This paper focuses on the problematic of intraocular pressure (IOP) measurements, performed by non-invasive methods. More specifically, the devices that are connected with the presented finding are non-contact tonometers that use concentrated air stream and optical sensors to determine the IOP within a human’s eye. The paper analyzes various influential factors that have an effect on the determination of the IOP values originating from the patients themselves and from the non-contact tonometer devices. The paper furthermore elaborates on the lack of independent methods of calibration and control of these devices. In order to fill this gap a measurement standard device that is capable of calibrating and testing these devices with traceability to the basic SI unit is presented. A detailed characterization and the determination of the expected uncertainty of the device are provided. By introducing an independent and traceable calibration method and control of non-contact tonometers into the clinical practice, the reliability of the measured IOP that is the primary indicator of glaucoma can be improved.

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Measuring the swing angle of a crane load is a relatively well-known but unsatisfactorily solved problem in technical practice. This measurement is necessary for the automatic stabilization of load swing without human intervention. This article describes a technically simple and new approach to solving this problem. The focus of this work is to determine the accuracy of the measuring device. The focus of this work remains on the design, the principle of operation of the equipment, and the determination of accuracy. The basic idea is to apply the strain gauge on an elastic, easily deformable component that is part of the device. One part of the elastic component is fixedly connected to the frame; the other part is connected to the crane rope by means of pulleys close to the rope. In this way, the bending of the elastic component in proportion to the swing angle of the payload is ensured.

This paper presents a simple-to-use system for estimating non-measurable components of crane state vector considering parameter changes. To obtain them, it is possible to use a numerical derivative, where the measurement noise causes great inaccuracies, or the Luenberger observer and Kalman filter, which require knowledge of the dynamics of the controlled system, which is constantly changing with the crane.