Thread Content
Development of combustion control at home and abroad. Heating furnaces are the main energy-consuming devices in steel rolling plants, and improving fuel efficiency is the key issue to be addressed in order to save energy and reduce consumption. The fuels used in the metallurgical industry both domestically and internationally are mainly mixed gas from coke ovens and blast furnaces, as well as various types of pure gas; natural gas is used in some cases, while heavy oil is employed by a few small rolling mills. Computer-controlled combustion processes involve finding the optimal air-fuel ratio under various combustion conditions, so as to keep the combustion in an optimal state. This improves the accuracy of temperature control in the furnace, ensures that steel ingots reach the desired casting temperature more quickly, saves energy, and reduces oxidation losses. Steel rolling heating furnaces are typically equipped with a control system centered around analog control instruments. When the calorific value of the fuel and its pressure remain stable, this control system performs fairly well. However, in situations where the calorific value and pressure of the fuel fluctuate frequently, conventional analog instrument systems struggle to achieve the desired results; operators must constantly observe the flame through a viewing port in order to adjust the air-fuel ratio and improve combustion efficiency. This not only causes many inconveniences for the operators, but also makes it difficult to keep up with the rate of change in calorific value when adjusting the air-fuel ratio manually. Moreover, heating furnaces need to be heated periodically in accordance with specific heating curves, and since the characteristics of these furnaces vary, to ensure their most efficient energy-saving operation it is also necessary to take into account factors such as the condition of the feed material (cold or hot ingots) as well as the operating status of the rolling mill in case of any faults. For these requirements, it is difficult to implement a simulation control system. Research on computer control technology for the heating furnace production process began abroad in the 1970s, and in China it started in the 1980s. With the improvement of detection equipment, instruments, and computer technology, in the 1990s Chinese steel rolling enterprises increasingly equipped themselves with computer-controlled continuous heating furnaces, implementing control systems to varying degrees. Due to differences in the scope of control and usage patterns, the results achieved were also diverse. At present, the development of control theory and key technologies in China is not very far behind that of advanced countries abroad; however, there is a significant gap in actual applications when compared with countries in Europe, America, Japan, and the former Soviet Union, which have more advanced metallurgical technologies. Since the late 1990s, many old enterprises in the country have upgraded their heating furnaces with computer-based combustion control systems; almost all of the computers used were imported, while the detection equipment and instruments were domestic-made. For new projects, most of the equipment was imported as a complete set. Main combustion control methods and applications 1: Cascade-parallel dual-cross-limiting control combustion. Dual-cross-limiting control has gone through four development stages: a ratio control system with fuel as the leading parameter or air as the leading parameter, a cascade-series combustion control system, a cascade-parallel combustion control system, and a cascade-parallel single-cross-limiting combustion control system. It features a furnace temperature control loop as the primary loop, with fuel flow and air flow control serving as secondary loops, thereby forming a cascade-parallel dual-cross-limiting control system. In a dual-cross-limit control system, as the load changes and various system parameters shift, the fuel flow rate is limited by upper and lower bounds based on the measured air flow rate; simultaneously, the air flow rate is also limited by upper and lower bounds based on the measured fuel flow rate. When the load increases or decreases, the fuel flow and air flow restrict each other and increase or decrease alternately, allowing the system to maintain a good air-fuel ratio even under dynamic conditions. Series-parallel dual-cross-limit combustion control is the basic method in instrument control and regulation circuits. In the past, due to limited computer capabilities, it was used less frequently; ratio control and cross-limit combustion control systems both functioned as independent control units. Now, computers are primarily used for control, and they are employed together with zirconia residual oxygen analyzers, calorific value analyzers, expert optimization methods, and fuzzy control; the control performance is better than when these methods were used alone in the past. 2 Zirconia residual oxygen analysis method: This electrochemical approach uses a detector made of zirconia solid electrolyte to measure the oxygen content in flue gas, thereby determining whether the gas is burning sufficiently in the furnace. It helps to avoid issues such as fluctuations in the calorific value and pressure of the gas, or pipe leaks, from affecting the control of the fuel ratio. The residual oxygen detection data is sent to the computer to be used in closed-loop control, providing fast feedback. The computer calculates the air-fuel ratio to achieve automatic control of series-parallel combustion. However, the main problem at present is that zirconia probes are expensive and have a short service life. In 1999, as part of the Sino-Japanese cooperation project for the Green Assistance Program at Jinan Iron and Steel Group Corporation (referred to as Jigang), an efficient combustion control system was implemented for the heating furnaces. This system utilized Japanese Yokogawa ZO21D zirconia residual oxygen analyzers in the two pusher-type heating furnaces at Jigang’s medium and heavy plate factory, thereby helping to save energy, reduce waste, lower emissions of harmful gases, and protect the environment. 3 Measure the calorific value of gas using a calorific value analyzer. A calorific value analyzer is essentially a small combustion furnace; it takes in the pre-treated, clean gas, reduces its pressure through a pressure regulator, passes it through a ceramic filter for filtration, and then adjusts the pressure so that the gas can mix with air supplied by a small combustion fan located in the combustion chamber and cabinet to undergo combustion. The microcomputer uses the exhaust gas temperature of the combustion chamber, as detected by thermocouples, together with calibrated coefficients and the pressure difference between gas and air, to calculate the calorific value and air-fuel ratio; it then outputs this signal to the computer responsible for combustion control or to other display devices. The data measured by a calorimeter is relatively accurate, but it requires a high initial investment, is troublesome to clean, and needs frequent maintenance. However, with the improvement in technology and the reduction in price of calorimeter analyzers, they will be increasingly used in large heating furnaces both domestically and internationally, becoming the mainstream testing equipment for air-fuel ratios. 4 Estimating the air-fuel ratio using the theory of the composition of high-coke mixed gas: The high-coke ratio is the ratio of the blast furnace gas flow rate to the coke oven gas flow rate. Assuming that the current high calorific value ratio is 7:3 (with moisture in the air ignored in the calculations), the theoretical air-fuel ratio can be determined based on the composition of the gas mixture (primarily consisting of CO, H2, and CH4). The theoretical amount of air required is: Amount of air = 1.77 (m3/m3). With an air excess factor of 1.05, the actual amount of air required becomes: Amount of air = 1.77 × 1.05 = 1.86 (m3/m3). When the high calorific value ratio of the gas mixture is 7:3, the air-fuel ratio is 1.86. The theoretical calculated air-fuel ratio uses the value before the mixing of blast furnace gas and coke oven gas, and factors such as gas pressure changes, moisture content, and impurities are also taken into account; therefore, the theoretically calculated value is only an approximation. Practice has shown that combining the calculation of the air-fuel ratio using a high focal ratio with several other methods results in rapid response and eliminates a significant amount of time required for optimization. The rolling mill of Laiwu Iron and Steel Co., Ltd. combined two methods – theoretical estimation of the air-fuel ratio based on the composition of mixed gas with a high coke ratio and a multi-objective expert optimization algorithm – and applied them to the primary reheating furnace, achieving good control results. Theoretical calculation of the air-fuel ratio requires no additional equipment, is simple to perform, and is cost-effective to use as a reference value. The flow rates of blast furnace gas and coke oven gas can be measured using the flow meters prior to mixing. The control concept of the 5-objective expert optimization algorithm is as follows: in situations where parameters such as the calorific value of gas and pressure are unstable, multiple factors affecting combustion are taken into account. The heating rate of the furnace temperature should be appropriate (it can be fast or normal), the heating rate of the flue gases should be within a certain range, the furnace pressure should also be within a specified range, and the heating rate of the hot air should meet certain criteria. Only when all these conditions are satisfied is it possible to achieve the \"optimal air-fuel ratio\". When the computerized combustion control system starts operating, the average air-fuel ratio currently used to control the furnace is taken as the base value; the \"expert optimization system\" then searches for an appropriate air-fuel ratio based on changes in factors such as furnace temperature, temperatures at the upper and lower parts of the flue gases, furnace pressure, and hot air. When the air-fuel ratio is appropriate, the heating and temperature maintenance curves are good; the \"expert optimization system\" does not operate, and this state is maintained with no changes in gas flow rate, hot air flow rate, or furnace pressure ； When the calorific value and pressure of the gas change, the expert optimization system’s inference engine uses the expertise stored in the database to determine the direction in which the gas amount should be increased or decreased, as well as the amount by which it should be adjusted, thereby finding the \"optimal air-fuel ratio\". The advantage of the multi-objective expert optimization algorithm is that it eliminates the need to use zirconia and calorimetry analyzers; the disadvantage is that its feedback time and data accuracy are not as good as those of zirconia and calorimetry analyzers. However, the concept of optimization algorithms has been widely recognized in combustion control and is increasingly applied in practice. 6 Applications of Fuzzy Control Technology: As fuzzy control technology continues to develop and improve, it is being utilized more and more in the combustion control of heating furnaces. The commonly used one is a 2D fuzzy controller, which takes the error and the rate of change of the error as inputs, with one output. Multidimensional fuzzy controllers (three dimensions and above) take into account not only the error but also the rate of change of the error and the rate of change of that rate of change; theoretically, this enables more precise control. However, as the number of input dimensions for fuzzy controllers increases, it becomes increasingly difficult to select control rules, and the corresponding control algorithms also become more complex. Jigang’s medium plate plant uses a two-input one-output fuzzy controller to determine the air-fuel ratio. Taking the increment ΔΤ of the furnace temperature (ΔΤ=Τi-Τi-1) and the optimization step size from the previous cycle, ui-1, as inputs, the output is the optimization step size for the current cycle, ui. Substitute into the formula: Appropriate gas volume = Current gas volume + Gas adjustment direction × Coefficient × Step size. Using a search method with variable step sizes can improve the search speed and reduce search losses. If the step size remains constant and is small, the convergence speed is slow, making it difficult to adapt to certain uncontrollable disturbances ； As the step size increases, the search loss rises, and oscillations may occur as well, preventing convergence, which should be avoided. When near an extreme point, which is reflected in a small rate of change in temperature difference, a small step size search can be used.