Theory: 50 %

Practice: 50 %

Recommended semester: 6

Study mode: full-time

Prerequisites:

Evaluation type: term mark

Course category:

Language: english

Responsible instructor: Dr. Pintér István

Responsible department: Department of Information Technologies

Instructor(s): Dr. Pintér István

Course objectives:
The objective of the course is to introduce the basic concepts of measurement systems and DAQ systems used in industrial processes, including modern digital signal and image processing tools and methods.

Course content - lectures:

1. Introducing 2. Elements of measurement systems 3. The role of DAQ systems in industrial processes. 4. Simple, multi-channel, and computerized measurement systems. 5. Measurement signals 6. Types, operation, and applications of measurement sensors. 7. Sampling 8. Quantization, 9. A/D and D/A converters, and their applications. 10. The fundamentals and industrial applications of digital signal processing. 11. The fundamentals and industrial applications of digital image processing. 12. The prospects for the development of measurement automation, signal and image processing.

Course content - labs:

To acquire skills-level knowledge, the purpose of the laboratory exercises is to introduce tools available for rapid application development (LabView, intelligent cameras).

Acquired competences:
Knowledge:

Capable of applying the technical specifications related to the operation of mechanical systems, as well as the principles of setting up and operating machinery and mechanical equipment, and their economic correlations. Able to understand and use the characteristic professional literature, computational, and library resources of their field. Capable of applying the most important terminologies, theories, and procedures of the given technical field when executing tasks related to them. Able to plan, organize, and conduct independent learning.

Skills:

Has a working knowledge of the measurement techniques used in mechanical engineering, including their tools, instruments, and measuring equipment. Thoroughly understands the learning, knowledge acquisition, data collection methods of the mechanical engineering field, their ethical limits, and problem-solving techniques. Knows the general and specific mathematical, natural science, and social science principles, rules, relationships, and procedures necessary for practicing the technical field.

Attitude:

Strives to solve problems in collaboration with others. Strives to ensure that self-education in the field of mechanical engineering is continuous and aligned with professional goals. Strives to make decisions on task solutions and leadership based on understanding the opinions of directed staff and, whenever possible, in collaboration.

Autonomy and responsibilities:

During the performance of professional tasks, collaborates with trained professionals from other disciplines (primarily technical, as well as economic and legal). Identifiesthe shortcomings of applied technologies, the risks of processes, and initiates actions to mitigate these. Monitors legislative, technical, technological, and administrative changes related to the field.

Additional professional competences:

Requirements, evaluation, grading:
Mid-term study requirements:
Achievement of at least the TVSz minimum with the assignments, study material and the mark paper. The examination is written, but a mark may be awarded for the subject in accordance with the current TVSz.
Exam requirements:

Study aids, laboratory background:

Compulsory readings:

Recommended readings:

M. Sonka, V. Hlavac, R. Boyle: Image Processing, Analysis and Machine Vision. Thomson, 2008. Herbert Bernstein: Messelektronik und Sensoren: Grundlagen der Messtechnik, Sensoren, analoge