A laser Doppler velocimetry technique has been implemented in this work to evaluate the water jet velocity distribution in water jet and abrasive water jet cutting applications. Knowledge of the water jet velocity is fundamental to determine the system cutting efficiency; in particular, it allows us to experimentally determine the specific performance of the orifices employed in the cutting process.

The paper presents the application of a phase-sensitive optical time-domain reflectometer (phi-OTDR) in the field of urban infrastructure monitoring. In particular, the branched structure of the urban network of telecommunication wells. The encountered tasks and difficulties are described. The possibilities of usage are substantiated, and the numerical values of the event quality classification algorithms applied to experimental data are calculated using machine learning methods. Among the considered methods, the best results were shown by convolutional neural networks, with a probability of correct classification as high as 98.55%.

In recent years, attention to the realization of a distributed fiber-optic microphone for the detection and recognition of the human voice has increased, whereby the most popular schemes are based on φ-OTDR. Many issues related to the selection of optimal system parameters and the recognition of registered signals, however, are still unresolved. In this research, we conducted theoretical studies of these issues based on the φ-OTDR mathematical model and verified them with experiments. We designed an algorithm for fiber sensor signal processing, applied a testing kit, and designed a method for the quantitative evaluation of our obtained results. We also proposed a new setup model for lab tests of φ-OTDR single coordinate sensors, which allows for the quick variation of their parameters. As a result, it was possible to define requirements for the best quality of speech recognition; estimation using the percentage of recognized words yielded a value of 96.3%, and estimation with Levenshtein distance provided a value of 15.

Vibration energy harvesting is a clean way to extract kinetic energy from the environment and convert it into electrical energy that can be used locally to power small electronic devices, like sensors and low-power electronic systems. A vibration energy harvester can be embedded into the transducer, allowing easy repositioning of the device, and providing a permanent power supply, with no need for batteries or cables. In industrial environments, machines in operating conditions can provide a large source of mechanical vibrations. The majority of energy harvesting devices that have been proposed in the literature use a single degree of freedom configuration, where an oscillating mass is constrained to vibrate in one direction only. When the vibration is changing direction, such devices are much less efficient. In this paper, a planar two degrees of freedom configuration is proposed where the natural frequency of the oscillator is independent of the direction of excitation. This potentially allows more efficient energy to be harvested in practical circumstances.

Converting otherwise wasted kinetic energy present in the environment into usable electrical energy to power wireless sensor nodes, is a green strategy to avoid the use of batteries and wires. Most of the energy harvesters presented in the literature are based on the exploitation of a one-degree-of-freedom arrangement, consisting of a tuned spring-mass system oscillating in the main direction of the exciting vibration source. However, if the direction of excitation changes, the efficiency of the harvester decreases. This paper thus proposes the idea of a curved cantilever beam with a two-degree-of-freedom arrangement, where the two bending natural frequencies of the mechanical resonator are designed to be equal. This is thought to lead to a configuration design that can be used in practical circumstances where excitation varies its direction in the plane. This, in turn, may possibly lead to a more effective energy-harvesting solution to power nodes in a wireless sensor network.

Accurate laser spot-size measurements are important in many scientific and industrial applications: the knife-edge technique is commonly used to measure the laser beam dimension due to the relative ease, low cost, and reliability of the measurement. We propose an original use of a numerical method to evaluate the standard uncertainty of the measured laser spot-size in knife-edge measurements and we apply it to the analysis of experimental data from two different laser sources. The method allows obtaining the sensitivities of the spot-size uncertainty to the uncertainties of relevant input quantities such as the measured optical power and the knife-edge displacement. Since the indirect measurement of laser spot-size by the knife-edge technique is non-linear, analytical calculation of the uncertainty sensitivities is not possible and they are evaluated numerically based on experimental data and specific input noise/uncertainty conditions. By our analysis, calculation of specific sensitivities for two different experimental conditions is done and then used to estimate the standard uncertainty of the measured parameter: the standard radius of a Gaussian-beam laser spot. More generally, the method proposed allows evaluating the effects of different uncertainty contributions on the laser spot-size uncertainty estimation. This can then suggest proper design of the measurement experiment with the goal of reducing the final uncertainty. Accurate measurements, and of known and tailorable accuracy, of the laser parameters are of interest in different industrial applications where precise beam shaping is important.