This paper presents the methods of detection and diagnosis of failures, that is, detecting
the existence and causes of failure that can be applied in systems that operate in real
time. The proposed system allows automatic and semi-automatic security management,
and provides general average or minimizes the consequences of disasters. In addition, it
defines the conditions, i.e. the intervals of parameter values, under which causes of failure
are created. Based on these parameters, optimal design of protection is possible and it
enables the efficient management of the system.
Suggested fi re safety system in the process of atmospheric rectification of oil offers the
possibility to choose an optimal diagnostic algorithm and its practical and economic usage.
A new approach should be applied in order to reduce fire hazards in the process of
atmospheric rectification of oil. Fire safety system should be inseparable from the
technological process, and vise versa.
The procedure recommended for fault detection and diagnosis consists of two phases.
The first phase involves the assessment of the process state, while the second involves the
identification of the values of processing parameters and their correlation with the process
model parameters

Cvetanović, Sveta

Mihajlović, Emina

Pešić, Dušica

Popović, Danilo

TRANSACTIONS of the VŠB – Technical University of Ostrava Safety Engineering Series

DSpace at VSB Technical University of Ostrava

Transactions of the VŠB - Technical university of OstravaSafety Engineering Series Vol. VI, No. 2, 201139A NEW APPROACH TO FIRE SAFETY SYSTEM IN THE PROCESS OF ATMOSPHERIC RECTIFICATION OF OILSveta CVETANOVIĆ1, Danilo POPOVIĆ1, Emina MIHAJLOVIĆ1, Dušica PEŠIĆ11 University of Niš, Faculty of Occupational Safety, Čarnojevića 10 a, 18 000 Niš, SerbiaAbstract: This paper presents the methods of detection and diagnosis of failures, that is, detecting the existence and causes of failure that can be applied in systems that operate in real time. The proposed system allows automatic and semi-automatic security management, and provides general average or minimizes the consequences of disasters. In addition, it defi nes the conditions, i.e. the intervals of parameter values, under which causes of failure are created. Based on these parameters, optimal design of protection is possible and it enables the effi cient management of the system. Suggested fi re safety system in the process of atmospheric rectifi cation of oil offers the possibility to choose an optimal diagnostic algorithm and its practical and economic usage. A new approach should be applied in order to reduce fi re hazards in the process of atmospheric rectifi cation of oil. Fire safety system should be inseparable from the technological process, and vise versa.  The procedure recommended for fault detection and diagnosis consists of two phases. The fi rst phase involves the assessment of the process state, while the second involves the identifi cation of the values of processing parameters and their correlation with the process model parameters.Key words: Fire safety system, atmospheric rectifi cation of oil, failures detection, diagnosis of failures, security management.IntroductionAdministration of any technological system requires current information about the parameter values that are important for a system of fi re protection. Thus, measurement of process parameters and their immediate availability is essential for the system to run a technological process. The development and improvement of the methods of the evaluation of the technological process is a continuous interest of science and technological experts. With the degree of complexity of the technological process arise the need to implement systems able to detect failures in the process of diagnosing their causes.For optimization and design of the protection system, methods to detect and diagnose failures are of special interest. That is, detecting the existence and causes of failure that can be applied in systems that operate in real time. There are cases when the cause of failure cannot be removed until the termination of operation, or the impact of failures on safety is insignifi cant but the early warning system can at least provide the information for better decision making about the management of care.By using proposed fi re protection system the likelihood of sudden accidents will be reduced, as well as achieving more effi cient management, and operating under such conditions will be adequate.The procedure recommended for the detection and diagnosis of failures consists of two phases. The fi rst assesses the state of the process, and the second identifi es the values of process parameters and compares them with the parameters of the model process.Materials and methodsProcess of Atmospheric Oil Rectifi cationBefore the rectifi cation of crude oil is prepared, water and impurities that could hinder the process must be separated. Water evaporates and the steam would be too discouraged and kept, increasing pressure rectifi cation, and salt and ingredients will be caught on the walls of the furnace, thus the heating will be less effi cient, and the amount of ash in the distillation residue will increase. The simplest way is that the oil is left to stand, possibly a slight heating (40 - 60 °C), at the same time the water shrug at the bottom with solid impurities (salt, sand, silt) but it takes a long time. Water and impurities can be removed in various ways: centrifugation, using Review articlep. 39 - 43 Transactions of the VŠB - Technical university of OstravaSafety Engineering Series Vol. VI, No. 2, 201140a variety of chemical agents to break the emulsion, by using dismulgators or by electricity (15,000 to 30,000 V) with the strong electric fi eld of charged droplets gather in larger drops and shrug. Methods of water separation could be combined. Maximum remaining of water in oil should be 0.2 % with 0.02 % salt. Oil is often cleaned with the springs that would save money in transportation. Oil , free of mineral impurities, is heated to 350 to 400 °C and under pressure introduced into the atmospheric distillation column. In this refraction column, free of pressure, lighter fractions evaporate immediately, and harder fractions that do not evaporate move to the bottom of the column. The evaporated gas phase is going to the top of the column in contact with the liquid phase, leaving on each fl oor heavier fractions that it still carries. The temperature in the column decreases from bottom to top, making the separation easier. To improve the fl ow and reduce the partial pressure of hydrocarbon in the column for rectifi cation, heated vaporous water is introduced, which mostly comes out of top of the column with a gasoline vapor, condenses with them, and then separates into a water separator.From distillation columns with different fl oors, at least four products are collected - gasoline from the top of the column, jet fuel, easy gas oil and heavy gas oil. Any faction that leaves the main column is still a mixture of larger number of hydrocarbons. That is why some fractions are further processed in additional columns. As the end products of atmospheric distillation, fuel gas, liquefi ed petroleum gas, gasoline (light, primary and feeder stream for platforming), jet fuel and kerosene, light and heavy gas oil are obtained. The waste streams from atmospheric distillation are gases from the furnace for heating crude oil (CO, SOx, NOx, unburned hydrocarbons and solid particles), volatile emissions of hydrocarbons, the emissions from the ejector and oily acidic water, which is separated by condensation in the separators of gasoline, and refi nery sour gas containing hydrogen sulfi de, ammonia, chlorides, mercaptans, phenol and hydrocarbons from petroleum. There is usually no or very little solid waste in this process. Gas oil is the heaviest fraction, which is obtained from atmospheric distillation. Heavier fractions do not stand out in this process, but they stay in the atmosphere or as a slight residual, which is isolated at the bottom of the column and which makes up 35 to 50 % of the quantity of crude oil that has entered the column. Atmospheric residue is usually processed in the second stage of primary production in the vacuum distillation.Fig. 1 shows the simplifi ed technological scheme of the crude distillation unit, indicating the wastewater fl ows.Fig. 1 Simplifi ed technological scheme of the atmospheric distillationPart of the condensate can be returned into the column as refl ux (to push fractions down). Fractions are obtained as condensates in some column fl oors. By combining the condensate with a number of fl oors, fractions with the desired composition can be obtained. Each of the factions is still a mix of high number of hydrocarbons. Fractions can be rectifi ed in additional columns that are close to the main column.If a sharper rectifi cation is needed, two or more rectifi cation columns may be used. Distillation can be done in two phases: crude oil is fi rst heated to a slightly lower temperature to 300 - 340 °C, where it receives only lower fraction, and the rest from the bottom of the column is heated in a furnace to a higher temperature 360 - 420 °C, and then rectifi ed in the second column, possibly in a vacuum.The rest of the plant consists of the extra column (stripper), heat exchangers, condensers and storage tanks, associated with pipe lines.ResultsDefi nition and Classifi cation of FailuresFrom the standpoint of security analysis system, canceling is the change outside certain limits of at least one of the characteristics of the system that cause injury to people or damage material or natural resources.p. 39 - 43Transactions of the VŠB - Technical university of OstravaSafety Engineering Series Vol. VI, No. 2, 201141To facilitate the analysis of security system, failures are classifi ed based on different criteria, making it possible to access the following classifi cation (Tab. 1).Tab. 1 Classifi cation system failureUnexpected (sudden) failures are caused by sudden changes of at least one element of the system parameters. Such changes are caused by hidden defects in materials and system components, or by incorrect use.Gradual failures are caused by gradual changes of at least one element of the system parameters. Changes often occur due to the disturbance of input system characteristics. Independent failures occur without the infl uence of another failure and are usually caused by only one element of the system.Complete failures are failures when the system can be repaired. Partial failures will result in deterioration of some characteristics of the system. Transient failures are failures that repair on their own intervention. Return failures are failures due to various disturbances to the side and follow quickly one after another.Systematic failures are failures where the failure intensity is constant, and are caused by many infl uences that come independently on each other. They may be early and cancellations due to aging. Early failures are characterized by a high decrease in the intensity of the process parameters over time and are caused by the lack of rough elements of the system. Failures due to aging have increasing intensity with time, due to the wear of elements of the system.Random failures are those whose failure intensity is changing in time. Harmless failures do not affect the reduction in the level of system security.Dangerous failures will result in endangering the security and may cause injury or damage to material or natural resources.Methods of Assessment, Identifi cation and Diagnosis FailureSimultaneous identifi cation of three elements in the process model includes: (1) state variables, (2) the output state, and (3) parameters. One of the most common approach for the determination of these three elements is to seek optimal solutions for the nonlinear model of the direct minimization (or maximization) of functions. Solving procedure requires a long calculation, shows the numerical uncertainty and can produce locally optimal solutions for any or all three elements.Another approach to the simultaneous assessment of these three elements is the use of hierarchical identifi cation strategy, a method which in principle is nothing but an alternative approach to nonlinear optimization, and it can also produce local optimal estimates and long-term calculations.Among the commonly used criteria are the minimum error square function or the minimum probability function. Selecting the least square function leads to a simple and fast calculation algorithms than when using the probability function. However, the likelihood function involves higher-order nonlinearities of quadratic functions that require more computing to reach a satisfactory solution as well as in the case of choosing the minimum of the quadratic function. Kalman fi lter (Watanabe and Himmelblau, 1984; Giles and Schuler, 1982) also presents a method for solving nonlinear problems of identifi cation. Kalman fi lter is a nonlinear fi lter The criterion for classifi cation Types of failure1. Kind of changes of the stateunexpected failuregradual failure2. Links to other dismissalsindependent failuredependent failure3. The usability of the system after failurecomplete cancellationpartial cancellation4. Natural eliminationpermanent cancellationcancellation that eliminates automaticlytransient cancellationreturn failure5. External eventsobvious failurecovert failure6. Cause of failurestructural failureconstructor error, imperfect method of constructiontechnological failureerror in production, imperfect technologyexploitation failureerrors in exploatation7. Nature of failurenatural terminationartifi cial termination8. Time of failurefailure during testingfailure in the period of preparationfailure at the end of service9. Failure intensityrandom failuresystematic failure10. According to the impact on safetysafe failuredangerous failurep. 39 - 43Transactions of the VŠB - Technical university of OstravaSafety Engineering Series Vol. VI, No. 2, 201142suitable for the evaluation of the category approach and the maximum likelihood function. Goldmann and Sargent (1971) applied the Kalman fi lter for cosmic spacecraft, Himmelblau used it to identify the parameters in nonlinear chemical processes, and Wels (1971) and Seinfeld (1970) and others apply it to the linear discrete model with abrupt or trendy changes in the parameters. All these researchers have achieved satisfactory results through simulation.To detect and diagnose errors, it is important to know the constant value of process conditions and parameters as compared to the same values that are achieved under normal operating conditions. Otherwise, there is a confusion in determining the actual cause of error.Strategy that Watanabe and Himmelblau (Watanabe and Himmelblau, 1984) suggested in their paper avoids expensive implementation due to: measuring the minimum number of conditions, reconstruction of the remaining inaccessible state variables using the reduced linear, considering the nonlinear process (module is known, but has unknown parameters and inputs).On the basis of interest, the examiner can use the estimated state variables to make decisions in relation to the failure, if the lower and upper limits for each stage are pre-arranged.Watanabe and Himmelblau take the view that the failure causes the changes of different process parameters. By the measurement of process parameters it is possible to determine the moment when it begins to take unwanted shares. Watanabe and Himmelblau state that better results than estimates of unknown parameters can be achieved by a combination of identifi ers and fi lters.Assessment of Rectifi cation ColumnsIn the area of chemical process control, regulation and optimal management of the rectifi cation column is rather treated (Koehne et al., 1977; Retzbach, 1972). The reason is the enormous energy savings opportunity. Given the fact that very often large processing units are analyzed and the savings are large, it could be easy to convince decision makers about the non-academic importance of the relatively complex algorithms. The following sequence of procedures for optimization has been developed: (1) mathematical modeling of processes, (2) validate the pilot column or computer simulations, (3) design a column with given performance and (4) algorithm of regulation that ensures consistency of all sizes that could cause the removal of pre-specifi ed conditions (e.g. feeder control fl ow, pressure drop, fl ow and temperature etc.).As measured parameters are taken the temperature changes in the fl oors where the separation of easily volatile components are conducted.Simulation analysis showed that the approach proposed by Watanabe and Himmelblau is optimal. Fig. 2 shows the comparison of performance when the process is regulated by PID controller and by using optimally managing the evaluation of the condition. Disorder caused by fl uctuations on the fl oor when the control exercised with PID temperature regulator, regulation and assessment of state is hardly noticeable. The authors do not specify the details, but it is obvious that the oscillation in the fi rst case is likely to seek termination of the column and was undoubtedly the performance of the above approaches.Legend:[1] - PID controller [2] - Optimal regulation control for evaluation of the identifi erS - Deviation of places matter changes in rectifi cation column from the steady-stateFig. 2 Oscillation parameters of rectifi cation columnsConclusionBased on preliminary examination and consideration we can conclude:Because of present danger, protective systems should prevent the failing or to minimize the consequences of possibly disaster. Installation of the protection system provides the option of automatic and semi-automatic protection, which has a direct impact on reducing fi re hazards.Reduce the risk of fi re in the atmospheric rectifi cation of oil should be handled well with new approach to the protection system that should be inseparable part of the technological process.Thereafter we should strive to implement the methods of evaluation and identifi cation for the detection and diagnosis of failures, which may provide before-failure assessment of the technological process of atmospheric rectifi cation of oil.p. 39 - 431 2 3 4 5t00-5-1051015S[2][1]Transactions of the VŠB - Technical university of OstravaSafety Engineering Series Vol. VI, No. 2, 201143The proposed system of fi re protection in the process of atmospheric rectifi cation of oil enables the selection of optimal diagnostic algorithms, as well as its economical application.Also, the system defi nes the conditions under which failure causes may be involved in the process model.Optimal design of fi re protection in the process of atmospheric rectifi cation, its management and diagnosis of failure allows only the specifi ed parameters.ReferencesGILES, E. D., SCHULER, H. (1982). Early Detection of Hazardous States in Chemical Reactors, Ger. Chem. Eng. 1982, 5, pp. 69.GOLDMANN, S.F., SARGENT, R.V. (1971). Applications of Linear Estimation Theorv to Chemical Processes, Chem.Eng. Sci. 1971, 26, pp. 1535.KOEHNE, M., SCHULER, H., ZEITZ, M. (1977). Applications of Observers for the Measurement of Unknovvn State Variables of Industrial Processes, Interkama- Kongr., 1977.RETZBACH, B. (1972). Einsatz von Svstem technischen Methoden am Beispeil einer Mehrostoffdestilation. Jahrestriffen der Verfahrensiigenieure, Baser, 1972.SEINFELD, J.H. (1970). Optimal Stohastic Control of Nonlinear Svstems, AlChE J1. 1970, 19, pp. 1016.WATANABE, K., HIMMELBLAU, D.M. (1984). Incipient Fault Diagnosis of Nonlinear processes with Multiple Causes of Faults, Chem. Eng. Sci. 1984, 39, pp. 491.WELS, G.N. (1971). Application of Modern Estimation, and dentifi cation Techniquesto Chemical Processes, AlChEJ 1. 1971, 17, pp. 966.p. 39 - 43

A new approach to fire safety system in the process of atmospheric rectification of oil

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A new approach to fire safety system in the process of atmospheric rectification of oil

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