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This paper aims to overcome the defect that the traditional clustering method is excessively dependent on initial clustering radius and also provide new technical measures for detecting the component content of lubricating oil based on the fuzzy neural system model.

According to the layers model of the fuzzy neural system model for the given sample data pair, the new clustering method can be implemented, and through the fuzzy system model, the detection method for the selected oil samples is given. By applying this method, the composition contents of 30 kinds of oil samples in lubricating oil are checked, and the actual composition contents of oil samples are compared.

Through the detection of 21 mineral elements in 30 oil samples, it can be known that the four mineral elements such as Zn, P, Ca and Mg have largest contribution rate to the lubricating oil, and they can be regarded as the main factors for classification of lubricating oil. The results show that the fuzzy system to be established based on sample data clustering has better performance in detection lubricant component content.

In spite of lots of methods for detecting the component of lubricating oil at the present, there is still no detection of the component of lubricating oil through clustering method based on sample data pair. The new nearest clustering method is proposed in this paper, and it can be more effectively used to detect the content of lubricating oil.

The purpose of this paper is to present a data fusion methodology for online oil condition and wear particles monitoring for assessment of a mechanical spur gear transmission system.

In this work, a background understanding of the tribological phenomena behind oil degradation and wear on the contact surface of mechanical elements is presented. Experimental results were obtained from oil continuously sampled from an operating a single-stage gearbox. Sampling was done by a multi-sensor automated prototype and online analysis performed by algorithms implemented in a C-code programmed graphical user interface.

Two sets of experiments were performed to observe different fault events frequently occurred in an industrial environment. Fault detection was achieved in appropriate time under constant operating conditions. Under variable operating conditions, same results were obtained by adjusting analysis parameters to critical operation conditions.

The value of this research work is the integration of the hardware and software necessary for online monitoring of oil condition and mechanical wear. The setup integrates online sampling with data acquisition, wireless communication, change detection and fault recognition computation. The approach has application in non-destructive online condition-based maintenance.

This paper aims to analyze the application of remotely piloted aircraft (RPA) for remote oil spill sensing.

This paper is an analysis of RPA strong points.

To increase the accuracy and eliminate potentially false contamination detection, which can be caused by external factors, an oil thickness measurement algorithm is used with the help of the multispectral imaging that provides high accuracy and is versatile for any areas of water and various meteorological and atmospheric conditions.

SWOT analysis of implementation of RPA for remote sensing of oil spills.

The use of RPA will improve the remote sensing of oil spills.

The concept of oil spills monitoring needs to be developed for quality data collection, oil pollution control and emergency response.

The research covers the development of a method and design of a device intended for taking samples and determining the presence of oil contamination in an aquatorium area; the procedure includes taking a sample from the water surface, preparing it for transportation and delivering the sample to a designated location by using the RPA. The objective is to carry out the analysis of remote oil spill sensing using RPA. The RPA provides a reliable sensing of oil pollution with significant advantages over other existing methods. The objective is to analyze the use of RPA employing all of their strong points. In this paper, technical aspects of sensors are analyzed, as well as their advantages and limitations.

Reports how the theorem of the texture “tuned” mask was modified to solve some problems encountered in the automatic faults (including filling bars, oil stains, weft‐lacking and holes) detection and recognition of the plain woven fabrics. These problems are the faults of variable shapes and sizes, those of variable structure and the grey‐level differences in the faults of oil stains. The index of the “tuned” mask in the texture “tuned” mask theorem was modified to converge the variability of the faults, and to elongate the distances between each fault’s average texture energy so that the texture energy in normal texture and in faults can be confined to different fixed ranges. The results show that the optimum texture “tuned” mask found from the modified theorem of the texture “tuned” mask can be used satisfactorily to identify different faults due to structure, shapes and size variation. However, in the case of undertoned oil stains and lower density filling bars, this method may sometimes cause misidentification.

THE ability to detect an impending failure in an aircraft engine mechanical power system, at an early stage, where expensive and possibly catastrophic system failures can be prevented, will provide enhanced aircraft safety by minimising the possibility of a serious engine failure, and the need for the pilot to shut down an engine during flight with all the attendant emergency ramifications that can arise. This will also improve the utilisation of the aircraft, by the scope to plan unscheduled engine removals to suit the aircraft downtime, and it will reduce the turnround time and costs to effect the necessary repairs; particularly if the skill of detection can also pinpoint the area of distress with accuracy.

Lubricating oil leakage is a common issue in thermal power plant operation sites, requiring prompt equipment maintenance. The real-time detection of leakage occurrences could avoid disruptive consequences caused by the lack of timely maintenance. Currently, inspection operations are mostly carried out manually, resulting in time-consuming processes prone to health and safety hazards. To overcome such issues, this paper proposes a machine vision-based inspection system aimed at automating the oil leakage detection for improving the maintenance procedures.

The approach aims at developing a novel modular-structured automatic inspection system. The image acquisition module collects digital images along a predefined inspection path using a dual-light (i.e. ultraviolet and blue light) illumination system, deploying the fluorescence of the lubricating oil while suppressing unwanted background noise. The image processing module is designed to detect the oil leakage within the digital images minimizing detection errors. A case study is reported to validate the industrial suitability of the proposed inspection system.

On-site experimental results demonstrate the capabilities to complete the automatic inspection procedures of the tested industrial equipment by achieving an oil leakage detection accuracy up to 99.13%.

The proposed inspection system can be adopted in industrial context to detect lubricant leakage ensuring the equipment and the operators safety.

The proposed inspection system adopts a computer vision approach, which deploys the combination of two separate sources of light, to boost the detection capabilities, enabling the application for a variety of particularly hard-to-inspect industrial contexts.

The Board of Agriculture, by virtue of the powers conferred upon them by the Sale of Food and Drugs Act, 1899, have made regulations whereby it may be presumed, until the contrary is proved, that milk containing less than 8·5 per cent. of solids‐not‐fat, or less than 3 per cent of fat, is adulterated within the meaning of the Act. The suggested limit for fat in milk recommended by the special committee appointed by the Board of Agriculture was 3·per cent., and it will therefore be observed that the new regulations have fixed a standard for milk‐fat which is even lower than the low limit recommended by the committee. There are even rumours that a further lowering of this standard is to bo urged upon the authorities. Although from the point of view of Public Analysts and the officials responsible for the enforcement of the Food and Drugs Acts it is satisfactory that an official standard for the composition of milk has at last been set up, it is idle to suppose that the fixing of such a limit will materially improve the character of the milk‐supply as a whole. It should be remembered that milk which contains only 3 per cent of fat, although under the new regulations legally “genuine,” is, as a matter of fact, of the poorest quality, and is only produced by a cow when in bad condition, or by a particular breed of cow which is remarkable more for the quantity than for the quality of the fluid yielded. Producers and vendors of milk of good quality have been placed in a very unfortunate position by the new regulations, as the tendency of the trade will be to lower all milk to the official limits, with the result that those dealers who are still desirous of maintaining a high standard of quality will have to compete in the matter of price with less conscientious traders, who, taking advantage of the protection afforded by the regulations, will be enabled to sell to the public “genuine” milk, from which all “superfluous” fat has been removed. Gradation of quality in an article of food cannot, of course, be provided for by official regulation, and for the purpose of legal classification it is only possible to differentiate between legally “genuine” and adulterated articles. Therefore, in a legal sense, and also in a popular sense, a milk containing 4 per cent. of fat is no more “ genuine ” than one containing 3 per cent., although the former is, of course, a superior article. Competition in the dairy trade, which has of late years become very keen, will, as the result of the fixing of this standard, become more acute than before, and to keep their position it will be necessary for those milk‐vendors who are desirous of maintaining their reputation as vendors of milk of good quality to give to their customers some guarantee that their product is indeed superior to the legalised article. Any statements of the traders themselves upon this point will naturally be received by customers with reserve, as proceeding from an interested source, and the guarantee, to be effective, must therefore be given by an authority whose statements are above suspicion. It is hero that the system of Control will be found to be a necessity both to the milk dealer and milk consumer.

The use of energy‐dispersive X‐ray fluorescence in the oil industries increases continuously. The use of polarized X‐rays especially increased enormously the performance of this technology. The reduction of background decreases the limits of detection by up to a factor of 10 in comparison with the traditional technology. Detection limits (in 3σ) of 1ppm are achieved for sulphur and chlorine. Generally the simultaneous multi‐element analysis allows the determination of all elements between Mg and U. Screening analysis with automatic matrix detection enables the quantitative analysis of waste or used oil with unknown water content. The high performance of this technology is proved by several applications.

Hempseed oil is a valuable emerging food product with recognized health positivity due to its composition. The paper aims to propose a multi-methodological chemical profiling of nine organic hempseed oil samples (different brands and prices) from the retail market, followed by multivariate data analysis.

Fatty acids, tocopherols, squalene, total carotenoids content, phenolic compounds, total phenolic content and anti-radical activity (DPPH• and ABTS•+ assays) were determined through chromatographic and spectrophotometric techniques. Multivariate (explorative and discriminant) analyses were applied to the profiling results to classify samples according to information claimed on the label, i.e. geographical origin (EU vs. non-EU), extraction procedure (cold-pressed vs. not cold-pressed) and price (lower or higher than 10 € per 250 mL).

The chemical analysis confirmed the 3 to 1 ?-6:?-3 ratio and the excellent content in antioxidant species. However, no specific trend of results can be stressed. PCA (after variables selection) highlighted a natural grouping of samples, so three discriminant analyses were performed: kNN, Naïve Bayes and LDA. The best classification efficiency was reached for the extraction procedure verification (93–100% correct classification), followed by geographical origin (83–94%) and prices (81.6–90%).

The integrated approach of chemical profiling coupled with multivariate analyses allowed the assessment of label information of the analyzed organic hempseed oil samples, despite the wide heterogeneity of the selected samples.

In this study, an attempt has been made to collect the research that has been done on the construction and design of the H₂O₂ sensor. So far, many efforts have been made to quickly and sensitively determine H₂O₂ concentration based on different analytical principles. In this study, the importance of H₂O₂, its applications in various industries, especially the food industry, and the importance of measuring it with different techniques, especially portable sensors and on-site analysis, have been investigated and studied.

Hydrogen peroxide (H₂O₂) is a very simple molecule in nature, but due to its strong oxidizing and reducing properties, it has been widely used in the pharmaceutical, medical, environmental, mining, textile, paper, food production and chemical industries. Sensitive, rapid and continuous detection of H₂O₂ is of great importance in many systems for product quality control, health care, medical diagnostics, food safety and environmental protection.

Various methods have been developed and applied for the analysis of H₂O₂, such as fluorescence, colorimetry and electrochemistry, among them, the electrochemical technique due to its advantages in simple instrumentation, easy miniaturization, sensitivity and selectivity.

Monitoring the H₂O₂ concentration level is of practical importance for academic and industrial purposes. Edible oils are prone to oxidation during processing and storage, which may adversely affect oil quality and human health. Determination of peroxide value (PV) of edible oils is essential because PV is one of the most common quality parameters for monitoring lipid oxidation and oil quality control. The development of cheap, simple, fast, sensitive and selective H₂O₂ sensors is essential.