TWI831484B - Viscosity learning and prediction system - Google Patents

Viscosity learning and prediction system Download PDF

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TWI831484B
TWI831484B TW111145005A TW111145005A TWI831484B TW I831484 B TWI831484 B TW I831484B TW 111145005 A TW111145005 A TW 111145005A TW 111145005 A TW111145005 A TW 111145005A TW I831484 B TWI831484 B TW I831484B
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mixture
viscosity
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process variable
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TW202422415A (en
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蕭仁忠
陳哲堅
曹凱傑
希瓦姆 庫馬
陳健南
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財團法人精密機械研究發展中心
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Abstract

一種黏度學習系統，具有一桶槽供容設混合物且設有一用以測量混合物黏度之量測單元，桶槽與至少一驅動件相連接，驅動件用以攪拌混合物，而量測單元於攪拌過程中偵測混合物的一黏度輸出變量資訊，一伺服器儲存有預先量測的混合物之濃度資訊，一第一控制單輸入混合物之一第一變量資訊並於攪拌過程中偵測混合物的一第一過程變量資訊，一第二控制單元輸入驅動件之一第二變量資訊並於攪拌過程中偵測驅動件的一第二過程變量資訊，藉由將第一過程變量資訊、第二過程變量資訊及黏度輸出變量傳送儲存至伺服器中，據以建置一用於預測混合物黏度之模型。 A viscosity learning system has a bucket for containing a mixture and a measuring unit for measuring the viscosity of the mixture. The bucket is connected to at least one driving member. The driving member is used to stir the mixture, and the measuring unit is used during the stirring process. A viscosity output variable information of the mixture is detected, a server stores pre-measured concentration information of the mixture, a first control unit inputs a first variable information of the mixture and detects a first variable information of the mixture during the stirring process. Process variable information, a second control unit inputs a second variable information of the driver and detects a second process variable information of the driver during the stirring process, by combining the first process variable information, the second process variable information and The viscosity output variable is sent to the server and used to build a model for predicting the viscosity of the mixture.

Description

黏度學習暨預測系統 Viscosity learning and prediction system

本發明與黏度預測有關，特別是指一種學習暨預測系統，用於食品加工產業且無須在桶槽設置感測器即可測量攪拌桶中混合物的黏度。 The present invention relates to viscosity prediction, and in particular refers to a learning and prediction system that is used in the food processing industry and can measure the viscosity of a mixture in a mixing barrel without setting a sensor in the barrel.

在食品加工業中，將多種原料倒入攪拌桶進行攪拌混合，而既有的流體或粉體混合物之黏度量測方式，是在攪拌桶內部設置一感測器，感測器持續地對桶內攪拌中的混合物進行量測與回報，然而，感測器只能感應測量到與其接觸的部分混合物之黏度數值，而無法全面地呈現混合物的真實黏度，故量測的黏度數值並非完全正確；再加上感測器發生損壞的後續更換相當麻煩，甚至必須更換整個攪拌桶，而導致維修成本的增加。 In the food processing industry, a variety of raw materials are poured into a mixing barrel for mixing. The existing method of measuring the viscosity of a fluid or powder mixture is to set a sensor inside the mixing barrel, and the sensor continuously monitors the barrel. The mixture being stirred inside is measured and reported. However, the sensor can only sense and measure the viscosity value of the part of the mixture in contact with it, but cannot fully present the true viscosity of the mixture, so the measured viscosity value is not completely accurate; In addition, if the sensor is damaged, subsequent replacement is very troublesome, and the entire mixing barrel may even have to be replaced, resulting in increased maintenance costs.

有鑑於此，如何解決上述問題，即為本發明所欲解決之首要課題。 In view of this, how to solve the above problems is the primary issue to be solved by the present invention.

本發明之主要目的，在於提供一種黏度學習暨預測系統，其預先在訓練系統以不同參數的輸入、輸出來得出黏度變化狀態，而供後續在預測系統中輸入部分參數以得到黏度預測值，無須在桶槽設置感測器即可依據黏度預測值完成攪拌作業，而具有黏度數值準確及降低成本之功效。 The main purpose of the present invention is to provide a viscosity learning and prediction system, which uses the input and output of different parameters in the training system to obtain the viscosity change state in advance, and then inputs some parameters in the prediction system to obtain the viscosity prediction value, without the need for Installing a sensor in the tank can complete the mixing operation based on the viscosity prediction value, which has the effect of accurate viscosity values and reducing costs.

為達前述之目的，本發明提供一種黏度學習系統，包括有：一桶槽，供容設混合物且設有一用以測量混合物黏度之量測單元，該桶槽與至少一驅動件相連接，該驅動件用以攪拌混合物，而該量測單元於攪拌過程中偵測混合物的一黏度輸出變量資訊； 一伺服器，具有一資料庫單元，且該伺服器與該量測單元透過網路連結，該伺服器接收資料並將預先量測的混合物之濃度資訊儲存至該資料庫單元；一第一控制單元，與該桶槽電性連接且與該伺服器網路連結，該第一控制單元輸入混合物之一第一變量資訊並於攪拌過程中偵測混合物的一第一過程變量資訊；一第二控制單元，與該桶槽電性連接且與該伺服器網路連結，該第二控制單元輸入該驅動件之一第二變量資訊並於攪拌過程中偵測該驅動件的一第二過程變量資訊；其中，該第一控制單元將該第一過程變量資訊傳送至該伺服器，該第二控制單元將該第二過程變量資訊傳送至該伺服器，該量測單元將該黏度輸出變量資訊傳送至該伺服器，並透過該伺服器將該第一過程變量資訊、該第二過程變量資訊及該黏度輸出變量資訊儲存至該資料庫單元中，以建置一模型。 In order to achieve the above purpose, the present invention provides a viscosity learning system, which includes: a barrel for containing the mixture and a measuring unit for measuring the viscosity of the mixture, the barrel is connected to at least one driving member, and the barrel is connected to at least one driving member. The driving member is used to stir the mixture, and the measuring unit detects a viscosity of the mixture and outputs variable information during the stirring process; A server has a database unit, and the server is connected to the measurement unit through a network. The server receives data and stores the concentration information of the pre-measured mixture to the database unit; a first control A unit is electrically connected to the tank and connected to the server network. The first control unit inputs a first variable information of the mixture and detects a first process variable information of the mixture during the mixing process; a second The control unit is electrically connected to the tank and to the server network. The second control unit inputs a second variable information of the driver and detects a second process variable of the driver during the mixing process. Information; wherein, the first control unit transmits the first process variable information to the server, the second control unit transmits the second process variable information to the server, and the measurement unit outputs the viscosity variable information. Transmit to the server, and store the first process variable information, the second process variable information and the viscosity output variable information into the database unit through the server to build a model.

較佳地，該第一變量資訊由混合物之濃度及溫度所構成。 Preferably, the first variable information consists of the concentration and temperature of the mixture.

較佳地，該驅動件由一馬達所構成，而該第二變量資訊即為馬達之運轉頻率。 Preferably, the driving member is composed of a motor, and the second variable information is the operating frequency of the motor.

較佳地，該第一過程變量資訊由攪拌過程中實際測量的混合物之溫度所構成。 Preferably, the first process variable information consists of the temperature of the mixture actually measured during the stirring process.

較佳地，該驅動件由一馬達所構成，而該第二過程變量資訊由攪拌過程中實際測量的馬達之運轉頻率、電壓及電流所構成。 Preferably, the driving member is composed of a motor, and the second process variable information is composed of the operating frequency, voltage and current of the motor actually measured during the stirring process.

而本發明更提供一種基於請求項1之黏度訓練系統所建置之黏度預測系統，包含有：一桶槽，供容設混合物，且該桶槽與至少一驅動件相連接，該驅動件用以攪拌混合物； 一伺服器，設有一資料庫單元，該資料庫單元設有一模型且與該桶槽透過網路連結，該模型預先建置有依據該黏度訓練系統綜整得出的一混合物濃度資訊、一第一過程變量資訊及一第二過程變量資訊，其中，將該桶槽中混合物之當前混合物濃度資訊、當前第一過程變量資訊及當前第二過程變量資訊傳送至該伺服器且輸入至黏度訓練系統中，並分別與該資料庫單元中預先建置的混合物濃度資訊、第一過程變量資訊及第二過程變量資訊進行比對，以預測得出當前混合物之黏度。 The present invention further provides a viscosity prediction system based on the viscosity training system of claim 1, which includes: a barrel for containing the mixture, and the barrel is connected to at least one driving member, and the driving member is to stir the mixture; A server is provided with a database unit. The database unit is provided with a model and is connected to the barrel through a network. The model is pre-built with a mixture concentration information integrated based on the viscosity training system, a first A process variable information and a second process variable information, wherein the current mixture concentration information, the current first process variable information and the current second process variable information of the mixture in the tank are transmitted to the server and input to the viscosity training system , and compare it with the pre-built mixture concentration information, first process variable information and second process variable information in the database unit to predict the viscosity of the current mixture.

較佳地，該桶槽更與一第一控制單元及一第二控制單元電性連接並透過網路連接至該伺服器，在該桶槽攪拌混合過程中將當前混合物濃度資訊輸入至該伺服器中，該伺服器透過該第一控制單元與該第二控制單元分別擷取當前第一過程變量資訊及當前第二過程變量資訊，將當前混合物濃度資訊、第一過程變量資訊及當前第二過程變量資訊輸入至黏度訓練系統中，並分別與該模型中的混合物濃度資訊、第一過程變量資訊及第二過程變量資訊進行比對，以預測得出當前混合物之黏度。 Preferably, the tank is electrically connected to a first control unit and a second control unit and connected to the server through a network, and the current mixture concentration information is input to the server during the stirring and mixing process of the tank. In the server, the server acquires the current first process variable information and the current second process variable information through the first control unit and the second control unit respectively, and combines the current mixture concentration information, the first process variable information and the current second process variable information. The process variable information is input into the viscosity training system and compared with the mixture concentration information, first process variable information and second process variable information in the model to predict the viscosity of the current mixture.

而本發明之上述目的與優點，不難從下述所選用實施例之詳細說明與附圖中獲得深入了解。 The above objects and advantages of the present invention can be easily understood from the following detailed description of selected embodiments and the accompanying drawings.

1:桶槽 1: barrel tank

11:驅動件 11:Driving parts

12:量測單元 12:Measurement unit

2:伺服器 2:Server

21:資料庫單元 21: Database unit

3:第一控制單元 3: First control unit

4:第二控制單元 4: Second control unit

5:模型 5:Model

第1圖為本發明黏度訓練系統之方塊結構示意圖。 Figure 1 is a schematic diagram of the block structure of the viscosity training system of the present invention.

第2圖為本發明黏度訓練系統之步驟流程圖。 Figure 2 is a flow chart of the steps of the viscosity training system of the present invention.

第3圖為本發明黏度訓練系統之流程示意圖。 Figure 3 is a schematic flow chart of the viscosity training system of the present invention.

第4圖為本發明黏度預測系統之方塊結構示意圖。 Figure 4 is a schematic diagram of the block structure of the viscosity prediction system of the present invention.

第5圖為本發明黏度預測系統之步驟流程圖。 Figure 5 is a step flow chart of the viscosity prediction system of the present invention.

第6圖為本發明黏度預測系統之流程示意圖。 Figure 6 is a schematic flow chart of the viscosity prediction system of the present invention.

首先，請參閱第1~3圖，為本發明所提供之黏度訓練系統，其由一桶槽1、一伺服器2、一第一控制單元3及一第二控制單元4所構成，其中：該桶槽1，於本實施例中，係用於食品加工產業中，供容設呈液體狀或粉體狀之混合物，該桶槽1與至少一驅動件11相連接，該驅動件11用以攪拌混合物，且該桶槽1設有一用以測量混合物黏度之量測單元12，且該量測單元12於攪拌過程中偵測混合物的一黏度輸出變量資訊，與本實施例中，該驅動件11由一馬達所構成。 First, please refer to Figures 1 to 3, which illustrate the viscosity training system provided by the present invention, which consists of a tank 1, a server 2, a first control unit 3 and a second control unit 4, wherein: The barrel 1, in this embodiment, is used in the food processing industry to accommodate liquid or powdery mixtures. The barrel 1 is connected to at least one driving member 11, and the driving member 11 is To stir the mixture, the tank 1 is provided with a measuring unit 12 for measuring the viscosity of the mixture, and the measuring unit 12 detects a viscosity of the mixture and outputs variable information during the stirring process. In this embodiment, the driver Element 11 consists of a motor.

該伺服器2，具有一資料庫單元21，且該伺服器2與該量測單元12透過網路連結，該伺服器2接收資料並將預先量測的混合物之濃度資訊儲存至該資料庫單元21，於本實施例中，該伺服器2由一電腦或一行動裝置所構成。 The server 2 has a database unit 21, and the server 2 and the measurement unit 12 are connected through a network. The server 2 receives data and stores the concentration information of the pre-measured mixture into the database unit. 21. In this embodiment, the server 2 is composed of a computer or a mobile device.

該第一控制單元3，與該桶槽1電性連接且與該伺服器2網路連結，該第一控制單元3輸入混合物之一第一變量資訊並於攪拌過程中偵測混合物的一第一過程變量資訊，於本實施例中，該第一控制單元3由一邏輯控制器所構成，且該第一變量資訊由混合物之濃度及溫度所構成，而該第一過程變量資訊由攪拌過程中實際測量的混合物之溫度所構成。 The first control unit 3 is electrically connected to the tank 1 and to the server 2. The first control unit 3 inputs a first variable information of the mixture and detects a first variable of the mixture during the stirring process. A process variable information. In this embodiment, the first control unit 3 is composed of a logic controller, and the first variable information is composed of the concentration and temperature of the mixture, and the first process variable information is composed of the stirring process. consists of the actual measured temperature of the mixture.

該第二控制單元4，與該桶槽1電性連接且與該伺服器2網路連結，該第二控制單元4輸入該驅動件11之一第二變量資訊並於攪拌過程中偵測該驅動件11的一第二過程變量資訊，於本實施例中，該第二控制單元4由一變頻器所構成，且該第二變量資訊由該驅動件11之頻率所構成，而該第二過程變量資訊由攪拌過程中實際測量的驅動件11之頻率、電壓及電流所構成(前述驅動件11之頻率，於本實施例即指馬達的運轉頻率)。 The second control unit 4 is electrically connected to the barrel 1 and connected to the server 2 via a network. The second control unit 4 inputs a second variable information of the driving member 11 and detects the second variable information during the stirring process. A second process variable information of the driving element 11. In this embodiment, the second control unit 4 is composed of a frequency converter, and the second variable information is composed of the frequency of the driving element 11, and the second The process variable information consists of the frequency, voltage and current of the driving element 11 actually measured during the stirring process (the frequency of the driving element 11 mentioned above refers to the operating frequency of the motor in this embodiment).

請繼續參閱第2、3圖，為本發明所提供之黏度訓練系統於實際應用於實驗設計訓練之步驟流程，首先透過該第一控制單元3與該第二控制單元4分別輸入混合物之第一變量資訊及該驅動件11之第二變量資訊，並在混合物於該桶槽1內部攪拌的過程中，該第一控制單元3偵測混合物的第一過程變量資訊，而該第二控制單元4偵測該驅動件11的第二過程變量資訊，且該量測單元12透過預先量測的混合物之濃度資訊與第一過程變量資訊於攪拌過程中綜整偵測混合物的黏度輸出變量資訊，接著該第一控制單元3將該第一過程變量資訊傳送至該伺服器2，該第二控制單元4將該第二過程變量資訊傳送至該伺服器2，該量測單元12將該黏度輸出變量資訊傳送至該伺服器2，並透過該伺服器2將該第一過程變量資訊、該第二過程變量資訊及該黏度輸出變量資訊儲存至該資料庫單元21中，而藉由將每一次實驗設計訓練後的混合物之濃度資訊、該第一過程變量資訊、該第二過程變量資訊及該黏度輸出變量資訊進行綁定，以建置一用於預測混合物黏度之模型。 Please continue to refer to Figures 2 and 3 for a step-by-step process of actually applying the viscosity training system provided by the present invention to experimental design training. First, the first control unit 3 and the second control unit 4 respectively input the first values of the mixture. The variable information and the second variable information of the driving member 11, and during the mixing process of the mixture inside the tank 1, the first control unit 3 detects the first process variable information of the mixture, and the second control unit 4 The second process variable information of the driving member 11 is detected, and the measurement unit 12 integrates the pre-measured concentration information of the mixture and the first process variable information to detect the viscosity of the mixture and outputs variable information during the stirring process, and then The first control unit 3 transmits the first process variable information to the server 2, the second control unit 4 transmits the second process variable information to the server 2, and the measurement unit 12 outputs the viscosity variable The information is transmitted to the server 2, and the first process variable information, the second process variable information and the viscosity output variable information are stored in the database unit 21 through the server 2, and by storing each experiment The concentration information of the trained mixture, the first process variable information, the second process variable information and the viscosity output variable information are designed to be bound to build a model for predicting the viscosity of the mixture.

而在該黏度訓練系統經過實驗設計訓練完成後，則需要部署於執行設備上，請參閱第4~6圖，為本發明基於該黏度訓練系統所建置的黏度預測系統，其由桶槽1及伺服器2所構成，其中：該桶槽1，供容設混合物，且該桶槽1與至少一驅動件11相連接，該驅動件11用以攪拌混合物。 After the viscosity training system is completed through experimental design and training, it needs to be deployed on the execution device. Please refer to Figures 4 to 6, which are the viscosity prediction system built based on the viscosity training system of the present invention. It consists of the barrel 1 and a server 2, wherein: the barrel 1 is used to accommodate the mixture, and the barrel 1 is connected to at least one driving member 11, and the driving member 11 is used to stir the mixture.

該伺服器2，設有資料庫單元21，該資料庫單元21設有模型5並與該桶槽1透過網路連結，該模型5係依據該黏度訓練系統建置而成，且該模型5建置有依據該黏度訓練系統綜整得出的一混合物濃度資訊、一第一過程變量資訊及一第二過程變量資訊，將該桶槽1中混合物之當前混合物濃度資訊、當前第一過程變量資訊及當前第二過程變量資訊傳送至該伺服器2，並分別與該模型5中的 混合物濃度資訊、第一過程變量資訊及第二過程變量資訊進行比對，以預測得出當前混合物之黏度。 The server 2 is provided with a database unit 21. The database unit 21 is provided with a model 5 and is connected to the bucket 1 through a network. The model 5 is built based on the viscosity training system, and the model 5 A mixture concentration information, a first process variable information and a second process variable information integrated based on the viscosity training system are constructed, and the current mixture concentration information of the mixture in the tank 1 and the current first process variable are information and the current second process variable information are sent to the server 2 and are compared with the model 5 respectively. The mixture concentration information, the first process variable information and the second process variable information are compared to predict the viscosity of the current mixture.

而於本實施例中，該第一過程變量資訊由攪拌過程中實際測量的混合物之溫度所構成，而該第二過程變量資訊由攪拌過程中實際測量的驅動件11之頻率、電壓及電流所構成，進一步地，該第二過程變量資訊的驅動件11電壓及電流亦可換算成驅動件11之功率，以作為該第二過程變量資訊的參數。 In this embodiment, the first process variable information is composed of the temperature of the mixture actually measured during the stirring process, and the second process variable information is composed of the frequency, voltage and current of the driving element 11 actually measured during the stirring process. Furthermore, the voltage and current of the driving element 11 of the second process variable information can also be converted into the power of the driving element 11 and used as parameters of the second process variable information.

請繼續參閱第5、6圖，為本發明所提供之黏度預測系統於實際應用在單純預測上之步驟流程，首先使用者將該桶槽1中混合物之當前混合物濃度資訊、當前第一過程變量資訊及當前第二過程變量資訊輸入至該伺服器2，接著藉由當前混合物濃度資訊、當前第一過程變量資訊及當前第二過程變量資訊分別與該模型5中的混合物濃度資訊、第一過程變量資訊及第二過程變量資訊進行比對，即可預測得出對應該黏度訓練系統中之黏度輸出變量資訊的當前混合物黏度。 Please continue to refer to Figures 5 and 6 for a step-by-step process of practical application of the viscosity prediction system provided by the present invention in simple prediction. First, the user obtains the current mixture concentration information of the mixture in tank 1 and the current first process variable. information and the current second process variable information are input to the server 2, and then the current mixture concentration information, the current first process variable information, and the current second process variable information are respectively combined with the mixture concentration information and the first process in the model 5 By comparing the variable information with the second process variable information, the current mixture viscosity corresponding to the viscosity output variable information in the viscosity training system can be predicted.

此外，本發明所提供之黏度預測系統亦可實際應用在攪拌混合的過程中，先將該桶槽1與第一控制單元例如邏輯控制器及第二控制單元例如變頻器電性連接並透過網路連接至該伺服器2，在該桶槽1實際攪拌混合過程中將當前混合物濃度資訊輸入至該伺服器2中，接著該伺服器2透過第一控制單元與第二控制單元分別擷取當前第一過程變量資訊及當前第二過程變量資訊，最後將當前混合物濃度資訊、當前第一過程變量資訊及當前第二過程變量資訊分別與該模型5中的混合物濃度資訊、第一過程變量資訊及第二過程變量資訊進行比對，進而同樣可預測得出當前混合物之黏度。 In addition, the viscosity prediction system provided by the present invention can also be actually used in the process of stirring and mixing. First, the tank 1 is electrically connected to a first control unit such as a logic controller and a second control unit such as a frequency converter and connected through a network. The server 2 is connected to the server 2 through the channel. During the actual stirring and mixing process of the tank 1, the current mixture concentration information is input into the server 2. Then the server 2 captures the current mixture concentration information through the first control unit and the second control unit respectively. The first process variable information and the current second process variable information are finally combined with the mixture concentration information, the first process variable information and the current second process variable information in the model 5 respectively. The second process variable information is compared, and the viscosity of the current mixture can also be predicted.

藉由上述本發明之結構，透過預先在該黏度訓練系統以不同參數的輸入、輸出來得出黏度變化狀態，而供後續在該黏度預測系統中輸入當前混合物濃度資訊即可預測得出當前混合物黏度之預測值，無須在桶槽1設置用於量測黏度的 量測單元即可依據黏度預測值完成攪拌作業，而具有黏度數值準確及降低成本之功效。 With the above structure of the present invention, the viscosity change state is obtained by inputting and outputting different parameters in the viscosity training system in advance, and then the current mixture concentration information can be input into the viscosity prediction system to predict the current mixture viscosity. The predicted value does not need to be set up in tank 1 for measuring viscosity. The measuring unit can complete the mixing operation based on the predicted viscosity value, thereby achieving accurate viscosity values and reducing costs.

以上實施例之揭示僅用以說明本發明，並非用以限制本發明，故舉凡數值之變更或等效元件之置換仍應隸屬本發明之範疇。 The disclosure of the above embodiments is only for illustrating the present invention and is not intended to limit the present invention. Therefore, any changes in numerical values or replacement of equivalent components shall still fall within the scope of the present invention.

綜上所述，當可使熟知本項技藝者明瞭本發明確可達成前述目的，實已符合專利法之規定，故依法提出申請。 To sum up, when it can be understood by those who are familiar with this art that the present invention can clearly achieve the aforementioned purpose, it actually complies with the provisions of the patent law, so the application is filed in accordance with the law.

1:桶槽 1: barrel tank

11:驅動件 11:Driving parts

12:量測單元 12:Measurement unit

2:伺服器 2:Server

21:資料庫單元 21: Database unit

3:第一控制單元 3: First control unit

4:第二控制單元 4: Second control unit

Claims (6)

一種黏度學習暨預測系統，包含有：一黏度訓練系統，包含有：一桶槽，供容設混合物且設有一用以測量混合物黏度之量測單元，該桶槽與至少一驅動件相連接，該驅動件用以攪拌混合物，而該量測單元於攪拌過程中偵測混合物的一黏度輸出變量資訊；一伺服器，具有一資料庫單元，且該伺服器與該量測單元透過網路連結，該伺服器接收資料並將預先量測的混合物之濃度資訊儲存至該資料庫單元；一第一控制單元，與該桶槽電性連接且與該伺服器網路連結，該第一控制單元輸入混合物之一第一變量資訊並於攪拌過程中偵測混合物的一第一過程變量資訊；一第二控制單元，與該桶槽電性連接且與該伺服器網路連結，該第二控制單元輸入該驅動件之一第二變量資訊並於攪拌過程中偵測該驅動件的一第二過程變量資訊；其中，該第一控制單元將該第一過程變量資訊傳送至該伺服器，該第二控制單元將該第二過程變量資訊傳送至該伺服器，該量測單元將該黏度輸出變量資訊傳送至該伺服器，並透過該伺服器將該第一過程變量資訊、該第二過程變量資訊及該黏度輸出變量資訊儲存至該資料庫單元中，以建置一模型；一黏度預測系統，其係基於該黏度訓練系統所建置而成，包含有： 該桶槽，供容設混合物，且該桶槽與該至少一驅動件相連接，該驅動件用以攪拌混合物；該伺服器，設有該資料庫單元，該資料庫單元設有該模型且與該桶槽透過網路連結，該模型預先建置有依據該黏度訓練系統綜整得出的一混合物濃度資訊、一第一過程變量資訊及一第二過程變量資訊，其中，將該桶槽中混合物之當前混合物濃度資訊、當前第一過程變量資訊及當前第二過程變量資訊傳送至該伺服器，並分別與該資料庫單元中預先建置的混合物濃度資訊、第一過程變量資訊及第二過程變量資訊進行比對，以預測得出當前混合物之黏度。 A viscosity learning and prediction system includes: a viscosity training system, including: a barrel for containing a mixture and a measuring unit for measuring the viscosity of the mixture; the barrel is connected to at least one driving member; The driver is used to stir the mixture, and the measuring unit detects a viscosity of the mixture and outputs variable information during the stirring process; a server has a database unit, and the server is connected to the measuring unit through a network , the server receives data and stores the pre-measured concentration information of the mixture to the database unit; a first control unit is electrically connected to the tank and connected to the server network, the first control unit Input a first variable information of the mixture and detect a first process variable information of the mixture during the mixing process; a second control unit, electrically connected to the tank and connected to the server network, the second control unit The unit inputs a second variable information of the driver and detects a second process variable information of the driver during the stirring process; wherein, the first control unit transmits the first process variable information to the server, and the The second control unit transmits the second process variable information to the server, the measurement unit transmits the viscosity output variable information to the server, and transmits the first process variable information, the second process variable information to the server through the server. The variable information and the viscosity output variable information are stored in the database unit to build a model; a viscosity prediction system is built based on the viscosity training system and includes: The tank is used to accommodate the mixture, and the tank is connected to the at least one driving member, and the driving member is used to stir the mixture; the server is provided with the database unit, and the database unit is provided with the model and Connected to the tank through the network, the model is pre-built with a mixture concentration information, a first process variable information and a second process variable information integrated according to the viscosity training system, wherein the tank The current mixture concentration information, the current first process variable information and the current second process variable information of the mixture in the mixture are sent to the server, and are compared with the pre-built mixture concentration information, first process variable information and the pre-built mixture concentration information in the database unit respectively. The two process variable information are compared to predict the viscosity of the current mixture. 如請求項1所述之黏度學習暨預測系統，其中，該第一變量資訊由混合物之濃度及溫度所構成。 The viscosity learning and prediction system of claim 1, wherein the first variable information consists of the concentration and temperature of the mixture. 如請求項1所述之黏度學習暨預測系統，其中，該驅動件由一馬達所構成，而該第二變量資訊即為馬達之運轉頻率。 The viscosity learning and prediction system of claim 1, wherein the driving member is composed of a motor, and the second variable information is the operating frequency of the motor. 如請求項1所述之黏度學習暨預測系統，其中，該第一過程變量資訊由攪拌過程中實際測量的混合物之溫度所構成。 The viscosity learning and prediction system of claim 1, wherein the first process variable information is composed of the temperature of the mixture actually measured during the stirring process. 如請求項1所述之黏度學習暨預測系統，其中，該驅動件由一馬達所構成，而該第二過程變量資訊由攪拌過程中實際測量的馬達之運轉頻率、電壓及電流所構成。 The viscosity learning and prediction system as described in claim 1, wherein the driving element is composed of a motor, and the second process variable information is composed of the operating frequency, voltage and current of the motor actually measured during the stirring process. 如請求項1所述之黏度學習暨預測系統，其中，該桶槽更與該第一控制單元及該第二控制單元電性連接並透過網路連接至該伺服器，在該桶槽攪拌過程中將當前混合物濃度資訊輸入至該伺服器中，該伺服器透過該第一控制單元與該第二控制單元分別擷取當前第一過程變量資訊及當前第二過程變量資訊，並將當 前混合物濃度資訊、當前第一過程變量資訊及當前第二過程變量資訊分別與該模型中的混合物濃度資訊、第一過程變量資訊及第二過程變量資訊進行比對，以預測得出當前混合物之黏度。 The viscosity learning and prediction system as described in claim 1, wherein the tank is electrically connected to the first control unit and the second control unit and connected to the server through the network. During the mixing process of the tank The current mixture concentration information is input into the server. The server acquires the current first process variable information and the current second process variable information through the first control unit and the second control unit respectively, and stores the current mixture concentration information into the server. The previous mixture concentration information, current first process variable information and current second process variable information are compared with the mixture concentration information, first process variable information and second process variable information in the model respectively to predict the current mixture viscosity.
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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180299375A1 (en) * 2015-04-27 2018-10-18 Virtual Fluid Monitoring Services LLC Fluid analysis and monitoring using optical spectroscopy
US20190121343A1 (en) * 2016-05-09 2019-04-25 Strong Force Iot Portfolio 2016, Llc Systems and methods of data collection and analysis of data from a plurality of monitoring devices
CN110935337A (en) * 2018-09-21 2020-03-31 三菱电机自动化(中国)有限公司 Stirring system and stirring method
CN112834729A (en) * 2021-01-08 2021-05-25 三一汽车起重机械有限公司 Hydraulic oil quality monitoring method, device and system
TW202223561A (en) * 2020-09-18 2022-06-16 德商巴斯夫歐洲公司 Chemical production control
CN114898819A (en) * 2022-04-06 2022-08-12 中国石油大学(北京) Mixed crude oil viscosity prediction model training method and device and application method
TW202243808A (en) * 2020-12-18 2022-11-16 美商應用材料股份有限公司 Adaptive slurry dispense system

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180299375A1 (en) * 2015-04-27 2018-10-18 Virtual Fluid Monitoring Services LLC Fluid analysis and monitoring using optical spectroscopy
US20190121343A1 (en) * 2016-05-09 2019-04-25 Strong Force Iot Portfolio 2016, Llc Systems and methods of data collection and analysis of data from a plurality of monitoring devices
CN110935337A (en) * 2018-09-21 2020-03-31 三菱电机自动化(中国)有限公司 Stirring system and stirring method
TW202223561A (en) * 2020-09-18 2022-06-16 德商巴斯夫歐洲公司 Chemical production control
TW202243808A (en) * 2020-12-18 2022-11-16 美商應用材料股份有限公司 Adaptive slurry dispense system
CN112834729A (en) * 2021-01-08 2021-05-25 三一汽车起重机械有限公司 Hydraulic oil quality monitoring method, device and system
CN114898819A (en) * 2022-04-06 2022-08-12 中国石油大学(北京) Mixed crude oil viscosity prediction model training method and device and application method

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