CN210954205U - Non-invasive automatic identification device for electric equipment - Google Patents
Non-invasive automatic identification device for electric equipment Download PDFInfo
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- CN210954205U CN210954205U CN201921710023.6U CN201921710023U CN210954205U CN 210954205 U CN210954205 U CN 210954205U CN 201921710023 U CN201921710023 U CN 201921710023U CN 210954205 U CN210954205 U CN 210954205U
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Abstract
The utility model discloses circuit structure designs novel non-invasive consumer automatic identification equipment, it includes: the current mutual inductance acquisition module is connected with the power main line and converts large current in the power main line into small current signals; the voltage mutual inductance acquisition module is connected with the power main line and converts large voltage in the power main line into small voltage signals; the current output end and the voltage output end of the current mutual inductance acquisition module and the voltage mutual inductance acquisition module are respectively connected with the microcontroller module, and the microcontroller module is used for acquiring the current value of the current mutual inductance acquisition module after being scaled down and the voltage value of the voltage mutual inductance acquisition module after being scaled down; and the data concentrator module is connected with the microcontroller module and is used for forming the electric appliance characteristic parameters sent by the microcontroller module into a training set and generating a decision tree according to the data training set, wherein the decision tree is used for identifying the current working electric equipment.
Description
Technical Field
The utility model relates to an electrical equipment discernment technical field especially relates to a non-invasive electrical equipment automatic identification equipment.
Background
The power load decomposition is an important research direction in the field of intelligent power utilization, and has important significance for countries, power grid companies and power consumers. With the gradual improvement of social energy-saving consciousness, an approach for acquiring energy consumption information of each load in a family is urgently needed. At present, the electric detail detection technology for the electric appliance mainly comprises an invasive technology and a non-invasive technology.
A non-intrusive (equipment) load monitoring (NILM or nilmm) is a method for identifying all operating electrical equipment on a monitored circuit from electrical parameter data of an electrical power main. The non-invasive load monitoring means that a monitoring device is installed at the main end of an electric power main line, and the using state of an electric appliance in a system is obtained by acquiring the characteristic parameters of the electric appliance and analyzing, so that the state monitoring of the electric appliance in the system is realized. Compared with invasive load identification, the non-invasive load identification has the advantages of convenience, strong maintainability, easy popularization and the like.
Disclosure of Invention
The utility model aims to overcome prior art's is not enough, adapts to reality needs, provides a circuit structure design novelty's non-intrusive formula consumer automatic identification equipment.
In order to realize the utility model discloses a purpose, the utility model discloses the technical scheme who adopts does:
designing a non-invasive electric equipment automatic identification device, which comprises:
the current mutual inductance acquisition module is connected with the power main line and converts large current in the power main line into small current signals;
the voltage mutual inductance acquisition module is connected with the power main line and converts large voltage in the power main line into small voltage signals;
the current output end and the voltage output end of the current mutual inductance acquisition module and the voltage mutual inductance acquisition module are respectively connected with the microcontroller module, and the microcontroller module is used for acquiring the current value of the current mutual inductance acquisition module after being scaled down and the voltage value of the voltage mutual inductance acquisition module after being scaled down;
and the data concentrator module is connected with the microcontroller module and is used for forming the electric appliance characteristic parameters sent by the microcontroller module into a training set and generating a decision tree according to the data training set, wherein the decision tree is used for identifying the current working electric equipment.
The current mutual inductance acquisition module comprises a current transformer, two current acquisition ends of the current transformer are connected with an electric power main line, a sampling resistor R1 is connected between a first current output end A0 and a second current output end A0 of the current transformer, and the second current output end A0 is connected with the microcontroller module;
the circuit also comprises a bias resistor R2 and a bias resistor R3 which are connected in series, wherein the input ends of the bias resistor R2 and the bias resistor R3 which are connected in series are connected with a power supply, and the output ends of the bias resistor R2 and the bias resistor R3 which are connected in series are grounded;
one end of a sampling resistor R1 connected with the first current output end is grounded through a capacitor C1, and the first current output end of the current transformer is also connected between a bias resistor R2 and a bias resistor R3.
The voltage mutual inductance acquisition module comprises a voltage transformer, a voltage wiring terminal on the voltage transformer is connected with a large-current wiring terminal, the voltage transformer is connected with a power main line through the large-current wiring terminal, and a resistor R7 is connected in series between a second voltage wiring terminal on the voltage transformer and the large-current wiring terminal;
a sampling resistor R4 is connected between a first voltage output end A1 and a second voltage output end of the voltage transformer, wherein the first voltage output end A1 is connected with the microcontroller module;
the circuit also comprises a bias resistor R5 and a bias resistor 6 which are connected in series, wherein the input ends of the bias resistor R5 and the bias resistor R6 which are connected in series are connected with a power supply, and the output ends of the bias resistor R5 and the bias resistor R6 which are connected in series are grounded;
one end of a sampling resistor R4 connected with the second voltage output end is grounded through a capacitor C2, and the second voltage output end of the voltage transformer is also connected between a bias resistor R5 and a bias resistor R6.
The beneficial effects of the utility model reside in that:
the non-invasive electric equipment recognition device has two modes of learning, analyzing and detecting when in use, the device is implanted with electric appliance characteristic parameters and an operation algorithm (the prior art) before recognizing the electric appliance, and the device recognizes the electric appliance (the prior art) by generating a decision tree through the electric appliance characteristic parameters, so that the recognition accuracy is greatly improved, the device is suitable for being popularized facing home users, and the device has important significance for energy conservation, environmental protection and intelligent power utilization.
Drawings
FIG. 1 is a schematic view of the overall structure of the apparatus;
FIG. 2 is a circuit diagram of a current mutual inductance acquisition module in the device;
fig. 3 is a circuit diagram of a voltage mutual inductance acquisition module in the device.
Detailed Description
The invention will be further described with reference to the following figures and examples:
example 1: a non-invasive automatic identification device for electric equipment, see fig. 1 to 3; it includes:
the current mutual inductance acquisition module converts a large current in a power main line into a small current signal which can be processed by the microcontroller module by using a current transformer;
the voltage mutual inductance acquisition module converts a large voltage in a power main line into a small voltage signal which can be processed by the microcontroller module by using a voltage transformer;
the current output end and the voltage output end of the current mutual inductance acquisition module and the voltage mutual inductance acquisition module are respectively connected with the microcontroller module, the microcontroller module acquires a current value after the current mutual inductance acquisition module is scaled down and a voltage value after the voltage mutual inductance acquisition module is scaled down, the microcontroller module obtains characteristic parameters of an electric main line of the current combined electric appliance, such as a current effective value, a voltage effective value, a power factor, active power, reactive power, apparent power and the like through internal operation, then sends each group of the characteristic parameters to the data concentrator module in a fixed format, and makes corresponding actions according to a control command sent by the data concentrator module;
and the data concentrator module is connected with the microcontroller module and is used for forming the electric appliance characteristic parameters sent by the microcontroller module into a training set, generating a decision tree according to the data training set and issuing a corresponding functional instruction to the microcontroller module, wherein the decision tree is used for identifying the current working electric equipment.
Specifically, referring to fig. 2, the current mutual inductance collecting module includes a current transformer, two current collecting terminals of the current transformer are connected to a power main, a sampling resistor R1 is connected between a first current output terminal and a second current output terminal a0 of the current transformer, and the second current output terminal a0 is connected to the microcontroller module.
The microcontroller module further comprises a bias resistor R2 and a bias resistor R3 which are connected in series, wherein the input ends of the bias resistor R2 and the bias resistor R3 which are connected in series are connected with a power supply, the output ends of the bias resistor R2 and the bias resistor R3 which are connected in series are grounded, the bias resistor R2 and the bias resistor R3 are used for generating bias voltage, the output end of the A0 is guaranteed to be positive voltage, and the output end of the A0 is connected with the input port of the ADC of the microcontroller module.
One end of a sampling resistor R1 connected with the first current output end is grounded through a capacitor C1, and the first current output end of the current transformer is also connected between a bias resistor R2 and a bias resistor R3.
In the mutual inductance current acquisition module circuit, the current transformer adopts the transformation ratio of 1000: 1, which can convert a large current of maximum 10A into a small current of 10 ma.
Specifically, referring to fig. 3, the mutual voltage inductance collecting module comprises a voltage transformer, a large current terminal is connected to a voltage terminal of the voltage transformer, the voltage transformer is connected to the power main line through the large current terminal, and a resistor R7 is connected in series between a second voltage terminal of the voltage transformer and the large current terminal.
A sampling resistor R4 is connected between a first voltage output end A1 and a second voltage output end of the voltage transformer, wherein the first voltage output end A1 is connected with the microcontroller module.
The circuit also comprises a bias resistor R5 and a bias resistor 6 which are connected in series, wherein the input ends of the bias resistor R5 and the bias resistor R6 which are connected in series are connected with a power supply, and the output ends of the bias resistor R5 and the bias resistor R6 which are connected in series are grounded.
One end of a sampling resistor R4 connected with the second voltage output end is grounded through a capacitor C2, and the second voltage output end of the voltage transformer is also connected between a bias resistor R5 and a bias resistor R6.
In the voltage mutual inductance acquisition module circuit, a voltage transformer adopts a rated input and output current of 2 ma: 2mA precision voltage transformer, the maximum current input is 10 mA. This design can convert voltage into electric current through series resistance R7, then through turn ratio 1500: 1500, the current is mutually inducted to the output end of the secondary coil, the current is converted into an ADC analog voltage value which can be born by the microcontroller through a sampling resistor R4 at the output end, and the A1 output end is connected with an ADC input port of the microcontroller module.
In the circuit of the device, the microcontroller module selects an AtmelSAM3X8E microcontroller based on an ARMCortex-M3 kernel, a 16-channel 12-bit ADC is integrated in the microcontroller module, a current mutual inductance acquisition module and a voltage mutual inductance acquisition module at the front end are controlled to measure current and voltage, and data communication is carried out between the microcontroller module and a data concentrator module through a USB interface. The power supply circuit of the device adopts 3.3V input voltage for power supply, and the internal voltage reference of the microcontroller is used as the reference input of the ADC, so that the microcontroller can obtain real-time accurate reference voltage.
The data concentrator module adopts a RaspberryPi3ModelB card type computer, the central processing unit adopts a BCM2837 chip of Broadcom company, an operating system transplanted on the data concentrator is a lightweight and compact Raspbian Linux system, and a USB interface is used for communicating with the microcontroller module.
The device has two modes of learning, analyzing and detecting when in use, the device is implanted with the characteristic parameters of the electric appliance and an operation algorithm (the prior art) before the electric appliance is identified, and the device identifies the electric appliance by generating a decision tree through the characteristic parameters of the electric appliance (the prior art).
When the device is used, the current and voltage values on the power pole wire are respectively collected by the current mutual inductance collection module and the voltage mutual inductance collection module, and then are respectively transmitted into the microcontroller module by the output ends A0 and A1 of the current mutual inductance collection module and the voltage mutual inductance collection module, the microcontroller module obtains the characteristic parameters of the current combined electric appliance such as the current effective value, the voltage effective value, the power factor, the active power, the reactive power, the apparent power and the like (the method of obtaining the current effective value, the voltage effective value, the power factor, the active power, the reactive power and the apparent power by calculation is the prior art), then each group of the characteristic parameters are sent to the data concentrator module in a fixed format, and then the data concentrator module forms the characteristic parameters of the electric appliance sent by the microcontroller module into a training set, and generating a decision tree according to the data training set (the technology of forming the training set by the characteristic parameters of the electric appliances and generating the decision tree is the prior art), and then identifying the current working electric equipment by the decision tree. The device can test and store the electric appliance characteristic parameters of each single electric appliance in various states for identifying the electric appliance and the working state thereof in a learning mode; and in the analysis monitoring mode, the type and the working state of the electric appliance can be indicated in real time.
The embodiment of the present invention discloses a preferred embodiment, but not limited thereto, and those skilled in the art can easily understand the spirit of the present invention according to the above embodiment, and make different extensions and changes, but do not depart from the spirit of the present invention, all of which are within the protection scope of the present invention.
Claims (3)
1. A non-invasive electrical equipment automatic identification device, characterized by comprising:
the current mutual inductance acquisition module is connected with the power main line and converts large current in the power main line into small current signals;
the voltage mutual inductance acquisition module is connected with the power main line and converts large voltage in the power main line into small voltage signals;
the current output end and the voltage output end of the current mutual inductance acquisition module and the voltage mutual inductance acquisition module are respectively connected with the microcontroller module, and the microcontroller module is used for acquiring the current value of the current mutual inductance acquisition module after being scaled down and the voltage value of the voltage mutual inductance acquisition module after being scaled down;
and the data concentrator module is connected with the microcontroller module and is used for forming the electric appliance characteristic parameters sent by the microcontroller module into a training set and generating a decision tree according to the data training set, wherein the decision tree is used for identifying the current working electric equipment.
2. The non-invasive consumer automatic identification apparatus of claim 1, wherein: the current mutual inductance acquisition module comprises a current transformer, two current acquisition ends of the current transformer are connected with an electric power main line, a sampling resistor R1 is connected between a first current output end A0 and a second current output end A0 of the current transformer, and the second current output end A0 is connected with the microcontroller module;
the circuit also comprises a bias resistor R2 and a bias resistor R3 which are connected in series, wherein the input ends of the bias resistor R2 and the bias resistor R3 which are connected in series are connected with a power supply, and the output ends of the bias resistor R2 and the bias resistor R3 which are connected in series are grounded;
one end of a sampling resistor R1 connected with the first current output end is grounded through a capacitor C1, and the first current output end of the current transformer is also connected between a bias resistor R2 and a bias resistor R3.
3. The non-invasive consumer automatic identification apparatus of claim 1, wherein: the voltage mutual inductance acquisition module comprises a voltage transformer, a voltage wiring terminal on the voltage transformer is connected with a large-current wiring terminal, the voltage transformer is connected with a power main line through the large-current wiring terminal, and a resistor R7 is connected in series between a second voltage wiring terminal on the voltage transformer and the large-current wiring terminal;
a sampling resistor R4 is connected between a first voltage output end A1 and a second voltage output end of the voltage transformer, wherein the first voltage output end A1 is connected with the microcontroller module;
the circuit also comprises a bias resistor R5 and a bias resistor 6 which are connected in series, wherein the input ends of the bias resistor R5 and the bias resistor R6 which are connected in series are connected with a power supply, and the output ends of the bias resistor R5 and the bias resistor R6 which are connected in series are grounded;
one end of a sampling resistor R4 connected with the second voltage output end is grounded through a capacitor C2, and the second voltage output end of the voltage transformer is also connected between a bias resistor R5 and a bias resistor R6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201921710023.6U CN210954205U (en) | 2019-10-12 | 2019-10-12 | Non-invasive automatic identification device for electric equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201921710023.6U CN210954205U (en) | 2019-10-12 | 2019-10-12 | Non-invasive automatic identification device for electric equipment |
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| Publication Number | Publication Date |
|---|---|
| CN210954205U true CN210954205U (en) | 2020-07-07 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201921710023.6U Expired - Fee Related CN210954205U (en) | 2019-10-12 | 2019-10-12 | Non-invasive automatic identification device for electric equipment |
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| Country | Link |
|---|---|
| CN (1) | CN210954205U (en) |
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2019
- 2019-10-12 CN CN201921710023.6U patent/CN210954205U/en not_active Expired - Fee Related
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Granted publication date: 20200707 Termination date: 20211012 |