Guided Lamb Wave Array Time-Delay-Based MUSIC Algorithm for Impact Imaging.

Composite materials, valued in aerospace for their stiffness, strength and lightness, require impact monitoring for structural health, especially against low-velocity impacts. The MUSIC algorithm, known for efficient directional scanning and easy sensor deployment, is gaining prominence in this area. However, in practical engineering applications, the broadband characteristics of impact response signals and the time delay errors in array elements' signal reception lead to inconsistencies between the steering vector and the actual signal subspace, affecting the precision of the MUSIC impact localization method. Furthermore, the anisotropy of composite materials results in time delay differences between array elements in different directions. If the MUSIC algorithm uses a fixed velocity value, this also introduces time delay errors, further reducing the accuracy of localization. Addressing these challenges, this paper proposes an innovative MUSIC algorithm for impact imaging using a guided Lamb wave array, with an emphasis on time delay management. This approach focuses on the extraction of high-energy, single-frequency components from impact response signals, ensuring accurate time delay measurement across array elements and enhancing noise resistance. It also calculates the average velocity of single-frequency components in varying directions for an initial impact angle estimation. This estimated angle then guides the selection of a specific single-frequency velocity, culminating in precise impact position localization. The experimental evaluation, employing equidistantly spaced array elements to capture impact response signals, assessed the effectiveness of the proposed method in accurately determining array time delays. Furthermore, impact localization tests on reinforced composite structures were conducted, with the results indicating high precision in pinpointing impact locations.

Impact monitoring of large size complex metal structures based on sparse sensor array and transfer learning.

During aircraft operations, the impact events experienced by the aircraft may cause damage to the structure, thus posing a safety hazard. Therefore, an accurate determination of where the impact occurred and the time history of the impact force can provide an important basis for assessing the condition of the aircraft. However, modern aircraft structures are often large and complex, and relying on dense arrays of sensors for monitoring adds additional weight to the aircraft and reduces the economics of aircraft operation. This paper proposes a region-to-point monitoring strategy. First, a Convolutional Neural Network (CNN) model with region localization capability is trained using the sparse sensor array acquisition data. Then, the weighted center algorithm is used to determine the specific location where the impact occurs, in which the added fuzzy genetic algorithm can provide the ability to adjust weights to improve localization accuracy adaptively. As for the impact force prediction, this paper adopts a model based on a Convolutional Neural Network-Gated Recurrent Unit combined with a Squeeze-Excitation attention mechanism (CNN-GRU-SE), which is capable of predicting the impact force occurring in the flat plate and reinforced structure region of the aircraft under different energy conditions. Finally, the impact of incorporating a transfer learning approach on model performance and training cost is investigated for fuselage regions with different structures.

Conformable Multifunctional Space Fabric by Metal 3D Printing for Collision Hazard Protection and Self-Powered Monitoring.

The monitoring of space debris assumes paramount significance to ensure the sustainability and security of space activities as well as underground bases in outer space. However, designing a wide range monitoring system with easy fabrication, low power, and high precision remains an urgent challenge under the scarcity of materials and extreme environment conditions of outer space. Here, we designed a one-piece, robust, but flexible, and repairable 3D metal-printed triboelectric nanogenerator (FR-TENG) by incorporating the advantages of standardization and customization of outer space 3D metal printing. Inspired by the structure of hexagonal and pangolin scales, a curved structure is ingeniously applied in the design of 3D printed metal to adapt different curved surfaces while maintaining superior compressive strength, providing excellent flexibility and shape adaptability. Benefiting from the unique structural design, the FR-TENG has a minimum length of 1 cm with a weight of only 3.5 g and the minimum weight resolution detected of 9.6 g, with a response time of 20 ms. Furthermore, a multichannel self-powered collision monitoring system has been developed to monitor minor collisions, providing warnings to determine potential impacts on the space station and bases surfaces. The system may contribute to ensuring the successful completion of space missions and providing a safer space environment for the exploration of extraterrestrial life and the establishment of underground protective bases.

Head Impacts in the Top 1% by Peak Linear Acceleration and/or Work Cause Immediate Concussion Signs and 'Check Engine' Responses in Military Service Members and Civilian Athletes.

PURPOSE: Historically, head impact monitoring sensors have suffered from single impact measurement errors, leading to their data described by clinical experts as 'clinically irrelevant.' The purpose of this study was to use an accurate impact monitoring mouthguard system and (1) define head impact distributions for military service members and civilians and (2) determine if there was a dose-response relationship between accurately measured head impact magnitudes versus observations of concussion signs. METHODS: A laboratory-calibrated commercial impact monitoring mouthguard system, along with video and hardware to confirm the sensor was on the teeth during impacts, was used to acquire 54,602 head acceleration events (HAE) in 973 military and civilian subjects over 3,449 subject days. RESULTS: There were 17,551 head impacts (32% of HAE) measured with peak linear acceleration (PLA) > 10 g and 37,051 low-g events (68% of HAE) in the range of activities of daily living < 10 g PLA. The median of all HAE and of all head impacts was 8 g/15 g PLA and 1 J/4 J Work, respectively. The top 1% of head impacts were above 47 g and 32 J, respectively. There were fifty-six (56) head impacts where at least one clinical indicator of a concussion sign was observed. All the clinical indicator impacts were in the top 1% by magnitude of PLA, Work, or both. The median magnitude of these 'check engine' impacts was 58 g and 48 J. This median magnitude was substantially larger than the median of all HAE as well as the median of all head impacts. CONCLUSION: This study shows a correlation between single head impacts in the top 1% by peak linear acceleration and/or Work and clinical indicators of concussion signs in civilians and military service members.

Air Pollution Health Impact Monitoring and Health Risk Assessment Technology and Its Application - China, 2006-2019.

Air pollution is a significant risk factor contributing to the burden of disease in China. Health risk assessment and management are important to reduce the impact of air pollution on public health. To help formulate standardized health risk assessment techniques, a series of studies were conducted from 2006 to 2019. Through systematic review, study of molecular mechanisms, epidemiological investigation, and health effect monitoring, the overall project established a monitoring and evaluation indicator system, a comprehensive information platform, software for automatic data cleaning, and standardized health risk assessment techniques. Technical specifications have been issued by the National Health Commission for promoting health risk assessments across China. This paper introduces the project, the research approach, its main research accomplishments, innovations, and public health significance, and describes directions for further research.

Monitoreo del impacto en la formación de especialistas en Medicina Intensiva y Emergencias en Matanzas / Monitoring the impact in the formation of specialist in intensive medicine and emergencies, Matanzas

Introducción: la evaluación y acreditación de la calidad en la formación de las especialidades médicas en Cuba, conceptualiza el monitoreo del impacto como el proceso dirigido a evaluar la correspondencia entre los objetivos del programa y los resultados alcanzados por sus participantes en el entorno social donde se desarrollan profesionalmente. Objetivo: aplicar la metodología diseñada para el monitoreo del impacto en la formación de las especialidades médicas en el Programa de Medicina Intensiva y Emergencias. Materiales y métodos: se realizó un estudio de corte pedagógico donde se aplicó la metodología diseñada en la Universidad de Ciencias Médicas de Matanzas, para monitorear el impacto en la formación de la especialidad de Medicina Intensiva y Emergencias, desarrollado en el Hospital Universitario Comandante Faustino Pérez Hernández. Participaron 6 egresados, 11 profesores, 8 tutores y 4 directivos de la última edición concluida (octubre de 2016 a noviembre de 2019). Resultados: se observó un alto impacto en la institución y mediano en el individuo, con contraste entre el diagnóstico inicial y durante la formación: de excelencia en el 100 % de los residentes, pero un diagnóstico final con 33,3 % excelente y 66,6 % bien. No se evaluó la etapa de transferencia o impacto en la sociedad, por el corto de tiempo de experiencia laboral de los egresados. Conclusiones:la metodología aplicada permitió conocer un mediano impacto en la formación de los egresados de Medicina Intensiva y Emergencias, por contrastación entre el diagnóstico inicial y durante la formación, de excelente con un diagnóstico final de bien (AU).

Introduction: the evaluation of the quality in the formation of the medical specialties in Cuba, conceptualize the monitored of the impact like the process directed to evaluate the correspondence among the objectives of the program and the results reached by their participants in the social environment where they are developed professionally, guaranteeing the relevancy of the program. Objective: to apply the methodology designed for the monitored of the impact in the formation of the medical specialties in the program of intensive Medicine and emergencies. Materials and methods: carried out a study of pedagogic court where the methodology was applied designed in the Medical University of Matanzas, for the monitored of the impact in the formation of the specialty of intensive Medicine and emergencies, developed in the university hospital "Faustino Pérez Hernández." They participated six graduate, four directives, 11 professors and tutors of the last concluded edition, from October of the 2016 to November of the one 2019. Results: a high impact was observed in the institution and medium in the individual, with a contrast among the initial diagnosis and during for formation of excellence in 100% of the residents, with a final diagnosis of 33,3% excellent and 66,6% well. It was not evaluated the transfer stage or impact in the society, for the short of time of labor experience of the graduate. Conclusions: the applied methodology allowed to know the medium impact in the formation of graduate in Intensive Medicine and Emergencies in Matanzas, for a contrast among the initial diagnosis and during the formation of excellent with the final diagnosis of well (AU).

Experiencia sobre monitoreo del impacto en la formación de dermatólogos en la Universidad Médica matancera / Experience on monitoring the impact in dermatologists training in the Medical University of Matanzas

RESUMEN Introducción: la evaluación y acreditación de la calidad en la formación conceptualiza el monitoreo del impacto como el proceso dirigido a evaluar la correspondencia entre los objetivos del programa y los resultados alcanzados por los participantes en el entorno social concreto, con el propósito de valorar el proceso formativo y propiciar la necesaria retroalimentación para elevar su pertinencia social. Objetivo: aplicar la metodología diseñada para el monitoreo del impacto de la formación para las especialidades médicas en el Programa de la Especialidad de Dermatología. Materiales y método: el estudio se desarrolló tomando como referente la metodología diseñada para las especialidades médicas en la Universidad de Ciencias Médicas de Matanzas, teniendo en cuenta los resultados obtenidos en las autoevaluaciones para el proceso de formación de especialistas en dicha especialidad, el cual se desarrolló en la institución objeto de estudio y abarcó el período comprendido de septiembre del 2014 a junio del 2019. Resultados: la metodología empleada arrojó un balance satisfactorio a partir de cada una de sus categorías, predominando el rango de alta y media en el proceso formativo. Se obtuvo el 60,2% en la categoría alta al concluir la formación y es de destacar que no se obtiene categoría baja, es decir, según la clasificación en el rango mínimo de 70 a 79 puntos. Conclusión: el estudio denotó la necesidad y pertinencia de la metodología aplicada, lo que permitió conocer impactos fundamentales del proceso de formación de especialistas en Dermatología e identificar oportunidades de mejora (AU).

SUMMARY Introduction: the quality evaluation and accreditation in training conceptualizes the impact monitoring as the process aimed to evaluate the correspondence between the objectives of the program and the results achieved by the participants in the concrete social environment, with the purpose of assessing the training process and propitiating the necessary feedback to increase its social pertinence. Objective: to apply the methodology designed for monitoring the impact of training for medical specialties on the Program of the Specialty Dermatology. Materials and methods: the study was developed taking as referent the methodology designed for medical specialties in the University of Medical Sciences of Matanzas and taking into account the results of the auto-evaluations for the process of specialists´ training in those specialties, that was developed in the studied institution in the period from September 2014 to June 2019, Results: the used methodology revealed a satisfactory balance from each of the categories, predominating High and Medium range in the training process. 60.2 % got the High category at the end of the training, and it is to be highlighted that Low category was not found. Conclusions: the study showed the necessity and pertinence of the applied methodology, allowing to know the main impacts of the training process of specialists in Dermatology and to identify improvement opportunities (AU).

An Improved Impact Source Locating System Using FBG Rosette Array.

For structures vulnerable to foreign object impact damages, it would be desirable to detect and locate any occurrence of such impacts. This can be achieved by monitoring the stress waves generated by an impact together with certain source localization algorithms. Being small, electromagnetic influence immune and durable, Fiber Bragg grating (FBG) sensors are advantageous for this task. One drawback of FBGs for this purpose is their uneven directional sensitivity, which limits its localization ability to within 50° on either side of the fiber axis. Beyond this range, the signal is too weak and masked by noises and the location errors increase abruptly. Two approaches have been tested on a 0.8 m × 0.8 m × 6 mm plate for possible improvement on the system accuracy: firstly, an interrogation scheme with stronger light source intensity and steeper edge filter is employed to enhance the signal-to-noise ratio and system sensitivity; secondly, rosettes with two orthogonal FBGs are cascaded together to replace single FBGs to alleviate the directional sensitivity problem. It was found that a four-fold increase in signal to noise ratio contributed by stronger light source does improve the location accuracy, but only marginally. For the rosette approach, the relative positions of the Bragg wavelength of the FBGs and the light source spectrum are crucial to accuracy. Three different wavelength configurations have been tested and the reasons for their success or failure are discussed. It was shown that with an optimal wavelength configuration, the rosette array can virtually extend the good location accuracy to all over the plate.

Sensor Distribution Optimization for Structural Impact Monitoring Based on NSGA-II and Wavelet Decomposition.

Optimal sensor placement is a significant task for structural health monitoring (SHM). In this paper, an SHM system is designed which can recognize the different impact location and impact degree in the composite plate. Firstly, the finite element method is used to simulate the impact, extracting numerical signals of the structure, and the wavelet decomposition is used to extract the band energy. Meanwhile, principal component analysis (PCA) is used to reduce the dimensions of the vibration signal. Following this, the non-dominated sorting genetic algorithm (NSGA-II) is used to optimize the placement of sensors. Finally, the experimental system is established, and the Product-based Neural Network is used to recognize different impact categories. Three sets of experiments are carried out to verify the optimal results. When three sensors are applied, the average accuracy of the impact recognition is 59.14%; when the number of sensors is four, the average accuracy of impact recognition is 76.95%.

Impact Monitoring for Aircraft Smart Composite Skins Based on a Lightweight Sensor Network and Characteristic Digital Sequences.

Due to the growing use of composite materials in aircraft structures, Aircraft Smart Composite Skins (ASCSs) which have the capability of impact monitoring for large-scale composite structures need to be developed. However, the impact of an aircraft composite structure is a random transient event that needs to be monitored on-line continuously. Therefore, the sensor network of an ASCS and the corresponding impact monitoring system which needs to be installed on the aircraft as an on-board device must meet the requirements of light weight, low power consumption and high reliability. To achieve this point, an Impact Region Monitor (IRM) based on piezoelectric sensors and guided wave has been proposed and developed. It converts the impact response signals output from piezoelectric sensors into Characteristic Digital Sequences (CDSs), and then uses a simple but efficient impact region localization algorithm to achieve impact monitoring with light weight and low power consumption. However, due to the large number of sensors of ASCS, the realization of lightweight sensor network is still a key problem to realize an applicable ASCS for on-line and continuous impact monitoring. In this paper, three kinds of lightweight piezoelectric sensor networks including continuous series sensor network, continuous parallel sensor network and continuous heterogeneous sensor network are proposed. They can greatly reduce the lead wires of the piezoelectric sensors of ASCS and they can also greatly reduce the monitoring channels of the IRM. Furthermore, the impact region localization methods, which are based on the CDSs and the lightweight sensor networks, are proposed as well so that the lightweight sensor networks can be applied to on-line and continuous impact monitoring of ASCS with a large number of piezoelectric sensors. The lightweight piezoelectric sensor networks and the corresponding impact region localization methods are validated on the composite wing box of an unmanned aerial vehicle. The accuracy rate of impact region localization is higher than 92%.

[Implementation and application of the new information system of air pollution and health impact monitoring].

OBJECTIVE: To establish a new information system of air pollution and health effects surveillance including of data collection, data management, data quality control and statistics and visual display. METHODS: To integrate the limits of authority, process management, quality control into the whole process of data collecting, data processing, data auditing and statistics through B/S framework according to the design concept of separating the professional applications from permissions management, and the data centralized management. RESULTS: The key functions of the information system including data collection, three level auditing, statistics, visual display and system management have been implemented. The system has been applied in the national project of 31 provinces, 65 cities and 126 monitoring points. Up to now there is more than 16 million business records stored in the system and the amount of the data has reached more than 10 G. CONCLUSION: The new information system has run well since it is online. It has not only met the monitoring requirements but also provided the foundational support for the research and policy making.

Laboratory Evaluation of the gForce Tracker™, a Head Impact Kinematic Measuring Device for Use in Football Helmets.

This study sought to compare a new head impact-monitoring device, which is not limited to specific helmet styles, against reference accelerometer measurements. Laboratory controlled impacts were delivered using a linear pneumatic impactor to a Hybrid III headform (HIII) fitted with a football helmet and the impact monitoring device (gForce Tracker-GFT) affixed to the inside of the helmet. Linear regression analyses and absolute mean percent error (MAPE) were used to compare the head impact kinematics measured by the GFT to a reference accelerometer located at the HIII's center of mass. The coefficients of determination were strong for the peak linear acceleration, peak rotational velocity, and HIC15 across all impact testing locations (r(2) = 0.82, 0.94, and 0.70, respectively), but there were large MAPE for the peak linear acceleration and HIC15 (MAPE = 49 ± 21% and 108 ± 58%). The raw GFT was accurate at measuring the peak rotational velocity at the center of mass of the HIII (MAPE = 9%). Results from the impact testing were used to develop a correction algorithm. The coefficients of determination for all impact parameters improved using the correction algorithm for the GFT (r(2) > 0.97), and the MAPE were less than 14%. The GFT appears to be a suitable impact-monitoring device that is not limited to specific styles of football helmets, however, correction algorithms will need to be developed for each helmet style.

Challenge of Using Passive Acoustic Monitoring in High-Energy Environments: UK Tidal Environments and Other Case Studies.

The use of passive acoustic monitoring (PAM) around marine developments is commonplace. A buffer-based PAM system (e.g., C-POD) is a cost-effective method for assessing cetacean acoustic presence. Devices have been deployed by Sea Mammal Research Unit (SMRU) Marine around the United Kingdom, allowing an examination of the performance of C-PODs with respect to background noise, tilt angle, and environmental factors. C-PODs were found to often only monitor for a few seconds of each minute, resulting in significant loss of monitoring time. Issues were likely driven by environmental and deployment factors. The practical limitations of buffer-based PAM systems in high-energy/noisy environments are indicated here.

Review of Offshore Wind Farm Impact Monitoring and Mitigation with Regard to Marine Mammals.

Monitoring and mitigation reports from 19 UK and 9 other European Union (EU) offshore wind farm (OWF) developments were reviewed, providing a synthesis of the evidence associated with the observed environmental impact on marine mammals. UK licensing conditions were largely concerned with mitigation measures reducing the risk of physical and auditory injury from pile driving. At the other EU sites, impact monitoring was conducted along with mitigation measures. Noise-mitigation measures were developed and tested in UK and German waters in German government-financed projects. We highlight some of the review's findings and lessons learned with regard to noise impact on marine mammals.

Real-Time Impact Visualization Inspection of Aerospace Composite Structures with Distributed Sensors.

For the future design of smart aerospace structures, the development and application of a reliable, real-time and automatic monitoring and diagnostic technique is essential. Thus, with distributed sensor networks, a real-time automatic structural health monitoring (SHM) technique is designed and investigated to monitor and predict the locations and force magnitudes of unforeseen foreign impacts on composite structures and to estimate in real time mode the structural state when impacts occur. The proposed smart impact visualization inspection (IVI) technique mainly consists of five functional modules, which are the signal data preprocessing (SDP), the forward model generator (FMG), the impact positioning calculator (IPC), the inverse model operator (IMO) and structural state estimator (SSE). With regard to the verification of the practicality of the proposed IVI technique, various structure configurations are considered, which are a normal CFRP panel and another CFRP panel with "orange peel" surfaces and a cutout hole. Additionally, since robustness against several background disturbances is also an essential criterion for practical engineering demands, investigations and experimental tests are carried out under random vibration interfering noise (RVIN) conditions. The accuracy of the predictions for unknown impact events on composite structures using the IVI technique is validated under various structure configurations and under changing environmental conditions. The evaluated errors all fall well within a satisfactory limit range. Furthermore, it is concluded that the IVI technique is applicable for impact monitoring, diagnosis and assessment of aerospace composite structures in complex practical engineering environments.