Міністерство освіти і науки України

Херсонський національний технічний університет

Кафедра іноземних мов

Рег. № 6/534 - 23.06.08

Методичні рекомендації

за темою “Machine vision: the eyes of integrated manufacturing ”

для проведення практичних занять

з дисципліни “ Іноземна мова професійного спілкування”

для студентів 3 курсу

для спеціальності 091401 Системи управління і автоматики

напряму підготовки 0914 Комп’ютеризовані системи,

автоматика і управління

факультету кібернетики

Херсон 2008

Методичні рекомендації для проведення практичних занять з дисципліни „Іноземна мова професійного спілкування” для студентів 3 курсу факультету кібернетики спеціальності 091401 Системи управління і автоматики напрямку підготовки 0914 Комп’ютеризовані системи, автоматика і управління за темою „Machine vision: the eyes of integrated manufacturing”.

Укладач : ст.викл. Сіденко Н.Г., кількість сторінок 13.

Рецензент : доц.Фоменко Н.С.

Затверджено

на засіданні кафедри іноземних мов

протокол №8 від 9.04.08

Зав.кафедри ____________доц.Фоменко Н.С.

Цілі

Практичні:

• формування вміння зрілого( аналітичного) читання для подальшого опанування засобами вторинної обробки інформації;

• розвиток вміння професійного спілкування.

Розвиваючі:

• розвиток аналітичного мислення;

• тренування розумових операцій.

Освітня:

• інтеграція фахових знань за темою.

Виховна:

• виховання поважного ставлення до майбутньої професії, усвідомлення її престижу та значення для суспільства.

Обладнання: Методичні рекомендації для практичного заняття по темі:„Machine vision: the eyes of integrated manufacturing.”

Хід заняття:

І. Організаційний момент.

ІІ. Смислова антиципація:

1. Before reading the text answer the following questions.

III. Активізація фонетичних навичок.

IV. Лексико- граматичний етап:

1.Remember the words before reading the text.

2. Match the words according to their similar/ opposite meaning.

3. Fill in the table with the words from the text according to the classification.

4. Translate the list of the words.

5. Translate the sentences.

6. Make the syntactical analysis of the sentence

V. Логіко- семантичний етап:

1. Find the correspondence.

2. Find, read and translate the sentences from the text illustrating the following items.

VI. Структурно-логічний етап:

1.Fill in the logic scheme with the points of the plan.

2. Make up an array ( matrix) of the text.

3. Using the matrix of the text speak on the points above- mentioned.

VII. Аналітичний етап:

( Do these exercises in Russian/ Ukrainian)

1. Explain the difference in operation between the early vision systems and modern commercial ones.

2. Describe how some vision systems evaluate images.

3. Define the advantages of vision systems over humans in quality control.

4. Explain why machine vision systems are vital element in factory automation.

5. Find out the relationship between:

a) analysts--- users--- experts;

b) observers--- vendors--- suppliers in the problem of

machine vision applications.

VIII. Заключний етап:

1. Пояснення домашнього завдання.

2. Підведення підсумків заняття.

I. Contents anticipation:

Before you read the text, read the following questions. Do you know the answers already? Discuss them briefly with your class- mates.

1. Why do you think machine vision is the eyes of integrated manufacturing?

2. Does machine vision include lasers, sonar and infrared sensors?

3. Why is machine vision necessary for integrated manufacturing?

II. Phonetic drill:

machine vision

infrared

environment

laser

processor

image

pixel

characteristic

multiple

technique

unique

vital

guidance

analyst

expert

advocate

supplier

criterion

requirement

purpose

sequence

The lexical- grammar stage.

III. Reading .

Text„Machine vision: the eyes of integrated manufacturing”

Remember the words:

environment (1) оточуюче середовище expensive(7) дорогий

dot (2) крапка scrap(7) відходи

light intensity(3) напруженість світла warranty costs(7) гарантійні витрати

to discern(3) розпізнавати benefits(9) користь

to evaluate(5) оцінювати to custom the program(11) добирати програму

to emerge (7) з’являтися vendor(11) продавець

( 1) Machine vision is a technique for gathering data from the surrounding environment. Although most often thought of as cameras and image processors, machine vision also includes technologies such as lasers as well as sonar and infrared sensors.

(2) Most vision systems, however, consist of a camera, image processor and an operator interface. Images are gathered by the camera in a field made of small dots called pixels. Each pixel represents the light at that point and is given a value as such. Early vision systems operated in a binary fashion, in which each pixel was reduced to a light/ no light value.

(3) Practical applications of vision systems demanded so-called gray scale images, in which each pixel is given a value representing light intensity. Most commercial vision systems can discern 64 levels of light, or gray scales, although some operate at 264 gray- scale levels to handle more demanding tasks.

(4) Another important characteristic of vision systems is resolution, the number of pixels that can be processed. Today’s vision systems typically operate at 512 ( horizontal) x 512 ( vertical) pixels. Newer versions handle 1,024 x 1,024 resolution, which increase the field of vision by a factor of four over 512 x 512 systems. Such systems eliminate or reduce the need for multiple cameras to make vision more reliable as well as easier to install and maintain.

(5) Many algorithms and techniques are needed to evaluate an image. This function generally determines the number of features the system can check and the time required to make such checks. Some vision systems evaluate images with sophisticated software, while others use unique hardware to speed up the process.

(6) Although vision systems can perform much more „intelligent” part of inspections than other type of equipment, a price must be paid and that is in programming. Telling the system exactly what to look for can be time- consuming. But sophisticated programming methods using computer graphics and menus ease this task greatly. Eventually, vision systems will be able to take part geometry directly from CAD/CAM to further reduce programming time.

(7) Machine vision systems are emerging as a vital element in factory automation, to help ensure quality and providing feedback to control production processes. Quality control applications are especially pushing the progress of machine vision. Although vision systems are fairly expensive, they can provide an increase in quality that can quickly pay for itself. These savings come from reduced scrap, less rework, and lower warranty costs.

(8) Most of this quality control is being implemented as inspection systems, in which the vision device checks parts for qualities that are impossible with means other than human inspection. But unlike humans, vision systems do not get tired or sick and are more accurate, faster, or both. Moreover, vision systems provide a consistent method for performing inspections, eliminating variations that may lead to rejection of good parts or acceptance of bad parts.

(9) Integrated manufacturing practically requires the benefits of machine vision. Since vision systems are computer- based, they can be programmed and can communicate with other intelligent devices and even higher-level computers such as CAD/CAM systems.

(10) Another application for vision in the factory is robot guidance. The idea is to allow robots to see what they are doing, increasing productivity and flexibility of the device. Industry analysts debate: the complexity and costs limit vision to a small percentage of installed robots.

(11) Advocates of robot vision , however, seem to be winning the argument.

Vision systems must become easier to program if they are to see widespread use in the factory. Users cannot afford experts to custom program each system since a large factory may have dozens or even hundreds of vision systems.

Industry observers also point out that vision vendors must become more „factory- oriented” if they are to meet the needs of integrated manufacturing. Many suppliers sprung from academia and therefore may not understand the harsh realities of the factory.

(12) Although work is being done on three- dimensional robot guidance, practical applications in vision systems are simpler.