A Novel Method for Intelligent Single Fault Detection of Bearings Using SAE and Improved D–S Evidence Theory

In order to realize single fault detection (SFD) from the multi-fault coupling bearing data and further research on the multi-fault situation of bearings, this paper proposes a method based on features self-extraction of a Sparse Auto-Encoder (SAE) and results fusion of improved Dempster–Shafer evidence theory (D–S). Multi-fault signal compression features of bearings were extracted by SAE on multiple vibration sensors’ data. Data sets were constructed by the extracted compression features to train the Support Vector Machine (SVM) according to the rule of single fault detection (R-SFD) this paper proposed. Fault detection results were obtained by the improved D–S evidence theory, which was implemented via correcting the 0 factor in the Basic Probability Assignment (BPA) and modifying the evidence weight by Pearson Correlation Coefficient (PCC). Extensive evaluations of the proposed method on the experiment platform datasets showed that the proposed method could realize single fault detection from multi-fault bearings. Fault detection accuracy increases as the output feature dimension of SAE increases; when the feature dimension reached 200, the average detection accuracy of the three sensors for bearing inner, outer, and ball faults achieved 87.36%, 87.86% and 84.46%, respectively. The three types’ fault detection accuracy—reached to 99.12%, 99.33% and 98.46% by the improved Dempster–Shafer evidence theory (IDS) to fuse the sensors’ results—is respectively 0.38%, 2.06% and 0.76% higher than the traditional D–S evidence theory. That indicated the effectiveness of improving the D–S evidence theory by evidence weight calculation of PCC

Spatiotemporal patterns and driving mechanism of tourism ecological security in Guangxi, China

Tourism ecological security (TES) is an important index reflecting the sustainable development of the regional economy. The construction of the China and ASEAN Free Trade Area has increased the total tourist consumption of Guangxi province by 36.48%. Unfortunately, overconsumption of resources, air pollution, disturbance of indigenous life, and other environmental degradation problems emerged due to the significant increase in tourists. Measuring the resilience of the tourism ecosystem is an urgent need to promote the high-quality development of tourism in Guangxi. To explore the dynamic changes in TES and its driving mechanism, the DPSIR (driver–pressure–state–impact–response) model for the tourism ecosystem was developed. The dynamic changes in TES and its driving mechanism from 2010 to 2019 were analyzed using fuzzy matter-element analysis, Markov chains, Geodetector, and other methods. The results show that: (1) the TES value increased steadily by 72.73%; the improvement speed was Northeast > Southwest > Southeast > Northwest; (2) TES was negatively correlated with location, 14 cities developed independently; (3) the TES has a smaller probability to shift the lower level; (4) urbanization, water consumption, green area, tourism revenue, and the number of students in colleges had significant effects on TES. Four policies were proposed to improve TES: (1) developing forest tourism; (2) implementing greening projects in abandoned mining areas; (3) increasing tourism technical personnel; and (4) reducing clearance time for inbound tourists

Technologies for safe and resilient earthmoving operations: A systematic literature review

Resilience engineering relates to the ability of a system to anticipate, prepare, and respond to predicted and unpredicted disruptions. It necessitates the use of monitoring and object detection technologies to ensure system safety in excavation systems. Given the increased investment and speed of improvement in technologies, it is necessary to review the types of technology available and how they contribute to excavation system safety. A systematic literature review was conducted which identified and classified the existing monitoring and object detection technologies, and introduced essential enablers for reliable and effective monitoring and object detection systems including: 1) the application of multisensory and data fusion approaches, and 2) system-level application of technologies. This study also identified the developed functionalities for accident anticipation, prevention and response to safety hazards during excavation, as well as those that facilitate learning in the system. The existing research gaps and future direction of research have been discussed

Percepción social del riesgo ambiental sobre la salud en áreas degradadas por la minería metálica : el caso del El Llano del Beal, (t.m. de Cartagena) en el sureste de la Península Ibérica

La Sierra Minera de La Unión-Cartagena, ubicada en la Región de Murcia, en el sureste de la Península Ibérica, ha sido una zona con gran actividad y desarrollo socio-económico estrechamente vinculado a actividades minero-metalúrgicas. La paralización de la minería, a comienzos de la década de los años 90 del siglo XX, ha dejado tras de sí un territorio cercado de Pasivos Ambientales Mineros (PAM). Estamos ante un conflicto socio-ecológico donde se han desarrollado numerosas crisis territoriales, socio-ambientales, político-administrativas y, en los últimos tiempos, sobre la salud, donde el problema principal de los PAM sigue sin ser resuelto. En esta investigación nos centramos en todo el proceso social surgido a partir de la revelación, para la opinión pública, de los posibles peligros sobre la salud, por la presencia de estos residuos mineros que rodean el núcleo de población de El Llano del Beal, ubicado en la Diputación del Beal, en el término municipal de Cartagena, atendiendo a los daños sobre la salud de las personas, derivados de la exposición a metales pesados y de transición, presentes en esos residuos mineros. Ha sido desarrollado un modelo para interpretar la Percepción Social del Riesgo Ambiental Sobre la Salud (PSRAS) adaptado al medio social de la comunidad vecinal de El Llano del Beal, uno de los pueblos más afectado por las actividades minero-metalúrgicas en esta Sierra Minera. Entre los años 2017 y 2018 se han realizado entrevistas semi-estructuradas en 235 viviendas en El Llano del Beal. Además, se ha entrevistado a los principales actores sociales de la comunidad vecinal, expertos científicos y dirigentes político-administrativos. También se llevaron a cabo dos grupos de discusión en el año 2022. La información obtenida fue analizada mediante un enfoque mixto, utilizando métodos cuantitativos y cualitativos. Los principales resultados de la investigación muestran cómo se estructura la Percepción Social del Riesgo Ambiental Sobre la Salud en base a las dimensiones establecidas. Se profundiza en aquellos elementos determinantes para que los riesgos de la minería sean o no percibidos por los sujetos. Las principales conclusiones destacan la necesidad de mejorar y capacitar a las poblaciones expuestas a los PAM para minimizar los posibles daños en la salud y mejorar las estrategias de información desde las administraciones competentes, para la adaptación de los sujetos al particular medio socio-ambiental.The Sierra Minera de La Unión-Cartagena, located in the Region of Murcia, in the southeast of the Iberian Peninsula, has been an area of great activity and socio-economic development closely linked to mining and metallurgical activities. The stoppage of mining in the early 1990s has left behind a territory surrounded by Mining Environmental Liabilities (MAP). We are facing a socio-ecological conflict in which numerous territorial, socio-environmental, political-administrative and, in recent times, health crises have developed, where the main problem of the MAPs remains unresolved. In this research we focus on the whole social process that has arisen from the revelation, to public opinion, of the possible dangers to health, due to the presence of these mining wastes that surround the population centre of El Llano del Beal, located in the Diputación del Beal, in the municipality of Cartagena, taking into account the damage to people's health, derived from the exposure to heavy and transition metals, present in these mining wastes. A model has been developed to interpret the Social Perception of Environmental Health Risk (PSRAS) adapted to the social environment of the neighbouring community of El Llano del Beal, one of the villages most affected by mining and metallurgical activities in the Sierra Minera. Between 2017 and 2018, semi-structured interviews were conducted in 235 households in El Llano del Beal. In addition, the main social actors of the neighbourhood community, scientific experts and political-administrative leaders were interviewed. Two focus groups were also carried out in 2022. The information obtained was analysed through a mixed approach, using quantitative and qualitative methods. The main results of the research show how the Social Perception of Environmental Health Risk is structured on the basis of the established dimensions. It explores in depth those elements that determine whether or not the risks of mining are perceived by the subjects. The main conclusions highlight the need to improve and train the populations exposed to MAPs in order to minimise possible damage to health and to improve the information strategies of the competent administrations for the adaptation of the subjects to the particular socio-environmental environment