Alarm Processing Research Articles

A Framework for Analyzing Residential Fire Outcomes in Homes with Operative Smoke Alarms

Operative smoke alarms have been shown to be effective in reducing home-fire fatalities, but there remain incidents in which injuries and death occur despite the presence of a working smoke alarm. The present work presents a scientifically-guided framework for evaluating the outcomes of such incidents from the perspective of human factors and, specifically, the warnings communication process. It considers the roles of environmental, individual, and situational factors in occupants’ detection, noticing, and processing of smoke alarms, as well as the behaviors produced in response. Such factors include the acoustic environment in which the alarm sounds, the occupants’ cognitive state and focus of attention, the occupants’ developmental and physical abilities, and the situational circumstances in which a response is chosen and executed. The synthesis of these findings provides one methodology for understanding real-world outcomes of fires, as well as informing development and evaluation of countermeasures for improving residential fire fatality rates.

Efficiency of bond graph and external model integration for alarm processing of a central air conditioning system

<p><span>The design of a supervision system based on the external model by structuring the industrial process according to several modes of operation (degraded and normal). The disadvantage of this model is that it describes the industrial process components as functions regardless of their dynamics without going into detail. Hence the interest of the bond graph model to fill the external model limits. The performance of the proposed supervisory system using both models lies in the detection and location of faults for each mode of operation. The bond graph model enriched by the concept of causality and thanks to these structural properties can clearly display the elements of the physical system taking into account their dynamics in normal and abnormal operation. The results of our research have been applied to central air conditioning system; the development of the proposed project has proceeded from the modeling stage to the reconfiguration stage of the system.</span></p>

A microgrid alarm processing method based on equipment fault prediction and improved support vector machine learning

Microgrids are important parts of modern strong intelligent power system. In recent years, new energy sources have developed rapidly in China, and research on microgrid technologies is in the ascendant. The typical microgrid has obvious advantages such as flexible network structure and small circuit loss. With its increasing scale and increasing application in the power system, it needs to be dealt with the complex operation mode. In order to achieve efficient operation and management, microgrid control still needs to be equipped with energy management system (EMS). One of the main problems that EMS needs to solve is the generation of massive alarm information within a short period of time after equipment failure. To this end, this paper proposes a microgrid alarm processing method based on equipment fault prediction and improved support vector machine learning. Based on historical operation risk and health state evaluation, the equipment fault prediction is carried out. Then we optimize and select kernel function for machine learning and have an improved SVM model. With this model, fault equipment sets are classified and verified so we can get the accurate source alarm and fault equipment. Finally, the validity and accuracy of this method are verified by a simple example.

Social capital, trust and social activity among librarians: Results of research conducted in 20 countries across the world

Libraries may stimulate social capital and social integration. They are institutions that enjoy a high level of social trust, which creates many opportunities. In 2018 and 2019, a survey on social capital, trust and social activity of librarians was conducted in 20 countries across the world. The research addresses the question of whether libraries as public institutions may prevent the alarming processes of social alienation of individuals. The findings show that librarians have an average level of individual social capital, but they have a relatively high level of trust in other people and often volunteer for their communities. Nonetheless, librarians tend to not believe in their own impact on the rest of the society/local community. Of most importance for them in their lives are emotional values, attachment and family values; they are less focused on material values, image, etc.

Analysis and supervision of a smart grid system with a systemic tool

Smart grids studies focus on improving their reliability and reducing the cost of energy, particularly when they are operated offshore. Smart grids Supervisory Control and Data Acquisition (SCADA) systems contain alarm signals providing significant important information. Pattern recognition embodies a set of promising techniques for intelligently processing smart grid SCADA alarms. This paper presents the feasibility study of SCADA alarm processing and description of the functional and operational control-command applications method SA-RT (Structured Analysis Real Time) is presented. The purpose of this article is to propose a general methodology of analysis and supervision of control-command applications based on the SA-RT method as well as the SCADA system

Simulation investigation on the smoke spread process in the large-space building with various height

In this paper, the fire growth and smoke spread process in Large-space building have been investigated through the Fire Dynamics Simulator (FDS). What's more, the alarm process of the Line-type Infra-red Beam Smoke Fire Detector (LSD) and the Aspirating Smoke Detection System (ASD) have discussed, some valuable results have been obtained. The results indicated that the raise of the difference between the two height, and the smoke spread process is becoming slower at the constant heat release rate. The set of fire alarm system in large-space should be consider the “height advantage”, as the higher set of the smoke decent responding earlier than the lower ones. What's more, referring to the ASD system the aspirator samplers close to the building's edge should be affected by the edge. For the LSD system should determine the parameter of install by the numerical or experimental test to optimizing the performance of the LSD, which has been proposed in the paper. In summary, the research investigates the basic fire alarm process for the LSD and the ASD System in the large-space buildings, and these are valuable for the selecting and setting of fire alarm system in the large-space buildings.

Signal Processing and Target Fusion Detection via Dual Platform Radar Cooperative Illumination

A modified signal processing and target fusion detection method based on the dual platform cooperative detection model is proposed in this paper. In this model, a single transmitter and dual receiver radar system is adopted, which can form a single radar and bistatic radar system, respectively. Clutter suppression is achieved by an adaptive moving target indicator (AMTI). By combining the AMTI technology and the traditional radar signal processing technology (i.e., pulse compression and coherent accumulation processing), the SNR is improved, and false targets generated by direct wave are suppressed. The decision matrix is obtained by cell averaging constant false alarm (CA-CFAR) and order statistics constant false alarm (OS-CFAR) processing. Then, the echo signals processed in the two receivers are fused by the AND-like fusion rule and OR-like fusion rule, and the detection probability after fusion detection in different cases is analyzed. Finally, the performance of the proposed method is quantitatively analyzed. Experimental results based on simulated data demonstrate that: (1) The bistatic radar system with a split transceiver has a larger detection distance than the single radar system, but the influence of clutter is greater; (2) the direct wave can be eliminated effectively, and no false target can be formed after suppression; (3) the detection probability of the bistatic radar system with split transceivers is higher than that of the single radar system; and (4) the detection probability of signal fusion detection based on two receivers is higher than that of the bistatic radar system and single radar system.

Research on Intelligent Diagnosis Technology of Emergency Diesel Generator in Nuclear Power Plant Based on New Monitoring Method

As the emergency power source of nuclear power plant, the emergency diesel generator sets need to provide power for the safety system of nuclear power plant after all external power sources of nuclear power plant are lost, to ensure the safe shutdown of nuclear power plant and prevent the leakage of radioactive materials to the environment. In view of the critical role of emergency diesel generator sets in ensuring the safe operation of the power station, high reliability is needed. Therefore, how to accurately monitor the state of diesel engine and how to diagnose the faults has become an urgent problem to be solved. In this paper, status monitoring system for diesel engine is designed and developed based on LabVIEW and new monitoring method to realize real-time and continuous collection during the operation of the diesel engine, intensive collection during the alarm process, and data display and storage. It can provide data support for fault diagnosis. The operation results show that the system has high reliability and meets the requirements of field inspection, regular test and fault analysis.

Application Research of Artificial Intelligence Technology in Power System Alarm Processing Method

The paper first introduces the principles of artificial intelligence and expert systems, and makes a detailed analysis of the application of expert systems in power systems. Secondly, the paper uses VC++ language to establish an expert system for judging power system fault areas and fault types. The system can identify power system bus faults, line faults, circuit breakers and relay malfunctions and refusal faults. Finally, the system simulation test shows that the fault diagnosis expert system established in this paper has certain theoretical and practical significance.

Intelligent Health Nursing System Based on Cloud Platform

The health of the elderly is mainly disturbed by chronic diseases. As the proportion of older persons living alone is increasing, the health problems of elderly have received extensive attention. Now the rapid development of sensor technology and network technology provide a technical guarantee for the realization of real-time health nursing. The existing intelligent nursing system does not reuse nursing data after judging the user’s health status and choosing alarm processing. This paper proposes a new intelligent health nursing system architecture, which integrates sensor network and wireless communication network, and uses FPGA cloud Platform to complete data storage and processing, which can effectively avoid the loss of function limited by the power consumption and computational performance of the user’s device. In addition, through the deep learning algorithm, the accuracy of abnormal nursing can be effectively improved as well.

Deforestation, cattle capitalism and neodevelopmentalism in the Chico Mendes Extractive Reserve, Brazil

ABSTRACTThe recent upsurge of deforestation inside conservation areas requires empirical investigation of the causes and consequences of this alarming process. Local relations between the agents of cattle capitalism, neodevelopmentalism and contemporary deforestation, from politicians and ranchers to the traditional extractive populations of multiple-use conservation areas, are assessed. Whether, when, and how state, market, and cultural institutions support the hegemony of cattle capitalism – and subvert the logic of traditional lived environments – are analyzed. Theoretically, the article shows how moral economic transformations, from rubber tapping to cowboy lifestyles, alongside neodevelopmentalist policies, enable regionally dominant political economies to expand through deforestation.

New Presentation Method of Human-Machine-Interfaces for EMS

Power demand is constant increasing, so power networks are push to the operation limits. Traditional presentation of SCADA/EMS HMI(Human-Machine-Interface) is not more suitable to this situation. Various technology such as AI base alarming, dynamic coloring, contour, map based diagrams, new presentation methods are purposed. New method for indication and measurement alarm processing, measurement presentation, topology presentation, risk assessment presentation, KPI presentation, map based presentation are implemented. Through these presentation techniques, the operators can comprehend the system information easily and more accurate, then more proper action can be promptly taken to ensure the power networks operate more safely and more economically.

Algorithm of reducing the false positives in IDS based on correlation Analysis

This paper proposes an algorithm of reducing the false positives in IDS based on correlation Analysis. Firstly, the algorithm analyzes the distinguishing characteristics of false positives and real alarms, and preliminary screen the false positives; then use the method of attribute similarity clustering to the alarms and further reduces the amount of alarms; finally, according to the characteristics of multi-step attack, associated it by the causal relationship. The paper also proposed a reverse causation algorithm based on the attack association method proposed by the predecessors, turning alarm information into a complete attack path. Experiments show that the algorithm simplifies the number of alarms, improve the efficiency of alarm processing, and contribute to attack purposes identification and alarm accuracy improvement.

Fast alarm processing without connectivity information

This study introduces an alarm processing without using any connectivity information of the substation electrical network. In order to do so, timestamp and location readily defines specific alarm patterns. In this sense, the proposed algorithm resembles the typical procedure that operators do. This specialised alarm processing allows fast recognition of the most important events in a substation: typically, more than 70% of the alarms belong to the three groups presented in this study. Tests in a notebook show that it is possible to process 1025 alarms/s with a state machine that model the specialist behaviour of each group, while a typical maximum density is 1000 alarms/min.

Analysis and countermeasures of various alarm in hemodialysis

Objective To explore how to reduce and quickly deal with all kinds of alarm in the dialysis process, to ensure the safety of dialysis, improve the coping ability of nurses, improve the quality of nursing and the satisfaction of patients. Methods Various kinds of alarm and nurse processing time in hemopurification center of our hospital from 2013 to 2014 were recorded and analyzed, the emergency treatment measures were found out, the coping methods were developed, the coping process were improved, and the training of nurses was strengthened. The various parameters were rerecorded and compared after training (2015 to 2016). Results The most common alarm in dialysis process was venous pressure alarm, accounting for 16.45%(15 925/96 831) of the total alarm, the lowest limit was 10.34% (10 020/96 831), and the highest limit was 6.11% (5 905/96 831). The total conductivity alarm was 10.33% (9 969/968 310), the nurse′s alarm processing time of the lowest limit was (53.11±12.84) s, the highest limit was (136.77±42.88) s, the conductivity alarm was (54.17±33.55) s. After the training of nurses, the alarm frequency was reduced (χ2=3.164, P<0.05), the venous pressure alarm accounts for 14.69% (15 415/104 913) of the total alarm, the lowest limit was 9.52% (9 985/104 913),and the highest limit was 5.18% (5 430/104 913) , the total conductivity alarm was 7.54% (7 913/104 913). The alarm processing time was shortened: the lowest limit was (40.94±10.38) s, the highest limit was (119.15±38.79) s (t=3.944, 3.304, P<0.05). The work efficiency and patient satisfaction degree were improved. Conclusions Through the summary and training of all kinds of alarm in the dialysis process, it can effectively reduce the alarm frequency of the dialysis process, improve the work efficiency of nurses, and improve the satisfaction degree of patients. Key words: Alarm; Reason; Analysis; Countermeasure; Hemodialysis

Real Time Alarm Processing for Predictive Failure Diagnosis in Petrochemical Plants

In this paper it is proposed a methodology for real time processing of alarms as a way to point out possible abnormal operating condition predictively. The proposed methodology consists of a knowledge base regarding critical scenarios. The critical scenarios are modeled by rules with expected alarm sequences for each deviation process. Each monitored scenario is assigned an occurrence index, which measures how close these scenarios are from happening. Finally, the system ranks the most probable critical scenario based on the similarity index with the expected scenario. In order to validate the proposal, a study was carried out using a simulated case in typical oil refining industrial plant.

GMTI for Squint Looking XTI-SAR with Rotatable Forward-Looking Array.

To realize ground moving target indication (GMTI) for a forward-looking array, we propose a novel synthetic aperture radar (SAR) system, called rotatable cross-track interferometry SAR (Ro-XTI-SAR), for squint-looking application in this paper. By changing the angle of the cross-track baseline, the interferometry phase component of squint-looking Ro-XTI-SAR caused by the terrain height can be approximately adjusted to zero, and then the interferometry phase of Ro-XTI-SAR is only sensitive to targets’ motion and can be equivalent to the along track interferometry SAR (ATI-SAR). Furthermore, the conventional displaced phase center array (DPCA) method and constant false alarm (CFAR) processing can be used to accomplish the successive clutter suppression, moving targets detection and relocation. Furthermore, the clutter suppressing performance is discussed with respect to different system parameters. Finally, some results of numerical experiments are provided to demonstrate the effectiveness of the proposed system.

Development and Application of Measurement and Control Systems in Coal Mines

The paper presents an analysis of the process of application of measurement and control systems in underground coal mines in Serbia. Particular attention is paid to the experience with the first systems introduced in the mines ‘Soko’ and ‘Aleksinacki Rudnici’. A significant part of the paper is devoted to the description of the process of the development and improvement of systems, described by three aspects (technical, exploitation and commercial/financial). The technical aspect is described by seven criteria (imported systems, basic technical knowledge, input/output properties, real-time functions, offline processing, alarm processing and presentation and education) and 18 indicators. The exploitation aspect is described by six criteria (system design, reliability and accuracy, data presentation, alarm processing, use of information, and operation and maintenance) and 21 indicators. The commercial and financial aspects are described by financial indicators that show the positive effects of domestic development of the system.

Road Network-Aware Spatial Alarms

Road network-aware spatial alarms extend the concept of time-based alarms to spatial dimension and remind us when we travel on spatially constrained road networks and enter some predefined locations of interest in the future. This paper argues that road network-aware spatial alarms need to be processed by taking into account spatial constraints on road networks and mobility patterns of mobile subscribers. We show that the Euclidian distance-based spatial alarm processing techniques tend to incur high client energy consumption due to unnecessarily frequent client wakeups. We design and develop a road network-aware spatial alarm processing system, called RoadAlarm , with three unique features. First, we introduce the concept of road network-based spatial alarms using road network distance measures. Instead of using a rectangular region, a road network-aware spatial alarm is a star-like subgraph with an alarm target as the center of the star and border points as the scope of the alarm region. Second, we describe a baseline approach for spatial alarm processing by exploiting two types of filters. We use subscription filter and Euclidean lower bound filter to reduce the amount of shortest path computations required in both computing alarm hibernation time and performing alarm checks at the server. Last but not the least, we develop a suite of optimization techniques using motion-aware filters, which enable us to further increase the hibernation time of mobile clients and reduce the frequency of wakeups and alarm checks, while ensuring high accuracy of spatial alarm processing. Our experimental results show that the road network-aware spatial alarm processing significantly outperforms existing Euclidean space-based approaches, in terms of both the number of wakeups and the hibernation time at mobile clients and the number of alarm checks at the server.

Idiopathic Interstitial Pneumonias (IIPs): Review of Clinical, Radiographic and High-Resolution Computed Tomography (HRCT)

Making a confident diagnosis is a complex task for a specific form of interstitial lung disease and providing appropriate management in an attempt to achieve normalization of the disease can put up an alarming process for the clinicians. A set of diffuse and restrictive lung diseases incorporate with idiopathic interstitial pneumonias, showing inflammation and fibrosis of the interstitium due to parenchymal damage. High-resolution computed tomography (HRCT) has magnified the diagnostic standpoint in stepwise identification and classified various patterns in the evaluation of interstitial lung disease. The aim of our review is to elaborate clinical, radiographic and typical and atypical HRCT findings of idiopathic interstitial pneumonias by correlating with its differential diagnosis. Idiopathic pulmonary fibrosis is the most predominant idiopathic interstitial pneumonias and its diagnosis needs to omit all other well-known causes of interstitial lung diseases. According to the 2011 evidence-based guidelines, usual interstitial pneumonia can be diagnosed by HRCT when all criteria are fulfilled. Non-specific interstitial pneumonia is distinguished by bilateral patchy ground-glass opacities and irregular linear/reticular opacities. Respiratory bronchiolitis associated-interstitial lung disease and desquamative interstitial pneumonia show centrolobular nodules and ground-glass opacities as imaging patterns. Cryptogenic organizing pneumonia consists of patchy peripheral or peribronchial consolidations, while ground-glass opacities with tendency for migration, which is evolving to fibrosis, in acute interstitial pneumonia. Lymphoid interstitial pneumonia and idiopathic pleuro-parenchymal fibroelastosis are classified under rare idiopathic interstitial pneumonias. HRCT images help radiologists in diagnosis and mapping specific patterns of idiopathic interstitial pneumonias. This article reviews the stages of evolution in HRCT features for idiopathic interstitial pneumonias.