CN102279326A - Electrical appliance recognition method and household user carbon emission metering system applying same - Google Patents
Electrical appliance recognition method and household user carbon emission metering system applying same Download PDFInfo
- Publication number
- CN102279326A CN102279326A CN2011101013984A CN201110101398A CN102279326A CN 102279326 A CN102279326 A CN 102279326A CN 2011101013984 A CN2011101013984 A CN 2011101013984A CN 201110101398 A CN201110101398 A CN 201110101398A CN 102279326 A CN102279326 A CN 102279326A
- Authority
- CN
- China
- Prior art keywords
- electrical equipment
- module
- current
- current characteristic
- electrical appliance
- 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.)
- Granted
Links
Images
Landscapes
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention discloses an electrical appliance recognition method. The method is characterized in that: an electrical appliance is recognized according to a matching result of current characteristic parameter values. The invention further provides a household user carbon emission metering system applying the method. The metering system comprises a bus voltage sampling module, a bus current detection module, a phase detection module, a signal conditioning module, an amplitude detection module, an electrical appliance recognition module and a carbon metering module, wherein the bus voltage sampling module is connected with the input ends of the phase detection module, the signal conditioning module and the amplitude detection module respectively; the bus current detection module is connected with the input end of the signal conditioning module; the output ends of the phase detection module, the signal conditioning module and the amplitude detection module are connected with the input end of the electrical appliance recognition module; and the output end of the electrical appliance recognition module is connected with the carbon metering module. In the system, carbon emission is metered on the basis of accurate recognition of the electrical appliance, so that people are helped to set up the consciousness of energy saving, emission reduction and low-carbon consumption and correct incorrect power utilization habits.
Description
Technical field
The present invention relates to electrical load identification of a kind of family and carbon emission monitoring and metering system, particularly a kind of electrical equipment recognition methods and use domestic consumer's carbon emission metering system of this method.
Background technology
Along with development of electronic technology, the multifunctional electric energy meter that with the single-chip microcomputer is core is popularized gradually, this class electric energy meter has higher measuring accuracy and arithmetic speed, adopt charactron or LCDs to show, can to each month electric energy consumption carry out record, preserve a maximum demand of electric energy, parameter etc. is set.But this only is confined to the power consumption of the whole electrical appliances of metering user, can not be accurate to each electrical appliance.And this class ammeter is the metering and the statistics of only carrying out electric energy according to the amplitude of the electric current and voltage of electrical network on measuring method, thereby function ratio is more single.The communication capacity of above-mentioned ammeter network is very poor or do not possess network communications capability, is difficult to realize communication and data sync with the network host computer.Existing electrical appliance recognition technology only can be carried out pilot relay power down process (patent No. 200620127335.0 has the electronic electric energy meter of electrical appliance recognition function) when the user has powerful electrical appliance to load; Another patent (201010250565.7 1 kinds of methods of utilizing the intelligent grid regulating and controlling carbon emission of users of the patent No.) has proposed a kind of identification user power supply composition and has come from pollution character power supply or cleaning properties power supply, and analyze energy consumption and carbon emission amount, do not realize the function of single electrical appliance identification in the existing technology.
If detect the power consumption of each electrical appliance, existing universal method is at the power import of each household electrical appliance voltage, current sensor to be installed, and carries out electrical measurement according to the data of collecting again.Though can reach corresponding target like this, on the high side, complexity is installed, feasibility is relatively poor.
Under existing conditions, the domestic consumer lacks the consciousness of energy-saving and emission-reduction and low-carbon (LC) consumption, seldom or does not at all consider the additional carbon emission amount that some electrical appliances in use produce, and so just may cause excessive carbon emission.Because the misleading of lowly adding some aspect of entire society's low-carbon (LC) consumption consciousness can cause it to continue to use some irrational life styles unconsciously, has destroyed the construction of entire environment in unconscious.
Summary of the invention
The object of the invention is to provide a kind of electrical equipment recognition methods, can accurately identify the electrical equipment that is using.
Another object of the present invention is to provides domestic consumer's carbon emission metering system of using said method, at first identifies the electrical equipment that is using, and measures the energy consumption and the carbon emission amount of this electrical equipment, and total system is easy for installation, simple in structure.
The technical solution adopted for the present invention to solve the technical problems is:
A kind of electrical equipment recognition methods and use domestic consumer's carbon emission metering system of this method: comprise the busbar voltage sampling module, bus current detection module, phase detecting module, the signal condition module, amplitude detection module, power module, human-computer interaction module, electrical equipment identification module, carbon metering module.
The busbar voltage sampling module is by voltage sensor (voltage sensor can be voltage transformer (VT), voltage hall sensor etc.), the bus current detection module is to convert the high-voltage large current of grid side to voltage signal by current sensor (current sensor can be current transformer, current Hall sensor, shunt etc.), send phase detecting module, signal condition module and amplitude detection module to, and realize the isolation of electric equipment compartment.
Phase detecting module comprises impact damper and hysteresis comparator, and the zero crossing of detection signal is for sampling and the extraction of characteristic parameter provide time reference; The signal condition module comprises buffer circuit, signal gain/decay part, and signal overlapping portion and frequency overlapped-resistable filter are nursed one's health suitable scope with sampled signal; The amplitude detection module comprises impact damper and peak value retaining part, the maximal value of detection signal.
Power module adopts the AC/DC switch transducer to provide electric energy for total system, with respect to the linear quantizer high efficiency.
Electrical equipment identification module and phase detecting module, the signal condition module, the amplitude detection module links to each other with human-computer interaction module, and link to each other with the carbon metering module by serial communication, by analysis and calculating to current and voltage data, blur according to the characteristic parameter of electrical appliance and to distinguish, realized the identification of the electrical appliance that the domestic consumer is using, and can write down the power consumption of each electrical appliance, and realize that superpower is handled and the Power Limitation of electrical appliance.Serial communication adopts the network addressing pattern, realizes communicating by letter of single serial ports and computer, carbon metering module.
The characteristic parameter of the electrical appliance that above-mentioned electrical equipment identification module detected comprises current peak, electric current average, current effective value, current first harmonics, current harmonics amplitude, current harmonics phase place, electrical appliance applied power, active power, electrical appliance power consumption curve, current harmonics length etc.
The electrical equipment recognition methods that above-mentioned electrical equipment identification module is adopted is a kind of fuzzy diagnosis algorithm based on mark.Matching degree according to corresponding parameter in the characteristic parameter of electrical appliance and the database obtains corresponding score value, and score value and qualifying score value relatively determine recognition result.
Above-mentioned property data base has the characteristic information of family's all types electrical appliance, and property data base can change according to the variation Real-time and Dynamic of domestic electric appliances.
The dynamic change of above-mentioned characteristic refers to according to electrical appliance characteristic parameter score value in each domestic electric appliances situation real-time update database and be written into new electrical appliance data when detecting new electrical appliance.
The liquid-crystal controller that human-computer interaction module 1 comprises can realize that the interface display content of touch LCD screen, touch sensible processing reach the communication of discerning master controller with electrical appliance.The interface display content of liquid crystal comprises the statistics of total electrical appliance energy consumption of family, the detail statistics of the single electrical appliance of electrical appliance and family that family uses in real time.
The carbon metering module adopts the serial communication mode to link to each other with human-computer interaction module 2 with the electrical equipment identification module, and is furnished with the internet communication interface.According to certain converting standard the power consumption of electrical appliance is converted to corresponding carbon value, realizes abstract carbon emission process is quantized, home energy source consumption is adjusted in monitoring.The touch LCD display that comprises by human-computer interaction module 2 presents the result of current carbon emission statistics in the mode of figure, provides Useful Information with the information of form.Tool is adjusted monitoring, individual's inquiry, and three functions of intelligence suggestion can be analyzed the direction that family consumes the carbon amount, and propose conductive suggestion.
Technique effect of the present invention is embodied in: adopt non-invasion monitoring method, need not at each electrical appliance power supply inlet pick-up unit, and just the voltage and current sensor is installed at the total upstream end of user's electric wire, gather voltage, current data in real time, analyze with software, to determine the power consumption of each household electrical appliance, drop into lowlyer, and monitoring device can be caught each information that changes constantly of electric load incessantly.Characteristic parameter according to electrical appliance carries out fuzzy diagnosis, has realized the identification of the electrical appliance that the domestic consumer is using, and writes down the power consumption of each electrical appliance, and can realize that superpower is handled and the Power Limitation of electrical appliance.Simultaneously data are sent to the carbon metering module, according to certain conversion standard, the consumption of electrical appliance is converted to corresponding carbon value write down and handle, help people to establish the consciousness of energy-saving and emission-reduction and low-carbon (LC) consumption, correct incorrect consumption habit, for environment is made the own share contribution.
Description of drawings
Fig. 1 is an one-piece construction schematic diagram of the present invention.
Fig. 2 is the bus current detection module and the signal condition module circuit diagram of an example of the present invention.
Fig. 3 is busbar voltage sampling module, phase detecting module, signal condition module, the amplitude detection module circuit diagram of an example of the present invention.
Fig. 4 is the power module circuitry figure of an example of the present invention.
Fig. 5 is processor (MCU) circuit diagram of the electrical equipment identification module of an example of the present invention.
Fig. 6 is the software flow pattern of the electrical equipment identification of an example of the present invention.
Fig. 7 is the obfuscation marking principle of an example of the present invention: the synoptic diagram that concerns scoring method based on the error linguistic variable.
Fig. 8 is the electrical equipment recognition methods process flow diagram of an example of the present invention.
Embodiment
Provide an embodiment below in conjunction with accompanying drawing:
As shown in Figure 1, a kind of electrical equipment recognition methods and use domestic consumer's carbon emission metering system of this method: comprise the busbar voltage sampling module, the bus current detection module, phase detecting module, signal condition module, amplitude detection module, power module, human-computer interaction module 1 and 2, electrical equipment identification module, carbon metering module.
The busbar voltage sampling module is by voltage sensor (voltage sensor can be voltage transformer (VT), voltage hall sensor etc.), the bus current detection module is to convert the high-voltage large current of grid side to low-voltage little electric current by current sensor (current sensor can be current transformer, current Hall sensor, shunt etc.), send phase detecting module, signal condition module and amplitude detection module to, and realize the isolation of electric equipment compartment.
As shown in Figure 2, this example current sensor adopts current closed-loop Hall element CSM010SY, and the primary current measurement range is-20A one 20A, and the secondary rated output voltage is 4V, and the linearity is less than 0.1%, and precision is less than 0.7%.The back level is a gain/attenuation two-way modulate circuit, employing has ultralow skew, low input bias current, low maladjustment voltage drift, overstable amplifier op07, assurance output signal accuracy optimum becomes voltage signal to give the electrical equipment identification module the big current conversion on the bus.
As shown in Figure 3, this example voltages sensor adopts voltage transformer (VT) TVA1421-01, and rated current is 6mA/6mA, and nonlinearity is less than 0.2%.Through after impact damper, sluggish zero-crossing comparator, the amplitude detector and behind the corresponding modulate circuit, become voltage signal to give the electrical equipment identification module the big voltage transitions on the subscriber's drop.
Phase detecting module is used to comprise impact damper and hysteresis comparator, and the zero crossing of detection signal is for sampling and the extraction of characteristic parameter provide time reference; The signal condition module comprises buffer circuit, signal gain/decay part, and signal overlapping portion and frequency overlapped-resistable filter are nursed one's health suitable scope with sampled signal; The amplitude detection module comprises impact damper and peak value retaining part, is used for the maximal value of detection signal.
As shown in Figure 4, adopt LH10-10A15 in the power module respectively, the AC/DC switch transducer; LM2576, the DC-DC switch converters; AS1117, linear DC transducer are the entire circuit power supply, have both guaranteed that conversion efficiency was by the stability that has guaranteed power supply.
As shown in Figure 5, electrical equipment identification module main control chip adopts ADuC7026, integrated 1MSPS in the single-chip, 12, the data acquisition system (DAS) of hyperchannel High Performance ADC, kernel are ARM7TDMI, and it is 16/32 RISC machines, and its peak performance peak value is up to 41MIPS.Chip integration becomes to have SRAM and the non-volatile Flash/EE storer of 62KB of 8KB.Can finish the identification of electrical appliance easily based on the system of this chip research and development, electrical measurement, the transmission of data, work such as incident management, the precision high reliability is strong.Human-computer interaction module 1 adopts 5.7 cun lcd touch display screens, makes the demonstration of data more directly perceived, and it is more convenient to operate.
Figure 6 shows that electrical equipment identification workflow diagram.12 ADC that at first use the last chip of ADuC7026 to carry sample to voltage and current signal.In the data sampling stage, in order to make system when operation, data do not get muddled, and can only make system carve image data in due course.In data handling procedure, data sampling is need be forbidden.Yet, keeping certain consistance in order to guarantee each data handling procedure, must have benchmark the zero hour of sampling.Because native system has been done zero passage detection to line voltage, voltage just passing zero moment provides possibility for data sampling.Based on above analysis, whether the concrete grammar of implementation data sampling: setting up zone bit Data hold to be used to refer to data needs to keep if being, putting 1 system thinks and needs to keep, it occurs over just the moment that data are adopted full 256 points, put 0 think the sampling can carry out sometime, it occurs over just the moment that data processing finishes; Whether set up zone bit AD enable to be used to refer to the AD sampling instant and arrive, putting 1, occur over just Data hold, putting 0, to occur in Data hold be moment of 1 if being 0 and moment of arriving constantly of voltage zero-cross.For satisfying under the 50Hz mains frequency, the demand of 256 points of one-period sampling has been set the timer of a 20000/256us.It is poor after sampling is finished this sampled data and last sampled data to be done, draw this sampled data of newly-increased electrical appliance, then sampled data is extracted corresponding characteristic parameter, simultaneously the data that sample are carried out the FFT conversion, extract corresponding characteristic parameter once more.This example makes the characteristic parameter of electrical appliance comprise current peak, electric current average, current effective value, current first harmonics, current harmonics amplitude, current harmonics phase place, electrical appliance active power, current harmonics length.Current peak, electric current average are just handled and can be accessed current data in real time when sampling.And characteristic parameters such as current effective value, first-harmonic can obtain after Fourier FFT conversion.After the FFT conversion, resulting data are not normalized as yet, in order to guarantee the consistance of characteristic parameter in access procedure, data need be carried out normalization.Normalized criterion is, is 100 with the fundamental voltage amplitude component, the corresponding geometric ratio adjustment of other harmonic componentss.For normalization data can be restored, also need to store the power information of each electrical appliance.Then, make comparison according to relevant parameter in these parameters and the database again, in order to reach the purpose of electrical appliance identification, what the employing of this example was shown in Figure 7 concerns scoring method based on the error linguistic variable.At first carry out fuzzy algorithm relatively at the analog value in a certain characteristic parameter and the existing database, if eigenwert and existing value coupling are very good, then provide a very high score value, the mark of beating along with the decline of matching degree also reduces accordingly.Then, at the recognition result of every kind of characteristic parameter obfuscation, corresponding matching factor is arranged all, matching factor multiply by this parameter and occupies score value, can obtain the score of this parameter.At last, with the score addition of all characteristic parameters, promptly obtain the coupling score value of this electrical appliance.For every kind in database electrical appliance, all can obtain a corresponding score value, maximum score value and qualifying score value determine relatively whether electrical appliance identification is successful.If maximum score value has exceeded definition and ruling, think that then system's electrical equipment discerns successfully, the result is and obtains the pairing electrical appliance of largest score; If maximum score value does not surpass and ruling, then think still not have this kind electrical appliance in the database, need be for further processing.This example is not limited to this with minimum the match is successful the requirement in qualifying score value location, can adjust according to test of many times result's recognition accuracy.
Figure 8 shows that the process flow diagram of electrical equipment identification.At first judge have electrical appliance to open or close according to the variation of the power of house lead in end, if power is constant, then before one-time detection recognition result constantly be current recognition result; Further, can verify recognition result, promptly the reference current characteristic ginseng value of each electrical equipment in the current recognition result is done and, itself and the current current characteristic parameter value that extracts are compared, if comparative result satisfies successfully requirement of minimum identification, then discern successfully, otherwise recognition failures.Minimum identification successfully requires to determine according to the accuracy rate of test result repeatedly.Because opening identification and closing identification of electrical appliance is two similar processes, be identified as example explanation identifying there to be electrical appliance to open below:
Beginning to detect electric wire house lead in end power increases, illustrated that electrical appliance opens, to the electrical appliance opened carry out the extraction of characteristic parameter according to the extraction characteristic parameter method of above explanation this moment, earlier with database in the relevant parameter of single electrical appliance compare, take above describedly to concern that based on the error linguistic variable scoring method is to the electrical appliance scoring of being correlated with.In order to enumerate the example of a marking below the explanation more clearly:
The reference current harmonic wave relevant information of table 1 display
As shown in table 1, be the reference current harmonic wave relevant information of display in the database of an example of the present invention.Harm_length is total harmonic length; Harm_num is corresponding overtone order; FFT_R is the imaginary part of this subharmonic after the FFT conversion; FFT_I is the real part of this subharmonic after the FFT conversion.
The detected new use electric current harmonic wave correlation parameter of table 2
Recognize a new electrical appliance that inserts, make comparisons with each electrical appliance relevant parameter of database storing respectively, provide mark.As shown in table 2, be the relevant parameter of the electrical appliance current harmonics that newly recognizes of an example of the present invention, here be example explanation marking process with this parameter, the total weight value of current harmonics is 0.8,80 minutes in the centesimal system just, and the weights of harmonic length are 0.3, just the 80*0.3=24 branch; The distribution weights of each harmonic wave serve as with reference to distributing with the harmonic parameters in the database, make comparisons such as this and the display in the database, the weights that then each harmonic wave is assigned to are 0.7/6=0.117, again the relevant parameter of the electrical appliance that newly recognizes is compared with it and draw score value, all the score value additions of this parameter, can draw the score value addition of all parameters as following table more at last:
Table 3 newly makes electrical appliance marking table
The mark beaten of electric fan is the highest as can be known by table 3, is 90 minutes, and remaining mark does not all have to pass, and should newly insert electrical appliance as can be known and be identified as electric fan.The relevant parameters such as power of while this electrical appliance of opening entry, above-mentioned single electrical appliance identifying is the phase one of identification.If all divide number average to fail then recognition failures, change the subordinate phase of identification over to.
The subordinate phase of identification: at first analyze the electrical appliance data message that collects, each electrical appliance reference record in the database is read, power information by each electrical appliance and harmonic information are carried out the permutation and combination between the different electrical appliance parameters, with the electrical appliance harmonic length is preferential combination principle, according to electrical appliance from less to more, draw the combination parameter of different electrical appliances.In fact, the anabolic process of a plurality of electrical appliances, a process of separating the multidimensional system of linear equations exactly.Afterwards, re-using similar single electrical appliance recognition methods discerns a plurality of electrical appliances of opening simultaneously.If discern successfully, the parameters such as power of opening entry electrical appliance, and show.If all divide number average to fail then recognition failures, change the next stage of identification over to.
The phase III of identification: above-mentioned identification is all unsuccessful, do not store the characteristic parameter of this new access electrical appliance in the database of descriptions, this moment can will be dynamically will this new electrical appliance characteristic parameter be loaded into database, and point out the name of importing this electrical appliance, so far entire identification process finishes.
In the identifying, because external interference has certain false recognition rate.Be the mistake identification of anti-locking system, even without new electrical appliance connecting system again, this moment, system still was in the real-time verification state.In this state, the work that system need do is: whether checking electrical appliance recognition result is correct, verification method is that characteristic information and real-time information after recognition result is superposeed are relatively fuzzy, obtain recognition result, if recognition result is incorrect, then recognition result is removed, all electrical appliances are discerned again, change the above-mentioned phase one over to, if correct, then continue to handle; Then, upgrade the weights of database feature parameter by real time data, so that more there is localized feature in system, the process of characteristic parameter weights in the new database more, actual is the maximized process of recognition result score value that makes correct electrical appliance; At last, send the electrical appliance data to computer and home client.
Table 4 electrical appliance energy consumption record queries signal table
As shown in table 4, after electrical appliance is discerned successfully, can write down corresponding energy consumption, wherein the query note form of electrical appliance energy consumption is: single accumulative total service time of electrical appliance title, electrical appliance usage time interval, electrical appliance, the power of electrical appliance, the energy consumption of electrical appliance etc., and can generate corresponding day statistics, month statistics, year statistics etc.And can carry out Power Limitation at corresponding electrical appliance, if exceed restriction, then can implement power down process.
Electrical appliance is closed identifying and electrical appliance, and to open identifying similar, just do not do too much to endure here and do not state.
Carbon metering module main control microprocessor type selecting is an ARM CortexM3 core chip, and human-computer interaction module 2 adopts 3.2 cun TFT touch LCD display screens.Home client provides monitoring accounting, inquiry service and the intelligence environment protection suggestion of the carbon emission value that home energy source is consumed.The one, home energy source consumption is adjusted in monitoring, statistics carbon emission volume.Two provide real-time inquiry service, can demonstrate the current carbon emission value and the carbon exchange rate in real time.The 3rd, carry out " intelligence " in conjunction with current carbon emission amount and relevant consumption information and analyze, thereby the suggestion that provides rationalization for the user is avoided exceeding the quata to pay the environmental protection fund at End Of Quarter because of the carbon emission value.Home client is upgraded current carbon emission information by connecting the internet.It can be unified into network by internet and family's relevant device, and accessible database is inquired about carbon emission amount record in the past, and the current carbon emission information of real-time update in time reminds the client to note reducing the life behavior of non-low-carbon (LC).Because it only can provide the function of data query to the user, and bottom is invisible for the client, so can effectively avoid the behavior of malicious sabotage carbon metering.
Although content of the present invention has been done detailed introduction by above-mentioned preferred embodiment, will be appreciated that above-mentioned description should not be restriction of the present invention.After those skilled in the art has read foregoing, for multiple modification of the present invention with to substitute be conspicuous.Therefore, protection scope of the present invention should have appending claims to limit.
Claims (7)
1. electrical equipment recognition methods is specially:
(1) from the current current characteristic parameter value of current draw of home dwelling electric wire house lead in end, described current characteristic parameter value comprises electrical appliance active power;
(2) judge whether current power and the last power constantly that detects change, if power is constant, then preceding one-time detection recognition result constantly is current recognition result, finishes; If power increases, then showing has new electrical equipment to be used, and enters step (3); If power reduction, then showing has electrical appliance to stop using, and enters step (6);
(3) current current characteristic parameter value and last detection current characteristic parameter value constantly is poor, obtain increasing newly the electric current characteristic ginseng value;
(4) will increase the electric current characteristic ginseng value newly mates with the reference current characteristic ginseng value of each electrical equipment that may use respectively, if the Optimum Matching result satisfies minimum the match is successful requirement, then Optimum Matching as a result the electrical equipment of correspondence be the electrical equipment that increases newly, the last electrical equipment that detects identification constantly adds the new electrical equipment that uses as current recognition result, finishes; Otherwise, each electrical equipment that may use is made up, to the reference current characteristic ginseng value of the electrical equipment in each combination do and, enter step (5);
(5) will increase the electric current characteristic ginseng value newly mates with the reference current characteristic ginseng value sum of each combination respectively, if the Optimum Matching result satisfies minimum the match is successful requirement, then the Optimum Matching electrical equipment combination of correspondence as a result is the electrical equipment of new use, the last electrical equipment that detects identification constantly adds the new electrical equipment that uses as current recognition result, finishes; Otherwise recognition failures finishes;
(6) current current characteristic parameter value and last detection current characteristic parameter value constantly is poor, obtain stopping using the electric current characteristic ginseng value;
(7) will stop using the electric current characteristic ginseng value to mate with the reference current characteristic ginseng value of each electrical equipment that may use respectively, if the Optimum Matching result satisfies minimum the match is successful requirement, then Optimum Matching as a result the electrical equipment of correspondence be withdraw from service electrical equipment, the last electrical equipment that detects identification is constantly removed withdraw from service electrical equipment as current recognition result, finishes; Otherwise, each electrical equipment that may use is made up, to the reference current characteristic ginseng value of the electrical equipment in each combination do and, enter step (8);
(8) will stop using the electric current characteristic ginseng value to mate with the reference current characteristic ginseng value sum of each combination respectively, if the Optimum Matching result satisfies minimum the match is successful requirement, then the Optimum Matching electrical equipment combination of correspondence as a result is withdraw from service electrical equipment, the last electrical equipment that detects identification is constantly removed withdraw from service electrical equipment as current recognition result, finishes.
2. electrical equipment recognition methods according to claim 1, it is characterized in that, also current recognition result is verified in the following manner: to the reference current characteristic ginseng value of each electrical equipment in the current recognition result do and, itself and the current current characteristic parameter value that extracts are compared, if comparative result satisfies successfully requirement of minimum identification, then discern successfully, otherwise recognition failures.
3. electrical equipment recognition methods according to claim 1, it is characterized in that described current characteristic parameter value also comprises or combination in current peak, electric current average, current effective value, current first harmonics, current harmonics amplitude, current harmonics phase place, the current harmonics length.
4. electrical equipment recognition methods according to claim 3, it is characterized in that, employing concerns that based on the error linguistic variable scoring method characterizes the matching degree of the reference current characteristic ginseng value of each current characteristic parameter value and electrical equipment, score value with each current characteristic parameter value is weighted summation again, obtains the matching result of current current characteristic parameter value and this electrical equipment.
5. electrical equipment recognition methods according to claim 1 is characterized in that, each electrical equipment that may use is made up from less to more according to quantity.
6. application rights one of requires in 1 to 5 domestic consumer's carbon emission metering system of described electrical equipment recognition methods, and comprising: the busbar voltage sampling module connects the input end of phase detecting module, signal condition module and amplitude detection module respectively; The bus current detection module connects the input end of signal condition module; The input end of the output terminal connecting circuit identification module of phase detecting module, signal condition module, amplitude detection module, the output terminal of electrical equipment identification module connects the carbon metering module; The electrical equipment that the electrical equipment identification module is using according to described method identification one of in the claim 1 to 4, the carbon metering module is the carbon emission amount with the energy consumption conversion of the electrical equipment that identifies, other has power module is other module for power supply.
7. domestic consumer's carbon emission metering system according to claim 6 is characterized in that, also comprises the human-computer interaction module that joins with electrical equipment identification module and/or carbon metering module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110101398.4A CN102279326B (en) | 2011-04-22 | 2011-04-22 | Electrical appliance recognition method and household user carbon emission metering system applying same |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110101398.4A CN102279326B (en) | 2011-04-22 | 2011-04-22 | Electrical appliance recognition method and household user carbon emission metering system applying same |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102279326A true CN102279326A (en) | 2011-12-14 |
| CN102279326B CN102279326B (en) | 2014-03-12 |
Family
ID=45104885
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201110101398.4A Expired - Fee Related CN102279326B (en) | 2011-04-22 | 2011-04-22 | Electrical appliance recognition method and household user carbon emission metering system applying same |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102279326B (en) |
Cited By (31)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102967758A (en) * | 2012-12-07 | 2013-03-13 | 珠海派诺科技股份有限公司 | Separating method for indirect subentry measurement of building energy consumption |
| CN103869181A (en) * | 2012-12-17 | 2014-06-18 | 财团法人工业技术研究院 | Monitoring device and method for identifying electric device thereof |
| CN104076213A (en) * | 2013-03-28 | 2014-10-01 | 索尼公司 | Method, sensor and system for analyzing appliances in a power line network |
| CN104076765A (en) * | 2013-03-28 | 2014-10-01 | 索尼公司 | Method, sensor and system for analyzing appliances in a power line network |
| CN104090176A (en) * | 2014-06-09 | 2014-10-08 | 深圳市宏电技术股份有限公司 | Intelligent household appliance recognition method based on power consumption characteristic curve |
| CN104111395A (en) * | 2014-07-22 | 2014-10-22 | 上海申瑞继保电气有限公司 | Identification method of user-side electric operating device |
| CN104931774A (en) * | 2015-07-03 | 2015-09-23 | 广东美的厨房电器制造有限公司 | An electric appliance electric quantity monitor system and a monitor method |
| CN105576453A (en) * | 2015-11-06 | 2016-05-11 | 黄锐锋 | Intelligent safe patch board and control method thereof |
| CN105675974A (en) * | 2016-01-18 | 2016-06-15 | 广东美的暖通设备有限公司 | Load identification method and device |
| CN105913006A (en) * | 2016-04-08 | 2016-08-31 | 湖南工业大学 | Electricity load type identification method |
| CN105913010A (en) * | 2016-04-08 | 2016-08-31 | 湖南工业大学 | Electric appliance type determination device |
| CN105913005A (en) * | 2016-04-08 | 2016-08-31 | 湖南工业大学 | Electric appliance load type intelligent identification method and device |
| CN105913009A (en) * | 2016-04-08 | 2016-08-31 | 湖南工业大学 | Electric appliance type identifier |
| CN106845553A (en) * | 2017-02-04 | 2017-06-13 | 武汉阿帕科技有限公司 | Load characteristic identification mechanism, method and auto-power-off device |
| CN106872824A (en) * | 2017-02-15 | 2017-06-20 | 宁波华创锐科智能科技有限公司 | A kind of network load appliance type identification and the method and its device of different electrical equipment electricity statistics |
| CN106909101A (en) * | 2017-01-13 | 2017-06-30 | 中国海洋大学 | A kind of non-intrusion type household electrical appliance sorter and method |
| CN106908657A (en) * | 2017-03-06 | 2017-06-30 | 中国海洋大学 | A kind of load switch detection means and method based on power |
| CN105785187B (en) * | 2016-04-08 | 2018-06-15 | 湖南工业大学 | A kind of students' dormitory electrical appliance type judgement method |
| CN108828406A (en) * | 2018-06-19 | 2018-11-16 | 深圳安顺通电力物联服务有限公司 | The fault recognition method and its system of non-intrusion type user power utilization |
| CN109239494A (en) * | 2018-09-21 | 2019-01-18 | 无锡风繁伟业科技有限公司 | A kind of non-intrusive electrical load alert detecting method and system |
| CN109299134A (en) * | 2018-09-18 | 2019-02-01 | 四川长虹电器股份有限公司 | The recognition methods of electric appliance under a kind of non-intruding monitor system |
| CN109633301A (en) * | 2018-12-03 | 2019-04-16 | 四川长虹电器股份有限公司 | Non-intrusion type electric appliance load recognition methods based on quantum genetic optimization |
| CN109828144A (en) * | 2019-03-08 | 2019-05-31 | 李玉诚 | It is a kind of to acquire the measuring system and measurement method that compare for the strange land data same period |
| CN111178393A (en) * | 2019-12-11 | 2020-05-19 | 广东浩迪智云技术有限公司 | Electric appliance power consumption classification metering method and device based on intelligent electric meter |
| CN112034238A (en) * | 2020-09-11 | 2020-12-04 | 山东润一智能科技有限公司 | Electric equipment identification method and system |
| CN112104329A (en) * | 2020-09-22 | 2020-12-18 | 唐有钢 | Thing networking data security signal calibration system |
| CN112255480A (en) * | 2020-10-12 | 2021-01-22 | 浙江长元科技有限公司 | Hall effect based electric appliance characteristic identification method and safety early warning system thereof |
| CN113063984A (en) * | 2021-03-16 | 2021-07-02 | 合肥艾通自动化工程有限公司 | Load identification device, identification method and system |
| CN114338450A (en) * | 2021-12-31 | 2022-04-12 | 天翼物联科技有限公司 | Internet of things terminal carbon emission monitoring method and device and related components |
| CN114966475A (en) * | 2022-06-07 | 2022-08-30 | 贵州电网有限责任公司 | Intelligent detection system and method for abnormal wiring before power transmission of electric energy metering device |
| CN115425763A (en) * | 2022-11-04 | 2022-12-02 | 天津滨电电力工程有限公司 | Electric power carbon emission metering device and layered distributed carbon emission metering system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN200989922Y (en) * | 2006-08-09 | 2007-12-12 | 太原市特普高电子科技有限公司 | Electronic energy meter with power-driven device identification function |
| CN201576279U (en) * | 2010-02-04 | 2010-09-08 | 姬宏旺 | Carbon calculator |
| CN101832795A (en) * | 2010-04-13 | 2010-09-15 | 上海霖碳节能科技有限公司 | Personal-based carbon dioxide recording and tracing system platform |
| CN101908177A (en) * | 2010-08-11 | 2010-12-08 | 李炳志 | Method for regulating and controlling carbon emission of users by using intelligent power grid |
| US20100315252A1 (en) * | 2009-06-10 | 2010-12-16 | Shirish Devidas Desphande | Customizable, long lasting, thermally efficient, environmentally friendly, solid-state lighting apparatuses |
| CN201697980U (en) * | 2010-05-25 | 2011-01-05 | 武汉力源信息技术股份有限公司 | Measuring display device for saving energy by electric appliances |
-
2011
- 2011-04-22 CN CN201110101398.4A patent/CN102279326B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN200989922Y (en) * | 2006-08-09 | 2007-12-12 | 太原市特普高电子科技有限公司 | Electronic energy meter with power-driven device identification function |
| US20100315252A1 (en) * | 2009-06-10 | 2010-12-16 | Shirish Devidas Desphande | Customizable, long lasting, thermally efficient, environmentally friendly, solid-state lighting apparatuses |
| CN201576279U (en) * | 2010-02-04 | 2010-09-08 | 姬宏旺 | Carbon calculator |
| CN101832795A (en) * | 2010-04-13 | 2010-09-15 | 上海霖碳节能科技有限公司 | Personal-based carbon dioxide recording and tracing system platform |
| CN201697980U (en) * | 2010-05-25 | 2011-01-05 | 武汉力源信息技术股份有限公司 | Measuring display device for saving energy by electric appliances |
| CN101908177A (en) * | 2010-08-11 | 2010-12-08 | 李炳志 | Method for regulating and controlling carbon emission of users by using intelligent power grid |
Non-Patent Citations (2)
| Title |
|---|
| 李江晨等: "碳足迹系统", 《电子产品世界》, 28 February 2011 (2011-02-28), pages 53 - 54 * |
| 王威等: "固定型DSP集成电路在电能测量仪表中的应用", 《中国仪器仪表》, no. 8, 31 August 2004 (2004-08-31), pages 40 - 42 * |
Cited By (44)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102967758A (en) * | 2012-12-07 | 2013-03-13 | 珠海派诺科技股份有限公司 | Separating method for indirect subentry measurement of building energy consumption |
| CN103869181A (en) * | 2012-12-17 | 2014-06-18 | 财团法人工业技术研究院 | Monitoring device and method for identifying electric device thereof |
| CN103869181B (en) * | 2012-12-17 | 2016-10-26 | 财团法人工业技术研究院 | Monitoring device and method for identifying electric device thereof |
| US9310405B2 (en) | 2012-12-17 | 2016-04-12 | Industrial Technology Research Institute | Monitor apparatus and method for identifying electronic apparatus thereof |
| CN104076213A (en) * | 2013-03-28 | 2014-10-01 | 索尼公司 | Method, sensor and system for analyzing appliances in a power line network |
| CN104076765A (en) * | 2013-03-28 | 2014-10-01 | 索尼公司 | Method, sensor and system for analyzing appliances in a power line network |
| CN104076765B (en) * | 2013-03-28 | 2018-06-26 | 索尼公司 | For analyzing the method for the electric appliance in power line network, sensor and system |
| CN104076213B (en) * | 2013-03-28 | 2018-08-03 | 索尼公司 | Method, sensor and system for analyzing the electric appliance in power line network |
| CN104090176A (en) * | 2014-06-09 | 2014-10-08 | 深圳市宏电技术股份有限公司 | Intelligent household appliance recognition method based on power consumption characteristic curve |
| CN104111395A (en) * | 2014-07-22 | 2014-10-22 | 上海申瑞继保电气有限公司 | Identification method of user-side electric operating device |
| CN104111395B (en) * | 2014-07-22 | 2016-09-14 | 上海申瑞继保电气有限公司 | User puts into operation side the recognition methods of electrical equipment |
| CN104931774A (en) * | 2015-07-03 | 2015-09-23 | 广东美的厨房电器制造有限公司 | An electric appliance electric quantity monitor system and a monitor method |
| CN105576453A (en) * | 2015-11-06 | 2016-05-11 | 黄锐锋 | Intelligent safe patch board and control method thereof |
| CN105576453B (en) * | 2015-11-06 | 2018-02-06 | 黄锐锋 | A kind of intelligent and safe wiring board and its control method |
| CN105675974A (en) * | 2016-01-18 | 2016-06-15 | 广东美的暖通设备有限公司 | Load identification method and device |
| CN105675974B (en) * | 2016-01-18 | 2019-08-27 | 广东美的暖通设备有限公司 | Load identification method and device |
| CN105913010A (en) * | 2016-04-08 | 2016-08-31 | 湖南工业大学 | Electric appliance type determination device |
| CN105913005A (en) * | 2016-04-08 | 2016-08-31 | 湖南工业大学 | Electric appliance load type intelligent identification method and device |
| CN105913006A (en) * | 2016-04-08 | 2016-08-31 | 湖南工业大学 | Electricity load type identification method |
| CN105785187B (en) * | 2016-04-08 | 2018-06-15 | 湖南工业大学 | A kind of students' dormitory electrical appliance type judgement method |
| CN105913009A (en) * | 2016-04-08 | 2016-08-31 | 湖南工业大学 | Electric appliance type identifier |
| CN106909101A (en) * | 2017-01-13 | 2017-06-30 | 中国海洋大学 | A kind of non-intrusion type household electrical appliance sorter and method |
| CN106909101B (en) * | 2017-01-13 | 2019-04-23 | 中国海洋大学 | A kind of non-intrusion type household electrical appliance sorter and method |
| CN106845553A (en) * | 2017-02-04 | 2017-06-13 | 武汉阿帕科技有限公司 | Load characteristic identification mechanism, method and auto-power-off device |
| CN106872824A (en) * | 2017-02-15 | 2017-06-20 | 宁波华创锐科智能科技有限公司 | A kind of network load appliance type identification and the method and its device of different electrical equipment electricity statistics |
| CN106908657A (en) * | 2017-03-06 | 2017-06-30 | 中国海洋大学 | A kind of load switch detection means and method based on power |
| CN108828406A (en) * | 2018-06-19 | 2018-11-16 | 深圳安顺通电力物联服务有限公司 | The fault recognition method and its system of non-intrusion type user power utilization |
| CN109299134A (en) * | 2018-09-18 | 2019-02-01 | 四川长虹电器股份有限公司 | The recognition methods of electric appliance under a kind of non-intruding monitor system |
| CN109299134B (en) * | 2018-09-18 | 2021-06-22 | 四川长虹电器股份有限公司 | Method for identifying electric appliance under non-invasive monitoring system |
| CN109239494A (en) * | 2018-09-21 | 2019-01-18 | 无锡风繁伟业科技有限公司 | A kind of non-intrusive electrical load alert detecting method and system |
| CN109633301A (en) * | 2018-12-03 | 2019-04-16 | 四川长虹电器股份有限公司 | Non-intrusion type electric appliance load recognition methods based on quantum genetic optimization |
| CN109633301B (en) * | 2018-12-03 | 2021-04-06 | 四川长虹电器股份有限公司 | Non-invasive electrical appliance load identification method based on quantum genetic optimization |
| CN109828144A (en) * | 2019-03-08 | 2019-05-31 | 李玉诚 | It is a kind of to acquire the measuring system and measurement method that compare for the strange land data same period |
| CN111178393A (en) * | 2019-12-11 | 2020-05-19 | 广东浩迪智云技术有限公司 | Electric appliance power consumption classification metering method and device based on intelligent electric meter |
| CN112034238A (en) * | 2020-09-11 | 2020-12-04 | 山东润一智能科技有限公司 | Electric equipment identification method and system |
| CN112104329A (en) * | 2020-09-22 | 2020-12-18 | 唐有钢 | Thing networking data security signal calibration system |
| CN112104329B (en) * | 2020-09-22 | 2021-03-30 | 山东维平信息安全测评技术有限公司 | Thing networking data security signal calibration system |
| CN112255480A (en) * | 2020-10-12 | 2021-01-22 | 浙江长元科技有限公司 | Hall effect based electric appliance characteristic identification method and safety early warning system thereof |
| CN113063984A (en) * | 2021-03-16 | 2021-07-02 | 合肥艾通自动化工程有限公司 | Load identification device, identification method and system |
| CN114338450A (en) * | 2021-12-31 | 2022-04-12 | 天翼物联科技有限公司 | Internet of things terminal carbon emission monitoring method and device and related components |
| CN114338450B (en) * | 2021-12-31 | 2024-05-17 | 天翼物联科技有限公司 | Internet of things terminal carbon emission monitoring method and device and related components |
| CN114966475A (en) * | 2022-06-07 | 2022-08-30 | 贵州电网有限责任公司 | Intelligent detection system and method for abnormal wiring before power transmission of electric energy metering device |
| CN115425763A (en) * | 2022-11-04 | 2022-12-02 | 天津滨电电力工程有限公司 | Electric power carbon emission metering device and layered distributed carbon emission metering system |
| CN115425763B (en) * | 2022-11-04 | 2023-03-14 | 天津滨电电力工程有限公司 | Electric power carbon emission metering device and layered distributed carbon emission metering system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102279326B (en) | 2014-03-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102279326B (en) | Electrical appliance recognition method and household user carbon emission metering system applying same | |
| AU2019218021B2 (en) | Non-intrusive load identification-based submetering smart electricity meter | |
| CN109813978A (en) | A kind of non-intruding load-type recognition methods of variation characteristic between comprehensive transient characteristic and stable state | |
| CN111242391B (en) | Machine learning model training method and system for power load identification | |
| WO2014075581A1 (en) | Current-mode matching method for non-invasive power load monitoring and decomposition | |
| CN106093565B (en) | A kind of electricity subentry measurement method and device based on steady state characteristic Waveform Matching | |
| KR20140132523A (en) | Non-intrusive load monitoring apparatus and method | |
| CN105182250B (en) | A kind of non-intrusion type distributed power source output monitoring device | |
| CN106406108A (en) | Intelligent household electric controller and control method | |
| CN202615205U (en) | Intelligent managing and monitoring device for laboratory instruments based on Internet of Things | |
| CN202373979U (en) | Intelligent reactive power compensation and power parameter display integrated control device | |
| Matthews et al. | Automatically disaggregating the total electrical load in residential buildings: a profile of the required solution | |
| Houidi et al. | Design of an electricity consumption measurement system for Non Intrusive Load Monitoring | |
| CN205826772U (en) | Non-intruding Fault Identification device | |
| CN106707019A (en) | Service robot electric quantity monitoring device | |
| Wu et al. | A nonintrusive fast residential load identification algorithm based on frequency‐domain template filtering | |
| CN113422432B (en) | Electrical fire prevention and control system based on non-invasive load monitoring | |
| CN207366634U (en) | A kind of load monitoring recording equipment | |
| Cho et al. | Home energy management system for interconnecting and sensing of electric appliances | |
| CN202033417U (en) | Power saving rate verification system of power saver | |
| CN206740953U (en) | A kind of computer intelligence energy collection terminal function test system based on Internet of Things | |
| CN205540111U (en) | High -power electrical apparatus intelligent recognition and electrical safety controller | |
| CN105277784A (en) | Electricity consumption information acquisition apparatus | |
| CN202586344U (en) | Power-saving device having power-saving rate verification system | |
| Zhao et al. | Design of a data acquisition system for building electrical fault diagnosis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20140312 Termination date: 20150422 |
|
| EXPY | Termination of patent right or utility model |