CN111931388A - LED street lamp operation analysis system and method based on big data - Google Patents
LED street lamp operation analysis system and method based on big data Download PDFInfo
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Abstract
The invention discloses an LED street lamp operation analysis system and method based on big data, wherein the operation analysis system comprises: collecting lamp parameter information and geographical environment information, monitoring the LED street lamp in real time through a lamp operation monitoring module, carrying out equipment service life simulation and 3D lighting simulation according to device information and an installation area selected by a user, carrying out comprehensive economic analysis on factors such as a simulation result, price and the like, and displaying the factors to the user. According to the invention, the data of the LED street lamp in actual use is acquired by using the LED street lamp Internet of things platform, the LED lamp selected by a user is subjected to equipment life simulation and 3D lighting simulation, comprehensive economic analysis is carried out according to the design scheme of the user, and an economic analysis report is generated to assist the user in designing and making decisions when comparing various LED street lamps.
Description
Technical Field
The invention relates to the field of big data technical analysis, in particular to an LED street lamp operation analysis system and method based on big data.
Background
With the development of LED street lamp technology, more and more cities are beginning to adopt LED street lamps instead of sodium lamps. The development of cities promotes the increase of street lamp types and the expansion of application ranges. Street lamps are needed to illuminate not only on public roads but also in urban areas such as streets, tunnels, subways, parks and the like. And the operation condition of the LED street lamp is needed to be analyzed by the LED street lamp operation analysis system when the street lamp is laid in a large range. When a city or a business decides to use a certain brand of LED street lamps, various factors need to be considered to help the selection. The establishment and perfection of the LED street lamp operation analysis system has been developed into a problem which must be solved.
Currently, the LED street lamp system in the prior art is biased to control and manage the LED street lamp, and the brightness and the on-off of the street lamp are adjusted according to the requirement. In the prior art, the calculation of the service life of a lamp is generally based on a service life curve provided by a lamp manufacturer for analysis, the theoretical service life of an LED lighting product is generally over tens of thousands of hours, but the theoretical service life of the LED lighting product is often shorter than the theoretical service life in actual use, and the actual service life of the LED lighting product is influenced by the environment such as temperature, precipitation, unstable voltage and the like. The prior art lacks a study of the practical service life of LED lighting products. Moreover, when a city or an enterprise selects an LED street lamp, it is necessary to refer to various factors such as actual service life, illuminance brightness, price, stability of operation under special conditions, and the like, and a corresponding economic operation analysis tool is lacked to help a decision maker to perform comprehensive consideration. Therefore, it is necessary to establish and perfect an operation analysis system of the LED street lamp.
Disclosure of Invention
The invention provides an LED street lamp operation analysis system and method based on big data, and aims to solve the technical problems that in the prior art, research on the actual service life of an LED illumination product is lacked, and a decision maker is helped to carry out comprehensive consideration due to the lack of a corresponding economic operation analysis tool when an LED street lamp is selected.
The invention comprises an LED street lamp operation analysis system based on big data, comprising:
the basic information acquisition module is used for acquiring basic information, wherein the basic information comprises lamp parameter information and geographic environment information;
the lamp operation monitoring module monitors the LED street lamps which are currently managed in a networking mode in real time through the big data center, records the current operation state of the LED street lamps in each area at fixed intervals, and acquires damage information;
the device information input module is used for selecting a corresponding lamp model or inputting user-defined device information by a user and selecting an installation area;
the device life simulation module is used for receiving the information input by the device information input module, carrying out device life simulation according to the device information and the installation area and calculating the service life of the LED street lamp;
the 3D lighting simulation module comprises a streetscape simulation module and a light effect simulation module, simulates the actual lighting effect by using the light effect simulation module through adjusting simulation parameters according to device information input by a user, and records the optimal simulation scheme selected by the user;
the comprehensive economic analysis module is used for receiving simulation results of the equipment service life simulation module and the 3D illumination simulation module and selecting a corresponding economic analysis model according to requirements to comprehensively analyze the simulation results and the price of the LED street lamp;
and the economic analysis result display module is used for displaying economic analysis results of different LED street lamps.
The lamp parameter information in the basic information acquisition module comprises: the LED lamp comprises a lamp name, a lamp shape, a lamp price, a lamp brand, a lamp manufacturer and design parameters, rated current, voltage and power provided by the manufacturer, wherein devices used by the LED lamp comprise an LED lamp cap, a lamp post, a lead material, a fixing screw, a chip, a sensor, a driving power supply, a packaging material, a lens, a radiator and the like, and device information comprises the device name, the device position and the average use time of the device;
the geographic environment information comprises geographic position information acquired by a GPRS positioning system, climate and temperature information of a fixed area, a street map in the area, the length and width of each street, a street lamp use time period, a road peak time period and an idle time period, night average pedestrian flow, vehicle flow and the like.
The lamp operation monitoring module comprises: the system comprises an LED street lamp real-time monitoring module, a big data center and a lamp maintenance information statistical device; the real-time monitoring module of the LED street lamp further comprises: the system comprises a lamp basic condition counting device, a state monitor, a state monitoring device and a state monitoring device, wherein the lamp basic condition counting device is used for recording the brand, the model, the installation number and the like of the LED street lamp used in the current area; the air temperature and humidity sensor is used for detecting specific parameter data of air temperature and humidity; illumination monitoring equipment: an illumination sensor is additionally arranged to monitor an external illumination signal; the environment monitoring equipment is used for monitoring severe weather conditions such as sand dust, dense fog, PM10, rainfall and the like; the multifunctional electric energy meter remotely collects the on-site road electricity consumption data; and abnormal operation state alarm devices, such as power supply grid fluctuation, large-scale power failure, voltage overload, major holiday voltage and current conditions and the like.
The LED street lamp real-time monitoring module collects data collected by each device, uploads the data to a big data center, and records the data into a background database according to date, time period, normal or abnormal categories; the lamp maintenance information statistical device is responsible for counting lamp damage and maintenance information, including street lamp fault information, fault reasons, specific damaged parts and devices, actual use duration, random lamp failure rate and the like.
In the device information entry module, if the corresponding lamp model selected by the user does not exist in the database, other lamps with the highest relevancy to the lamp are identified as substitutes according to the device name input by the user.
The device life simulation module comprises: the life interval prediction module predicts the life interval of the lamp according to the basic information and the real-time monitoring data of the lamp; the life curve building module simulates an actual use environment according to real-time monitoring data by using luminous flux attenuation as failure criterion, describes the service life of the lamp by using a Weibull model, and builds a lamp life curve through statistical analysis processing; the predicted value correction module is used for correcting the LED service life prediction by adopting a fuzzy evaluation method; selecting basic data information, geographical position information and running state detection information as an LED simulation element set, defining corresponding weights according to the influence degree of each element on the service life of the LED, constructing an evaluation matrix by using an analytic hierarchy process, selecting a weighted evaluation function for calculation, and obtaining a fuzzy evaluation result as a correction value.
The device life simulation module further comprises: and the major fault and special condition simulation module is used for setting an operation condition to simulate an emergency condition and calculating the stability of the lamp according to the abnormal information acquired by the big data center.
The 3D lighting simulation module includes: the street view simulation module simulates street views through the geographic environment information collected by the basic data module; the lighting effect simulation module is used for calculating the illumination and brightness of each lamp through the lamp parameter information collected by the basic data module and simulating the actual lighting effect; adjusting simulation parameters according to device information input by a user, simulating an actual illumination effect through a light effect simulation module, and storing an optimal simulation scheme selected by the user; the simulation parameters comprise lamp holder size, lamp post height, lamp post distance, lamp quantity and the like.
The integrated economic analysis module comprises: the LED street lamp quantity calculating module is used for calculating the quantity of consumed resources of the required lamps in the service time input by the user according to the service life of the LED street lamps calculated by the equipment life simulation and the quantity of street lamps required by the 3D lighting simulation; and the economic analysis module is used for generating an economic analysis report by integrating the price and the stability of the lamp, and a user can adjust the service life, the illumination brightness, the price and the stability weight in the economic analysis model according to the requirement and score and sort the economic analysis results.
The economic analysis result display module comprises: the device display module is used for matching the two-dimensional shape or the three-dimensional shape of the device stored in the operation analysis system according to the device information input by the user and displaying the two-dimensional shape or the three-dimensional shape of the device on display equipment of the user; an assistant decision module: the economic analysis results obtained from the device information entered by the user are displayed in a manner including, but not limited to, a graph.
The invention also comprises an LED street lamp operation analysis method based on big data, which comprises the following steps:
step 1, collecting basic information, wherein the basic information comprises lamp parameter information and geographic environment information;
step 2, monitoring the operation of the lamp, namely monitoring the LED street lamp which is currently managed in a networking mode in real time through a big data center, recording the current operation state of the LED street lamp in each area at fixed intervals, and acquiring damage information;
step 3, inputting device information, wherein a user selects a corresponding lamp model or inputs custom device information, and selects an installation area;
step 4, simulating the service life of the equipment, namely simulating the service life of the equipment according to the device information and the installation area, and calculating the service life of the LED street lamp;
step 5,3D lighting simulation, including street view simulation and light effect simulation, simulating the actual lighting effect by using a light effect simulation module through adjusting simulation parameters according to device information input by a user, and recording an optimal simulation scheme selected by the user;
step 6, carrying out comprehensive economic analysis, namely selecting a corresponding economic analysis model according to the requirement to carry out comprehensive analysis on the simulation result and the price of the LED street lamp;
and 7, displaying the economic analysis result, and displaying the economic analysis results of different LED street lamps.
In step 1, the lamp parameter information includes: the LED lamp comprises a lamp name, a lamp shape, a lamp price, a lamp brand, a lamp manufacturer and design parameters, rated current, voltage and power provided by the manufacturer, wherein devices used by the LED lamp comprise an LED lamp cap, a lamp post, a lead material, a fixing screw, a chip, a sensor, a driving power supply, a packaging material, a lens, a radiator and the like, and device information comprises the device name, the device position and the average use time of the device;
the geographic environment information comprises geographic position information acquired by a GPRS positioning system, climate and temperature information of a fixed area, a street map in the area, the length and width of each street, a street lamp use time period, a road peak time period and an idle time period, night average pedestrian flow, vehicle flow and the like.
The step 2 of monitoring the LED street lamp which is currently managed in a networking mode in real time through the big data center comprises the following steps: recording the brand, the model, the installation number and the like of the LED street lamp used in the current area;
the recording of the current running state of the LED street lamps in each area comprises the following steps: detecting alternating current input voltage, current and equipment temperature of the street lamp circuit in a normal state through a state monitor; detecting specific parameter data of air temperature and humidity through an air temperature and humidity sensor; by the illumination monitoring device: an illumination sensor is additionally arranged to monitor an external illumination signal; monitoring severe weather conditions such as sand dust, dense fog, PM10, rainfall and the like through environment monitoring equipment; the method comprises the steps of remotely acquiring field road power consumption data through a multifunctional electric energy meter; acquiring abnormal operation state information including power supply grid fluctuation, large-scale power failure, voltage overload, major holiday voltage and current conditions and the like; collecting and uploading the collected data to a big data center, and recording the collected data into a background database according to date, time period, normal or abnormal categories;
and collecting maintenance information, including statistics of lamp damage and maintenance information, including street lamp fault information, fault reasons, specific damaged parts and devices, actual use duration, random lamp failure rate and the like.
And 3, when the device information is recorded in the step 3, if the corresponding lamp model selected by the user does not exist in the database, identifying other lamps with the highest relevance with the lamp as substitutes according to the device name input by the user.
The step 4 of performing the device life simulation includes:
step 4.1, predicting the service life interval of the lamp according to the basic information and the real-time monitoring data of the lamp;
step 4.2, utilizing luminous flux attenuation as a failure criterion, simulating an actual use environment according to real-time monitoring data, describing the service life of the lamp by using a Weibull model, and constructing a lamp service life curve through statistical analysis processing;
4.3, correcting the service life prediction of the LED by adopting a fuzzy evaluation method; selecting basic data information, geographical position information and running state detection information as an LED simulation element set, defining corresponding weights according to the influence degree of each element on the service life of the LED, constructing an evaluation matrix by using an analytic hierarchy process, selecting a weighted evaluation function for calculation, and obtaining a fuzzy evaluation result as a correction value.
The device life simulation further comprises: and (4) performing simulation on major faults and special conditions, setting operation conditions to simulate emergency conditions according to the abnormal information acquired by the big data center, and calculating the stability of the lamp.
The 3D lighting simulation in step 5 comprises:
simulating street scenes through the geographic environment information collected by the basic data module; calculating the illumination and brightness of each lamp through lamp parameter information collected by the basic data module, and simulating the actual light effect; adjusting simulation parameters according to device information input by a user, simulating an actual illumination effect through a light effect simulation module, and storing an optimal simulation scheme selected by the user; the simulation parameters comprise lamp holder size, lamp post height, lamp post distance, lamp quantity and the like.
The performing of the comprehensive analysis in step 6 comprises: calculating the consumption resource quantity of the lamps required in the service time input by the user according to the service life of the LED street lamps calculated by the equipment life simulation and the quantity of street lamps required by the 3D lighting simulation; and an economic analysis report is generated by integrating the price and the stability of the lamp, and a user can adjust the service life, the illumination brightness, the price and the stability weight in the economic analysis model according to the requirement and score and sort the economic analysis results.
The economic analysis result display in the step 7 comprises the following steps: matching a two-dimensional shape or a three-dimensional shape of the device stored in the operation analysis system according to device information input by a user, and displaying the two-dimensional shape or the three-dimensional shape of the device on display equipment of the user; and displaying the economic analysis result obtained by the device information input by the user.
According to the invention, the data of the LED street lamp in actual use is acquired by using the LED street lamp Internet of things platform, the LED lamp selected by a user is subjected to equipment life simulation and 3D lighting simulation, comprehensive economic analysis is carried out according to the design scheme of the user, and an economic analysis report is generated to assist the user in designing and making decisions when comparing various LED street lamps.
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Fig. 1 is a system framework of an LED street lamp operation analysis system based on big data.
Detailed Description
The content of the invention will now be discussed with reference to a number of exemplary embodiments. It is to be understood that these examples are discussed only to enable those of ordinary skill in the art to better understand and thus implement the teachings of the present invention, and are not meant to imply any limitations on the scope of the invention.
As used herein, the term "include" and its variants are to be read as open-ended terms meaning "including, but not limited to. The term "based on" is to be read as "based, at least in part, on". The terms "one embodiment" and "an embodiment" are to be read as "at least one embodiment". The term "another embodiment" is to be read as "at least one other embodiment".
As shown in fig. 1, in a preferred embodiment of the present invention, an LED street lamp operation analysis system based on big data mainly includes:
s01, a basic information acquisition module, wherein the basic information comprises lamp parameter information and geographical environment information.
Wherein the luminaire parameter information comprises: lamp name, lamp shape, lamp price, lamp brand, design parameters, rated current, voltage and power provided by manufacturers.
Meanwhile, the main components of the LED lighting lamp comprise a light source, a driving power supply, a package, a lens, a radiator and the like, the service life of the LED lighting lamp is usually determined by the design of the light source, the driving power supply and the heat dissipation part, the service life of the LED lighting lamp is influenced by the failure of any part, and the collection of device information is beneficial to lamp matching and service life analysis in the later stage. Hence the luminaire parameter information further comprises: the LED lamp comprises devices such as an LED lamp cap, a lamp post, lead materials, fixing screws, a chip, a sensor, a driving power supply, packaging materials, a lens, a radiator and the like, wherein device information comprises a device name, a device position and device average service life;
the basic information acquisition module can also comprise a device information management module which is used for inputting, editing and storing the device information. The device information of each device used by the common LED street lamp in the market is recorded, and after the recording is finished, the device information management module can store the device information. When the device information needs to be called again, the device information can be directly called for use.
The geographic environment information comprises geographic position information acquired by a GPRS positioning system, and climate and temperature information of a fixed area, a street map in the area, the length and width of each street, a street lamp use time period, a road peak time period and an idle time period, night average pedestrian flow, vehicle flow and the like. The street lamp placement requirements of different areas can be collected more accurately when a simulation model is established, and decision making is assisted.
And S02, the lamp operation monitoring module monitors the LED street lamps which are currently managed in a networking mode in real time through the big data center, records the current operation state of the LED street lamps in each area at fixed intervals and collects damage information.
The lamp operation monitoring module is realized based on the Internet of things of the LED street lamp and comprises an LED street lamp real-time monitoring module, a big data center and a lamp maintenance information statistical device;
the real-time monitoring module of the LED street lamp comprises: the lamp basic condition statistics device records the brand, the model, the installation number and the like of the LED street lamp used in the current area;
the state monitor is used for detecting the alternating current input voltage, the alternating current and the equipment temperature of the street lamp circuit in a normal state;
the air temperature and humidity sensor is used for detecting specific parameter data of air temperature and humidity;
the illumination monitoring equipment is additionally provided with an illumination sensor and is used for monitoring an external illumination signal;
the environment monitoring equipment is used for monitoring severe weather conditions such as sand dust, dense fog, PM10, rainfall and the like;
the multifunctional electric energy meter remotely collects the on-site road electricity consumption data;
abnormal operation state alarm devices, such as power supply grid fluctuation, large-scale power failure, voltage overload, major holiday voltage and current conditions and the like; the LED street lamp real-time monitoring module is responsible for summarizing and uploading data acquired by each device to a big data center, and recording the data into a background database according to date, time period, normal or abnormal categories;
the lamp maintenance information statistical device is responsible for counting lamp damage and maintenance information, including street lamp fault information, fault reasons, specific damaged parts and devices, actual use duration, random lamp failure rate and the like.
And S03, a device information entry module, wherein the user selects the corresponding lamp model or self-defines the input device information and selects the installation area.
The user can select one or more lamps for analysis and can also customize the lamp content to be input into the device information management module. And if the corresponding lamp type input by the user does not exist in the database, identifying other lamps with the highest relevancy to the lamp as substitutes according to the lamp device name input by the user. For example, the components that most affect the service life of the LED lamp include the driving power supply, the chip and the heat sink, and the lamp using the same type of device and similar power is searched in the database as a substitute.
And S04, the equipment life simulation module receives the information recorded by the device information recording module, performs equipment life simulation according to the device information and the installation area, and calculates the service life of the LED street lamp.
The device life simulation module comprises: and the life interval prediction module predicts the life interval of the lamp according to the basic information and the real-time monitoring data of the lamp.
And the life curve building module simulates an actual use environment according to real-time monitoring data by using luminous flux attenuation as a failure criterion, describes the service life of the lamp by using a Weibull model, and builds a lamp life curve through statistical analysis processing.
The predicted value correction module is used for correcting the LED service life prediction by adopting a fuzzy evaluation method; selecting basic data information, geographical position information and running state detection information as an LED simulation element set, defining corresponding weights according to the influence degree of each element on the service life of the LED, constructing an evaluation matrix by using an analytic hierarchy process, selecting a weighted evaluation function for calculation, and obtaining a fuzzy evaluation result as a correction value.
In an embodiment, the device lifetime simulation module may further include: and the major fault and special condition simulation module is used for setting an operation condition to simulate an emergency condition and calculating the stability of the lamp according to the abnormal information acquired by the big data center. For example, important festival data in a big data center is analyzed, and the stability of similar lamps is estimated by the influence of power grid fluctuation caused by power demand change on the street lamp illumination and the device damage rate of the area.
And S05, the 3D lighting simulation module comprises a street view simulation module and a light effect simulation module, the light effect simulation module is used for simulating the actual lighting effect by adjusting the simulation parameters according to the device information input by the user, and the optimal simulation scheme selected by the user is recorded.
The 3D lighting simulation module specifically comprises: and the street view simulation module simulates street views through the geographic environment information collected by the basic data module.
The lighting effect simulation module calculates the illumination and brightness of each lamp through the lamp parameter information collected by the basic data module, and simulates the actual lighting effect; according to device information input by a user, analog parameters such as lamp holder size, lamp post height, lamp post distance and lamp quantity are adjusted, the actual illumination effect is simulated through the light effect simulation module, the user is assisted to design the street lamp light more intuitively, and the optimal simulation scheme selected by the user is saved after simulation is finished.
And S06, the comprehensive economic analysis module receives the simulation results of the equipment service life simulation module and the 3D lighting simulation module, and selects a corresponding economic analysis model according to the requirements to comprehensively analyze the simulation results and the price of the LED street lamp.
The comprehensive economic analysis module comprises: the LED street lamp quantity calculating module is used for calculating the quantity of consumed resources of the required lamps in the service time input by the user according to the service life of the LED street lamps calculated by the equipment life simulation and the quantity of street lamps required by the 3D lighting simulation;
and the economic analysis module is used for generating an economic analysis report by integrating the price and the stability of the lamp, and a user can adjust the predicted service life, the power consumption, the price of the LED lamp, the maintenance cost and the stability weight in the economic analysis model according to the requirement and sort the economic analysis results.
Each evaluation index can be represented as an N-dimensional vector:
，
the ith evaluation index is shown, and N is the number of the evaluation indexes.
The embodiment of the invention adopts the following formula:
and performing weighted calculation on each evaluation index, wherein,
and (4) for evaluating the weight vector of the set, and Score for comprehensive economic evaluation Score, and finally sorting the calculation results according to the comprehensive economic evaluation Score. The user can adjust the weights according to actual requirements to obtain the desired ranking.
And S07, the economic analysis result display module displays the economic analysis results of different LED street lamps.
The economic analysis result display module comprises: the device display module is used for matching the two-dimensional shape or the three-dimensional shape of the device stored in the operation analysis system according to the device information input by the user and displaying the two-dimensional shape or the three-dimensional shape of the device on display equipment of the user;
and the auxiliary decision module is used for displaying the economic analysis result obtained by the device information input by the user, and the economic analysis result includes but is not limited to displaying the predicted service life, the power consumption, the price of the LED lamp, the maintenance cost and the stability calculated by the system to the user in a chart form so as to assist the user in making decisions.
The invention also provides an LED street lamp operation analysis method based on big data, which comprises the following steps:
step 1, collecting basic information, wherein the basic information comprises lamp parameter information and geographic environment information;
step 2, monitoring the operation of the lamp, namely monitoring the LED street lamp which is currently managed in a networking mode in real time through a big data center, recording the current operation state of the LED street lamp in each area at fixed intervals, and acquiring damage information;
step 3, inputting device information, wherein a user selects a corresponding lamp model or inputs custom device information, and selects an installation area;
step 4, simulating the service life of the equipment, namely simulating the service life of the equipment according to the device information and the installation area, and calculating the service life of the LED street lamp;
step 5,3D lighting simulation, including street view simulation and light effect simulation, simulating the actual lighting effect by using a light effect simulation module through adjusting simulation parameters according to device information input by a user, and recording an optimal simulation scheme selected by the user;
step 6, carrying out comprehensive economic analysis, namely selecting a corresponding economic analysis model according to the requirement to carry out comprehensive analysis on the simulation result and the price of the LED street lamp;
and 7, displaying the economic analysis result, and displaying the economic analysis results of different LED street lamps.
In step 1, the lamp parameter information includes: the LED lamp comprises a lamp name, a lamp shape, a lamp price, a lamp brand, a lamp manufacturer and design parameters, rated current, voltage and power provided by the manufacturer, wherein devices used by the LED lamp comprise an LED lamp cap, a lamp post, a lead material, a fixing screw, a chip, a sensor, a driving power supply, a packaging material, a lens, a radiator and the like, and device information comprises the device name, the device position and the average use time of the device;
the geographic environment information comprises geographic position information acquired by a GPRS positioning system, and climate and temperature information of a fixed area, a street map in the area, the length and width of each street, a street lamp use time period, a road peak time period and an idle time period, night average pedestrian flow, vehicle flow and the like.
The step 2 of monitoring the LED street lamp which is currently managed in a networking mode in real time through the big data center comprises the following steps: recording the brand, the model, the installation number and the like of the LED street lamp used in the current area;
the recording of the current running state of the LED street lamps in each area comprises the following steps: detecting alternating current input voltage, current and equipment temperature of the street lamp circuit in a normal state through a state monitor; detecting specific parameter data of air temperature and humidity through an air temperature and humidity sensor; by the illumination monitoring device: an illumination sensor is additionally arranged to monitor an external illumination signal; monitoring severe weather conditions such as sand dust, dense fog, PM10, rainfall and the like through environment monitoring equipment; the method comprises the steps of remotely acquiring field road power consumption data through a multifunctional electric energy meter; acquiring abnormal operation state information, such as power supply grid fluctuation, large-scale power failure, voltage overload, major holiday voltage and current conditions and the like; collecting and uploading the collected data to a big data center, and recording the collected data into a background database according to date, time period, normal or abnormal categories;
and collecting maintenance information, including statistics of lamp damage and maintenance information, including street lamp fault information, fault reasons, specific damaged parts and devices, actual use duration, random lamp failure rate and the like.
And 3, when the device information is input in the step 3, if the corresponding lamp model selected by the user does not exist in the database, identifying other lamps with the highest relevance with the lamp as substitutes according to the device name input by the user.
The simulation of the service life of the equipment in the step 4 comprises the following steps:
step 4.1, predicting the service life interval of the lamp according to the basic information and the real-time monitoring data of the lamp;
step 4.2, utilizing luminous flux attenuation as a failure criterion, simulating an actual use environment according to real-time monitoring data, describing the service life of the lamp by using a Weibull model, and constructing a lamp service life curve through statistical analysis processing;
4.3, correcting the service life prediction of the LED by adopting a fuzzy evaluation method; selecting basic data information, geographical position information and running state detection information as an LED simulation element set, defining corresponding weights according to the influence degree of each element on the service life of an LED, constructing an evaluation matrix by using an analytic hierarchy process, selecting a weighted evaluation function for calculation, and obtaining a fuzzy evaluation result as a correction value;
the simulation of the service life of the equipment further comprises the following steps: and (4) performing simulation on major faults and special conditions, setting operation conditions to simulate emergency conditions according to the abnormal information acquired by the big data center, and calculating the stability of the lamp.
The 3D lighting simulation in step 5 comprises:
simulating street scenes through the geographic environment information collected by the basic data module; calculating the illumination and brightness of each lamp through lamp parameter information collected by the basic data module, and simulating the actual light effect; adjusting simulation parameters according to device information input by a user, simulating an actual illumination effect through a light effect simulation module, and storing an optimal simulation scheme selected by the user; the simulation parameters comprise lamp holder size, lamp post height, lamp post distance, lamp quantity and the like.
The comprehensive analysis performed in step 6 includes: calculating the consumption resource quantity of the lamps required in the service time input by the user according to the service life of the LED street lamps calculated by the equipment life simulation and the quantity of street lamps required by the 3D lighting simulation; and an economic analysis report is generated by integrating the price and the stability of the lamp, and a user can adjust the service life, the illumination brightness, the price and the stability weight in the economic analysis model according to the requirement and score and sort the economic analysis results.
Matching a two-dimensional shape or a three-dimensional shape of the device stored in the operation analysis system according to device information input by a user, and displaying the two-dimensional shape or the three-dimensional shape of the device on display equipment of the user;
the economic analysis results obtained from the device information entered by the user are displayed in a manner including, but not limited to, a graph.
The method and system of the preferred embodiment of the present invention may be implemented as pure software, such as a software program written in the Java language and based on JRE8 and the above versions of the Java runtime environment; or may be implemented as pure hardware, such as a dedicated ASIC chip or FPGA chip, as desired; it may also be implemented as a system combining software and hardware, such as a firmware system with fixed code stored thereon.
Another aspect of the invention is a computer-readable medium having computer-readable instructions stored thereon that, when executed, perform a method of embodiments of the invention.
While various embodiments of the present invention have been described above, the above description is intended to be illustrative, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The scope of the claimed subject matter is limited only by the attached claims.
Claims (18)
1. The utility model provides a LED street lamp operation analytic system based on big data which characterized in that includes:
the basic information acquisition module is used for acquiring basic information, wherein the basic information comprises lamp parameter information and geographic environment information;
the lamp operation monitoring module monitors the LED street lamps which are currently managed in a networking mode in real time through the big data center, records the current operation state of the LED street lamps in each area at fixed intervals, and acquires damage information;
the device information input module is used for selecting a corresponding lamp model or inputting user-defined device information by a user and selecting an installation area;
the device life simulation module is used for receiving the information input by the device information input module, carrying out device life simulation according to the device information and the installation area and calculating the service life of the LED street lamp;
the 3D lighting simulation module comprises a streetscape simulation module and a light effect simulation module, simulates the actual lighting effect by using the light effect simulation module through adjusting simulation parameters according to device information input by a user, and records the optimal simulation scheme selected by the user;
the comprehensive economic analysis module is used for receiving simulation results of the equipment service life simulation module and the 3D illumination simulation module and selecting a corresponding economic analysis model according to requirements to comprehensively analyze the simulation results and the price of the LED street lamp;
and the economic analysis result display module is used for displaying economic analysis results of different LED street lamps.
2. The operation analysis system according to claim 1, wherein the lamp parameter information in the basic information collection module comprises: the LED lamp comprises a lamp name, a lamp shape, a lamp price, a lamp brand, a lamp manufacturer and design parameters, rated current, voltage and power provided by the manufacturer, wherein devices used by the LED lamp comprise an LED lamp holder, a lamp post, a lead material, a fixing screw, a chip, a sensor, a driving power supply, a packaging material, a lens and a radiator device, and device information comprises the device name, the device position and the average use time of the device;
the geographic environment information comprises geographic position information acquired by a GPRS positioning system, climate and temperature information of a fixed area, a street map in the area, the length and width of each street, a street lamp use time period, a road peak time period and an idle time period, night average pedestrian flow and vehicle flow.
3. The operation analysis system according to claim 1, wherein the lamp operation monitoring module comprises: the system comprises an LED street lamp real-time monitoring module, a big data center and a lamp maintenance information statistical device;
the real-time monitoring module of the LED street lamp further comprises: the lamp basic condition statistics device records the brand, the model and the installation number of the LED street lamps used in the current area;
the state monitor is used for detecting the alternating current input voltage, the alternating current and the equipment temperature of the street lamp circuit in a normal state;
the air temperature and humidity sensor is used for detecting specific parameter data of air temperature and humidity;
the illumination monitoring equipment is additionally provided with an illumination sensor and is used for monitoring an external illumination signal;
the environment monitoring equipment is used for monitoring sand dust, dense fog, PM10 or severe rainfall weather conditions;
the multifunctional electric energy meter remotely collects the on-site road electricity consumption data;
the abnormal operation state alarm device comprises power supply network fluctuation, large-scale power failure, voltage overload and major holiday voltage and current conditions;
the LED street lamp real-time monitoring module collects data collected by each device, uploads the data to a big data center, and records the data into a background database according to date, time period, normal or abnormal categories;
the lamp maintenance information statistical device is responsible for counting lamp damage and maintenance information, including street lamp fault information, fault reasons, specific damaged parts and devices, actual use time length and random lamp failure rate.
4. The operation analysis system according to claim 1, wherein in the device information entry module, if the corresponding lamp model selected by the user does not exist in the database, other lamps with the highest degree of correlation with the lamp are identified as substitutes according to the device name input by the user.
5. The operational analysis system of claim 1, wherein the equipment life simulation module comprises:
the life interval prediction module predicts the life interval of the lamp according to the basic information and the real-time monitoring data of the lamp;
the life curve building module simulates an actual use environment according to real-time monitoring data by using luminous flux attenuation as failure criterion, describes the service life of the lamp by using a Weibull model, and builds a lamp life curve through statistical analysis processing;
the predicted value correction module is used for correcting the LED service life prediction by adopting a fuzzy evaluation method; selecting basic data information, geographical position information and running state detection information as an LED simulation element set, defining corresponding weights according to the influence degree of each element on the service life of the LED, constructing an evaluation matrix by using an analytic hierarchy process, selecting a weighted evaluation function for calculation, and obtaining a fuzzy evaluation result as a correction value.
6. The operational analysis system of claim 5, wherein the equipment life simulation module further comprises: and the major fault and special condition simulation module is used for setting an operation condition to simulate an emergency condition and calculating the stability of the lamp according to the abnormal information acquired by the big data center.
7. The operational analysis system of claim 1, wherein the 3D lighting simulation module comprises:
the street view simulation module simulates street views through the geographic environment information collected by the basic data module;
the lighting effect simulation module is used for calculating the illumination and brightness of each lamp through the lamp parameter information collected by the basic data module and simulating the actual lighting effect; adjusting simulation parameters according to device information input by a user, simulating an actual illumination effect through a light effect simulation module, and storing an optimal simulation scheme selected by the user; the simulation parameters comprise lamp holder size, lamp post height, lamp post distance and lamp quantity.
8. The operational analysis system of claim 1, wherein the synthetic economic analysis module comprises:
the LED street lamp quantity calculating module is used for calculating the quantity of consumed resources of the required lamps in the service time input by the user according to the service life of the LED street lamps calculated by the equipment life simulation and the quantity of street lamps required by the 3D lighting simulation;
and the economic analysis module is used for generating an economic analysis report by integrating the price and the stability of the lamp, and a user can adjust the service life, the illumination brightness, the price and the stability weight in the economic analysis model according to the requirement and score and sort the economic analysis results.
9. The operation analysis system according to claim 1, wherein the economic analysis result presentation module includes:
the device display module is used for matching the two-dimensional shape or the three-dimensional shape of the device stored in the operation analysis system according to the device information input by the user and displaying the two-dimensional shape or the three-dimensional shape of the device on display equipment of the user;
an assistant decision module: the economic analysis results obtained from the device information entered by the user are displayed in a manner including, but not limited to, a graph.
10. An LED street lamp operation analysis method based on big data is characterized by comprising the following steps:
step 1, collecting basic information, wherein the basic information comprises lamp parameter information and geographic environment information;
step 2, monitoring the operation of the lamp, namely monitoring the LED street lamp which is currently managed in a networking mode in real time through a big data center, recording the current operation state of the LED street lamp in each area at fixed intervals, and acquiring damage information;
step 3, inputting device information, wherein a user selects a corresponding lamp model or inputs custom device information, and selects an installation area;
step 4, simulating the service life of the equipment, namely simulating the service life of the equipment according to the device information and the installation area, and calculating the service life of the LED street lamp;
step 5,3D lighting simulation, including street view simulation and light effect simulation, simulating the actual lighting effect by using a light effect simulation module through adjusting simulation parameters according to device information input by a user, and recording an optimal simulation scheme selected by the user;
step 6, carrying out comprehensive economic analysis, namely selecting a corresponding economic analysis model according to the requirement to carry out comprehensive analysis on the simulation result and the price of the LED street lamp;
and 7, displaying the economic analysis result, and displaying the economic analysis results of different LED street lamps.
11. The operation analysis method according to claim 10, wherein the lamp parameter information in step 1 comprises: the LED lamp comprises a lamp name, a lamp shape, a lamp price, a lamp brand, a lamp manufacturer and design parameters, rated current, voltage and power provided by the manufacturer, wherein devices used by the LED lamp comprise an LED lamp cap, a lamp post, a lead material, a fixing screw, a chip, a sensor, a driving power supply, a packaging material, a lens, a radiator and the like, and device information comprises the device name, the device position and the average use time of the device;
the geographic environment information comprises geographic position information acquired by a GPRS positioning system, climate and temperature information of a fixed area, a street map in the area, the length and width of each street, a street lamp use time period, a road peak time period and an idle time period, night average pedestrian flow and vehicle flow.
12. The operation analysis method according to claim 10, wherein the step 2 of monitoring the currently networked LED street lamps in real time through the big data center comprises the following steps: recording the brand, the model and the installation number of the LED street lamps used in the current area;
the recording of the current running state of the LED street lamps in each area comprises the following steps: detecting alternating current input voltage, current and equipment temperature of the street lamp circuit in a normal state through a state monitor; detecting specific parameter data of air temperature and humidity through an air temperature and humidity sensor; by the illumination monitoring device: an illumination sensor is additionally arranged to monitor an external illumination signal; monitoring sand dust, dense fog, PM10 and severe rainfall weather conditions through environment monitoring equipment; the method comprises the steps of remotely acquiring field road power consumption data through a multifunctional electric energy meter; acquiring abnormal operation state information including power supply grid fluctuation, large-scale power failure, voltage overload and major holiday voltage and current conditions; collecting and uploading the collected data to a big data center, and recording the collected data into a background database according to date, time period, normal or abnormal categories;
and collecting maintenance information, including statistics of lamp damage and maintenance information, including street lamp fault information, fault reasons, specific damaged parts and devices, long actual use time and random lamp failure rate.
13. The operation analysis method according to claim 10, wherein when the device information is entered in step 3, if the model of the corresponding lamp selected by the user does not exist in the database, the other lamp having the highest correlation with the lamp is identified as a substitute according to the device name input by the user.
14. The operational analysis method of claim 10, wherein said performing a device life simulation in step 4 comprises:
step 4.1, predicting the service life interval of the lamp according to the basic information and the real-time monitoring data of the lamp;
step 4.2, utilizing luminous flux attenuation as a failure criterion, simulating an actual use environment according to real-time monitoring data, describing the service life of the lamp by using a Weibull model, and constructing a lamp service life curve through statistical analysis processing;
4.3, correcting the service life prediction of the LED by adopting a fuzzy evaluation method; selecting basic data information, geographical position information and running state detection information as an LED simulation element set, defining corresponding weights according to the influence degree of each element on the service life of the LED, constructing an evaluation matrix by using an analytic hierarchy process, selecting a weighted evaluation function for calculation, and obtaining a fuzzy evaluation result as a correction value.
15. The operational analysis method of claim 14, wherein the device life simulation further comprises: and (4) performing simulation on major faults and special conditions, setting operation conditions to simulate emergency conditions according to the abnormal information acquired by the big data center, and calculating the stability of the lamp.
16. The operational analysis method of claim 10, wherein the 3D lighting simulation in step 5 comprises:
simulating street scenes through the geographic environment information collected by the basic data module; calculating the illumination and brightness of each lamp through lamp parameter information collected by the basic data module, and simulating the actual light effect; adjusting simulation parameters according to device information input by a user, simulating an actual illumination effect through a light effect simulation module, and storing an optimal simulation scheme selected by the user; the simulation parameters comprise lamp holder size, lamp post height, lamp post distance and lamp quantity.
17. The operational analysis method of claim 10, wherein said performing a comprehensive analysis in step 6 comprises: calculating the consumption resource quantity of the lamps required in the service time input by the user according to the service life of the LED street lamps calculated by the equipment life simulation and the quantity of street lamps required by the 3D lighting simulation; and synthesizing the price and the stability of the lamp to generate an economic analysis report, and adjusting the service life, the illumination brightness, the price and the stability weight in the economic analysis model by a user according to the requirement to score and sort the economic analysis results.
18. The operation analysis method according to claim 10, wherein the economic analysis result presentation in step 7 includes:
matching a two-dimensional shape or a three-dimensional shape of the device stored in the operation analysis system according to device information input by a user, and displaying the two-dimensional shape or the three-dimensional shape of the device on display equipment of the user; and displaying the economic analysis result obtained by the device information input by the user.
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