•2D spectrogram images of the recorded signals are created.•Reflection and transmission signals are used in the moisture content of a grain type.•S11 and S21 scattering parameters are obtained in the ...frequency range of 1–2.4 GHz.•The developed CNN models are used to determine the moisture content for grain types.•Present first application of CNN models to estimate moisture content in flowing grain.
In order to preserve the stored grain for a long time without deterioration, the moisture content must be accurately known. In this study, the moisture content of flowing grain was determined using radar spectrogram data and CNN structure. A free-space measurement technique-based experimental environment was established for the purpose of collecting the necessary signals to measure the moisture content. The measurement plant is composed of two horn antennas, a vector network analyzer (VNA), and a flowing grain mechanism. In the experimental environment, the S11 and S21 parameter values are recorded from the VNA. The short-time Fourier transforms (STFT) of the recorded signals were then taken, and 2D spectrogram images were created. The dataset, comprising 22,780 images, was split into 80 % for training and 20 % for testing; then, they were subjected to regression analysis using CNNs. First, the mean absolute error (MAE) values of the 27 pre-trained CNN architectures in a single epoch are calculated. Subsequently, the architecture with the best four regression results is automatically selected. The training and testing steps are performed independently for each selected architecture, and the results are recorded. The MAE, root mean square error (RMSE), mean square error (MSE) and mean absolute percentage error (MAPE) metrics are employed to assess the efficacy of the CNN architectures. Among these, ResNet50 is the architecture that yields the most favorable results. Subsequently, a subsequent architecture with fewer parameters and a more expeditious processing time is proposed. The novel deep-learning CNN architecture demonstrated superior performance compared to the pre-trained architectures. The results are as follows: MAE = 0.0411, MSE = 0.0149, RMSE = 0.122, and MAPE = 0.0397. When comparing the time spent on training and testing, the least time-consuming architecture required approximately 72 min, whereas this study was completed in approximately 325 s. The pronounced disparity is readily apparent. The results demonstrate that when the CNN is appropriately modeled and trained, the combination of CNN and appropriate signal processing can effectively determine the moisture content of grains.
The Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey. SMAP will make ...global measurements of the soil moisture present at the Earth's land surface and will distinguish frozen from thawed land surfaces. Direct observations of soil moisture and freeze/thaw state from space will allow significantly improved estimates of water, energy, and carbon transfers between the land and the atmosphere. The accuracy of numerical models of the atmosphere used in weather prediction and climate projections are critically dependent on the correct characterization of these transfers. Soil moisture measurements are also directly applicable to flood assessment and drought monitoring. SMAP observations can help monitor these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing will also reduce a major uncertainty in quantifying the global carbon balance by helping to resolve an apparent missing carbon sink on land over the boreal latitudes. The SMAP mission concept will utilize L-band radar and radiometer instruments sharing a rotating 6-m mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these observations with advanced modeling and data assimilation to provide deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP is scheduled for launch in the 2014-2015 time frame.
Moisture-related microbial growth is a key factor contributing to food spoilage in developing countries. Dehydration or drying of food reduces the moisture content supporting this microbial growth, ...thereby addressing this problem. Hence the moisture content of food materials is a key factor influencing the quality of storage thereby reducing post-harvest loss and is thus very important for the farmers.
Current moisture measurement techniques (both destructive and non-destructive) available do not take into account the inherent difficulties in the context of developing countries including the relatively high instrumentation cost, unreliable power supply, specificity of the measurement method to food type, and training and maintenance requirements, among others. This paper includes a review of the existing moisture content measurement methods followed by an evaluation of their applicability for this proposed application in developing countries.
Key Findings and Conclusions: A few recently developed instruments show promise but there is little research on how small-scale farms and co-operatives in developing countries can achieve a safe standard for their dried foods. Of these, two potential methods, equilibrium relative humidity and infrared imaging, were identified as promising techniques, but further research and development would be needed to make them suitable for use in small-scale operations in developing countries.
•Study presents review of common moisture content measurement methods.•Current techniques do not consider inherent difficulties in developing countries.•Analysis conducted to determine feasible methods for developing country applications.•Equilibrium relative humidity and infrared imaging identified as promising techniques.
Currently, near-surface soil moisture at a global scale is being provided using National Aeronautics and Space Administration's (NASA's) Soil Moisture Active Passive (SMAP) and European Space ...Agency's (ESA's) Soil Moisture and Ocean Salinity (SMOS) satellites, both of which utilize L-band (1.4 GHz; 21 cm wavelength) passive microwave remote sensing techniques. However, a fundamental limitation of this technology is that the water content can only be measured for approximately the top 5-cm layer of soil moisture, and only over low-to-moderate vegetation covered areas in order to meet the 0.04 <inline-formula> <tex-math notation="LaTeX">\text{m}^{3}/\text{m}^{3} </tex-math></inline-formula> target accuracy, limiting its applicability. Consequently, a longer wavelength radiometer is being explored as a potential solution for measuring soil moisture in a deeper surface layer of soil and under denser vegetation. It is expected that P-band (wavelength of 40 cm and frequency of 750 MHz) could potentially provide soil moisture information for the top <inline-formula> <tex-math notation="LaTeX">\sim 10 </tex-math></inline-formula>-cm layer of soil, being one-tenth to one-quarter of the wavelength. In addition, P-band is expected to have higher soil moisture retrieval accuracy due to its reduced sensitivity to vegetation water content and surface roughness. To demonstrate the potential of P-band passive microwave soil moisture remote sensing, a short-term airborne field experiment was conducted over a center pivot irrigated farm at Cressy in Tasmania, Australia, in January 2017. First results showing a comparison of airborne P-band brightness temperature observations against airborne L-band brightness temperature observations and ground soil moisture measurements are presented. The P-band brightness temperature was found to have a similar but stronger response to soil moisture compared to L-band.
The Soil Moisture Active Passive (SMAP) mission, which is the newest L-band satellite that is specifically designed for soil moisture monitoring, was launched on January 31, 2015. A beta quality ...version of the SMAP radiometer soil moisture product was recently released to the public. It is crucial to evaluate the reliability of this product before it can be routinely used in hydrometeorological studies at a global scale. In this paper, we carried out a preliminary evaluation of the SMAP radiometer soil moisture product against in situ measurements collected from three networks that cover different climatic and land surface conditions, including two dense networks established in the U.S. and Finland, and one sparse network set up in Romania. Results show that the SMAP soil moisture product is in good agreement with the in situ measurements, although it exhibits dry or wet bias at different network regions. It well reproduces the temporal evolution and anomalies of the observed soil moisture with a favorable correlation greater than 0.7. The overall ubRMSE (unbiased root mean square error) of SMAP product is 0.036 m 3 · m -3 , well within the mission requirement of 0.04 m 3 · m -3 . The error sources of SMAP soil moisture product may be associated with the parameterization of vegetation and surface roughness but still needs to be tested and confirmed in more extent. Considering that the algorithms are still under refinement, it can be reasonably expected that hydrometeorological applications will benefit from the SMAP radiometer soil moisture product.
This study describes a low-cost sensor-based scheme for online moisture measurement in transformer oil. Considering a harsh environment, moisture measurement of oil at ppm level is challenging, so ...the sensor should be highly sensitive and thermally and chemically stable. The conventional methods are mostly offline, have long test times and are costly. A thin-film parallel plate capacitive moisture sensor has been fabricated using inexpensive materials to measure the moisture of fresh, aged and 0.5% water content oil samples. The moisture sensing film is highly hydrophilic and is made of alumina oxide, a very stable material. Experiments were conducted to determine the response parameters of the sensor in the presence of moist nitrogen gas, the concentration of which was measured by a commercial SHAW dew point meter. Experiments were also performed to measure the moisture of different oil samples in the laboratory. Results show that the output of the sensor is sensitive (6 pF/ppm moisture), has negligible hysteresis (∼1% at 1 kHz) and has fast response and recovery times (Tres = 70 s, Trec = 170 s).
Validation is an important and particularly challenging task for remote sensing of soil moisture. A key issue in the validation of soilmoisture products is the disparity in spatial scales between ...satellite and in situ observations. Conventional measurements of soil moisture are made at a point, whereas satellite sensors provide an integrated area/volume value for a much larger spatial extent. In this paper, four soil moisture networks were developed and used as part of the Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) validation program. Each network is located in a different climatic region of the U.S., and provides estimates of the average soil moisture over highly instrumented experimental watersheds and surrounding areas that approximate the size of the AMSR-E footprint. Soil moisture measurements have been made at these validation sites on a continuous basis since 2002, which provided a seven-year period of record for this analysis. The National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) standard soil moisture products were compared to the network observations, along with two alternative soil moisture products developed using the single-channel algorithm (SCA) and the land parameter retrieval model (LPRM). The metric used for validation is the root-mean-square error (rmse) of the soil moisture estimate as compared to the in situ data. The mission requirement for accuracy defined by the space agencies is 0.06 m3/m3. The statistical results indicate that each algorithm performs differently at each site. Neither the NASA nor the JAXA standard products provide reliable estimates for all the conditions represented by the four watershed sites. The JAXA algorithm performs better than the NASA algorithm under light-vegetation conditions, but the NASA algorithm is more reliable for moderate vegetation. However, both algorithms have a moderate to large bias in all cases. The SCA had the lowest overall rmse with a small bias. The LPRM had a very large overestimation bias and retrieval errors. When site-specific corrections were applied, all algorithms had approximately the same error level and correlation. These results clearly show that there is much room for improvement in the algorithms currently in use by JAXA and NASA. They also illustrate the potential pitfalls in using the products without a careful evaluation.
Moisture accumulates with the growing aging progress of oil-paper insulation and further shortens the remaining life of the transformer. The frequency-domain spectroscopy (FDS) technique can be used ...to realize the moisture estimation. However, the moisture estimation results would be unreliable once the aging effect on FDS was ignored. Given this issue, an alternative model including the aging effect is thus proposed using FDS and intelligent algorithm. In this work, the feature parameters of FDS data are used to build the databases for characterizing the aging degree and moisture. Then, the moisture estimation models are developed using the weighted K-nearest neighbor (K-NN) algorithm. The accuracy and applicability of the proposed models are finally discussed in laboratory and field conditions. In that respect, the findings reveal that the reported model is available for moisture estimation of transformer oil-paper insulation under various aging degrees and test temperatures.
Moisture is one of the most significant parameters that can accelerate ageing in paper/pressboard insulation. In order to understand the impact of moisture and ageing on Frequency Domain Spectroscopy ...(FDS) measurements, oil impregnated pressboard samples of different moisture contents are prepared and aged at 105°C temperature. FDS measurements on pressboard samples are carried out at different ageing time. Other measurements such as moisture, degree of polymerization (DP), Furan and Dissolved Gas Analysis (DGA) are also performed on oil and pressboard samples. It is observed that FDS measurements on pressboard samples are mostly influenced by the moisture contents. Several other pressboard samples are prepared under different conditions to determine how FDS measurements are affected by moisture, aged oil and ageing of pressboard sample considering each of the parameter individually as well as in different combinations. Results suggest that FDS measurements are sensitive to the change in moisture, ageing products and ageing of pressboard (DP) sample. However, impact of ageing products and ageing of pressboard sample (DP) on FDS measurements are smaller in comparison to moisture.
Recently, 2-frame interdigital fringe-field (ID-FF)-based capacitive sensors have been widely employed for soil moisture measurement. The present challenge with this design is to achieve both ...penetration depth and sensitivity simultaneously. In this work, keeping the electrode contour area fixed, multi-frame ID-FF capacitive soil moisture sensors are proposed and designed to enhance sensitivity and penetration depth, simultaneously. A theoretical model for capacitance is extended to a multi-frame configuration. The estimated capacitance from this extended theoretical model is compared against simulation results and found to be well-correlated. Multi-frame ID-FF configurations with 2, 3, 4, 6, 8, and 9 frames are used to develop single-sided (s-s) and dual-sided (d-s) ID-FF capacitive soil moisture sensor models. Simulation results show an increase in the sensitivity and penetration depth with reference to the generic 2-frame ID-FF capacitive sensor configuration. The models with distinct multi-frame configurations and an associated signal-conditioning circuit are also fabricated. Experiments for sensitivity indicate an average error of less than 6% with reference to simulation, which is lower than that reported in the recent literature. One of the fabricated sensors is calibrated using the thermogravimetric method. The performance of the fabricated sensors is then compared with a standard commercial sensor with respect to the thermogravimetric method and is found to meet the expected requirements with a correlation coefficient of 0.997.
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