Development of Advanced Advisory System for Anomalies (AAA) to Predict and Detect the Abnormal Operation in Fired Heaters for Real Time Process Safety and Optimization

As the technology is emerging, the process industries are actively migrating to Industry 4.0 to optimize energy, production, profit, and the quality of products. It should be noted that real-time process monitoring is the area where most of the energies are being placed for the sake of optimization and safety. Big data and knowledge-based platforms are receiving much attention to provide a comprehensive decision support system. In this study, the Advanced Advisory system for Anomalies (AAA) is developed to predict and detect the abnormal operation in fired heaters for real-time process safety and optimization in a petrochemical plant. This system predicts and raises an alarm for future problems and detects and diagnoses abnormal conditions using root cause analysis (RCA), using the combination of FMEA (failure mode and effects analysis) and FTA (fault tree analysis) techniques. The developed AAA system has been integrated with databases in a petrochemical plant, and the results have been validated well by testing the application over an extensive period. This AAA online system provides a flexible architecture, and it can also be integrated into other systems or databases available at different levels in a plant. This automated AAA platform continuously monitors the operation, checks the dynamic conditions configured in it, and raises an alarm if the statistics exceed their control thresholds. Moreover, the effect of heaters’ abnormal conditions on efficiency and other KPIs (key performance indicators) is studied to explore the scope of improvement in heaters’ operation.

Development and Approbation of Methodology Aimed to Define the Reasons for Turbine Unit Capacity Limitation Based on the Specified Mathematical Model of its Condenser

The purpose of this work is to develop and test the methodology of elucidation of the reasons for turbine unit capacity limitations based on a mathematical model of its condenser. This pur-pose is achieved by using a mathematical model of the condenser as part of the developed methodology, taking into account the separate effects of contamination of the heat exchange surfaces, air suction into the vacuum system and the operating mode of the main ejector. Based on operational data sampling, the value of the limiting pressure in the condenser, excess of which leads to limitation of turbine unit capacity, was determined. It was established that the cause of power limitation is the abnormal operation of the main ejector due to inadmissible high temperature in the intermediate cooler of its first stage. For regimes that were not pressure-limited, using a mathematical model, the degree of tubes contamination, its influence on the condenser pressure and the power generated by the turbine unit, and the influence of actual air suctions on the condenser pressure were determined. The most important result of the study is to determine the possibility and feasibility of using the developed and tested methodology for solv-ing similar problems for any type of turbine unit equipped with a condenser. The significance of the work lies in the fact that the proposed approach expands the possibilities of using mathemat-ical models of this class in terms of solving such problems.

Near-Field-Based 5G Sub-6 GHz Array Antenna Diagnosis Using Transfer Learning

In this paper, we propose a method for near-field-based 5G sub 6-GHz array antenna diagnosis using transfer learning. A classification network was implemented for normal/abnormal operation of the array antenna and the failure of a specific port. Furthermore, a regression network that could predict the amplitude and phase of the excitation signal of the array antenna was employed. Additionally, to accelerate the array antenna diagnosis, several near-field lines were sampled and reflected in the regression network. The proposed method was verified by measuring a fabricated 5G sub-6 GHz band 4×4 array antenna in various scenarios using a divider and coaxial cables. The tests showed that the trained network accurately diagnosed 29 of 30 measurement results.

Data Processing in the Pilot Training Process on the Integrated Aircraft Simulator

Flight safety is an integral part of air transportation. Flight accidents are highly unlikely to appear but most of them are caused by the human factor. The aircrew training system for abnormal operations relies on integrated aircraft simulator-based exercises. Crew needs to be trained not to degrade piloting technique quality when facing increased psychophysiological tension. Therefore, methods evaluating the characteristics of ergatic aircraft control systems, warning systems for deterioration due to failures in avionics systems, piloting technique quality, and abnormal operation algorithms are necessary. An analysis of the bank angle has revealed that there are hidden increased tension manifestations in the human operator expressed in the transition of the flight parameter variation from a stationary random process to deterministic fluctuations in the form of a sinusoid. The goal of the research is to increase the efficiency of pilots’ training using integrated aircraft simulators based on the design and implementation of statistical data processing algorithms. To achieve the goal of the research, two algorithms for detecting deterministic fluctuations based on the Neyman-Pearson criterion and the optimal Bayesian criterion are developed. The presented algorithms can be used in the integrated simulator software to automate the decision-making process on piloting quality.

PERENCANAAN SISTEM PERAWATAN MESIN DUST COLLECTOR PECS ID FAN MENGGUNAKAN METODE RELIABILITY CENTERED MAINTENANCE

Dust Collector PECS ID Fan adalah fasilitas penyaring debu yang berfungsi sebagai penampung serta penyaring debu dan uap panas yang dihasilkan dari proses pembakaran produk kokas batubara. Kerusakan PECS ID Fan dapat menyebabkan mesin trip, temperatur bearing tinggi dan terjadi kebocoran media filter pada unit Dust Collector. Penelitian ini bertujuan mengetahui penyebab abnormal operation dan merancang sistem perawatan pada mesin PECS ID Fan. Penelitian ini menggunakan tahapan Reliability Centered Maintenance untuk mendapatkan model perawatan yang efektif pada PECS ID Fan. Hasil penelitian menunjukkan penyebab abnormal operation disebabkan kurangnya penerapan perawatan yang terencana. Sistem perawatan dengan menggunakan Reliability Centered Maintenance memperoleh hasil perawatan pada komponen Chamber (Cage dan Membrane Filter), Air Compressor (Pulsing Pipe) dan Cyclone Dust (Venturi Valve) mengimplementasikan tindakan Failure Finding (FF), komponen ID Fan (Motor, Coupling, Impeller dan Bearing) menerapkan tindakan Condition Direct (CD) dan sub-komponen Screw dari komponen Rotary Lock menerapkan tindakan perawatan Time Directed (TD). Reliability Centered Maintenance dapat mampu merencanakan sistem perawatan komponen peralatan berdasarkan tingkat kerusakan dan pengaruh terhadap operasi.

Stress-strain analysis of details and units of the seeding section of a grain seed drill

The analysis of failure of parts and units of the sowing section during abnormal operation of seeders is given. Using modern CAD systems, a stress-strain analysis of parts and assemblies of the sowing section was carried out, which made it possible to identify a failure above the indicated one, which is associated with a violation of the technological and technical process of operating seeders when sowing grain and industrial crops.

Failure analysis of automobile engine pump shaft bearing

The shaft bearing is the key component of water pump and its fatigue failure results in the abnormal operation of the system. However, the failure mechanisms of bearing are still unclear. In this paper, the failure analysis on the engine water pump shaft bearing was carried out by using the measurement of material composition and properties, observation of macro and micro morphologies, and theoretical analysis of fatigue failure. The wear behavior and failure mechanisms were clarified, and the prevention measures was further proposed. The bearing failure reflected from the fracture of bearing cage and serious wear of roller and mandrel. The wear behavior of the mandrel originated from the surface fatigue, and the failure was attributed to the large radial deflection load. Further, the decreased weight of impeller and shaft connector and the increased bearing thickness were recommended to improve the bearing operation.