CN103777624A - Photovoltaic lighting controller intelligent detection system - Google Patents
Photovoltaic lighting controller intelligent detection system Download PDFInfo
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- CN103777624A CN103777624A CN201310622777.7A CN201310622777A CN103777624A CN 103777624 A CN103777624 A CN 103777624A CN 201310622777 A CN201310622777 A CN 201310622777A CN 103777624 A CN103777624 A CN 103777624A
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Abstract
The invention discloses a photovoltaic lighting controller intelligent detection system, which is designed for solving the technical problems that a conventional method involves firstly reading data such as current, voltage and the like through a data collector, then manually observing hundreds of thousands of the data piece by piece, and afterwards, carrying out analyzing and determining to obtain a detection result such that not only are enormous manpower and time saved, a determination result is also directly related with the level and experience of a detector, the detection is not standardized, and the like. The detection system is mainly composed of two parts, i.e., an intelligent control instrument and a detection software system. Through the intelligent control instrument, the detection data of the current and voltage of a controller is acqured, and whether various important technical indicators of the controller are qualified or not is automatically detected, so that a computer can automatically determine whether the controller accords with requirements; and at the same time, a controller detection report is automatically printed and outputted. The photovoltaic lighting controller intelligent detection system changes a conventional detection method dependent on manual observation and analysis, saves enormous manpower and time, and greatly improves the working efficiency and working quality.
Description
Technical field
The present invention relates to a kind of intelligent checking system, relate in particular to a kind of intelligent checking system of photovoltaic lighting controller.This detection system is mainly used in the detection of the controller of solar energy illuminating products such as detecting single load, two load and power station.
Background technology
At present the detection method of controller is just passed through to the data such as data acquisition unit read current, voltage, a large amount of data usually reach hundreds of thousands, then observe one by one these data by experienced testing staff, judgement need test item to mistake, a large amount of manpowers and time are not only wasted, and judged result and testing staff's level and experience have direct relation, very lack of standardization.
Summary of the invention
The present invention is in order to solve existing detection method just by data such as data acquisition unit read current, voltages, again by after manually hundreds of thousands data being observed one by one, analyze judgement and draw testing result, a large amount of manpowers and time are not only wasted, and judged result and testing staff's level and experience have direct relation, the technical matters such as very lack of standardization, a kind of intelligent inspection system of photovoltaic lighting controller is provided, and this detection system is mainly made up of intelligent controller and detection software systems two parts.
Described intelligent controller, formed by data acquisition module, control module and serial port module, wherein data acquisition module amplifies through amplifier the analog signals gathering from solar illuminating system controller is regulated, again by amplify after signal through digital to analog converter, simulating signal is converted to digital signal; Described control module, is responsible for system parameters, sends data and data-transmission channel control to host computer; Described serial port module, is connected the primary processor that detection software systems are housed by serial communication interface with intelligent controller.
Described detection software systems, bear by primary processor the digital signal collecting are processed; Mainly by detecting data read-in process, the data that gather being completed by test item intelligent decision process and the large step of o controller final detection result three; Specific implementation process is as follows.
(1) data that convert simulating signal to digital signal by serial communication interface are directly read in higher level lanquage variable.
(2) adopt intelligent Artificial Neural Network to detect, can adopt BP neural network or other can realize the neural net method of classification judgement.First carry out e-learning; and then carry out classification and Detection; test item comprises one by one: charging process, over-charge protective, discharge process, discharge time, Cross prevention, mistake are put nine projects such as recovery, trickle charge, light-operated starting duty voltage, light-operated disconnecting consumers voltage; finally pass through advanced language programming; realize the automatic decision whether controller is qualified, step is as follows.
1) network learning procedure.
A. determine respectively scope, type and the detection number of times of the above-mentioned electric current of test item one by one and magnitude of voltage.
B. determine the type of BP neural network, determine the number of plies, input layer number, output layer number, middle layer number of network etc.
C. select learning sample, select multiple controller products of known good, gather respectively electric current and the magnitude of voltage of nine projects, repeated sampling goes out multiple qualified controller samples; Select known underproof multiple controller products again, gather respectively electric current and the magnitude of voltage of nine projects, repeated sampling goes out multiple defective controller samples.
D. determine network parameter values, by BP network definite in the sample input b selecting in c, for qualified sample, make nine output valves all equal 1 respectively, for underproof sample, make nine output valves all equal zero respectively; Finally, by e-learning, determine the parameter value of network.
2) testing process:
Gather electric current and the magnitude of voltage of controller to be detected, input in above-mentioned definite BP neural network, it is qualified that network output valve equals 1 detection, and null Xiang Zewei is defective; If output valve all equals 1, this controller is specification product, otherwise is substandard product.
(3) testing result of each test item is formed to examining report, automatically show and printout.
Feature of the present invention and beneficial effect: by the detection data of intelligent controller acquisition controller electric current and voltage, whether automatically detect the every important technology qualified of controller, whether meet the requirements thereby computing machine automatic decision goes out controller; Automatic printing o controller examining report simultaneously.Change the detection method of leaning at present manual observation, analysis, saved a large amount of manpowers and time, greatly improved work efficiency and work quality.
Accompanying drawing explanation
Fig. 1 structural representation of the present invention.
The structural representation of intelligent controller in Fig. 2 the present invention.
The structural representation of data acquisition module in Fig. 3 the present invention.
In Fig. 4 the present invention, detect the BP neural network learning process basic flow sheet of software systems.
In Fig. 5 the present invention, detect the BP neural network testing process basic flow sheet of software systems.
Embodiment
Referring to Fig. 1-Fig. 5, intelligent inspection system of photovoltaic lighting controller, is mainly made up of intelligent controller and detection software systems two parts.
Described intelligent controller, formed by data acquisition module, control module and serial port module, wherein data acquisition module amplifies through amplifier the analog signals gathering from solar lighting controller system is regulated, again by amplify after signal through digital to analog converter, simulating signal is converted to digital signal; Described control module, is responsible for system parameters, sends data and data-transmission channel control to host computer; Described serial port module, is connected the primary processor that detection software systems are housed by serial communication interface with intelligent controller.
Described detection software systems, bear by primary processor the digital signal collecting are processed; Mainly by detecting data read-in process, the data that gather being completed by test item intelligent decision process and the large step of o controller final detection result three; Specific implementation process is as follows.
(1) data that convert simulating signal to digital signal by serial communication interface are directly read in higher level lanquage variable.
(2) adopt intelligent Artificial Neural Network to detect, can adopt BP neural network or other can realize the neural net method of classification judgement.First carry out e-learning; and then carry out classification and Detection; test item comprises one by one: charging process, over-charge protective, discharge process, discharge time, Cross prevention, mistake are put nine projects such as recovery, trickle charge, light-operated starting duty voltage, light-operated disconnecting consumers voltage; finally pass through advanced language programming; realize the automatic decision whether controller is qualified, step is as follows.
1) network learning procedure.
A. determine respectively scope, type and the detection number of times of the above-mentioned electric current of test item one by one and magnitude of voltage.
B. determine the type of BP neural network, determine the number of plies, input layer number, output layer number, middle layer number of network etc.
C. select learning sample, select multiple controller products of known good, gather respectively electric current and the magnitude of voltage of nine projects, repeated sampling goes out multiple qualified controller samples; Select known underproof multiple controller products again, gather respectively electric current and the magnitude of voltage of nine projects, repeated sampling goes out multiple defective controller samples.
D. determine network parameter values, by BP network definite in the sample input b selecting in c, for qualified sample, make nine output valves all equal 1 respectively, for underproof sample, make nine output valves all equal zero respectively; Finally, by e-learning, determine the parameter value of network.
2) testing process
Gather electric current and the magnitude of voltage of controller to be detected, input in above-mentioned definite BP neural network, it is qualified that network output valve equals 1 detection, and null Xiang Zewei is defective; If output valve all equals 1, this controller is specification product, otherwise is substandard product.
(3) testing result of each test item is formed to examining report, automatically show and printout.
Embodiment
Referring to Fig. 1, can find out that solar panel, accumulator, load, controller in Fig. 1 are solar illuminating system, intelligent inspection system of photovoltaic lighting controller is mainly made up of intelligent controller and detection software systems two parts, is connected with solar lighting controller system by intelligent controller.Concrete connected mode is: the controller of photovoltaic system is responsible for controlling the charging and discharging time, overcharge and Cross prevention, the functions such as light-operated starting and disconnection, respectively with solar panel, accumulator, load and intelligent controller are connected, solar panel is connected with intelligent controller with controller, accumulator is connected with intelligent controller with controller, controller is connected with load, solar panel is used for charging a battery, accumulator is used for to load discharge, intelligent controller respectively with solar panel, accumulator, controller, load and detection software systems are connected, for gathering the voltage and current of solar panel, the voltage and current of accumulator, the voltage and current of load, and the data that gather are controlled and transmitted, detect software systems and be connected with intelligent controller, carry out communication by serial ports.
(1) intelligent controller
Referring to Fig. 2, intelligent controller is made up of data acquisition module, control module and serial port module.After the analog signals that wherein data acquisition module will gather regulates, amplify through amplifier, then by the signal after amplifying through digital to analog converter, analog quantity is converted to digital quantity, process after gathering its value by primary processor; Acquisition principle is referring to Fig. 3.Control module is responsible for system parameters, is sent data and data-transmission channel etc. to host computer; Serial communication interface is connected host computer with slave computer.
(2) detect software systems
Referring to Fig. 4, be connected with host computer by serial ports, the detection data of Read Controller electric current and voltage, directly read in data in higher level lanquage variable, carry out by higher level lanquage the automatic detection whether controller is qualified.Test item comprises one by one: charging process, over-charge protective, discharge process, discharge time, Cross prevention, mistake are put recovery, trickle charge, light-operated starting duty voltage, light-operated disconnecting consumers voltage, charge efficiency etc., adopt neural net method, automatically detect the above-mentioned every important technology qualified of controller or defective, wherein have one defectively to think that controller is defective; Whether computing machine automatic decision goes out controller and meets the requirements; Then testing result and excel table is connected, automatically demonstrates misdata and the type of makeing mistakes, finally automatically show and print the examining report that whether each test item is qualified and whether controller is qualified.
Claims (1)
1. intelligent inspection system of photovoltaic lighting controller, is characterized in that: be mainly made up of intelligent controller and intelligent software detection system two parts:
Described intelligent controller, formed by data acquisition module, control module and serial port module, wherein data acquisition module amplifies through amplifier the analog signals gathering from solar illuminating system controller is regulated, again by amplify after signal through digital to analog converter, simulating signal is converted to digital signal; Described control module, is responsible for system parameters, sends data and data-transmission channel control to host computer; Described serial port module, is connected the primary processor that detection software systems are housed by serial communication interface with intelligent controller;
Described detection software systems, bear by primary processor the digital signal collecting are processed; Mainly by detecting data read-in process, the data that gather being completed by test item intelligent decision process and the large step of o controller final detection result three; First the data that convert simulating signal to digital signal by serial communication interface are directly read in higher level lanquage variable; then adopt intelligent Artificial Neural Network to detect; can adopt BP neural network or other can realize the neural net method of classification judgement; classification and Detection project comprises: charging process, over-charge protective, discharge process, discharge time, Cross prevention, mistake are put the projects such as recovery, trickle charge, light-operated starting duty voltage, light-operated disconnecting consumers voltage; finally realize the automatic decision whether controller is qualified, show and printout.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110320897A (en) * | 2019-08-15 | 2019-10-11 | 厦门城光联链科技有限公司 | A kind of solar street lamp controller production test tooling and test method |
| CN117193258A (en) * | 2023-10-10 | 2023-12-08 | 朗戈智能系统(上海)有限公司 | Automatic detection method, equipment and computer readable medium for light-operated controller |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101763094A (en) * | 2009-12-11 | 2010-06-30 | 沈阳工程学院 | Intelligent inspection system of photovoltaic lighting controller |
| CN101925231A (en) * | 2010-07-30 | 2010-12-22 | 李钢 | Intelligent device for tracking, controlling and managing energy efficiency of illumination |
| CN102548147A (en) * | 2011-03-16 | 2012-07-04 | 泰州祥和新能源科技有限公司 | Control system applied to wind energy photovoltaic power supply illumination |
| CN102778644A (en) * | 2012-07-20 | 2012-11-14 | 汕头大学 | Device and method for detecting performance of solar illuminating system |
| CN103344857A (en) * | 2013-06-28 | 2013-10-09 | 辽宁太阳能研究应用有限公司 | Solar photovoltaic charging and discharging controller large current detection system |
-
2014
- 2014-02-26 CN CN201310622777.7A patent/CN103777624A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101763094A (en) * | 2009-12-11 | 2010-06-30 | 沈阳工程学院 | Intelligent inspection system of photovoltaic lighting controller |
| CN101925231A (en) * | 2010-07-30 | 2010-12-22 | 李钢 | Intelligent device for tracking, controlling and managing energy efficiency of illumination |
| CN102548147A (en) * | 2011-03-16 | 2012-07-04 | 泰州祥和新能源科技有限公司 | Control system applied to wind energy photovoltaic power supply illumination |
| CN102778644A (en) * | 2012-07-20 | 2012-11-14 | 汕头大学 | Device and method for detecting performance of solar illuminating system |
| CN103344857A (en) * | 2013-06-28 | 2013-10-09 | 辽宁太阳能研究应用有限公司 | Solar photovoltaic charging and discharging controller large current detection system |
Non-Patent Citations (2)
| Title |
|---|
| 刘福才 等: "基于VC和无线数传模块的光伏电站远程监控系统的设计", 《工业控制计算机》 * |
| 王国义 等: "PWM充电策略在光伏照明系统中的应用", 《自动化与仪器仪表》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110320897A (en) * | 2019-08-15 | 2019-10-11 | 厦门城光联链科技有限公司 | A kind of solar street lamp controller production test tooling and test method |
| CN117193258A (en) * | 2023-10-10 | 2023-12-08 | 朗戈智能系统(上海)有限公司 | Automatic detection method, equipment and computer readable medium for light-operated controller |
| CN117193258B (en) * | 2023-10-10 | 2024-05-07 | 朗戈智能系统(上海)有限公司 | Automatic detection method, equipment and computer readable medium for light-operated controller |
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Application publication date: 20140507 |