CN110773378A - Dispensing method, dispensing equipment, dispensing system, server device and storage medium - Google Patents

Dispensing method, dispensing equipment, dispensing system, server device and storage medium Download PDF

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Publication number
CN110773378A
CN110773378A CN201810854559.9A CN201810854559A CN110773378A CN 110773378 A CN110773378 A CN 110773378A CN 201810854559 A CN201810854559 A CN 201810854559A CN 110773378 A CN110773378 A CN 110773378A
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dispensing
equipment
data
control parameters
current
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CN201810854559.9A
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Chinese (zh)
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龙荣深
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Alibaba Group Holding Ltd
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Alibaba Group Holding Ltd
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Priority to CN201810854559.9A priority Critical patent/CN110773378A/en
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
    • B05C—APPARATUS FOR APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
    • B05C5/00—Apparatus in which liquid or other fluent material is projected, poured or allowed to flow on to the surface of the work
    • B05C5/02—Apparatus in which liquid or other fluent material is projected, poured or allowed to flow on to the surface of the work the liquid or other fluent material being discharged through an outlet orifice by pressure, e.g. from an outlet device in contact or almost in contact, with the work
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
    • B05C—APPARATUS FOR APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
    • B05C11/00—Component parts, details or accessories not specifically provided for in groups B05C1/00 - B05C9/00
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
    • B05C—APPARATUS FOR APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
    • B05C11/00—Component parts, details or accessories not specifically provided for in groups B05C1/00 - B05C9/00
    • B05C11/10—Storage, supply or control of liquid or other fluent material; Recovery of excess liquid or other fluent material
    • B05C11/1002—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
    • B05D—PROCESSES FOR APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
    • B05D1/00—Processes for applying liquids or other fluent materials
    • B05D1/26—Processes for applying liquids or other fluent materials performed by applying the liquid or other fluent material from an outlet device in contact with, or almost in contact with, the surface

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  • Application Of Or Painting With Fluid Materials (AREA)

Abstract

The embodiment of the application provides a dispensing method, a dispensing system, dispensing equipment, a server device and a storage medium. In this embodiment, when there is a dispensing requirement, the dispensing device may send current state data to the server; when the server device receives the current state data sent by the dispensing equipment, at least one part of dispensing control parameters required by the dispensing operation is obtained based on the current equipment state parameters, and the dispensing control parameters are returned to the dispensing equipment; the dispensing device can execute dispensing operation on the product to be processed based on at least a part of the received dispensing control parameters. In the process, the dispensing equipment interacts with the server device, and at least one part of dispensing control parameters adaptive to the current equipment state can be obtained according to dispensing requirements, so that an intelligent dispensing process is realized, and the dispensing yield is favorably improved.

Description

Dispensing method, dispensing equipment, dispensing system, server device and storage medium
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a method, an apparatus, a system, a server device, and a storage medium for dispensing.
Background
In the LED (Light Emitting Diode) packaging industry, dispensing is a critical process. In the dispensing process, electronic glue, oil or other liquid can be coated, encapsulated and dripped to the dispensing position of the product, so that the product has the functions of adhering, encapsulating, insulating, fixing or surface smoothing and the like.
In the conventional dispensing method, dispensing is usually performed at a fixed dispensing position with a fixed dispensing amount. But this kind of point glue mode is not intelligent enough, and the point glue defective rate is higher.
Disclosure of Invention
In various aspects, embodiments of the present disclosure provide a dispensing method, a dispensing system, a dispensing apparatus, a server device, and a storage medium, so that a dispensing process is more intelligent and a dispensing yield is improved.
The embodiment of the application provides a dispensing method, which is suitable for dispensing equipment and comprises the following steps: sending the current state data to a server device so that the server device determines at least one part of dispensing control parameters required by the dispensing operation according to the current state data; receiving the at least one part of dispensing control parameters sent by the server device; and executing the dispensing operation on the product to be processed according to the at least one part of dispensing control parameters.
The embodiment of the present application further provides a dispensing method, which is applicable to a server device, and includes: receiving current state data of the dispensing equipment; acquiring at least one part of dispensing control parameters required by the dispensing operation of the dispensing equipment according to the current state data; and returning the at least one part of dispensing control parameters to the dispensing equipment so that the dispensing equipment performs dispensing operation on the product to be processed according to the at least one part of dispensing control parameters.
An embodiment of the present application further provides a dispensing system, including: dispensing equipment and a server device; the dispensing equipment is used for sending the current state data of the dispensing equipment to the server device so that the server device can determine at least one part of dispensing control parameters required by the dispensing operation according to the current state data; receiving the at least one part of dispensing control parameters sent by the server device; performing dispensing operation on the product to be processed according to the at least one part of dispensing control parameters; the server device is used for receiving the current state data of the dispensing equipment; acquiring at least one part of dispensing control parameters required by the dispensing operation of the dispensing equipment according to the current state data; and returning the at least one part of dispensing control parameters to the dispensing equipment so that the dispensing equipment performs dispensing operation on the product to be processed according to the at least one part of dispensing control parameters.
An embodiment of the present application further provides a dispensing apparatus, including: a memory, a processor, and a communication component; the memory to store one or more computer instructions; the processor to execute one or more computer instructions to: sending the current state data of the dispensing equipment to the server device through the communication assembly so that the server device determines at least one part of dispensing control parameters required by the dispensing operation according to the current state data; receiving the at least one part of dispensing control parameters sent by the server device; and executing the dispensing operation on the product to be processed according to the at least one part of dispensing control parameters.
The embodiment of the application also provides a computer readable storage medium storing a computer program, and the computer program can realize the steps in the glue dispensing method executed by one side of the glue dispensing equipment when being executed.
An embodiment of the present application further provides a server apparatus, including: a memory, a processor, and a communication component; the memory to store one or more computer instructions; the processor to execute one or more computer instructions to: receiving current state data of the dispensing equipment through the communication assembly; acquiring at least one part of dispensing control parameters required by the dispensing operation of the dispensing equipment according to the current state data; and returning the at least one part of dispensing control parameters to the dispensing equipment so that the dispensing equipment performs dispensing operation on the product to be processed according to the at least one part of dispensing control parameters.
The embodiment of the application also provides a computer readable storage medium storing a computer program, and the computer program can realize the steps in the dispensing method executed by the server device side when being executed.
In the embodiment of the application, when the dispensing requirement exists, the dispensing equipment can send current state data to the server; when the server device receives the current state data sent by the dispensing equipment, at least one part of dispensing control parameters required by the dispensing operation is obtained based on the current equipment state parameters, and the dispensing control parameters are returned to the dispensing equipment; the dispensing device can execute dispensing operation on the product to be processed based on at least a part of the received dispensing control parameters. In the process, the dispensing equipment interacts with the server device, and at least one part of dispensing control parameters adaptive to the current equipment state can be obtained according to dispensing requirements, so that the dispensing process is more intelligent, and the dispensing yield is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic structural diagram of a dispensing system according to an exemplary embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of a dispensing system according to another exemplary embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a dispensing system according to another exemplary embodiment of the present application;
fig. 4 is a flowchart of a dispensing method according to another exemplary embodiment of the present application;
fig. 5 is a flowchart of another dispensing method according to another exemplary embodiment of the present application;
fig. 6 is a schematic structural diagram of a dispensing apparatus according to another exemplary embodiment of the present application;
fig. 7 is a schematic structural diagram of a server device according to another exemplary embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In some conventional dispensing processes, dispensing operations are usually performed at fixed positions of products to be processed by a fixed dispensing amount, but the dispensing method is not intelligent enough and the dispensing defect rate is high. For example, in the LED packaging industry, if the phosphor is coated at a fixed position of the LED chip by a fixed dispensing amount, the thickness of the phosphor on the LED chip is not uniform, the coating is not uniform, and even the phosphor cannot cover the LED light emitting device, which may result in that the spectrum index of the LED product does not meet the product requirement.
For the technical problem, in some exemplary embodiments of the present application, when there is a dispensing requirement, the dispensing equipment may request the server to obtain at least a portion of dispensing control parameters, and the server device obtains at least a portion of dispensing control parameters required by the dispensing operation and then sends the at least a portion of dispensing control parameters to the dispensing equipment, so that the dispensing equipment may perform the dispensing operation based on the at least a portion of dispensing control parameters sent by the server device. In the process, the dispensing equipment interacts with the server device, and at least one part of dispensing control parameters adaptive to the current equipment state can be obtained according to dispensing requirements, so that an intelligent dispensing process is realized, and the dispensing yield is favorably improved. The embodiments of the present application will be described in detail below with reference to the accompanying drawings.
Fig. 1 is a schematic structural diagram of a dispensing system according to an exemplary embodiment of the present disclosure. As shown in fig. 1, the system includes: a dispensing device 10 and a server device 20.
The dispensing device 10 and the server device 20 may be in wireless or wired communication connection. If the dispensing apparatus 10 is in communication connection with the server device 20 through a Wireless communication mode, the Wireless communication mode may be any one of bluetooth, ZigBee, WiFi (Wireless-Fidelity), infrared, and the like. If the dispensing apparatus 10 is communicatively connected to the server device 20 through a mobile network, the network system of the mobile network may be any one of 2G (gsm), 2.5G (gprs), 3G (WCDMA, TD-SCDMA, CDMA2000, UTMS), 4G (LTE), 4G + (LTE +), WiMax, and the like.
In the dispensing system, the server device 20 mainly provides dispensing control parameter services to the dispensing apparatus 10. For example, when there is a dispensing requirement for the dispensing apparatus 10, the dispensing apparatus 10 may send the current state data to the server apparatus 20 to request the server apparatus 20 to return at least a part of dispensing control parameters adapted to the current apparatus state; the server device 20 receives the current state data sent by the dispensing apparatus 10, acquires at least a part of dispensing control parameters required by the dispensing apparatus 10 for the current dispensing operation based on the current state data, and returns the acquired at least a part of dispensing control parameters to the dispensing apparatus 10, so that the dispensing apparatus 10 performs the dispensing operation according to the at least a part of dispensing control parameters.
In this embodiment, the implementation form of the server device 20 is not limited, and the server device 20 may be any device that can provide computing services and can respond to and process service requests, and may be, for example, a regular server, a cloud host, a virtual center, or the like. The server device 20 mainly includes a processor, a hard disk, a memory, a system bus, and the like, and is similar to a general computer architecture.
In the dispensing system, the dispensing apparatus 10 is mainly used for controlling the glue and dropping, coating or encapsulating the glue onto the surface or inside the product to be processed. For the dispensing apparatus 10, when there is a dispensing requirement, the current state data of the dispensing apparatus can be sent to the server device 20, so that the server device 20 determines at least a part of dispensing control parameters required by the dispensing operation according to the current state data and returns the dispensing control parameters; then, at least a part of the dispensing control parameters returned by the server device 20 is received, and the dispensing operation is performed on the product to be processed according to the at least a part of the dispensing control parameters.
In some exemplary embodiments, as shown in fig. 1, the main hardware components of the dispensing apparatus 10 may include: a dispensing syringe 101, a dispensing needle 102, a dispensing needle driving device 103, a dispensing control device 104, a sensor 105 and a communication unit 106.
The dispensing syringe 101 is used for storing glue, and the dispensing needle 102 is used for discharging glue; usually, the dispensing needle 102 is located at the dispensing outlet of the dispensing syringe 101, and the two are detachably connected. The type of the dispensing needle 102 can be selected according to actual requirements, for example, when the glue is quick-dry glue, a teflon dispensing needle can be selected; when the product to be processed is an LED or optical communication product, a high-precision glue dispensing needle head can be selected.
Optionally, the dispensing needle driving device 103 is configured to precisely drive the dispensing needle 102 to a target dispensing position on the product to be processed. In some exemplary embodiments, the driving force of the dispensing needle driving device 103 may be provided by a hydraulic, pneumatic, electrical, or mechanical driving structure, which is not described herein.
Optionally, the glue supply control device 104 is configured to control the amount of glue supplied from the glue dispensing syringe 101. In some exemplary embodiments, the glue feeding control device 104 may be a pneumatic type or a metering type, and the precision of the two in controlling the glue feeding amount is different and can be selected according to actual requirements. For some dispensing scenarios with high requirement on the accuracy of the glue feeding amount, such as a chip LED package scenario, the metering type glue feeding control device 104 may be used to accurately control the glue feeding amount.
Optionally, the sensor 105 includes one or more high precision sensors, such as a vision sensor, a pressure sensor, a distance sensor, or a chemical sensor, among others. The distance sensor may be configured to detect a current amount of glue in the dispensing syringe 101, the pressure sensor may be configured to detect a current pressure value in the dispensing syringe 101, the chemical sensor may be configured to detect a glue dispensing component of a glue in the dispensing syringe 101, and the visual sensor may be configured to detect a current position of the dispensing needle 102. Of course, the above sensor types and uses are merely exemplary, and the sensors used in the practice of the present application include, but are not limited to, the above.
Optionally, the communication unit 106 may include a data receiving subunit and a data sending subunit, and when there is a dispensing requirement, the data sending subunit may send the current state data of the dispensing apparatus 10 to the server device 20; when the server device 20 determines and returns at least a part of dispensing control parameters required by the dispensing operation this time, the data receiving subunit may receive at least a part of dispensing control parameters required by the dispensing operation this time sent by the server device 20; furthermore, the glue dispensing needle head driving device and the glue feeding control device can be matched with the glue dispensing needle cylinder and the glue dispensing needle head to perform glue dispensing operation on the product to be processed based on at least one part of glue dispensing control parameters.
In this embodiment, when there is a dispensing requirement, the dispensing device may send current state data to the server; when the server device receives the current state data sent by the dispensing equipment, at least one part of dispensing control parameters required by the dispensing operation is obtained based on the current equipment state parameters, and the dispensing control parameters are returned to the dispensing equipment; the dispensing device can execute dispensing operation on the product to be processed based on at least a part of the received dispensing control parameters. In the process, the interaction between the dispensing equipment and the server device enables the dispensing process to be more intelligent, and at least a part of dispensing control parameters acquired by the dispensing equipment from the server device are matched with the dispensing requirement, so that the dispensing yield is improved.
In some exemplary embodiments, the current state data sent by the dispensing apparatus 10 to the server device 20 includes: the current glue amount in the glue dispensing syringe 101, the current pressure in the glue dispensing syringe 101, the glue dispensing composition data and/or the current position of the glue dispensing needle 102 may be collected by the sensor 105.
In some exemplary embodiments, at least a part of the dispensing control parameters required for the current dispensing operation returned by the server apparatus 20 include the driving path of the needle driving apparatus 103 and the dispensing amount of the dispensing control apparatus 104 during the current dispensing operation. The driving path of the needle driving device 103 is used for the target dispensing position that the dispensing needle 102 should reach when the dispensing operation is executed; the glue feeding amount of the glue control device 104 is used for indicating the glue amount that the glue dispensing syringe 102 should feed when the glue dispensing operation is executed this time.
Based on the above, after receiving at least a part of the dispensing control parameters required by the dispensing operation sent by the server device 20, the dispensing apparatus 10 may determine the driving path of the dispensing needle head driving device 103 and the dispensing amount of the dispensing control device 104 according to the at least a part of the dispensing control parameters. Then, the dispensing needle head driving device 103 is controlled to move along the driving path so as to drive the dispensing needle head 102 to a target dispensing position on the product to be processed; and controlling the glue feeding control device 104 to feed glue matched with the glue feeding amount from the glue dispensing needle cylinder 101 so as to dispense glue at the target glue dispensing position according to the glue feeding amount.
Optionally, in the process of the current dispensing operation, the dispensing apparatus 10 may further perform image acquisition on the dispensing operation process through the sensor 105, and upload the acquired image to the server device 20, so that the server device 20 obtains the data of the current dispensing process and the data of the current dispensing result from the image acquisition, so as to perform other operations based on the data of the current dispensing process and the data of the current dispensing result.
Optionally, when the dispensing device 10 performs image acquisition on the dispensing process through the sensor 105, the image acquisition may be performed simultaneously from multiple directions, which is beneficial for the server device 20 to subsequently obtain the dispensing process data and the dispensing result data from the images more comprehensively. The server device 20 receives the image collected in the dispensing process sent by the dispensing device 10, obtains data of the dispensing process and data of the dispensing result, and then can identify whether the dispensing result meets the product requirements based on the data. Of course, in addition to identifying whether the dispensing result meets the product requirement, if the server device 20 calculates at least a part of dispensing control parameters required by the dispensing operation using the dispensing model, the data of the dispensing process and the data of the dispensing result may also be used as incremental samples for training the dispensing model, so as to update the dispensing model based on the incremental samples, which will be described in detail in the following embodiments.
The server device 20 may adopt various embodiments when acquiring at least a part of dispensing control parameters required by the dispensing operation according to the current state data sent by the dispensing apparatus 10. An alternative implementation based on a dispensing model is listed in the following examples of the present application, but is not limited thereto.
In this alternative embodiment based on the dispensing model, after receiving the current state data sent by the dispensing apparatus 10, the server device 20 may use the current state data as an input parameter of the dispensing model, operate the dispensing model to obtain at least a part of dispensing control parameters required by the current dispensing operation of the dispensing apparatus, and issue at least a part of dispensing control parameters required by the current dispensing operation to the dispensing apparatus 10.
Further, due to the structure of the dispensing apparatus 10 and the composition of the glue, the dispensing process may be affected by the current environment of the dispensing apparatus 10. For example, the temperature of the environment in which the dispensing apparatus 10 is currently located may affect the volume or state of the glue in the dispensing syringe 101. For another example, when the dispensing apparatus 10 employs the pneumatic dispensing control device 104, the air pressure and the air flow of the current environment of the dispensing apparatus 10 may affect the corresponding relationship between the pressure value output by the dispensing control device 104 and the dispensing amount of the dispensing syringe 101. Therefore, when the server device 20 calculates at least a portion of dispensing control parameters required for each dispensing operation, environmental factors corresponding to the dispensing apparatus 10 may be considered to improve the accuracy and stability of the calculated at least a portion of dispensing control parameters.
In some exemplary embodiments, as shown in fig. 2, the dispensing system may further include an environmental sensor 30. The environment sensor 30 is configured to obtain current environment data of an environment where the dispensing apparatus 10 is located, for example, data of a temperature, an air pressure, and/or an air flow of the environment where the dispensing apparatus 10 is located, and send the data to the server device 20. It should be understood that the environmental data related to the embodiments of the present application includes, but is not limited to, the above list, and all the environmental data related to the dispensing process and capable of affecting the dispensing process are applicable to the embodiments of the present application.
Then, the server device 20 may obtain the current environment data of the environment where the dispensing apparatus 10 is located, and then use the current environment data as a basis for calculating at least a part of dispensing control parameters required by the dispensing operation. The at least one part of dispensing control parameters required by the dispensing operation of this time, which are calculated by combining the current equipment state parameters sent by the dispensing equipment 10 and the current environment data of the environment where the dispensing equipment 10 is located, fully combines the dispensing requirement and the objective environment, so that the calculated at least one part of dispensing control parameters have good environmental adaptability, and the fitting degree of the dispensing result and the actual dispensing requirement is favorably improved.
In some exemplary embodiments, one way of calculating at least a part of dispensing control parameters required for the dispensing operation in combination with the current device state parameter sent by the dispensing device 10 and the current environment data of the environment where the dispensing device 10 is located is as follows: and taking the current state data and the current environment data of the environment where the dispensing equipment is located as input parameters of the dispensing model, and operating the dispensing model to obtain at least a part of dispensing control parameters required by the dispensing equipment in the dispensing operation. In the above embodiment, an optional implementation manner is described in which the server apparatus 20 can obtain at least a part of dispensing control parameters required by the dispensing operation according to the dispensing model, and the following embodiment exemplarily describes a training process of the dispensing model:
firstly, input samples and output samples required by the training dispensing model are determined.
Optionally, if the influence of the environmental factors on the dispensing process is not considered, the historical apparatus state parameters and the historical dispensing control parameters of the dispensing apparatus 10 in the historical dispensing operation may be selected as input samples; if the influence of the environmental factors on the dispensing process is considered to establish a dispensing model that better meets the actual requirements, the historical apparatus state parameters, the historical dispensing control parameters, and the historical environmental data of the dispensing apparatus 10 during the historical dispensing operation can be simultaneously selected as the input samples.
Optionally, for the input sample, the server apparatus 20 may obtain historical dispensing process data and historical dispensing result data of the dispensing apparatus 10 in the historical dispensing operation, as an output sample. One way for the server device 20 to obtain the historical dispensing process data and the historical dispensing result data of the dispensing apparatus 10 in the historical dispensing operation is as follows: and performing image recognition on the image of the historical dispensing operation process acquired by the dispensing equipment 10, and acquiring historical dispensing process data and historical dispensing result data according to the image recognition result. For example, from the image of the historical dispensing operation process, the relative position change between the dispensing needle 102 and the product to be processed is identified as the historical dispensing process data, and the position, thickness and uniformity of the glue on the product to be processed are identified as the historical dispensing result data.
And then, learning the corresponding relation between the input sample and the output sample by adopting a machine learning method so as to obtain the dispensing model. In some exemplary embodiments, the machine learning method used for training the dispensing model may be a logistic regression algorithm, a support Vector machine (svm) algorithm, a deep neural network algorithm dnn (deep neural network), a naive bayes algorithm, or the like. In fact, the embodiment does not limit which machine learning algorithm is employed. The following embodiment will exemplarily describe a manner of training a dispensing model by taking a deep neural network DNN as an example.
First, the server device 20 may pre-process the acquired input samples and output samples. Wherein the preprocessing operation may include: filtering out dirty data in the input samples and the output samples, supplementing missing values in the samples, and performing one or more of row-column conversion on data in the samples. Thereafter, the server device 20 may perform an association operation on the preprocessed input sample and the output sample. Specifically, the input samples and the products to be processed and/or the dispensing operation batches corresponding to the output samples may be used as a basis for classification, for example, the input samples and the output samples corresponding to the products to be processed a are associated into a group, and the input samples and the output samples corresponding to the products to be processed B are associated into a group; for example, the input samples and the output samples corresponding to the m-th dispensing operation are associated into a group; associating the input samples and the output samples corresponding to the nth dispensing operation into a group; for another example, the input samples and the output samples corresponding to the mth dispensing operation of the product A to be processed are associated into a group; and associating the input samples and the output samples corresponding to the nth dispensing operation of the product B to be processed into a group.
And then, performing feature extraction on the obtained at least one group of input samples and output samples to obtain at least one group of input sample features and output sample features. One way of performing feature extraction on at least one group of obtained input samples and output samples is as follows: firstly, performing principal component equal dimension reduction operation on at least one group of input samples and output samples; next, for the continuous data in the input sample and the output sample after the dimension reduction, the mean value, the standard deviation, the maximum value, the minimum value, and/or the like of the continuous data are calculated as the features of the continuous data. And carrying out ONE HOT encoding operation on the discrete data in the input sample and the output sample after dimension reduction as the characteristics of the discrete data. According to the characteristics of the continuous data and the characteristics of the discrete data, at least one group of input sample characteristics and at least one group of output sample characteristics corresponding to at least one group of input samples and at least one group of output samples can be obtained.
Next, model training is performed using a deep neural network DNN. The DNN is an artificial neural network, and the neural network layers inside the DNN can be divided into an input layer, a hidden layer and an output layer. The layers are all connected, that is, any neuron of the ith layer is necessarily connected with any neuron of the (i + 1) th layer, and the output of the next layer and the output of the previous layer can be expressed by a linear relation. For example, the output vector y of the (i + 1) th layer iMay be represented as: y is i＝σ(W ix i-1+b i) Where σ () represents an activation function, W iA matrix of linear relation coefficients representing the i-th layer, b iRepresents the bias vector, x, of the ith layer i-1Representing the output vector of layer i-1.
Based on the above, after obtaining at least one set of input sample features and output sample features, the at least one set of input sample features may be used as input layer parameters of the deep neural network DNN model, and the output sample features may be used as output layer parameters of the deep neural network DNN. Then, according to the input layer parameters and the output layer parameters, a linear coefficient matrix W corresponding to a hidden layer of the deep neural network DNN model is calculated iAnd a bias vector b i(ii) a Linear coefficient matrix W based on calculation iAnd a bias vector b iAnd obtaining the dispensing model.
Based on the above, after the current state data and the current environment data of the environment where the dispensing equipment is located are input into the dispensing model, the dispensing model may be based on the linear coefficient matrix W when running iAnd a bias vector b iAnd performing linear calculation on the input data to obtain an output result. According to the output result of the dispensing model, at least a part of dispensing control parameters required by the dispensing operation can be determined.
It should be noted that, in some exemplary embodiments, the server device 20 may update the dispensing model according to the increment sample data acquired in real time. An optional model update method is: after the server device 20 returns at least a part of dispensing control parameters required by the dispensing operation to the dispensing equipment 10, acquiring an image acquired by the dispensing equipment 10 for the dispensing operation process, and extracting the dispensing process data and the dispensing result data from the image; and then, updating the dispensing model by taking the dispensing process data, the dispensing result data, the current equipment state parameter, the current environment data of the environment where the dispensing equipment is located and at least one part of dispensing control parameters required by the dispensing operation as incremental samples.
In the updating process, the data of the current dispensing process and the data of the current dispensing result may be used as an increment output sample, and the current device state parameter, the current environment data of the environment where the dispensing device is located, and at least a part of dispensing control parameters required by the current dispensing operation may be used as an increment input sample, which is not described again. In the embodiment, the glue dispensing model is updated in real time by adopting the incremental samples, so that the reliability of the glue dispensing model can be further improved, and the aim of improving the yield of the glue dispensing products is fulfilled.
In fact, the dispensing system provided by the embodiment of the application can be applied to various application scenarios. For example, the adhesive can be applied to the industrial processing fields of adhesion of mobile phone accessories, electromagnetic shielding silicone packaging, battery packaging of mobile phones/notebook computers, coil dispensing, Printed Circuit Board (PCB) bonding adhesive, Integrated Circuit (IC) adhesive, Personal Digital Assistant (PDA) adhesive, Liquid Crystal Display (LCD) packaging, LED packaging, optical device adhesion, Circuit element and substrate adhesion, Printed Circuit boards, and the like.
When the product to be processed corresponding to the dispensing process is an optical product, such as an LCD or an LED, the optical product has a dedicated dispensing result evaluation index, such as a spectrum index, compared to other products. Therefore, for the dispensing requirement of the optical product, when the server device 20 calculates at least a portion of the dispensing control parameters corresponding to each dispensing operation, the spectral index of the optical product can be used as a calculation basis, which is beneficial to improving the yield of the optical product obtained after the dispensing operation is performed, so that the actual spectral index data of the optical product obtained after the dispensing operation is performed is as close as possible to the target spectral index data. The actual spectrum index data can be an actual detection value obtained by performing spectrum analysis on a product to be processed after dispensing is finished; the target spectral index data is an ideal value and can be specified by a user or a worker according to actual needs.
Optionally, in the model training method described in the above embodiment, the server device 20 may further obtain historical actual spectral index data generated after the product to be processed is subjected to the dispensing operation, and use the historical actual spectral index data, the historical dispensing process data, and the historical dispensing result data as an output sample of the training dispensing model. For the specific training process, reference is made to the descriptions of the above embodiments, which are not repeated.
Based on this, the server device 20 may obtain the target spectrum index data of the product to be processed when calculating at least a part of dispensing control parameters required by the dispensing operation. Then, the current state data, the current environment data of the environment where the dispensing apparatus is located, and the target spectrum index data are used as input parameters of a dispensing model, and the dispensing model is operated to obtain at least a part of dispensing control parameters required by the dispensing operation of the dispensing apparatus 10 at this time.
Optionally, in order to facilitate analysis of the spectrum index of the product to be processed obtained after the dispensing operation, as shown in fig. 2, the dispensing system provided in the embodiment of the present application further includes a light splitter 40. The light splitter device 40 may perform spectral analysis on the product to be processed obtained after performing the dispensing operation during each dispensing operation, and generate actual spectral index data corresponding to each dispensing operation.
For the historical dispensing operation, the historical actual spectral index data generated by the spectrometer device 40 may be sent to the server device 20 to be used as an output sample required for training the dispensing model. For the dispensing operation, the actual spectrum index data generated by the light splitter device 40 may be sent to the server device 20, so as to be used as an incremental output sample together with the dispensing process data and the dispensing result data, and the dispensing model is updated, which is not described herein.
In some exemplary embodiments, the dispensing system 10 further includes: the device 50 is monitored. The monitoring device is configured to perform fault monitoring on the dispensing device 10 according to current device parameters and historical device parameters of the dispensing device 10. Optionally, the historical device parameters of the dispensing device 10 may include: the dispensing apparatus 10 may be configured to perform one or more kinds of apparatus operation data corresponding to the historical dispensing operations, such as data on whether the dispensing needle 103 is smoothly discharged or blocked, data on operation of the dispensing needle driving device 103, data on operation of the dispensing control device 104, data on data transmission and reception of the sensor 105, and the like. The monitoring device 50 may establish a fault monitoring model based on the historical device parameters of the dispensing device 10, and perform real-time early warning of device faults according to the current device parameters of the dispensing device 10 in real time, which is beneficial to improving the industrial production efficiency.
In some exemplary embodiments, as shown in fig. 2, the dispensing system 10 further includes: and the industrial data analysis device 60 is used for analyzing the industrial data generated in the gluing operation process to form a visual analysis result and displaying the visual analysis result. For example, the industrial data analysis device 60 may analyze the usage of the glue amount during the dispensing operation, the yield, or the production progress, and display the analysis result on a display screen of the production workshop for a workshop worker to check in real time.
The following will further describe the dispensing system provided in the present application by taking an intelligent LED dispensing system for packaging LEDs as an example.
As shown in fig. 3, in the dispensing system, the server device may include a cloud computing platform and a data cloud service component. When the LED packaging requirements exist, the intelligent LED dispensing machine can acquire the current glue amount of the glue dispensing needle cylinder, the current glue barrel pressure, the component data of fluorescent powder in the glue dispensing needle cylinder, the current position of the glue dispensing needle head and the like through the high-precision sensor arranged on the intelligent LED dispensing machine, the current glue amount, the current glue barrel pressure, the component data of the fluorescent powder in the glue dispensing needle cylinder, the current position of the glue dispensing needle head and the like are used as current equipment state parameters, and the.
The cloud computing platform can acquire target spectrum index data of an LED appointed by a customer and current environment data of the environment where the intelligent LED intelligent dispenser is located, which is sent by the environment sensor through the cloud service assembly on the data, while receiving current equipment state parameters sent by the intelligent LED dispenser.
And then, the cloud computing platform inputs the obtained data into a dispensing model together, generates a driving path of a dispensing needle head driving device and a glue feeding amount of a glue feeding control device in the dispensing operation, and sends the driving path and the glue feeding amount to the intelligent LED dispenser. The intelligent LED dispensing machine drives the dispensing needle head to a target dispensing position of the LED product based on a driving path of the dispensing needle head driving device, controls the dispensing needle cylinder to give a target dispensing amount based on the dispensing amount of the dispensing control device, and coats the target dispensing position of the LED product.
After the dispensing operation is completed, the intelligent LED dispenser can transmit the dispensed LED to the LED light splitting machine equipment. The LED light splitting machine equipment can perform spectrum analysis on the LED subjected to dispensing, generate actual spectrum index data and send the actual spectrum index data to the cloud computing platform through the data cloud service assembly.
In the dispensing operation process, the monitoring equipment can detect the fault state of the intelligent LED dispenser in real time based on data received by the cloud computing platform. The industrial data counting equipment can count the production condition, the glue amount using condition, the product yield and the like of the LED package according to the data received by the cloud computing platform in real time, and output a display screen of a value workshop in real time for watching.
The foregoing embodiments describe the system architecture and system functions of the dispensing system provided in the present application, and the following sections will specifically describe the dispensing method provided in the embodiments of the present application with reference to the accompanying drawings.
Fig. 4 is a flowchart of a dispensing method according to an exemplary embodiment of the present application, which can be implemented based on the dispensing system shown in fig. 1-2, and is mainly described from the perspective of a dispensing apparatus. As shown in fig. 4, the method includes:
step 401, sending the current state data of the dispensing equipment to the server device, so that the server device determines at least a part of dispensing control parameters required by the dispensing operation according to the current state data.
Step 402, receiving at least a part of dispensing control parameters sent by the server device.
Step 403, performing a dispensing operation on the product to be processed according to at least a portion of the dispensing control parameters.
In some exemplary embodiments, a method for performing dispensing operations on a product to be processed according to at least a portion of a dispensing control parameter includes: determining a driving path of a dispensing needle head driving device and a glue feeding amount of a glue feeding control device according to at least a part of dispensing control parameters; controlling the dispensing needle head driving device to move along the driving path so as to drive the dispensing needle head to a target dispensing position on a product to be processed; and controlling the glue feeding control device to feed glue matched with the glue feeding amount from the glue dispensing needle cylinder so as to dispense glue at the target glue dispensing position according to the glue feeding amount.
In some exemplary embodiments, further comprising: and carrying out image acquisition aiming at the dispensing operation process, and uploading the acquired image to the server side device so that the server side device can obtain dispensing process data and dispensing result data from the server side device.
In some exemplary embodiments, the current state data includes: the current glue amount in the glue dispensing needle cylinder, the current pressure in the glue dispensing needle cylinder, the glue dispensing component data and/or the current position of the glue dispensing needle head.
In this embodiment, when dispensing is required, the dispensing apparatus may send the current state data to the server, receive at least a portion of the dispensing control parameters sent by the server device, and perform dispensing operation on the product to be processed based on the at least a portion of the dispensing control parameters. In the process, the dispensing equipment interacts with the server device, and at least one part of dispensing control parameters adaptive to the current equipment state can be obtained according to dispensing requirements, so that an intelligent dispensing process is realized, and the dispensing yield is favorably improved.
Fig. 5 is a flowchart of another dispensing method according to an exemplary embodiment of the present application, which can be implemented based on the dispensing system shown in fig. 1-2, and is mainly described from the perspective of a server device. As shown in fig. 5, the method includes:
step 501, receiving current state data of the dispensing equipment.
Step 502, obtaining at least a part of dispensing control parameters required by the dispensing operation of the dispensing equipment according to the current state data.
Step 503, returning at least a part of the dispensing control parameters required by the dispensing operation to the dispensing equipment, so that the dispensing equipment performs the dispensing operation on the product to be processed according to the at least a part of the dispensing control parameters required by the dispensing operation.
In some exemplary embodiments, a method for obtaining at least a part of dispensing control parameters required by the dispensing apparatus for the dispensing operation according to the current state data includes: and taking the current state data as an input parameter of the dispensing model, and operating the dispensing model to obtain at least a part of dispensing control parameters required by the dispensing operation of the dispensing equipment.
In some exemplary embodiments, a method for operating a dispensing model to obtain at least a portion of dispensing control parameters required by the dispensing apparatus for the current dispensing operation by using current state data as input parameters of the dispensing model includes: receiving current environment data of the environment where the dispensing equipment is located, which is uploaded by an environment sensor; and taking the current state data and the current environment data of the environment where the dispensing equipment is located as input parameters of the dispensing model, and operating the dispensing model to obtain at least a part of dispensing control parameters required by the dispensing equipment in the dispensing operation.
In some exemplary embodiments, a method for operating a dispensing model to obtain at least a part of dispensing control parameters required by the dispensing operation of the dispensing apparatus using current state data and current environment data of an environment where the dispensing apparatus is located as input parameters of the dispensing model includes: if the product to be processed is an optical product, acquiring target spectrum index data of the product to be processed; and taking the current state data, the current environment data of the environment where the dispensing equipment is located and the target spectrum index data as input parameters of a dispensing model, and operating the dispensing model to obtain at least one part of dispensing control parameters required by the dispensing equipment in the dispensing operation.
In some exemplary embodiments, before the step of using the current state data and the current environment data of the environment where the dispensing apparatus is located as the input parameters of the dispensing model and operating the dispensing model to obtain at least a part of dispensing control parameters required by the dispensing operation of the dispensing apparatus, the method further includes: obtaining historical equipment state parameters, historical dispensing control parameters and historical environment data of the dispensing equipment in historical dispensing operation as input samples; acquiring historical dispensing process data and historical dispensing result data corresponding to the historical dispensing operation as output samples; and learning the corresponding relation between the input sample and the output sample by adopting a machine learning method so as to obtain the dispensing model.
In some exemplary embodiments, a method for learning a correspondence between input samples and output samples using a machine learning method to obtain a dispensing model includes: performing feature extraction on the input sample and the output sample to obtain input sample features and output sample features; taking the input sample characteristics as input layer parameters of a deep neural network DNN model, and taking the output sample characteristics as output layer parameters of the deep neural network DNN; calculating a linear coefficient matrix and a bias vector corresponding to a hidden layer of the DNN model according to the input layer parameters and the output layer parameters; and determining a dispensing model according to the linear coefficient matrix and the bias vector.
In some exemplary embodiments, after returning at least a part of the dispensing control parameters to the dispensing apparatus, the method further includes: acquiring an image acquired by a dispensing device aiming at the dispensing operation process; extracting the data of the current dispensing process and the data of the current dispensing result from the image; and updating the dispensing model by taking the dispensing process data, the dispensing result data, the current equipment state parameter, the current environment data of the environment where the dispensing equipment is located and at least a part of dispensing control parameters as incremental samples.
In some exemplary embodiments, if the product to be processed is an optical product, obtaining the output sample further comprises: acquiring historical actual spectral index data generated after a product to be processed is subjected to historical dispensing operation and dispensing; accordingly, updating the dispensing model comprises: and obtaining current actual spectrum index data of a product to be processed after the product is subjected to glue dispensing through the glue dispensing operation, taking the glue dispensing process data, the glue dispensing result data, the current equipment state parameter, the current environment data of the environment where the glue dispensing equipment is located, at least one part of glue dispensing control parameters and the current actual spectrum index data as incremental samples, and updating the glue dispensing model.
In this embodiment, when receiving current state data sent by the dispensing equipment, the server device obtains at least a part of dispensing control parameters required by the dispensing operation based on the current equipment state parameters, and returns the dispensing control parameters to the dispensing equipment; further, the dispensing device can perform dispensing operation on the product to be processed based on the received at least a part of the dispensing control parameters. In the process, the dispensing equipment interacts with the server device, and at least one part of dispensing control parameters adaptive to the current equipment state can be obtained according to dispensing requirements, so that an intelligent dispensing process is realized, and the dispensing yield is favorably improved.
It should be noted that in some of the flows described in the above embodiments and the drawings, a plurality of operations are included in a specific order, but it should be clearly understood that the operations may be executed out of the order presented herein or in parallel, and the sequence numbers of the operations, such as 401, 402, etc., are merely used for distinguishing different operations, and the sequence numbers do not represent any execution order per se. Additionally, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel.
As described above, the dispensing method is applicable to the alternative embodiment of the dispensing apparatus 10 side, as shown in fig. 6, in practice, the dispensing apparatus 10 may include: memory 60, processor 61, communication component 62, and power component 63.
The memory 60 may be configured to store other various data to support operation on the dispensing apparatus 10. Examples of such data include instructions for any application or method operating on the dispensing apparatus 10, contact data, phonebook data, messages, pictures, videos, and the like. The memory may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
In the present embodiment, memory 60 is used to store one or more computer instructions.
A processor 61, coupled to the memory 60, for executing one or more computer instructions in the memory 60 for: sending the current state data of the dispensing equipment to the server device so that the server device determines at least one part of dispensing control parameters required by the dispensing operation according to the current state data; receiving at least one part of dispensing control parameters sent by a server device; and executing the dispensing operation on the product to be processed according to at least a part of the dispensing control parameters.
In an optional embodiment, the processor 60, when performing the dispensing operation on the product to be processed according to at least a part of the dispensing control parameters, is specifically configured to: determining a driving path of a dispensing needle head driving device and a glue feeding amount of a glue feeding control device according to at least a part of dispensing control parameters; controlling the dispensing needle head driving device to move along the driving path so as to drive the dispensing needle head to a target dispensing position on a product to be processed; and controlling the glue feeding control device to feed glue matched with the glue feeding amount from the glue dispensing needle cylinder so as to dispense glue at the target glue dispensing position according to the glue feeding amount.
In an alternative embodiment, processor 60 is further configured to: and carrying out image acquisition aiming at the dispensing operation process, and uploading the acquired image to the server side device so that the server side device can obtain dispensing process data and dispensing result data from the server side device.
In an alternative embodiment, the current state data includes: the current glue amount in the glue dispensing needle cylinder, the current pressure in the glue dispensing needle cylinder, the glue dispensing component data and/or the current position of the glue dispensing needle head.
In an alternative embodiment, the power supply component 63 is used to provide power to the various components of the dispensing apparatus 10. The power components may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the dispensing device 10.
In this embodiment, when dispensing is required, the dispensing apparatus may send the current state data to the server, receive at least a portion of the dispensing control parameters sent by the server device, and perform dispensing operation on the product to be processed based on the at least a portion of the dispensing control parameters. In the process, the interaction between the dispensing equipment and the server device enables the dispensing process to be more intelligent, and at least a part of dispensing control parameters acquired by the dispensing equipment from the server device are matched with the dispensing requirement, so that the dispensing yield is improved.
Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program, where the computer program can implement the steps in the method embodiment that can be executed by the dispensing apparatus in the above method embodiment.
As described above, the dispensing method is applicable to the alternative embodiment of the server device side, as shown in fig. 7, in practice, the server device 20 may include: memory 70, processor 71, communication component 72, and power component 73.
The memory 70 may be configured to store other various data to support operations on the server device 20. Examples of such data include instructions for any application or method operating on the server device 20, contact data, phonebook data, messages, pictures, videos, and so forth. The memory may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
In the present embodiment, the memory 70 is used to store one or more computer instructions.
A processor 71, coupled to the memory 70, for executing one or more computer instructions in the memory 70 for: receiving current state data of the dispensing device through the communication component 72; according to the current state data, at least one part of dispensing control parameters required by the dispensing operation of the dispensing equipment at this time are obtained; and returning at least one part of the dispensing control parameters to the dispensing equipment so that the dispensing equipment performs dispensing operation on the product to be processed according to at least one part of the dispensing control parameters.
In an optional embodiment, the processor 71 obtains at least a part of dispensing control parameters required by the dispensing apparatus for the dispensing operation according to the current state data, and specifically is configured to: and taking the current state data as an input parameter of the dispensing model, and operating the dispensing model to obtain at least a part of dispensing control parameters required by the dispensing operation of the dispensing equipment.
In an optional embodiment, when the processor 71 uses the current state data as an input parameter of the dispensing model and runs the dispensing model to obtain at least a part of dispensing control parameters required by the dispensing apparatus for the current dispensing operation, the processor is specifically configured to: receiving current environment data of the environment where the dispensing equipment is located, which is uploaded by an environment sensor; and taking the current state data and the current environment data of the environment where the dispensing equipment is located as input parameters of the dispensing model, and operating the dispensing model to obtain at least a part of dispensing control parameters required by the dispensing equipment in the dispensing operation.
In an optional embodiment, when the current state data and the current environment data of the environment where the dispensing apparatus is located are used as input parameters of the dispensing model, and the processor 71 runs the dispensing model to obtain at least a part of dispensing control parameters required by the current dispensing operation of the dispensing apparatus, the processor is specifically configured to: if the product to be processed is an optical product, acquiring target spectrum index data of the product to be processed; and taking the current state data, the current environment data of the environment where the dispensing equipment is located and the target spectrum index data as input parameters of a dispensing model, and operating the dispensing model to obtain at least one part of dispensing control parameters required by the dispensing equipment in the dispensing operation.
In an optional embodiment, before the processor 71 uses the current state data and the current environment data of the environment where the dispensing apparatus is located as the input parameters of the dispensing model, and runs the dispensing model to obtain at least a part of dispensing control parameters required by the dispensing apparatus for the current dispensing operation, the processor is further configured to: obtaining historical equipment state parameters, historical dispensing control parameters and historical environment data of the dispensing equipment in historical dispensing operation as input samples; acquiring historical dispensing process data and historical dispensing result data corresponding to the historical dispensing operation as output samples; and learning the corresponding relation between the input sample and the output sample by adopting a machine learning method so as to obtain the dispensing model.
In an alternative embodiment, when learning the corresponding relationship between the input sample and the output sample by using a machine learning method to obtain the dispensing model, the processor 71 is specifically configured to: performing feature extraction on the input sample and the output sample to obtain input sample features and output sample features; taking the input sample characteristics as input layer parameters of the DNN model, and taking the output sample characteristics as output layer parameters of the DNN; calculating a linear coefficient matrix and a bias vector corresponding to a hidden layer of the DNN model according to the input layer parameter and the output layer parameter; and determining a dispensing model according to the linear coefficient matrix and the bias vector.
In an alternative embodiment, after the processor 71 returns at least a portion of the dispensing control parameters to the dispensing apparatus, it is further configured to: acquiring an image acquired by a dispensing device aiming at the dispensing operation process; extracting the data of the current dispensing process and the data of the current dispensing result from the image; and updating the dispensing model by taking the dispensing process data, the dispensing result data, the current equipment state parameter, the current environment data of the environment where the dispensing equipment is located and at least a part of dispensing control parameters as incremental samples.
In an alternative embodiment, if the product to be processed is an optical product, the processor 71, when obtaining the output sample, is further configured to: acquiring historical actual spectral index data generated after a product to be processed is subjected to historical dispensing operation and dispensing; accordingly, updating the dispensing model comprises: and obtaining current actual spectrum index data of a product to be processed after the product is subjected to glue dispensing through the glue dispensing operation, taking the glue dispensing process data, the glue dispensing result data, the current equipment state parameter, the current environment data of the environment where the glue dispensing equipment is located, at least one part of glue dispensing control parameters and the current actual spectrum index data as incremental samples, and updating the glue dispensing model.
In an alternative embodiment, the power supply component 73 is used to provide power to the various components of the server device 20. The power components may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the server device 20.
In this embodiment, when receiving current state data sent by the dispensing equipment, the server device obtains at least a part of dispensing control parameters required by the dispensing operation based on the current equipment state parameters, and returns the dispensing control parameters to the dispensing equipment; further, the dispensing device can perform dispensing operation on the product to be processed based on the received at least a part of the dispensing control parameters. In the process, the interaction between the server device and the dispensing equipment enables the dispensing process to be more intelligent, and the server device can provide at least one part of dispensing control parameters matched with the dispensing requirement to the dispensing equipment, so that the dispensing yield is improved.
Accordingly, the present application further provides a computer-readable storage medium storing a computer program, where the computer program can implement the steps in the method embodiment that can be executed by the server device 20 in the above-mentioned method embodiment.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims (21)

1. A glue dispensing method is suitable for glue dispensing equipment, and is characterized by comprising the following steps:
sending the current state data of the dispensing equipment to a server device so that the server device determines at least one part of dispensing control parameters required by the dispensing operation according to the current state data;
receiving the at least one part of dispensing control parameters sent by the server device;
and executing the dispensing operation on the product to be processed according to the at least one part of dispensing control parameters.
2. The method of claim 1, wherein performing dispensing operations on the products to be processed according to the at least a portion of the dispensing control parameters comprises:
determining a driving path of the dispensing needle head driving device and a glue feeding amount of the glue feeding control device according to at least one part of dispensing control parameters;
controlling the dispensing needle head driving device to move along the driving path so as to drive the dispensing needle head to a target dispensing position on the product to be processed;
and controlling the glue feeding control device to feed glue matched with the glue feeding amount from a glue dispensing needle cylinder so as to dispense glue at the target glue dispensing position according to the glue feeding amount.
3. The method of claim 1 or 2, further comprising:
and carrying out image acquisition aiming at the dispensing operation process, and uploading the acquired image to the server side device so that the server side device can acquire dispensing process data and dispensing result data from the server side device.
4. The method according to claim 1 or 2, wherein the current state data comprises: the current glue amount in the glue dispensing needle cylinder, the current pressure in the glue dispensing needle cylinder, the glue dispensing component data and/or the current position of the glue dispensing needle head.
5. A dispensing method is suitable for server-side equipment, and is characterized by comprising the following steps:
receiving current state data of the dispensing equipment;
acquiring at least one part of dispensing control parameters required by the dispensing operation of the dispensing equipment according to the current state data;
and returning the at least one part of dispensing control parameters to the dispensing equipment so that the dispensing equipment performs dispensing operation on the product to be processed according to the at least one part of dispensing control parameters.
6. The method according to claim 5, wherein obtaining at least a portion of dispensing control parameters required by the dispensing apparatus for the dispensing operation according to the current state data comprises:
and taking the current state data as an input parameter of a dispensing model, and operating the dispensing model to obtain at least a part of dispensing control parameters required by the dispensing operation of the dispensing equipment.
7. The method as claimed in claim 6, wherein the step of operating the dispensing model to obtain at least a part of dispensing control parameters required by the dispensing apparatus for the current dispensing operation with the current state data as input parameters of the dispensing model comprises:
receiving current environment data of the environment where the dispensing equipment is located, which is uploaded by an environment sensor;
and taking the current state data and the current environment data of the environment where the dispensing equipment is located as input parameters of a dispensing model, and operating the dispensing model to obtain at least a part of dispensing control parameters required by the dispensing equipment in the dispensing operation.
8. The method according to claim 7, wherein the step of operating the dispensing model to obtain at least a part of dispensing control parameters required by the current dispensing operation of the dispensing apparatus by using the current state data and the current environment data of the environment where the dispensing apparatus is located as input parameters of a dispensing model comprises:
if the product to be processed is an optical product, acquiring target spectrum index data of the product to be processed;
and taking the current state data, the current environment data of the environment where the dispensing equipment is located and the target spectrum index data as input parameters of a dispensing model, and operating the dispensing model to obtain at least a part of dispensing control parameters required by the dispensing equipment in the dispensing operation.
9. The method according to claim 7, wherein before the current state data and the current environment data of the environment where the dispensing apparatus is located are used as input parameters of a dispensing model and the dispensing model is run to obtain at least a part of dispensing control parameters required by the current dispensing operation of the dispensing apparatus, the method further comprises:
obtaining historical equipment state parameters, historical dispensing control parameters and historical environment data of the dispensing equipment in historical dispensing operation as input samples; and the number of the first and second groups,
obtaining historical dispensing process data and historical dispensing result data corresponding to the historical dispensing operation as output samples;
and learning the corresponding relation between the input sample and the output sample by adopting a machine learning method so as to obtain the dispensing model.
10. The method of claim 9, wherein learning the correspondence between the input samples and the output samples by using a machine learning method to obtain the dispensing model comprises:
performing feature extraction on the input sample and the output sample to obtain input sample features and output sample features;
taking the input sample characteristics as input layer parameters of a deep neural network DNN model, and taking the output sample characteristics as output layer parameters of the deep neural network DNN;
calculating a linear coefficient matrix and a bias vector corresponding to a hidden layer of the DNN model according to the input layer parameters and the output layer parameters;
and determining the dispensing model according to the linear coefficient matrix and the bias vector.
11. The method of claim 9, wherein after returning the at least a portion of the dispensing control parameters to the dispensing device, further comprising:
acquiring an image acquired by the dispensing equipment aiming at the dispensing operation process;
extracting the data of the current dispensing process and the data of the current dispensing result from the image;
and updating the dispensing model by taking the dispensing process data, the dispensing result data, the current equipment state parameter, the current environment data of the environment where the dispensing equipment is located and at least a part of dispensing control parameters as incremental samples.
12. The method of claim 11, wherein obtaining the output sample if the product to be processed is an optical product further comprises: obtaining historical actual spectral index data generated after the products to be processed are subjected to glue dispensing through the historical glue dispensing operation;
accordingly, updating the dispensing model comprises: and obtaining current actual spectrum index data generated after the product to be processed is subjected to glue dispensing through the glue dispensing operation, and updating the glue dispensing model by taking the glue dispensing process data, the glue dispensing result data, the current equipment state parameter, the current environment data of the environment where the glue dispensing equipment is located, the at least part of glue dispensing control parameters and the current actual spectrum index data as incremental samples.
13. A dispensing system, comprising: dispensing equipment and a server device;
the dispensing equipment is used for sending the current state data of the dispensing equipment to the server device so that the server device can determine at least one part of dispensing control parameters required by the dispensing operation according to the current state data;
receiving the at least one part of dispensing control parameters sent by the server device; performing dispensing operation on the product to be processed according to the at least one part of dispensing control parameters;
the server device is used for receiving the current state data of the dispensing equipment; acquiring at least one part of dispensing control parameters required by the dispensing operation of the dispensing equipment according to the current state data; and returning the at least one part of dispensing control parameters to the dispensing equipment so that the dispensing equipment performs dispensing operation on the product to be processed according to the at least one part of dispensing control parameters.
14. The system of claim 13, further comprising: an environmental sensor;
the environment sensor is used for acquiring current environment data of the environment where the dispensing equipment is located and sending the current environment data to the server device.
15. The system of claim 13, further comprising: a spectrometer device;
and when the product to be processed is an optical product, the light splitting machine equipment is used for performing spectral analysis on the product to be processed obtained after the current dispensing operation is performed so as to generate actual spectral index data and send the actual spectral index data to the server device.
16. The system of any one of claims 13-15, further comprising: monitoring equipment;
the monitoring equipment is used for monitoring the faults of the dispensing equipment according to the current equipment parameters and the historical equipment parameters of the dispensing equipment.
17. The system of any one of claims 13-15, further comprising an industrial data analysis device;
the industrial data analysis equipment is used for analyzing industrial data generated in the dispensing operation process to form a visual analysis result and displaying the visual analysis result.
18. A dispensing apparatus, comprising: a memory, a processor, and a communication component;
the memory to store one or more computer instructions;
the processor to execute one or more computer instructions to: sending the current state data of the dispensing equipment to the server device through the communication assembly so that the server device determines at least one part of dispensing control parameters required by the dispensing operation according to the current state data; receiving the at least one part of dispensing control parameters sent by the server device; and executing the dispensing operation on the product to be processed according to the at least one part of dispensing control parameters.
19. A computer-readable storage medium storing a computer program, wherein the computer program is capable of implementing the steps of the method of claims 1-4 when executed.
20. A server-side device, comprising: a memory, a processor, and a communication component;
the memory to store one or more computer instructions;
the processor to execute one or more computer instructions to: receiving current state data of the dispensing equipment through the communication assembly; acquiring at least one part of dispensing control parameters required by the dispensing operation of the dispensing equipment according to the current state data; and returning the at least one part of dispensing control parameters to the dispensing equipment so that the dispensing equipment performs dispensing operation on the product to be processed according to the at least one part of dispensing control parameters.
21. A computer-readable storage medium storing a computer program, wherein the computer program is capable of implementing the steps of the method according to claims 5-12 when executed.
CN201810854559.9A 2018-07-30 2018-07-30 Dispensing method, dispensing equipment, dispensing system, server device and storage medium Pending CN110773378A (en)

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