本文選題：中藥　切入點(diǎn)：物聯(lián)網(wǎng)　出處：《河北工業(yè)大學(xué)》2014年碩士論文

【摘要】：隨著我國(guó)經(jīng)濟(jì)的持續(xù)快速發(fā)展和人們生活水平的提高，產(chǎn)品質(zhì)量問(wèn)題越來(lái)越受到公眾的關(guān)注，因此，中藥生產(chǎn)企業(yè)越來(lái)越重視對(duì)產(chǎn)品生產(chǎn)過(guò)程的監(jiān)控。物聯(lián)網(wǎng)技術(shù)作為一種新興技術(shù)，在工業(yè)上已經(jīng)開(kāi)始應(yīng)用，主要集中在制造業(yè)供應(yīng)鏈管理、產(chǎn)品生產(chǎn)過(guò)程監(jiān)控、能源管理和生產(chǎn)安全等。中藥生產(chǎn)過(guò)程監(jiān)控應(yīng)用物聯(lián)網(wǎng)技術(shù)，為實(shí)現(xiàn)生產(chǎn)過(guò)程中產(chǎn)品信息的跟蹤和追溯提供了基礎(chǔ)平臺(tái)，為提高中藥產(chǎn)品質(zhì)量、規(guī)范企業(yè)管理方式、增強(qiáng)企業(yè)信息化水平有重大作用。 本文所研究的中藥生產(chǎn)過(guò)程監(jiān)控系統(tǒng)正是基于工業(yè)物聯(lián)網(wǎng)提出來(lái)的，將中藥生產(chǎn)的提取、濃縮、醇沉等工藝流程以及其他操作環(huán)節(jié)與工業(yè)物聯(lián)網(wǎng)技術(shù)相結(jié)合，分別從感知控制層、數(shù)據(jù)傳輸層、數(shù)據(jù)存儲(chǔ)層、應(yīng)用決策層四個(gè)方面對(duì)中藥生產(chǎn)過(guò)程監(jiān)控系統(tǒng)進(jìn)行了詳細(xì)的設(shè)計(jì)。并對(duì)其中應(yīng)用到的數(shù)據(jù)采集、工業(yè)以太網(wǎng)和數(shù)據(jù)庫(kù)知識(shí)進(jìn)行了分析，將整個(gè)中藥生產(chǎn)過(guò)程監(jiān)控起來(lái)，建立一個(gè)從自動(dòng)化級(jí)到管理級(jí)的同一信息流，提高整個(gè)企業(yè)的效率和競(jìng)爭(zhēng)力。 在監(jiān)控系統(tǒng)設(shè)計(jì)開(kāi)發(fā)中，針對(duì)感知控制層中料液濃度無(wú)法直接通過(guò)現(xiàn)有傳感器檢測(cè)問(wèn)題，提出了一種基于最小二乘支持向量機(jī)的軟測(cè)量預(yù)測(cè)模型優(yōu)化方案，，根據(jù)可檢測(cè)的輔助變量推導(dǎo)出主變量，可準(zhǔn)確估算當(dāng)前料液濃度情況。針對(duì)管理層對(duì)車(chē)間生產(chǎn)信息存在的信息孤島問(wèn)題，提出了將中藥生產(chǎn)執(zhí)行系統(tǒng)對(duì)應(yīng)用決策層的優(yōu)化方案，實(shí)現(xiàn)對(duì)企業(yè)生產(chǎn)過(guò)程全方位的監(jiān)控管理，對(duì)系統(tǒng)的功能模塊進(jìn)行詳細(xì)的設(shè)計(jì)并通過(guò)編程實(shí)現(xiàn)。隨著縱向數(shù)據(jù)集成成為可能，管理層將非常容易獲得底層實(shí)時(shí)數(shù)據(jù)，有了這些信息，管理級(jí)將更容易做出迅速、明智的決策。
[Abstract]:With the sustained and rapid development of our economy and the improvement of people's living standard, the problem of product quality has been paid more and more attention to by the public. As a new technology, Internet of things (IOT) technology has been applied in industry, mainly in the supply chain management of manufacturing industry and the monitoring of product production process. Energy management and production safety, etc. The application of the Internet of things technology in the process of traditional Chinese medicine production monitoring provides a basic platform for the tracking and tracing of product information in the production process, for improving the quality of traditional Chinese medicine products and for standardizing the management of enterprises. Enhancing the level of enterprise information has a major role. The traditional Chinese medicine production process monitoring system studied in this paper is based on the industrial Internet of things, which combines the extraction, concentration, alcohol precipitation and other operating links of traditional Chinese medicine production with the industrial Internet of things technology. The monitoring system of traditional Chinese medicine production process is designed in detail from four aspects: perceptual control layer, data transmission layer, data storage layer and decision layer. The knowledge of industrial Ethernet and database is analyzed, the whole production process of traditional Chinese medicine is monitored and a same information flow from automation level to management level is established, so as to improve the efficiency and competitiveness of the whole enterprise. In the design and development of monitoring system, a soft sensor prediction model optimization scheme based on least square support vector machine (LS-SVM) is proposed to solve the problem that the concentration of material in the perceptual control layer can not be detected directly through the existing sensors. The main variable can be deduced according to the detectable auxiliary variable, and the current concentration of feed liquid can be accurately estimated. Aiming at the problem of information isolated island existing in the production information of workshop by management, the optimization scheme of applying decision level to the execution system of traditional Chinese medicine production is put forward. Realize the omni-directional monitoring and management of the production process of the enterprise, design the function module of the system in detail and realize it by programming. With the possibility of vertical data integration, the management will easily obtain the real-time data of the bottom layer. With this information, it will be easier to make quick and informed decisions at the management level.
【學(xué)位授予單位】：河北工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TP277;TP391.44;TN929.5

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