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Dynamic weighing, i.e., weighing of objects in motion, without stopping them on the weighing platform, allows one to increase the rate of operation of automatic weighing systems, used in industrial production processes, without compromising their accuracy. Since the classical identification-based approach to dynamic weighing, based on the second-order mass–spring–damper model of the weighing system, does not yield satisfactory results when applied to conveyor belt type checkweighers, several extensions of this technique are examined. Experiments confirm that when appropriately modified the identification-based approach becomes a reliable tool for dynamic mass measurement in checkweighers. [ABSTRACT FROM AUTHOR]

Abstract: Conveyor belt type checkweighers are complex mechanical systems consisting of a weighing sensor (strain gauge load cell, electrodynamically compensated load cell), packages (of different shapes, made of different materials) and a transport system (motors, gears, rollers). Disturbances generated by the vibrating parts of such a system are reflected in the signal power spectra in a form of strong spectral peaks, located usually in the lower frequency range. Such low frequency components overlap in the frequency domain with the useful signal and it is very difficult to eliminate them. The conventional way of suppressing disturbances is via low-pass filtering of the signal obtained from the load cell. However, if the speed of the conveyor belt is high, the response of the applied filter may not settle fast enough to enable accurate weighing of objects in motion, i.e., without stopping them on the weighing conveyor. Since attempts to overcome this problem using classical linear time-invariant low-pass filtering fail for high belt speeds, the paper presents and verifies experimentally a new approach, based on time-variant low-pass filtering. It is shown that, when properly tuned, the proposed time-variant filter fulfills the measurement accuracy requirements for a wide range of operating conditions. [Copyright &y& Elsevier]

SUMMARY SONIC (self-optimizing narrowband interference canceler) is an acronym of a recently proposed active noise control algorithm with interesting adaptivity and robustness properties. SONIC is a purely feedback controller, capable of rejecting nonstationary sinusoidal disturbances (with time-varying amplitude and/or frequency) in the presence of plant (secondary path) uncertainty. We show that although SONIC can work reliably without access to a reference signal, even when the frequency of the disturbance is unknown and possibly time varying, the algorithm can take advantage of such additional source information. Unlike classical hybrid solutions, the reference signal is used only to extract information about the instantaneous frequency of the disturbance. The advance-time advantage, available because the acoustic delay in the system is larger than the electrical delay, allows one to incorporate in the control loop a smoothed, and hence more accurate, frequency estimate. This increases the attenuation efficiency of SONIC and widens its operating range-the modified algorithm can be safely used in the presence of rapid frequency changes. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The problem of cancellation of strong, potentially nonstationary, echoes in noise radars and passive radars utilizing digital transmissions is considered. The proposed solution is a multi-stage procedure. Initial clutter estimates, obtained using the least mean squares (LMS) algorithm, are refined using specially designed filters, “matched” to spectral densities of targets and clutter. When the postprocessing filters are noncausal, the performance of the proposed canceler is improved compared to the solution based on causal filters. [ABSTRACT FROM AUTHOR]

The problem of extraction/elimination of a nonstationary complex sinusoidal signal buried in noise is considered. This problem is usually solved using adaptive notch filtering (ANF) algorithms. It is shown that accuracy of signal estimation can be increased if the results obtained from ANF are further processed using a cascade of appropriately designed filters. The resulting adaptive notch smoothing (ANS) algorithms can be employed in many offline or nearly real-time online applications. Whenever signal frequency varies in a sufficiently smooth manner, the proposed fixed-interval and fixed-lag ANS algorithms, based on a new, quasi-linear model of frequency changes, outperform the existing solutions. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to rejection of complex-valued sinusoidal disturbances acting at the output of a discrete-time stable linear plant with unknown and possibly time-varying dynamics. It is assumed that both the instantaneous frequency of the sinusoidal disturbance and its amplitude may be slowly varying with time and that the output signal is contaminated with wideband measurement noise. It is not assumed that a reference signal, correlated with the disturbance, is available. The proposed disturbance rejection algorithm is an extension of the algorithm derived for the constant-known-frequency case, described in Part I of this paper. [ABSTRACT FROM AUTHOR]