Search results

This paper describes a state‐of‐the‐art, commercially available optical correlator that has been used to perform industrial applications. The optical correlator can be used in many different applications including quality control, defect detection, target tracking and pattern recognition. The correlator has been designed to be rugged and is compatible with VGA and NTSC standards. The plug‐and‐play configuration makes it easy for engineers to test new industrial applications.

To introduce a new, low‐cost and easy‐to‐use leak detection system to help water utilities improve their effectiveness in locating leaks. The paper also presents an overview of leakage management strategies including acoustic and other leak detection techniques.

The design approach was based on the use personal computers as a platform and enhanced signal processing algorithms. This eliminated the need for a major component of the usual hardware of leak pinpointing correlators which reduced the system's cost; made it easy to use, and improved the effectiveness of locating leaks in all types of pipes.

Effectiveness of the new leak detection system for pinpointing leaks was demonstrated using real world examples. The system has promising potential for all water utilities, including small and medium‐sized ones and utilities in developing countries.

The leak detection system presented in the paper will help all water utilities, including small and medium‐sized ones and utilities in developing countries, to save water by dramatically improving their effectiveness in locating leaks in all types of pipes.

The paper presents information about a new effective system for locating leaks in water distribution pipes. Effective leak detection tools are needed by water utilities worldwide.

Sensor networks have found wide applications in the monitoring of environmental events such as temperature, earthquakes, fire and pollution. A major challenge with sensor network hardware is their limited available energy resource, which makes the low power design of these sensors important. This paper aims to present a low power sensor which can detect sound waveform signatures.

A novel mixed signal hardware is presented to correlate the received sound signal with a specific sound signal template. The architecture uses pulse width modulation and a single bit digital delay line to propagate the input signal over time and analog current multiplier units to perform template matching with low power usage.

The proposed method is evaluated for a chainsaw signature detection application in forest environments, under different supply voltage values, input signal quantization levels and also different template sample points. It is observed that an appropriate combination of these parameters can optimize the power and accuracy of the presented method.

The proposed mixed signal architecture allows voltage and power reduction compared with conventional methods. A network of these sensors can be used to detect sound signatures in energy limited environments. Such applications can be found in the detection of chainsaw and gunshot sounds in forests to prevent illegal logging and hunting activities.

The purpose of this paper is to study the effect of diode power detector modelling on six-port communication receiver performance.

Based on proposed and conventional squared diode model, six-port receiver’s demodulation and its error vector magnitude (EVM) performance due to hardware impairments are studied. Through considering both the models, the accuracy of proposed power detector model is compared to the squared model, and then both results are validated with envelope simulation (ENV) in advanced design system (ADS).

Comparing the numerical results with envelope simulation results proved that the proposed model is much more accurate than the conventional squared model for a wide range of input power levels.

Studying the receiver’s performance numerically, by considering the new proposed analytical approach for diode power detectors which is more accurate than the conventional squared model.

SECANT is an acronym that stands for the SEparation and Control of Aircraft using Non‐synchronous Techniques. It is a cooperative transponding system which operates at L‐band, and performs the collision avoidance function by transmitting probes and receiving replies with a 1‐microsecond pulse, at 1,000 pulses/sec, on 24 different frequencies. Various discriminants are used to eliminate the undesired signals or “fruit”: different frequencies are allocated as a function of altitude of the flight of the aircraft; the fields above and below the aircraft are probed separately; analogue thresholds are established, based on the range required for the collision avoidance function, which discriminate against signals coming from aircraft too far away to be involved.

There has been a sustained interest over the past couple of decades in developing sophisticated leak detection techniques (LDTs) that are economical and reliable. Majority of current commercial LDTs are acoustics based and they are not equally suitable to all pipe materials and sizes. There is also limited knowledge on the comparative merits of such acoustics-based leak detection techniques (ALDTs). The purpose of this paper is to review six commercial ALDTs based on four decisive criteria and subsequently develop guidance for the optimal selection of an ALDT.

Numerous publications and field demonstration reports are reviewed for evaluating the performance of various ALDTs in this study to inform their optimal selection using an integrated multi-criteria decision analysis (MCDA) framework. The findings are validated using interviews of water utility experts.

The study approach and the findings will have a broad impact on the water utility industry by identifying a suite of suitable ALDTs for a range of typical application scenarios. The evaluated ALDTs include listening devices, noise loggers, leak-noise correlators, free-swimming acoustic, tethered acoustic, and acoustic emissions. The evaluation criteria include cost, reliability, access requirements, and the ability to quantify leakage severity. The guidance presented in this paper will support efficient decision making in water utility management to minimize pipeline leakage.

This study attempts to address the problem of severe dearth of performance data for pipeline inspection techniques. Performance data reported in the published literature on various ALDTs are appropriately aggregated and compared using a MCDA, while the uncertainty in performance data is addressed using the Monte Carlo simulation approach.

The purpose of this paper is to improve the tracking performance of the carrier phase lock loop (PLL) in the strapdown inertial navigation system/global positioning system (SINS/GPS) integrated system with an innovative scheme of ultra‐tight integration.

First, providing the Doppler frequency for PLL using SINS velocity could enlarge the loop equivalent bandwidth and reduce the dynamic effect on the carrier loop. Meanwhile, lowering the filter bandwidth could increase the immunity to noise. Second, the relationships between the PLL and SINS errors have been analyzed, and then the PLL error model is established to eliminate the correlation between the pseudo‐range‐rate error and SINS velocity error. Third, the carrier frequency is regulated to improve the tracking accuracy, according to the error estimations of Kalman filter.

The innovative ultra‐tightly integrated system could not only enhance the anti‐jamming capability and the dynamic tracking performance of the tracking loops, but also improve the pseudo‐range‐rate measurements accuracy for the integrated filter.

This paper provides further study on the method of enhancing the carrier‐tracking performance and improving the integration mode in the ultra‐tightly integrated system based on the software‐defined GPS receiver.

Most residential building owners often report problems associated with the plumbing systems. If identified at the early stages, plumbing-related defects can be easily repaired. However, if unnoticed for a long period of time, they could lead to major damages and incur a significant cost to repair. Despite the problems, studies investigating plumbing anomalies and their root causes in residential buildings are limited. This study aims to explore plumbing defects and their potential causes, diagnosis methods and repair techniques in residential buildings.

This research used data collected through an extensive survey of both academic and grey literature. Through the content analysis, plumbing defects and the associated causes have been identified and presented in tabular format.

The study investigated the anomalies and causes in the residential plumbing system under five key sub-systems: water supply system; sanitary plumbing system; roof drainage system; heating, ventilation, air conditioning and gas system; and swimming pool. Accordingly, some of the identified plumbing defects include leakages, corrosion, water penetration, slow drainage and cracks. Damaged pipes, faulty equipment and installations are some of the common causes of the anomalies. Visual inspection, hydrostatic pressure test, thermography, high-tech pipe cameras, infrared cameras, leak noise correlators and leak loggers are techniques used for diagnosing anomalies. Reactive, preventive, predictive and reliability-centred maintenance strategies are identified to control or prevent anomalies.

The findings of this research can be used as a useful tool or guideline for contractors, plumbers, facilities managers and building surveyors to identify and rectify plumbing system-related defects in residential buildings.

In a global positioning system (GPS) receiver, one of the most time-consuming tasks is to identify and track the visible satellites. The paper aims to propose and examine in detail new and shorter identification patterns or lite pseudo-codes – pseudo-random numbers (PRNs) – that allow GPS receivers to reduce dramatically the computational effort to identify and track GPS satellites. Obtaining lite pseudo-codes is a multi-objective optimization problem that the paper resolves using genetic algorithms (GAs).

The lite PRNs are obtained by using NSGA-II and omni-optimizer multi-objective optimization techniques.

The new PRNs obtained with the proposed single/multi-objective solutions are always better than previously presented when the highest detection peak (DP) is required for the GPS receiver.

Results demonstrate that the problem of “obtaining lite pseudo-codes” is a multi-objective optimization problem. In other words, the solutions obtained with the single-objective approach could belong to a local minimum. The multi-objective approach provides a better solution than the single-objective approach in a 37 percent of the satellites while in other cases the multi-objective approach reaches the same DPs with a similar noise.

Quality control charts are statistical process control tools aimed at monitoring a (manufacturing) process to detect any deviations from normal operation and to aid in process diagnosis and correction. The information presented on the chart is a key to the successful implementation of a quality process correction system. Pattern recognition methodology has been pursued to identify unnatural behaviour on quality control charts. This approach provides the ability to utilize patterning information of the chart and to track back the root causes of process deviation, thus facilitating process diagnosis and maintenance. Presents analysis and development of a statistical pattern recognition system for the explicit identification of unnatural patterns on control charts. Develops a set of statistical pattern recognizers based on the likelihood ratio approach and on correlation analysis. Designs and implements a training algorithm to maximize the probability of identifying unnatural patterns, and presents a classification procedure for real‐time operation. Demonstrates the system performance using a set of newly defined measures, and obtained results based on extensive experiments illustrate the power and usefulness of the statistical approach for automating unnatural pattern detection on control charts.