Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Eco-structure data forms : classification of data analysis using perceived design affordances for musical outcomes

This paper explores a method of comparative analysis and classification of data through perceived design affordances. Included is discussion about the musical potential of data forms that are derived through eco-structural analysis of musical features inherent in audio recordings of natural sounds. A system of classification of these forms is proposed based on their structural contours. The classifications include four primitive types; steady, iterative, unstable and impulse. The classification extends previous taxonomies used to describe the gestural morphology of sound. The methods presented are used to provide compositional support for eco-structuralism.

The structure of selected magnesium carbonate minerals : a near infrared and mid-infrared spectroscopic study

The approach to remove green house gases by pumping liquid CO2 several kilometres below the ground implies that many carbonate containing minerals will be formed. Among these minerals the formation of dypingite and artinite are possible; thus necessitating a study of such minerals. Two carbonate bearing minerals dypingite and artinite with a hydrotalcite related formulae have been characterised by a combination of infrared and near-infrared spectroscopy. The infrared spectra of both minerals are characterised by OH and water stretching vibrations. Both the first and second fundamental overtones of these bands are observed in the NIR spectra in the 7030 to 7235 cm-1 and 10490 to 10570 cm-1. Intense (CO3)2- symmetric and antisymmetric stretching vibrations confirm the distortion of the carbonate anion. The position of the water bending vibration indicates water is strongly hydrogen bonded to the carbonate anion in the mineral structure. Split NIR bands at around 8675 and 11100 cm-1 indicates that some replacement of magnesium ions by ferrous ions in the mineral structure has occurred.

Smectite flocculation structure modified by AI13 macromolecules; as revealed by the Transmission X-ray Microscopy (TXM)

The aggregate structure which occurs in aqueous smectitic suspensions is responsible for poor water clarification, difficulties in sludge dewatering and the unusual rheological behaviour of smectite rich soils. These macroscopic properties are dictated by the 3-D structural arrangement of smectite finest fraction within flocculated aggregates. Here, we report results from a relatively new technique, Transmission X-ray Microscopy (TXM), which makes it possible to investigate the internal structure and 3-D tomographic reconstruction of the smectite clay aggregates modified by Al13 keggin macro-molecule [Al13(O)4(OH)24(H2O)12 ]7+. Three different treatment methods were shown resulted in three different micro-structural environments of the resulting flocculation.

Multi-spectral fusion for surveillance systems

Surveillance systems such as object tracking and abandoned object detection systems typically rely on a single modality of colour video for their input. These systems work well in controlled conditions but often fail when low lighting, shadowing, smoke, dust or unstable backgrounds are present, or when the objects of interest are a similar colour to the background. Thermal images are not affected by lighting changes or shadowing, and are not overtly affected by smoke, dust or unstable backgrounds. However, thermal images lack colour information which makes distinguishing between different people or objects of interest within the same scene difficult. ----- By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using either modality individually. We evaluate four approaches for fusing visual and thermal images for use in a person tracking system (two early fusion methods, one mid fusion and one late fusion method), in order to determine the most appropriate method for fusing multiple modalities. We also evaluate two of these approaches for use in abandoned object detection, and propose an abandoned object detection routine that utilises multiple modalities. To aid in the tracking and fusion of the modalities we propose a modified condensation filter that can dynamically change the particle count and features used according to the needs of the system. ----- We compare tracking and abandoned object detection performance for the proposed fusion schemes and the visual and thermal domains on their own. Testing is conducted using the OTCBVS database to evaluate object tracking, and data captured in-house to evaluate the abandoned object detection. Our results show that significant improvement can be achieved, and that a middle fusion scheme is most effective.

The structure of the copper(II) complex with 4,5-dichlorophthalic acid: The 1:1 complex 'adduct' salt trans-tetraaqua(2-carboxy-4,5-dichlorobenzoato)(4,5-dichlorobenzene-1,2-dicarboxylic acid)copper(II) 2-carboxy-4,5-dichlorobenzoate

The unusual (1:1) complex ‘adduct’ salt of copper(II) with 4,5-dichlorophthalic acid (H2DCPA), having formula [Cu(H2O)4(C8H3Cl2O4) (C8H4Cl2O4)] . (C8H3Cl2O4) has been synthesized and characterized using single-crystal X-ray diffraction. Crystals are monoclinic, space group P21/c, with Z = 4 in a cell with dimensions a = 20.1376(7), b =12.8408(4) c = 12.1910(4) Å, β = 105.509(4)o. The complex is based on discrete tetragonally distorted octahedral [CuO6] coordination centres with the four water ligands occupying the square planar sites [Cu-O, 1.962(4)-1.987(4) Å] and the monodentate carboxyl-O donors of two DCPA ligand species in the axial sites. The first of these bonds [Cu-O, 2.341(4) Å] is with an oxygen of a HDCPA monoanion, the second with an oxygen of a H2DCPA acid species [Cu-O, 2.418(4) Å]. The un-coordinated ‘adduct’ molecule is a HDCPA counter anion which is strongly hydrogen-bonded to the coordinated H2DCPA ligand [O… O, 2.503(6) Å] while a number of peripheral intra- and intermolecular hydrogen-bonding interactions give a two-dimensional network structure.

Hydrogen bonding in the water stabilized structure of the modified unsymmetrically substituted viologen chromophore, N-ethyl-N'-(2-phosphonomethyl)-4,4'-bipyridylium dichloride

The crystal structure of the modified unsymmetrically N, N'-substituted viologen chromophore, N-ethyl- N'-(2-phosphonoethyl)-4, 4'-bipyridinium dichloride 0.75 hydrate. (1) has been determined. Crystals are triclinic, space group P-1 with Z = 2 in a cell with a = 7.2550(1), b = 13.2038(5), c = 18.5752(7) Å, α = 86.495(3), β = 83.527(2), γ = 88.921(2)o. The two independent but pseudo-symmetrically related cations in the asymmetric unit form one-dimensional hydrogen-bonded chains through short homomeric phosphonic acid O-H...O links [2.455(4), 2.464(4)A] while two of the chloride anions are similarly strongly linked to phosphonic acid groups [O-H…Cl, 2.889(4), 2.896(4)Å]. The other two chloride anions together with the two water molecules of solvation (one with partial occupancy) form unusual cyclic hydrogen-bonded bis(Cl...water) dianion units which lie between the layers of bipyridylium rings of the cation chain structures with which they are weakly associated.

Influence of smectite suspension structure on sheet orientation in dry sediments : XRD and AFM applications

The structure-building phenomena within clay aggregates are governed by forces acting between clay particles. Measurements of such forces are important to understand in order to manipulate the aggregate structure for applications such as dewatering of mineral processing tailings. A parallel particle orientation is required when conducting XRD investigation on the oriented samples and conduct force measurements acting between basal planes of clay mineral platelets using at. force microscopy (AFM). To investigate how smectite clay platelets were oriented on silicon wafer substrate when dried from suspension range of methods like SEM, XRD and AFM were employed. From these investigations, we conclude that high clay concns. and larger particle diams. (up to 5 μm) in suspension result in random orientation of platelets in the substrate. The best possible laminar orientation in the clay dry film, represented in the XRD 0 0 1/0 2 0 intensity ratio of 47 was obtained by drying thin layers from 0.02 wt.% clay suspensions of the natural pH. Conducted AFM investigations show that smectite studied in water based electrolytes show very long-range repulsive forces lower in strength than electrostatic forces from double-layer repulsion. It was suggested that these forces may have structural nature. Smectite surface layers rehydrate in water environment forms surface gel with spongy and cellular texture which cushion approaching AFM probe. This structural effect can be measured in distances larger than 1000 nm from substrate surface and when probe penetrate this gel layer, structural linkages are forming between substrate and clay covered probe. These linkages prevent subsequently smooth detachments of AFM probe on way back when retrieval. This effect of tearing new formed structure apart involves larger adhesion-like forces measured in retrieval. It is also suggested that these effect may be enhanced by the nano-clay particles interaction.