CN113242280A - LED fluorescent powder coating remote monitoring system and coating effect prediction method - Google Patents
LED fluorescent powder coating remote monitoring system and coating effect prediction method Download PDFInfo
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- CN113242280A CN113242280A CN202110445310.4A CN202110445310A CN113242280A CN 113242280 A CN113242280 A CN 113242280A CN 202110445310 A CN202110445310 A CN 202110445310A CN 113242280 A CN113242280 A CN 113242280A
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- 238000000576 coating method Methods 0.000 title claims abstract description 98
- 239000011248 coating agent Substances 0.000 title claims abstract description 91
- 239000000843 powder Substances 0.000 title claims abstract description 54
- 238000012544 monitoring process Methods 0.000 title claims abstract description 26
- 238000000034 method Methods 0.000 title claims abstract description 21
- 230000000694 effects Effects 0.000 title claims abstract description 18
- 238000004891 communication Methods 0.000 claims abstract description 26
- 238000004519 manufacturing process Methods 0.000 claims abstract description 25
- 230000003595 spectral effect Effects 0.000 claims description 27
- 238000003062 neural network model Methods 0.000 claims description 24
- 238000012549 training Methods 0.000 claims description 22
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 claims description 17
- 230000002596 correlated effect Effects 0.000 claims description 12
- 238000009877 rendering Methods 0.000 claims description 12
- 239000007921 spray Substances 0.000 claims description 9
- 238000005507 spraying Methods 0.000 claims description 9
- 238000013528 artificial neural network Methods 0.000 claims description 8
- 230000000875 corresponding effect Effects 0.000 claims description 6
- 238000001228 spectrum Methods 0.000 claims description 6
- 238000010183 spectrum analysis Methods 0.000 claims description 5
- 238000012360 testing method Methods 0.000 claims description 3
- 239000000463 material Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000003292 glue Substances 0.000 description 1
- 238000004806 packaging method and process Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
- H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L33/00—Semiconductor devices having potential barriers specially adapted for light emission; Processes or apparatus specially adapted for the manufacture or treatment thereof or of parts thereof; Details thereof
- H01L33/48—Semiconductor devices having potential barriers specially adapted for light emission; Processes or apparatus specially adapted for the manufacture or treatment thereof or of parts thereof; Details thereof characterised by the semiconductor body packages
- H01L33/50—Wavelength conversion elements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L2933/00—Details relating to devices covered by the group H01L33/00 but not provided for in its subgroups
- H01L2933/0008—Processes
- H01L2933/0033—Processes relating to semiconductor body packages
- H01L2933/0041—Processes relating to semiconductor body packages relating to wavelength conversion elements
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Abstract
The invention relates to a remote monitoring system for LED fluorescent powder coating and a method for predicting the coating effect, wherein the system comprises the following components: the system comprises industrial personal computer equipment, LED fluorescent powder coating machine equipment, a remote client interface, a communication network, integrating sphere spectrometer equipment and a remote server; the production line comprises industrial personal computer equipment, LED fluorescent powder coating machine equipment and integrating sphere spectrometer equipment; the industrial personal computer equipment, the remote client interface and the integrating sphere spectrometer equipment are communicated with a remote server through a communication network to transmit data. According to the LED fluorescent powder coating remote monitoring system, each LED fluorescent powder coating machine is remotely monitored, the running state of each LED fluorescent powder coating machine is displayed on the remote client interface, the running fault can be timely found, labor and time consumption are reduced, the monitoring on a production line is realized, and the production efficiency is improved.
Description
Technical Field
The invention relates to the technical field of semiconductor application and packaging, in particular to a remote monitoring system for LED fluorescent powder coating and a coating effect prediction method.
Background
Since the LED has been invented and is highly favored by people with its excellent green and environmental-friendly properties, such as high brightness, small volume, low power consumption, long life, and fast response speed, the LED lamp is widely used in various aspects of life. At present, a layer of yellow fluorescent powder glue is coated on a blue LED chip in the production process of the LED, and mechanical equipment is required to accurately operate according to a set coating mode in the coating production process.
In order to ensure the normality of mechanical equipment in the coating operation process, manual monitoring is needed, when production equipment is huge, a large amount of manpower and material resources are consumed, and the problem that the interior of the mechanical equipment is fine in operation cannot be found manually. Meanwhile, production parameters of each mechanical device are different, so even if the coating parameters are consistent, the coated effect is different, and the LED light-emitting effect expected by customers cannot be achieved sometimes. The phosphor coating material is very expensive, and coating tests cannot be performed on a certain coating device to obtain coating parameters of the LED light emitting effect satisfactory to customers, which causes very serious waste.
Therefore, in view of these problems, there is a need for a remote monitoring system for LED phosphor coating equipment to replace manual monitoring of the normal operation of the coating process, and for each unique equipment, the effect after coating is completed can be predicted according to the coating parameters, so as to meet the customer's requirements and save the cost.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides the LED fluorescent powder coating remote monitoring system, which is used for remotely monitoring each LED fluorescent powder coating machine device, displaying the running state of the LED fluorescent powder coating machine device on a remote client interface, finding out running faults in time, reducing manual labor consumption and time consumption, and monitoring on a production line, and improving the production efficiency.
Another objective of the present invention is to provide a method for predicting the coating effect of LED phosphor, which is combined with a remote monitoring system, and uses a neural network model, and can predict the effect of each unique device after coating according to the coating parameters, so as to greatly reduce the cost and find out the LED phosphor coating method capable of meeting the customer requirements.
The system of the invention is realized by adopting the following technical scheme: a remote monitoring system for LED fluorescent powder coating comprises industrial personal computer equipment, LED fluorescent powder coating machine equipment, a remote client interface, a communication network, integrating sphere spectrometer equipment and a remote server; the production line comprises industrial personal computer equipment, LED fluorescent powder coating machine equipment and integrating sphere spectrometer equipment; the industrial personal computer equipment, the remote client interface and the integrating sphere spectrometer equipment are communicated with a remote server through a communication network to transmit data.
The method is realized by adopting the following technical scheme: a method for predicting the coating effect of LED fluorescent powder comprises the following steps:
s1, selecting air pressure x1 of the charging barrel, thimble opening x2 of the spray gun, fluorescent powder concentration x3 and spraying time x4 as input of a neural network model, and taking correlated color temperature y1, color rendering index y2 and spectral curve parameter y3 in a spectrum result of the LED chip coated with the fluorescent powder as output of the neural network model;
s2, by acquiring and storing coating parameters and coating result data, in the coating process of the LED fluorescent powder coating machine equipment, uploading the coating parameters, the air pressure x1 of the charging barrel, the thimble opening x2 of the spray gun, the fluorescent powder concentration x3 and the spraying time x4 to a remote server through a communication network, after coating is completed, putting the LED chip into integrating sphere spectrometer equipment for spectral analysis, and obtaining corresponding correlated color temperature y1, color rendering index y2 and spectral curve parameter y3 and uploading the corresponding correlated color temperature y1, color rendering index y2 and spectral curve parameter y3 to the remote server for storage;
s3, determining the number of hidden layers and the number of nodes of the neural network, and training the neural network through data stored in the remote server until the set training error precision or the maximum iteration number is reached;
s4, storing the trained neural network model in a remote server, enabling a client to set coating parameters, the air pressure x1 of a charging barrel, the thimble opening x2 of a spray gun, the fluorescent powder concentration x3 and the spraying time x4 through a remote client interface, requesting the remote server to return a predicted coating result through the remote client interface, and enabling the remote server to output results of the correlated color temperature y1, the color rendering index y2 and the spectral curve parameter y3 according to the trained neural network model and return the results to the remote client interface through a communication network for displaying.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. according to the invention, each LED fluorescent powder coating machine is remotely monitored through the LED fluorescent powder coating remote monitoring system, and the running state of the LED fluorescent powder coating machine is displayed on the remote client interface, so that the running fault can be timely found, the labor and time consumption are reduced, the monitoring on a production line is realized, and the production efficiency is improved.
2. According to the LED fluorescent powder coating effect prediction method, the effect after coating is finished can be predicted according to the coating parameters by combining with a remote monitoring system and applying a neural network model aiming at each unique device, so that the cost is greatly reduced, and the LED fluorescent powder coating method capable of meeting the requirements of customers is found out.
Drawings
FIG. 1 is a block diagram of an LED phosphor coating remote monitoring system of the present invention;
FIG. 2 is a flow chart of a method for predicting the coating effect of the LED fluorescent powder according to the present invention;
FIG. 3 is a neural network model training flow chart of the LED phosphor coating effect prediction method of the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto.
Example 1
As shown in fig. 1, the LED phosphor coating remote monitoring system of the present embodiment includes an industrial personal computer device, an LED phosphor coating machine device, a remote client interface, a communication network, an integrating sphere spectrometer device, and a remote server; the system comprises an industrial personal computer device, an LED fluorescent powder coating machine device and an integrating sphere spectrometer device, wherein the industrial personal computer device, the LED fluorescent powder coating machine device and the integrating sphere spectrometer device form a production line; the industrial personal computer equipment, the remote client interface and the integrating sphere spectrometer equipment are communicated with a remote server through a communication network to transmit data.
In this embodiment, the industrial personal computer device controls the automatic production operation of the LED phosphor coating machine device, detects the operation state of the LED phosphor coating machine device, and uploads the operation state and production failure information of the device to the remote server through the communication network for storage through the wireless communication module provided in the industrial personal computer device.
In this embodiment, the LED phosphor coating machine equipment is self-grinding equipment, and the motion control board card thereof is controlled by the industrial personal computer equipment to realize the automatic coating process of the LED chip.
In this embodiment, the remote client interface is installed on a PC computer, and the operating state and production fault data of the LED phosphor coating machine device in the remote server are acquired through a communication network and displayed on the remote client interface for the user to check and monitor.
In this embodiment, the communication network is a computer network, and a plurality of routers are deployed in a production line workshop, so that the wireless network cards on the industrial personal computer device and the integrating sphere spectrometer device of each production line can access the network to perform communication.
In this embodiment, the integrating sphere spectrometer device is a subsequent process of the LED phosphor coating machine device, wherein the integrating sphere spectrometer device is composed of an integrating sphere with a radius of 0.5m, a spectrum analyzer and a PC computer, an LED chip dried after being coated by the LED phosphor coating machine device is placed in the integrating sphere for spectrum analysis, a spectrum of the coated LED chip and various light emitting indexes are obtained, and the PC computer uploads test result data to a remote server through a communication network.
In this embodiment, the remote server is a cloud server based on cloud computing, server processes are deployed on the cloud server, a receiving and sending part of the server performs multithread programming in a Reactor mode, the number of connected clients is maximized by fully utilizing resources, and data requests and uploads from the industrial personal computer device, the remote client interface and the integrating sphere spectrometer device can be distinguished and processed.
Example 2
As shown in fig. 2, the method for predicting the LED phosphor coating effect of the present embodiment mainly includes the following steps:
s1, selecting the air pressure x1 of the charging barrel, the thimble opening x2 of the spray gun, the fluorescent powder concentration x3 and the spraying time x4 as the input of the neural network model, and taking the correlated color temperature y1, the color rendering index y2 and the spectral curve parameter y3 in the spectral result of the LED chip coated with the fluorescent powder as the output of the neural network model.
In this embodiment, the spectral curve parameter y3 in step S1 is obtained by fitting a spectral model using spectral curve data obtained by an integrating sphere spectrometer, specifically using the following spectral model:
wherein y is light intensity; x is the wavelength; the spectral curve parameter y3 includes a blue light peak size parameter of the spectral curve
The amplitude parameter a of each Gaussian function1、a2、a3、a4Parameter b of symmetry axis of each gaussian function1、b2、b3、b4And a variance parameter c for each Gaussian function11、c12、c2、c3、c4(ii) a Spectral curve data obtained by integrating sphere spectrometer equipment comprises data points (x, y) with wavelengths from 380nm to 780nm, and spectral model parameters can be obtained by using the data
a1、a2、a3、a4、b1、b2、b3、b4、c11、c12、c2、c3、c4。
S2, acquiring and storing the coating parameters and the coating result data, and in the coating process of the LED fluorescent powder coating machine, the coating parameters are: the air pressure x1 of the charging barrel, the thimble opening x2 of the spray gun, the fluorescent powder concentration x3 and the spraying time x4 are uploaded to a remote server through a communication network; and after coating, putting the LED chip into an integrating sphere spectrometer device for spectral analysis to obtain corresponding correlated color temperature y1, color rendering index y2 and spectral curve parameter y3, and uploading the corresponding correlated color temperature y1, color rendering index y2 and spectral curve parameter y3 to a remote server for storage.
S3, determining the number of hidden layers and the number of nodes of the neural network, and then training the neural network through data stored in the remote server until the set training error precision is 0.1 or the maximum iteration number is 10000;
in the embodiment, the number of the neural network nodes is based on an empirical formula
Determining, wherein n is the number of nodes of an input layer, m is the number of nodes of an output layer, a is a constant between 0 and 10, and 8 can be taken first; in the production process, new training samples are continuously provided in the remote server, so as to avoid the problem of excessive training efficiency and resource consumption caused by the fact that all samples are collected for training together, as shown in fig. 3, the samples are trained in batches, samples which are not used for training the neural network model are obtained and then loaded into the stored neural network model, the training samples in batches are used for training the network model, parameters of the network model are updated, when the training error does not reach the preset precision or the maximum iteration number, the next round of training is carried out, otherwise, the neural network model is stored, and the training of the neural network model is ended.
S4, storing the trained neural network model in a remote server, and setting coating parameters by a client through a remote client interface: the method comprises the following steps that a charging barrel is subjected to air pressure x1, the thimble opening x2 of a spray gun, the fluorescent powder concentration x3 and the spraying time x4, a remote server is requested to return a predicted coating result through a remote client interface, and the remote server outputs the result according to a trained neural network model: the correlated color temperature y1, the color rendering index y2, and the spectral curve parameter y3 are returned to the remote client interface for display over the communications network.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.
Claims (10)
1. A remote monitoring system for LED fluorescent powder coating comprises industrial personal computer equipment, LED fluorescent powder coating machine equipment, a remote client interface, a communication network, integrating sphere spectrometer equipment and a remote server; the production line comprises industrial personal computer equipment, LED fluorescent powder coating machine equipment and integrating sphere spectrometer equipment; the industrial personal computer equipment, the remote client interface and the integrating sphere spectrometer equipment are communicated with a remote server through a communication network to transmit data.
2. The LED fluorescent powder coating remote monitoring system of claim 1, wherein the industrial personal computer device controls automatic production operation of the LED fluorescent powder coating machine device, detects the operation state of the LED fluorescent powder coating machine device, and uploads the operation state and production fault information of the device to a remote server for storage through a communication network through a wireless communication module arranged on the industrial personal computer device.
3. The LED fluorescent powder coating remote monitoring system of claim 1, wherein the LED fluorescent powder coating machine device controls a motion control board card thereof through an industrial personal computer device to automatically coat the LED chip.
4. The LED phosphor coating remote monitoring system of claim 1, wherein the remote client interface is installed on a PC computer, and the operating status and production failure data of the LED phosphor coating machine equipment in the remote server are obtained through a communication network and displayed on the remote client interface for a user to view and monitor.
5. The LED fluorescent powder coating remote monitoring system according to claim 1, wherein the communication network is a computer network, and a plurality of routers are deployed in a production line workshop to enable the industrial personal computer device and the wireless network card on the integrating sphere spectrometer device of each production line to access the network for communication.
6. The LED fluorescent powder coating remote monitoring system according to claim 1, wherein the integrating sphere spectrometer device comprises an integrating sphere, a spectrum analyzer and a PC computer, an LED chip dried after being coated by the LED fluorescent powder coating machine device is placed in the integrating sphere for spectrum analysis, the spectrum and various luminous indexes of the coated LED chip are obtained, and the PC computer uploads test result data to a remote server through a communication network.
7. The LED fluorescent powder coating remote monitoring system according to claim 1, wherein the remote server is a cloud server based on cloud computing, server processes are deployed on the cloud server, and a receiving and sending part of the server adopts a Reactor mode to perform multithread programming so as to distinguish and process data requests and uploads from an industrial personal computer device, a remote client interface and an integrating sphere spectrometer device.
8. A method for predicting the coating effect of LED fluorescent powder comprises the following steps:
s1, selecting air pressure x1 of the charging barrel, thimble opening x2 of the spray gun, fluorescent powder concentration x3 and spraying time x4 as input of a neural network model, and taking correlated color temperature y1, color rendering index y2 and spectral curve parameter y3 in a spectrum result of the LED chip coated with the fluorescent powder as output of the neural network model;
s2, by acquiring and storing coating parameters and coating result data, in the coating process of the LED fluorescent powder coating machine equipment, uploading the coating parameters, the air pressure x1 of the charging barrel, the thimble opening x2 of the spray gun, the fluorescent powder concentration x3 and the spraying time x4 to a remote server through a communication network, after coating is completed, putting the LED chip into integrating sphere spectrometer equipment for spectral analysis, and obtaining corresponding correlated color temperature y1, color rendering index y2 and spectral curve parameter y3 and uploading the corresponding correlated color temperature y1, color rendering index y2 and spectral curve parameter y3 to the remote server for storage;
s3, determining the number of hidden layers and the number of nodes of the neural network, and training the neural network through data stored in the remote server until the set training error precision or the maximum iteration number is reached;
s4, storing the trained neural network model in a remote server, enabling a client to set coating parameters, the air pressure x1 of a charging barrel, the thimble opening x2 of a spray gun, the fluorescent powder concentration x3 and the spraying time x4 through a remote client interface, requesting the remote server to return a predicted coating result through the remote client interface, and enabling the remote server to output results of the correlated color temperature y1, the color rendering index y2 and the spectral curve parameter y3 according to the trained neural network model and return the results to the remote client interface through a communication network for displaying.
9. The method of claim 8, wherein the spectral curve parameter y3 in step S1 is obtained by obtaining spectral curve data through an integrating sphere spectrometer device and then fitting a spectral model, specifically using the following spectral model:
wherein y is light intensity; x is the wavelength; the spectral curve parameter y3 includes a blue light peak size parameter of the spectral model
The amplitude parameter a of each Gaussian function1、a2、a3、a4Parameter b of symmetry axis of each gaussian function1、b2、b3、b4And a variance parameter c for each Gaussian function11、c12、c2、c3、c4。
10. The method for predicting the coating effect of the LED fluorescent powder according to claim 8, wherein the neural network training process in the step S3 is as follows: obtaining a sample which is not used for training the neural network model, then loading the stored neural network model, using the batch of training samples to train the neural network model, updating parameters of the network model, performing the next round of training when the training error does not reach the preset precision or the maximum iteration number, otherwise, storing the neural network model, and finishing the training of the neural network model.
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