Measurements and Control in Biosystems Engineering

44B0718

Bachelor

German

5.0

only summer term

1 semester

The module is a hybrid module. A large percentage of the module must be completed by students on their own responsibility by carrying out experiments and exercises. Weekly meetings with presentations on the basics, tasks, but also on the problems in solving the homework round off the module, which therefore focuses to a large extent on action orientation. 

The module aims to increase students' digital skills (i.e. understanding and handling digital data). Through 8 special exercises, which are carried out in an action-oriented manner as homework on real objects (plants, liquids, gases, etc.), these skills are developed in a sustainable and independent manner.  Students are provided with a specially compiled hardware and software kit for this purpose. 

An introductory session introduces the topic of "Measuring and Analysis", presents the tasks and explains procedures. The students are then given the exercise materials (hardware and software kit). 

The 8 work sessions in the first week of each session consist of a brief introduction to the underlying sensor technology and information on the task and solution approaches. In the second session week, there will be a joint question and answer session on problems encountered when working on the homework exercise. The deadline for submitting the homework is in the third week of the session. In the fourth week of the session, the digital homework is returned by the team of lecturers with notes, corrections and grading. "24/7 support" in interval mode in Ilias-Learning-Platform forum supports student work with current problems.

At the end of the module, there is a session that focuses on the oral examination of the term paper and thus goes through the homework again. Furthermore, the construction kits are handed in, the components are checked together with the students and maintenance lists are worked through. 

The homework is submitted in electronic form.

Sessions:
0. Introduction to measurements with RedLab/Labjack and Arduino (without exercise evaluation)
1. Self-construction of a psychrometer and evaluation with resistance sensors, RedLab and ProfiLab-Expert.
2. Self-construction of a level measurement system with ultrasonic sensors, Arduino and Python.
3. Radiation measurement with plant reference using solarimeter, Redlab and Excel.
4. Soil moisture measurement with capacitive sensor, Arduino and Excel.
5. Leaf area evaluation with cell phone and ImageJ.
6. Classification of plant species with Handy, ImageJ and NeuralDesigner (KNN).
7. Tracer gas measurement with capacitive sensor,
Arduino and R-Studio.
8. Phytopathological determinations with remote sensing (spectrometry, infrared camera technology and lidar technology) and evaluation algorithms in R. (two dates)

The total workload for the module is 150 hours (see also "ECTS credit points and grading").

Other: Independent development and implementation of measurement chains in the field of biosystems technology: from sensor selection to presentation of results. 

• Work practical and oral exam

Work sample: timely submission of 8 homework exercises, each homework exercise counts equally, total share of work samples in the grade: 50%

Oral examination: questioning on individual work samples, total share of the oral examination in the grade: 50%.

Work samples: 8 of 8 work samples must be handed in

Oral examination: 15 minutes with 2 examiners

Basic knowledge of growth factors and an interest in solving problems using technology, especially computer technology. Programming prerequisites are explicitly not required. Knowledge of Excel and R is an advantage, but not mandatory. 

After successfully completing the module, students are able to put their theoretical knowledge of data collection with sensors into practice. They acquire knowledge in the area of algorithm development and programming using conventional programming languages as well as graphical programming and special programming tools such as R.

After completing the module, students will have detailed knowledge of growth factors and technical parameters in biosystems. They will know how data can be collected and which special features (e.g. data scaling, sensor calibrations, sensor placement, subtleties of statistical evaluation) must be taken into account in biosystems. 

After completing the module, students will be able to record, process and evaluate digital data. In detail:
1. they are able to set up measurement chains, calibrate sensor systems, adapt data formats and process them further with software.
2. be able to collect digital measurement data using the latest software, summarize it statistically and present it graphically or in tabular form. 
3. understand the most important measurement principles of modern measurement technology in biosystems engineering and can use them in real environments.
4. be able to create algorithms for data acquisition and processing in different programming environments and languages.

Students can apply the knowledge they have learned to all measurements during their studies. The module enables them to work in scientific fields and to learn further special methods quickly and efficiently.

Students will be able to select which measurement methods are suitable for specific measurement tasks using which current hardware and software. They are also able to understand and critically scrutinize new measurement concepts. 

After completing the module, students will be able to participate verbally and in writing in meetings, discussions and presentations on the measurement technology sector with its special vocabulary. They will know the most important technical terms, be able to implement algorithmic methods and present them verbally, graphically and textually using technical terms and expressions. 

Students increase their professionalism and self-confidence with regard to the handling of digital data, algorithms and processes, especially in the areas of plants and bioprocess engineering. They will be able to professionally set up measurement chains and use them in a beneficial and qualified manner in their future field of work.  

• Rath, Thomas

• Rath, Thomas