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As more features are added to the heavy-duty construction equipment, its complexity increases and early fault detection of certain components becomes more challenging due to too many fault codes generated when a failure occurs. Hence, there is a need to complement the present onboard diagnostics method with a more reliable diagnostics method for adequate condition monitoring of the heavy-duty construction equipment in order to improve uptime. Major components of the driveline (such as the gearbox, torque converter, bearings and axles) are components necessary to monitor. A failure among any of these major components of the driveline may result in the machine standing still until a repair is scheduled. In this paper, vibration based condition monitoring methods are presented with the purpose to provide a diagnostic framework possible to implement onboard for monitoring of critical driveline parts in order to reduce service cost and improve uptime. For the development of this diagnostic framework, sensor data from the gearbox, torque converter, bearings and axles are considered. Further, the feature extraction of the data collected has been carried out using adequate signal processing methods, which includes: Adaptive Line Enhancer and Order Power Spectrum respectively. In addition, Bayesian learning was utilized for adaptive learning of the extracted features for deviation detection. Bayesian learning is a powerful prediction method as it combines the prior information with knowledge measured to make updates. The results indicate that the vibration properties of the gearbox, torque converter, bearings and axle are relevant for early fault detection of the driveline. Furthermore, vibration provides information about the internal features of these components for detecting deviations from normal behavior. In this way, the developed methods may be implemented onboard for the continuous monitoring of these critical driveline parts of the heavy-duty construction equipment. Thus, if their health starts to degrade a service and/or repair may be scheduled well in advance of a potential failure and in that way the downtime of a machine may be reduced and costly replacements and repairs avoided.

The gravel road network is an essential function for rural residents and entrepreneurs. Traditional maintenance of gravel roads is well-functioning but provides a relatively high maintenance cost per unit length of the road. In addition, every maintenance action and extraction and transport of new gravel contribute to increased climate impact and resource depletion. Today, maintenance planning is carried out periodically based on the maintenance history, which also is reflected in the economic models and procurement methods. Current maintenance plans may be enhanced and will not be a reliable basis in the future, for instance due to climate change. Instead, real needs and conditions must be given greater consideration. Today, appropriate maintenance management systems are lacking, e.g., to be able to evaluate maintenance deficiencies, prioritize objects and choose the appropriate maintenance action. Moreover, the knowledge available at specific stakeholders is not shared with other actors. In this paper, an Information and Communication Technology (ICT) system for gravel road maintenance is proposed in the form of a cloud-based system covering the information needs of stakeholders in the gravel road maintenance ecosystem. Requirement specifications are given for the subsystems intended for the maintenance executioner and the maintenance planner. The specifications are based on workshops and interviews conducted with stakeholders, where requirements were acquired using techniques such as User stories, Use case scenarios, and mock-up prototypes. System examples corresponding to the requirements specifications are also given. [ABSTRACT FROM AUTHOR]

High quality information is essential for the efficient decision making. Road condition is, together with traffic frequency, commonly used as input for classifying road status. Road condition is also a major input for the maintenance executor (vehicle operator) when deciding on maintenance actions, such as amount of gravel to replenish. With better condition related information, the maintenance execution as well as maintenance planning could be greatly improved. The current deficiencies in gravel road condition monitoring methods and technologies are described in this paper, and an approach for objective measurement of gravel road condition is proposed, including new measurement techniques and systems as well as information processing for decision making. This is realized by utilizing research findings from the area of signal processing, maintenance engineering, and information systems engineering in the specific context of gravel road monitoring, thus utilizing available technologies and methods as well as physics. [ABSTRACT FROM AUTHOR]

This paper reports on a state-of-the-art remote laboratory project called Virtual Instrument Systems in Reality (VISIR). VISIR allows wiring and measuring of electronic circuits remotely on a virtual workbench that replicates physical circuit breadboards. The wiring mechanism is developed by means of a relay switching matrix connected to a PCI eXtensions for Instrumentation (PXI) instrumentation platform. The entire equipment is controlled by LabVIEW server software, in addition to a measurement server software that protects the equipment from hazard connections by verifying input circuit designs, sent by students, before being executed. This paper addresses other approaches such as remote labs based on Data Acquisition Cards (DAQs), NetLab, and RemotElectLab, comparing them with VISIR in order to emphasize its singularity. Topics discussed are as follows: the technical description, software, operation cycle, features, and provided services. In addition, the feedback received by students at several universities and the encountered drawbacks along with the proposed solutions are highlighted. The paper finally addresses the ongoing and future challenges within the VISIR community including its integration with Learning Management Systems (LMSs) and iLab Shared Architecture (ISA), its new hardware version release that is based on LAN eXtensions for Instrumentation (LXI), and its new open platform version that supports federated access. [ABSTRACT FROM PUBLISHER]

In this paper, an initial investigation of the nonlinear dynamic properties of clamped boring bars is carried out. Two nonlinear, single-degree-of-freedom models with different softening spring nonlinearities are introduced for modeling the nonlinear dynamic behavior of the fundamental bending mode in the cutting speed direction of a boring bar. Also, two different methods for the simulation of nonlinear models are used. The dynamic behavior in terms of frequency response function estimates for the nonlinear models and the experimental modal analysis of the clamped boring bar is compared. Similar resonance frequency shift behavior for varying excitation force levels is observed for both the nonlinear models and the actual boring bar. [ABSTRACT FROM AUTHOR]

To utilize the full noise-attenuation potential of an active noise control (ANC) system applied to duct noise, it is important to be able to minimize the turbulence-induced noise in the microphone signals. This is the second paper in a series of two, that treats the problem of turbulence-induced noise originating from the airflow inside the ducts, when applying ANC to ducts. Part I contains theoretical and experimental investigations of the influence of the turbulence-induced noise on the filtered-x LMS algorithm used in the ANC system. Part II (the present paper) is concerned with the design and investigations of microphone installations, which produce a sufficient amount of turbulence suppression while also meeting industry requirements. These requirements are, for example, that the microphone installations should be based on standard ventilation parts, and that they should be easily installed and maintained. Furthermore, results concerning the performance of an ANC system with different microphone installations are presented. Some of the results were obtained at an acoustic laboratory according to an ISO standard. The attenuation achieved with ANC was approximately 15-25 dB between 50-315 Hz, even for airflow speeds up to 20 m/s. [ABSTRACT FROM AUTHOR]

Low noise level is an essential feature when installing ventilation systems today. To achieve attenuation over a broad frequency range, the passive silencers traditionally used to attenuate ventilation noise can be combined with an active noise control (ANC) system. To insure reliable operation and desirable levels of attenuation when applying ANC to duct noise, it is highly important to be able to suppress the contamination of the microphone signals due to the turbulent pressure fluctuations, which arise as the microphones are exposed to the airflow in the duct. This paper is the first in a series of two regarding the problem of turbulence-induced noise originating from the airflow inside the ducts. Part I is concerned with theoretical and experimental investigations of the influence of the turbulence-induced noise on the adaptive algorithm in the ANC system. Part II is concerned with the design and the investigations of microphone installations for turbulence suppression and the results concerning the performance of an ANC system with the different microphone installations are presented. Some of the results were obtained at an acoustic laboratory according to an ISO-standard. The attenuation achieved with ANC was approximately 15-25 dB between 50-315 Hz, even for airflow speeds up to 20 m/s. [ABSTRACT FROM AUTHOR]

Vibration in internal turning is a problem in the manufacturing industry. A digital adaptive controller for the active control of boring bar vibration may not be a sufficient solution to the problem. The inherent delay in a digital adaptive controller delays control authority and may result in tool failure when the load applied by the work-piece on the tool changes abruptly, e.g. in the engagement phase of the cutting edge. A robust analog controller, based on a lead-lag compensator, with simple adjustable gain and phase, suitable for the industry application, has been developed. Also, the basic principle of an active boring bar with embedded actuator is addressed. The performance and robustness of the developed controller has been investigated and compared with an. adaptive digital controller based on the feedback filtered-x algorithm. In addition, this paper takes into account those variations in boring bar dynamics which are likely to occur in industry; for example, when the boring bars is clamped in a lathe. Both the analog and the digital controller manage to reduce the boring bar vibration level by up to approximately 50 dB. [ABSTRACT FROM AUTHOR]

This study compared the relative efficacy of a therapist-assisted relaxation treatment programme with a self-help approach and a self-monitoring condition in the treatment of chronic headaches in adolescents within a school setting. The subjects were 46 high school students, 16-18 years of age, who were randomly assigned to the three treatment conditions. The results indicated that the sell-help approach was as effective as the therapist-assisted relaxation condition in reducing the students' headache, and that these findings were maintained at a 5-month follow-up evaluation. The results suggest that the self-help relaxation procedure is a potential low-cost alternative treatment to a more traditional therapist-based intervention condition [ABSTRACT FROM AUTHOR]

The author comments on the appropriate spectrum estimator to use in measuring periodic signals. The topics discussed include the attributes of discrete fourier transform (DFT), the measurement of physical quantities, and the effectiveness of spectrum estimator in the measurement of periodic signals.