Design And Control System of Automatic Control System of Coal Flow on Belt Conveyor Installation

In a power plant unit whose main fuel is coal, there is generally use a belt conveyor installation. This conveyor belt serves to supply coal from the crusher unit to the combustion chamber of the power generation unit. In this study, we discuss a case where the installation of a belt conveyor which was initially only one line was then made a new branch that supplies coal to other power generating units. Equitable capacity distribution and continuity of coal distribution are the main focus of this study. Therefore, a design of automatic control system of coal flow divider on belt conveyor installation was designed. The working principle of this coal flow splitting system is to control the movement of the straight blade plough that directs the flow of coal to each unit at the certain time and continuously. Straight blade plough in the form of steel metal plate with a thickness of about 10 millimeters in which one end is connected to the end of the pneumatic cylinder. Automatic control system of coal flow divider in belt conveyor installation designed using CX-Programmer and CX-Designer applications. CX-Programmer serves to create automatic control logic concepts. While the CX-designer functions to create a Human Machine Interface (HMI), making it easier for operators to control the course of the coal supply process. The results of this study are in the form of control logic lines that can be applied to Programmable Logic Control (PLC) device and Human Machine Interface (HMI) equipment.

Dynamic Coal Quantity Detection and Classification of Permanent Magnet Direct Drive Belt Conveyor Based on Machine Vision and Deep Learning

Real-time and accurate measurement of coal quantity is the key to energy-saving and speed regulation of belt conveyor. The electronic belt scale and the nuclear scale are the commonly used methods for detecting coal quantity. However, the electronic belt scale uses contact measurement with low measurement accuracy and a large error range. Although nuclear detection methods have high accuracy, they have huge potential safety hazards due to radiation. Due to the above reasons, this paper presents a method of coal quantity detection and classification based on machine vision and deep learning. This method uses an industrial camera to collect the dynamic coal quantity images of the conveyor belt irradiated by the laser transmitter. After preprocessing, skeleton extraction, laser line thinning, disconnection connection, image fusion, and filling, the collected images are processed to obtain coal flow cross-sectional images. According to the cross-sectional area and the belt speed of the belt conveyor, the coal volume per unit time is obtained, and the dynamic coal quantity detection is realized. On this basis, in order to realize the dynamic classification of coal quantity, the coal flow cross-section images corresponding to different coal quantities are divided into coal type images to establish the coal quantity data set. Then, a Dense-VGG network for dynamic coal classification is established by the VGG16 network. After the network training is completed, the dynamic classification performance of the method is verified through the experimental platform. The experimental results show that the classification accuracy reaches 94.34%, and the processing time of a single frame image is 0.270[Formula: see text]s.

ANALISA KEBOCORAN PADA BODY MILL / PULVERIZER MENGGUNAKAN METODA ROOT CAUSE FAILURE ANALYSIS (RCFA)

AbstrakAbstrak PT PJB UBJOM PLTU Tanjung Awar-awar unit 1 dengan kapasitas total daya 350 MW. Setelah dilakukan program combusition tunning di bulan februari 2017, PLTU tanjung awar-awar dapat meningkatkan effisiensi peralatan tertinggi pada sistem pembangkit jawa-bali dan mendapatkan merrit order tertinggi oleh PLN. Permasalahan yang sering terjadi di adalah terjadi kebocoran body pulverizer. Kebocoran ini di sebabkan over velocity pulverizer akibat penggunaan variasi batubara. Dalam penggunaan batubara low range coal, operator harus menaikan flow primary air untuk mencapai outlet temperatur yang sesuai. Kenaikan tersebut menyebabkan naiknya coal flow pada Mill/Pulverizer, coal flow maksimal pada pulverizer 38.5 t/h sedangkan actual opeasi 43.7 t/h. Over velocity yang terjadi pada pulverizer secara tidak langsung meningkatkan laju abrasive di dalam coal pulverizer. Dengan penerapan metode Root Cause Failure Analysis di dapat melakuakan redesign inner linning body pulverizer. Redesign ini bertujuan menekan laju abrasive yang tinggi di dalam pulverizer dengan menaikan hardness pada dinding pulverizer. Kondisi awal plate S5 222 HB atau 19 RC menjadi 625 HB atau 60 Rc. Dengan melakukan Redesign inner linning body pulverizer, maka akan membantu mengoptimalkan kehandalan pengoperasian pulverizer. Kata kunci : Mill/Pulverizer, kebocoran body, RCFA (Root Cause Failure Analysis)

Development of a High Pressure Dry Coal Feed System for a 100 kWt Oxy-Coal Reactor

A design concept to feed dry coal from a hopper to a 100 kWt pressurized oxy-coal (POC) reactor using CO2 at 2 MPa was developed using transient computational fluid dynamics (CFD) simulations and bench-scale measurements. The feed system was required to maintain a steady flow of gas and solids at a coal flowrate of approximately 3.8 g/s and a CO2-to-coal mass ratio in the range 1–2. A 5.08-cm diameter vertical coal hopper feeding into a 0.635-cm diameter horizontal pipe was used to represent key elements of the feed system. A fluidized bed concept was found capable of providing the desired coal flowrate and CO2-to-coal flow ratio. Use of separate fluidization and dilution flows allowed the coal flowrate and CO2-to-coal flow ratio to be controlled independently. The amount of coal transported from the hopper was dependent on the net CO2 flow in the hopper but independent of the CO2 dilution flow. Pipe exit coal flowrates were found to fluctuate at levels acceptable for steady burner operation. Tests from a bench-scale apparatus using Pittsburgh 8 coal with a median particle diameter of 50 µm and moisture content of 6% confirmed the feasibility of the fluidization design. However, for a given CO2 fluidization flowrate, experimental coal flowrates were lower than predicted coal flow, in part due to simplifying assumptions of dry, spherical coal particles and smooth piping in the simulations.