis result, and the alarm instruction comprises a brake separating instruction and an alarm instruction.

After the preprocessing signal is deeply diagnosed, a fault analysis result is obtained and sent to an instruction generating unit.

The instruction generating unit stores the mapping of the fault analysis result and the alarm instruction, generates the alarm instruction according to the fault analysis result and sends the alarm instruction to the instruction executing module.

The instruction execution module comprises an audible and visual alarm module and a brake separating module; the sound and light alarm module is used for executing an alarm instruction; the brake separating module is used for executing a brake separating instruction; the instruction execution module also comprises a display screen for displaying the fault analysis result; the alarm instruction comprises a voice broadcast fault analysis result and a suggested action.

The working principle of the invention is as follows: the method acquires the operation data, and then preprocesses the operation data to obtain an ammeter vibration signal-time curve, an ammeter temperature signal-time curve, a current signal-time curve and a voltage signal-time curve, so as to obtain an inlet wire power-time curve, an outlet wire power-time curve, a branch power-time curve, an inlet wire electric energy consumption-time curve, an outlet wire electric energy consumption-time curve and a branch electric energy consumption-time curve. And then, different processing methods are adopted according to the particularity of different models, so that the type of the fault is diagnosed, and a diagnosis and analysis result is obtained.

In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.