Automatic fault detection in a low cost frequency domain (capacitance based) soil moisture sensor
Introduction
In irrigation management, there are varied techniques for determining the water requirements of a crop. These measuring techniques include the determination of water requirements by obtaining the volume of water based on a water balance. In general, these techniques can be divided into direct measurement or indirect measurement of the water requirements of a crop. An example of the first technique is lysimetry (Schaetzl and Rothstein, 2016). In this case, there is a direct measuring of a parameter (weight, volume, pressure, among others) that is varying over time. The indirect techniques are based on indirect measurement of the parameters of the water balance. The indirect determining of soil water balance in a crop can be obtained by several techniques: remote sensing (Maes et al., 2016); use of plant sensors (Torres et al., 2016); use of meteorological sensors (Gao et al., 2016) among others and a combination of the previous cited. Another technique for determining the water balance based in indirect measurements is the measuring of soil moisture. The use of soil-based water measurements is used in a various devices (Ojha et al., 2015, Jaguey et al., 2015, Navarro-Hellin et al., 2015, Tarange et al., 2015). The ultimate objective of these techniques is to provide farmers with information about the most appropriate volumes of irrigation to apply in each phenological period of the crop, depending on the desired yield levels and other parameters. For determining soil moisture, a great range of sensors are used (Vienken et al., 2013).
There is a wide range of electrically based soil moisture measurement techniques well established in the fields of geophysical surveying (Linck and Fassbinder, 2014, Lehmann et al., 2014) and agronomy (Fatas et al., 2014, Baghdadi et al., 2014), These include resistivity based methods such as the Wenner (Jiao-Jun et al., 2014) and Schlumberger Arrays (Mosuro et al., 2012); capacitance based methods such as Frequency Domain Reflectometry (FDR) (Al-Asadi and Mouazen, 2014, Jaria and Madramootoo, 2013); Time Domain Reflectometry (TDR) (Janik et al., 2014); as well as Radiation based techniques such as the Neutron Probe (Kodikara et al., 2014). Whilst low cost implementations of resistive based sensors have been suggested in the past (Austin and Rhoades, 1979, Igboama and Ugwu, 2011), commercial implementations of these units (for example the Landviser® Landmapper®, that include interpretation software for vertical electrical properties of the soil) are expensive (typically $500–$1600), lack integrated data-logging capabilities, or are simply unavailable.
Frequency Domain Reflectometry (FDR) or the frequency domain capacitance probe, is used to determine the moisture content of soils. The principle of operation of the Frequency Domain capacitance probe relies on the fact that the dielectric constant between water and air differs by a factor of 80. Thus the presence of water in the soil between the probe plates produces a highly significant change in its capacitance, the higher the water concentration, the higher the capacitance. This capacitance can then be measured by electrical means. As the probe is electrically insulated, there is no direct current flow within the soil, and thus the conductive effect of ion based salts in the soil is minimized. However different soil types can be expected to display different properties (Hanson and Peters, 2000).
These capacitance based probes are critically dependent on the insulation provided between their plates. Should this become damaged, the sensor would give erroneous results, which could however still appear to be in normal operational range. This would lead to erroneous irrigation decisions.
This paper investigates how this damage can be automatically detected despite the individual readings appearing to be within normal ranges. For this purpose, a low cost Frequency Domain sensor system was designed and implemented in an experimental plot. The manuscript includes, firstly, the description of the two electrical methods that are used to determine the effective capacitance of the probe for the designed sensor system. Moreover, the description of five experiments to illustrate the fault detection in the designed sensor system will be developed. Subsequently, the obtained results in the five cited experiments are discussed. Finally, some conclusions about the experiments and the possibilities of the employment of this device for irrigation management are added.
Section snippets
Material and methods
A low cost Frequency Domain sensor system for measuring the soil moisture was designed and implemented and this is described in detail in Vázquez de León et al., 2015. For the experiments in soil (Experiments 2, 4 and 5 that are explained below), an insulated probe was used inserted vertically with its top buried 3 cm into a hi-silica, clay based soil in an experimental plot without crops. The location of the cited soil of the experimental plot is latitude: 37° 57′ 29.60″N and longitude: 0° 48′
Results and discussion
Fig. 2 shows the clearly linear relationship between the Time to Charge or Discharge for the capacitor against the value of the Capacitance. This is not at all surprising, the difference in the slopes being a feature of the different resistances though which the current must flow. It also shows the near-linear relationship between the rescaled reciprocal of the signal strength and the capacitance, however it is clear that the rSS125 plot (reciprocal of Signal Strength at 125 kHz) is the
Conclusions
By utilising two different capacitive measurement techniques on the same probe, one based on a fixed frequency principle the other on a variable frequency, distinction of experimental conditions can be determined.
In terms of raw resolution, the fixed frequency Signal Strength technique is more sensitive to dry soil conditions than the variable frequency Time to Charge/Discharge technique.
By looking at the ratio of Time to Charge vs Time to Discharge, it can be determined if the probe or sensor
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