Diagnostic techniques for the monitoring and control of practical flames

Provided is a display input device including: a touch panel (1) which displays and inputs an image; an oscillation sensor (proximity sensor (12)) which detects an oscillation of a detection object against the touch panel (1); an oscillation correction unit (304) which executes an oscillation correction if the oscillation of the detection object detected by the oscillation sensor exceeds a predetermined amount; and a control unit (3) which deforms an image in a display region of a certain range displayed on the touch panel, according to the position of the detection object which has been subjected to the oscillation correction.

Display input device

A controller operable to control an array of processing elements comprises a retrieval unit operable to retrieve instruction items for each of a plurality of instructions streams, each instruction stream having a plurality of instructions items, a combining unit operable to combine the plurality of instruction streams into a serial instruction stream, and a distribution unit operable to distribute the serial instruction stream to an array of processing elements.

Parallel data processing apparatus

The present invention is directed to perform fine low-voltage control without largely increasing the circuit layout area in a low-power consumption structure. In the case of shifting a region to a low-speed mode, a system controller outputs a request signal and an enable signal to a power switch controller and a low-power drive circuit, respectively, to turn off a power switch and to perform a control so that the voltage level of a virtual reference potential becomes about 0.2 V to about 0.3V. The region operates on voltages between a power supply voltage and a virtual reference potential, so that it is controlled in the low-speed mode.

Semiconductor Integrated Circuit Device

In this paper, the possibility of visualization of three-dimensional (3-D) temperature distributions in large-scale boiler furnaces from radiative energy images captured by multiple charge-coupled device (CCD) cameras mounted around the furnace is studied numerically. For the calculation of the radiative energy image formation, a fast algorithm proposed by the authors for pinhole imaging is used in this paper, which is based on the Monte Carlo method and combined with a concept of angular factor effective for image formation. This algorithm is applicable for the emitting, absorbing, and isotropic scattering medium. For the inversion of the 3-D temperature distributions which is an ill-posed problem, a modified Tikhonov regularization method is improved, where the finite difference regularizer is defined and can be used in 3-D cases, and the optimal regularization parameter is suggested to be selected by using a post-treatment method. For a 3-D unimodal temperature distribution, the numerical simulation results show that the reconstruction errors for the 3-D temperature distribution can be maintained at levels similar to the measurement error and the visualization quality of the temperature distribution is satisfactory. For a kind of bimodal temperature distribution, the reconstruction errors are higher than those for the unimodal distribution, but the bimodal feature of the temperature distribution can also be reproduced clearly.

Visualization of three-dimensional temperature distributions in a large-scale furnace via regularized reconstruction from radiative energy images: numerical studies

A method for predicting unburnt carbon in a coal-fired utility boiler has been developed using an image processing technique. The method consists of an image processing unit and a furnace model unit. The temperature distribution of combustion flames can be obtained through the former unit. The latter calculates dynamics of the carbon reduction from the burner stages to the furnace outlet using coal feed rate, air flow rate, and the chemical and ash content of the coal. An experimental study in the Sendai Power Station of Tohoku Electric Company Inc. shows that the prediction error of the unburnt carbon can be reduced to 10%. The results show that the unburnt carbon prediction algorithm could be widely used for evaluation, optimization and diagnosis of combustion systems for various boiler and coal types. >

Prediction method of unburnt carbon for coal fired utility boiler using image processing technique of combustion flame

PURPOSE: To execute the process control by using a model of a distributed parameter system plant by inpputting a variable for constituting a physical expression of the model to a physical expression of a lumped constant forming model, deriving the state quantity of the process by executing an operation, and deriving a manipulated variable by using this state quantity CONSTITUTION: The system is constituted by providing a target value predictive system 2 for deriving a predictor of a target value of a vapor temperature of a thermal power plant 1, a vapor temperature predictive system 3 for deriving a predictor of the vapor temperature and a manipulated variable determining system 4 for determining a manipulated variable according to the predictor of the target value and the predictor of the vapor temperature, a model tuning system 5 for tuning a parameter of a model for predeicting the vapor temperature, and a switch 6 for selecting whether the predictor of the predictive system is used, or a controlled variable is used directly The target value predictive system 2, the vapor temperature predictive system 3, the manipulated variable determining system 4 and the switch 6 are realized by a second master control controller 1200 of a predictive control system COPYRIGHT: (C)1994,JPO&Japio

Adaptive control method for process and control system for process

PROBLEM TO BE SOLVED: To provide a predictive control unit for processes which has a short adjustment period and high performance of predictive control. SOLUTION: A steam temperature prediction part 310 has a prediction part 330 and a switching part 332 which feeds one of a predicted value Ys and a plant output value (controlled variable) Y as its output back to a controller 320 and a parameter adjustment part 340, which consists of a controller model 346 simulating the function of a controller 320, a controlled system model 344 simulating the function of a controlled system 100, a predicting function model 350 simulating a prediction part 330, a model adjustment part 342 which adjusts the parameters of the controlled system model 344 and predicting function model 350, and a parameter optimization part 348 which determines the parameters Kc and Tc of the controller 320 and the prediction time interval τs of the prediction part 330. COPYRIGHT: (C)2000,JPO

Predictive control unit

PURPOSE:To automatically and precisely optimize a control parameter by correcting the control parameter of a feedback controller until it reaches a parameter target value which is previously set by a knowledge processing. CONSTITUTION:The feedback controller tuner 6 of an auto-tuner 4 corrects the control parameter of the feedback controller (PI controller). The feed forward controller tuner 7 of the auto-tuner 4 corrects the control parameter of a feed forward controller 3. At that time, the control parameter of the feedback controller 1 is corrected until it reaches the parameter which is previously set by the knowledge processing, for example. Thus, the control parameter can be optimized and can automatically be adjusted. Then, the fluctuation of the deviation of a controlled system can be suppressed to a minimum when the target value changes or when disturbance is impressed. Namely, the control parameter at the time of using feed forward control and feedback control together can automatically be optimized.

Feed forward/feedback controller

PROBLEM TO BE SOLVED: To describe higher-order blocks in a simple and easy-to-see state. SOLUTION: At the time of describing hierarchical macros 112a and 112b with a same function in higher-order block graphics 11b and 11c, the same input signal 23 and output signal 24 are described as a name in the input/output terminal of each macro. When the macros 112a and 112b use the medium-order block graphic 12b in common, the same signals 23 and 24 as the macros 112a and 112b in the graphic 12b. When large macros 111a and 111b belonging to the graphic 12b are provided with the same function and both of the use a low-order bloc graphic 13b, the names of the same input and output signals 25 and 26 as the macros 111a and 111b in the graphic 13b.

Kimura Toru

Papers

Prediction method of unburnt carbon for coal fired utility boiler using image processing technique of combustion flame

Adaptive control method for process and control system for process

Predictive control unit

Feed forward/feedback controller

Hierarchy description method for control circuit