The system will be going down for regular maintenance at 6pm NZT today for approximately 15minutes. Please save your work and logout.
High speed weighing system analysis via mathematical modelling : a thesis presented in partial fulfilment of the requirements for a degree of Masters of Engineering, Mechatronics at Massey University, Albany, Auckland, New Zealand
In-process electronic high speed weighing systems play an important role in the highly
automated, continuously evolving industrial world of today. They are an essential component
in sorting, grading and quality control within a diverse range of industries, including;
robotics, automotive and food. Load cells are considered to be the definitive force sensor for
industrial weighing systems. Load cell output is in the form of an oscillatory response in
which the measurand contributes to the response characteristics. Current methods require the
oscillatory response to settle in order to achieve an accurate measurement. This is time
consuming and speed limiting.
The focus of this paper is to find alternative weighing analysis methods for a system which
utilises two load cells, placed either side of a carrier travelling on a chain conveyor, running
at speeds of 10 items a second. It is necessary to determine the value of the measurand in the
fastest time possible to speed up the process and increase throughput. This has been
approached by mathematically modelling the system to allow accurate prediction of the
weights passing the load cells before the settling time of the oscillatory response. Models of
harmonic motion have been considered for the motion of a load cell.
An experimental system was built and weighing data collected for different speeds and loads.
Spectral analysis of the weighing data was analysed to determine dominant frequencies and
estimate system parameters.
This thesis describes the work done on load cell modelling and improving an in-process
electronic weighing system by successfully predicting the weight during the transient period
of the oscillatory response. The assumptions and results of both simulations and experimental
data are presented.