Predicting livestock behaviour using accelerometers: A systematic review of processing techniques for ruminant behaviour prediction from raw accelerometer data

peer-reviewedPrecision Technologies are emerging in the context of livestock farming to improve management practices and the health and welfare of livestock through monitoring individual animal behaviour. Continuously collecting information about livestock behaviour is a promising way to address several of these target areas. Wearable accelerometer sensors are currently the most promising system to capture livestock behaviour. Accelerometer data should be analysed properly to obtain reliable information on livestock behaviour. Many studies are emerging on this subject, but none to date has highlighted which techniques to recommend or avoid. In this paper, we systematically review the literature on the prediction of livestock behaviour from raw accelerometer data, with a specific focus on livestock ruminants. Our review is based on 66 surveyed articles, providing reliable evidence of a 3-step methodology common to all studies, namely (1) Data Collection, (2) Data Pre-Processing and (3) Model Development, with different techniques used at each of the 3 steps. The aim of this review is thus to (i) summarise the predictive performance of models and point out the main limitations of the 3-step methodology, (ii) make recommendations on a methodological blueprint for future studies and (iii) propose lines to explore in order to address the limitations outlined. This review shows that the 3-step methodology ensures that several major ruminant behaviours can be reliably predicted, such as grazing/eating, ruminating, moving, lying or standing. However, the areas faces two main limitations: (i) Most models are less accurate on rarely observed or transitional behaviours, behaviours may be important for assessing health, welfare and environmental issues and (ii) many models exhibit poor generalisation, that can compromise their commercial use. To overcome these limitations we recommend maximising variability in the data collected, selecting pre-processing methods that are appropriate to target behaviours being studied, and using classifiers that avoid over-fitting to improve generalisability. This review presents the current situation involving the use of sensors as valuable tools in the field of behaviour recording and contributes to the improvement of existing tools for automatically monitoring ruminant behaviour in order to address some of the issues faced by livestock farming

Efficient prediction of the forced response statistics of mistuned bladed discs

This paper presents two efficient reduced-order modelling techniques for predicting the forced response statistics of bladed disc assemblies. First, the formulation presented in (1) is extended to the forced response problem. Component modes for a blade-disc sector are used as basis vectors, leading to a reduced model of the same size as the number of sectors and allowing for pass-band calculations. For each realization of the random system parameters, a reduced system of equations is solved to compute the displacement vector for each frequency band of interest. Statistics of responses at each frequency point can be therefore estimated by performing Monte Carlo Simulations of cost comparable to single degree-of-freedom mass-spring systems. Second, a stochastic reduced basis approach is applied to the mistuning analysis problem. Here, the system response in the frequency domain is represented using a linear combination of complex stochastic basis vectors which span the preconditioned stochastic Krylov Subspace (2,3). Orthogonal stochastic projection schemes are employed for computing the undetermined coefficients in the stochastic reduced basis representation. These schemes lead to explicit expressions for the response to be obtained, thereby allowing the efficient computation of the response statistics

Statistical investigation of the free vibration mistuned blade system

A statistical investigation of the effects of uncertainty in root fixity on the free vibration of turbine blades is made. Emphasis is particularly placed on the statistical properties of the random eigenvalues and essentially on their standard deviations. These are evaluated using the direct product technique between matrices [1] and validated by Monte Carlo SImulations (MCS). The studied system is a simplified model of a shrouded blade assembly under the conditions of weak interblade coupling. It essentially consists of a cyclic chain of continuous beams with identical properties, fixed at one end via rotational springs with random stiffnesses representing the uncertain roots stiffnesses and coupled via linear springs at their tips. Finite Element Method is used as a discretization technique to obtain the equations of motion of the tuned and mistuned systems and the corresponding random eigenvalue problem.Numerical simulations show that small differences between the rotational springs stiffnesses spoilt the natural frequencies that were in pairs, increase the width of each frequency-cluster and strongly localizes the vibration around one blade. This strong localization has been shown to occur in a chain of single-degree-of-freedom, nearly identical, coupled oscillators if the coupling frequency between the subsystems is of order of, or smaller than the spread in the natural frequencies [2]However, for the multi-degree-of-freedom and randomly mistuned system considered her, multiple realizations are required to capture the behaviour of the eigenvalues appearing in frequency-clusters. It is found that for each frequency-cluster, when the standard deviations of the eigenvalues are plotted against the mode number, they form a U-shaped curve. For the particular case when the coupling frequency line crosses a curve, this essentially shows that the vibration localization is stronger at the first and last modes than at the mid frequencies, which belong to one passband in the tuned system

Model-order reduction and pass-band based calculations for disordered periodic structures

This paper is concerned with the dynamics of disordered periodic structures. The free vibration problem is considered. A method akin to the Rayleigh method is presented. This method is particularly suitable for the study of periodic structures as it exploits the nominal periodicity leading to an approximation that greatly reduces the order of the model. The method is used to calculate the natural frequencies and mode shapes for a pass-band by treating the unknown phases between the nominally identical bays as the generalized co-ordinates of the problem. An illustrative example of a cyclically coupled beam model is presented. In spite of a very large reduction in the computational effort, the results obtained are very accurate both for frequencies and mode shapes even when strong mode localization is observed. To test the performance of the proposed approximation further, a situation where two pass-bands are brought close to each other is considered (a coupled beam model having inherent bending–torsion coupling). The method presented here is general in its formulation and has the potential of being used for more complex geometries

Forced response statistics of mistuned bladed disks: a stochastic reduced basis approach

This paper presents a stochastic reduced basis approach for predicting the forced response statistics of mistuned bladed-disk assemblies. In this approach, the system response in the frequency domain is represented using a linear combination of complex stochastic basis vectors with undermined coefficients. The terms of the preconditioned stochastic Krylov subspace are used here as basis vectors. Two variants of the stochastic Bubnov–Galerkin scheme are employed for computing the undetermined terms in the reduced basis representation, which arise from how the condition for orthogonality between two random vectors is interpreted. Explicit expressions for the response quantities can then be derived in terms of the random system parameters, which allow for the possibility of efficiently computing the response statistics in the post-processing stage. Numerical studies are presented for mistuned cyclic assemblies of mono-coupled single-mode components. It is demonstrated that the accuracy of the response statistical moments computed using stochastic reduced basis methods can be orders of magnitude better than classical perturbation methods. <br/

Experiments in adaptation-guided retrieval in case-based design

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