System for diagnosing and detecting blockages in direct-fired process furnace tubes

Abstract

This invention reveals a diagnostic and blockage detection system for direct heating process furnaces, aimed at enhancing operational efficiency and safety. The system comprises an accurate dynamic model of the furnace, measuring equipment, and a fault identifier, which work in conjunction to monitor and analyze furnace performance. The dynamic model is constructed using thermodynamic principles, heat transfer, and mass transfer relationships. It is implemented on a powerful computer and calibrated using dimensional specifications and real system data. The model incorporates empirical and semi-empirical relations governing the thermodynamic conditions of crude oil, as well as heat transfer coefficients in both single-phase and two-phase regimes, considering the effects of flame height and combustion conditions. To facilitate real-time monitoring, the system employs various measuring devices, including thermocouples (7) and pressure sensors (6), to capture essential parameters such as fuel flow rate, combustion air flow rate, combustion temperature, and the temperature, pressure, and flow rates of input and output crude oil. These measured values serve as inputs to the mathematical model, allowing for the comparison of model outputs with actual system performance. The fault identifier is designed to classify data into acceptable and unacceptable categories, issuing alerts when the blockage level in the pipes (10) exceeds predetermined thresholds. This functionality enables operators to take preventive actions, such as clearing blockages or performing maintenance, ensuring optimal furnace operation. Overall, this innovative device significantly enhances the ability to detect and analyze blockages in direct heating furnaces, thereby improving operational reliability and reducing downtime, ultimately contributing to better process efficiency in industrial applications.

Description

System for diagnosing and detecting blockages in direct-fired process furnace tubes

[0001] The technical field of this invention is related to the condition monitoring of process furnaces used in the oil, gas, and petrochemical industries, and specifically focuses on the system for diagnosing and detecting blockages in process furnace tubes. It is also associated with the fields of mechanical engineering and instrumentation.

[0002] Diagnostic and blockage detection systems for direct-fired process furnace tubes hold significant importance due to the critical role of furnaces in the oil, gas, petrochemical, and chemical industries. These tubes are exposed to extremely high temperatures and corrosive materials, which, over time, can lead to the formation of deposits, corrosion, or blockages inside the tubes. Such issues gradually reduce system efficiency and pose serious safety risks. Therefore, the development of early-stage diagnostic and blockage detection systems has been a priority in the thermal process industry.

[0003] To date, various methods have been proposed for monitoring performance, diagnosing, and cleaning blockages in process systems. Some patents that address diagnostic and blockage detection systems for direct-fired process furnace tubes include the following examples:

[0004] U.S. Patent Application No. US4176544A relates to a method for determining deposits. This method involves detecting the fouling tendency of a liquid by heating the liquid and adding a solution or suspension that contains one or more inorganic and / or organic foulants to enhance the concentration of the foulant within the liquid. The resulting liquid is then passed through a heated tubular test section, where the increase in pressure drop and / or the decrease in temperature across the test section is measured over a specified period.

[0005] U.S. Patent Application No. US4822475A It discloses a method for determining the fouling tendency of crude oil, which This invention relates to a process for determining the fouling tendency of a crude petroleum oil feed, which includes the following steps. First, a selected volume of crude oil sample is mixed with a selected volume of a solvent medium. The resulting mixture is then agitated continuously to solubilize the fouling-determining materials in the solvent. Next, a sample is taken from the resulting solvent medium. Following that, the absorbance of the solvent medium is measured at a wavelength of 230-270 nm, and the absorbance of a control solvent medium is subtracted from this value to obtain the corrected absorbance of the resulting solvent medium. Finally, the fouling tendency of the crude petroleum oil sample is determined by correlating the corrected absorbance of the solvent medium with specific calibration data for the solvent, the ratio of oil sample to polar solvent, and the wavelength at which absorbance is measured. The fouling tendency determined by this method can be used to predict the amount of antifouling agent required to prevent fouling during downstream processing. This method not only aids in assessing and controlling the quality of crude oil feed but also facilitates the optimization of related industrial processes.

[0006] U.S. Patent Application No. US4910999A This invention relates to a laboratory device that produces a fouling deposit under controlled temperature and pressure, simulating actual plant conditions. The device accurately measures the accumulation of foulant deposits during the deposition process. It is utilized for testing the fouling tendencies of various fluids that change upon contact with a hotter surface, forming solid or semi-solid deposits that adhere to the surface. The device is capable of calibration and temperature measurement, and it can also monitor temperature changes during fouling, which can be effectively correlated with the amount of fouling present. The apparatus includes multiple probes, each supporting removable test wires that are electrically heated to selected temperatures. This allows for simultaneous multiple fouling tests under a constant heat flux or at a constant temperature. Overall, this invention aids in a better understanding of the fouling process and provides the means for optimizing industrial systems.

[0007] U.S. Patent Application No. US7827006B2 he detection of one or more abnormal conditions is performed using statistical methods such as mean, median, and standard deviation, based on measurements of process parameters or system variables. This detection helps evaluate the health and performance of heat exchangers in the plant, particularly in identifying fouling conditions. Among the statistical measures, calculating the overall thermal resistance of the heat exchanger can indicate its performance, especially in detecting performance degradation caused by fouling. This method allows for more precise and faster monitoring of fouling issues and performance decline in heat exchangers, preventing further complications in industrial processes.

[0008] U.S. Patent Application No. US2013003048A1 This invention relates to a fouling detection system and method for determining the amount of fouling on the surfaces of fluid processing devices and / or internal components of such devices, which are exposed to the fluid and are subject to fouling. Fouling detection systems and methods are useful for monitoring the fouling on surfaces, such as heat transfer surfaces, and for overseeing the cleaning process of these fluid processing devices and / or their internal components. According to the invention, the detection system includes at least one sensor, equipped with means to measure the optical transparency (T) and / or electrical conductivity (Q) of the fluid. The sensor features at least one sensitive area, located near or on the surfaces, and this area is at least temporarily exposed to the fluid.

[0009] U.S. Patent Application No. US9709384B2 This invention describes a method for the direct on-line measurement of the thickness of fouling deposits formed on the tube walls of a pulverized-coal firing furnace, as well as an apparatus designed for this method. The technique involves imaging a light spot generated on the surface of the deposit by the apparatus. A position-sensitive image detector is employed to track the spot as deposits accumulate, and the image signal is processed in real time, enabling the monitoring of fouling deposit formation during the furnace's operation. The system also simultaneously determines the reflectivity of the deposit surface. Additionally, the apparatus can be integrated into an automatic soot-blowing system.

[0010] U.S. Patent Application No. US11365886B2 This invention refers to an advanced system and method for optimizing the performance of fired heaters in chemical plants. Fired heaters, as essential tools for heating process streams, utilize hot combustion gases to raise the temperature of fluids flowing through tubes within the heater. This process facilitates the transfer of fluids at the required temperature to subsequent stages of the reaction process and can also perform reactions such as thermal cracking. In this invention, new systems and methods are introduced that can assist in optimizing the performance of heaters and reducing their energy consumption. This not only helps decrease operational costs and enhance efficiency but can also provide significant improvements in sustainability and environmental impacts of production operations. Overall, this invention presents important innovations in the design and operation of fired heaters and can serve as an effective tool in enhancing the efficiency of chemical plants.

[0011] U.S. Patent Application No. US20230143324A1 A system and method are provided for determining cleaning schedules for equipment. The equipment includes fired heaters and / or heat exchangers. The method involves obtaining historical sensor data, transforming the obtained sensor data using an engineering first principles process, and applying data analytics to the transformed data to generate at least one statistical model. The method also includes predicting an indicator of fouling in the equipment using operational data and the at least one statistical model, obtaining cost data associated with the equipment being analyzed, determining a desired cleaning schedule for the equipment based on the prediction and cost data, and providing an output related to the desired cleaning schedule.

[0012] U.S. Patent Application No. US11890654B2 describes a system and method for cleaning coils in a fired heater. The cleaning system incorporates a data acquisition tool designed to navigate through the coils to gather data. This system establishes a pre-cleaning fouling baseline based on the collected data from the coils. Using this baseline, the cleaning system develops an optimized cleaning plan specifically tailored for the coils. This plan focuses on cleaning areas of fouling within the coils. Additionally, the cleaning system includes at least one cleaning pig, which is configured to perform the cleaning according to the optimized plan. Furthermore, the system is equipped with a decoking truck that utilizes the cleaning pig to effectively clean the coils, following the established optimized cleaning strategy.

[0013] This summary is intended to provide an overview of the subject matter of the disclosed invention and is not aimed at identifying the essential or key elements of the subject matter. Additionally, it is not used to determine the scope of the claimed implementations.

[0014] This invention is based on the dynamic modeling of the entire crude oil pre-heater system. Given that the model developed in this research is used to analyze the effects of fouling and temperature distribution, the parameters affecting the performance of the furnace, including combustion temperature, excess air percentage, fuel flow rate, oil flow rate, etc., have been considered in the model. The ability to examine the behavior of the system over a long period and under various operating conditions, to determine the crude oil conditions at the exit of all pipes, and to determine the temperature of all pipes simultaneously, as well as to account for nonlinear conditions and interactions between system variables, to predict fouling and estimate its extent in the pipes based on the input conditions of the furnace and the output of the pipes in different conditions and scenarios, are among the key advantages of this invention. The device is installed in the desired location, which can be in a local control panel or a panel of a distributed control system. The connection between the temperature sensors installed on the furnace is possible either through direct connection or by receiving data from a shared system. Upon detecting the connection of the sensors to the device, the activation option is enabled. After starting the device, information regarding the thermal status of the furnace is received and compared with the output of the internal model of the equipment, determining the deviation of the furnace temperature at various points from the predicted temperature of those points by the internal model. The deviation must remain within a specified range and between upper and lower thresholds. Exceeding these limits determines the remaining amount. The diagnostic observer analyzes the remaining amount and determines the state of pipe fouling and its rate of change. In a fault-free operational state, the remaining amount is equal to zero. When the fouling of the pipe reaches a point where noticeable temperature changes occur due to inadequate heat transfer, the remaining amount will be a non-zero value that exceeds the tolerance threshold. In this condition, an alert is given to take appropriate actions for clearing the path, shutting down the furnace, or performing preventive maintenance.

[0015] Other key features include:

[0016] Dynamic Modeling Capabilities: The ability to create and analyze dynamic models for predicting performance under varying operational conditions.

[0017] Real-time Monitoring: Continuous monitoring of temperature and pressure in various parts of the system for immediate data analysis and response.

[0018] Non-linear Conditions Handling: The capacity to account for non-linear relationships between different parameters in the system.

[0019] Fouling Prediction and Estimation: Advanced algorithms to predict fouling based on input conditions and historical data.

[0020] Adaptive Thresholding: Setting operational limits and alarms that adjust based on historical performance and operational context.

[0021] Integration with Control Systems: Compatibility with local control panels or distributed control systems for seamless operation.

[0022] Data Acquisition Methods: Options for direct connection of temperature sensors or data collection from a shared system.

[0023] Maintenance Alerts: Automatic alerts when fouling levels exceed predefined thresholds, prompting necessary maintenance actions.

[0024] User Interface: An intuitive user interface for operators to monitor system status and adjust parameters easily.

[0025] Simulation of Various Scenarios: The ability to simulate different operational scenarios to understand potential impacts on system performance.

[0026] Crude Oil Pre-Heater Furnaces are one of the essential pieces of equipment for supplying heat in the process of separating petroleum derivatives and producing various products in separation towers. To enhance thermal efficiency, parallel paths are utilized to increase heat transfer and position these paths in the direct radiation of flames produced by the burner; therefore, they are referred to as direct heat furnaces. Given the positioning of each of these paths, any changes in the combustion process, heat transfer degradation, and changes in process load can lead to significant variations in the output temperature of each of these paths, the final output of the furnace, and ultimately a decrease in product quality. In such conditions, important phenomena that disrupt the performance of these types of furnaces include the growth of deposits, tube blockages, and the formation of wax or coking in the tubes. A crucial issue is that as the thickness of the blockage in the tubes increases, the rate of heat transfer to the process fluid inside the tube significantly decreases. The heat generated from combustion radiation can cause the formation of hot spots on the process tubes. Continued conditions may lead to melting and the temperature of the tube reaching a critical state, resulting in tube rupture and the entry of flammable materials into the internal chamber of the furnace. The consequence of this is a catastrophic fire, destruction, and potential explosion of the furnace. Unfortunately, several factors can lead to the formation of coke and blockages in the tubes. Poor distribution of flow through the furnace streams, faults in the combustion system, malfunctioning burner tips, flame impingement on the tubes, and temperature changes upstream of the process furnaces are factors that can accelerate tube blockages. However, the natural blockage of tubes over time is also an unavoidable issue that occurs gradually. For blockages that develop over a period of 2 to 3 years, preventive maintenance and replacement of furnace tubes are viable solutions. Nevertheless, under unstable conditions in the combustion system, this time may reduce to 2 to 3 days, indicating a potential risk. Therefore, predicting the condition of tube blockages and monitoring the online status of the furnace is essential. The necessity of this is based on having a comprehensive database and analysis regarding the furnace, which is usually not available given its conditions. Since the method and system of the present invention are based on a software core and direct measurement of system variables to predict the thermal status of the tubes and infer the degree of tube blockage, the implementation costs are relatively lower, and its speed and accuracy of operation are greater compared to conventional troubleshooting methods.

[0027] Modeling of crude oil preheating furnaces is crucial due to their significant role in designing control systems and troubleshooting these units. Despite their importance, research activities in this area have been limited. Establishing a suitable structure and creating accurate models for different sections of a crude oil preheating furnace that can effectively represent nonlinear conditions and the interactions among system variables such as flow rate, pressure, and temperature are of great significance. Accordingly, this invention is based on the dynamic modeling of the entire crude oil preheating furnace system. The developed model is intended to analyze the effects of blockage and temperature distribution. Key performance parameters for the furnace, such as combustion temperature, excess air percentage, fuel flow rate, and oil flow rate, have been included in the model. The ability to examine system behavior over extended periods and under various operating conditions, determine the conditions of crude oil at the output of all tubes, and assess the temperature of all tubes simultaneously, while considering nonlinear conditions and interactions among system variables, is among the most notable advantages of this invention. It also predicts blockage and estimates its extent in the tubes based on input conditions to the furnace and output from the tubes under various scenarios. Blockage represents one of the most critical economic and environmental challenges in petrochemical industries worldwide. In crude oil preheating furnaces, this phenomenon depends on various factors, including flow rate, flow temperature (which is influenced by combustion conditions, properties of the incoming crude oil, etc.), and fluid composition. Therefore, accurately modeling blockage under different operating conditions is quite complex. The occurrence of blockage can lead to severe issues in the furnaces, such as decreased efficiency, resulting in increased consumption of fuel, water, and electricity, as well as energy losses due to increased pressure drop and elevated carbon dioxide emissions from excessive fuel usage. Additionally, maintenance, repairs, and the need for larger surfaces to compensate for reduced heat transfer incur significant costs. In some cases, improper characteristics of gaseous fuels can result in massive fires in furnaces. Moreover, shutting down one burner may lead to the shutdown of other burners. These unfortunate experiences underscore the necessity of paying attention to slight changes in the operational status of the furnace and its deviation from ideal conditions, as these factors can lead to significant and irreparable damages over time. Typically, crude oil preheating furnaces need to be shut down after 2 to 3 years of operation due to the high percentage of blockage in the tubes caused by various issues. Predicting blockage based on input and output characteristics of the furnace, as well as determining the percentage of blockage in the tubes for timely control of this phenomenon, is essential for improving the quality of the output products and preventing irreparable damages. To achieve this, the independent input parameters that affect the furnace's behavior will first be identified, followed by the design and simulation of experiments to evaluate the desired response. In the industry, the designed experiments are used to systematically study the processes or variables affecting product quality. After identifying the process conditions and components influencing product quality, efforts will focus on advancing production capabilities, reliability, quality, and field performance. Correctly designed experiments yield larger volumes of data with higher accuracy and typically require fewer test executions. Moreover, some predicted results can be reliably evaluated. The design of experiments is often conducted in four phases: planning, testing, optimization, and validation. Subsequently, using the results of the provided modeling, a model-based detector is designed, and its performance in the early prediction of blockage occurrence in the pipe paths is examined. Finally, the percentage of blockage in the tubes will be determined based on the input conditions to the furnace and the output from the tubes.

[0028] The proposed method offers a model-based troubleshooting approach based on precise dynamic modeling of direct heat furnaces, which is applicable to various flow paths and tubes, enabling long-term evaluation of the furnace. It takes into account the critical position of the tube, where the maximum allowable thickness of blockage on the inner surfaces of the tube is minimized. Experiments are designed to investigate the main and interaction effects of the factors influencing the system's behavior. The experimental design is conducted using Minitab software and the central composite design method. Independent factors affecting the furnace output include the inlet oil temperature, inlet oil flow rate, fuel flow rate, combustion pressure, and the percentage of blockage in one of the tubes in the radiant section of the furnace. Given the number of independent factors, the experiments are designed using Minitab software. After conducting the designed experiments using the proposed model, the desired responses are recorded. By evaluating each response and based on the analysis of variance table, the accuracy of the designed experiments and the most important parameters influencing the desired response are determined. From a statistical perspective, a suitable model is one in which the squared residual values, both in the adjusted and unadjusted states, are maximized and closely aligned. This approach enables the prediction of the occurrence of blockages and estimation of their percentage in the tubes based on the input conditions to the furnace and the output from the tubes. Additionally, it provides the capability for early identification of blockages in process tubes, especially in direct heat furnaces.

[0029] Fig.1

[0030] Shows a view of the diagnostic system and its main components.Fig.2

[0031] Shows a side view of the diagnostic system.Fig.3

[0032] Shows a cross-sectional view of the diagnostic system and its internal components.Fig.4

[0033] Shows the details of the channel and pipe passage.Fig.5

[0034] Shows the details of the data collection device and its connections.Fig.6

[0035] Shows a side view of the details of the data collection device connections.

[0036] This document discloses a system for troubleshooting and detecting blockages in the pipes of direct heat process furnaces. Given that the furnace in question contains numerous pipes as described in the present invention, we will focus on analyzing one of these pipes. In this invention, thermocouples (7), surface thermocouples (9), and pressure sensors (6) are installed at the inlet and outlet of the pipes. The system operates in such a way that it provides information regarding possible clogging within the pipe. When the furnace is active, the pipes (1) are heated by the flame, which transfers heat to the pipe shell (1). Consequently, the fluid inside pipe (1) absorbs the heat. Depending on the phase of the fluid, the temperature of the pipe shell does not change significantly because crude oil, unlike water, is composed of a variety of hydrocarbons, each with a different boiling point. As the temperature rises, part of the crude oil evaporates, while some of it remains in liquid form. This causes the surface temperature of the pipe to increase more in certain sections compared to others.

[0037] The system, equipped with thermocouples (7), surface thermocouples (9), and pressure sensors (6) at the inlet and outlet of each pipe, measures the fluid temperature, surface temperature of the pipe, and the pressure of the fluid inside the pipe. Knowing the fluid's location within the pipe allows us to predict its behavior in that pipe. By having the input and output temperatures and pressures, and knowing the pipe length, we can use a model to estimate the outlet temperature and the approximate surface temperature of the outlet pipe. The device uses this model and the collected data to calculate the pipe's outlet temperature.

[0038] It is also worth noting that clamp (8) is used to secure surface thermocouple (9) and attach it to the pipe’s surface. The model is stored in the data logger (5), where the calculations are performed. The system collects information from thermocouples (7) through wire (2), from the pressure sensor through wire (3), and from surface thermocouples (9) via wires (4). After processing, the system calculates the outlet temperature. If fouling (10) occurs inside the pipe, it prevents heat transfer from the flame to the fluid, raising the surface temperature of the pipe while lowering the fluid temperature. If the outlet temperature is not within the desired range and is significantly lower, it can be concluded that fouling (10) has occurred in the pipe, and the system issues an alert.

[0039] First, the device is installed at the designated location, which can be either at a local control panel or within a distributed control system (DCS) panel. The connection between the temperature sensors mounted on the furnace can be established in two ways: direct connection or receiving data from a shared system. Once the sensors are detected by the device, the start-up option is activated. After the device is started, the furnace's thermal status data is collected and compared with the output of the device's internal model. The temperature deviation of different furnace points from the predicted temperature at those points is determined by the internal model.

[0040] The deviation must remain within a specific range, bounded by an upper and lower adaptive limit. Exceeding these limits determines the residual amount. The diagnostic monitor analyzes the residual and determines the status of the pipe blockage and the rate of change. In normal, fault-free operation, the residual is zero. When a blockage in the pipe becomes significant enough to cause noticeable temperature changes due to inadequate heat transfer, the residual value becomes non-zero and exceeds the tolerance threshold. In this scenario, an alert is triggered, prompting appropriate actions such as clearing the passage, shutting down the furnace, or conducting preventive maintenance.

[0041] Easy installation in various locations:

[0042] The device can be installed in local control panels or distributed control systems (DCS) and can communicate with sensors installed on the furnace.

[0043] Data collection via temperature and pressure sensors:

[0044] The device uses thermocouples (7) and surface thermocouples (9) to measure the fluid temperature and the pipe surface temperature, and pressure sensors (6) to measure the pressure of the fluid inside the pipes (1).

[0045] Internal model for predicting outlet temperature:

[0046] The device is equipped with an internal model that analyzes input data and accurately predicts the outlet temperature of the pipe (1).

[0047] Determining temperature deviation from predictions:

[0048] The device compares the actual furnace temperature with the predicted temperature from the internal model, and calculates the deviation, which must remain within a specified range.

[0049] Detection of pipe blockages (10):

[0050] If the outlet temperature of the pipe deviates from the predicted value, the device detects a potential pipe blockage (10) through residual analysis.

[0051] Automatic alerts for maintenance actions:

[0052] When the temperature deviation exceeds the acceptable limits due to pipe blockage, the device automatically triggers an alert, notifying the user of the need for maintenance actions or shutting down the furnace.

[0053] Sensor connection via multiple wires:

[0054] Data from the thermocouples (7) is transmitted via wire (2), from the pressure sensors (6) via wire (3), and from the surface thermocouples (9) via wires (4) to the device.

[0055] Data storage and processing in data logger (5):

[0056] The information collected from the sensors is stored and processed in the data logger (5), where calculations are performed to update and provide the system output.

[0057] Clamp (8) for securing surface thermocouples:

[0058] Clamps (8) are used to securely attach the surface thermocouples (9) to the pipe surface, ensuring accurate data collection from the surface of the pipes.

[0059] This equipment is designed for use in the oil, gas, and petrochemical industries for the continuous monitoring of tube conditions in process furnaces. It provides real-time reporting on the status of the tubes and predicts the timing of potential incidents caused by overheating due to blockage. Specifically tailored for direct-fired process furnaces, this device can be installed in strategic locations, such as in local control panels or as part of a comprehensive Distributed Control System (DCS). By doing so, it enables online health monitoring of the furnace, ensuring optimal performance and safety.

[0060] Citation List follows:

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[0067] Inventor(克里斯·A·赖特格伦·B·布龙斯曼纽尔·S·阿尔瓦雷斯彼得·W·雅各布森沙伦·A·费伊勒乔治·A·卢兹). (2011). Title of the invention: Method and system controlling the amount of anti-fouling additive for particulate-induced fouling mitigation in refining operations (Patent No. CN102177224A). State Intellectual Property Office of the People's Republic of China.

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[0069] Inventor (Glen Barry BronsChris Aaron WrightIi George A. LutzDaniel P. Leta). (2015). Title of the invention: Method of blending high tan and high sbn crude oils and method of reducing particulate induced whole crude oil fouling and asphaltene induced whole crude oil fouling (Patent No. EP2054489B1). European Patent Office.

[0070] Inventor (ハウデスヘル，マイケル，ジェイムズ). (2014). Title of the invention: Method for dispersing hydrocarbon contaminants in a hydrocarbon treatment fluid (Patent No. JP5474037B2). Japan Patent Office.

Claims

What is claimed is a diagnostic and blockage detection device for direct heating process furnaces, consisting of an accurate dynamic model of the furnace, measuring equipment, and a fault identifier. This device utilizes thermocouples(7) and surface thermocouples (9) to measure fluid temperature and pipe surface temperature, as well as pressure sensors(6) to measure the fluid pressure inside the pipes (1). The information obtained from these sensors is processed by the data logger (5) to analyze the thermal state and fluid flow in the furnace.According to Claim 1, an accurate mathematical model of various parts of the furnace is developed based on thermodynamic, heat transfer, and mass transfer relations implemented in a powerful computer. The model parameters are determined and calibrated based on dimensional specifications and available data from the actual system. Additionally, empirical and semi-empirical relations governing the thermodynamic conditions of crude oil, heat transfer coefficients in single-phase and two-phase regimes, as well as the effects of flame height and combustion conditions on furnace dynamics are incorporated into the model.According to Claim 1, measuring equipment, including thermocouples (7) and pressure sensors (6), is provided to determine the values of fuel flow rate, combustion air flow rate, combustion temperature, combustion pressure, and the temperature, pressure, and flow rate of input and output crude oil through various passes in real-time.According to Claim 2, the measured values serve as data from the actual system considered as inputs to the model. Additionally, to compare the model output with actual values, the temperature and pressure of the output crude oil from different passes are measured.According to Claim 1, considering the input parameters of the furnace, including the temperature of crude oil at the furnace inlet, input crude oil flow rate, combustion pressure, and fuel flow rate, as well as modeling blockages in the pipes (10), the output temperature and pressure of the oil in the pipes and the temperature and pressure of oil exiting the passes are calculated and recorded. A network with 5 inputs and 1 output for each output is formed, with the desired range for each output defined. A fault identifier is designed to classify the data into two classes: acceptable and unacceptable.According to Claim 1, the designed fault identifier is capable of issuing alerts corresponding to the blockage levels in the pipes. The pressure of oil at the output of the selected pipe and the temperature of the pipe, along with the input oil temperature, input oil pressure, fuel flow rate, and combustion pressure, are considered as input variables, with the percentage of blockage in the pipe as the output. Thus, a network with 5 inputs and 1 output is trained, and its performance in predicting the percentage of blockage is evaluated.

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