Aircraft Crash Research Articles

A Neural-Metaheuristic Kalman Filter for Moving Microburst Wind Shear Identification

Microburst wind shears (MB) are powerful localized three dimensional (3D) columns of wind that occur when cooled air drops from the base of thunderstorms at high speeds. They eventually hit the ground and spread out in all directions. As such MBs are considered a major atmospheric hazard for aircrafts (ACs), especially in terminal flight phases. Though pilots train regularly to survive it, yet the most recommended practice within the aviation community is to avoid its encounter upon detection. Some modern aircrafts have predictive wind shear warning systems, but they have limited short range capability and do not provide quantitative data for engineering application. In this sense, accurate onboard detection and identification of MBs and its characteristics is of importance for flight safety, whose success can lead to design of automatic flight control systems (FCSs) that reduce the risk of aircraft crash landings and accidents. Even though there are some studies on FCS designs for MB encounter, research on MB identification is rare but ongoing. To this aim, the present study is among the firsts that focuses on online identification of multiple and moving MB parameters using onboard aircraft air data and inertial sensors. The identification task is initially performed using the aircraft six degrees of freedom (6DoF) equations of motion (EOM) integrated with a 3D MB model via the utility of nonlinear Kalman filtering (KF) algorithms. Subsequently, an enhanced neural metaheuristic Kalman filter (NMKF) is proposed that improves the estimation accuracy of the MB model parameters. The results demonstrate the efficacy of the proposed NMKF in comparison with previous studies.

Fractographic investigation of carbon/epoxy PRSEUS composites exposed to flame after compressive failure

After a structural-related composite aircraft crash, a fractographic forensic analysis of the damaged surfaces is typically performed to assess the root causes of mechanical failures. Such accident reconstruction efforts, however, can be impeded if the aircraft catches on fire on the ground (i.e., a post-crash fire occurs), where flames or heat exposure can obscure or destroy the fracture surface morphologies of the fibers (i.e., the primary load carrying constituent). In this study, carbon/epoxy Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) skin-stringer assemblies were subjected to uniaxial compression and subsequently exposed to direct flame using a Bunsen burner. Specimens were oriented parallel, orthogonal, and at 45° to the flame axis for durations of 60 s. Additional vertical burn tests were performed for durations up to 300 s. Fractographic inspection of the failure surfaces before and after flame exposure was performed using a combination of destructive sectioning and scanning electron microscopy. The warp-knitted skin (fascia) surrounding the pultruded rod effectively served as a thermal protection layer, which shielded the rod’s broken filaments from significant thermal degradation and facilitated the identification of microbuckling and other mechanical failure mechanisms. This suggests that the presence of fascia, bulkheads, ribs, skins, and other intermediate layers in aircraft structures may significantly shield underlying principal structural element failure surfaces from fire exposure, facilitating post-crash forensic assessments of composite aircraft. Additionally, the through-thickness VectranTM stitching remained intact even after extended flame exposure, suggesting that such stitching can enhance the fire resistance of composite structures.

The Feel of Peace: Noise Pollution and the Sovereignty of Wind

Abstract: This essay analyzes the interconnected struggles of US military occupation in Okinawa and Hawai'i through analysis of noise pollution, aircraft crashes, and community responses to these issues. While the violence of airbases transforms air into a space of violence, I turn to the ways that Okinawan and Hawaiian communities articulate their respective sovereignties through the wind. I read legal testimonies from the first noise pollution lawsuit in Okinawa and community testimonies from across O'ahu, putting them in conversation with poetry by Nakazato Yūgō and Brandy Nālani McDougall. Against military reports that implicate wind as a threat which facilitates aircraft accidents and death, the testimony and poetry elucidate how wind builds relation and enables the preservation of intergenerational memory. This archive challenges state formulations of "resolution" by elucidating how deeper histories than the state has considered press onto the body, carrying into the present not only historical wounds but also the capacity for their healing. The sovereignty of wind that they put forth marks a renewal of relationships to air and memory at the same time they are organized around radical returns of land, of night, of the body itself.

Local structural behaviour of the outer containment of an NPP against hard missile impact

An aircraft crash and missile impact on a nuclear containment structure is currently described as an event beyond design basis; however, soon, it will be qualified as a primary design criterion. In the present study, the structural and dynamic behaviour of the outer containment of a nuclear power plant (NPP) has been studied to substantiate its structural integrity against the rigid missile impact. Scaled experiments (at a 1:4 and 1:3 ratio with respect to shell thickness) have been performed to study the localized behaviour of the containment structure against 10 and 20-kg rigid steel projectiles. The reinforced cement concrete (RCC) targets of thicknesses 150 and 200 mm have been subjected to impact at incidence velocity close to the landing and taking of velocity of the aircraft. The flexural reinforcement ratio was considered 1.25 % for a 150 mm thick target and 1.53 % for a 200 mm thick target. The effect of shear reinforcement on the penetration and perforation resistance has been studied for a 200 mm thick RCC target. A detailed post-test examination was conducted to evaluate the localized physical damage characteristics such as spalling and scabbing of concrete, penetration, perforation, crack propagation, and the damage induced in both flexural and shear reinforcements. The mechanics of deformation and failure modes of the target were investigated under varying incidence velocities, 60–115 m/s. The reinforcement characteristics under dynamic loading, such as strain time histories, strain rate sensitivity, and dynamic material properties, were also investigated. The presence of transverse reinforcement in 200 mm thick targets improved the ballistic performance by 12.50 %. Furthermore, the transverse reinforcement also played a crucial role in restricting the bending of the rear face flexural reinforcement and controlling the rear face damage propagation.

Improved Casualty Depiction System for Simulated Mass Casualty Exercises.

Assessing military medical teams' ability to respond to large-scale mass casualty (MASCAL) events has become a priority in preparing for future conflicts. MASCAL exercises rely on large numbers of simulated patients with limited medical training. Role-players must be appropriately prepared to ensure that medical exercises adequately assess the expected capabilities of military medical units. The Uniformed Services University of the Health Sciences (USUHS) has evaluated future military providers for decades using a large-scale, multiday, immersive simulation called Bushmaster. Despite a robust casualty training system, the fidelity of the portrayals remained limited. Through collaboration with national military medical experts, a comprehensive casualty depiction system was developed. This system relied on structured casualty cards linked to time-based illness scripts. Structured casualty cards included an appropriate balance of disease non-battle injuries and trauma, included multipatient presentations based on shared events (i.e., multiple injured personnel due to an aircraft crash), normal and pathologic combat stress, population/unit considerations, requirements for different roles within the medical unit, and expected clinical outcomes. Illness scripts, supplemented by video guides, included time-based courses of illness/injury and prescribed responses to different typical treatments. This system was piloted during an annual MASCAL exercise (Operation Bushmaster) at USUHS. Clinical faculty were queried on the fidelity of this new system while role-players were evaluated on feasibility. Three hundred casualty cards linked to 49 illness scripts were created, peer-reviewed, and piloted at Bushmaster. A total of 170 military members with limited medical training portrayed simulated patients utilizing the new casualty depiction system. Clinical faculty members strongly agreed that the improved casualty depiction system improved the realism of individual patient presentations (96%). Eighty-three percent of role-players strongly agreed that the casualty depiction system was easy to understand. This improved casualty depiction system was a feasible approach to enhance the fidelity of a MASCAL exercise. It has since been shared with military medical units around the globe to assist with their MASCAL exercises, making future multisite evaluations of this casualty depiction system possible.

Aircraft Accident and Crash Images Processing with Machine Learning

The aviation industry is in constant need of innovations in terms of safety and operational efficiency. In this context, low-light image enhancement technologies play an important role in a numerous areas of disciplines, from night flights to accident and collision investigations. Machine learning, deep learning methods and traditional methods not only provide the aviation industry with an effective image processing and improvement capacity in low light conditions, but also reveal important information by analysing the data of low-light images of crashed and destroyed aircraft. Within the scope of the study, traditional methods, deep learning method and machine learning are combined in order to enhance and process low-light ambient images of crashed and destroyed aircraft. By using Swish and Tanh activation functions together in the deep learning model, the performance of the neural networks used in the process of improving low-light environment images was improved and the image quality was increased. The enhanced images were evaluated and compared using PSNR and MSE as objective quality assessment measures. According to the PSNR and MSE criteria, the numerical results obtained from the image enhancement studies of the deep learning model were calculated as 29.85 and 100.44, respectively. The results introduce that the deep learning model provides better image enhancement than traditional methods. In conclusion, improvement of low-light image and processing is an important technological advancement in the aviation industry, enabling safer and more efficient operations. The successful of machine learning include deep learning and traditional methods shows that the aviation industry will achieve a safer and innovative structure in the future.

Acoustic Characterization of Integrated Circuits During Operation

Abstract Power electronics are widely serving as core components of propulsion systems in electric vertical takeoff and landing (VTOL) aircraft. Nevertheless, affected by the Paschen effect, the breakdown voltage of these electronics during flight is significantly lower than that on the ground, which could deteriorate system stability, or even cause aircraft faults or crashes, increasing safety risks for the public. As such, condition monitoring of power electronics has become critical for the safe operation of eVTOL. To achieve non-intrusive monitoring, acoustic emissions (AE) sensors have gained traction with their prominent resistance to electromagnetic interference and high temperatures. However, existing studies yield conflicting results regarding whether an increase in loading voltage impacts the internal mechanical stress of electronics. To address this issue, we present this work to probe the existence and the pattern of a relationship between load voltage and stress wave, since the change of mechanical stress could generate acoustic waves that can be acquired by AE sensors. In this study, an AE sensor was applied onto an oscillator placed upon an epoxy substrate to characterize the acoustic waves emitted from the device under various input loads. In the experiment, we observed a unique AE signal pattern characterized by two distinct components that consistently intersect at a specific frequency. The time required to establish such intersections progressively lengthens as the load voltage increases. Through time-domain and frequency-domain analyses of the unique AE signals under different load voltages, it was discovered that certain features of the unique AE signals have an approximately linear relationship with the load voltage.

Avionics System Design using MBSE Methodology

Abstract: The West Air Sweden Flight 294 serves as a reminder of tragic crashes of aircraftdue to Avionics System failure. Due to malfunction of the Inertial Reference Unit (IRU), the aircraft lost its control resulting in tragic loss of life of the peopleon board. The Avionics System is a complex set of instruments, logical and physical links which must comply with the guidelines of Dob178c. The design of the system is complicated. This paper aims to understand the behavior of the Avionics System using the state-of-the-art Model Based System Engineering (MBSE) technology. This includes the two widely used tools – Capella and Simulink. We aim to understand the dynamic nature of avionics through these tools. Model Based System Engineering can be specifically beneficial because it will help the engineers to detect the flaws in the avionics system much earlier. This will potentially contribute to helping to prevent aircraft crashes due to avionics system failure. The idea of model-based system engineering includes the concept of taking a model as a reference to systematically solve the complex designs of any engineering stage. Before the concept of Model Based Systems Engineering came to be, Documents Based Systems Engineering was the trend in the system engineering department. However, it would take a lot of time, effort and accuracy to correctly pinpoint the information and accordingly design the system from a bunch of documents. MBSE, however, eases such kind of trouble by providing a model as a reference for the systems design

Exploring Legitimization of Religio-Politico Discursive Practices: A Critical Discourse Analysis

The current study examines the legitimacy of religio-politico discursive practices prevalent in the novel a case study of exploding mangoes (2008) by Muhammad Hanif. This text is a cut-throat satire on the military interference in state affairs. Critical Discourse Analysis (CDA) is used as a major method under the theoretical lens of legitimization theory to execute the study. The major character of the novel, General Zia ul Haq, exercises his powers and controls the government of Pakistan by the takeover of the military forces till his death in an aircraft crash on 17 August 1988 in Bahawalpur. On multiple levels, Hanif reveals the religio-political mechanisms wielded by the titled political and religious stooges. The theory of Legitimization interprets how power structures legalize their authority on social, political, and religious groundings. The study also underscores the religiosity imposed by Zia under the pretext of Islamization in this particular era. The study's objective is to spotlight various doctrines of religio-political machinery used to manipulate the political system in the 1980s.

Analysis of injuries in aircraft accident victims in 2002–2022 based on the resources of the Jagiellonian University Department of Forensic Medicine in Kraków = Analiza obrażeń ofiar katastrof lotniczych w latach 2002–2022 na podstawie danych pochodzących z materiałów Zakładu Medycyny Sądowej Uniwersytetu Jagiellońskiego w Krakowie

Aim: The study aimed to analyse the most common injuries of victims of aviation accidents and compare it with the most recent literature. Methods and materials: Retrospective analysis of autopsy protocols of aircraft crash victims from the Forensic Medicine Department from years 2002–2022. The case selection has been made by two independent researchers. After applying the exclusion criteria 27 cases were obtained. Further searched for features that the bodies of victims had in common. There were analysed sex, age, circumstances of the incident, injuries, presence of psychoactive substances (alcohol, drugs), and blood concentration of carboxyhemoglobin. Results: Among 27 cases we found 19 airplane crashes, 4 glider accidents, 3 motor glider accidents, and one helicopter crash. The 1 case had no information about the type of aircraft. The injuries that emerged in each of the victims were typical results of direct impact forces. The most common were rupture of the lungs 63.0 % (n = 17/27), heart 55.6% (n = 15/27), liver 51.9% (n = 14/27), aorta 40.7% (n = 11/27) and spleen 29.6% (n = 8/27). Common bone traumas included fractures of the ribs 77.8% (n = 21/27) upper limbs 77.8% (n = 21/27), skull 74.1% (n = 20/27), pelvis 59.3% (n = 16/27) and spine 51.9% (n = 14/27). Injuries of the cervical spine occurred in victims who violently tilted their heads back. Conclusions: In most cases, the immediate cause of death was extensive multi-organ injuries, followed by thermal burns or brain injuries. In almost half of the victims, the presence of carboxyhemoglobin in the blood indicates that they were alive during the crashes. Knowledge of injury patterns can improve aviation safety and guide in reconstructing the mechanisms and sequences of the accidents.

Underwater acoustic analysis reveals unique pressure signals associated with aircraft crashes in the sea: revisiting MH370

Data analysis from the hydroacoustic stations of the Comprehensive Nuclear-Test-Ban Treaty Organization has unveiled distinctive pressure signals linked to aircraft crashes of varying sizes in the ocean. Notably, these signals were detected at distances ranging from two to five thousand kilometres, highlighting the efficacy of underwater acoustic technology in event identification and classification in marine environments. In this study, we investigate the plausibility of an aircraft, such as Malaysian Airlines Flight 370 (MH370), crashing into the sea leaving a discernible pressure signal at distant hydrophones. Consequently, we focus on recordings obtained from the hydroacoustic monitoring stations located at Cape Leeuwin and Diego Garcia, within a few minutes of the last satellite ping on the 7th arc, associated with the assumed crash time and location. Among the available data, only one relevant signal has emerged as a potential candidate, albeit recorded at a single station out of the two stations available. To ensure a comprehensive analysis, we also examine the time frame and location of the airplane along its initial route. Though no corresponding signal was observed. Nevertheless, the findings in this study narrow down the range of possibilities and present a novel scientific approach to investigate such incidents. These findings contribute to our understanding of acoustic signals associated with aircraft crashes at sea. They emphasise the potential for hydrophones to detect events even when the signal travels long distances through land. Ultimately, this research offers recommendations for conducting on-site experiments involving controlled explosions with energy levels similar to the impact of MH370 along the 7th arc. The aim is to encourage pertinent authorities to implement actions that could reveal insights into the destiny of MH370 specifically. Additionally, this initiative seeks to establish a comprehensive framework for addressing comparable incidents in the broader ocean context.

Geophysical Methods Reveal Aviation Impacturbation and Inform Forensic Archaeological Recovery of Historic Aircraft Crash Sites

ABSTRACTThis paper demonstrates the utility of ground‐penetrating radar (GPR) to inform forensic archaeology recovery efforts of missing service members from historic conflict‐related aircraft crash sites. This approach is becoming more common and improving recovery strategies by pinpointing potential subsurface anomalies prior to excavation. Two examples of recovery efforts at WWII aircraft crash sites are presented, revealing the diversity of landscape upheaval signatures that result from aircraft impacts. In both situations, the GPR successfully located feature boundaries and identified aviation impacturbation. The landscape signature varied in both cases due to factors including the trajectory and velocity of the aircraft crash and the topography of the impacted landscape. Notably, a ‘halo’ effect was identified in association with one crash site, revealing the force of the impact on sandy soils. Recognition of these anthropogenic signals is important to promote effective recovery strategies, thus saving time, labour and funds, particularly in historic sites where postincident taphonomic conditions have severely altered the morphology of the landscape.

Discovering latent themes in aviation safety reports using text mining and network analytics

Aviation accidents, referring to unexpected and undesirable events involving aircraft, often cause great damage to property and human life. Learning from historical accidents is pivotal for improving safety in aviation. However, aviation accidents are typically documented and stored as unstructured or semi-structured free-text, rendering the ability to analyze such data a difficult task. This study presents a novel framework that combines text mining and network analytics techniques and provides the ability to analyze aviation accident reports automatically. The framework comprises a four-step modelling approach to: (1) the transformation of unstructured aviation safety report texts into structured numeric matrices using the TF-IDF matrix; (2) the identification of aviation accident topics using a Structural Topic Model (STM); (3) the production of a Word Co-occurrence Network (WCN) to determine the interrelations between aviation safety risk factors; and (4) quantitative analysis by technology of keywords to pinpoint key causal factors in aviation safety events. The proposed framework is validated by analyzing aviation accident reports collected by the National Transportation Safety Board (NTSB). The results indicate that STM provides a more granular partitioning of topics and better distinguishes between similar events compared to traditional Latent Dirichlet Allocation (LDA). Among the identified topics, “Fuel and Power” and “En-route Phase” have the highest occurrence rate according to STM. Additionally, “Aircraft Crash” is the most prevalent topic in aviation accidents that resulted in fatal injuries, while “Landing phase” is the most prevalent topic in non-fatal injuries on accidents. Based on the word co-occurrence network, three centrality measures highlight “inspection of equipment” and “take off” as the most important risk factors in aviation safety. The proposed framework provides a comprehensive solution for in-depth analysis of aviation safety reports, offering decision support for aviation safety management and accident prevention, thereby reducing risks and strengthening safety measures.

Implementation of SORA Methodology Version 2.5 for Medical Delivery Using Quadrotor UAS in Remote Areas

The innovative quadrotor Unmanned Aircraft Systems (UAS) approach for delivery missions presents significant opportunities to address logistical distribution challenges (i.e. medical delivery) in remote areas. The efficiency of quadrotor UAS, which does not need additional infrastructure like runways, makes it increasingly applicable to remote regions. However, the potential implementation of UAS for medical delivery missions comes with considerable risks, such as collisions with manned aircraft or UAS crashes that could damage infrastructure and cause fatal injuries to human life. Therefore, in UAS operations, a method of operational risk assessment is needed to ensure safety, resilience, and operational success. The Joint Authorities for the Rulemaking of Unmanned Systems (JARUS) offers a risk assessment methodology named Specific Operational Risk Assessment (SORA) for UAS operations. The European Union Aviation Safety Agency (EASA) and the Indonesian Ministry of Transportation have recognised and approved this methodology as a risk assessment method for specific UAS categories. SORA provides a step-by-step framework in risk assessment to identify, evaluate, and determine necessary mitigation actions to achieve an acceptable means of compliance (MoC). EASA has announced using the latest version, SORA V2.5, planned for implementation in the fourth quarter of 2023. The Indonesian Ministry of Transportation also plans to adopt this latest version for UAS operations. Several updates and simplifications have been made to this version. Therefore, this paper presents the application of risk assessment using SORA V2.5 for medical delivery operations in remote areas using quadrotor UAS. The analysis in this paper covers each step of SORA V2.5, including risk identification and evaluation, as well as the implementation of mitigations in the conducted mission. The results indicate that SORA V2.5 can be implemented in this mission by taking appropriate mitigation actions to assure operational safety. There are also recommendations for optimising risk identification and it can complement the SORA methodology.

Tort Claims Arising From Military Aircraft Crashes Are Not Preempted By The Federal Aviation Act

The Second Circuit's landmark ruling in Jones v. Goodrich Pump & Engine Control Sys., Inc. establishes crucial precedent by asserting that tort claims stemming from military aircraft crashes are not field or conflict preempted by the Federal Aviation Act (the Act). This decision, the first of its kind at the appellate level, carries far-reaching implications. The court’s rationale, grounded in the Act’s plain language, emphasizes that “public aircraft,” including military ones, are exempt from Federal Aviation Administration regulation. Title 49, section 44701(a)(1), explicitly excludes public aircraft from the Act’s purview. While the court’s analysis relies on the Act’s text, it is fortified by a comprehensive examination of legislative history dating back to the early days of aviation. This Article contends that the Second Circuit’s reasoning, supported by both statutory language and over a century of legislative evolution, should serve as a universally adopted guideline. The separation of civil and military aircraft regulation, initiated in the Paris Convention of 1919 and continued through subsequent legislative acts, underscores the distinct standards governing military aviation. The inherent divergence in purpose and design between civil and military aircraft, coupled with Congress’s consistent exclusion of military aircraft from FAA regulation, solidifies the argument against preemption. As the sole appellate authority on this matter, the Jones decision provides a robust foundation for future courts facing Federal Aviation Act preemption challenges in “public aircraft” tort cases.

The effect of global warming and climate changes on aircraft accidents between 2010-2022

PurposeOne of the sectors most affected by the variable weather events caused by climate change and global warming is the aviation sector. Especially in aircraft accidents, weather events increasing with climate change and global warming are effective. The purpose of this study is to determine how much the change in weather conditions caused by global warming and climate changes affect the aircraft in the world between the years 2010 and 2022.Design/methodology/approachIn this study, it was investigated which weather events were more effective in aircraft crashes by determining the rates of air events and aircraft crashes in aircraft crashes with a passenger capacity of 12 or more that occurred between 2010 and 2022.FindingsIt is clearly seen that increasing weather conditions with global warming and climate change increase the effect of weather conditions in aircraft crashes.Originality/valueThe difference of this study from other studies is the evaluation of the data of the past 12 years, in which the increasing consequences of global warming and climate change have been felt more. It also reveals the necessity of further research on the effects of weather conditions on aircraft.

A Refined Analysis Method for Flight Safety Based on a Multi-stage Reliability Model

Flight verification is an indispensable key step in the process of aircraft development. Due to the inevitable existence of protected targets in and around the flight area, the accidental crash of aircraft during flight will pose a threat to the protected targets, so it is necessary to carry out a quantitative analysis of flight safety risks. To meet the requirements of flight safety risk quantitative analysis and improve the refinement degree of risk quantification, this paper proposes a flight safety refinement analysis method based on a multi-stage reliability model. Firstly, the failure modes of the aircraft flight process are summarized, and then the stage distribution logic analysis method and quantitative calculation method of failure modes are proposed. Finally, the target threat probability calculation model is given, which realizes the quantitative evaluation of the safety risk of the flight area and provides support for the optimization design of the flight safety control area.

Head Flail Corridors From Sled Impact Acceleration Tests for Use in Occupant-Centric Vehicle Design.

In aircraft crashes, injuries to the head and upper torso are frequently reported, with head injury reported most frequently of all body regions. Because preventing flail of the head and body is of utmost importance for occupant survival, the Aircraft Crash Survival Design Guide (ACSDG), the guide to crashworthy aircraft design, published flail envelopes. However, the ACSDG flail envelopes are based on a single test with an anthropomorphic test device subjected to a frontal acceleration. In this article, human research volunteer (HRV) response data are used to calculate head flail corridors and evaluate the ACSDG flail envelopes. Data from HRV sled tests were obtained from the historical Naval Biodynamics Laboratory collection of the Biodynamics Data Resource. Digitized high-speed film for each test was tracked and processed to represent the head flail response in a format amenable to corridor development. Time-based and position-based head flail corridors were developed for groups of exposure-matched tests and then compared to the ACSDG flail envelopes. A collection of 714 HRV sled tests conducted in six different impact directions ranging from 3 to 15 g was used to develop time-based and position-based head flail corridors for 39 match groups. The ACSDG vertical limit and anteroposterior limit and curve were not exceeded by the flail corridors, but the lateral limit and curve were exceeded by 4.6 cm to 15.8 cm. The flail corridors provide a useful baseline for representing the well-restrained occupant response at lower, non-injurious exposure levels and across multiple impact directions. Under these conditions, the ACSDG lateral limit and curve are not adequate. At higher exposure levels or with modified restraints, seating, or equipment, the ACSDG vertical limit and anteroposterior limit and curves may also be inadequate.

Design of foreign object debris detecting and monitoring using two sets of sensor system

<span>Foreign object debris (FOD) is a foreign object that should not be on the runway which might cause the risk of aircraft crashes and put the lives of humans at risk. In this research, we designed a system to detect FOD using two sets of a sensor system for a wider, area of detection. This research was commenced by designed the entire hardware and software and tested the system. The object used as the testing object were rock, bolts, plastic bottles as well as iron pieces with varied distances and position angles. Based on the testing result, both sets of sensor system could detect objects with distance accuracy on the sensor system set of FOD 1 and FOD 2 consecutively were 98% and 94% for rock, 97% and 96% for bolts, 96% and 94% for plastic bottles, 96% and 94% for the iron pieces. The accuracy of angle measurement on the sets of sensor system FOD 1 and FOD 2 consecutively were 96% for rock, 98% for bolts, 97% and 95% for plastic bottles, 97% and 94% for the iron pieces. Monitoring system testing was carried out using black box testing and website response speed test towards the variation of database number.</span>

Adaptive receptive field based on multi-size convolution kernel for micro-defect detection of turbine blades

Because turbine blades are essential parts of aircraft engines, micro-defects on the surface of turbine blades induce accidents in aircraft crashes. The detection of micro-defects in aerospace turbine blades is achieved within the realm of non-destructive evaluation. Given that most of the defects are tiny and spread randomly on a curved surface, which cannot be completely detected by current target detection methods, it is feasible for micro-defects to be effectively detected by the fluorescent magnetic particle method. In this paper, we propose a Defect Classification (DCLS)-Deformable Detection Transformer (DETR) model to inspect micro-defects in an automatic fluorescent magnetic particle inspection system. In the DCLS-Deformable DETR model, an adaptive receptive field (ARF) attention module is designed, which considers the interdependencies between the channel features of different feature maps. The weights between the channels of each feature map were also considered, while adaptively adjusting the receptive field according to the detection target size. The DCLS-Deformable DETR model with ARF increased the AP from 63.4% to 64% and AP50 from 95.2% to 97.2%, compared to the Deformable DETR. Turbine blades include three typical defects: linear cracks, reticular cracks, and pitting corrosion. Compared with the original model, the proposed model enhances the AP of three defect types by 1.8%, 2% and 4.7% respectively. The DCLS-Deformable DETR model considers the position, level information, and channel information of the input samples, which can capture micro-defects around large defects.