Method and system for determining target gas concentration in fluid environment

Abstract

A system and method for determining a target gas concentration in a fluid environment using a gas sensor, the system and method improve the efficiency and accuracy of the measurement of the gas sensor by measuring the electrical characteristics of the gas sensor at different temperatures, measuring during transitions between a first temperature and a second temperature, making more frequent measurements, detecting when the gas sensor reaches equilibrium, and measuring the electrical characteristics of the gas sensor during transitions between the first temperature and the second temperature. Multiple sensors are used, offsets and drifts are taken into account, the time that the sensors are not real-time is reduced, various algorithms are used, or any combination thereof.

Description

This application is a divisional application of the Chinese patent application with application number 202080041349.3, application date April 6, 2020, and invention name "Method and system for determining the concentration of a target gas in a fluid environment." Technical Field

[0001] The present invention relates to systems and methods for determining the concentration of a gas in a fluid environment. Background Art

[0002] Many gas sensors are known in the art. The gas concentration can be measured by observing changes in the electrical properties of the sensor, such as current, voltage, capacitance, resistance, etc. Thus, resistive sensors, capacitive sensors, and semiconductor sensors (such as transistor or diode sensors) are known in the art.

[0003] As a specific example, thin film PdNi alloy resistors have been used to detect gases (such as hydrogen) and measure their concentrations. Hydrogen is soluble in PdNi, and the resistivity of thin film PdNi alloys increases when exposed to hydrogen, and the amount of increase is proportional to the square root of the hydrogen partial pressure. Some gas sensors (such as gas sensors with a PdNi lattice) may experience an increase in resistance or a change in capacitance or semiconductor properties as the H2 concentration increases. For example, the resistance may increase linearly in proportion to the square root of the hydrogen in the PdNi lattice (which in turn is related to the gaseous H2 pressure, as described by Sievert's law).

[0004] For a given application, a gas sensing system can be designed to detect the pressure of a target gas (e.g., H2). However, in addition to the target gas pressure, there may be factors that can affect the measurement results of the gas sensor. For example, the temperature of the gas sensor can affect the measurement results. To address this problem, a heater can be used to maintain the gas sensor within a desired temperature range. In addition to temperature, other factors may also affect the gas sensor measurement results, such as the bias voltage applied to the gas sensor or the overall pressure of the fluid environment. Due to baseline drift associated with aging and the presence of undesirable gases and the offset of sensor characteristics, these measurements are also prone to errors. For example, if a table is generated that associates the hydrogen partial pressure with the resistance of the sensor (assuming that these resistances are associated with the same sensor temperature), then due to the above example, these associations will no longer hold over time. The measurement results based on the table will therefore be in error. A solution to this problem is to use a system that performs calibration and performs gas measurements at two different temperatures.

[0005] Non-target gases (such as O2) can also affect the measurement results of gas sensors. The presence of non-target gases can affect or interfere with the target gas measurement results in at least two ways. First, since the sensor responds to both the target gas and the non-target gas, the sensor reading may be too high or too low. In this respect, the impact of non-target gases can be considered as an offset of the target gas reading. Secondly, the presence of non-target gases changes the way the sensor measures the target gas. For example, non-target gases can occupy receptor sites inside or on the surface of the lattice. This leaves fewer available receptor sites, thereby reducing the sensitivity of the sensor to the target gas. As another example, in a PdNi gas sensor, the presence of oxygen in the lattice may affect the resistance or capacitance characteristics of the sensor. Therefore, the lattice infiltrated by oxygen may respond to the presence of hydrogen in a different way than when the lattice is not infiltrated by oxygen. When oxygen infiltrates the lattice, the adsorption of hydrogen causes the formation of molecules such as H2O, OH, etc. These molecules themselves may affect the resistance or capacitance characteristics of the gas sensor.

[0006] One attempted solution for reducing the impact of non-target gases may be to use a barrier coating on the gas sensor to filter such non-target gases. However, such filtering may reduce the sensitivity of the gas sensor or increase the response time. Another attempted solution may be to use multiple gas sensors to specifically detect non-target gases to determine and illustrate the concentration information of the non-target gases. However, such a solution may be expensive and / or bring additional system complexity. Yet another attempted solution is to simply limit the gas sensing application to applications that do not include interfering gases. A solution to the drift problem is to repeatedly manually recalibrate the drifting sensor.

[0007] For the foregoing reasons, there is a need for methods and systems for accurately and efficiently measuring gas concentrations having advantages such as, but not limited to: reducing or eliminating the need for calibration requiring a reference gas; and maintaining or exceeding the accuracy, response time, and precision required for hydrogen measurement and hydrogen monitoring applications; while providing continuous or minimally interrupted readings. Summary of the invention

[0008] The present invention relates to methods and systems that can efficiently and accurately measure gas concentration or gas content in a fluid environment. These methods and systems include using devices and techniques that perform the following operations: measuring at different temperatures, measuring during the transition between a first temperature and a second temperature, performing more frequent measurements, detecting when a gas sensor reaches equilibrium, using multiple sensors, taking into account offsets and drifts, reducing the time when the sensor is not real-time, using algorithms, or any combination thereof. Therefore, the systems and methods of the present application reduce or eliminate the need for periodic calibration in some hydrogen measurement and hydrogen monitoring applications, physically achieve the accuracy, response time, and precision of current hydrogen measurement and monitoring products, and reduce or eliminate gaps in hydrogen reporting. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 It is an embodiment of the present invention.

[0010] Figure 2 The balanced detector is shown marking stable points in the data.

[0011] Figure 3A The operating principle utilizing two gas sensors is shown, where a multi-temperature (MT) sensor (a sensor used at two temperatures) can feed correction to a single temperature (ST) sensor (a sensor used at one temperature), and the ST sensor can feed stability information back to the MT sensor.

[0012] Figure 3B A flow chart is shown of a method of measuring gas concentration using a two-gas sensor system, wherein a first gas sensor is used at a single temperature and a second gas sensor is used at two temperatures.

[0013] Figure 3C A state machine for dual temperature sensor operation is shown, where LT is "low temperature state", ELT is "end of low temperature state", HT is high temperature state, and EHT is "end of high temperature state".

[0014] Figure 3D An example of dual sensor operation is shown.

[0015] Figure 4A Resistance measurements of a gas sensor exposed to various hydrogen concentrations are shown, where the temperature of the resistive sensing element is modulated by a sinusoidal curve throughout the test.

[0016] Figure 4B Shown with Figure 4A The magnitude-frequency response associated with the resistance measurement results.

[0017] Figure 4C It shows that hydrogen Figure 4BThe change in the amplitude-frequency response.

[0018] Figure 4D Shows the use of Figure 4C The calibration table in Figure 4B The hydrogen concentration was calculated from the data in .

[0019] Figure 4E Shows the use of Figure 4A and 4B The thermal sinusoidal operation method shown in Figure 2 measures the accuracy of hydrogen concentration.

[0020] Figure 5 The principle of two-sensor operation is shown, where each sensor operates in MT mode and the temperature transitions are staggered so that one sensor can always be real-time.

[0021] Fig. 6A Two isotherms associated with a gas sensor operating at two temperatures are shown, where each isotherm is defined by a piecewise calibration.

[0022] Figure 6B Shows Fig. 6A The difference between the two isotherms shown in , and how the Delta-R measurement can be looked up to generate a hydrogen reading.

[0023] Figure 6C A comparison of hydrogen measurement performance on the same set of data is shown. DETAILED DESCRIPTION

[0024] The detailed description set forth below in conjunction with the accompanying drawings is intended as a description of the present preferred embodiment of the present invention and is not intended to represent the only form in which the present invention can be constructed or utilized. This description sets forth functions and step sequences for constructing and operating the present invention in conjunction with the embodiments shown. However, it should be understood that the same or equivalent functions and sequences can be realized by different embodiments, and these different embodiments are equally intended to be included in the spirit and scope of the present invention.

[0025] The present invention relates to systems and methods for determining the concentration of a target gas in a fluid environment (such as the concentration of hydrogen in the fluid environment) by measuring changes in the electrical properties of the gas sensor at at least two different temperatures, as disclosed in U.S. Provisional Application No. 62 / 830,182 filed on April 5, 2019, which is incorporated herein by reference in its entirety. Measuring the electrical properties of a gas sensor at two different temperatures can be used to calculate the gas concentration or can be used to calibrate or correct the electrical property measurements of the gas sensor at a single temperature. Preferably, these systems and methods can determine the gas concentration continuously without losing accuracy. By way of example only, the system may include a gas sensor as described in U.S. Patent Application No. 14 / 624,400 filed on February 17, 2015, which is incorporated herein by reference in its entirety. Reference Figure 1 In some embodiments, the sensor tube includes a gas sensor, which in turn includes a tube core having a gas resistor, a temperature resistor and a heater, and the two gas sensors are connected to respective electronic board sets. The gas resistor can be a hydrogen resistor. The method for measuring gas concentration includes various techniques as described below, which can be used alone or in any combination thereof to improve the accuracy of measuring gas concentration in a fluid environment.

[0026] Two-temperature transient gas calculation characteristics

[0027] A method for improving gas concentration measurements in a fluid environment is to monitor system response (how the electrical characteristics (output) of the sensor change with sensor temperature and environmental conditions (input) by dynamically measuring the electrical properties (such as current, voltage, capacitance, resistance, etc.) of a gas sensor while the gas sensor is changing between two different temperatures. This two-temperature operation includes: the gas sensor is at a first temperature for a first period of time, transitions to a second temperature for a second period of time (first transition period), is at the second temperature for a third period of time, and transitions back to the first temperature for a fourth period of time (second transition period).

[0028] Alternatively, the gas sensor may transition to a third temperature during a fourth time period (second transition period). The third temperature may be the same as the first temperature, or the third temperature may be different from the first temperature. Preferably, if the second temperature is a temperature rise compared to the first temperature, the third temperature is a temperature drop. Conversely, if the second temperature is a temperature drop compared to the first temperature, the third temperature may be a temperature rise compared to the second temperature. Thus, the change in temperature may follow a waveform, but the amplitude and time period need not be the same.

[0029] During the transition period, the electrical properties of the gas sensor are also in a transient state, called a transient electrical response or simply a transient response. For example, a gas sensor may have a transient resistance response to a changing temperature, which can be analyzed to calculate real-time hydrogen readings, even during an unstable transient response. This can be done by analyzing the magnitude and / or phase of the response. The system response may include a transient response or may also be a response that is not transient, such as, for example, an instantaneous resistance change of a Pd sensor due to a change in temperature, since the resistance of any resistor will change with temperature. This may also create instabilities in the Pd sensor if the sensor contains hydrogen, and the hydrogen must then slowly enter or leave the lattice to reach a new equilibrium, which has secondary, time-dependent effects.

[0030] The transient electrical response, especially for hydrogen resistors, can depend heavily on the coating on the die. Multiple coatings / passivation layers are used on different elements of the die, such as between the palladium nickel lattice and the environment. Therefore, a coating that is permeable to hydrogen is selected so that the transient response can be more easily used to calculate the hydrogen concentration. The coating interferes with the movement of hydrogen from the measured environment into the sensor or from the sensor out to the measured environment, so the coating adds delay (i.e., increases the time constant) and affects the transient response. The thickness of the coating, the density of the coating, and multiple other parameters that are loosely or tightly controlled can affect this time constant. The delay or change in time can be used to help identify whether hydrogen is present. For example, if hydrogen is present, the step response of the hydrogen sensor may overshoot or undershoot as the die temperature changes. Since hydrogen is balanced, the balance between the sensor element (e.g., palladium nickel sensor) and the surrounding hydrogen may be disrupted, and it may take time for the system to reach equilibrium (i.e., when the measurement results stabilize). In other words, there is an equilibrium resistance or steady-state behavior that can be achieved in the lattice (e.g., the resistance that a gas sensor will achieve given a sufficient amount of time assuming that the hydrogen partial pressure and gas sensor temperature remain constant) and is a function of the hydrogen partial pressure in the surrounding environment. Changes in the hydrogen partial pressure in the environment are not immediately translated to the lattice, and it will take time to reach a new equilibrium based on factors such as the sensor temperature and the dielectric constant of the coating. This time can range from a few minutes to a few hours. The time required for the system to reach equilibrium can be controlled and can be advantageously used to measure and classify the environment. For example, the more hydrogen in the sensor, the longer it will take to reach equilibrium. By calibrating the transient response to a known hydrogen concentration, a model (such as the sinusoidal model described herein) can be developed to measure hydrogen based on the measured transient response.

[0031] Repeating thermal waveform characteristics

[0032] Rather than simply changing the temperature of the sensor from a first temperature to a second temperature, the temperature of the gas sensor is maintained in a constant state of change. Preferably, the temperature of the gas sensor can be repeatedly changed in a pattern called a repetitive thermal waveform. Therefore, the electrical characteristics of the gas sensor can be in a constant system response state to a repetitive thermal waveform (such as a sine curve). By continuously monitoring and measuring the transient response, the amplitude and / or phase of the transient response can be measured using a short-time Fourier transform (STFT) or wavelet analysis. Because the concentration of hydrogen affects the transient response, the frequency response can be used to measure hydrogen. The frequency response includes an amplitude-frequency response and a phase-frequency response. A table with an interpolation or regression function can be created using several calibration points related to the amplitude, phase, or both of the frequency response to the hydrogen concentration. The amplitude-frequency response is the amplitude of the frequency spectrum associated with the electrical characteristics of the response to the excitation. The phase-frequency response is the phase of the frequency spectrum associated with the electrical characteristics of the response to the excitation. Merely by way of example, a spectrum may be generated by recording data of the electrical characteristics of a response, sampling the data at a rate (sampling frequency) for a specific duration defined by the total number of samples (window length), and generating a discrete Fourier transform (DFT) using a fast Fourier transform (FFT) algorithm. The process of Fourier transforming a short-time segment of a signal is called a short-time Fourier transform (STFT). The sampling frequency and window length may be selected based on desired bandwidth, spectral resolution, processing delays, etc.

[0033] In conventional multi-temperature sensors, transitioning from one temperature to another can result in a destructive transient response, making the hydrogen measurement inaccurate for a period of time after the transition. Calculating the hydrogen concentration factor in the presence of a destructive transient response is very difficult. In a system using a repetitive thermal waveform approach, the system is continuously in a known and controlled thermal transient response state, and therefore, the system can be characterized due to the nature of the repetitive thermal waveform. The system can be nonlinear, but when modulated with a repetitive thermal waveform to excite the system, the amplitude and phase delay of the transient response can be correlated to the hydrogen concentration.

[0034] Preferably, the sinusoidal excitation has a single frequency, which makes the characterization of the system response in the frequency domain mathematically simpler than other repetitive waveforms that include multiple frequencies. It is observed that the system response to a thermal sine wave is nonlinear, so the response includes multiple frequencies. Methods of using multiple sine wave frequencies in the excitation are discussed later, but the frequency associated with each sine wave must be carefully selected. The system response with multiple frequencies included from a single frequency excitation is still superior to the system response to an excitation with multiple frequencies because each frequency component of the excitation will produce multiple frequency responses at the output, resulting in a complex mixing of frequencies in the response. For example, a repetitive waveform that causes a step change in temperature will result in a system response that includes a theoretically infinite number of sine waves, complicating the model implemented to calculate hydrogen from the response. In Figure 4A An example of the resistance response of a gas sensor excited by a thermal sine wave at various hydrogen concentrations is shown in . In this example, the sine wave period is 8 minutes, and the amplitude of the thermal waveform ranges from 50°C to 150°C. FIG. 4A to FIG. 4D The hydrogen concentration shown in FIG. 1 is the volume concentration when the background gas is nitrogen at 1 absolute atmosphere pressure.

[0035] A model can be created that utilizes a calibration table based on the system response in order to benefit from the baseline drift removal advantages of a multi-temperature system without the negative downtime side of not being able to accurately count hydrogen (or at least having difficulty doing so) during transients created by temperature transitions. For example, by using the STFT of the transient response with a window length equal to the number of samples contained within one cycle of a repetitive thermal waveform (and in this example, a sine wave (8 minutes)), the amplitude associated with the fundamental frequency of the excitation can be measured over time. Figure 4B An example of such a calculation based on a transient response is shown in Figure 4A A transfer function or calibration table may then be created that relates gas concentration to a frequency response (such as an amplitude frequency response and / or a phase frequency response). Figure 4C Shown based on Figure 4B The calibration table for hydrogen is generated from the amplitude-frequency response data of Figure 4C ), Figure 4B The data can be used to generate hydrogen readings. Figure 4D Shown in.

[0036] The long-term accuracy of the model may be affected if the underlying system response changes. For example, foreign particles deposited on the sensor will slow the response time, effectively changing the characteristics of the sensor. Without some method to compensate for this, the accuracy of the hydrogen readings will degrade. (See Figure 4E) In addition, while there are no gaps in the hydrogen calculations due to temperature transitions, changes in hydrogen concentration that share frequency components with the fundamental frequency of the excitation can affect the hydrogen calculations, causing undesirable spikes in the readings. Therefore, when these transitions occur, it may be beneficial to add additional filtering and / or other signal processing techniques (such as masking the hydrogen readings) until the environment stabilizes to minimize or eliminate these spikes. This effect can be seen in Figure 4D , where large spikes in the hydrogen readings can be seen as the applied hydrogen concentration transitions from one value to another. Additional filtering and signal processing (including masking) can be used to minimize or eliminate these spikes.

[0037] For single sensor applications using this model, there are several ways to correct for changes in the system response (i.e., changes in the time constant). One approach is to have the end user apply a known partial pressure of a gas (e.g., hydrogen) to the sensor, allow the device to generate a certain frequency response, and use this data to mathematically apply corrections to the existing frequency response calibration table. This process can be repeated with additional known hydrogen partial pressures to achieve better accuracy. It is assumed that this manual calibration will be performed less frequently than a single temperature sensor to maintain hydrogen measurement performance. Another approach is to allow the device to switch to a two-temperature operating method automatically or in an externally triggered manner. For this method, accurate hydrogen readings can be captured. The device will then switch back to the thermal repetitive waveform, obtain a new frequency response, and mathematically apply corrections to the existing frequency response calibration table. One assumption is that the hydrogen partial pressure to which the sensor is exposed is constant throughout this process. Another assumption is that this process is performed infrequently and will provide better performance in some applications than a sensor that only utilizes the two-temperature method. While there may still be gaps in the hydrogen readings during the switch to the two temperature operating method, these gaps are less frequent than with the two temperature operating method, or may be triggered when there is an acceptable amount of time for gaps in the hydrogen readings to occur.

[0038] There are several methods to reduce or remove the effects of hydrogen transitions that contain frequency components in the sensor response. As discussed previously, when using the amplitude-frequency response calibration table ( Figure 4C ), these shared frequency components cause large errors in the hydrogen calculations (in Figure 4D). One way to mitigate this effect is to simply mask the final hydrogen calculation if a large change in the hydrogen calculation is detected. The disadvantage is that there will be gaps in the readings, especially when the hydrogen partial pressure around the sensor is more dynamic. An alternative approach is to modulate the temperature of the sensor with multiple sine waves at a specific target frequency, amplitude, and phase. The final repetitive thermal waveform consists of the superposition of each sine wave, which means that the waveform is defined as the sum of sine waves, where each sine wave can be described by its amplitude, frequency, and phase. The system response to this waveform consists of the superposition of the system response (output) to each sine wave that makes up the thermal waveform (input). If the frequencies of the thermal waveform input are sufficiently separated (meaning there are low frequency waveforms and high frequency waveforms), common signal filtering techniques (such as bandpass filtering or notch filtering) can be used to distinguish the output corresponding to each input frequency. In order to calculate hydrogen, each frequency has a corresponding frequency response calibration table. It was found in experiments that lower frequency excitations have better resolution in hydrogen measurements, but share more frequency components with hydrogen transitions, resulting in larger errors during transitions. If multiple frequencies are used, the device can switch to using data from a higher frequency excitation when a transition is detected by analyzing the stability of the frequency response of the lower frequency excitation. When it is determined that the system is stable again, the device will switch back to using data from the lower frequency excitation.

[0039] The disadvantage of using multiple excitation frequencies in a thermal repetitive waveform is that the total energy of the system response must be conserved and shared among all the generated frequencies. The generated frequency response corresponding to each frequency contains only a portion of the signal energy of the frequency response of the single frequency (single sine wave) excitation. This reduces the signal-to-noise ratio (SNR) of the final hydrogen calculation. The signal energy can be increased by increasing the temperature variation (amplitude, or maximum and minimum temperature) of the thermal excitation. However, this is limited by physical factors (maximum temperature of the material, ambient temperature, etc.).

[0040] By way of example only, the temperature variation range may be from about 30 degrees Celsius to about 180 degrees Celsius. Preferably, the temperature variation range is from about 35 degrees Celsius to about 180 degrees Celsius. More preferably, the temperature variation range is from about 40 degrees Celsius to about 180 degrees Celsius. Through experiments, it was found that the greater the temperature variation (sinusoidal amplitude), the higher the hydrogen sensitivity using the amplitude-frequency response. This makes it easier to distinguish hydrogen partial pressures and results in lower noise in the final calculation. However, because the sensor's response to hydrogen varies with temperature (the system's time constant decreases with increasing temperature), the system response becomes distorted. That is, when the sensor is excited using a thermal sinusoid, the phase of the resistance for a constant applied hydrogen is not constant. The phase delay increases during the sinusoidal trough (temperature is at its lowest value), while the phase delay decreases during the sinusoidal peak (temperature is at its highest value). In addition, the sensitivity of the sensor varies with the sensor temperature. The result of these effects is a distortion of the thermal sinusoid used for excitation, which is composed of multiple harmonics in the resistance response.

[0041] The system may include a control loop and a feedback loop to control the temperature cycle. The control loop continuously tracks a sinusoidal shaped time wave through a sinusoidal method. The temperature sensor measures the temperature of the die, and the temperature measurement is fed into a digital control loop. The heater may be adjusted so that the correct heat is output to achieve the desired temperature of the gas sensor. The heater may be controlled by a controller to use a constant transient, so any waveform may be used, including a sawtooth wave, a square wave, or any random waveform.

[0042] In some embodiments, the period of the waveform may not be fixed. In some multi-temperature embodiments, the repeating waveform does not have a fixed period. In some dual-temperature embodiments, the repeating waveform may or may not have a fixed period. In some embodiments, the amplitude, phase, waveform, and period may not be consistent over time. While the sinusoidal curve has some use, if the system is driven by a heater and the gas environment to which the hydrogen sensor is exposed is measured, different tools can be used to analyze the response.

[0043] In a linear system, when excited at one frequency, the output contains only the same single frequency. Since the system of the present application is nonlinear, one frequency input results in multiple frequency outputs (responses). Therefore, the present invention uses a pure sine wave to induce the response of the hydrogen sensor, which will be different in amplitude, phase and may contain multiple frequencies of low amplitude or power, but the changes will diagnose the hydrogen concentration. However, the fundamental frequency of the hydrogen sensor will follow the frequency of the temperature change (system excitation) and its amplitude should be related to the original waveform (i.e., the driving waveform). Since the system is nonlinear, higher frequency harmonics will also appear, but the fundamental frequency will match the fundamental frequency (lowest frequency component) of the temperature modulation. This system does not have a gap during the transient caused by temperature where the gas concentration cannot be calculated. Therefore, unlike traditional gas sensors, which will take several minutes to respond between temperatures and then wait for a minute or more before another real-time hydrogen reading can be taken; for the sine system, the gas measurement results are real-time and can be continuous because the sensor temperature is continuously modulated by the thermal waveform. Therefore, continuous hydrogen measurement can be performed. In other words, the measurements are made in seconds, as opposed to periodic hydrogen measurements with gaps of an hour or more between measurements.

[0044] An important aspect is the difference between applying a strong heating waveform to the die and observing the response of the hydrogen resistor. If there is no hydrogen, the response of the hydrogen resistor can be a proportional copy of the driving waveform in time and frequency. There is almost no offset or distortion. If the gas sensor is placed in a hydrogen environment, differences in the waveforms will be seen. These differences are associated with the time constants for hydrogen to pass through the coating or for the hydrogen sensor to reach equilibrium with its environment. As the temperature of the Pd substrate changes, hydrogen is forced to enter or leave the lattice and pass through the coating. The rate at which hydrogen passes through the coating and the hydrogen resistor reaches equilibrium with its environment can be used. All of these physical processes take time. Some of them are very fast, but others are within the operating frequency used for measurement. Given some applied hydrogen conditions, the amplitude-frequency response and phase-frequency response of the sensor depend on the system behavior, which also determines the time constant. A calibration table can be generated based on this information.

[0045] Having two different temperatures at which hydrogen concentration measurements can be made enables calculations or measurements with minimal or no drift or offset. However, under the given environmental conditions discussed previously, the use of a sinusoidal temperature waveform enables real-time and continuous hydrogen concentration readings with minimal or no drift. Therefore, measurements of hydrogen concentration can be determined in real time and with minimal or no gaps due to the response to temperature transitions. In conventional sensors, reliable measurements are determined at the end of a cycle in order to give the system time to reach equilibrium. In this case, a means for determining whether the sensor has reached equilibrium is needed. With a sinusoidal waveform, the gas sensor no longer needs to reach equilibrium before determining a gas concentration measurement.

[0046] Thus, in some embodiments, a method for determining a target gas concentration in a fluid environment includes: exposing a gas sensor to the fluid environment, the gas sensor having an electrical characteristic that varies with the concentration of the target gas concentration; modulating the temperature of the gas sensor, wherein the modulation takes the form of a repetitive thermal waveform that induces a system response (e.g., a transient response) in the electrical characteristic; during the step of modulating the temperature of the gas sensor, monitoring the electrical characteristics; and calculating the target gas concentration based on a frequency response of the electrical characteristic of the gas sensor. The frequency response can be an amplitude-frequency response of the electrical characteristic, a phase-frequency response of the electrical characteristic, or both an amplitude-frequency response and a phase-frequency response of the electrical characteristic.

[0047] Preferably, the repetitive thermal waveform is a sine wave. In some embodiments, the repetitive thermal waveform is generated by a single frequency sine wave excitation. In some embodiments, the repetitive thermal waveform is generated by a plurality of superimposed sine wave frequencies, wherein each sine wave frequency has a corresponding frequency response calibration table (e.g., an amplitude frequency response and / or a phase frequency response). The plurality of sine waves include a first group of sine waves having a first set of frequencies and a second group of sine waves having a second set of frequencies (wherein each group of sine waves has a frequency response calibration table, such as an amplitude frequency response calibration table and / or a phase frequency response calibration table), wherein the first group of frequencies is lower than the second group of frequencies (i.e., the frequency value or frequency value range in the first group is lower than the frequency value or frequency value range in the second group), and wherein the calculation of the target gas concentration is based on the frequency response (e.g., amplitude frequency response and / or phase frequency response) of a group of frequencies in the first group of frequencies or the second group of frequencies. For example, the target gas concentration may be based on the first group of frequency responses or the second group of frequency responses. In other words, the frequency response to a group of frequencies may be filtered out. A cutoff between a low frequency wave and a high frequency wave may be determined to improve the accuracy of gas measurement or calculation.

[0048] A calibration table based on the system response can be generated. Preferably, the calibration table is generated by correlating gas concentrations with frequency responses (e.g., amplitude frequency response, phase frequency response, or both) measured using a short-time Fourier transform of the system response. Using this table, hydrogen gas readings can be generated so that accuracy does not degrade over time under certain environmental conditions.

[0049] In some embodiments, the offset in the system response is corrected by applying a known gas partial pressure to the sensor, allowing the sensor to generate a second frequency response (e.g., a magnitude frequency response, a phase frequency response, or both), and applying a correction to the calibration table based on the second frequency response.

[0050] In some embodiments, the calibration table can be corrected by: allowing the sensor to generate a second frequency response; changing the operating mode of the gas sensor to operate at two temperatures; alternatingly controlling the temperature of the gas sensor between a first temperature and a second temperature while exposing the gas sensor to a fluid environment, wherein the temperature of the gas sensor is maintained at the first temperature during a first time period, transitions from the first temperature to the second temperature during a second time period, and is maintained at the second temperature during a third time period; monitoring the electrical characteristics of the gas sensor during the second time period and a fourth time period; calculating the gas concentration based on the electrical characteristics; and calculating the correction based on the second frequency response and the calculated gas concentration.

[0051] Using the systems and methods described herein, gas concentrations may be calculated continuously and in real time.

[0052] Balanced Detector Characteristics

[0053] In some embodiments, in order to achieve accurate gas concentration readings, the environment must be stable and the sensor system must be in equilibrium. However, the length of time at a constant temperature (the first and third time periods described above) can vary based on the equilibrium state of the sensor. Therefore, the time at one temperature depends on the system and the environment reaching equilibrium, which is unknown. Conventional systems are time-based and use multi-temperature operation for automatic calibration, and require that the sensor measurements corresponding to each sensor temperature be in equilibrium in order to calculate an accurate calibration, but it is unknown whether the system and the environment are in equilibrium. Perform multi-temperature automatic calibration to generate potential calibrations for the sensor. If the environment is not in equilibrium or the sensor is not in equilibrium in response to changes in sensor temperature, the calibration will be inaccurate. Therefore, it is necessary to determine whether the results of the calibration are meaningful, and accept or reject the calibration as needed. In other words, after acquiring the sensor measurement data, a partial or full judgment is made on whether the calibration calculated based on the sensor measurement data is accurate. If the calibration appears to be inaccurate, the sensor measurement data is not used, and the calibration must be retried. For this method, there is usually a period of time when the system has been stable for a long time, and measurements for the multi-temperature equation can be made earlier than scheduled. Other times the system is not very stable, but the temperature transition is timed just before equilibrium is reached, effectively wasting the attempt to obtain a measurement. With a balanced detector, the post-sensor measurement data acquisition judgment factor is removed by first determining if the system and environment have reached equilibrium before taking a measurement at one temperature and moving on to the next, thereby ensuring that the calibration will be accurate and time is not wasted.

[0054] Currently, whether the system has reached equilibrium is based on time. The time allotted for the system to reach equilibrium in response to changes in sensor temperature is fixed and set so that most sensors will have enough time to reach equilibrium. This fixed time is based on experimental data. However, changes in the environment can make the readings unstable and require more time for the system to stabilize, but current implementations do not strictly use this information.

[0055] The heating element of the gas sensor can drive the temperature, but the regulation of the die temperature is done by the temperature sensor on the die and that part of the die is maintained at a specific temperature, although the specific temperature may not be the same as the temperature of all parts or stages of operation, but it will usually go through a specific sequence. Therefore, although the sensor may be at one temperature in the first time period and then enter the second temperature in the second time period to obtain a complete cycle of the multi-temperature system and make measurements, if instability is detected, the existing program can change the arrangement of the temperature cycle. Such instability may include large changes in ambient temperature or large changes in the measured electrical properties of the sensor, and the threshold of the parameter is determined experimentally. For example, when the first time period at the first temperature is normally scheduled, the system can repeat the third time period at the second temperature to quickly obtain sensor measurement data associated with the second temperature condition. This operation can be performed so that the automatic calibration can be calculated faster without having to go through all the normally scheduled time periods (the fourth time period of transition to the first temperature, then back to the first time period at the first temperature, then to the second time period of transition to the second temperature, and then finally able to repeat the third time period at the second temperature). Therefore, these control points are fixed time selections in traditional systems.

[0056] However, a more adaptive equilibrium detector provides some unique properties and helps eliminate the unknown time factor. For example, the equilibrium detector can indicate the state of the hydrogen resistor. In the present invention, a PID type heater control loop is used to change the temperature of the sensor. The equilibrium detector determines whether the gas sensor has reached equilibrium in response to the temperature change and whether the environment in which the sensor is located has reached equilibrium. The method for determining equilibrium is based on physical measurements of the sensor, such as temperature, resistance, and power supplied to heat the sensor, as well as higher-level information such as hydrogen readings calculated using any model used by the sensor and the parameters that generate the hydrogen readings within the model. These properties can be statistically analyzed and processed using techniques such as filtering or averaging, calculating variance (or related indicators). These indicators can then be updated as new data is captured to produce additional indicators such as changes over time (first-order derivatives), changes over time (second-order derivatives), etc. The thresholds for these indicators are determined experimentally and depend on the accuracy requirements of the desired application.

[0057] For example, the temperature of the gas sensor die may change, or the ambient gas concentration may change. To be able to know if the sensor is in equilibrium, a routine in the firmware can look at the above metrics and determine if the sensor is in equilibrium based on experimentally determined thresholds. Figure 2 An example of an equilibrium detector determining when a sensor has reached equilibrium following a change in hydrogen gas as well as a change in sensor temperature is shown.

[0058] Thus, in some embodiments, a system and method for determining a target gas concentration in a fluid environment includes: exposing a gas sensor to the fluid environment, the gas sensor having an electrical characteristic that varies with the target gas concentration; controlling the temperature of the gas sensor alternately between a first temperature and a second temperature while exposing the gas sensor to the fluid environment, wherein the temperature of the gas sensor is maintained at the first temperature for a first time period, transitions from the first temperature to the second temperature for a second time period, maintained at the second temperature for a third time period, and transitions from the second temperature to the third temperature for a fourth time period; continuously monitoring the electrical characteristic of the gas sensor during the second time period and the fourth time period; and calculating the gas concentration based on a system response (e.g., a transient response) in the electrical characteristic of the gas sensor measured during the second time period and the fourth time period as the temperature transitions between the first temperature and the second temperature. To further improve the accuracy of the readings, the system can determine whether the gas sensor has reached equilibrium with a balance detector.

[0059] Dual sensor features

[0060] In some embodiments, rather than having one gas sensor change temperature, two gas sensors may be used in parallel. In some embodiments, the hydrogen reading from the dual temperature sensor is interrupted each time the sensor switches temperature. Because the dual temperature sensor uses a multi-temperature equation, its accuracy does not degrade over time, but it may have gaps in readings due to its response to temperature transitions. In contrast, a single temperature sensor may be used (never a temperature transition) with real-time readings (e.g., approximately 1 sample / second readings in the present invention), but true hydrogen readings are obtained from a second sensor to correct for any baseline sensor drift each time the single temperature sensor completes a temperature cycle, which may require from once an hour to once every few days. It is assumed that the accuracy of the single temperature sensor does not degrade outside the application specification before the dual / multi-temperature sensor can send a correction to the single temperature sensor.

[0061] The first sensor operates at a single temperature (single temperature sensor) so that it can continuously measure hydrogen without interruption. The second sensor calculates hydrogen using a two-temperature method (two temperature sensors) so that it is at a first temperature for a first period of time, transitions to a second temperature for a second period of time, is at the second temperature for a third period of time, and transitions back to the third temperature for a fourth period of time. The third temperature can be the same temperature as the first temperature or a different temperature. Because the second sensor can account for drift over time (due to instability, oxidation, interfering gases such as CO or H2S, etc.), but has only intermittent but reliable hydrogen measurements, it can pass these measurements to the first sensor as a calibration. In other words, as each automatic calibration is completed, information is fed forward from the second sensor to the first "real-time" sensor.

[0062] Figure 3A An example of the output from a dual sensor embodiment is shown, where the first sensor (lower curve) shows the hydrogen concentration reading, while the second sensor (upper square wave) shows the results of the gas sensor using a two-temperature method, which is used to calibrate the output of the first sensor. Figure 3A The position where the ST sensor indicates that the hydrogen is stable 1 and the MT sensor begins cycling its temperature is shown. When this temperature cycle is complete, the ST sensor indicates that the hydrogen is stable 2. The correction is fused 3 into the hydrogen reading of the ST sensor. As this process repeats, the ST sensor indicates that the hydrogen is stable 4 and the MT sensor begins cycling its temperature again. If the ST sensor shows a change in hydrogen concentration 5, the MT sensor cancels its cycle and returns to the baseline.

[0063] Figure 3BA flow chart illustrating the process is shown. When the process begins, the system determines whether the first gas sensor and the second gas sensor are in equilibrium. If not, the system waits and continues to check whether the two sensors have reached equilibrium. When the gas sensors reach equilibrium, the hydrogen concentration reading of the first gas sensor (single temperature sensor) is recorded, while the resistance (or some other electrical property) of the second gas sensor (two temperature sensor) is recorded. Then, the time since the gas sensors were last in equilibrium is determined. If the time since the gas sensors last reached equilibrium is greater than a predetermined time, any previous readings are invalid. The second gas sensor is then switched to another operating temperature (i.e., the second temperature if previously operating at the first temperature), and the process repeats the step of determining whether the sensors are in equilibrium again. If there are valid readings for a full cycle (the second gas sensor has recorded a reading for each of the two temperatures, and the first sensor has recorded a hydrogen reading associated with each of the two temperatures of the second gas sensor), then the correction calculation can be started. First, the change in gas concentration (e.g., the percentage change in hydrogen concentration) compared to the previous reading of the first gas sensor is calculated. Then, the change in the electrical property (e.g., resistance) of the second gas sensor corresponding to the change in gas concentration of the first sensor is calculated. The second gas sensor can then calculate the hydrogen concentration associated with the most recent sensor temperature based on the change in resistance due to the temperature change of the second gas sensor and the hydrogen change recorded by the first gas sensor. This hydrogen concentration calculated by two temperature sensors is considered to be more accurate than the hydrogen concentration calculated by a single temperature sensor. The difference in reading between the reading of the single temperature sensor and this reading, if any, is considered to be the error of the single temperature sensor. A correction factor is calculated to eliminate this error in the single temperature sensor reading and the correction factor is incorporated into its hydrogen reading. The second gas sensor is switched to its other operating temperature and the process is repeated.

[0064] like Figure 3C As shown, when the second gas sensor reaches the end of the low temperature state (ELT) through the determination of the balance detector, it transitions to the high temperature state (HT). As the end of the high temperature state (EHT) is determined again by the balance detector, it transitions back to the low temperature state (LT), and the process repeats.

[0065] Figure 3DExperimental data for this process is shown. The figure contains three sets of data; real-time hydrogen calculations (MT sensor readings) for two temperature sensors, hydrogen calculations (calculated) using the multi-temperature equation for two temperature sensors, and real-time hydrogen calculations for a single temperature sensor. The sensors were exposed to a variety of hydrogen concentrations (5% H2 / N2, 2% H2 / N2, 5% H2 / N2, and then 1% H2 / N2, all at a pressure of 1 absolute atmosphere). Looking at the real-time hydrogen calculations (MT sensor readings) for the two temperature sensors, occasional spikes in the readings can be seen. These spikes are the result of temperature transitions and can last from minutes to hours, depending on the response time of the sensor, the magnitude of the temperature change, and the hydrogen in the Pd lattice. It can be seen that the update frequency of the hydrogen calculations (calculated) based on the multi-temperature equation for the two temperature sensors is much lower than the real-time readings. Updates to the readings can only occur at the end of the temperature state of the two temperature sensors, which can be seen in the figure using the above spikes as markers. As previously described, these less frequent updates of the hydrogen readings calculated from the multi-temperature equations are considered accurate and will not degrade over time. To benefit from this, as these calculations are updated, they are fed forward to the real-time single temperature sensor readings (ST sensor readings). In order to be able to use the multi-temperature equations when the hydrogen concentration changes between the temperatures (associated with the two temperature sensors), the single temperature sensor must record the hydrogen changes associated with the resistance measurements used in the multi-temperature equations. This is described in more detail in the single temperature sensor feedback feature below.

[0066] Thus, in some embodiments, a system and method for determining a target gas concentration in a fluid environment includes: exposing a first gas sensor to the fluid environment, the first gas sensor having an electrical characteristic that varies with the target gas concentration; exposing a second gas sensor to the fluid environment, the second gas sensor having an electrical characteristic that varies with the target gas concentration; alternatingly controlling the temperature of the second gas sensor between a first temperature and a second temperature while exposing the second gas sensor to the fluid environment, wherein the temperature of the second gas sensor is maintained at the first temperature for a first time period, transitions from the first temperature to the second temperature for a second time period, maintained at the second temperature for a third time period, and transitions from the second temperature to the third temperature for a fourth time period; monitoring the electrical characteristic of the second gas sensor during the second time period and the fourth time period; and calculating the target gas concentration based on the electrical characteristic of the first gas sensor, wherein data from the second gas sensor is used to correct for baseline sensor drift of the first gas sensor. Preferably, the first gas sensor operates at a single temperature.

[0067] A second sensor using a repeating thermal waveform

[0068] The dual sensor feature described above can be combined with the repetitive thermal waveform feature so that instead of the second sensor utilizing a two temperature approach, the second sensor can be in a constant transient response state to a repetitive thermal waveform (such as the aforementioned sinusoidal curve). The second gas sensor passes the correction to the first gas sensor to maintain the calibration of the first gas sensor.

[0069] Single temperature sensor feedback characteristics

[0070] In some embodiments, changes in the environment can be taken into account by working together with a single temperature sensor, dual temperature sensors, or auto-calibration sensors. For example, a single temperature sensor can show hydrogen changes if changes do occur (e.g., by measuring changes using resistance measurements and calibration tables), and by knowing the changes and quantifying the changes, a multi-temperature correction can be calculated. In order for the multi-temperature equation to be valid, it is assumed that the resistance measurements associated with the two temperatures correspond to the same hydrogen partial pressure. That is, if the hydrogen partial pressure changes between the two measurements, the hydrogen calculations performed using the equation will be incorrect. However, a single temperature sensor (if present) can track changes in hydrogen partial pressure during the period in which the dual temperature sensor records the resistance of each of the two sensors. If the single temperature sensor detects any changes, the dual temperature sensor can use its own calibration information to adjust one of the resistance measurements. The "corrected" resistance value is adjusted to the resistance in the absence of a change in hydrogen concentration. This can only be known because a single temperature sensor can track changes, while a dual temperature sensor cannot track changes in response to temperature transitions. Thus, data from one of these sensors may be used for another sensor, such as a first gas sensor reporting changes in the partial pressure of hydrogen detected in the first gas sensor to a second gas sensor.

[0071] In other words, the two-sensor approach can again be used with a second sensor using the two-temperature approach, but if the hydrogen partial pressure changes between the equilibrium state of the second sensor's first period (temperature 1) and the equilibrium state of the second sensor's third period (temperature 2), the first sensor can communicate the magnitude of the change in hydrogen partial pressure to the second sensor. This change can be compensated for using the sensitivity to hydrogen at one of the two temperatures of the second sensor, allowing the second sensor to still perform autocalibration in a way that can remove drift. (Information is fed back from the first "live" sensor to the second sensor, allowing the second sensor to complete its autocalibration despite changes in the environment.) This is described mathematically below:

[0072] make X0=X+C 偏移 Y0=Y+C 偏移

[0073] Where X0 and Y0 are the hydrogen partial pressure readings of the ST sensor associated with the actual applied hydrogen partial pressure value X and Y plus an offset C respectively. 偏移 In addition, X0 is the reading when the MT sensor is at temperature T2, and Y0 is the reading when the MT sensor is at temperature T1.

[0074] make R T2 =m T2 X+b T2 R T1 =m T1 X+b T1

[0075] Among them, m T2 and b T2 are the sensitivity and offset associated with the T2 isotherm, and m T1 and b T1 is the sensitivity and offset associated with the T1 isotherm. Further, let R T2 is the measured resistance associated with the hydrogen partial pressure X at temperature T2, and let R T1 is the unknown resistance associated with the hydrogen partial pressure X at temperature T1.

[0076] These can be combined to solve for X using the following multi-temperature equation, R T2 -R T1 =m T2 X+b T2 -m T1 Xb T1

[0077] Finally, let R′=m T1 Y+b T1

[0078] Wherein, R' is the resistance value actually measured by the MT sensor at temperature Tl when hydrogen concentration Y is applied.

[0079] Taking the difference in the hydrogen partial pressure readings from the ST sensor removes its offset and yields the following equation: a.

[0080] The unknown X is solved using only the known values. It can also be solved in a similar manner using the other isotherms. Therefore, the offsets cancel each other out.

[0081] Dual temperature sensor features

[0082] In some embodiments, two sensors may be used as described above, but wherein both sensors use a two-temperature hydrogen measurement method. The time periods of each sensor are staggered or offset so that the real-time sensor is always in the first time period (temperature 1) or the third time period (temperature 2) while the other sensor is in the transition time period (second or fourth), such as Figure 5 . The real-time sensor alternates between the first gas sensor (upper square wave) and the second gas sensor (lower square wave) with each transition between the states of the two sensors. Therefore, while one sensor is experiencing a transient response (which makes it more difficult to calculate the changing hydrogen), the other sensor is in equilibrium. When the results of the two gas sensor readings are combined, a continuous gas concentration reading is shown (lower line).

[0083] Thus, in some embodiments where the first gas sensor operates at two temperatures, measuring the gas concentration further includes alternatingly controlling the temperature of the first gas sensor between the first temperature and the second temperature while exposing the first gas sensor to the gas, wherein the temperature of the first gas sensor is maintained at the first temperature during a first time period, transitions from the first temperature to the second temperature during a second time period, maintained at the second temperature during a third time period, and transitions from the second temperature to the third temperature during a fourth time period; wherein the temperature of the first gas sensor and the temperature of the second gas sensor are staggered such that when the first gas sensor is in the first time period or the third time period of the first gas sensor, the second gas sensor is in the second time period or the fourth time period of the second gas sensor. In other words, when the first gas sensor is in its first time period, the second gas sensor is in its second time period (transition period), and when the first gas sensor is in its second time period (transition period), the second gas sensor is in its first time period (or third time period).

[0084] Second-order isotherm characteristics

[0085] In some embodiments, a two-temperature approach may be used, but instead of using a line to describe the change in resistance with hydrogen at each isotherm, a second-order polynomial is used. The offset (c T1 and c T2 ) can be removed as follows mathematically, where, at a given constant sensor temperature T1 or T2, the hydrogen partial pressure The resistance (R T1 and R T2 ) are the three corresponding coefficients a given for each corresponding temperature T1 , b T1 and c T1and a T2 , b T2 and c T2 The second order function in the case of:

[0086] make a. b.

[0087] Then, these equations are linearly subtracted, c.

[0088] Solving for the hydrogen partial pressure There are two solutions: i.

[0089] The solution that most closely matches the isotherm working region is shown below (the other solution results in negative or extremely large hydrogen partial pressure calculations, regardless of the isotherm concavity): i.

[0090] Piecewise linear isotherm characteristics

[0091] The sensitivity of a system refers to how effectively the resistance (or other electrical property) of a gas sensor changes with hydrogen content. The sensitivity of a sensor is not necessarily constant over the entire range of hydrogen content. A gas sensor may have different sensitivities when exposed to different hydrogen content. Therefore, it is beneficial to consider the sensitivity as it varies based on the hydrogen content of the environment being measured.

[0092] Factors that affect the sensitivity of a gas sensor include the composition of the sensor (e.g., palladium / nickel ratio) and the temperature of the gas sensor. The more palladium in the sensor, the greater the change in resistance with hydrogen; thereby increasing the sensitivity of the gas sensor. Additionally, the lower the temperature, the more sensitive the gas sensor. The palladium content and operating temperature can be determined based on the performance requirements of the product application.

[0093] Assuming the best information is available, a two-temperature approach can be used by using the sensitivity and intercept (resistance as a function of hydrogen partial pressure at a given temperature) of two isotherms based on the hydrogen partial pressure measured by the sensor. That is, over the entire hydrogen range, for concentrations between X0 and X1, sensitivity and intercept A0 are used, for concentrations between X1 and X2, sensitivity and intercept A1 are used, and so on.

[0094] refer to FIG. 6A to FIG. 6C , if ΔR(R T2 -R T1 ) falls within the range of ΔR in Region 3:

[0095]

[0096]

[0097]

[0098] The standard multi-temperature equations shown above still apply, but the value of G 3_T1 , G 3_T2 , R base_3T1 and R base_3T2 All correspond to specific segments or regions in the segment table. If ΔR(R T2 -R T1 ) falls in a different region, the above variables associated with that region will be used. These variables are determined during calibration.

[0099] In order to determine ΔR(R T2 -R T1 ) falls in which region, we can take the difference of isotherms, such as Figure 6B shown.

[0100] Figure 6C A comparison of different methods for interpolating isotherms is shown, as well as a comparison of the calibration table for a single temperature sensor using a piecewise linear fit. Figure 6B Using a standard linear regression on the isotherms will result in much larger errors in the model than using a quadratic regression (shown in Figure 2) or a quadratic regression (2nd order polynomial regression).

[0101] Piecewise 2nd order isotherm characteristics

[0102] Another feature of the present invention is to use a 2nd order polynomial isotherm but with different sets of coefficients for different hydrogen regions as described in the piecewise linear isotherm.

[0103] General nonlinear calibration feature

[0104] The isotherms can be described as nth order polynomials, power functions, or similar nonlinear functions. The coefficients of these isotherms can be determined generically for the wafer based on base resistance and sensitivity. During calibration, the nonlinear isotherm function can be calibrated using two points (known hydrogen partial pressure and resistance) and the coefficients adjusted using a linear transformation to fit these two points.

[0105] Multiple temperature limit transition characteristics

[0106] Two-temperature operation requires a significant temperature difference between the first temperature and the second temperature, so that the transition period between temperature states can cause an undesirable transient response of the hydrogen sensor, which often results in a reduction in measurement capability, or in the worst case, no measurement capability. Alternatively, n temperature states can be added between temperature A and temperature A+N, so that only a small temperature increase or decrease occurs at a time to reduce the magnitude of the undesirable transient response. That is, the sensor can be at temperature A in the first period, then transition to temperature A+1 in the second period, remain at temperature A+1 in the third period, transition to temperature A+2 in the fourth period, transition to temperature A+N in the n-1 period, and remain at temperature A+N in the nth period. The sensor can return to temperature A in the reverse order. It is assumed that hydrogen can be calculated in real time with the highest accuracy in each temperature state, and hydrogen can be calculated with a possibly reduced accuracy during the transition state. The measurement results of the temperature A and A+N states are used in the two-temperature formula to calculate hydrogen after the offset is removed.

[0107] To reduce undesirable transient responses, the step size from one temperature to the next may be made small enough that any undesirable transient response is very small and short-lived to the point where there is little disruption to the hydrogen reading.

[0108] By way of example only, a large step from a first temperature to a second temperature may be approximately 20 degrees Celsius. In order for the gas sensor to make reliable measurements, equilibrium must be reached, which may take 30 minutes. Therefore, 30 minutes must pass before the gas sensor is real again. On the other hand, if a full large step of 20 degrees is not taken, and a small step of one degree is used, the time required to reach equilibrium is shorter, and the gas sensor may be real again after 30 seconds instead of 30 minutes. The gas sensor can then perform measurements in multiple small steps spaced apart to approximate the total large step of 20 degrees, and use a multi-temperature equation to calculate the hydrogen concentration for each small step. This technique effectively reduces the amount of time that the system is unable to make measurements while it is in equilibrium, without having to rely on transient responses during the transition period.

[0109] Heater power correction feature

[0110] Given a constant hydrogen partial pressure and sensor operating temperature in an environment without interfering gases, the resistance should remain constant (except for small drifts due to instabilities). However, as the ambient heat load on the die changes (due to ambient temperature, flow rate, etc.), the sensor resistance will change. This change in resistance can be compensated for using the measured power used to maintain the sensor die temperature. The correction assumes that the resistance adjustment is proportional to the heater power measurement. The compensated resistance is equal to the measured resistance plus this adjustment, as follows: ii.Rcomp =R meas -R adj

[0111] in, iii.R adj =αP

[0112] When used to compensate for measured resistance, the heater power factor α effectively normalizes the resistance to that which would occur when no power is applied.

[0113] Temperature dependent heater power correction feature

[0114] Heater power correction, where the heater power factor is also a function of operating temperature.

[0115] Hydrogen related heater power correction feature

[0116] In the heater power correction method, the heater power coefficient can also be a function of the hydrogen partial pressure.

[0117] Heater power calculation ambient temperature characteristics

[0118] In the two-temperature method, the power required to heat the die at equilibrium during the first period (Temperature 1) and the third period (Temperature 2) can be measured and recorded. Assuming that the ambient temperature and the heat load on the die are constant, the ambient temperature can be calculated using the linear function described below:

[0119] make a. is the die heater power at temperature T1 b. is the die heater power at temperature T2 T env Unknown ambient temperature, lower than T1 and T2

[0120] Then, d.

[0121] Use T1 information to solve, e.

[0122] Or, in full form, f.

[0123] The above description of preferred embodiments and features of the present invention has been presented for illustration and description purposes. The above description is not intended to be exhaustive or to limit the invention to the precise forms disclosed. In view of the above teachings, many modifications, variations and combinations are possible. The scope of the present invention is not intended to be limited by this detailed description, but by the claims and equivalents of the appended claims.

Claims

1. A method for determining a target gas concentration of a target gas in a fluid environment, the method comprising the following steps: (a) exposing a gas sensor to the fluid environment, the gas sensor having an electrical characteristic that varies with the concentration of the target gas; (b) during step (a), modulating the temperature of the gas sensor, wherein the modulation takes the form of a repetitive thermal waveform that induces an amplitude-frequency response in the electrical characteristic; (c) monitoring the electrical characteristic during step (b); and (d) Calculating the target gas concentration based on the amplitude-frequency response of the electrical characteristics of the gas sensor.

2. The method of claim 1, further comprising generating a calibration table based on the amplitude-frequency response.

3. The method of claim 2, wherein: The calibration table is generated by correlating the target gas concentration with the amplitude-frequency response measured using a short-time Fourier transform.

4. The method of claim 3, further comprising correcting an offset in the amplitude frequency response by applying a known partial pressure of the target gas to the sensor, allowing the sensor to generate a second amplitude frequency response, and applying a correction to the calibration table based on the second amplitude frequency response.

5. The method of claim 3, further comprising applying a correction to the calibration table by: (a) allowing the sensor to generate a second amplitude-frequency response; (b) changing the operating mode of the gas sensor to operate at two temperatures; (c) controlling the temperature of the gas sensor alternately between a first temperature and a second temperature while exposing the gas sensor to the gas, wherein The temperature of the gas sensor is maintained at the first temperature during a first time period, changes from the first temperature to the second temperature during a second time period, and is maintained at the second temperature during a third time period; (d) monitoring an electrical characteristic of the gas sensor during the second time period and a fourth time period; (e) calculating the target gas concentration based on the electrical characteristics; and (f) calculating the correction based on the second amplitude frequency response and the calculated target gas concentration.

6. The method of claim 1, wherein: The repetitive thermal waveform is generated by superimposing multiple sine waves.

7. The method of claim 6, wherein: Each sine wave has a corresponding amplitude-frequency response calibration table.

8. The method of claim 6, wherein: The plurality of sinusoidal waves include a first set of sinusoidal waves having a first set of frequencies and a second set of sinusoidal waves having a second set of frequencies, wherein the first set of frequencies is lower than the second set of frequencies, and wherein the calculation of the target gas concentration is based on an amplitude-frequency response of one of the first set of frequencies or the second set of frequencies.

9. A method for determining a target gas concentration of a target gas in a fluid environment, the method comprising the steps of: (a) exposing a gas sensor to the fluid environment, the gas sensor having an electrical characteristic that varies with the concentration of the target gas; (b) during step (a), modulating the temperature of the gas sensor, wherein the modulation takes the form of a repetitive thermal waveform that induces a phase-frequency response in the electrical characteristic; (c) monitoring the electrical characteristic during step (b); and (d) Calculating the target gas concentration based on a phase-frequency response of an electrical characteristic of the gas sensor.

10. The method of claim 9, further comprising generating a calibration table based on the phase-frequency response.

11. The method of claim 10, wherein: The calibration table is generated by correlating the target gas concentration with the phase-frequency response measured using a short-time Fourier transform.

12. The method of claim 11 further comprising correcting an offset in the phase-frequency response by applying a known partial pressure of the target gas to the sensor, allowing the sensor to generate a second phase-frequency response, and applying a correction to the calibration table based on the second phase-frequency response.

13. The method of claim 11, further comprising applying a correction to the calibration table by: (a) allowing the sensor to generate a second phase-frequency response; (b) changing the operating mode of the gas sensor to operate at two temperatures; (c) controlling the temperature of the gas sensor alternately between a first temperature and a second temperature while exposing the gas sensor to the gas, wherein The temperature of the gas sensor is maintained at the first temperature during a first time period, changes from the first temperature to the second temperature during a second time period, and is maintained at the second temperature during a third time period; (d) monitoring an electrical characteristic of the gas sensor during the second time period and a fourth time period; (e) calculating the target gas concentration based on the electrical characteristics; and (f) calculating the correction based on the second phase-frequency response and the calculated target gas concentration.

14. The method of claim 9, wherein: The repetitive thermal waveform is generated by superimposing multiple sine waves.

15. The method of claim 14, wherein: Each sine wave has a corresponding phase-frequency response calibration table.

16. The method of claim 14, wherein: The plurality of sinusoidal waves include a first set of sinusoidal waves having a first set of frequencies and a second set of sinusoidal waves having a second set of frequencies, wherein the first set of frequencies is lower than the second set of frequencies, and wherein the calculation of the target gas concentration is based on a phase-frequency response of one of the first set of frequencies or the second set of frequencies.

17. A method for determining a target gas concentration of a target gas in a fluid environment, the method comprising the steps of: (a) exposing a gas sensor to the fluid environment, the gas sensor having an electrical characteristic that varies with the concentration of the target gas; (b) during step (a), modulating the temperature of the gas sensor, wherein the modulation takes the form of a repetitive thermal waveform that induces a frequency response in the electrical characteristic; (c) monitoring the electrical characteristic during step (b); and (d) Calculating the target gas concentration based on the frequency response of the electrical characteristics of the gas sensor.

18. The method of claim 17, further comprising generating a calibration table based on the frequency response, wherein: The calibration table is generated by correlating the target gas concentration with the frequency response measured using a short-time Fourier transform.

19. The method of claim 18, further comprising correcting for an offset in the frequency response by applying a known partial pressure of the target gas to the sensor, allowing the sensor to generate a second frequency response, and applying a correction to the calibration table based on the second frequency response.

20. The method of claim 18, further comprising applying a correction to the calibration table by: (a) allowing the sensor to generate a second frequency response; (b) changing the operating mode of the gas sensor to operate at two temperatures; (c) controlling the temperature of the gas sensor alternately between a first temperature and a second temperature while exposing the gas sensor to the gas, wherein The temperature of the gas sensor is maintained at the first temperature during a first time period, changes from the first temperature to the second temperature during a second time period, and is maintained at the second temperature during a third time period; (d) monitoring an electrical characteristic of the gas sensor during the second time period and a fourth time period; (e) calculating the target gas concentration based on the electrical characteristics; and (f) calculating the correction based on the second frequency response and the calculated target gas concentration.

21. The method of claim 17, wherein: The repetitive thermal waveform is generated by superimposing multiple sine waves.

22. The method of claim 21, wherein: Each sine wave has a corresponding frequency response calibration table.

23. The method of claim 21, wherein: The plurality of sinusoidal waves include a first set of sinusoidal waves having a first set of frequencies and a second set of sinusoidal waves having a second set of frequencies, wherein the first set of frequencies is lower than the second set of frequencies, and wherein the calculation of the target gas concentration is based on a frequency response of one of the first set of frequencies or the second set of frequencies.

24. A method for determining a target gas concentration of a target gas in a fluid environment, the method comprising: (a) exposing a first gas sensor to the fluid environment, the first gas sensor having an electrical characteristic that varies with the concentration of the target gas; (b) exposing a second gas sensor to the fluid environment, the second gas sensor having an electrical characteristic that varies with the concentration of the target gas; (c) alternatingly controlling the temperature of the second gas sensor between a first temperature and a second temperature while exposing the second gas sensor to a fluid environment, wherein the temperature of the second gas sensor is maintained at the first temperature during a first time period, transitions from the first temperature to the second temperature during a second time period, maintained at the second temperature during a third time period, and transitions from the second temperature to the third temperature during a fourth time period; (d) monitoring an electrical characteristic of the second gas sensor during the second time period and the fourth time period; and (e) calculating the target gas concentration based on the electrical characteristics of the first gas sensor, wherein data from the second gas sensor is used to correct for baseline sensor drift of the first gas sensor.

25. The method of claim 24, wherein: The first gas sensor operates at a single temperature.

26. The method of claim 25, wherein: The second gas sensor is in a constant system response state to the repetitive thermal waveform.

27. The method of claim 26, further comprising the first gas sensor reporting to the second gas sensor a change in partial pressure of the target gas detected in the first gas sensor.

28. The method of claim 24, wherein: The first gas sensor operates at two temperatures, and further includes alternatingly controlling the temperature of the first gas sensor between a first temperature and a second temperature while exposing the first gas sensor to the fluid environment, wherein the temperature of the first gas sensor is maintained at the first temperature during a first time period, transitions from the first temperature to the second temperature during a second time period, maintained at the second temperature during a third time period, and transitions from the second temperature to the third temperature during a fourth time period; wherein the temperature of the first gas sensor and the temperature of the second gas sensor are staggered such that when the first gas sensor is in the first time period or the third time period of the first gas sensor, the second gas sensor is in the second time period or the fourth time period of the second gas sensor.

Images