Portable fiber optic cable processing for avionics

The system of preventive maintenance for various types of equipment is considered. To identify the need for managerial influence on the processes of maintenance and repair of the product, the coefficient of variation of the maintenance (repair) cycle is proposed. This coefficient is formed by the values of operating time or work between stops for maintenance or repair. To determine its numerical value, it is recommended to use such concepts as "maintenance (repair) cycle" and "frequency of maintenance (repair)". The values of the coefficient characterizing the stability of the process of repair and maintenance of the product are determined. These values of the coefficient are proposed to be used to justify the need to analyze the causes of failures or, in other words, the instability of the repair and maintenance process. The main managerial influences on the process of maintenance and repair are determined, which can be taken as a result of the analysis of the causes of failures. These include: the decision to search for a technical service provider, expanding the competencies of employees, updating the material base. Modern industry 4.0 tools allow you to get the required level of quality when working with a large data stream. The use of neural network technology in various technical service management tasks is due to some advantages over classical methods of statistical processing of results. The experiments of various authors are presented in which it is shown that neural network technologies are able to interpret graphic information, justify its use in technical diagnostics at the stage of analyzing diagnostic information in the form of oscillograms, which allows the use of complex diagnostic equipment in the absence of experts. A neural network simulation was carried out to recognize defects in bearing assemblies. As a result, the created neural network recognized the type of defect in accordance with the matrices of input signals and the output matrix of types of defects, which makes it possible to develop a mechanism for improving technical service using neural networks as a tool for analyzing diagnostic information in the absence of experts in this field.

The article considers a possible approach to the formation of a risk management model in locomotive companies providing maintenance and repair of rolling stock. The model suggested can be implemented in the system applied for the organization of repair and maintenance processes of a rolling stock. Of particular relevance is the problem of increasing the maintenance and repair efficiency of high-tech rolling stock providing a high complexity of its parts and units. The analysis and elaboration of solutions on increasing the efficiency of repair and maintenance using the risk management model providing for the improving the quality of these processes. The lowering number of failures in rolling stock maintenance and repair can be reached at the active use of the risk-oriented model taking into account the possibility of forecasting risk factors. In this view, the authors consider the issues related to the introduction of risk management in a service locomotive depot. The article provides the most reasonable approach on risk management introduction for most uncontrollable factors which significantly influence the process. The authors suggest the model for solving multi-criteria problems as one of the options for selecting optimal conditions to implement maintenance and repair processes. The authors consider the approach towards taking management decisions on increasing the quality of rolling stock repair and maintenance.KeywordsFailure of maintenance and repair processesRolling stockCorrective actionsProcess efficiencyRisk managementUncontrollable factorsUncertaintyExpert methodManagement process modelingDecision takingRisk function

Vision-Specific Quality-of-Life Research: A Need to Improve the Quality

The aerospace industry has made great strides in recent years deploying fiber optics and photonics technologies on commercial and military platforms which must operate in harsh environments. This trend will continue to grow as avionics fiber-optic system architectures, networking schemes, and components evolve and mature. In parallel with data and video transmission, photonics technology for analog/RF, flight control, freespace communication, and vehicle monitoring applications will have an increasing role for future aerospace platforms.

This article explores processes of relational damage, repair, and maintenance within adult daughters' accounts of their current relationships with their nonresidential fathers. Drawing on research of a sample of self-selected adult daughters who experienced parental divorce in childhood, the author explores how the processes of relational damage, repair, and maintenance contribute to and are of consequence to adult daughters' understandings of their current relationships. The author demonstrates that it is through exploring the gathered relational histories that processes of relational development are highlighted, offering a way of better understanding the consequences of divorce on the construction of parent–child relationships throughout the life course.

The war with Russia, which our country is waging for the sixth year in a row, gave impetus to the deep modernization of existing weapons and military equipment of the Armed Forces of Ukraine and the introduction of completely new troops, such as armored personnel carrier BTR-4; tactical combat wheeled vehicle «Dozor-B» and «Spartan», etc. These models were created taking into account the modern requirements for the base chassis and using modern technologies that focus on electronics and automation, respectively, significantly increased the complexity of their maintenance and repair. This, combined with the need to carry out maintenance and repairs in isolation from the permanent deployment of units in conditions as close as possible to the combat zone, where resources are severely limited, creates serious problems for technical personnel. The main question is how to give these specialists the competence to perform the basic tasks necessary to return the model of armored weapons and equipment back into operation. The experience of combat use of armored weapons and equipment in the anti-terrorist operation indicates a low level of professional training of crew members of combat vehicles, which does not meet modern requirements and does not ensure the implementation of combat missions assigned to units in full. And the complexity of designing armored weapons and equipment and computerizing them usually deprives unit commanders and crews of their combat vehicles to quickly and efficiently perform repairs and maintenance in isolation from permanent locations, as they require special diagnostic equipment and highly qualified specialists. This is confirmed by the examples of the first experience of using armored personnel carriers BTR-4 in 2014 by units of the National Guard, which had to leave cars that for various reasons could not move on their own, destroying them without even finding out the cause of the malfunction. Thus, even one of the samples of the armored personnel carriers BTR-4 fell into the hands of Russian mercenaries. An attempt has been made to analyze possible ways of using augmented reality technology (AR technology) to create a set of software and hardware that will allow tactical commanders and crews of combat vehicles, even without the participation of specialists, or remotely, to detect and troubleshoot in different operating conditions and with different levels of technical training. The advent of augmented reality technology has every chance to revolutionize the process of maintenance and repair, as well as operation. The new and unique additional opportunities offered by these technologies will significantly affect how and at what level these actions are carried out. Involved in an integrated process of maintenance, repair, operation and supply of military equipment, these technologies will increase the independence and self-sufficiency of advanced forces deployed in isolation from stationary diagnostic and repair tools. As a result - faster repair work and, accordingly, faster return of equipment or weapons to combat units. In addition, it will increase the number of forces and resources available to perform operational tasks. This new approach to maintenance and repair is becoming a factor in increasing combat capability and combat power, which can positively affect the ratio of victories and defeats in modern military conflicts. Keywords: armored vehicles, maintenance, repair of armored vehicles, augmented reality.

Agriculture is one of the biggest sectors and energy consumption during agricultural production causes a release of 11 % of greenhouse gasses leading to climate change. Since after the industrialization of agriculture, farming systems shifted towards high-intensity farming, yet in Türkiye, traditional farming methods continue. In this study we compare the energy efficiency of organic vs. conventional olive groves in Kaz Mountains, Türkiye. 71 farmers were interviewed face-to-face in two subsequent years and the energy efficiency of the olive production process was calculated as the ratio of the energy spent during farming to the energy content of the fruit. Fuel use was calculated under the direct energy input, whereas production processes of fertilizer, agricultural machinery, maintenance and repair, human and animal labor were calculated under indirect energy inputs. Here we show that conventional olive production was less energy efficient due to the high indirect energy input during the production of synthetic fertilizers. There was no relationship between the energy input and yield. This study shows that by improving energy efficiency, the technical performance of agricultural systems can be increased and their negative impact on the environment can be reduced.

Reliable modeling for thermal infrared (IR) signatures of real-world city scenes is required for signature management of civil and military platforms. Traditional modeling methods generally assume that scene objects are individual entities during the physical processes occurring in infrared range. However, in reality, the physical scene involves convective and conductive interactions between objects as well as the radiations interactions between objects. A method based on radiosity model describes these complex effects. It has been developed to enable an accurate simulation for the radiance distribution of the city scenes. Firstly, the physical processes affecting the IR characteristic of city scenes were described. Secondly, heat balance equations were formed on the basis of combining the atmospheric conditions, shadow maps and the geometry of scene. Finally, finite difference method was used to calculate the kinetic temperature of object surface. A radiosity model was introduced to describe the scattering effect of radiation between surface elements in the scene. By the synthesis of objects radiance distribution in infrared range, we could obtain the IR characteristic of scene. Real infrared images and model predictions were shown and compared. The results demonstrate that this method can realistically simulate the IR characteristic of city scenes. It effectively displays the infrared shadow effects and the radiation interactions between objects in city scenes.

The rapid deployment of fiber optic technology in military, avionic, and consumer platforms is driving the need for improvement in fiber optic cable field maintenance, specifically a reduction in operator inspection complexity and ambiguity. Current inspection technology depends on operator experience with various inspection standards and is further complicated in military field deployments where bench top capable inspection equipment does not lend itself to field installations. Military fiber endface inspection is currently very expertise driven and time consuming for avionic environments. Thus there is a need for automated, portable fiber optic inspection technology that is suitable for all skill levels, and is capable of field deployment and maintenance. This paper explores the issue of current fiber optic field inspection technology and present an automated test inspection set to address these problems.

The purpose of this research was to develop a fiber optic (FO) dissolution method for quantification of multiple actives in combination pharmaceutical tablets. FO dissolution allows direct API quantification in the vessel, obviating the need for error-prone facets of traditional dissolution methods. However, FO dissolution is potentially challenged by overlapping UV spectra, matrix effects, UV-active excipients, API interactions with excipients and media, and undissolved components attenuating the UV signal. These obstacles might render FO dissolution method development more complex than LC-end dissolution. The case study in this manuscript has the added complexity of a triple combination product (Midol), where acetaminophen, caffeine, and pyrilamine maleate exhibit similar release kinetics, share largely overlapping UV spectra and span an order of magnitude difference in concentration. Single-wavelength quantification required unique features for the actives of interest, which were not available for the formulation of interest without preprocessing. The methods employed for the quantification of actives were a partial least squares multivariate calibration and a peak area calibration, both using prepared mixtures as reference data. The selected combination tablet demonstrated collinear API release; therefore, individual quantification required a design of experiments for mixture design. The advantages of FO dissolution will be discussed in the context of the formulation under investigation. Additionally, some general guidelines will be suggested for the development of other FO methods.

System-based concept for a mixed reality supported maintenance phase of an industrial plant

Plant maintenance bot is an innovative approach to develop a robot to water plants by monitoring the moisture content in the soil and to detect disease in the plant. This paper presents the methodology to automate the process of plant maintenance without human interference. The entire operation is fully automated to obtain the results quickly and efficiently. The bot is pure hinges on embedded systems, and a specific code is written. The robot is used to recognize moisture content in soil and detect disease in the plant without human interference. We use 14-pin Arduino UNO, a microcontroller board based on the ATmega328P datasheet. The embedded system employs sensor technology with the microcontroller, servo motor, DC motor, and DC pump. Bots that are deployed in a particular area detect a plant and specific plant conditions that prevail in that particular area. Pests that affect the plant can also be identified and sprays the peculiar pesticide. Automated plant maintenance bot can be further extended for a large agricultural area and can be developed to cater to the needs of the farmer depending on the physical orientation of the moisture in the soil and disease in the plant. This process can be implemented in any terrain by improving the hardware components to last long in the process. This paper mainly focuses on maintenance of the plant, and water management to reduce the amount of water used by automating the process is efficient than manually.KeywordsAutomationBotEmbedded systemImage processingMicrocontroller

We experimentally demonstrate the distributed measurement of Fermi–Pasta–Ulam (FPU) recurrence in an optical fiber. Square-shaped pulses with weak modulation are injected into a single-mode fiber to exhibit FPU recurrence. Rayleigh backscattering signals of various sidebands are recorded to measure the power vibration along the optical fiber. The validity of the distributed method is confirmed both by the numerical simulation and the cutting-back method. Compared with the traditional cutting-back method, the distributed method has significant advantages, such as short measurement time, low cost, and good repeatability. We also believe that the distributed method has a great potential for the measurement of other nonlinear effects in optical fiber.

The optical fiber distributed strain sensor based on the optical frequency domain reflectometer (OFDR) preserves its dominant position in short-distance measurement fields with high spatial resolution, such as biomedical treatment, soft robot, etc. However, owing to the weak intensity of the Rayleigh backscattered signal (RBS) in the single-mode fiber (SMF) and complex computation, the large strain changes cannot be precisely and rapidly demodulated by the traditional cross-correlation method. In this work, the OFDR with backscattering enhanced optical fiber (BEOF) is proposed and demonstrated for fast and large strain measurement. By enhancing the RBS amplitude, the signal-to-noise ratio (SNR) is improved, resulting in a higher similarity between the reference signal and test signal, which is beneficial for the expansion of the strain measurement range. Moreover, the adaptive local feature extraction and matching (ALFEM) algorithm is presented and demonstrated, which replaces the traditional cross-correlation method for strain demodulation and fast measurement. On account of the enhancement ratio of BEOF, the dominant characteristic data segment can be extracted from whole wavelength data. In the experiments, the enhancing ratio of BEOF is designed as 10, resulting in the spatial resolution reaches 400µm and the strain measurement range is greatly increased to 4800µɛ. Further, the effectiveness of the ALFEM algorithm has been verified, in which the strain demodulation time is approximately 25% of that of the traditional method. This scheme fully exploits the enhancement characteristic of the BEOF and is also applicable to the systems based on other types of BEOF, different strain changes and sensing distances.

Purpose: Case-based learning (CBL) is now used as a teaching strategy to promote clinical problem-solving ability. The purpose of this study was to determine whether CBL is superior to the traditional teaching method in teaching lung cancer curriculum to oncology students.Methods: This study was a randomized controlled trial, enrolled 80 first-year oncology postgraduates from Bengbu medical college in the past 3 years. They were randomized to divide into 2 groups, had courses with the same lung cancer contents and timing. The experimental group (n = 40) utilized the CBL method while the control group (n = 40) used the traditional lecture-based teaching method. A questionnaire was used to attain the students’ learning satisfaction and self-efficacy of the course, and a post-study examination was used to assess end-of-course performance.Results: Complete data were obtained from participating students (n = 40 in CBL; n = 40 in traditional teaching). The CBL group performed significantly better in questionnaire and examination compared to traditional teaching groups. Students showed high levels of satisfaction and problem-solving ability in the CBL group.Conclusion: Compared with the traditional teaching method. The case teaching method is a more effective teaching method to improve the ability of problem-solving for graduate students in medical oncology.