Wood Moisture-Content Measurement Accuracy of Impregnated and Nonimpregnated Wood

The influence of the impregnation process of pine wood (Pinus sylvestris L.) samples on the electrical resistance changes and the moisture-content measurement accuracy is presented in this paper. In this study, the resistances of impregnated and nonimpregnated green pine timber harvested from northern Poland were compared. An impregnation method based on a vacuum-pressure chamber was used. Copper salts were applied as the impregnated solutions. The obtained results of the electrical resistance comparison showed a dependence of wood resistance on the moisture content. Higher conductivity occurred in impregnated wood samples filled with copper salt compared with wood samples without impregnation. Noticeable differences in the electrical resistance values were observed when the wood moisture content was significantly above the Fibre Saturation Point (FSP).

Capacitive Online Corn Moisture Content Sensor Considering Porosity Distributions: Modeling, Design, and Experiments

An online corn moisture content measurement device would be a key technology for providing accurate feedback information for industrial drying processes to enable the dynamic tracking and closed-loop control of the process. To overcome the problem of large measurement error caused by the characteristics of the corn flow state and the pore distribution when a parallel plate capacitor is applied to the online moisture content measurement process, in this study, we summarized the constraint conditions of the sensor’s structure parameters by mathematical modeling and calculated the optimal sensor design size. Moreover, the influence of porosity variation on moisture content measurement was studied by using the designed sensor. In addition, a mathematical model for calculating corn moisture content was obtained for the moisture content range of 14.7% to 26.4% w.b., temperature of 5 °C to 35 °C, and porosity of 38.4% to 44.6%. The results indicated that the fluctuation in the online moisture content measurement value was obviously reduced after the porosity compensation. The absolute error of the measured moisture content value was −0.62 to 0.67% w.b., and the average of absolute values of error was 0.32% w.b. The main results provide a theoretical basis and technical support for the development of intelligent industrial grain–drying equipment.

Sensitivity of PR2 Capacitance Soil Moisture Meter for Irrigation Scheduling

Accurate soil moisture content measurement is essential for designing a robust irrigation scheduling and integrated water resources management (I.W.R.M.). Capacitance-based sensors have widely been used to monitor soil moisture at different measuring depths coupled with continuous and instantaneous outputs. This study's objective was to evaluate the PR2 capacitance moisture meter's performance on mineral and organic soil water content. The outputs of PR2 in m3 /m3 and vol.% were compared with gravimetrically measured soil moisture. The R.M.S.E. measurement at Site A at the first and second replicates increased from 0.49% to 0.67%. In contrast, the r2 value of 0.99 was obtained for the two replications when comparing the soil moisture content observed from gravimetric measurement and the automated outputs from the PR2 Probe soil monitor. The R.M.S.E. values were 0.48%, and 1.32% were estimated for the first and second replications at Site B. The result indicates that the PR2 Profile Probe could be a reliable alternative to other time-consuming, complex computer algorithms for accurate point measurement of soil moisture.

Sensitivity of PR2 Capacitance Soil Moisture Meter for Irrigation Scheduling

Accurate soil moisture content measurement is essential for designing a robust irrigation scheduling and integrated water resources management (I.W.R.M.). Capacitance-based sensors have widely been used to monitor soil moisture at different measuring depths coupled with continuous and instantaneous outputs. This study’s objective was to evaluate the PR2 capacitance moisture meter’s performance on mineral and organic soil water content. The outputs of PR2 in m3/m3 and vol.% were compared with gravimetrically measured soil moisture. The R.M.S.E. measurement at Site A at the first and second replicates increased from 0.49% to 0.67%. In contrast, the r2 value of 0.99 was obtained for the two replications when comparing the soil moisture content observed from gravimetric measurement and the automated outputs from the PR2 Probe soil monitor. The R.M.S.E. values were 0.48%, and 1.32% were estimated for the first and second replications at Site B. The result indicates that the PR2 Profile Probe could be a reliable alternative to other time-consuming, complex computer algorithms for accurate point measurement of soil moisture.

Analysis of Wood Chip Characteristics for Energy Production in Lithuania

Wood chips and logging residues currently comprise the largest share of biomass fuels used for heat generation in district heating plants and are provided by a variety of suppliers. Ash and moisture contents, as well as the calorific value, may vary considerably depending on the composition of the fuel, seasonality, location, and other factors. This paper provides the summarized results of the main characteristics of wood chip moisture and ash content and calorific value, experimentally tested for a significant range of samples. Chip samples were collected from two district heating companies and tested for a significant range of samples. Chip samples were collected from two district heating companies and tested for a 3-year period. The data on fuel chip prices were taken from the electronic wood chip trading platform. The tests were performed using standard express methods, where two sub-samples were taken and analyzed from every chip sample. It was determined that the moisture content of the wood chips varied from 35% to 45%, the calorific value from 18.4 to 19.6 MJ/kg, and the ash content from 0.5% to 4.5%. The calculated relative expanded uncertainty of the moisture content measurement was ±2.1%, of calorific value—±1.5%, and of ash—±1.0%. The repeatability of the results was estimated as the pooled standard deviation.

Sensor Node Network for Remote Moisture Measurement in Timber Based on Bluetooth Low Energy and Web-Based Monitoring System

This paper proposes an IoT system based on wireless BLE connectivity to monitor the moisture content of wood, using a compact and low-cost moisture device that relies on a resistance measurement method valid for an ultra-wide range of resistance values. This device is digitally controlled with a BLE-incorporated micro-controller characterized by its small size and low power consumption, providing long-life battery. The proposed system consists of two main parts: first, the BLE moisture device including the moisture content measurement and wireless capability (BLE); second, the cloud-based monitoring platform, providing remote visualization and control for all the sensor nodes of the network. The complete infrastructure shows how multiple nodes can read and transmit moisture content of timber in buildings using small and unattended devices, with data saved in a central database and monitored by multiple commercial devices such as PC, smartphone, tablet, etc. The proposed system is innovative, scalable and low cost, and it can be deployed in wooden buildings and the wood industry, providing a practical solution that will help to avoid rot and other damaging effects caused by the moisture content.