Daniel Ronnow

Determining moisture content (MC) in wood chips finds its application in many industries including energy production. In this letter, we aim to develop an automated method for determining MC in woodchips using ultra-wideband (UWB) radio signals and machine learning algorithms. Firstly, to acquire UWB signals through wood chips on conveyor belts in industrial plants, we use measurement devices with a radio transmitter and receiver, and a laser sensor to determine the thickness of the wood chips. UWB and laser data corresponding to 1923 samples from four power plants is acquired. Secondly, we extract the amplitude and delay-based features, and these are finally, fed to three different machine learning algorithms namely; linear regression, artificial neural network (ANN), and ensemble trees to determine the MC. The proposed method achieves best results when the ANN is used. More specifically, our method achieves a mean absolute error (MAE) of 2.75% when the features from both UWB and laser sensors are used for determining MC. MAE of 3.95% is achieved when features only from UWB data (without the laser) are used for determining MC. Our results for industrial data suggest that the proposed method is effective for determining MC in industrial applications.

Digital twins are an emerging technology that can be harnessed for the digitalization of the industry. Steel industry systems contain a large number of electro-hydraulic components as proportional valves. An input–output model for a water proportional cartridge valve was derived from physical modeling based on fluid mechanics, dynamics, and electrical principles. The valve is a two-stage valve with two two/two-way water proportional valves as the pilot stage and a marginally stable poppet-type cartridge valve as the main valve. To our knowledge, this is the first time that an input–output model was derived for a two-stage proportional cartridge valve with a marginally stable main valve. The orifice equation, which is based on Bernoulli principles, was approximated by a polynomial, which made the parameter estimation easier and modeling possible without measuring the pressure of the varying control volume, in contrast with previous studies of similar types of valves situated in the pilot stage part of the valve. This work complements previous studies of similar types of valves in two ways: (1) data were collected when the valve was operating in a closed loop and (2) data were collected when the valve was part of a press mill machine in a steel manufacturing plant. Model parameters were identified from data from these operating conditions. The parameters of the input–output model were estimated by convex optimization with physical constraints to overcome the problems caused by poor system excitation. For comparison, a simple linear model was derived and the least squares method was used for the parameter estimation. A thorough estimation of the parameters’ relative errors is presented. The model contains five parameters related to the design parameters of the valve. The modeled position output was in good agreement with experimental data for the training and test data. The model can be used for the real-time monitoring of the valve’s status by the model parameters. One of the model parameters varied linearly with the production cycles. Thus, the aging of the valve can be monitored.

Digital twins are an emerging technology that could be harnessed for the digitalization of the industry. Steel industry systems contain a large number of electro-hydraulic components, as proportional valves. An input-output model for a novel water proportional cartridge valve is derived from physical modelling based on fluid mechanics, dynamics, and electrical principles. The valve is a two-stage valve with two 2/2-way water proportional valves as the pilot stage and a marginally stable poppet-type cartridge valve as the main valve. The orifice equation, which is based on Bernoulli principles, is approximated by a polynomial which makes parameter estimation easier and makes modelling possible without measuring pressure of the varying control volume situated in the pilot stage part of the valve. Data were collected when the valve was operating as a component in a closed-loop system as part of a press-mill machine in a steel manufacturing plant. Parameter estimation was made by convex optimization with physical constraints to overcome problems caused by poor system excitation. For comparison, a simple linear model was derived and the least squares method used for parameter estimation. A thorough estimation of the parameters relative errors is presented. The model contains 5 parameters related to the design parameters of the valve. The modelled position output is in good agreement with experimental data for training and test data. The model can be used for real time monitoring of the valve’s status by the model parameters. One of the model parameters varies linearly with production cycles. Thus, aging of the valve can be monitored.

A measurement system for the measurement of microwave dielectric properties of mineral compounds at temperatures up to +1000°C is presented. It includes the simultaneous measurement of mass and temperature. Samples volumes in the range 0.01 to 0.1 m ³ can be studied. The system comprises a heat reaction chamber on a mass scale with mounted ultra-wideband (UWB) radio sensors and temperature probes. The complex refractive index is determined from the UWB signals using a technique with windowing to suppress interference and fitting of a modelled signal to the experimental ones. The developed method is validated by measuring the complex refractive index of water from +82°C down to +23°C and comparing with literature values. The systems is used to study calcination of limestone, i.e. the chemical decomposition of CaCO ₃ to CaO and CO ₂ when heated up to +1000°C. The chemical decomposition is clearly seen as a decrease in mass and as significant changes in the complex refractive index. The system could be used also for other mineral compounds and other types of materials.

The complex microwave permittivity—including anisotropy- of wood chips of softwood has been measured for different moisture contents in the band 0.75 to 2.5 GHz using an ultra-wide band radio transmission technique. The real and imaginary parts increase monotonically with moisture content. The wood chips are oriented by gravity, which gives anisotropic permittivity. The anisotropy ratio of the real part increases from 1.1 to 1.6 with moisture content from 0 to 120%. The anisotropy ratio of the imaginary part is around 2.5 at all moisture contents. Effective medium models were used to model the permittivity. The Bruggeman, and two versions of the Maxwell Garnett model gave good results at low moisture content (below the fiber saturation point). Above the fiber saturation point only the Bruggeman model gave results in agreement with experiments. The difference in model performance suggests that the free water does not follow the wood chips geometry.

An ultra-wide band measurement method for determining the complex refractive index of large-volume objects is presented. The method is intended for industrial non-destructive testing. It uses a frequency-domain technique in which transmitted radio pulses are analyzed and the effects of near field and coupling on the determined refractive index are compensated. Measurements were performed in an industrial setup with electromagnetic sensors buried in the object. The results are presented for woodchips as an object. The refractive index was experimentally determined in the frequency range 0.5-3.0 GHz. Additionally, we designed and manufactured planar quasi-differential elliptical-antennas as electromagnetic sensors. The results from the industrial measurement setup were compared with the results of the laboratory setup, in which the sensors were placed outside the test box and near field and coupling effects could be neglected. The complex refractive index determined for the two setups was in good agreement, which corroborates the proposed method for compensating for coupling and near-field effects. The complex refractive index of woodchips changes with the moisture content. It is experimental verified using the industrial setup that the moisture content can be determined with a 2 percent error.

We present a printed lens for radar applications. The structure of the presented lens consists of an array of modified micro-strip lines, which is positioned in the antenna’s aperture on the same planar substrate. Simulations show that the gain and directivity increase with the proposed lens in a wide band frequency band. The proposed design is insensitive to rotation of the antenna. This paper focuses on real industrial applications and problems. Further, we show that the lens can be used to improve the object detection ability of an ultrawide band radar system, which is used in industrial applications such as non-destructive monitoring of built-structures and for use in the renovation process. The signal to noise ratio is improved. Furthermore, we show how the microwave lens can also be used to reduce the clutter in applications where the complex refractive index of objects is determined. Further, different simulated results (for different cases) are compared, presented and concluded.