CN107422218B - Bad load recognizer and recognition methods - Google Patents
Bad load recognizer and recognition methods Download PDFInfo
- Publication number
- CN107422218B CN107422218B CN201710884387.5A CN201710884387A CN107422218B CN 107422218 B CN107422218 B CN 107422218B CN 201710884387 A CN201710884387 A CN 201710884387A CN 107422218 B CN107422218 B CN 107422218B
- Authority
- CN
- China
- Prior art keywords
- module
- waveform
- sampling
- load
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
- Measurement Of Current Or Voltage (AREA)
Abstract
The invention discloses one of safety utilization of electric power and field of energy-saving technology bad load recognizer and recognition methods, the identifier includes that MCU and electric energy metering module connected to it, memory module, AD sampling module, communication module, relay control and detection module, each module realize data acquisition and processing (DAP) respectively, measure the effects of electricity consumption, storing data, waveform sampling, data communication, state of a control；This method include beginnings, sampling, the sampling of overpower threshold decision, Wave data, waveform separation, phase difference analysis, waveform similarity analysis, electric conductivity value handle, sine wave judge and bad load handle and etc..The present invention is not high to the accuracy of identification of bad load in view of the prior art, and cannot identify the defect of some special bad load equipment, and accuracy of identification is high, reduces erroneous judgement probability, while can recognize special bad load equipment.
Description
Technical field
The present invention relates to safety utilization of electric power and field of energy-saving technology, in particular to a kind of bad load recognizer and
Recognition methods.
Background technique
In recent years, as the continuous expansion of high school scale, number of student steeply rise, many colleges and universities all carry out logistics management
Socialization, at the same time, the report about College Students ' Apartments fire incident are also increasing.Show according to related data this kind of
Fire is used caused by the high-power resistive loads such as immersion heater, Electric stove since student is violating the regulations.To prevent such thing
Therefore generation limit the use of high-power resistive load under the premise of ensuring student's normal electricity consumption, ensure the peace of student's electricity consumption
Full property is a problem to be solved, therefore is of great significance to the research of bad load identification.
Load recognizer currently on the market has 3 kinds:
(1) power identification controller: such identifier is using power as identification parameter, more than the power threshold of default
When, system automatic trip.
(2) bad load recognizer of analogue technique: the advantages of product is that cost is relatively low, and effect is obvious, to general
High-power resistive electrothermal load can identify solve the problems, such as the safety utilization of electric power of students' dormitory substantially substantially.
(3) bad load recognizer of digital technology: using singlechip technology, judges load to active power, idle function
The influence (i.e. to the influence of power factor) of rate, apparent energy, carries out the identification of bad load.
But the accuracy of identification of above-mentioned three kinds of load recognizers is not high, and cannot identify that some special bad loads are set
It is standby, such as current curve is the sinusoidal wave device being truncated, current curve is sine wave and dephased equipment etc..
Summary of the invention
In order to overcome the shortcomings of existing technology, the present invention provides a kind of bad load recognizer and recognition methods.
Technical solution of the present invention is as described below:
On the one hand, a kind of bad load recognizer, which is characterized in that including MCU, electric energy metering module, memory module, AD
Sampling module, communication module and relay control and detection module, it is the electric energy metering module, the communication module, described
Memory module, the AD sampling module and relay control are connect with detection module with the MCU；
The MCU controls each module, and data are acquired and are handled；
The electric energy metering module is acquired electric power data, and measures electricity consumption；
The parameter of the memory module storage current power data, waveform sampling data and user setting；
The AD sampling module carries out the sampling of voltage, current waveform；
The communication module is connect by wired or wireless way with collector, and the communication of server and identifier is completed；
The relay control and the current time of day of detection module real-time detection relay, and control the tripping of relay
With combined floodgate.
According to the present invention of above scheme, which is characterized in that the communication module carries out wire communication by RS-485.
According to the present invention of above scheme, which is characterized in that the communication module is communicated by zigbee communication module, 4G
Module or 470 communication modules carry out wireless communication.
According to the present invention of above scheme, which is characterized in that further include LCD MODULE, the LCD MODULE with
The MCU connection, the LCD MODULE show the failure shape of current parameters of electric power, electricity consumption and current identifier
State.
On the other hand, a kind of recognition methods of bad load recognizer, which comprises the following steps:
Step 1 starts, and carries out the initialization of data；
Wave data sampling before step 2, load start；
Step 3, the judgement of overpower threshold values judge that step power is during Wave data sampling before load starts
It is no to be greater than threshold values set by user, such as if so, the sampling of Wave data before load starts will be stopped, and proceeded to next
Step, if not, then return to step 2；
Wave data samples after step 4, load starting；
Step 5, waveform separation；
Step 6, phase difference analysis, the difference waveform of electric current is compared with voltage waveform, judges whether there is phase
Difference directly carries out in next step, if there is phase difference, carrying out phase difference processing, making its phase difference zero if without phase difference, then
It carries out in next step；
Voltage waveform data and current differential Wave data are carried out waveform similarity analysis by step 7, waveform similarity analysis,
When similarity is in fixed range, it is believed that the load of addition is bad load, will be directed into bad load processing, otherwise
It enters in next step；
Step 8, electric conductivity value processing carry out electric conductivity value processing in voltage waveform and current differential waveform dissmilarity；
Step 9 is truncated sine wave judgement, by the processing of electric conductivity value, if occurring in one section of continuous time point in result
Electric conductivity value approach be 0, the electric conductivity value in one section of continuous time point levels off to equal, then it is assumed that the difference waveform of electric current is one
The sine wave that part is truncated, will be directed into bad load processing step, on the contrary then resampling Wave data, under waiting
Changed power；
Step 10, bad load processing carry out identifier according to user setting after detecting that bad load accesses power grid
Alarm or tripping, then resampling Wave data, waits changed power next time.
According to the present invention of above scheme, which is characterized in that the step 2 includes the sampling of voltage and current waveform.
According to the present invention of above scheme, which is characterized in that in the step 5, Wave data is adopted after loading starting
Sample is completed, and the current waveform data using load starting front and back is subtracted each other to obtain the difference waveform of electric current, to complete waveform
Separation.
According to the present invention of above scheme, which is characterized in that in the step 8, by voltage waveform data and current difference
Value Wave data carries out obtaining electric conductivity value Rn by a division operation.
According to the present invention of above scheme, the beneficial effect is that, the present invention can not only realize the basic metering function of ammeter
The monitoring of energy and parameters of electric power.The identification to bad load can also be met, accuracy of identification is high, erroneous judgement probability is reduced,
It also can recognize simultaneously and be directed to existing bad load identification technology, and the equipment to bad load remodeling created is (such as controllable
Silicon socket)；The present invention also support teledata copy set and remote relay control, utilize power consumption management.
Detailed description of the invention
Fig. 1 is the structural diagram of the present invention.
Fig. 2 is identification process figure of the invention.
Specific embodiment
With reference to the accompanying drawing and the present invention is further described in embodiment:
As shown in Figure 1, bad load recognizer, including MCU, electric energy metering module, LCD MODULE, memory module,
AD sampling module, communication module and relay control and detection module, electric energy metering module, LCD MODULE, communication mould
Block, memory module, AD sampling module and relay control are connect with detection module with MCU.
Wherein: MCU is controlled with memory module, communication module and relay and is bi-directionally connected with detection module, MCU and liquid crystal
Display module unidirectionally connects, and electric energy metering module and AD sampling module are unidirectionally connect with MCU.
MCU:
MCU is nucleus module, is controlled each module, and data are acquired and are handled.
Electric energy metering module:
Electric energy metering module is acquired electric power data (voltage, electric current, power etc.), and measures electricity consumption.
LCD MODULE:
LCD MODULE shows the malfunction of current parameters of electric power, electricity consumption and current identifier.
Memory module:
Memory module stores the parameter of current power data, waveform sampling data and user setting.
AD sampling module:
AD sampling module carries out the sampling of voltage, current waveform using three road ∑s-Δ ADC.
Communication module:
Communication module is connect by wired or wireless way with collector, and the communication of server and identifier is completed, wherein
Hardware supported RS-485 is communicated in wired mode, and zigbee communication module, 4G communication module, 470 communications are supported in wireless mode
The modules such as module.
Server is mainly to carry out copying for data to bad load recognizer to set and the long-range control of relay；Acquisition
Device connects bad load recognizer and remote server, plays the role of data connection.
Relay control and detection module:
Tripping and combined floodgate of the relay control with detection module control relay, while passing through relay real-time detection relay
The current time of day of device.
As shown in Fig. 2, a kind of recognition methods of bad load recognizer, comprising the following steps:
1, start: carrying out the initialization of data.
2, Wave data sampling before load starts: after system starting, start sampled voltage, current waveform data.
3, overpower threshold values judges: during Wave data sampling before load starts, judging whether step power is big
Threshold values set by user, such as if so, the sampling of Wave data before load starts will be stopped, and proceeded in next step, if
It is invalid, then return to step 2.
4, Wave data samples after load starting: after step power is greater than threshold values, by Wave data after triggering load starting
Sampling.
5, waveform separates: Wave data sampling is completed after loading starting, utilizes the current wave figurate number of load starting front and back
According to being subtracted each other to obtain the difference waveform of electric current, to complete waveform separation.
6, phase difference is analyzed: the difference waveform of electric current is compared with voltage waveform, judges whether there is phase difference, if
There is no phase difference then directly to carry out in next step, if there is phase difference, carrying out phase difference processing, making its phase difference zero, then carry out
In next step.
7, waveform similarity analysis: by voltage waveform data and current differential Wave data, waveform similarity analysis is carried out, phase is worked as
When like degree in fixed range, it is believed that the load of addition is bad load, will be directed into bad load processing, otherwise enters
To in next step.In the present embodiment, the fixed range of similarity is 0.998-1.
8, electric conductivity value is handled: in voltage waveform and current differential waveform dissmilarity, electric conductivity value processing is carried out, specifically,
Voltage waveform data and current differential Wave data are carried out by a division operation (AD electric current 1/AD voltage 1.AD electric current
N/AD voltage n), acquired results R1......Rn.
9, it is truncated sine wave judgement: by the processing of electric conductivity value, if occurring in one section of continuous time point in result
RI......RJ (I >=1, J≤n) approach is 0, and RK......RM (K >=1, the M≤n) approach in another section of continuous time point
In equal, then it is assumed that the difference waveform of electric current is the sine wave that a part is truncated, and will be directed into bad load processing
Step, on the contrary then resampling Wave data wait changed power next time.
10, bad load is handled: after detecting that bad load accesses power grid, carrying out identifier alarm according to user setting
Or tripping, then resampling Wave data, waits changed power next time.
It should be understood that for those of ordinary skills, it can be modified or changed according to the above description,
And all these modifications and variations should all belong to the protection domain of appended claims of the present invention.
Illustrative description has been carried out to the invention patent above in conjunction with attached drawing, it is clear that the realization of the invention patent not by
The limitation of aforesaid way, if the method concept of the invention patent and the various improvement of technical solution progress are used, or without
It improves and the conception and technical scheme of the invention patent is directly applied into other occasions, be within the scope of the invention.
Claims (7)
1. the recognition methods of bad load recognizer, which comprises the following steps:
Step 1 starts, and carries out the initialization of data；
Wave data sampling before step 2, load start；
Step 3, the judgement of overpower threshold values judge whether step power is big during Wave data sampling before load starts
Threshold values set by user, such as if so, the sampling of Wave data before load starts will be stopped, and proceeded in next step, if
It is invalid, then return to step 2；
Wave data samples after step 4, load starting；
Step 5, waveform separation, Wave data sampling is completed after loading starting, utilizes the current wave figurate number of load starting front and back
According to being subtracted each other to obtain the difference waveform of electric current, to complete waveform separation；
Step 6, phase difference analysis, the difference waveform of electric current is compared with voltage waveform, judges whether there is phase difference, if
There is no phase difference then directly to carry out in next step, if there is phase difference, carrying out phase difference processing, making its phase difference zero, then carry out
In next step；
Voltage waveform data and current differential Wave data are carried out waveform similarity analysis, work as phase by step 7, waveform similarity analysis
When like degree in fixed range, it is believed that the load of addition is bad load, will be directed into bad load processing, otherwise enters
To in next step；
Step 8, electric conductivity value processing carry out electric conductivity value processing in voltage waveform and current differential waveform dissmilarity；
Step 9 is truncated sine wave judgement, by the processing of electric conductivity value, if occurring the electricity in one section of continuous time point in result
Value approach is led as 0, and the electric conductivity value in another section of continuous time point level off to it is equal, then it is assumed that the difference waveform of electric current is one
The sine wave that part is truncated, will be directed into bad load processing step, on the contrary then resampling Wave data, under waiting
Changed power；
Step 10, bad load processing carry out identifier alarm according to user setting after detecting that bad load accesses power grid
Or tripping, then resampling Wave data, waits changed power next time.
2. the recognition methods of bad load recognizer according to claim 1, which is characterized in that the step 2 includes electricity
The sampling of pressure and current waveform.
3. the recognition methods of bad load recognizer according to claim 1, which is characterized in that, will in the step 8
Voltage waveform data and current differential Wave data carry out obtaining electric conductivity value Rn by a division operation.
4. the recognition methods of bad load recognizer according to claim 1, which is characterized in that bad load recognizer packet
MCU, electric energy metering module, memory module, AD sampling module, communication module and relay control and detection module are included, it is described
Electric energy metering module, the communication module, the memory module, the AD sampling module and relay control and detection
Module is connect with the MCU；
The MCU controls each module, and data are acquired and are handled；
The electric energy metering module is acquired electric power data, and measures electricity consumption；
The parameter of the memory module storage current power data, waveform sampling data and user setting；
The AD sampling module carries out the sampling of voltage, current waveform；
The communication module is connect by wired or wireless way with collector, and the communication of server and identifier is completed；
The relay control and the current time of day of detection module real-time detection relay, and control the tripping and conjunction of relay
Lock.
5. the recognition methods of bad load recognizer according to claim 4, which is characterized in that the communication module passes through
RS-485 carries out wire communication.
6. the recognition methods of bad load recognizer according to claim 4, which is characterized in that the communication module passes through
Zigbee communication module, 4G communication module or 470 communication modules carry out wireless communication.
7. the recognition methods of bad load recognizer according to claim 4, which is characterized in that further include liquid crystal display mode
Block, the LCD MODULE are connect with the MCU, the LCD MODULE show current parameters of electric power, electricity consumption with
And the malfunction of current identifier.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710884387.5A CN107422218B (en) | 2017-09-26 | 2017-09-26 | Bad load recognizer and recognition methods |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710884387.5A CN107422218B (en) | 2017-09-26 | 2017-09-26 | Bad load recognizer and recognition methods |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107422218A CN107422218A (en) | 2017-12-01 |
| CN107422218B true CN107422218B (en) | 2019-11-29 |
Family
ID=60436092
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710884387.5A Active CN107422218B (en) | 2017-09-26 | 2017-09-26 | Bad load recognizer and recognition methods |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107422218B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108152552A (en) * | 2017-12-29 | 2018-06-12 | 江苏林洋能源股份有限公司 | A kind of electricity anti-theft method for precisely capture Dimmer interference |
| CN108828345B (en) * | 2018-04-17 | 2020-06-30 | 武汉阿帕科技有限公司 | Method and system for identifying silicon controlled load in power line |
| CN110967585B (en) * | 2019-12-20 | 2022-03-15 | 武汉盛帆电子股份有限公司 | Malignant load identification method and device |
| CN112611931A (en) * | 2020-12-23 | 2021-04-06 | 南方电网电力科技股份有限公司 | Method, system and storage medium for identifying and processing malignant load based on discrete waveform |
| CN114089015A (en) * | 2021-10-25 | 2022-02-25 | 深圳市移动力量科技有限公司 | Detection method and device for illegal electrical appliance and readable storage medium |
| CN115825634B (en) * | 2023-02-16 | 2023-05-26 | 上海红檀智能科技有限公司 | Malignant load identification method based on load complex impedance characteristics |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201166677Y (en) * | 2008-03-26 | 2008-12-17 | 广州集超电子有限公司 | Electric energy meter for recognizing carrier by resistance load |
| CN203299266U (en) * | 2013-06-27 | 2013-11-20 | 常州瑞信电子科技有限公司 | Micro programming load recognizer |
| CN204330955U (en) * | 2014-12-31 | 2015-05-13 | 厦门大学嘉庚学院 | Circuit load intelligent identification device |
| CN104655922A (en) * | 2013-11-20 | 2015-05-27 | 江南大学 | Vicious load judging system based on voltage and current sampling data |
| CN105186693A (en) * | 2015-09-28 | 2015-12-23 | 南方电网科学研究院有限责任公司 | Non-invasive electrical load identification system and method |
| CN105529823A (en) * | 2014-09-28 | 2016-04-27 | 杭州久笛电子科技有限公司 | Terminals and terminal building system based on electric load management intelligent recognition system |
| CN105913005A (en) * | 2016-04-08 | 2016-08-31 | 湖南工业大学 | Electric appliance load type intelligent identification method and device |
-
2017
- 2017-09-26 CN CN201710884387.5A patent/CN107422218B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201166677Y (en) * | 2008-03-26 | 2008-12-17 | 广州集超电子有限公司 | Electric energy meter for recognizing carrier by resistance load |
| CN203299266U (en) * | 2013-06-27 | 2013-11-20 | 常州瑞信电子科技有限公司 | Micro programming load recognizer |
| CN104655922A (en) * | 2013-11-20 | 2015-05-27 | 江南大学 | Vicious load judging system based on voltage and current sampling data |
| CN105529823A (en) * | 2014-09-28 | 2016-04-27 | 杭州久笛电子科技有限公司 | Terminals and terminal building system based on electric load management intelligent recognition system |
| CN204330955U (en) * | 2014-12-31 | 2015-05-13 | 厦门大学嘉庚学院 | Circuit load intelligent identification device |
| CN105186693A (en) * | 2015-09-28 | 2015-12-23 | 南方电网科学研究院有限责任公司 | Non-invasive electrical load identification system and method |
| CN105913005A (en) * | 2016-04-08 | 2016-08-31 | 湖南工业大学 | Electric appliance load type intelligent identification method and device |
Non-Patent Citations (1)
| Title |
|---|
| 恶性负载智能识别方法研究;赵万欣 等;《科技广场》;20140331(第3期);48-50 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107422218A (en) | 2017-12-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107422218B (en) | Bad load recognizer and recognition methods | |
| CN201532590U (en) | Temperature and humidity controller | |
| CN109116085B (en) | Automobile quiescent current monitoring system and method | |
| CN104965147B (en) | Low-voltage customer electric energy meter is visited one house after another detecting system and detection method | |
| CN110412347B (en) | Electricity stealing behavior identification method and device based on non-invasive load monitoring | |
| CN102279326A (en) | Electrical appliance recognition method and household user carbon emission metering system applying same | |
| CN101533043A (en) | Test system for vehicle quiescent current | |
| CN211208607U (en) | Monitoring device for battery management system and battery management system | |
| CN111983546B (en) | Ammeter detection configuration device and method | |
| CN209417148U (en) | A kind of multifunction electric meter having function expanding module self-identifying technology | |
| CN102043106B (en) | Detection method ofdirect current charging pile field detection system | |
| CN205388615U (en) | Novel it is anti -electricity -theft device | |
| CN203849400U (en) | Intelligent ammeter carrier wave communication module dynamic power consumption detector | |
| CN107203152B (en) | A kind of energy-saving device and the weight testing method that economizes on electricity | |
| CN108663568A (en) | Solar module debugging and testing device and testing method thereof | |
| CN106245041B (en) | Cathode protection remote monitoring terminal based on Internet of things and control method thereof | |
| CN204882853U (en) | Electric energy meter pressure resistance test installation | |
| CN107765118A (en) | A kind of test device and method of light-operated converter valve recovery protection firing unit | |
| CN201813072U (en) | Wireless sensor network measure and control device for prefabricated substations | |
| CN206224183U (en) | A kind of Internet of Things gas meter controller based on the GPRS communication technologys | |
| CN109270342A (en) | Multifunctional electric meter with external expansion module self-identifying technology | |
| CN202886581U (en) | Line fault indicator detecting system | |
| CN102290864A (en) | Method and device for implementing virtual load management terminal | |
| CN109633426A (en) | Switch detection method | |
| CN205736039U (en) | The safety control system of 3D printer |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |