How to stretch system reliability exploiting mission constraints: A practical roadmap for industries

Reliability analysis can be committed to companies by customers willing to verify whether their products comply with the major international standards or simply to verify the design prior of market deployment. Nevertheless, these analyses may be required at the very preliminary stages of design or when the design is already in progress due to low organizational capabilities or simple delay in the project implementation process. The results sometime maybe be far from the market or customer target with a subsequent need to redesign the whole asset. Of course, not all the cases fall in the worst scenario and maybe with some additional consideration on mission definition it is possible to comply with the proposed reliability targets. In this paper the author will provide an overview on the approach which could be followed to achieve the reliability target even when the project is still on-going providing a practical case study

A Low Complexity Rolling Bearing Diagnosis Technique Based on Machine Learning and Smart Preprocessing

In this work, we present a diagnosis system for rolling bearings that leverages simultaneous measurements of vibrations and machine rotation speed. Our approach combines the robustness of simple time domain methods for fault detection with the potential of machine learning techniques for fault location. This research is based on a neural network classifier, which exploits a simple and novel preprocessing algorithm specifically designed for minimizing the dependency of the classifier performance on the machine working conditions, on the bearing model and on the acquisition system set-up. The overall diagnosis system is based on light algorithms with reduced complexity and hardware resource demand and is designed to be deployed in embedded electronics. The fault diagnosis system was trained using emulated data, exploiting an ad-hoc test bench thus avoiding the problem of generating enough data, achieving an overall classifier accuracy larger than 98%. Its noteworthy ability to generalize was proven by using data emulating different working conditions and acquisition set-ups and noise levels, obtaining in all the cases accuracies greater than 97%, thereby proving in this way that the proposed system can be applied in a wide spectrum of different applications. Finally, real data from an on-line database containing vibration signals obtained in a completely different scenario are used to demonstrate the distinctive capability of the proposed system to generalize

Gas sensing properties of In2O3 nano-films obtained by low temperature pulsed electron deposition technique on alumina substrates

Nanostructured Indium(III) oxide (In2O3) films deposited by low temperature pulsed electron deposition (LPED) technique on customized alumina printed circuit boards have been manufactured and characterized as gas sensing devices. Their electrical properties have monitored directly during deposition to optimize their sensing performance. Experimental results with oxidizing (NO2) as well as reducing (CO) gases in both air and inert gas carriers are discussed and modeled

Chiral azole derivatives. 4. Enantiomers of bifonazole and related antifungal agents: synthesis, configuration assignment, and biological evaluation

The first synthesis, full stereochem. characterization and biol. evaluation of of both enantiomers of bifonazole (I) and the related II, III and IV are described

Strategies for the Accurate Measurement of the Resonance Frequency in QCM-D Systems via Low-Cost Digital Techniques

In this paper, an FPGA (Field Programmable Gate Array)-based digital architecture for the measurement of quartz crystal microbalance (QCM) oscillating frequency of transient responses, i.e., in QCM-D (QCM and Dissipation) applications, is presented. The measurement system is conceived for operations in liquid, with short QCM transient responses due to the large mechanical load. The proposed solution allows for avoiding the complex processing systems typically required by the QCM-D techniques and grants frequency resolutions better than 1 ppm. The core of the architecture is a reciprocal digital frequency meter, combined with the preprocessing of the QCM signal through mixing operations, such as a step-down of the input frequency and reducing the measurement error. The measurement error is further reduced through averaging. Different strategies are proposed to implement the proposed measurement solution, comprising an all-digital circuit and mixed analog/digital ones. The performance of the proposed architectures is theoretically derived, compared, and analyzed by means of experimental data obtained considering 10 MHz QCMs and 200 μs long transient responses. A frequency resolution of about 240 ppb, which corresponds to a Sauerbrey mass resolution of 8 ng/cm2, is obtained for the all-digital solution, whereas for the mixed solution the resolution halves to 120 ppb, with a measurement time of about one second over 100 repetitions

A Distributed IoT Air Quality Measurement System for High-Risk Workplace Safety Enhancement

The safety of an operator working in a hazardous environment is a recurring topic in the technical literature of recent years, especially for high-risk environments such as oil and gas plants, refineries, gas depots, or chemical industries. One of the highest risk factors is constituted by the presence of gaseous substances such as toxic compounds such as carbon monoxide and nitric oxides, particulate matter or indoors, in closed spaces, low oxygen concentration atmospheres, and high concentrations of CO2 that can represent a risk for human health. In this context, there exist many monitoring systems for lots of specific applications where gas detection is required. In this paper, the authors present a distributed sensing system based on commercial sensors aimed at monitoring the presence of toxic compounds generated by a melting furnace with the aim of reliably detecting the insurgence of dangerous conditions for workers. The system is composed of two different sensor nodes and a gas analyzer, and it exploits commercial low-cost commercially available sensors

Space-Air-Ground Integrated 6G Wireless Communication Networks: A Review of Antenna Technologies and Application Scenarios

A review of technological solutions and advances in the framework of a Vertical Heterogeneous Network (VHetNet) integrating satellite, airborne and terrestrial networks is presented. The disruptive features and challenges offered by a fruitful cooperation among these segments within a ubiquitous and seamless wireless connectivity are described. The available technologies and the key research directions for achieving global wireless coverage by considering all these layers are thoroughly discussed. Emphasis is placed on the available antenna systems in satellite, airborne and ground layers by highlighting strengths and weakness and by providing some interesting trends in research. A summary of the most suitable applicative scenarios for future 6G wireless communications are finally illustrated

Characterization of the Response of Magnetron Sputtered In2O3−x Sensors to NO2

The response of resistive In2O3−x sensing devices was investigated as a function of the NO2 concentration in different operative conditions. Sensing layers are 150 nm thick films manufactured by oxygen-free room temperature magnetron sputtering deposition. This technique allows for a facile and fast manufacturing process, at same time providing advantages in terms of gas sensing performances. The oxygen deficiency during growth provides high densities of oxygen vacancies, both on the surface, where they are favoring NO2 absorption reactions, and in the bulk, where they act as donors. This n-type doping allows for conveniently lowering the thin film resistivity, thus avoiding the sophisticated electronic readout required in the case of very high resistance sensing layers. The semiconductor layer was characterized in terms of morphology, composition and electronic properties. The sensor baseline resistance is in the order of kilohms and exhibits remarkable performances with respect to gas sensitivity. The sensor response to NO2 was studied experimentally both in oxygen-rich and oxygen-free atmospheres for different NO2 concentrations and working temperatures. Experimental tests revealed a response of 32%/ppm at 10 ppm NO2 and response times of approximately 2 min at an optimal working temperature of 200 °C. The obtained performance is in line with the requirements of a realistic application scenario, such as in plant condition monitoring

Ontogeny of synaptophysin and synaptoporin in the central nervous system

The expression of the synaptic vesicle antigens synaptophysin (SY) and synaptoporin (SO) was studied in the rat striatum, which contains a nearly homogeneous population of GABAergic neurons. In situ hybridization revealed high levels of SY transcripts in the striatal anlage from embryonic day (E) 14 until birth. In contrast. SO hybridization signals were low, and no immunoreactive cell bodies were detected at these stages of development. At E 14, SY-immunoreactivity was restricted to perikarya. In later prenatal stages of development SY-immunoreactivity appeared in puncta (identified as terminals containing immunostained synaptic vesicles), fibers, thick fiber bundles and ‘patches’. In postnatal and adult animals, perikarya of striatal neurons exhibited immunoreaction for SO; ultrastructurally SO antigen was found in the Golgi apparatus and in multivesicular bodies. SO-positive boutons were rare in the striatum. In the neuropil, numerous presynaptic terminals positive for SY were observed. Our data indicate that the expression of synaptic vesicle proteins in GABAergic neurons of the striatum is developmentally regulated. Whereas SY is prevalent during embryonic development, SO is the major synaptic vesicle antigen expressed postnatally by striatal neurons which project to the globus pallidus and the substantia nigra. In contrast synapses of striatal afferents (predominantly from cortex, thalamus and substantia nigra) contain SY