Configure Oil, Gas, and Petroleum Multi-Sensors with a Delta-Sigma ADC
The solution to high-precision multi-sensor electronics lies with the high-resolution analog-to-digital converter (ADC). The thermocouple, RTD, pressure sensors, and high-speed multi-channel delta-sigma (ΔΣ) ADC combination creates a high-precision, robust, multi-sensor system for oil, gas, and petroleum electronics. This design solution introduces issues associated with achieving a precise temperature and pressure cell interface with a ΔΣ ADC. The application circuit uses a pressure, thermocouple, and RTC sensor to achieve a single-device comprehensive conversion.
Multi-sensor configurations for oil, gas, and petroleum measurements continually acquires sensitive pressure and thermal data. However, capturing the various combinations of physical temperature and pressure entities requires a very concise, high-resolution system.
This is challenging for designers, as the high-resolution sensor circuitry required spreads across wide ranges of temperature and pressure. In most cases, multi-sensor electronics are too large for factory application and discrete analog signal conditioning are not precise or rugged enough (Figure 1).
The solution to multi-sensor electronics lies with the high-resolution ADC. The combination of thermocouple, RTD, pressure sensors, and ADC are attainable with a precise, high-speed, multi-channel delta-sigma analog-to-digital converter (ΔΣ ADC), where the key specification is RMS noise. This creates a high-precision, robust multi-sensor system for oil, gas, and petroleum electronics.
This design solution briefly discusses the issues associated with achieving a precise temperature and pressure cell interface using a ΔΣ ADC.
Figure 1. Pressure safety valve protects a piping system from overpressure.
The pressure measurement device classifications are those that require electrical excitation and those where pressure is the only source of power. The mechanical style devices include bellows, diaphragms, bourdons, tubes, and manometers. With these devices, a change in pressure initiates a mechanical reaction, such as a change in the position of mechanical arm or a tube’s liquid level.
Electrically excited pressure sensors are synergistic with ΔΣ ADCs and microcontrollers. These styles of sensors can be capacitive sensors, linear variable differential transformers (LVDT) or piezoresistive. Most typically, the piezoresistive sensor is the sensor of choice (Figure 2).
Figure 2. A piezoresistive pressure sensor (a) with an electrically excited resistive bridge model (b).
In Figure 2a, the fabricated sensor’s top side is a resistive material and the bottom is a diaphragm.
The high side of the piezoresistive bridge model (Figure 2b) requires a voltage or current excitation. The magnitude of excitation effects the dynamic range of the output of the sensor, the maximum difference between VOUT+ and VOUT- in a 3.3V system generally ranges from 10s of millivolts to several hundred millivolts. Electronics, which follow the bridge sensor using amplifiers and an ADC, change the differential output signal to digital representation.
The Importance of Temperature Sensing
There are numerous types of temperature sensors that are appropriate to any application in terms of temperature range, linearity, accuracy, ruggedness, and ease of use. The temperature sensors in this application monitor the pressure sensor’s temperature to ensure that reliable pressure readings occur. To perform this temperature measurement, this application uses a K-type thermocouple and resistive temperature device (RTD) (Figure 3).
Figure 3. A two-lead TYPE-K thermocouple requires a second temperature measurement with the RTD for cold-junction-compensation (CJC).
In Figure 3, the rugged thermocouple temperature sensor can sense high temperatures up to +1260°C, while the RTD measures the temperature at the thermocouple/copper junctions.
With ADCs, there is a very strong tradeoff between resolution and speed. Of the fastest converters, the pipeline ADC can produce data rates in speeds of tens of giga-samples-per-second (Gsps) while producing respectable resolutions up to 12 bits. The middle-of-the-road ADC is the successive-approximation-register (SAR) converter. This converter produces samples at an output slower than the pipeline converter around 10ksps to 10Msps and at an increase in resolution up to 18 bits. The SAR converter is a good industry workhorse, if the acceptable input voltage least-significant-bit (LSB) sizes are in microvolts (µV). However, if the application needs conversions of LSB sizes in the nanovolts (nV) region, the only feasible alternative is a ΔΣ ADC (Figure 4).
Figure 4. A block diagram of a basic ΔΣ ADC.
The ΔΣ ADC in Figure 4 receives the input voltage into a modulator. The modulator creates a one-bit, noise-shaped, pulse train that represents the analog input voltage. The converter then accumulates the one-bit pulse train and through oversampling, performs a variety of digital filtering on the signal. With time, the filter rejects higher frequency noise and produces multi-bit results as high as 24 bits. The converter sends these results to the output terminal of an external microcontroller.
The ΔΣ modulator starts the ADC’s noise reduction process. Close examination of this modulator quickly reveals where the ΔΣ label comes from in Figure 5.
Figure 5. The 2nd-order ΔΣ modulator comprises of a feedback system containing a front-end Δ function followed by two integrators (Σ function).
In Figure 5, after the two integrators, the signal goes converts through a 1-bit ADC with a sample rate equaling FS and then feeds back through a 1-bit DAC with the same sample rate to the inputs of the two integrators. In this system, there is an injection of quantization noise (ei) with the 1-bit ADC. Per the formula at the bottom of Figure 5, the noise appears at the output along with noise from previous conversions.
The modulator generates a noise-shaping effect on the accumulation of the signal at the modulators output. This noise shaping effect shapes the 1-bit conversion quantization noise into higher frequencies (Figure 6).
Figure 6. The noise at the output of the modulator creates a noise-shaped response.
In Figure 6, the Nyquist frequency for the system is the modulator’s sampling frequency (FS).
The order of the modulator determines the level of the quantization noise over frequency (Figure 7).
Figure 7. The noise-shaping capability of a 1st-order, 2nd-order, and 3rd-order modulators.
In Figure 7, the quantization noise of the lower order modulators is higher near DC and lower at high frequency. The ΔΣ ADC collects or oversamples the modulators 1-bit output stream and exercises lowpass digital filtering.
With the ΔΣ ADC core there are two actions that occur to reduce system noise. The modulator successfully shapes its quantization noise to higher frequencies and the digital/decimation filter attenuates the high-frequency noise.
The ADC’s output data rate, as dictated by the following digital lowpass filter cutoff frequency, is FD. The frequency response of the digital/decimation filter (dashed line, Figure 4) successfully attenuates the higher frequency noise.
The Complete ΔΣ ADC Picture
A complete working ΔΣ ADC at the core requires a ΔΣ modulator, Sinc, and FIR digital filters (Figure 8).
Figure 8. A complete working ΔΣ ADC with pressure sensor and temperature sensor inputs.
In the core ΔΣ ADC block diagram (Figure 4), there is a digital/decimation filter. The actual ΔΣ ADC in Figure 8 has the common Sinc and FIR digital filters which completes the converter’s low-noise picture.
The Sinc digital filter performs a lowpass filter function. A 1st order filter design settles in one data-word period. The 4th order Sinc filter or Sinc4 settles in four data-word periods. The frequency domain filter shape appears with dips over frequency (Figure 9).
Figure 9. The frequency response of a 3rd order Sinc filter (Sinc3).
In Figure 9, the lowest attenuation can be programmed to match convenient frequencies such as multiples of 50Hz or 60Hz. The device in Figure 8 implements a Sinc4 digital filter.
The rounded characteristics of Sinc digital filters is one of the simplest digital filters to implement and it is very useful in mixed signal applications. However, there are applications where sharper corners are preferable. The FIR filter offers sharper corners with an added benefit of stability. The ΔΣ ADC in Figure 8 has a 50Hz/60Hz filter that provides > 90dB rejection at 50Hz and 60Hz at a data rate of 16sps.
The complete ΔΣ ADC (Figure 8) has additional auxiliary functions, such as an input multiplexer, programmable gain amplifier (PGA), complex digital filter, clock generator, and reference matrix. With a PT100 RDT, a 160µA current source, and a PGA gain of 128, the MAX11410 ±100°C input range is to 1.234V to 2.837V. With this 24-bit converter in a Sinc4 configuration, the voltage LSB size is 0.039µVRMS. The temperature accuracy over the ±100°C range and RTD accuracy is ～4.7µ°C/bit.
This design soluiton presents issues associated with achieving a precise temperature and pressure cell interface with a ΔΣ ADC for oil, gas, and petroleum electronics. The application circuit uses a pressure, thermocouple and an RTC sensor to achieve a single device comprehensive conversion, where the key specifications are noise, an input multiplexer, and BOM cost.
A similar version of this design solution originally appeared in EDN on August 31, 2020.