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One of the most important design factors in modern turbomachinery is the vibration of turbomachinery blading. There is a need for developing an in-service, noncontacting, noninterfering method for the measurement and monitoring of gas turbine, jet engine, and steam turbine blade vibrations and stresses. Such a technique would also be useful for monitoring rotating helicopter blades. In the power generation industry, blade failures can result in millions of dollars of downtime. The measurement of blade vibrations and dynamic stresses is an important guide for preventive maintenance, which can be a major contributor to the availability of steam turbine, gas turbine, and helicopter operations. An experiment is designed to verify the feasibility of such a vibration monitoring system using the reference beam on-axis laser-Doppler technique. The experimental setup consists of two flat, cantilever blades mounted on a hub attached to the shaft of a dc motor. The motor rests on a linear bearing permitting motion only in the direction of the motor shaft. The motor and blade assembly is then excited via an electrodynamic shaker at the first natural frequency of the blades. The resulting blade vibration is then detected using a laser vibrometer. The vibration frequencies and amplitudes of the two rotating blades are successfully measured.

Applied privacy research has so far focused mainly on consumer relations in private life. Privacy in the context of employment relationships is less well studied, although it is subject to the same legal privacy framework in Europe. The European General Data Protection Regulation (GDPR) has strengthened employees’ right to privacy by obliging that employers provide transparency and intervention mechanisms. For such mechanisms to be effective, employees must have a sound understanding of their functions and value. We explored possible boundaries by conducting a semi-structured interview study with 27 office workers in Germany and elicited mental models of the right to informational self-determination, which is the European proxy for the right to privacy. We provide insights into (1) perceptions of different categories of data, (2) familiarity with the legal framework regarding expectations for privacy controls, and (3) awareness of data processing, data flow, safeguards, and threat models. We found that legal terms often used in privacy policies used to describe categories of data are misleading. We further identified three groups of mental models that differ in their privacy control requirements and willingness to accept restrictions on their privacy rights. We also found ignorance about actual data flow, processing, and safeguard implementation. Participants’ mindsets were shaped by their faith in organizational and technical measures to protect privacy. Employers and developers may benefit from our contributions by understanding the types of privacy controls desired by office workers and the challenges to be considered when conceptualizing and designing usable privacy protections in the workplace.

The increasing presence of renewable sources requires power grid operators to continuously monitor electricity generation and demand in order to maintain the grid's stability. To this end, smart meters have been deployed to collect real-time information about the current grid load and forward it to the utility in a timely manner. High resolution smart meter data can however reveal the nature of appliances and their mode of operation with high accuracy, and thus endanger user privacy. In this paper, we investigate the impact on user privacy when the consumption data collected by distributed smart metering devices are preprocessed prior to their usage. We therefore assess the impact on the successful classification of appliances when sensor readings are (1) quantized, (2) down-sampled at a lower sampling rate, and (3) averaged by means of an FIR filter. Our evaluation shows that a combination of these preprocessing steps can provide a balanced trade-off that is in the interests of both users (privacy protection) and utilities (near real-time information).