Debris Monitoring Research Articles

Online Symmetric Magnetic Excitation Monitoring Sensor for Metal Wear Debris

The metal wear debris in mechanical transmission can feedback the characteristics of mechanical equipment failure, and its online monitoring efficacy directly affects the operating performance of mechanical equipment. Specific to the need for online fault detection of the mechanical transmission system, a double-coil reverse excitation method is adopted to provide a magnetic field environment for metal wear debris testing in the lubricating oil circuit of the mechanical transmission system. Based on the magnetic field distribution model of a single-coil solenoids, a coupling magnetic field distribution model of reverse-symmetric double-coil magnetic excitation is established. On the basis of detecting the coils to obtain the signals of magnetic field disturbance when metal water debris passing through the magnetic excitation field, an online monitoring sensor for metal wear debris with a reverse-symmetric double-coil magnetic excitation balance magnetic field is developed. Taking the monitoring of metal wear debris in a large-aperture flow channel as an example, a semi-physical simulation test has been carried out on metal wear debris in different grain diameters and textures, whose experimental results indicate that this sensor can detect <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$100 ~\mu \text{m}$ </tex-math></inline-formula> ferromagnetic metal and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1000 ~\mu \text{m}$ </tex-math></inline-formula> non-ferromagnetic metal in an 8 mm flow channel, which, as a detection sensor for metal wear debris, can also be used for metal wear debris monitoring in the mechanical lubricants of mechanical transmission and engines.

Foreign object monitoring method in aero-engines based on electrostatic sensor

This paper introduces the principle of Ingested Debris Monitoring System in aero-engine and establishes a mathematical model of its core component, the ring-like probe; this paper simulates foreign object's movement based on the established model and performs numerical analysis of the induced charge pulse waveform. Pulse amplitude and pulse width are used as the two pulse features of pulse waveform. Numerical analysis gets the relationship between pulse features and foreign object's charge amount, velocity and radial position. A new method for estimating foreign object's radial position and charge amount has been proposed based on the conclusion of numerical analysis. Both the correctness of numerical analysis and the new estimating method has been verified in the oil calibration test rig. All the relative errors are within 10%. Further experiments with high velocity condition are carried out in an air-gun test rig. The occurrence time, radial position, charge amount, velocity and material category of foreign object can all be obtained, which has important significance to the safety of aero-engines.

The Occurrence of Microplastics in Sediment Cores from Two Mangrove Areas in Southern Thailand

Mangroves are areas that connect the land and sea, and are important to the ecosystem. They are important places for food sources and the habitat of aquatic fauna in the tidal areas. However, the existence of plastic debris poses a risk to the aquatic environment. This study aimed to investigate the accumulation of microplastics (MPs) in sediment cores from two mangrove areas. The first mangrove area is in the outer section of the Songkhla lagoon (SK), while the second is in the coastal area of Pattani province (PN). Sediment core sampling was performed from SK = 8 stations and PN = 5 stations. Surface enrichment of MP was observed, especially in sediments of 0–4 cm. MPs were found throughout the depth in both areas, while fewer MPs were found in deeper sediment core layers (p &lt; 0.05) at some stations inside the mangrove zone. Simple linear regression of the observed MPs and distance in the horizontal were found to be significant at SK within the mangrove zone with r2 = 0.79 (p &lt; 0.05). MP fibers were the most commonly found MP type in both areas and were less than 1 mm. Blue and black MPs were the most abundant colors found in both areas. The six polymer types reported in this study comprised polyethylene, rayon, rubber, styrene, Poly (vinyl acetate), and paint. The findings of the present study suggest that long-term monitoring of marine debris along coastlines is necessary to help improve national policies and measures related to marine plastic debris.

Deterioration state diagnosis and wear evolution evaluation of planetary gearbox using vibration and wear debris analysis

The deterioration state of planetary gearboxes with pitting faults cannot be diagnosed and evaluated effectively with a single type of monitoring signal and traditional features. In this study, a new diagnose method was proposed based on the tribology and vibration signal of planetary gear systems. A new feature extraction approach was exploited to construct a multi-feature fusion relevance vector machine (MFFRVM) model for diagnosing the deterioration state of planetary gearboxes. Meanwhile, a novel index for online wear debris monitoring (ADIDC) was extracted to evaluate the wear evolution of planetary gears. Condition monitoring experiments were conducted on a planetary gearbox. Experimental results show that the diagnostic method combining the MFFRVM model and ADIDC index achieves better accuracy than other methods. This study provides guidance for the wear evolution evaluation of planetary gears with pitting faults and the early fault recognition of planetary gearboxes.

Comparing methods for monitoring nest debris using silver gulls as a case study

Global plastics production is increasing exponentially and contributing to significant pollution of the marine environment. Of particular concern is ingestion and entanglement risks for marine wildlife, including when items such as rope are incorporated into nest structures. These events are commonly documented using photographic and visual surveys, and each presents a number of challenges and benefits for species conservation and monitoring. Here we compare an invasive (i.e., removing debris from nests) and non-invasive (i.e., photographs) sampling method for quantifying nest debris using the silver gull (Chroicocephalus novahollandiae) as a case study. Overall, 17 debris items were detected in 9% of gull nests. While the use of photographs to monitor nest debris is increasingly popular, the invasive method detected one additional debris item not identified using photography. We therefore recommend caution for nest debris and other monitoring programs where identifying small or cryptic items may require a high level of skill.

A New In Situ Coaxial Capacitive Sensor Network for Debris Monitoring of Lubricating Oil.

Wear debris monitoring of lubricant oil is an important method to determine the health and failure mode of key components such as bearings and gears in rotatory machines. The permittivity of lubricant oil can be changed when the wear debris enters the oil. Capacitive sensing methods showed potential in monitoring debris in lubricant due to the simple structure and good response. In order to improve the detection sensitivity and reliability, this study proposes a new coaxial capacitive sensor network featured with parallel curved electrodes and non-parallel plane electrodes. As a kind of through-flow sensor, the proposed capacitive sensor network can be in situ integrated into the oil pipeline. The theoretical models of sensing mechanisms were established to figure out the relationship between the two types of capacitive sensors in the sensor network. The intensity distributions of the electric field in the coaxial capacitive sensor network are simulated to verify the theoretical analysis, and the effects of different debris sizes and debris numbers on the capacitance values were also simulated. Finally, the theoretical model and simulation results were experimentally validated to verify the feasibility of the proposed sensor network.

Design of decision support system service in the Space Science Center using microservices approach

Development of the Decision Support Systems (DSS) has been written up in the Space Science Center’s roadmap for the next few years. The main programs have to be achieved such as related to the DSS are Space Weather, HF Radio Communication, Space Debris Monitoring, and Navigation activities. Of course, accessing those DSS services separately may become a problem for users who need information as fast as possible. We proposed an information system as a portal to integrate all DSS services collecting the latest information from each main program. We applied the microservice approach for design of this Information System prototype, which will it grows up as the modern application model that is capable to handle multiple features, high scalability but still lightweight. Microservices approach is a method that breaks an application into a single-function module for optimizing its performance. In addition, usage of web service technology and REST-ful API also can support system interoperability functions. In this design we conducted several stages, use case Diagrams, design of microservices database, and prototyping frontend pages in the results. This study purposes to provide an initial system design with a detailed explanation of specification requirements so that the design of the Decision Support System Service in the Space Science Center environment can be developed as expected.

Monitoring of plastic debris in the lower Citarum River using Unmanned Aerial Vehicles (UAVs)

Plastic pollution has become a problem in recent years. Various methods are used to reduce and prevent plastic pollution. Many methods have been used to estimate the abundance and transportation of plastics in waters, especially rivers. This paper presents the use of an Unmanned Aerial Vehicle (UAV) to observe plastic waste in river flow. Monitoring plastic debris was conducted at the downstream part of the Citarum river in the Muara Gembong sub-district, Bekasi Regency, West Java Province, on March 6, 8, and 10, 2021. The type of drone used was the DJI Phantom 3 Pro. Data analysis uses the CVAT program developed by Intel to label images. The results show differences between visual counting and UAV, visual counting has a higher value than UAV, but VC might suffer from an observer bias. The counting bias is dependent on the current and the ability of the eye. On the other hand, the results of aerial surveys during the calculation process can be reinterpreted manually or automatically and corrected again. Monitoring plastic debris using UAVs can be an alternative to observing the plastic transportation process in rivers, especially in areas that are difficult to access.

A False Alarm Elimination Algorithm of Foreign Objects Debris Detection Based on Duffing Oscillator

The main challenge of foreign objects debris (FOD) monitoring based on millimeter-wave (MMW) radar is the interference of strong ground clutter. The clutter-map constant false alarm rate (CM-CFAR) method is commonly utilized for FOD monitoring, but detection results are usually accompanied by many false alarms in the complex ground clutter environment. To solve this problem, this work proposed a false alarm elimination algorithm. Specifically, the CM-CFAR method is firstly used to separate the suspicious targets (including FOD and false alarms) from the background clutter. Then, the Duffing detection system is constructed to detect the sinusoidal frequencies associated with suspicious targets. Finally, according to the detection results of Duffing system, suspicious targets can be classified as FOD and false alarms. In addition, in order to detect the sinusoidal frequencies efficiently, a quantitative detection method based on Poincare section points analysis is proposed to identify the state transition of Duffing oscillator. The results from both simulation and field case show the excellent false alarm elimination performance of the proposed algorithm.

Impedance Sensor with Multi-coil for Oil Debris Monitoring

Impedance Sensor with Multi-coil for Oil Debris Monitoring

Capacitive–Inductive Magnetic Plug Sensor With High Adaptability for Online Debris Monitoring

A capacitive&#x2013;inductive magnetic plug sensor for online condition monitoring is proposed in this article, which can achieve particle counting, debris measurement, and wear rate estimation. The sensor can detect capacitance and inductance parameters, the coil is the outer electrode to detect the dielectric change in capacitance mode, and the coil directly induces magnetic field disturbance in inductance mode. Through introducing a reference unit, Wheatstone bridge circuits are constructed to enhance the response to debris and reduce the interference of oil temperature and viscosity. A postprocessing circuit with filtering and amplifying functions is adopted to improve accuracy. The sensor output characteristics and debris position effect are studied through the experiment. The comprehensive analysis of the detection results in two modes can improve sensor adaptability and overcome the deficiency of low reliability based on a single detection method. This sensor can provide more accurate debris information for the fault diagnosis of hydraulic equipment and is of great significance for intelligent maintenance.

Unmanned aerial vehicles and deep learning for assessment of anthropogenic marine debris on beaches on an island in a semi-enclosed sea in Japan

The increasing prevalence of marine debris is a global problem, and urgent action for amelioration is needed. Identifying hotspots where marine debris accumulates will enable effective control; however, knowledge on the location of accumulation hotspots remains incomplete. In particular, marine debris accumulation on beaches is a concern. Surveys of beaches require intensive human effort, and survey methods are not standardized. If marine debris monitoring is conducted using a standardized method, data from different regions can be compared. With an unmanned aerial vehicle (UAV) and deep learning computational methods, monitoring a wide area at a low cost in a standardized way may be possible. In this study, we aimed to identify marine debris on beaches through deep learning using high-resolution UAV images by conducting a survey on Narugashima Island in the Seto Inland Sea of Japan. The flight altitude relative to the ground was set to 5 m, and images of a 0.81-ha area were obtained. Flight was conducted twice: before and after the beach cleaning. The combination of UAVs equipped with a zoom lens and operation at a low altitude allows for the acquisition of high resolution images of 1.1 mm/pixel. The training dataset (2970 images) was annotated by using VoTT, categorizing them into two classes: ‘anthropogenic marine debris’ and ‘natural objects.’ Using RetinaNet, marine debris was identified with an average sensitivity of 51% and a precision of 76%. In addition, the abundance and area of marine debris coverage were estimated. In this study, it was revealed that the combination of UAVs and deep learning enables the effective identification of marine debris. The effects of cleanup activities by citizens were able to be quantified. This method can widely be used to evaluate the effectiveness of citizen efforts toward beach cleaning and low-cost long-term monitoring.

A new model for bearing spall size estimation based on oil debris

This paper presents a study on damage severity estimation of spalled bearings based on an Oil Debris Monitoring (ODM). Several failure progression tests on angular contact ball bearings were performed. The spalls formed at the end of the tests were expanded over more then 180° of the bearing race. Based on the ODM data analysis, it was possible to discriminate between the three stages of spall growth i.e., initiation, steady-state propagation, and accelerated propagation. A well-established dynamic model of bearings was used to simulate the dynamic behaviour of the angular contact ball bearing with a variety of spall sizes on the inner race. The analysis of the simulated signals from the model revealed that the transition from the steady-state to the accelerated propagation stages occurred at the arc length between two adjacent balls. This finding allowed the development of a new ODM model for spall size estimation in the accelerated propagation stage. The new ODM model relates the loss of mass from a bearing, as measured by an ODM sensor, to the size of the spall in the bearing. The ODM model considers the change in the spall geometry as the bearing deteriorates. The estimated spall size was in good agreement (maximum error of 13%) with the measured spall size at the end of the failure progression tests.

A New Inductive Debris Sensor Based on Dual-Excitation Coils and Dual-Sensing Coils for Online Debris Monitoring.

Lubricants are of key importance for mechanical processing, and exist in nearly every mechanical system. When the equipment is in operation, debris particles will be generated in mechanical lubricants. The detection of debris particles can indicate the wear degree of machinery components, and provide prognosis warning for the system before the fault occurs. In this work, a novel type of inductive debris sensor consisting of two excitation coils and two sensing coils is proposed for online debris monitoring. The developed sensor was proven to be of high sensitivity through experimental verification. The testing results show that, using the designed sensor, ferrous metal debris with a size of 115 μm and nonferrous metal debris with a size of 313 μm in a pipe with an inner diameter of 12.7 mm can be effectively detected. Moreover, the proposed inductive debris sensor structure has better sensitivity at higher throughput and its design provides a useful insight into the development of high-quality sensors with superior performances.

Stereovision for surveillance of Earth orbiting objects: Two methods and their validation with synthetic data

Due to the new trend of space economy and to the resulting increase of space objects, Space Surveillance and Space Traffic Management are becoming essential to reduce the risk of in-orbit collisions and of potential on Earth damages from uncontrolled re-entries. Ground based optical observations, where cameras are coupled with telescopes, represent an invaluable resource for space debris monitoring and tracking. Observations from one single site may provide angular celestial coordinates of a space object, but they must be supplemented with filters and astrodynamic models to provide an estimate of the object trajectory. An alternative approach is the use of multi-site optical observations, where images of the same portion of sky collected with different cameras are matched to retrieve the 3D instantaneous position of space objects without the need of a priori knowledge of the object orbit parameters. Therefore, multi-site observations are extremely convenient to track uncontrolled Earth re-entry and close approach, where the orbit parameters are generally not stable. Here we focus on two-cameras systems and we discuss the use of two triangulation methods: one based on analytic geometry, the other one based on projective geometry. As a proof-of-concept, we compare the performance of the two methods in terms of accuracy in the 3D reconstruction on synthetic images that reproduce the night sky – including orbiting objects and stars – from different locations. To simulate realistic data sets, we produced images taking into account the effect of refraction and annual aberration on the stars, and we added gaussian noise to the position of the stars and of the space objects on the images. The comparison between the two methods shows that they are both valuable, with the projective method being more robust against noise.

Characterization of gas turbine ingested sand particles based on electrostatic signal

Particle ingestion into a gas turbine can have serious effects on both performance and engine in-service reliability. Thus there exists a need for in situ monitoring and characterizing particulate matter entering an aircraft engine inlet for the purposes of engine damages estimation and prognosis. This paper presents the initial development of Ingested Debris Monitoring System (IDMS) signal processing method of characterizing the ingested particles. A theoretical analysis and simulation study were carried out to study the relationships between the characteristics of the ingested sand particles and the features of the IDMS signal both in frequency- and time-domain. A Finite-Element Modeling (FEM) for the IDMS Sensor was developed, then the validated FEM modeling was used for simulation experiments of particles ingestion under various conditions of different particle moving speeds, concentrations and charge-to-mass ratios. Results of the theoretical analysis and simulation study demonstrates the feasibility and effectiveness of the proposed method to provide real time information characterizing the size and concentration of ingested sand particles, and will serve as an impetus to carry out further research.

Marine debris database development using international best practices: A case study in Vietnam

Marine debris, particularly plastic debris is a ubiquitous global pervasive problem. The international community recognizes that a reduction in plastic debris density is central to sustainable ocean use based on reduction performance metrics. Although many national databases already exist or are being developed, an internationally accepted index of plastic debris density does not currently exist. Standardized methods for monitoring marine debris can help inform policy decisions to reduce sources marine debris and support mitigation effectiveness.Vietnam recently committed to addressing marine debris nationally and internationally and developed ambitious targets to manage and reduce ocean plastic debris, yet Vietnam does not currently have a national marine debris monitoring database. This study identified international best practices and standards; developed a marine plastic database for accurate, efficient information gathering, management, and reporting; and developed a centralized database platform for future marine plastic debris management in Vietnam that can be adapted for other jurisdictions.

Coordination and harmonization of a marine plastic debris monitoring program for beaches in the Wider Caribbean Region: Identifying strategic pathways forward

An aim of the United Nations Decade of Ocean Science is to quantify marine plastic debris in the marine environment. This study analyzes peer-reviewed articles on marine debris monitoring conducted on beaches in the Wider Caribbean Region, with a focus on marine plastic debris. Governance and funding regimes for monitoring events were assessed to determine strategies needed for coordinated and harmonized marine plastic debris monitoring in the Wider Caribbean Region. High variation in standardized survey protocols were observed during monitoring events. Standardization of sampling methodology and reporting metrics among other considerations, are needed to establish a regional marine plastic debris monitoring program that can inform policy for the Wider Caribbean Region.

Marine debris monitoring in the coastal area of the District of Banyuwangi, Indonesia: Characterization of the debris type and composition

This study was aimed to monitor and collect the data on marine debris in the coastal area of the District of Banyuwangi, Indonesia. The survey was conducted in two periods, i.e., July and October of 2020 in Cemara Beach and Syariah Beach. The coastal marine debris sampling was done in accordance with the guideline published by Indonesian Ministry of Environment and Forestry. In terms of number of debris/m2, the result shows that plastic was the dominant coastal marine debris. The density of macro plastic and meso plastic debris in July 2020 are 1.96 – 5.44 debris/m2 and 0.28 – 0.80 debris/m2, respectively; while in October 2020, the density of macro plastic and meso plastic debris are 1.24 – 3.24 debris/m2 and 0.56 – 2.24 number of debris/m2, respectively. The information on the characteristics of marine debris could assist the authority in formulating the proper strategy to overcome the problem as well as support the government in planning a good sustainable coastal management.

A Case Study in Planning and Executing a Source-Control Exercise Using a Visual Simulator as a Well Response Training Tool

ABSTRACT Since the 2010 Macondo incident, the oil industry has made many strides in improving offshore blowout prevention and preparedness. This includes manufacturing over 20 large subsea capping stacks with other supporting subsea source control equipment (e.g. cutting tools for debris removal, injection and monitoring equipment for subsea dispersants) , and routinely conducting emergency exercises to demonstrate the ability to simulate deploying their subsea control equipment defined in their source control emergency response plans, often on short notice for government initiated unannounced exercises. In 2017, Anadarko partnered with U.S. and Mexican government agencies to conduct a joint-preparedness exercise to demonstrate a binational response to a hypothetical pollution incident that would threaten the border zone of both countries. The exercise conduced in accordance with the Mexico – US (MEXUS) Plan, a bilateral agreement between both countries for offshore spill that would originate in one country and could impact the other country. Coordinating a drill that involved over 300 participants from multiple companies and organizations took several years. A short coming of previous similar exercises have been the lack of visualization and sense of realism. A fit-for-purpose visualization simulator was used improve the overall training and learning experience. The visual simulator is coupled with a dynamic multi-phase simulator to ensure that the physics of the blowout and intervention operations are as realistic as possible. The improved visualizations and physics of the source-control operation significantly improved the learnings compared to previous exercise events. This paper explains the general methodology for closing a capping stack, and, more importantly, the planning process that made the drill successful.