本文選題：全自動(dòng)生化分析儀　切入點(diǎn)：遺傳算法　出處：《湖南大學(xué)》2012年碩士論文

【摘要】：生化分析儀作為一種主要醫(yī)療儀器通過(guò)采集的血液或體液樣本完成人體中各種生化指標(biāo)（如血糖、血脂、膽紅素及各種催化酶）的定量分析，檢測(cè)肝功、腎功、心肌酶譜、電解質(zhì)等健康狀況。目前，國(guó)內(nèi)絕大多數(shù)醫(yī)院主要采用國(guó)外進(jìn)口生化分析儀，具有檢測(cè)精度高、穩(wěn)定性強(qiáng)、自動(dòng)化程度高、功能強(qiáng)大等諸多優(yōu)點(diǎn)。隨著技術(shù)的進(jìn)步，國(guó)外一些生化分析儀制造廠家研發(fā)出了大型全自動(dòng)生化分析儀，能夠完成多指標(biāo)及復(fù)雜任務(wù)的快速檢測(cè)，無(wú)需人工參與。相比國(guó)外發(fā)展?fàn)顩r，國(guó)內(nèi)全自動(dòng)生化分析儀的發(fā)展較為緩慢，雖然已實(shí)現(xiàn)生化分析基本功能，但卻有諸多不足之處，主要體現(xiàn)在以下幾個(gè)方面：（1）國(guó)內(nèi)全自動(dòng)生化分析儀所需光源、高精密吸液機(jī)構(gòu)等核心元器件主要依靠進(jìn)口，尚無(wú)自主研發(fā)能力；（2）生化分析檢測(cè)方法簡(jiǎn)單，生化分析結(jié)果精度低、重復(fù)性和穩(wěn)定性差，常需人工參與，進(jìn)行重復(fù)或稀釋測(cè)試；（3）生化分析調(diào)度自動(dòng)化程度低，常采用人工設(shè)定的固定周期進(jìn)行項(xiàng)目調(diào)度，導(dǎo)致單次生化分析時(shí)間長(zhǎng)、多任務(wù)并行檢測(cè)技術(shù)瓶頸難以突破。 本文根據(jù)目前國(guó)內(nèi)大中型生化分析儀研發(fā)過(guò)程中存在的上述問(wèn)題，進(jìn)行了系統(tǒng)深入研究，取得的工作和創(chuàng)新具體如下： 針對(duì)用動(dòng)力學(xué)法測(cè)定酶活力過(guò)程中遇到的底物耗盡問(wèn)題，建立新的數(shù)據(jù)處理模型，運(yùn)用所提出的新算法自動(dòng)判別數(shù)據(jù)的線性區(qū)間與非線性區(qū)間，自動(dòng)選擇合適的線性數(shù)據(jù)用于酶活力的計(jì)算，，從而提高儀器的工作效率，降低重復(fù)測(cè)試的次數(shù)，擴(kuò)大儀器對(duì)樣品測(cè)試的濃度范圍，進(jìn)一步加快了使用的工作效率。 針對(duì)目前全自動(dòng)生化分析儀中對(duì)調(diào)度問(wèn)題采用的最大固定周期流水作業(yè)方法中存在檢測(cè)時(shí)間長(zhǎng)、效率低、存在間歇性和不連續(xù)性等諸多問(wèn)題，和已有的基于Job-Shop生化調(diào)度方法中易搜索至局部最優(yōu)和搜索效率不高的問(wèn)題，提出了一種基于遺傳算法尋優(yōu)的非固定周期多任務(wù)調(diào)度方法。該方法打破了按機(jī)械位置次序依次檢測(cè)的執(zhí)行方式，以批次處理時(shí)間最短為原則，設(shè)計(jì)基于grefenstette編碼的遺傳算法ATSP模型，優(yōu)化交叉和變異算子，解決在交叉和變異過(guò)程中產(chǎn)生非法路徑的難題，建立全自動(dòng)生化分析儀的ATSP模型，優(yōu)化全自動(dòng)生化分析儀調(diào)度。 本文在Delphi環(huán)境下實(shí)現(xiàn)了所提算法和新的數(shù)據(jù)處理模型的建立，采用SQLSever完成了數(shù)據(jù)庫(kù)模塊的設(shè)計(jì)，對(duì)生化分析儀的軟、硬件系統(tǒng)進(jìn)行了詳細(xì)的介紹，并基于該平臺(tái)完成對(duì)本文所提方法的驗(yàn)證，較好的完成預(yù)期目標(biāo)。
[Abstract]:Biochemical analyzer as a major medical instrument by collecting blood or body fluid samples to complete various biochemical indexes of body (such as blood glucose, blood lipids, bilirubin and various enzymes) quantitative analysis and detection of liver function, renal function, myocardial enzymes, electrolytes and other health conditions. At present, most domestic hospitals mainly using imported biochemical analyzer has high detection precision, strong stability, high degree of automation, powerful advantages. With the development of technology, some foreign manufacturers of biochemical analyzer developed large-scale automatic biochemical analyzer, rapid detection of multi index and able to complete complex tasks, without artificial participation. Compared the development situation of foreign and domestic development automatic biochemical analyzer is relatively slow, although the realization of the basic functions of biochemical analysis, but there are many shortcomings, mainly reflected in the following aspects: (1) China In the automatic biochemical analyzer for light source, the core components of high precision suction mechanism mainly rely on imports, there is no independent research and development ability; (2) the biochemical analysis of biochemical analysis of the detection method is simple, low precision, repeatability and stability is poor, often need artificial participation, repeat or dilution test; (3) the biochemical analysis of dispatching automation low level, often using fixed cycle artificial set of project scheduling, resulting in a single biochemical analysis of long time, multi task parallel bottleneck detection technology is difficult to break.
Based on the above problems existing in the development process of large and medium-sized biochemical analyzers in China, this paper makes a systematic and in-depth research.
According to the kinetic method for the determination of enzyme activity in the process of encounter substrate exhaustion problem, build a new data processing model, a new algorithm using the proposed automatic identification of linear and nonlinear interval interval data calculation, automatic selection of linear data suitable for enzyme activity, so as to improve the work efficiency of the instrument, reduce the number of repeated testing, expand the concentration range of the instrument on the sample test, and further accelerate the use efficiency.
Aiming at the detection time of maximum fixed cycle flow current methods of automatic biochemical analyzer on the scheduling problem in the long, low efficiency, intermittency and discontinuity problems based on Job-Shop biochemical scheduling method and the easy to search the local optimum and the search efficiency is not high, this paper proposes a fixed cycle multi task scheduling method based on genetic algorithm optimization. The method breaks the order according to the mechanical position detection means of implementation, to batch the principle of shortest time, genetic algorithm design of ATSP model based on grefenstette encoding optimization, crossover and mutation operators, solve the problem of generating illegal path in the process of crossover and mutation the establishment of ATSP model, automatic biochemical analyzer, automatic biochemical analyzer to optimize the scheduling.
In the Delphi environment to achieve the proposed algorithm and a new data processing model, using SQLSever to complete the design of the database module, the biochemical analyzer software and hardware system are introduced in detail, and based on the platform to complete the verification of the proposed method, accomplish the expected goal.

【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：R318.6

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