Jörg Matthes

Source localization by spatially distributed electronic noses for advection and diffusion

Based on continuous concentration measurements from spatially distributed electronic noses, the location of a point source is to be determined. It is assumed that the emitted substance is transported by advection caused by a known homogeneous wind field and by isotropic diffusion. A new two-step approach for solving the source localization problem is presented. In the first step, for each sensor i, the set of points P/sub i/ is determined, on which the source can lie, taking only the specific concentration measurement C/sub i/ at sensor i into account. In the second step, an estimate for the source position is evaluated by intersecting the sets P/sub i/. The new approach overcomes the problem of poor convergence of iterative algorithms, which try to minimize the least squares output error. Finally, experimental results showing the capability of the new approach are presented.

Constrained Ellipse Fitting with Center on a Line

Fitting an ellipse to given data points is a common optimization task in computer vision problems. However, the possibility of incorporating the prior constraint “the ellipse’s center is located on a given line” into the optimization algorithm has not been examined so far. This problem arises, for example, by fitting an ellipse to data points representing the path of the image positions of an adhesion inside a rotating vessel whose position of the rotational axis in the image is known. Our new method makes use of a constrained algebraic cost function with the incorporated “ellipse center on given line”-prior condition in a global convergent one-dimensional optimization approach. Further advantages of the algorithm are computational efficiency and numerical stability.

Optimal weighting of networked electronic noses for the source localization

Based on concentration measurements from spatially distributed electronic noses, the location of a point source is to be determined. It is assumed that the emitted substance is transported by advection caused by a known homogeneous wind field and by diffusion. A new two-step approach for solving the source localization problem is presented. The new approach overcomes the problem of poor convergence of iterative algorithms, which try to minimize the least squares output error An optimal weighting strategy is introduced, which yields to approximate maximum-likelihood estimates for the source position.

Combustion plant monitoring and control using infrared and video cameras

Abstract For an optimal combustion of fuels with changing properties advanced control strategies based on a continuous process monitoring are necessary. The monitoring is performed by cameras in conjunction with an automatic image analysis to provide additional information for the adaption. In this paper we discuss the capabilities and limitations of video and infrared camera for monitoring and control at the example of grate firing plants and rotary kilns. The software system INSPECT is introduced which provides the online image analysis for an camera aided combustion control.

Model based source localisation by distributed sensors for point sources and diffusion

Abstract The inverse problem of locating a point source of an emission based on measurements from spatial distributed sensors is studied for isotrope diffusion. Equivalent localisation problems concern heat sources or pollution sources. A new two-step approach with the steps: estimation of a scalable sensor-source-distance for each sensor and estimation of the source position using these distances is presented. In contrast to conventional one-step approaches for solving the nonlinear least squares output error problem by iterative algorithms, the new approach is not sensitive to local minima.

Camera based Identification and Control of the Waelz Process

TheWaelz process is the most common technique for the pyro-metallurgical treatment of zinc-bearing residues using a rotary kiln. However, this process will only result in a good zinc recovery, if the temperature of the material (slag) within the kiln is controlled at specific optimal setpoints depending on the material mixture. Until now, slag temperature measurement is carried out by pyrometers which give only pointwise information that can be disturbed by cold slag lumps. Additionally, the temperature control is performed only manually by operators, who have to adapt the amount of process air frequently to keep the process stable at the desired setpoints. In this paper an infrared-camera based measurement of the slag temperature using image processing techniques is presented. Based on that temperature measurement a process model is conducted. Its parameters are estimated by a model-output-error based process identification. The process model is used for the tuning of parameters of an automatic closed loop control. Finally, results from an industrial application of the new camera based slag temperature control are given.

A Structure from Motion Approach for the Analysis of Adhesions in Rotating Vessels

While processing material in rotating vessels such as rotary kilns, adhesions on the inner vessel wall can occur. Large adhesions usually affect the process negatively and need to be prevented. An online detection and analysis of adhesions inside the vessel during operation could allow the process control to deploy counter-measures that prevent additional adhesions or reduce the adhesions sizes. In this paper, we present a new method that enables an image-based online detection, tracking and characterization of adhesions inside a rotating vessel. Our algorithm makes use of the rotational movements of adhesions in a structure from motion approach which allows for the measurement of the positions and heights of adhesions with a single camera. The applicability of our method is shown by means of image sequences from a rotating vessel model as well as from an industrially used cement rotary kiln.

Source localization with a network of electronic noses

A new two-step approach for locating an emission source is presented. It is based on an analytical diffusion-advection model and on pointwise concentration measurements from a network of stationary spatially distributed electronic noses (EN). In the first step, for each EN the set of points is determined, on which the source can lie, taking only the concentration measurement from the particular EN into account. In the second step, an estimate for the source position is evaluated by intersecting these sets. The new two-step approach overcomes the problem of poor convergence and multiple solutions of iterative algorithms, which minimize the output error of the model. Finally, experimental results are given, that show the capability of the new approach.

Identification and Control of the Waelz Process Using Infrared Image Processing

Today, the recycling of zinc from zinc-bearing residues is mostly done by the pyro-metallurgical Waelz process in a rotary kiln. The optimum recovery rate is only achieved, if the temperature of the slag within the kiln is controlled at optimal values. These optimal temperatures vary and depend on the material mixture. The slag temperature is measured by pyrometers so far. They yield only pointwise measurements that can be erroneous due to cold slag lumps. The control of the slag temperature takes place manually by experienced operators, who adapt the process air to stabilize the process at the desired temperature setpoint. The paper presents a slag temperature measurement system with an infrared camera and an image processing system. It contains an automatic motion based slag detection. Using the camera based measurements, a process model for the Waelz process is derived and its parameters are estimated by a process identification. Using the process model the controller parameters are optimized by minimizing a cost functional. The sensitivity of the cost functional with respect to the controller parameters is analyzed. The optimized automatic closed-loop control is finally demonstrated at an industrial Waelz kiln.

Image-Based Characterization of Alternative Fuel Combustion With Multifuel Burners

Many industrial high-temperature processes such as cement production employ multifuel burners in order to achieve the required energy input with low-cost alternative fuel. So far, a constant operation of multifuel burners with high fractions of alternative fuel (>70%) is not possible due to inherent fluctuating fuel properties. Energy input and product quality are directly affected by varying points of combustion time, different scattering of fuel, and insertion of unburned fuel or chemical substances into the product. We propose an image-processing system based on infrared images that detects the alternative fuel streakline and derives parameters for the characterization of the flight and burning behavior. Using these parameters, an adjustment of the burner settings depending on the fluctuating fuel properties can be carried out. This automatic monitoring and control of the combustion process allows an increased use of alternative fuels in constant operation. Experimental data from a rotary kiln for cement clinker production are used to validate the image-processing system.