Preventing collisions involving surface mining equipment: a GPS-based approach

PROBLEM: An average of three workers a year are killed in surface mining operations when a piece of haulage equipment collides with another smaller vehicle or a worker on foot. Another three workers are killed each year when haulage equipment backs over the edge of a dump point or stockpile. Devices to monitor the blind areas of mining equipment are needed to provide a warning to operators when a vehicle, person, or change in terrain is near the equipment. METHOD: A proximity warning system (PWS) based on the global positioning system (GPS) and peer-to-peer communication has been developed to prevent collisions between mining equipment, small vehicles, and stationary structures. RESULTS: A final system was demonstrated using one off-highway haul truck, three smaller vehicles, and various stationary structures at a surface mining operation. The system successfully displayed the location of nearby vehicles and stationary structures and provided visual and audible warnings to the equipment operator when they were within a preset distance. SUMMARY: Many surface mining operations already use GPS technology on their mobile equipment for tracking and dispatch. Our tests have shown that it is feasible to add proximity warning to these existing systems as a safety feature. Larger scale and long-term tests are needed to prove the technology adequately. IMPACT ON INDUSTRY: A PWSs that incorporates a combination of technologies could significantly reduce accidents that involve collisions or driving over an edge at surface mining operations.     

Fault detection and diagnostics of a three-phase separator

A high demand of oil products on daily basis requires oil processing plants to work with maximum efficiency. Oil, water and gas separation in a three-phase separator is one of the first operations that are performed after crude oil is extracted from an oil well. Failure of the components of the separator introduces the potential hazard of flammable materials being released into the environment. This can escalate to a fire or explosion. Such failures can also cause downtime for the oil processing plant since the separation process is essential to oil production. Fault detection and diagnostics techniques used in the oil and gas industry are typically threshold based alarm techniques. Observing the sensor readings solely allows only a late detection of faults on the separator which is a big deficiency of such a technique, since it causes the oil and gas processing plants to shut down.A fault detection and diagnostics methodology for three-phase separators based on Bayesian Belief Networks (BBN) is presented in this paper. The BBN models the propagation of oil, water and gas through the different sections of the separator and the interactions between component failure modes and process variables, such as level or flow monitored by sensors installed on the separator. The paper will report on the results of the study, when the BBNs are used to detect single and multiple failures, using sensor readings from a simulation model. The results indicated that the fault detection and diagnostics model was able to detect inconsistencies in sensor readings and link them to corresponding failure modes when single or multiple failures were present in the separator.     

The need for a systems theory approach to road safety

In other hazardous complex socio-technical systems in society, e.g. nuclear power and aviation, systems-theoretical assumptions are considered a promising way to better understand and manage safety. In this paper, two fundamental approaches to road safety were assessed in the light of a systems theory approach. One approach, is based on a premise where individual road-users are solely responsible when crashes occur. In that case countermeasures are aimed at altering the behavior of the road-user in order to adapt him/her to the road transport system. The other approach, the so-called zero-tolerance position, or Vision Zero approach, to road safety is built around two axioms; the system must be adapted to the psychological and physical conditions and limitations of the human being and the responsibility for road safety must be shared between the road-users and the designers and professional operators of the system. It was found that the most important determinants of systems theory are basically not present in the road-user approach. However, even if the Vision Zero approach clearly takes step towards systems theory, it does leave room for articulating even more features of systems theory.     

A shell-based magnetic field model for magnetic proximity detection systems

Several magnetic proximity detection systems have been developed for mining vehicles and mobile machinery to protect nearby workers. Magnetic field generators are often used in these systems to establish magnetic fields around the equipment. A sensor worn by a worker provides a measurement of the magnetic flux density that is used to estimate the proximity to the machine. The proximity detection systems currently available for underground mining equipment are capable of identifying whether a worker is near the machine. However, it is a challenge for these systems to accurately locate the worker. Mining machines, which have fast-moving, articulated parts, present hazards that change depending on the situation at hand as well as the specific location of the worker. In addition, the dynamic nature and confined spaces of the mining environment often demand that the workers be close to the machinery. Therefore, in many cases, simply knowing the proximity of a worker may be inadequate. To provide the most effective protection, it would be advantageous to know the worker’s exact location relative to specific parts of the machine. To lay the foundation for measuring such a location, we have developed a shell-based model of the magnetic flux density distribution for a ferrite-cored generator. This paper will present an analysis of the model along with a model construction process. Also presented are the laboratory test results of a prototype system that implements this model to determine the exact location of a magnetic sensor using the fields from two generators.     

A socio-technical approach of risk management applied to collisions involving fishing vessels

To make a study of accident and risk management, it is necessary to analyze the socio-technical system in which these accidents occur. The strategies by which the actors involved respond to critical situations can only be understood within their own context, by recognizing the exigencies and constraints of the system in which they operate. According to the chart of migrations and transgressions of professional practices [Amalberti, R., 2001. The paradoxes of almost totally safe transportation systems. Safety Science 37, 109–126], a system, any system, is conceived as responding to the triple pressure of social regulations, available technology and the financial returns of performance. Without curbs or checks, the system would evolve toward an increase in performance and individual profit. Barriers define the boundaries within which operations are considered to be safe.A case-by-case analysis of collisions at sea enabled us to identify two basic causes: undetected signals, and wrong diagnoses. It has also allowed us to define the real operating space of the functional units (fishing vessels) most often involved in collisions, as well as the permeable areas of the safety barriers, through which operations are allowed to migrate toward unsafe zones. As far as the collision risk is concerned, functional units work in a borderline area, close to the limits of safe behavior. To prevent accidents, it will be necessary to reinforce these too-permeable safety barriers, thus limiting the migration factor and bringing the functional units back into an area in which the factors of safety, performance and individual profits are all acceptable.     

基于CNN_LSTM模型的复杂支路故障电弧检测*

在低压交流配电系统中,当多支路并联的复杂系统的某1支路中出现串联电弧故障时,识别难度大幅提升。为了预防此类情况引发的电气火灾,提出1种卷积神经网络(CNN)与长短时记忆网络(LSTM)结合的串联故障电弧检测方法。首先,搭建实验平台用以采集不同负载在不同支路下发生故障时和正常工作时的干路电流数据;然后,构建CNN_LSTM模型并做出相应改进,将电流数据直接输入到模型中,由模型自主提取波形特征并进行分类。研究结果表明:该方法可以快速、准确地识别出电弧故障,准确率达99.04%以上,且能够较为准确地检测出是哪类负载所在的支路发生电弧故障,准确率达97.90%,可为复杂支路下的电弧故障识别研究提供参考。     

ARX modeling approach to leak detection and diagnosis

This work presents a time series strategy for detection, location and quantification of leaks in large pipeline systems. The technology has two active components, which operate sequentially: the Detector and the Localizer. The Detector continuously screens real-time data, searching for any anomalies such as leaks, which are detected (or not) depending on their size and position. The Detector is based on auto-regressive multi-input/multi-output (MIMO) ARX predictors with one input filter. Subsequent to successful leak detection, the Localizer is launched to diagnose the leak via estimation of its parameters – diameter and location – using recorded data on a Search Time Window that includes information in the neighborhood of the instant of detection. The Localizer is also an ARX predictor, but with two input processors, the first is a filter for dynamic plant inputs and the second filter processes “parameter signals” of active leaks. The Localizer is developed beforehand via model identification with plant data under the action of known, artificially simulated, leaks. It is, therefore, able to recognize an active pattern of leak parameters, by maximizing the adherence of its predictions to data in the Search Time Window. The proposed detection and location methods were successfully tested in simulated leak scenarios for an industrial naphtha pipeline.     

Fuzzy AHP approach to selection problems in process engineering involving quantitative and qualitative aspects

Selection problems are common in process engineering. In most cases, it is necessary to rank alternatives based on multiple criteria (e.g., cost, safety, environmental impact), which are often conflicting. In addition, some criteria may be fundamentally difficult to quantify due to data scarcity, in which case subjective assessments need to be used as a proxy. Decision analysis tools such as the analytic hierarchy process (AHP) are useful to ensure decision-making is done rationally. In this work, we propose a fuzzy AHP variant, wherein pairwise comparison of decision elements by domain experts is expressed with triangular fuzzy numbers. This approach allows the degree of confidence of the expert to be quantified explicitly; it also allows inconsistencies in judgment to be reconciled within the bounds of the fuzzy numbers to generate reasonable values for the weighting factors. We demonstrate the methodology on three case studies, involving the comparison of different types of chlor-alkali electrolytic cells, CO₂ capture techniques in cement plants and wastewater treatment options for municipal wastewater.     

Self-ignition tendency of solid fuels: A gas emissions approach for early detection

Self-ignition of solid fuels storage is one of the main causes of human and economic losses. Additionally, each fire caused by this phenomenon emits an amount of toxic gases that contributes on the development of climate change. Nowadays, several methodologies are used in order to detect the self-ignition tendency of solid fuels, but they have as main disadvantages the amount of money and time that they require. The aim of this study is to propose a methodology of detection of incipient self-ignition of solid fuels through the measurement of gas emissions. This study compares existing methodologies to detect self-ignition tendency, such as TG, DSC or susceptibility, and to combustion related gas emission results. Different methods have been used to evaluate the results from the gas emission test, showing that interval and inflexion methods provide early detection of the self-heating process. With this methodology, it is possible to determine this process in advance with the equipment currently available in every industrial facility, reducing costs and improving efficiency.     

On the divergence criterion for runaway detection: Application to complex controlled systems

It is well-known that, for certain values of the operative parameters influencing the dynamic behavior of a chemical reactor, a phenomenon known as thermal runaway (that is, a loss of the reactor temperature control) may arise. Such a situation can be really dangerous because above a certain threshold temperature value unwanted side reactions or, worse, decompositions of the reacting mixture may be triggered evolving high amounts of flammable or toxic gases that can cause reactor pressurization and, eventually, its explosion. For this reason, since the beginning of the previous century a number of studies concerning the prediction of the so called runaway boundaries has been carried out. In this work, a modified version of the divergence criterion for runaway detection, originally developed by Zaldívar and co-workers, is presented. Such a modified divergence criterion is capable of treating whatever type of complex controlled reacting system (taking into account not only temperature control but also dosing strategies) and its reliability has been demonstrated for isoperibolic semibatch reactors using literature experimental data concerning the nitration of 4-Chlorobenzotrifluoride in mixed acids and the nitric acid oxidation of 2-octanol to 2-octanone and further carboxylic acids.     

Bolted flange joints equipped with FBG sensors in industrial piping systems subjected to seismic loads

The vulnerability of major-hazard industrial plants to natural hazards has been recognized as an emergent issue whose importance is underlined by the Sendai Framework, established immediately after the Tohoku earthquake of 2011, in Japan. Hence, seismic risk analysis is of paramount importance as testified by the intense research activity that characterized the last years. In this respect, structural health monitoring can represent a valuable tool able to strongly help the decision-making phase. Along this main vein, optical fibers (OFs) represent a class of sensors able to both monitor critical conditions, as leakage of hazardous material, and activate safety barriers, if any. More precisely, optical fibers represent an economic solution, whose characteristics appear particularly suitable for dangerous environments like major-hazard plants. However, investigations relevant to their use for seismic monitoring of chemical/petrochemical plants are rather limited, especially when subject to strong dynamic excitations. As a result, this paper deals with the analysis of optical fiber Bragg gratings (FBGs) applied to bolted flange joints (BFJ) under cyclic loadings. More precisely, two experimental programs, i.e., a cyclic test on a single BFJ and a series of shaking table tests on BFJs of a multicomponent system, demonstrated the effectiveness of the proposed monitoring systems in detecting hazardous conditions and, thus, their potential use in conjunction with safety barriers.     

强膨胀软岩巷道锚网喷架联合支护技术研究

强膨胀软岩巷道的支护问题是西部地区矿井建设中普遍遇到的难题。为解决强膨胀软岩遇水泥化、崩解等给巷道掘进、支护等工程带来的困难,以强膨胀软岩巷道支护工程为研究对象,通过理论分析和现场调研,研究强膨胀软岩巷道变形机理;利用有限元分析软件MIDAS/GTS建立强膨胀软岩巷道数值仿真模型,分析了锚网喷架联合支护时巷道塑性区范围、表面位移和钢支架的受力特征。进行现场测试,获得了巷道围岩变形和锚杆受力变化规律。结果表明,采用钢支架与锚网喷构成联合支护体系可有效提高支护结构整体刚度,提升围岩的自稳能力和自承能力。     

An entropy-based TOPSIS approach for analyzing and assessing crisis management systems in petrochemical industries

Crisis management systems should be assessed and updated in petrochemical industries due to hazards, such as fire and explosion. Successful crisis management systems can protect both personnel and property in the petrochemical industries. The present study aimed to assess crisis management systems of five petrochemical plants in terms of three aspects, including organizational aspects, human aspects, and technical aspects. A questionnaire was designed, encompassing 34 items to cover all three aspects at both management and staff levels. A multi-criteria decision making (MCDM) approach, including the entropy method and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), was used to analyze the collected data. The outcomes of the entropy method indicated that organizational and human aspects had the greatest influence on crisis management systems of the plants with 58% and 49% importance at management and staff levels, respectively. The crisis management systems of the investigated plants were ranked and analyzed using the TOPSIS approach. The findings of this study could assist managers and other decision-makers to address the issues of crisis management systems in petrochemical industries.     

Fault diagnosis of pipeline and pump unit systems using status coupling analysis

Earlier studies on fault diagnosis of the pipeline and pump unit systems (PPU) relied mainly on independent equipment analyses, which usually lead to false alarms because of the loss of information fusion. The aim of this study is to utilize the status coupling relationship to improve fault detection sensitivity and reduce false alarm rate. A real-time status identification of related equipment step is added between capturing abnormal signals and listing out diagnosis results. For example, when the pipeline pressure fluctuation is found abnormal, a status analysis of pump units is performed immediately, if the pump units are proven to be operational normally, then the pipeline leak alarm is acknowledged valid. The logical reasoning algorithm is used to capture abnormal conditions of pipeline pressures. The pump unit faults are captured by combining information from multiple sources. Field applications show that the proposed method significantly improves the PPU fault detection capability on fault detection sensitive and accuracy.     

Model-based information fusion investigation on fault isolation of subsea systems considering the interaction among subsystems and sensors

The offshore oil industry has expanded to deep water and Arctic. The harsh operating conditions (e.g., ice and strong wind) and increasing complicated system raise the occurrence likelihood of system faults. This requires timely fault isolation and management in the subsea system. However, the offshore oil industry mainly relies on humans to isolate faults based on alarms. With harsh operating conditions and increasing complicated system, this industry urgently needs research on more efficient fault isolation and cause diagnosis methods. Unfortunately, limited research is conducted on fault isolation method in the offshore oil industry. Furthermore, in industry 4.0 era, large amounts of information are obtained. This provides precondition for the application of information fusion technique which aims to improve diagnosis results. However, to the authors’ knowledge, information fusion has not been much studied in the fault isolation of the offshore oil industry. Moreover, the interaction of different subsystems contains valuable information. How the interaction of different subsystems can influence the fault diagnosis has not been explored. This paper proposes a Bayesian network (BN) based method for timely fault isolation and cause diagnosis for the offshore oil industry. The work fuses different information, and it also includes the dependency among different subsystems in the fault diagnosis. As an important alarm source, false alarms are also taken into account in the model. A case study on the subject of the subsea wellhead and chemical injection systems is conducted to demonstrate the functions and merits of the proposed method.     

火灾自动报警系统可靠性研究

火灾自动报警系统主要包括火灾探测器、火灾报警控制器、减灾装置和灭火装置4部分,从这4部分分析了其工作原理。在此基础上,着重分析了误报、漏报概率较高的火灾探测系统(包括火灾探测器和火灾报警控制器)在使用过程中可能出现的失效状态。其失效的根本原因是在探测器的设计、选型与安装中出现的问题以及各类控制器和控制软件出现的问题。火灾自动报警系统在设计、安装和使用过程中出现的一些问题可能导致整个系统失效,主要包括硬件故障、系统失误和管理缺陷3类。因此,从火灾自动报警系统设计、软硬件产品质量、选型与安装及维护保养等方面给出了提高火灾自动报警系统可靠性的措施。最后应用系统安全及可靠性理论建立了包括电源系统、触发装置、报警控制装置和警报装置4个指标的火灾自动报警系统可靠度计算模型。     

基于压电传感板的建筑疏散照明技术(英文)

在当今世界,电力、能源和安全是人们日常生活的基本要求。为了应对日益增长的能源需求,最终的解决办法是实施可再生能源,然后将其用于人类的安全。可再生能源需要以它们各自正确的方式实施。研究基于压电传感器片的迈步发电装置,并演示了如何利用这些能量实现建筑物疏散照明。我们在传感器的下方和顶部分别固定了木板和可移动网螺栓,利用压电传感器系统,行人可以通过迈步向发电装置施加电能,另外,将硅凝胶粘贴在位于下部木板空洞中的所有传感器顶部。当有人踩到板上时,就会自动施加压力。在木板的顶部和底部设置了一个孔,以便随时调整在底部和顶板之间安装的可移动网螺栓。烟雾传感器用于启动灯光。使用这种设备,我们实现了建筑物疏散路径上的LED灯正常运行。结果表明,这种安全发电的设计和方法具有一定的实用价值,同时也满足了全球对能源的需求。     

A new approach to quantitative assessment of reliability of passive systems

The objective of this paper is to show how probabilistic reliability can be assessed for complex systems in the absence of statistical data on their operating experience, based on performance evaluation of the dominant underlying physical processes. The approach is to distinguish between functional and performance probabilities when dealing with the quantification of the overall probability of a system to perform a given function in a given period of time (reliability). In the case of systems where sufficient statistical operating experience data are available, one can focus the quantitative evaluation entirely on the assessment of the functional probability for a given active item (e.g. a pump) by assuming that the specification, layout, construction and installation is such that the item is providing the assigned performance, e.g. in the form of generating the required flow rate. This is how traditional probabilistic safety assessments (PSAs) focus the reliability analysis for the various safety features on the calculation of values for the availability per demand. In contrast, for various systems relevant in advanced technical applications, such as passive safety features in innovative reactor designs, it is essential to evaluate both functional and performance probabilities explicitly and combine the two probabilities later on. This is of course due to the strong reliance of passive safety systems on inherent physical principles. In practice, this means that, for example, in case of a passive cooling system based on natural circulation of a given medium, one has to evaluate and to assess the probability to have a medium condition and a flow rate such that a cladding temperature, represented by a probability distribution, can be hold at a required level. A practical example of this method is given for the case of the reliability assessment of a residual passive heat removal system. General conclusions are drawn regarding reliability estimation of complex, interconnected systems in the absence of statistical performance data, such as for infrastructures.     

Triangular typology approach to studying performance management systems in high-tech firms

To reflect the needs of high-tech firms and high-tech employees a set of interrelated models (triangular typology) of performance management systems is developed. The triangular typology articulates and aligns the elements in the performance management process and it expands on traditional binary models by adding a third (high-tech) dimension for each element. It is hypothesized that high-tech employees prefer the ‘high-tech’ dimensions over the other two dimensions of each triangle. A mail questionnaire is used to collect data on the actual and desired performance management practices. All but one of the hypotheses are supported. The ‘actual’ practices are mostly in the traditional corner of the triangle. The disparity between the level of actual practices and the level of desired practices indicates that high-tech employees are not well served by current performance management systems.     

Two leaks detection in viscoelastic pipeline systems by means of transient

This paper presents a technique for detecting and locating leaks in a single viscoelastic pipe, by means of transient analysis. The system studied is a reservoir-pipe-valve structure. The viscoelastic behavior of the pipe wall material is modeled by a generalized KelvinVoigt model. To determine the leak location, the mathematical formulation has been solved by the method of characteristics. The approach by the method of characteristics is often chosen because it is based on the concept of acoustic wave propagation which is the main mechanism of all transient events considered. The presence of the two leaks in a pipe partially reflects pressure waves initiated by the sudden closure of a downstream shut-off valve. These waves affect the shape and the amplitude of the time-history-pressure. The computed results describe the influence of the presence of two leaks on pressure time-history and the effect of leaks locations and sizes on the pressure signal behavior. The effect of the pipe wall viscoelasticity on the two leaks detection and sizing is also discussed. The leaks discharges are determined by resolving two independent equations derived from literatures and based on transient analysis. The friction and leaks depths effects on two leaks locations and sizing are involved.