Sensors and Instrumentation, Volume 5

High power density, high reliability and good controllability for varying load requirements are typical characteristics of hydraulic drive systems used for power transmission in stationary and mobile applications. Furthermore, hydraulic systems are usually safety related systems. Consequently, the handling of uncertainties in hydraulic systems is essential. A major source of uncertainty is, in particular, the wear induced change of the system behavior. Nowadays, the most common way to face uncertainty is the oversized system design to ensure reliable system operation. However, the uncertainty remains. In the first part of the paper we present a general approach to face uncertainty by means of a soft sensor network. Soft sensor networks make it possible to gather system information redundantly. In this way the occurrence of data conflicts are allowed which serve as an indicator of uncertainty. The resolution of these conflicts either lead to increased confidence for the model-based system information or allows the detection of changing component characteristics. The application of a soft sensor network to a hydraulic drive system is illustrated and discussed in the second part of this paper.

The aim of experimental modal analysis is to determine the structural dynamic characteristics of a given component or assembly. However, modal models are based on linear systems of equations and assume material orthotropy and linear stiffness components. Many industrial elements made of highly-complex, composite materials, do not accomplish these assumptions due to their non-linear material behavior. One practical measurement method is performing iterative modal analyses; this is, measurements at different force input levels. Several iterations lead to the knowledge of different points of the structural force/response spring curve and how this behavior affects the modal test.

In this paper, a novel Scalable Automatic Modal hammer (SAM) is presented. The SAM allows exciting the structure with precisely adjustable and reproducible force amplitudes. The test device is designed in a way that only the inertia mass of the hammer tip impacts the structure with a finely amplitude-adjustable Dirac impulse. The non-linear behavior of composite materials and jointed structures can be investigated with the SAM in terms of impact force-depending natural frequencies and damping ratios. This leads to an increase in the accuracy of the experimental data and therefore, a more straightforward modal model correlation in regards to the real structure.

Conventional excitation techniques such as modal impact hammer and shakers are commonly used in experimental modal testing. However, these excitation approaches require the excitation device to be in direct contact with test articles. It can result in distorted measurements, particularly for small structures, such as a MEMS cantilever and thumb nail size turbine blade. In addition, it is physically difficult or even impossible to apply these contact type excitations to some structures such as low stiffness structures or biological tissues. Moreover, these conventional excitations have limited bandwidth, usually less than 10 kHz, and thus are not applicable to extract information in higher frequency modes. Dynamic focused ultrasound radiation force has been recently used to excite structures with sizes ranging from micro to macro-scale and having a frequency bandwidth from tens of Hertz to up to 100 kHz. Therefore, it can potentially be used as an alternative, non-contact excitation method to these conventional contact excitation techniques for experimental modal analysis. Yet, this force remains to be quantified and calibrated in order to obtain the input-output relationship necessary to compute accurate frequency response functions of test structures. In this work a spherically focused ultrasound transducer (UT) is driven by double sideband suppressed carrier amplitude modulation (DSB-SC AM) signals with a scanning difference frequency and randomly varying carrier frequency. The radiated pressure field generated by the UT is experimentally measured employing a pressure microphone, which acts as a target object for the ultrasonic waves. Then, the recorded values are used to analytically evaluate the dynamic focused ultrasound radiation force. Results show that the measured radiation pressure and estimated force are characterized by a focal spot small enough to be compared to an impact hammer tip appropriate for future modal testing.

Numerous damage detection methods that use data obtained from contact sensors, physically attached to structures, have been developed. However, damage sensitive features used for these methods such as modal properties of steel and reinforced concrete structures are sensitive to environmental conditions such as temperature and humidity. These uncertainties are difficult to address with a regression model or any other temperature compensation method, and these are primary causes of false alarms. In order to address some of these challenges of the traditional sensing system, a vision-based remote sensing system can be one of the alternatives as it gives us explicit intuitions of structural conditions. In addition, bolted connections are common engineering practices, and very few vision-based techniques are developed for loosened bolt detection. Thus, this paper proposes an automated vision-based method for detecting loosened structural bolts using the Viola-Jones algorithm. Images of bolt connections are taken with a DSLR camera. The Viola-Jones algorithm is trained on two datasets of images with and without bolts. The trained algorithm localizes all bolts on images. The localized bolts are cropped and binarized to calculate bolt head dimensions and exposed shank length. The extracted features are fed into a support vector machine to generate a decision boundary separating loosened and tight bolts. We test our method on images taken by DSLR and smartphone cameras.

A number of methods for non-linear system identification in the time and frequency domain have been developed in the past. These methods have been applied to many systems, ranging from micro-scale devices to macro-scale systems, sometimes with uncertain results. The aim of this paper is to assess the efficiency of a subset of methods and understand their range of usability. The methods considered in this study are the restoring force surface (RFS), Hilbert transform (HT), zero-crossing (ZC), direct quadrature (DQ), short-time Fourier transform (SFT) and zero-crossing for asymmetric systems (ZCA). The accuracy and robustness of the methods against measured noise were evaluated using simulated data from a SDOF system. The application of the selected methods to a simulated non-linear MDOF system was also investigated. It could be shown that under certain conditions these methods may still provide reliable results for MDOF systems although generally their use should be avoided. The methods were also applied to data from a micro-electro-mechanical-systems (MEMS). Unfortunately, due to lack of symmetry in the experimental data, only the RFS and ZCA could have been used, leading to the finding that the MEMS device may be modelled using quadratic stiffness.

This study is a comprehensive effort in analyzing the vibro-acoustic characteristics of a top loaded washing machine, and focuses on the identification of the main noise source. For this purpose, the vibro-acoustic behaviors of components in washing machine are investigated systematically. Modal analysis of the main components in the system (cabinet, tub, and motor) are performed for identification of vibration modes that are related to noise radiation. The cogging torque that is associated with the brushless DC motor is identified with the order analysis. The critical frequency bands are determined with respect to components, and preliminary investigation for the noise source identification is concluded. For a quantitative ranking of contributions from several components to output noise during operation of the washing machine, Operational Transfer Path Analysis method is used. The vibration and acoustic response are measured in a relation to stepwise control of the operation speed of the BLDC motor. Transmissibility functions with respect to transfer paths are calculated, and cross-talk cancellation is applied using principal component analysis. The evaluated synthesized response matched well with the measured noise output through all measurement steps.

Component-based Transfer Path Analysis allows us to analyse and predict vibration propagation between an active source and passive receiver structures. The forces that characterise the active source are determined using sensors placed on the connected passive substructure. These source characterisation forces, often called blocked or equivalent forces, are an inherent and unique property of the source, allowing to predict vibration levels in assemblies with different connected passive structures. In order to obtain a unique and accurate characterisation, accurate measurements are of key importance. The success of the characterisation is not only dependent on the hammer skill of the experimentalist, but also relates to sensor placement, overdetermination and matrix conditioning. In this paper the effects of each of these influences are studied using theoretical approaches, numerical studies and measurements on a benchmark structure designed for in-situ source characterisation. An assembly of two substructures is tested, representing an active substructure with a source and a passive substructure. In order to determine a criterion for the placement of indicator sensors, the effect of the various influences on the in-situ characterisation is compared. Using the results, a structured approach for the use of indicator sensors for in-situ blocked force TPA is proposed.

This paper studies how a particular variation in a wireless mobile sensor configuration can influence modal identification accuracy. A mobile sensor network simultaneously measures vibration data in time while scanning over a large set of points in space. Previous research has demonstrated that such data can be specified under the dynamic sensor network (DSN) data class and examined using the truncated physical state-space model (TPM). The extended structural dentification using expectation maximization (STRIDEX) algorithm is applied to determine maximum likelihood estimates of the TPM model parameters, which are related to structural modal properties. With this approach, numerous mode shape ordinates can be extracted from each sensor, exemplifying the advantageous spatial information provided by mobile sensors as well as DSN data in general.

In the experiments, a step-motor and pulley system drove mobile sensing cars, each equipped with a wireless accelerometer, across the longitudinal span of a beam testbed. Feedback between the motor and a computer provided a precise spatial grid and accurate time-stamped positions for the sensors. Given four mobile sensors (two groups of two sensor cars), sensor configurations were designed with different distances between the groups. Two sensor configurations were applied through the experimental platform and the identification results are compared to those obtained using fixed sensors. The work builds on a previous study on this testbed which considered two mobile sensor arrangements: one in which the sensor groups moved in the same direction and the other in which they moved in opposition. This study considers a constant distance between the sensor groups, which move in the same direction, at the same speed, and examine the potential influence on modal identification, further contributing to experimental results with mobile sensors. At a greater scale, measurements from this data class represent idealized bridge response measurements collected by public smartphones. Crowdsourced data streams could contribute greatly to the health monitoring of critical bridges across the country.

This work analyses the feasibility of a new kind of instrument for geological exploration based on the reciprocating drilling technology. The instrument design is particularly challenging, given the harsh environmental conditions typical of this field. After the analysis of the state of the art in the field of reciprocating drilling we focused on the measurement system for the computation of the drill trajectory. The Monte Carlo method is first used to compare the robustness of three different algorithms for the identification of the trajectory. On the basis of this simulation the measurement system has been designed and its principal components, underwent a metrological calibration procedure in order to evaluate the basic performances at high temperatures.

In order to predict flight environments for ground support equipment, a small-scale, direct-field acoustic test (DFAT) laboratory was recently constructed at Sandia National Laboratories. This unique laboratory setup—consisting of 24 commercial off-the-shelf monitor speakers driven by a multi-input multi-output control system—was capable of exciting the component with an acoustic environment of 103 dB overall sound pressure level (OASPL). The resulting measured data was used to predict the flight environment response of the component and to derive vibration test specifications for future mechanical shaker testing. This paper describes the small-scale DFAT laboratory setup, the applied acoustic test method, and the process used to predict the flight environments for the given ground support equipment.

Oak Ridge National Laboratory (ORNL) has performed a 2-year evaluation of the performance of an in-house developed consumer electronics-based data acquisition system (DAS). The main advantage of this approach compared to conventional instrumentation grade systems is cost; instrument grade data acquisition systems average costs range from $800 to $2000 per channel compared to a range of $200 – 400 per channel for a consumer electronics-based system.

The DAS is operated as a full-time in-situ vibration monitor. The resulting data is streamed over the ORNL network, at an aggregate rate of approximately two megabytes/s, to a Linux server. The server includes the capability to implement event-triggered data stores, as well as real-time files for the implementation of continuous display monitoring of the spectra. Detailed spectral analysis is performed post event.

The DAS is installed on a large industrial chiller and cooling water pump associated with ORNL’s Titan supercomputer. These mechanical systems include rotating components that operate at fundamental frequencies within the range of 30 Hz to over 3 KHz.

Evaluation of the DAS data over a 2-year operating period leads to the conclusion that for many industrial processes this system could form the basis for a cost effective means of obtaining operating health data in real time from rotating machinery. The deployment has also shown that the DAS technology is reliable. Furthermore, because the cost of the DAS is low, the other significant advantage of this approach is that the DAS can be deployed in a dedicated manner and operated on a full-time basis.