Polychaete-assisted sand filters – prawn farm wastewater remediation trial

Medium bedding sand which is commonly available in coastal sedimentary deposits, and a marine polychaete-worm species from Moreton Bay recently classified as Perinereis helleri (Nereididae), were deployed in a simple low-maintenance sand filter design that potentially has application at large scale. Previous work had shown that this physical and biological combination can provide a new option for saline wastewater treatment, since the worms help to prevent sand filter blocking with organic debris and offer a profitable by-product. To test the application of this new concept in a commercial environment, six 1.84 m2 Polychaete-assisted sand filters were experimentally tested for their ability to treat wastewater from a semi-intensive prawn culture pond. Polychaetes produced exclusively on the waste nutrients that collected in these gravity-driven sand filters were assessed for their production levels and nutritional contents. Water parameters studied included temperature, salinity, pH, dissolved oxygen (DO), oxidation/ reduction potential (redox), suspended solids, chlorophyll a, biological oxygen demand (BOD), and common forms of nitrogen and phosphorus. Pond water which had percolated through the sand bed had significantly lower pH, DO and redox levels compared with inflow water. Suspended solids and chlorophyll a levels were consistently more than halved by the process. Reductions in BOD appeared dependant on regular subsurface flows. Only marginal reductions in total nitrogen and phosphorus were documented, but their forms were altered in a potentially useful way: dissolved forms (ammonia and orthophosphate) were generated by the process, and this remineralisation also seemed to be accentuated by intermittent flow patterns. Flow rates of approximately 1,500 L m-2 d-1 were achieved suggesting that a 1 ha polychaete bed of this nature could similarly treat the discharge from a 10 ha semi-intensive prawn farm. Sixteen weeks after stocking sand beds with one-month-old P. helleri, over 3.6 kg of polychaete biomass (wet weight) was recovered from the trial. Production on a sand bed area basis was 328 g m-2. Similar (P>0.05) overall biomass production was found for the two stocking densities tested (2000 and 6000 m-2; n = 3), but survival was lower and more worms were graded as small (<0.6 g) when produced at the higher density (28.2 ± 1.5 % and approx. 88 %, respectively) compared with the lower density (46.8 ± 4.4 % and approx. 76 %, respectively). When considered on a weight for weight basis, about half of the worm biomass produced was generally suitable for use as bait. The nutritional contents of the worms harvested were analysed for different stocking densities and graded sizes. These factors did not significantly affect their percentages of dry matter (DM) (18.23 ± 0.57 %), ash (19.77 ± 0.80 % of DM) or gross energy 19.39 ± 0.29 MJ kg-1 DM) (n = 12). Although stocking density did not affect the worms’ nitrogen and phosphorus contents, small worms had a higher mean proportion of nitrogen and phosphorus (10.57 ± 0.17 % and 0.70 ± 0.01 % of DM, respectively) than large worms (9.99 ± 0.12 % and 0.65 ± 0.01 % of DM, respectively) (n = 6). More lipid was present in large worms grown at the medium density (11.20 ± 0.19 %) compared with the high density (9.50 ± 0.31 %) and less was generally found in small worms (7.1-7.6 % of DM). Mean cholesterol and total phospholipid levels were 5.24 ± 0.15 mg g-1 and 13.66 ± 2.15 mg g-1 DM, respectively (n = 12). Of the specific phospholipids tested, phosphatidyl-serine or sphingomyelin were below detection limits (<0.05 mg g-1), whilst mean levels of phosphatidyl-ethanolamine, phosphatidyl-inositol, phosphatidyl-choline and lysophosphatidyl-choline were 6.89 ± 1.09, 0.89 ± 0.26, 4.04 ± 1.17 and 1.84 ± 0.37 mg g-1, respectively (n = 12). Culture density generally had a more pronounced effect on phospholipid contents than did size of worms. By contrast, worm size had a more pronounced effect on total fatty acid contents, with large worms containing significantly higher (P<0.001) levels on a DM basis (46.88 ± 2.46 mg g-1) than smaller worms (27.76 ± 1.28 mg g-1). A very broad range of fatty acids were detected with palmitic acid being the most heavily represented class (up to 14.23 ± 0.49 mg g-1 DM or 27.28 ± 0.22 % of total fatty acids). Other heavily represented classes included stearic acid (7.4-8.8 %), vaccenic acid (6.8-7.8 %), arachidonic acid (3.5-4.4 %), eicosapentaenoic acid (9.9-13.8 %) and docosenoic acid (5.7-7.0 %). Stocking density did not affect (P>0.05) the levels of amino acids present in polychaete DM, but there was generally less of each amino acid tested on a weight per weight basis in large worms than in small worms. This difference was significant (P<0.05) for the most heavily represented classes being glutamic acid (73-77 mg g-1), aspartic acid (50-54 mg g-1), and glycine (46-53 mg g-1). These results demonstrate how this polychaete species can be planted and sorted at harvest according to various strategies aimed at providing biomass with specific physical and nutritional qualities for different uses.

Marine Polychaete Sand Filters - prawn farm wastewater remediation trial

The purpose of the trial is to assess the growth and production level of cultured Polychaetes, and wastewater remediation properties of Polychaete beds at a commercial prawn farm.

Nutritional status of a nereidid polychaete cultured in sand filters of mariculture wastewater

This study examined the nutritional composition of the intertidal marine polychaete Perinereis helleri (Nereididae)when artificially cultured in sand filters treating mariculture wastewater. Moisture levels in harvested P. helleri ranged from 758 to 855 g kg1, and ash, from 23 to 61 g kg1 wet matter (WM). Stocking density and graded size after harvest significantly affected their composition. Higher total lipid contents were found in large (>0.6 g) P. helleri(16–19 g kg1 WM) and those grown at the lowest density(1000 m2: 18 g kg 1 WM) than in small (≤0.6 g) ones (14 g kg1 WM) and those grown at the highest densities (4000–6000 m2: 13–16 g kg1 WM). Several fatty acids within a very broad profile (some 30 identified) reflected this pattern, yet their ARA/EPA/DHA ratios were relatively unaffected. Feeding the polychaete-assisted sand filters (PASF) with fish meal to increase worm biomass productivity significantly increased their DHA content. Other components (e.g. protein, phospholipids, cholesterol, carbohydrate, amino acids, nitrogen, minerals and bromophenols) and nutritional factors (e.g. maturity, feeding seaweed and endemic shrimp viral content) were also investigated. Results suggest that PASF-produced P. helleri have a well-balanced nutritional profile for penaeid shrimp and fish broodstock.

Very-high-Q inductor simulation for active tuned filters

Abstract is not available.

A rational approach to the synthesis of one-dimensional acoustic filters

The velocity ratio algorithm developed from a heuristic study of transfer matrix multiplication has been employed to bring out the relative effects of the elements constituting a linear, one-dimensional acoustic filter, the overall dimensions of which are fixed, and synthesize a suitable straight-through configuration for a low-pass, wide-band, non-dissipative acoustic filter. The potential of the foregoing approach in applications to the rational design of practical acoustic filters such as automotive mufflers is indicated.

Jet Engine Health Signal Denoising Using Optimally Weighted Recursive Median Filters

The removal of noise and outliers from health signals is an important problem in jet engine health monitoring. Typically, health signals are time series of damage indicators, which can be sensor measurements or features derived from such measurements. Sharp or sudden changes in health signals can represent abrupt faults and long term deterioration in the system is typical of gradual faults. Simple linear filters tend to smooth out the sharp trend shifts in jet engine signals and are also not good for outlier removal. We propose new optimally designed nonlinear weighted recursive median filters for noise removal from typical health signals of jet engines. Signals for abrupt and gradual faults and with transient data are considered. Numerical results are obtained for a jet engine and show that preprocessing of health signals using the proposed filter significantly removes Gaussian noise and outliers and could therefore greatly improve the accuracy of diagnostic systems. [DOI: 10.1115/1.3200907].

Novel window functions for digital filters

Window technique is one of the simplest methods to design Finite Impulse Response (FIR) filters. It uses special functions to truncate an infinite sequence to a finite one. In this paper, we propose window techniques based on integer sequences. The striking feature of the proposed work is that it overcomes all the problems posed by floating point numbers and inaccuracy, as the sequences are made of only integers. Some of these integer window sequences, yield sharp transition, while some of them result in zero ripple in passband and stopband.

Nonlinear structural dynamical system identification using adaptive particle filters

The problem of identifying parameters of nonlinear vibrating systems using spatially incomplete, noisy, time-domain measurements is considered. The problem is formulated within the framework of dynamic state estimation formalisms that employ particle filters. The parameters of the system, which are to be identified, are treated as a set of random variables with finite number of discrete states. The study develops a procedure that combines a bank of self-learning particle filters with a global iteration strategy to estimate the probability distribution of the system parameters to be identified. Individual particle filters are based on the sequential importance sampling filter algorithm that is readily available in the existing literature. The paper develops the requisite recursive formulary for evaluating the evolution of weights associated with system parameter states. The correctness of the formulations developed is demonstrated first by applying the proposed procedure to a few linear vibrating systems for which an alternative solution using adaptive Kalman filter method is possible. Subsequently, illustrative examples on three nonlinear vibrating systems, using synthetic vibration data, are presented to reveal the correct functioning of the method. (c) 2007 Elsevier Ltd. All rights reserved.

Noise minimization in RC-active filters using generalized impedance converters

A procedure has been given for minimizing the total output noise of a Generalized Impedance Converter (GIC), subject to constraints dictated by signal handling capability of the Operational Amplifiers and ease of microcircuit fabrication. The noise reduction is achieved only by the adjustment of RC elements of the GIC, and the total output noise after optimization in the example cited is close to the theoretical lower limit. The output noise of a higher-order filter can be reduced by RC-optimizing the individual GIC's of the active realization. Experimental results on a 20–24 kHz channel bank band-pass filter demonstrate the effectiveness of the above procedure.

Particle filters for structural system identification using multiple test and sensor data: A combined computational and experimental study

The problem of structural system identification when measurements originate from multiple tests and multiple sensors is considered. An offline solution to this problem using bootstrap particle filtering is proposed. The central idea of the proposed method is the introduction of a dummy independent variable that allows for simultaneous assimilation of multiple measurements in a sequential manner. The method can treat linear/nonlinear structural models and allows for measurements on strains and displacements under static/dynamic loads. Illustrative examples consider measurement data from numerical models and also from laboratory experiments. The results from the proposed method are compared with those from a Kalman filter-based approach and the superior performance of the proposed method is demonstrated. Copyright (C) 2009 John Wiley & Sons, Ltd.

Design of some 2-D filters through the transformation technique

The transformation technique is a tool FIR designing 2-D filters, useful for the design of specially shaped filters with passband/stopband regions not centred around the origin. The authors extend this technique to design two types or filters. A notch filter has a stopband centred about a small region in the 2-D frequency plane. The authors propose an extension to the transformation technique with the windowing concept to achieve the design of notch filters. A directional filter has a passband extending fully along: a straight line pacing through the origin. The transformation technique is: further extended to yield such directional filters. Design and application examples for both these fillers are also presented.

Performance analysis of surface acoustic wave matched filters

SAW matched filter is commonly used in spread spectrum communication receivers in order to maximize the SNR prior to detection, At times the receiver would be a mobile one while the signal is processed at the IF level, In that case frequency deviations due to Doppler shift or temperature dependence of the acoustic medium used for SAW device would, severely effect it's performance, The impact of these errors on the receiver performance is analyzed on a generalised basis.

Three- and Seven-Point Optimally Weighted Recursive Median Filters for Gas Turbine Diagnostics

Measured health signals incorporate significant details about any malfunction in a gas turbine. The attenuation of noise and removal of outliers from these health signals while preserving important features is an important problem in gas turbine diagnostics. The measured health signals are a time series of sensor measurements such as the low rotor speed, high rotor speed, fuel flow, and exhaust gas temperature in a gas turbine. In this article, a comparative study is done by varying the window length of acausal and unsymmetrical weighted recursive median filters and numerical results for error minimization are obtained. It is found that optimal filters exist, which can be used for engines where data are available slowly (three-point filter) and rapidly (seven-point filter). These smoothing filters are proposed as preprocessors of measurement delta signals before subjecting them to fault detection and isolation algorithms.

Data rectification and detection of trend shifts in jet engine path measurements using median filters and fuzzy logic

Filtering methods are explored for removing noise from data while preserving sharp edges that many indicate a trend shift in gas turbine measurements. Linear filters are found to be have problems with removing noise while preserving features in the signal. The nonlinear hybrid median filter is found to accurately reproduce the root signal from noisy data. Simulated faulty data and fault-free gas path measurement data are passed through median filters and health residuals for the data set are created. The health residual is a scalar norm of the gas path measurement deltas and is used to partition the faulty engine from the healthy engine using fuzzy sets. The fuzzy detection system is developed and tested with noisy data and with filtered data. It is found from tests with simulated fault-free and faulty data that fuzzy trend shift detection based on filtered data is very accurate with no false alarms and negligible missed alarms.

Noise and outlier removal from jet engine health signals using weighted FIR median hybrid filters

The removal of noise and outliers from measurement signals is a major problem in jet engine health monitoring. Topical measurement signals found in most jet engines include low rotor speed, high rotor speed. fuel flow and exhaust gas temperature. Deviations in these measurements from a baseline 'good' engine are often called measurement deltas and the health signals used for fault detection, isolation, trending and data mining. Linear filters such as the FIR moving average filter and IIR exponential average filter are used in the industry to remove noise and outliers from the jet engine measurement deltas. However, the use of linear filters can lead to loss of critical features in the signal that can contain information about maintenance and repair events that could be used by fault isolation algorithms to determine engine condition or by data mining algorithms to learn valuable patterns in the data, Non-linear filters such as the median and weighted median hybrid filters offer the opportunity to remove noise and gross outliers from signals while preserving features. In this study. a comparison of traditional linear filters popular in the jet engine industry is made with the median filter and the subfilter weighted FIR median hybrid (SWFMH) filter. Results using simulated data with implanted faults shows that the SWFMH filter results in a noise reduction of over 60 per cent compared to only 20 per cent for FIR filters and 30 per cent for IIR filters. Preprocessing jet engine health signals using the SWFMH filter would greatly improve the accuracy of diagnostic systems. (C) 2002 Published by Elsevier Science Ltd.