Performance Comparison of Three Density-Independent Calibration Functions for Microwave Moisture Sensing in Unshelled Peanuts during Drying

HighlightsReal-time, free-space transmission measurements of relative complex permittivity in unshelled peanuts during dryingDynamic application: temperature, density and moisture content changing during dryingThree density-independent calibration functions evaluated for accuracy in real-time moisture content determinationReal-time moisture content determination with standard error of performance (SEP) = 0.55% moisture content for all calibration functionsCalibration function most commonly used with microwave moisture sensor was determined to be most accurate; SEP = 0.448% moisture contentAbstract. A microwave moisture sensor, developed within USDA ARS, has been used to determine moisture content in unshelled peanuts during drying. Relative complex permittivities of the peanuts obtained from free-space transmission measurements at 5.8 GHz are used for the moisture determination. Due to variations in density caused by drying, it is advantageous to estimate moisture content independent of bulk density. Therefore, moisture content was estimated with three density-independent calibration functions to assess which one provided optimal accuracy. One of the functions is based on the measured attenuation and phase shift, and the other two are permittivity based (one of which is commonly used with the microwave moisture sensor). The sensor was calibrated for peanut pod moisture content determination over a temperature range of 10°C to 40°C and a moisture content range of 6.5% to 19% wet basis (w.b.). Statistical analysis showed high coefficients of determination (r2), = 0.97 for the calibration with each function. Peanut pod moisture content was determined with the sensor in real-time as peanuts dried, and estimated moisture content was compared to the reference oven drying method. While the standard error of performance (SEP) for the three functions was = 0.55% moisture content, the calibration function most commonly used with the microwave sensor was observed to be the most accurate (SEP = 0.448% moisture content). Microwave sensing is a viable solution for nondestructive, real-time determination of moisture content in peanuts in dynamic situations such as drying. Keywords: Complex permittivity, Dielectric properties, Free-space measurements, Microwave sensing, Moisture content, Peanut drying.

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Estimating Energy Costs of Nonbeneficial Dryer Operation by Using a Peanut Drying Monitoring System

Applied Engineering in Agriculture ◽

10.13031/aea.12624 ◽

2018 ◽

Vol 34 (3) ◽

pp. 491-496 ◽

Cited By ~ 1

Author(s):

Micah A. Lewis ◽

Samir Trabelsi ◽

Stuart O. Nelson

Keyword(s):

Relative Humidity ◽

Moisture Content ◽

Real Time ◽

Monitoring System ◽

Electric Energy ◽

Monitoring Systems ◽

Moisture Sensor ◽

M 10 ◽

Average Size ◽

Moisture Content Determination

Abstract. Knowledge of kernel moisture content during peanut drying is important to ensure that the bed of peanuts is dried appropriately. However, the lack of a commercially available, industry-accepted solution for real-time kernel moisture content determination during peanut drying makes its detection cumbersome and laborious. Samples of unshelled peanuts are extracted from the semitrailer by an operator periodically, and the samples have to be cleaned and shelled to determine kernel moisture content with the official meter. A peanut drying monitoring system that includes a microwave kernel moisture sensor, developed within the USDA ARS, provides a means for monitoring in-shell kernel moisture content in real-time. The system determines kernel moisture content with a standard error of prediction (SEP) of 0.55% moisture content when compared to the reference oven-drying method. During recent peanut harvest seasons, peanut drying monitoring systems were placed in 13.7-m (45-ft) drying semitrailers, one 3 m (10 ft) from the front of the trailer and the other 3 m (10 ft) from the back of the trailer. As the peanuts dried, pod and kernel moisture content, temperature of the drying peanuts, temperature and relative humidity of the air exhausted from the peanuts, and temperature and relative humidity of the air being blown into the peanuts were measured every 12 seconds. The continuous data, provided by the monitoring systems, were useful in observing the loss of moisture by the peanuts throughout drying. The data also revealed periods of at least 3 hours during which dryer operation did not result in loss of moisture from the peanuts; thus, identifying nonbeneficial dryer operation. Such periods cause a peanut buying point to accumulate unnecessary expenses for propane and/or electric energy which can total up to $3,250 annually for an average-size buying point. Keywords: Dielectric properties, Energy cost, In-shell kernel moisture content, Microwave sensing, Peanut drying, Real-time monitoring, Sensors.

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Precision and accuracy in moisture content determination of wood fuel chips using a handheld electric capacitance moisture meter

Silva Fennica ◽

10.14214/sf.6993 ◽

2018 ◽

Vol 52 (5) ◽

Cited By ~ 1

Author(s):

Lars Fridh ◽

Lars Eliasson ◽

Dan Bergström

Keyword(s):

Moisture Content ◽

Calibration Function ◽

Drying Method ◽

Oven Drying ◽

Content Determination ◽

Accuracy And Precision ◽

Moisture Meter ◽

Capacitance Meter ◽

Moisture Content Determination

According to the Swedish Timber Measurement Act, measurements affecting payments for wood fuels to landowners must be accurate and precise. In this regard, moisture content is an important quality parameter for wood chips which influences the net calorific value as received and thus the economic value. As standard practice moisture content is determined with the oven-drying method, which is cumbersome to use for deliveries to facilities without drying-ovens, which in turn necessitates that samples are taken elsewhere for measurement. An alternative solution is to use a portable moisture meter. Our aim was to evaluate the precision of a handheld capacitance moisture meter. Accuracy and precision of a capacitance meter was determined in the lab and a calibration function was made. Thereafter, the calibrated moisture meter was compared with the standard method for moisture content determination of truckloads of chips. The capacitance meter showed a moderate accuracy by underestimating moisture content by 6.0 percentage points (pp), compared to the reference method, at a precision of Â±3.8 pp (CI 95%). For chips with Mâ>â50%, both accuracy and precision decreased. Calibration increased the accuracy in the follow up study by 3 pp for chips with Mâ<â50% but could not be made for wetter chips. The oven-drying method and the capacitance meter can provide equally accurate estimates of mean moisture content for chips with Mâ<â50% if a larger sample is taken with the latter. It should be possible to use capacitance meters to measure moisture content even when used to calculate payments depending of the needed accuracy. A calibration function for each assortment is needed.

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Low hydrogen SMAW electrode moisture content determination using electrical capacitance

Journal of Materials Engineering ◽

10.1007/bf02834069 ◽

1990 ◽

Vol 12 (2) ◽

pp. 159-165 ◽

Cited By ~ 1

Author(s):

D. E. Bunnell ◽

S. Liu ◽

D. L. Olson

Keyword(s):

Moisture Content ◽

Electrical Capacitance ◽

Content Determination ◽

Moisture Content Determination

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Determination of readiness for laying based on material moisture, corresponding relative humidity, and water release

Materials Testing ◽

10.1515/mt-2020-621012 ◽

2020 ◽

Vol 62 (10) ◽

pp. 1033-1040

Author(s):

Christoph Strangfeld ◽

Sabine Kruschwitz

Keyword(s):

Relative Humidity ◽

Moisture Content ◽

Embedded Sensors ◽

Residual Water ◽

Floor Covering ◽

Water Release ◽

Content Determination ◽

Two Samples ◽

Moisture Content Determination

Abstract The moisture content of the subfloor has to be determined before installation to avoid damage to the floor covering. Only if readiness for layering is reached, can an installation without damage be expected in all cases. In general, three approaches exist to measure residual water content: determination of moisture content, determination of water release, or determination of the corresponding relative humidity. All three approaches are tested under laboratory conditions at eight screed types including two samples thicknesses in each case. Moisture content and water release are measured by sample weighing, the corresponding relative humidity is measured by embedded sensors. All three approaches are compared and correlated. The evaluations show only a weak correlation and, in several cases, contradicting results. Samples are considered ready for layering and not ready for layering at the same time, depending on the chosen approach. Due to these contradicting results, a general threshold for a risk of damage cannot be derived based on these measurements. Furthermore, the experiment demonstrates that the measurement of corresponding relative humidity is independent of the screed type or screed composition considered. This makes humidity measurement a potentially very promising approach for the installation of material moisture monitoring systems.

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