CN105372541A - Household appliance intelligent set total detection system based on pattern recognition and working method thereof - Google Patents
Household appliance intelligent set total detection system based on pattern recognition and working method thereof Download PDFInfo
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- G—PHYSICS
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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Abstract
The invention relates to a household appliance intelligent set total detection system based on pattern recognition and a working method thereof. The detection system comprises an AC voltage transformer VT, an AC current transformer CT, a primary processing unit PM and an advanced processing unit CM; two ends of a primary coil of the AC voltage transformer VT are respectively connected with a service entrance zero line and a service entrance fire wire; a primary coil of the AC current transformer CT is connected with the service entrance zero line or the service entrance fire wire; a secondary coil of the AC voltage transformer VT and a secondary coil of the AC current transformer CT are taken as input ends of the primary processing unit PM, and the primary processing unit PM is connected with the advanced processing unit CM through an Internet of Things. The household appliance intelligent detection system based on the pattern recognition is the intelligent set total detection system, only samples a voltage and a current at a position of the service entrance lines, and does not need to sample a voltage and a current of each household appliance; and system hardware cost is reduced, the Internet of Things topological structure is simplified, and sampling data objectivity is improved.
Description
Technical field:
The present invention relates to a kind of household electrical appliance based on pattern-recognition intelligence lump detection system and method for work thereof, belong to the technical field of mode identification technology application.
Background technology:
Along with the fast development of science and technology, kind and the function of household electrical appliance get more and more, and household electrical appliance positive pole the earth changes the life of modern.Certainly, the importance of household electrical appliances to family life is more and more higher, and technical sophistication degree also becomes more and more higher, cause ordinary consumer to understand fewer and feweri to the know-why of household electrical appliances, thus the monitoring of different types of household electrical appliance running status, analysis and fault diagnosis and prediction are become more and more important.
In prior art, civil power enters through subscriber's drop switch, and connects n household electrical appliance (DQ
1~ DQ
n), the home appliance monitor system (as shown in Figure 1) of main flow is by an embedded or external monitoring module (PM at each household electrical appliance
1~ PM
n), monitoring module is responsible for the monitoring of corresponding household appliance, and by Internet of Things, the running status of corresponding household appliance is uploaded to advanced processes unit CM, carries out data store and further data analysis by CM.
This by configuring a monitoring module to each household electrical appliance, and by distributed household electrical appliances intelligent monitor system poor reliability, complex structure that Internet of Things forms; In current this system each household electrical appliances mostly without built-in monitoring module (even if having, communications protocol is also often incompatible), and data often standard, the form disunity that the built-in monitoring module that manufacturer provides provides, accuracy also cannot ensure, is difficult to allow people convince; If unified external monitoring module significantly can increase system cost, especially on the small domestic appliance of each low cost, low-power consumption, configuring a monitoring module, is obviously also unrealistic and unscientific.
Distributed household electrical appliances intelligent monitor system is discussed more in detail and sees Master's thesis " design and implimentation of intelligent home control system " (Tang Rong rosy clouds Shandong University 2009).
Pattern-recognition (English: PatternRecognition) is the automatic process and the interpretation that are carried out research mode by computing machine mathematical technique method.We are referred to as environment and object " pattern ".Pattern-recognition is a primary mental ability of the mankind, and in daily life, people carry out " pattern-recognition " through being everlasting.Along with the appearance of computing machine and the rise of artificial intelligence, people certainly also wish general-purpose computers to replace or expand the part brainwork of the mankind.(computing machine) pattern-recognition develops rapidly in early 1960s and becomes a new disciplines.Pattern-recognition refer to characterize things or phenomenon various forms of (numerical value, word with logical relation) information processes and analyzes, with the process being described things or phenomenon, recognizing, classifying and explaining, it is the important component part of information science and artificial intelligence.
Edge check and time-domain analysis technology are the important branch of Digital Signal Processing.
Time-domain analysis refers to that control system is under certain input, according to the time-domain expression of output quantity, and the stability of analytic system, transient state and steady-state behaviour.Because time-domain analysis is directly in the time domain to the method that system is analyzed, so time-domain analysis has directly perceived and advantage accurately.
The frequency-domain analysis of test signal is that the amplitude of signal, phase place or energy conversion are represented with frequency coordinate axle, and then analyzes a kind of analytical approach of its frequency characteristic, is also called spectrum analysis.Spectrum analysis is carried out to signal and can obtain more useful informations, as tried to achieve each frequency content in Dynamic Signal and frequency distribution scope, obtaining amplitude distribution and the energy distribution of each frequency content, thus obtaining the frequency values of main amplitude and energy distribution.
Chinese patent CN100495918 discloses a kind of sync signal detection apparatus, and this device exports the pulse signal of described edge detecting unit generation or the internal clock signal of described clock generator generation according to the signal-selectivity exported from described pulse signal detection unit.
Summary of the invention:
For the deficiencies in the prior art, the invention provides a kind of household electrical appliance based on pattern-recognition intelligence lump detection system.
The present invention also provides a kind of method of work of above-mentioned household electrical appliance intelligence lump detection system.
Summary of the invention:
Household electrical appliance based on pattern-recognition of the present invention intelligence lump detection system by sampling to domestic consumer's primary voltage/electric current, computation and analysis, realize variety classes household electrical appliance lump Intelligent Recognition, running state analysis and fault diagnosis and fault prediction.This system is by sampling to house lead in electric current and voltage, and by information about power such as the effective value of calculating sampling signal, meritorious/reactive power, power factor, harmonic waves, and the event information such as appliance starting, stopping, then adopt algorithm for pattern recognition Intelligent Recognition user in the classification/model of electrical appliance, quantity, power and the parameter such as running status, moving law, and the potential risk that exists of equipment of estimating and fault.
Technical scheme of the present invention is as follows:
Based on a household electrical appliance intelligence lump detection system for pattern-recognition, comprise AC voltage transformer VT, AC current transformer CT, primary treatment unit PM and advanced processes unit CM; The two ends of the primary coil of described AC voltage transformer VT are connected with house lead in zero line N and house lead in live wire L respectively; The primary coil of described AC current transformer CT is connected with house lead in zero line N or house lead in live wire L; The secondary coil of described AC voltage transformer VT and the secondary coil of AC current transformer CT are as the input end of primary treatment unit PM; Described primary treatment unit PM is connected with advanced processes unit CM by Internet of Things.Described primary treatment unit PM Real-time Obtaining is at the information about power of electrical appliance; And adopt edge sense technology and time-domain analysis technical limit spacing at the time sequence information of electrical appliance; Adopt spectrum analysis technique to obtain the exclusive characteristic frequency spectrum of different household electrical appliance (such as, rectification electric appliances, electric machinery electrical equipment and electrical heating electric appliances) because of its principle of work, the formation of structure and material difference simultaneously.(spectrum analysis technique frequencyspectrumanalysis, technologyof are a kind of technical methods of announcement and analytic signal and (or) system performance in frequency field)
Described information about power comprises, the effective value of house lead in voltage, electric current, meritorious/reactive power, power factor and harmonic wave etc.; Described time sequence information comprises, open/stopping time carves, opens/and the stopping time is long and open/have a power failure the information such as stream.
Preferably, described primary treatment unit PM comprises digital signal processing chip (DSP).Digital signal processing chip carries out computing to the sampled value of house lead in voltage/current, obtain at the information about power with household electrical appliance, time sequence information and its characteristic frequency spectrum, then adopt algorithm for pattern recognition Intelligent Recognition in the classification of electrical appliance, model, quantity and the information such as running status, moving law.In the prior art, for information about power, time sequence information and characteristic frequency spectrum building database that the electrical equipment of different classes of, model, quantity and running status, moving law is corresponding, obtain corresponding classification at electrical appliance, model, quantity and the information such as running status, moving law when obtaining " information about power, time sequence information and characteristic frequency spectrum " by algorithm for pattern recognition to make those skilled in the art.
Preferably, described advanced processes unit CM comprises storage unit, and described storage unit is carried out classification to the data that primary treatment unit PM uploads and stored.Advanced processes unit CM is according to the long history data stored, under more long period yardstick, Data Analysis Services is carried out to different household electrical appliance, further excavate user's different household electrical appliance long-time running rule, running status (the long period variation rule as the frequency of utilization/efficiency/load factor of certain household electrical appliance), and then infer " health " situation of household electrical appliances, and the deep information such as potential operation risk and fault; And come out from different manufacturer further, with the performance difference between kind household electrical appliance.In the prior art, carry out storing for the data uploaded from primary treatment unit PM and set up another database, with make those skilled in the art to obtain after " information about power in certain time length, time sequence information and characteristic frequency spectrum " namely estimate by algorithm for pattern recognition corresponding to the deep informations such as " health " situation of electrical appliance, potential operation risk and faults; And come out from different manufacturer further, with the performance difference between kind household electrical appliance.
Preferred further, described advanced processes unit CM is computer, workstation or server.
Preferably, described AC current transformer CT is wideband linear mutual inductor.Wideband linear mutual inductor can become in tens hertz of frequency ranges to hundreds of KHz low distortion send current signal.
A method of work for the above-mentioned intelligence of the household electrical appliance based on pattern-recognition lump detection system, comprises step as follows,
1) voltage transformer (VT) VT, AC current transformer CT isolate and transformation of scale house lead in voltage and house lead in electric current;
2) primary treatment unit PM samples to the house lead in voltage after isolation and transformation of scale and house lead in electric current, and computing is carried out to sampled value, obtain the data do not coexisted with household electrical appliance, described data comprise information about power, time sequence information and characteristic frequency spectrum; And obtain in the classification with household electrical appliance, model, quantity, running status and moving law information further;
3) data are regularly passed to advanced processes unit CM by Internet of Things by primary treatment unit PM;
4) advanced processes unit CM carries out classification storage and process further to data; By adding up the frequency of utilization of each household electrical appliance, work efficiency and load factor, estimate the operation risk that each household electrical appliance are potential and potential failure message.
Preferably, described step 2) in acquisition do not coexist with the time sequence information of household electrical appliance and the concrete grammar of characteristic frequency spectrum and be, employing edge sense technology and time-domain analysis technical limit spacing are at the time sequence information of electrical appliance; Spectrum analysis technique is adopted to obtain the characteristic frequency spectrum of different household electrical appliance; Estimate at the concrete grammar of the classification with household electrical appliance, model, quantity, running status and moving law information to be algorithm for pattern recognition.
Preferably, described step 4) middle-and-high-ranking processing unit CM also comprises the process that data are further processed, contrast different manufacturer, with the frequency of utilization between kind household electrical appliance, work efficiency and load factor data, obtain different manufacturer, with the performance difference between kind household electrical appliance.
Preferably, described step 4) middle-and-high-ranking processing unit CM to data carry out classify store concrete grammar be that the information about power of household electrical appliance, time sequence information and characteristic frequency spectrum are stored respectively.
Advantage of the present invention is:
1. the household electrical appliance intelligent checking system based on pattern-recognition of the present invention is a kind of intelligent lump detection system, is namely only sampled by the voltage to house lead in place, electric current, samples without the need to the voltage to each household electrical appliance, electric current; Thus reduce system hardware cost, simplify Internet of Things topological structure, improve the objectivity of sampled data;
2. the intelligence of the household electrical appliance based on pattern-recognition lump detection system of the present invention, described primary treatment unit PM Land use models recognizer carries out analyzing and processing to the information about power of subscriber's drop voltage/current, time-domain information, characteristic frequency spectrum information, obtains in the classification of electrical appliance, model, quantity and the information such as running status, moving law further;
3. the intelligence of the household electrical appliance based on pattern-recognition lump detection system of the present invention, by the long-term operation data analysis process of advanced processes unit CM to household electrical appliance, further excavation different household electrical appliance long-time running rule, state, and then infer " health " situation of household electrical appliances, and the deep information such as potential operation risk and fault;
4. the intelligence of the household electrical appliance based on pattern-recognition lump detection system of the present invention, by the contrast of data message between different system, can add up from different manufacturers further with performance difference between kind household electrical appliance.
Accompanying drawing illustrates:
Fig. 1 is the structural representation of the supervisory system of household electrical appliance in prior art;
Fig. 2 is the structural representation of the household electrical appliance based on pattern-recognition of the present invention intelligence lump detection system;
Embodiment:
Below in conjunction with embodiment and Figure of description, invention is described in detail, but is not limited thereto.
Embodiment 1,
As shown in Figure 2, in figure, 220V electric main enters in user family through subscriber's drop K switch 1, after meet n variety classes household electrical appliance DQ
1~ DQ
n.
Based on a household electrical appliance intelligence lump detection system for pattern-recognition, comprise AC voltage transformer VT, AC current transformer CT, primary treatment unit PM and advanced processes unit CM; The two ends of the primary coil of described AC voltage transformer VT are connected with house lead in zero line N and house lead in live wire L respectively; The primary coil of described AC current transformer CT is connected with house lead in zero line N; The secondary coil of described AC voltage transformer VT and the secondary coil of AC current transformer CT are as the input end of primary treatment unit PM; Described primary treatment unit PM is connected with advanced processes unit CM by Internet of Things.Described primary treatment unit PM Real-time Obtaining is at the information about power of electrical appliance, and described information about power comprises house lead in voltage, the effective value of electric current, meritorious/reactive power, power factor and harmonic wave etc.; And adopting edge sense technology and time-domain analysis technical limit spacing at the time sequence information of electrical appliance, described time sequence information comprises, open/stopping time carves, opens/and the stopping time is long and open/have a power failure stream; Adopt spectrum analysis technique to obtain the characteristic frequency spectrum of different household electrical appliance simultaneously.
Embodiment 2,
The intelligence of the household electrical appliance based on pattern-recognition lump detection system according to embodiment 1, its difference is, described primary treatment unit PM comprises digital signal processing chip DSP.Digital signal processing chip DSP carries out computing to the sampled value of house lead in voltage/current, obtain at the information about power with household electrical appliance, time sequence information and its characteristic frequency spectrum, then adopt algorithm for pattern recognition Intelligent Recognition user in the classification of electrical appliance, model, quantity and the information such as running status, moving law.
Embodiment 3,
The intelligence of the household electrical appliance based on pattern-recognition lump detection system according to embodiment 1, its difference is, described advanced processes unit CM comprises storage unit, and described storage unit is carried out classification to the data that primary treatment unit PM uploads and stored.Advanced processes unit CM is according to the long history data stored, under more long period yardstick, Data Analysis Services is carried out to different household electrical appliance, further excavate user's different household electrical appliance long-time running rule, running status (the long period variation rule of the frequency of utilization/efficiency/load factor of household electrical appliance), and then infer " health " situation of household electrical appliances, and the deep information such as potential operation risk and fault; And come out from different manufacturer further, with the performance difference between kind household electrical appliance.
Embodiment 4,
The intelligence of the household electrical appliance based on pattern-recognition lump detection system according to embodiment 3, its difference is, described advanced processes unit CM is computer.
Embodiment 5,
The intelligence of the household electrical appliance based on pattern-recognition lump detection system according to embodiment 1, its difference is, described AC current transformer CT is wideband linear mutual inductor.Wideband linear mutual inductor can become in tens hertz of frequency ranges to hundreds of KHz low distortion send current signal.
Embodiment 6,
The intelligence of the household electrical appliance based on pattern-recognition lump detection system according to embodiment 1, its difference is, the primary coil of described AC current transformer CT is connected with house lead in live wire L.
Embodiment 7,
A method of work for the intelligence of the household electrical appliance based on pattern-recognition lump detection system as described in embodiment 1-6, comprises step as follows,
1) voltage transformer (VT) VT, AC current transformer CT isolate and transformation of scale house lead in voltage and house lead in electric current;
2) primary treatment unit PM samples to the house lead in voltage after isolation and transformation of scale and house lead in electric current, and computing is carried out to sampled value, obtain the data do not coexisted with household electrical appliance, described data comprise information about power, time sequence information and characteristic frequency spectrum; And obtain in the classification with household electrical appliance, model, quantity, running status and moving law information further;
3) data are regularly passed to advanced processes unit CM by Internet of Things by primary treatment unit PM;
4) advanced processes unit CM carries out classification storage and process further to data; By adding up the frequency of utilization of each household electrical appliance, work efficiency and load factor, estimate the operation risk that each household electrical appliance are potential and potential failure message.
Embodiment 8,
As described in Example 7 based on household electrical appliance intelligence lump detection system and the method for work thereof of pattern-recognition, its difference is, described step 2) in acquisition do not coexist with the time sequence information of household electrical appliance and the concrete grammar of characteristic frequency spectrum and be, employing edge sense technology and time-domain analysis technical limit spacing are at the time sequence information of electrical appliance; Spectrum analysis technique is adopted to obtain the characteristic frequency spectrum of different household electrical appliance; Estimation at the concrete grammar of the classification with household electrical appliance, model, quantity, running status and moving law information is, algorithm for pattern recognition.
Embodiment 9,
As described in Example 7 based on household electrical appliance intelligence lump detection system and the method for work thereof of pattern-recognition, its difference is, described step 4) middle-and-high-ranking processing unit CM also comprises the process that data are further processed, contrast different manufacturer, with the frequency of utilization between kind household electrical appliance, work efficiency and load factor data, obtain different manufacturer, with the performance difference between kind household electrical appliance.
Embodiment 10,
As described in Example 7 based on household electrical appliance intelligence lump detection system and the method for work thereof of pattern-recognition, its difference is, described step 4) middle-and-high-ranking processing unit CM to data carry out classify store concrete grammar be that the information about power of household electrical appliance, time sequence information and characteristic frequency spectrum are stored respectively.
Claims (9)
1., based on a household electrical appliance intelligence lump detection system for pattern-recognition, it is characterized in that, comprise AC voltage transformer VT, AC current transformer CT, primary treatment unit PM and advanced processes unit CM; The two ends of the primary coil of described AC voltage transformer VT are connected with house lead in zero line N and house lead in live wire L respectively; The primary coil of described AC current transformer CT is connected with house lead in zero line N or house lead in live wire L; The secondary coil of described AC voltage transformer VT and the secondary coil of AC current transformer CT are as the input end of primary treatment unit PM; Described primary treatment unit PM is connected with advanced processes unit CM by Internet of Things.
2. the intelligence of the household electrical appliance based on pattern-recognition lump detection system according to claim 1, it is characterized in that, described primary treatment unit PM comprises digital signal processing chip DSP.
3. the intelligence of the household electrical appliance based on pattern-recognition lump detection system according to claim 1, it is characterized in that, described advanced processes unit CM comprises storage unit, and described storage unit is carried out classification to the data that primary treatment unit PM uploads and stored.
4. the intelligence of the household electrical appliance based on pattern-recognition lump detection system according to claim 3, it is characterized in that, described advanced processes unit CM is computer, workstation or server.
5. the intelligence of the household electrical appliance based on pattern-recognition lump detection system according to claim 1, it is characterized in that, described AC current transformer CT is wideband linear mutual inductor.
6. the method for work of the intelligence of the household electrical appliance based on the pattern-recognition lump detection system according to claim 1-5 any one, is characterized in that, comprise step as follows,
1) voltage transformer (VT) VT, AC current transformer CT isolate and transformation of scale house lead in voltage and house lead in electric current;
2) primary treatment unit PM samples to the house lead in voltage after isolation and transformation of scale and house lead in electric current, and computing is carried out to sampled value, obtain the data do not coexisted with household electrical appliance, described data comprise information about power, time sequence information and characteristic frequency spectrum; And obtain in the classification with household electrical appliance, model, quantity, running status and moving law information further;
3) data are regularly passed to advanced processes unit CM by Internet of Things by primary treatment unit PM;
4) advanced processes unit CM carries out classification storage and process further to data; By adding up the frequency of utilization of each household electrical appliance, work efficiency and load factor, estimate the operation risk that each household electrical appliance are potential and potential failure message.
7. the method for work of the intelligence of the household electrical appliance based on pattern-recognition lump detection system according to claim 6, it is characterized in that, described step 2) in acquisition do not coexist with the time sequence information of household electrical appliance and the concrete grammar of characteristic frequency spectrum and be, employing edge sense technology and time-domain analysis technical limit spacing are at the time sequence information of electrical appliance; Spectrum analysis technique is adopted to obtain the characteristic frequency spectrum of different household electrical appliance; Estimation at the concrete grammar of the classification with household electrical appliance, model, quantity, running status and moving law information is, algorithm for pattern recognition.
8. the method for work of the intelligence of the household electrical appliance based on pattern-recognition lump detection system according to claim 6, it is characterized in that, described step 4) middle-and-high-ranking processing unit CM also comprises the process that data are further processed, contrast different manufacturer, with the frequency of utilization between kind household electrical appliance, work efficiency and load factor data.
9. the method for work of the intelligence of the household electrical appliance based on pattern-recognition lump detection system according to claim 6, it is characterized in that, described step 4) middle-and-high-ranking processing unit CM to data carry out classify store concrete grammar be that the information about power of household electrical appliance, time sequence information and characteristic frequency spectrum are stored respectively.
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