Multi-frequency sensing system and method

Abstract

The sensor system 100 is described with improved measurement accuracy achieved by reducing noise, baseline drift, or both based on processing a group of sensor element response signals 342. The response signals 342 may be received in response to applying stimuli to the sensor elements using different excitation frequencies over time. For example, a sensor circuit may apply excitation signals to the sensing elements at multiple excitation frequencies over time. The sensor system 100 may include storage and processing circuitry for receiving the response signals 342 and generating correction values ​​based on analyzing the received response signals 342. The sensor system 100 may then provide a response signal that is adjusted by reducing noise, baseline drift, or both based on the correction values.

Description

[Technical Field]

[0001] One or more embodiments are disclosed that relate to systems and methods for detecting gases.

[0002] Government Licensing Rights This invention was made with Government support under Contract W15QKN-18-9-1004 awarded to the CWMD Consortium by ACC-NJ. The Government has certain rights in this invention. [Background technology]

[0003] Gas sensors may be based on sensing materials including metal oxide semiconductor (MOS) materials, dielectric polymers, conducting polymers, nanotubes, metal organic frameworks, graphene, supramolecular compounds, and others.

[0004] Conventional MOS sensors have a relatively narrow dynamic range of measurement due to the nature of the interaction mechanism between the MOS sensing material and the surrounding environment. While MOS materials may be commercially successful due to their widespread use for gas alarms in residential and industrial facilities, readout of MOS materials is traditionally achieved by measuring the material's change in resistance as a function of gas concentration. Such a relationship follows a well-known power law, with saturation of the sensor response occurring at high concentrations. Conventional single-output sensors that measure values ​​and / or inductive changes related to resistance, capacitance, current, light intensity, and other changes in a single output are known as zero-order analytical instruments. Summary of the Invention [Means for solving the problem]

[0005] In one or more embodiments, a sensor system is described that includes a sensing element, a controller, and an excitation / detection system. The controller may provide one or more control signals for monitoring at least one component in a fluid. The excitation / detection system may be coupled to the sensing element and the controller. The excitation / detection system may perform one or more operations based on the one or more control signals. The operations may include providing a plurality of stimulus signals to the sensing element, wherein the excitation / detection system is configured to provide each stimulus signal of the plurality of stimulus signals with a different frequency within a frequency range to the sensing element; receiving a plurality of sensor responses from the sensing element in response to providing the plurality of stimulus signals; determining one or more noise values, one or more baseline drift values, or both based on analyzing the plurality of sensor responses; determining at least one noise-reduction value, at least one baseline drift-reduction value, or both; and reducing at least one noise value of the one or more noise values ​​based on the at least one noise-reduction value, reducing the at least one baseline drift value based on the baseline drift-reduction value, or both.

[0006] Another embodiment provides a method that includes performing operations by a controller of a sensor system. According to the method, one or more control signals are provided by the controller of the sensor system to a sensing element of the sensor system to overwrite generation of a plurality of stimulus signals, each stimulus signal having a different frequency. A plurality of sensor responses from the sensing element are received by the controller in response to providing the plurality of stimulus signals. One or more noise values, one or more baseline drift values, or both are determined by the controller based on analyzing the plurality of sensor responses. At least one noise reduction value, at least one baseline drift reduction value, or both are determined by the controller. At least one noise value of the one or more noise values ​​is reduced by the controller based on the at least one noise reduction value, and / or the at least one baseline drift value is reduced by the controller based on the baseline drift reduction value.

[0007] In another embodiment, a computer-readable medium is described that includes computer-executable instructions that, when executed, cause a processor associated with a sensor system to perform operations. The operations may include providing one or more control signals to a sensing element of the sensor system's excitation circuit to generate a plurality of stimulus signals, each stimulus signal having a different frequency, receiving a plurality of sensor responses from the sensing element in response to providing the plurality of stimulus signals, determining one or more noise values, one or more baseline drift values, or both based on analyzing the plurality of sensor responses, determining at least one noise-reduction value, at least one baseline drift-reduction value, or both, and reducing at least one noise value of the one or more noise values ​​based on the at least one noise-reduction value, reducing the at least one baseline drift value based on the baseline drift-reduction value, or both. [Brief explanation of the drawings]

[0008] [Figure 1]1 illustrates an implementation of a sensor system according to an embodiment. [Figure 2] 1 illustrates exemplary locations of a wearable sensor system according to one embodiment. [Figure 3] 2 illustrates a non-limiting example of the design of the sensor shown in FIG. 1 according to one embodiment. [Figure 4] 1 illustrates an implementation of a sensor according to an embodiment. [Figure 5] 1 shows a graph depicting a response signal and an adjusted response signal according to one embodiment. [Figure 6] 5 is a process for improving the accuracy of the sensors of FIGS. 1, 3, and 4 according to one embodiment. [Figure 7] 1 shows graphs depicting improved and adjusted response signals with desired limits of detection (LOD) based on applying multivariate curve resolution techniques according to one embodiment. [Figure 8] 1 shows a graph illustrating exemplary results in determining the limit of detection (LOD) of a sensor according to one embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] One or more embodiments of the subject matter described herein provide sensing systems and methods that allow for reconfiguration of the sensitivity and dynamic range of gas measurements.

[0010] 1 illustrates one embodiment of a sensor system 100 that may be used to test a fluid in contact with the system 100. The fluid may be a gas, a liquid, a gas-liquid mixture, particles or particulate matter, or the like, including one or more analyte gases. In some cases, the sensor system 100 (e.g., a fluid sensor) may measure the concentration of one or more fluids continuously and / or in real time to determine changes in the concentration of the one or more fluids. The sensor system 100 may convert such measurements into an analytically useful signal for continuous monitoring of at least one component in the fluid.

[0011] The fluid may include indoor or outdoor ambient air. Another example of a fluid is air in industrial, residential, military, construction, urban, and any other known locations. Another example of a fluid is ambient air with relatively varying concentrations of hydrocarbons and / or other contaminants. For example, the fluid may include relatively low concentrations of chemical warfare agents, such as benzene, naphthalene, carbon monoxide, ozone, formaldehyde, nitrogen dioxide, sulfur dioxide, ammonia, hydrofluoric acid, hydrochloric acid, phosphine, ethylene oxide, carbon dioxide, hydrogen sulfide, nerve, blisters, and blood, hydrocarbons, and / or other contaminants. Another example of a fluid is disinfectants, such as alcohol, aldehydes, chlorine dioxide, and hydrogen peroxide. Another example of a fluid is ambient air with relatively low, medium, and high concentrations of flammable or combustible gases, such as methane, ethane, propane, butane, hydrogen, and / or other gases.

[0012] In certain embodiments, the fluid may include an analyte gas that is an indoor pollutant. A non-limiting list of exemplary indoor pollutants may include, but is not limited to, acetaldehyde, formaldehyde, 1,3-butadiene, benzene, chloroform, methylene chloride, 1,4-dichlorobenzene, perchloroethylene, trichloroethylene, naphthalene, and polycyclic aromatic compounds. In certain embodiments, the fluid may include an analyte gas that is an outdoor pollutant. A non-limiting list of exemplary outdoor pollutants may include, but is not limited to, ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide.

[0013] Another example of a fluid is at least one gas dissolved in an industrial liquid such as transformer oil, bioprocessing medium, fermentation medium, wastewater, and / or any other medium, gas, or liquid. Another example of a fluid is at least one gas dissolved in a consumer liquid such as milk, non-alcoholic beverages, alcoholic beverages, cosmetics, etc. Another example of a fluid is at least one gas dissolved in a consumer liquid such as milk, non-alcoholic beverages, alcoholic beverages, cosmetics, etc. Another example of a fluid is at least one gas (e.g., a biomarker) dissolved in a bodily fluid such as blood, sweat, tears, saliva, urine, etc.

[0014] Another example of a fluid is at least one gas dissolved in a bodily fluid, such as blood, sweat, tears, saliva, or urine. Another example of a fluid is transformer oil or any insulating fluid in an electrical transformer installed and / or located below ground level, above ground level, near ground level, or any other location. In another embodiment, the fluid may be a gas or fuel, such as a hydrocarbon-based fuel. One example of a fluid is natural gas supplied to a power system (e.g., a vehicle or a stationary generator set) for consumption. Other examples of such fluids may include gasoline, diesel fuel, jet fuel or kerosene, biofuels, petroleum diesel-biodiesel fuel blends, natural gas (liquid or compressed), and fuel oil.

[0015] In certain embodiments, the fluid may include an analyte gas that is a toxic industrial material or a toxic industrial chemical. A non-limiting list of exemplary toxic industrial materials and chemicals includes, but is not limited to, ammonia, arsine, boron trichloride, boron trifluoride, carbon disulfide, chlorine, diborane, ethylene oxide, fluorine, formaldehyde, hydrogen bromide, hydrogen chloride, hydrogen cyanide, hydrogen fluoride, hydrogen sulfide, nitric acid (fume), phosgene, phosphorus trichloride, sulfur dioxide, sulfuric acid, and tungsten hexafluoride. In certain embodiments, the fluid may include an analyte gas that is a toxic substance with a medium risk factor index.

[0016] A non-limiting list of exemplary toxic substances with an intermediate hazard quotient includes, but is not limited to, acetone cyanohydrin, acrolein, acrylonitrile, allyl alcohol, allylamine, allyl chlorocarbonate, boron tribromide, carbon monoxide, carbonyl sulfide, chloroacetone, chloroacetonitrile, chlorosulfonic acid, diketene, 1,2-dimethylhydrazine, ethylene dibromide, hydrogen selenide, methanesulfonyl chloride, methyl bromide, methyl chloroformate, methylchlorosilane, methylhydrazine, methyl isocyanate, methyl mercaptan, nitrogen dioxide, phosphine, phosphorus oxychloride, phosphorus pentafluoride, selenium hexafluoride, silicon tetrafluoride, stibine, sulfur trioxide, sulfuryl chloride, sulfuryl fluoride, tellurium hexafluoride, n-octyl mercaptan, titanium tetrachloride, trichloroacetyl chloride, and trifluoroacetyl chloride.

[0017] In certain embodiments, the fluid may include an analyte gas that is a toxic substance with a low hazard quotient. A non-limiting list of exemplary toxic substances with a low hazard quotient includes allyl isothiocyanate, arsenic trichloride, bromine, bromine chloride, bromine pentafluoride, bromine trifluoride, carbonyl fluoride, chlorine pentafluoride, chlorine trifluoride, chloroacetaldehyde, chloroacetyl chloride, crotonaldehyde, cyanogen chloride, dimethyl sulfate, diphenylmethane-4,40-diisocyanate, ethyl chloroformate, ethyl chlorothioformate, ethyl phosphonate dichloride, ethyl phosphonate dichloride, ethyleneimine, hexachlorocyclopentadiene, and the like. Examples of suitable organic solvents include, but are not limited to, chloroformate, hydrogen iodide, iron pentacarbonyl, isobutyl chloroformate, isopropyl chloroformate, isopropyl isocyanate, n-butyl chloroformate, n-butyl isocyanate, nitric oxide, n-propyl chloroformate, parathion, perchloromethyl mercaptan, sec-butyl chloroformate, tert-butyl isocyanate, tetraethyl lead, tetraethyl pyrophosphate, tetramethyl lead, toluene 2,4-diisocyanate, and toluene 2,6-diisocyanate.

[0018] System 100 may include a fluid reservoir 112 for holding a fluid and a multivariable gas sensor 114 disposed at least partially on or within fluid reservoir 112. Alternatively, sensor 114 may be located in the fluid flow path outside reservoir 112, such as coupled to an in-line connector in fluid communication with the fluid reservoir defining the flow path. In either case, sensor 114 may continuously monitor the concentration of one or more components of one or more analyte gases based on an interval or upon receiving a control signal indicative of a gas concentration measurement.

[0019] The multivariable gas sensor 114 may provide two or more outputs that are substantially independent of each other. The fluid reservoir 112 may be in the form of a container having a controlled volume, or in the form of an open area such as an indoor facility (e.g., a room, hall, house, school, hospital, confined space, etc.), or in the form of an outdoor facility (e.g., a stadium, gas production area, beach, forest, etc.). In one embodiment, the sensor 114 may provide continuous monitoring of the fluid in the reservoir or flow path. In one or more embodiments, the sensor 114 may be an impedance gas sensor, an electromagnetic sensor, a photonic sensor, an electronic sensor, a hybrid sensor, or another type of sensor. Optionally, the multivariable gas sensor may be a sensor array.

[0020] The sensor 114 may detect characteristics or properties of a fluid via a resonant or non-resonant impedance spectral response. One or more inductor-capacitor-resistor resonant circuits (LCR resonators) may measure the sensor's resonant impedance spectral response. A non-resonant impedance spectral response is measured when the resistor-capacitor (RC) circuit does not include an inductor (L). The resonant or non-resonant impedance spectrum of the sensor 114 in proximity to or in contact with a fluid changes based on the sample's composition and / or components and / or temperature. The measured resonant or non-resonant impedance values ​​Z' (which may be the real part of the impedance, Zre) and Z'' (which may be the imaginary part of the impedance, Zim) reflect the sensor 114's response to the fluid.

[0021] Other embodiments of the subject matter described herein include other sensor designs beyond resonant and non-resonant impedance sensors. Other multivariable sensors may be electromechanical resonator sensors (e.g., tuning forks, cantilever sensors, acoustic device sensors), thermal sensors, optical sensors, acoustic sensors, photoacoustic sensors, near-infrared sensors, ultraviolet sensors, infrared sensors, visible light sensors, fiber optic sensors, reflective sensors, or any other multivariable sensor. The sensors may generate electrical, electromagnetic, or optical stimuli to measure gases in ambient air in industrial, residential, military, construction, urban, and any other known locations, or to measure gases in transformer oil or insulating fluid. The insulating fluid of the transformer may be insulating oil, mineral oil, synthetic oil, vegetable oil, or any other suitable insulating fluid.

[0022] A stimulation signal (e.g., an electric or magnetic field) may be applied to the sensing material or sensing film of the sensor 114 via electrodes. The distance between the electrodes and the electrode geometry, as well as the cyclic voltage applied to the electrodes, may define the magnitude of the stimulation signal applied to the sensor 114 (e.g., to the sensing material or sensing film). The electrodes may be in direct contact with the sensing material. For example, the sensor 114 may be a combination of a sensing region and associated circuitry, and / or the sensing region may be coated with a sensing material. The sensing material may be a semiconductor material or a metal oxide material.

[0023] The sensor 114 may apply an electrical and / or electromagnetic stimulus, hereinafter referred to as stimulus, to measure the impedance value of the sensing material. In some cases, the sensor 114 may store impedance values ​​measured on the sensing material (e.g., a dielectric material) in response to applying stimuli with different excitation frequencies to the sensing material. In some embodiments, excitation or dielectric excitation of the sensor 114 (e.g., a metal-oxide semiconductor (MOS) sensing material) refers to alternating current (AC) excitation of the sensor 114 (e.g., a MOS sensing material) at the shoulder of its dielectric relaxation region.

[0024] Furthermore, the impedance of the sensor 114 may be a non-limiting term for any electrical response of the sensing system to an AC current applied to the gas sensing material of the sensor 114. For example, the sensor 114 may determine and / or store an impedance spectrum based on storing impedance values ​​measured when applying stimuli with different excitation frequencies. Thus, the impedance spectrum may include impedance values ​​of the sensing material of the sensor 114 measured in response to applying stimuli having different excitation frequencies (e.g., a frequency sweep).

[0025] Suitable sensors may include single-use or multi-use sensors. A suitable multi-use sensor may be a reusable sensor that can be used for the life of the system in which it is incorporated. In one embodiment, the sensor may be a disposable sensor that can be used during all or part of the monitored reaction or process.

[0026] Data from the sensors 114 may be acquired via data acquisition circuitry 116, which may be associated with the sensors or with a control system such as a controller or workstation 122 that includes data processing circuitry, where additional processing and analysis may be performed. The controller 122 may include one or more wireless or wired components and may communicate with other components of the system 100. Suitable communication modes include wireless or wired communications. At least one suitable wireless mode includes a radio frequency device, such as radio frequency identification (RFID) wireless communications.

[0027] Other wireless communication modalities may be used based on application-specific parameters. Non-limiting examples include Bluetooth, LoRa, Wi-Fi, 3G, 4G, 5G, etc. For example, certain modalities may work while others do not when there is potential electromagnetic field (EMF) interference. The data acquisition circuitry 116 may optionally be located partially or entirely within the sensor 114. Other suitable locations may include a location partially or entirely within the controller 122. Additionally, the controller 122 may be replaced by an overall process control system in which the sensor and its data acquisition circuitry may be connected to the process control system.

[0028] Depending on the design of the sensing material, interrogation of the sensing material may be performed over an appropriate frequency range. For example, the sensing material may be a MOS sensing material or a polymer sensing material, and interrogation of the sensing material may be performed in the radio frequency or microwave regions of the electromagnetic spectrum. In another example, the sensing material may be a photonic nanostructure iridescent sensing material or a plasmonic nanoparticle sensing material, and interrogation of the sensing material may be performed in the optical region of the electromagnetic spectrum.

[0029] The data acquisition circuitry 116 may be in the form of a sensor reader that may be configured to communicate wirelessly or via wires with the sensors 114 and / or the controller 122. For example, the sensor reader may be a battery-powered device and / or may be powered using energy available from a master control system or by harvesting energy from ambient sources (light, vibration, heat, or electromagnetic energy).

[0030] Additionally, the data acquisition circuitry may receive data from one or more sensors 114 (e.g., multiple sensors located at different locations within or around the fluid reservoir). The data may be stored in short-term and / or long-term memory storage devices, such as an archival communication system, which may be located within the system or remotely from the system and / or may be reconstructed and displayed for an operator, such as at an operator workstation. The sensors 114 may be located on or in the fluid reservoir, associated piping components, connectors, flow-through components, and any other associated process components.

[0031] The data acquisition circuitry 116 may include one or more processors for analyzing data received from the sensor(s) 114. For example, the one or more processors may be one or more computer processors, controllers (e.g., microcontrollers), or other logic-based devices that perform operations based on one or more instruction sets (e.g., software). Furthermore, the instructions by which the one or more processors operate may be stored in a tangible, non-transitory computer-readable storage medium, such as a memory device. The memory device may include a hard drive, a flash drive, RAM, ROM, EEPROM, etc. Alternatively, one or more of the instruction sets that direct the operation of the one or more processors may be hardwired into the logic of the one or more processors, such as by hardwired logic formed and / or stored in the hardware of the one or more processors.

[0032] In addition to displaying data, the controller 122 may control the aforementioned operations and functions of the system 100. The controller 122 (e.g., an operator workstation) may include one or more processor-based components, such as a general-purpose or application-specific computer or processor 124. In addition to the processor-based components, the computer may include various memory and / or storage components, including magnetic and optical mass storage devices, internal memory such as RAM chips, etc. The memory and / or storage components may be used to store programs and routines for carrying out the techniques described herein, which may be executed by the controller 122 or associated components of the system 100.

[0033] Alternatively, the programs and routines may be stored in computer-accessible storage devices and / or memory remote from the controller 122 but accessible via network and / or communication interfaces present on the computer 124. The computer 124 may include various input / output (I / O) interfaces as well as various network or communication interfaces. The various I / O interfaces may enable communication with user interface devices such as a display 126, a keyboard 128, an electronic mouse 130, and a printer 132, which may be used to view and input configuration information and / or operate the imaging system. Other devices not shown may be useful for interfacing, such as a touchpad, a heads-up display, a microphone, etc. The various network and communication interfaces may enable connection to both local and wide-area intranets and storage networks and the Internet. The various I / O and communication interfaces may utilize wires, lines, or suitable wireless interfaces, as appropriate or desired.

[0034] In one or more embodiments, sensor system 100 may be a handheld sensor system. In one or more embodiments, sensor system 100 may be a wearable sensor system, may be held within a wearable and / or non-wearable transferable object (e.g., military or industrial eyeglass frames), or the like. A wearable device may be worn by a subject, such as a human or animal, may be removably coupled to or integrated with an article worn by the subject (e.g., a shirt, pants, safety vest, protective clothing, eyeglasses, hat, helmet, hearing device, etc.), or may be any alternative device that may be transferable so that the sensor can be moved between different positions, may be stationary or substantially stationary, etc. FIG. 2 shows exemplary locations of different wearable sensors 114. In the illustrated embodiment of FIG. 2, the subject is a human subject, but the subject may also be a mammalian subject, a plant subject, etc.

[0035] 3 shows a non-limiting example design of the sensor 114. The sensing electrode structure 234 of the sensor 114 may be connected to the data acquisition circuitry 116. The sensing electrode structure 234 may be coated with a sensing film 236 (or sensing material). The sensing electrode structure 234, together with the sensing film 236, forms a sensing element 238. The sensing electrode structure 234, together with the sensing film 236 forming the sensing element 238, may be in operative contact with a fluid. The fluid includes one or more analyte gases therein.

[0036] Suitable interdigital electrode structures for probing fluid samples include two-electrode structures and four-electrode structures. Suitable materials for the electrodes include stainless steel, platinum, gold, precious metals, etc. Suitable materials for the substrate may include silicon dioxide, silicon nitride, alumina, ceramics, etc. Suitable examples of sensing materials or sensing films include metal oxide materials, metal oxide semiconductor materials, composite materials, semiconductor materials, n-type semiconductor materials, p-type semiconductor materials, nanocomposite materials, inorganic materials, organic materials, polymeric materials, compounded materials, any known sensing material, etc.

[0037] Suitable electrodes may be formed using metal etching, screen printing, inkjet printing, and mask-based metal deposition techniques. The thickness of the electrodes fabricated on the substrate may range from about 10 nanometers to about 1,000 micrometers. The materials for the interdigital electrode structure, substrate, sensing layer, and electrode formation method may be selected based at least in part on application-specific parameters.

[0038] Also, in the illustrated embodiment, the sensor 114 may include a selector 240 that includes a memory device 242 and a processor 244. In some embodiments, the memory device 242 may include excitation parameters for applying stimuli to the sensing electrode structure 234 and / or the sensing membrane 236. In some cases, the processor 244 may reference the memory device 242 to determine excitation parameters for applying each stimuli at a different excitation frequency to the sensing element 238. In such cases, the processor 244 may provide one or more control signals based on retrieving the excitation parameters.

[0039] For example, the processor 244 may provide one or more control signals to an excitation circuit of the sensor 114 to generate stimuli with different excitation frequencies (or perform a frequency sweep). Further, the excitation circuit of the sensor 114 may apply stimuli to the sensing electrode structure 234, the sensing membrane 236, or both. The sensing element 238 may provide a response signal based on respective receipt of the stimulus signal and based on exposure to one or more analyte gases in proximity / contact of the sensing element 238. The sensitivity of the sensing element 238 to different analyte gases at different concentrations may change based on receipt of stimuli with different excitation frequencies.

[0040] Additionally, the response signal may be received by an impedance analyzer of the sensor 114. If uncompensated, the response signal may include noise from the environment or power source and / or may exhibit drift based on various variables, such as ambient or environmental conditions at the sensor 114. In some embodiments, the impedance analyzer of the sensor 114 may analyze the response signal to reduce baseline drift (e.g., baseline impedance drift) or noise in the response signal, as described in more detail below.

[0041] In some embodiments, processor 244 may include such an impedance analyzer. Alternatively or additionally, the impedance analyzer may be implemented separately from processor 244 and may provide processor 244 with an indication of the analyzed response signal or baseline drift or noise in the response signal. Some embodiments relating to impedance analyzers and excitation circuits are described in more detail below. Furthermore, while selector 240, including memory device 242 and processor 244, is shown as part of sensor 114, it should be understood that in different embodiments, controller 122 (shown in FIG. 1 ) may include memory device 242 and / or processor 244. Alternatively or additionally, memory device 242, processor 244, or both may be implemented as stand-alone components.

[0042] 4 illustrates one embodiment of a multivariable gas sensor 114. The sensor 114 includes a substrate 302, such as a dielectric material, a sensing film or sensing material 236 bonded to the substrate 302, and a sensing element 238 having electrodes 310 and 312. The sensing film 236 is exposed to, in contact with, or indirectly contacts at least one analyte gas.

[0043] In some cases, one or more heating elements 304, such as high resistance resistors, are coupled to a different side of the substrate 302 relative to the sensing film 236. The heating elements 304 receive current from a heater controller 306, which corresponds to hardware circuitry that conducts a heater current or voltage to the heating elements 304 to heat the substrate 302 and the sensing film or sensing film 236 coupled to another side of the substrate 302.

[0044] In one or more embodiments of the subject matter described herein, the sensing film 236 may include a MOS material. The sensing film 236 may include one or more materials deposited on the substrate 302 to function to predictably and reproducibly affect the impedance sensor response upon interaction with an environment. For example, a metal oxide semiconductor material such as SnO may be deposited as the sensing film 236. Other examples of MOS materials include single metal oxides (e.g., ZnO, CuO, CoO, SnO, TiO, ZrO, CeO, WO, MoO, InO), perovskite oxide structures with two different sized cations (e.g., SrTiO, CaTiO, BaTiO, LaFeO, LaCoO, SmFeO), and mixed metal oxide compositions (e.g., CuO_BaTiO, ZnO_WO, SnO_TiO).

[0045] In the illustrated embodiment, the sensing electrodes 310 and 312 are coupled to and / or disposed on or in the sensing film 236 and connected to the substrate 302. The sensing electrodes 310 and 312 are electrical conductors that are conductively coupled to the excitation / detection circuit 314. In some embodiments, the impedance analyzer 332 may include a frequency impedance source and a detector system. For example, the excitation / detection circuit 314 may include an excitation circuit 322 that includes a frequency impedance source and an impedance analyzer 332 that includes a detector system. Alternatively or additionally, the impedance analyzer 332 may include circuitry for transmitting received signals from the sensing electrodes 310 and 312 to the sensor system controller 316 for processing. In either case, in the illustrated embodiment, the sensing electrodes 310 and 312 may be directly and independently conductively coupled to the excitation / detection circuit 314. Alternatively, the sensing electrodes 310 and 312 may not be conductively coupled (eg, indirectly coupled) to one of the excitation circuit 322 and / or the impedance analyzer 332 .

[0046] In some embodiments, the sensor 114 may include a sensor system controller 316. In alternative or additional embodiments, the sensor system controller 316 may be located external to the sensor 114 and operably coupled thereto. For example, the sensor system controller 316 may be coupled to the excitation / detection circuit 314 and the heater controller 306. The sensor system controller 316 may include one or more processing circuits, including one or more processors, microprocessors, field programmable gate arrays, and / or integrated circuits. For example, the sensor system controller 316 may include at least a portion of the processor 244 and / or controller 122 described above.

[0047] In some cases, the sensor system controller 316 may include one or more processing units, each performing one or more functions for analyzing a group of multiple response signals to determine an adjusted response signal. For example, the sensor system controller 316 may include a processor unit for collecting multiple response signals over a range of excitation frequencies. The processor unit may determine the effects of the analyte gas and variable ambient conditions (e.g., not mixing) to facilitate reducing baseline drift and noise caused by the variable ambient conditions. The processor unit or a different processor unit may determine and apply correction values ​​to provide an adjusted response signal. Additionally, one of the aforementioned processor units or a separate processor unit may consider timing (or time constants) associated with detected events, baseline drift changes, and gas mixture variations.

[0048] The sensor system controller 316 may provide one or more control signals to the excitation / detection circuit 314 by controlling the excitation circuit 322. The sensor system controller 316 may provide one or more control signals to apply electrical or electromagnetic stimuli at a single or individual excitation frequency or at a range of different excitation frequencies to interrogate the sensing material or sensing film 236. The sensor system controller 316 may also control the integration time for applying the electrical or electromagnetic stimuli to measure the sensor response at each excitation frequency. The sensor system controller 316 may include one or more processing units, each performing one or more functions to provide one or more control signals and / or measure the sensor response.

[0049] The excitation circuit 322 of the excitation / detection circuit 314 may include circuitry for generating one or more excitation or stimulation signals for interrogating the sensing membrane 236. For example, the excitation circuit 322 may generate the stimulation signals based on one or more control signals indicating the excitation frequency, integration time, and / or amplitude of the stimulation signal from the selector 240. The excitation circuit 322 may apply stimulation to the sensing electrodes 310 and 312, and thereby to the sensing membrane 236.

[0050] Additionally, stimulated electrodes 310 and 312 and sensing membrane 236 may provide one or more response signals based on receiving the stimuli and exposure to one or more analyte gases. In some cases, excitation circuit 322 may apply multiple stimuli (e.g., apply a frequency sweep), each having a different excitation frequency, based on receiving one or more control signals. For example, excitation circuit 322 may receive one or more control signals from, among others, processor 244 of sensor 114 described with reference to FIG. 3, controller 122 associated with sensor 114 described with reference to FIG. 1.

[0051] In some cases, the excitation circuit 322 and / or the impedance analyzer 332 may include processing circuitry, including one or more microprocessors, field programmable gate arrays, and / or integrated circuits. In alternative embodiments, the impedance analyzer 332 may include common and / or unique integrated circuits and / or circuitry that enable the system to operate as either an impedance system and / or a resistance detector system. Additionally or alternatively, the impedance analyzer 332 may include common and / or unique integrated circuits and / or circuitry for providing and / or transmitting received signals to the sensor system controller 316 for processing. For example, the impedance analyzer 332 may include at least a portion of the processor 244 and / or controller 122 described above. In either case, the impedance analyzer 332 may receive electrical signals from the sensing electrodes 310 and 312 that represent the electrical impedance or impedance response of the sensing element 238 during exposure of the sensing membrane 236 to the fluid sample.

[0052] In some embodiments, the sensor system controller 316 may examine the received signals as described herein. For example, the excitation / detection circuitry 314 may provide scanning capabilities to measure the sensor impedance response at single or multiple discrete excitation frequencies. Alternatively, the excitation / detection circuitry 314 may interrogate the sensor 114 to measure the sensor impedance response over a range of excitation frequencies. Thus, each received signal may have a different excitation frequency based on the excitation frequency of the stimulus.

[0053] Thus, the sensor system controller 316 may determine and analyze the impedance variations of the signal provided to the sensing element 238 over a range of excitation frequencies. That is, the sensor system controller 316 may examine the electrical impedance of the sensing element 238 to determine the presence and / or amount (e.g., concentration) of one or more analyte gases in the environment to which the sensing membrane 236 is exposed. In either case, the sensor system controller 316, the processor 244, the controller 122 (described above), or a combination thereof, may receive and analyze the signals by utilizing multivariate curve resolution (MCR) techniques. MCR techniques may include modeling methods for analyzing data from first-order, second-order, and higher-order analytical instruments, such as the sensor 114. Thus, the sensor 114 may analyze a group of multiple response signals to provide or generate an analyzed response signal with reduced noise and / or baseline drift (e.g., a conditioned response signal).

[0054] Further, in alternative or additional embodiments, the excitation circuit 322 may provide stimulation over different ranges of additional variables. Such additional variables may include, among others, temperature, resistance, impedance, voltage, and / or combinations thereof. For example, the sensor system controller 316 may further provide one or more control signals to the heater controller 306 to control the heating element 304 to provide stimulation over a range of temperatures. In such embodiments, the impedance analyzer 332 may receive and analyze response signals based on a range of excitation frequencies and the additional variables (e.g., different temperatures). Thus, the sensor 114 may include circuitry for analyzing one or more analyte gases based on performing a primary measurement (e.g., a sweeping excitation frequency), a secondary measurement based on a range of excitation frequencies and one additional independent variable, a tertiary measurement based on a range of excitation frequencies and two additional independent variables, etc.

[0055] With the above in mind, FIG. 5 shows graph 340 depicting response signal 342 and conditioned response signal 344. For example, excitation circuit 322 may generate a stimulus signal over a range of excitation frequencies over time 346. For example, excitation circuit 322 may generate a stimulus signal over a range of excitation frequencies from 10 kHz to 200 kHz. Steps 360, 362, and 364 are repeated responses of the sensor to three concentrations of NO2: 80, 160, and 240 parts per billion (ppb), collected over time (e.g., a 45-hour test).

[0056] The aforementioned impedance analyzer 332 may receive a response signal 342 that includes noise 348 (e.g., noise effects) and baseline drift 350. The noise 348 may be generated by various variables, such as non-ideal components, ambient conditions of the analyte gas, and / or components of the sensor 114, among others. The baseline drift 350 may be caused by various variables, similar or different, in one instance or over time. In some cases, the baseline drift 350 may be measured relative to a baseline 352. For example, the baseline drift 350 between the response signal 342 and the baseline 352 may change over time. The baseline drift 350 may be measured based on receiving the response signal 342 as a primary measurement, a secondary measurement, etc., using various techniques, such as MCR techniques. In either case, the baseline drift 350 may cause the value of the response signal 342 to shift consistently in the respective direction, and the noise 348 may cause fluctuations and / or random variations in the response signal 342. For example, baseline drift 350 and / or noise 348 may be measured based on the difference in measurements compared to when the sensing element 238 is in contact with clean carrier gas.

[0057] In either case, the conditioned response signal 344 may include reduced noise and / or baseline drift relative to the measured response signal 342. In some cases, the impedance analyzer 332 may include processing circuitry such as at least a portion of the sensor system controller 316, processor 244, and / or controller 122 described above. Alternatively or additionally, the impedance analyzer 332 may receive one or more control signals to perform operations. The operations may include receiving the response signal 342, determining values ​​for noise 348, baseline drift 350, or both, determining a noise reduction value and / or baseline correction value, and reducing the noise 348 and / or baseline drift 350 by the noise reduction value and / or baseline correction value to provide the conditioned response signal 344. In either case, the conditioned response signal 344 may include reduced noise and / or baseline drift relative to the measured response signal 342 based on applying the MCR technique. Additionally, MCR techniques may be used based on providing a stimulus signal and receiving a response signal over a range of excitation frequencies.

[0058] 6 illustrates a process 380 for improving baseline stability and reducing noise in the aforementioned sensor 114, thereby improving the accuracy of sensor performance. Process 380 may be performed by a controller, such as excitation circuit 322 and impedance analyzer 332, controller 122, processor 244, sensor system controller 316, or any other executable processing circuitry. Additionally, in some embodiments, a tangible, non-transitory, computer-readable storage medium, such as memory 242, may store and provide at least a portion of the instructions for performing the functions described herein. It should be understood that the described process blocks are exemplary, and that additional or fewer process blocks may be performed in alternative or additional embodiments. Furthermore, while the process blocks are described in a particular order, in alternative or additional embodiments, the process blocks may be performed in a different order.

[0059] In block 382, ​​the controller may provide multiple signals having different frequencies to the sensing element. For example, the signals may include electrical and / or electromagnetic signals. In some cases, the controller may provide the signals with frequencies within a frequency range and perform a frequency sweep operation based on the frequency range. In some cases, the controller may provide the signals with frequencies within a frequency range and perform steps across a range of frequencies, where the steps can have the same or different widths within the frequency range. In different embodiments, the frequency range may vary based on various variables, such as the type of sensing material 236, the analyte gas of interest, the signal amplitude and / or integration time, among others.

[0060] In block 384, the controller may receive a response signal 342 from the sensing element 384. In some cases, the controller may store the response signal 342 in a memory device, such as memory device 242. In block 386, the controller may determine one or more baseline drift values ​​(e.g., baseline drift 350), one or more sensor response noise values ​​(e.g., noise 348), or both. The controller may execute one or more processor-executable routines, such as a routine for performing a multivariate curve resolution technique on the plurality of response signals to determine a baseline drift value, a sensor response noise value, or both. The noise value may include random short-term fluctuations in the response (e.g., measurements) of the sensor 114 when the sensing element 384 is in contact with the clean carrier gas. The short-term fluctuations are the fluctuations between adjacent (or consecutive) readings of the sensor 114.

[0061] In block 388, the controller may determine one or more baseline correction values, one or more response noise reduction values, or both. In block 390, the controller may reduce one or more baseline drift values, one or more sensor response noise values, or both. The controller may determine one or more baseline correction values ​​based on the one or more baseline drift values ​​and the one or more baseline correction values. Further, the controller may determine one or more sensor response noise values ​​based on the sensor response noise values ​​and the one or more response noise reduction values.

[0062] FIG. 7 shows a graph 390 depicting a response signal 392 and an adjusted response signal 394 according to one embodiment. The graph 390 illustrates the results of applying MCR techniques to correct for baseline drift 396 due to dielectric excitation and reduce baseline noise 398 of the sensor 114 (e.g., primary sensing element), as previously described. As shown in the illustrated example, the sensor 114 may apply the MCR technique to the response signal 392 after a first measurement cycle 393. For example, the response signal 392 illustrates the raw response of the sensor 114 based on applying each measurement cycle by applying an excitation signal to the sensor and observing the sensor responses 360, 362, and 364 over time to three concentrations of NO gas: 80, 160, and 240 ppb. Additionally, the sensor 114 may perform configuration setup or any form of initialization based on the first measurement cycle 393. Accordingly, the sensor 114 may apply the MCR technique to the response signal 392 during a measurement cycle 395 following the first measurement cycle 393. For example, the sensor 114 may be exposed to a fluid such as NO2.

[0063] As previously mentioned, MCR techniques may include modeling methods for analyzing data from primary, secondary, and higher order analytical instruments (e.g., sensors 114). For primary sensors 114, MCR techniques can be described by Equation 1: JPEG2025536879000002.jpg2689

[0064] In Equation 1, D is the multi-frequency impedance data received or determined by the sensor 114 over time. The sensor 114 may provide values ​​of D when exposed to various gas (or fluid) concentrations. In some cases, the sensor 114 may provide D as a data matrix with an m×n data size, where m is the number of recorded multi-frequency impedance data (e.g., impedance spectra) and n is the number of frequencies in the sensor's multi-frequency impedance data. C may include an m×k matrix of data, whose columns include the responses of pure components as a function of time during the transformation. A pure component may include a group of features that may change based on a pattern (e.g., time). For example, the impedance data coming from the sensor's multi-frequency impedance response may not have a pattern. S may include an n×k matrix of data including columns of multi-frequency impedance spectra of each pure component. T may include a mathematical transpose operator. Furthermore, E may include a residual for D (e.g., the raw multi-frequency impedance spectrum), which may account for errors by the model and / or factors not considered.

[0065] Additionally, the sensor 114 (impedance analyzer 332, controller 122, processor 244, sensor system controller 316, or any other possible processing circuitry described above) may determine a noise-reduced 399 adjusted response signal 394 by applying MCR techniques to the response signal 392. Baseline drift 396 may be reduced by applying MCR techniques to the response signal 392.

[0066] FIG. 8 depicts a graph 400 showing non-limiting example results when determining the limit of detection (LOD) of the sensor 114. In the non-limiting example of FIG. 8, an LOD result 402 is determined based on the aforementioned adjusted response signal 394, based on applying MCR techniques to the response signal 392. In one non-limiting example, the LOD result 402 may be determined at 30 kHz (LOD=6 ppb). For example, the LOD result 402 may not be improved by a desired margin (e.g., based on a threshold) by averaging the response signal 392 of the sensor 114 at adjacent frequencies between 10 kHz and 50 kHz (LOD=6.4 ppb). In such cases, the LOD value may be improved based on the desired threshold by applying an MCR algorithm (e.g., by a factor of 3.5 to 3.75). In the illustrated embodiment, applying MCR techniques to the response signal 392 may improve (e.g., reduce) the LOD value to a desired LOD value (e.g., NO detection of 1.7 ppb).

[0067] As used herein, elements or steps listed in the singular and preceded by the word "a" or "an" should be understood as not excluding a plurality of said elements or steps, unless such exclusion is expressly stated. Furthermore, references to "one embodiment" of the subject matter described herein are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features. Furthermore, unless expressly stated to the contrary, embodiments "comprising," "including," or "having" (or similar terminology) an element having a particular characteristic or multiple elements having a particular characteristic can include additional such elements that do not have the specified characteristic.

[0068] As used herein, terms such as "system" or "controller" can include hardware and / or software that operates to perform one or more functions. For example, a system or controller can include a computer processor or other logic-based device that performs operations based on instructions stored in a tangible, non-transitory, computer-readable storage medium, such as a computer memory. Alternatively, a system or controller can include a hardwired device that performs operations based on the device's hardwired logic. The systems and controllers shown in the figures can represent hardware that operates based on software or hardwired instructions, software that directs hardware to perform operations, or a combination thereof.

[0069] As used herein, terms such as "operably connected," "operatively connected," "operably coupled," "operably connected," "operably contacted," "operable contact," and the like indicate that two or more components are connected in a manner that allows or enables at least one of the components to perform a specified function. For example, when two or more components are operatively connected, there may be one or more connections (electrical and / or wireless connections) that allow the components to communicate with each other, allow one component to control another, allow each component to control the other, and / or allow at least one of the components to operate in a specified manner.

[0070] It is to be understood that the subject matter described herein is not limited in its application to the details of construction and the arrangement of elements set forth in the description herein or illustrated in the drawings herein. The subject matter described herein is capable of other embodiments and of being practiced or carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for purposes of description and should not be regarded as limiting. The use of "including," "comprising," or "having," and variations thereof, herein is meant to encompass the items listed thereafter and equivalents thereof, as well as additional items.

[0071] It should be understood that the above description is illustrative, and not limiting. For example, the above-described embodiments (and / or aspects thereof) can be used in combination with each other. Additionally, many modifications may be made to adapt a particular situation or material to the teachings of the subject matter described herein without departing from its scope. While the dimensions, materials, and coating types described herein are intended to define the parameters of the disclosed subject matter, they are by no means limiting and are exemplary embodiments. Many other embodiments will be apparent to those skilled in the art upon reviewing the above description.

[0072] The scope of the subject matter should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. In the appended claims, the terms "including" and "in which" are used as the plain-English equivalents of the terms "comprising" and "wherein," respectively. Moreover, in the following claims, terms such as "first," "second," and "third" are used merely as labels and are not intended to impose numerical requirements on their subject matter. Moreover, the limitations of the following claims are not written in means-plus-function form and are not intended to be construed under 35 U.S.C. § 112(f) unless and until such claim limitations expressly use the phrase "means for" followed by a recitation of a function without further structure.

[0073] This specification uses examples to disclose some embodiments of the present subject matter and to enable those skilled in the art to practice embodiments of the disclosed subject matter, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the subject matter is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims or if they contain equivalent structural elements that differ insubstantially from the literal language of the claims.

Claims

1. A sensing element; a controller configured to provide one or more control signals for monitoring at least one component in the fluid; an excitation / detection system coupled to the sensing element and the controller; Equipped with The excitation / detection system is configured to perform one or more operations based on the one or more control signals, the one or more operations including: providing a plurality of stimulus signals to the sensing element, the excitation / detection system being configured to provide each stimulus signal of the plurality of stimulus signals with a different frequency within a frequency range to the sensing element; receiving a plurality of sensor responses from the sensing element in response to applying the plurality of stimulus signals; determining one or more noise values, one or more baseline drift values, or both based on analyzing the plurality of sensor responses; determining at least one noise reduction value, at least one baseline drift reduction value, or both; reducing at least one noise value of the one or more noise values ​​based on the at least one noise reduction value, reducing at least one baseline drift value based on the baseline drift reduction value, or both; A sensor system comprising:

2. 10. The sensor system of claim 1, wherein analyzing the plurality of stimulus signal responses comprises applying analysis of the plurality of stimulus signals with different frequencies within a frequency range to the sensing element across a radio frequency range of the electromagnetic spectrum.

3. The sensor system of claim 1 , wherein analyzing the plurality of stimulus signal responses comprises applying a multivariate curve resolution algorithm.

4. The sensor system of claim 1 , wherein the sensor system comprises a first order, second order, or higher order sensor.

5. The sensor system of claim 1 , wherein the sensor response comprises an impedance measurement of the sensing element based on applying the plurality of stimulus signals.

6. The sensor system of claim 1 , wherein the one or more baseline drift values ​​include a drift from a baseline value of the sensor when in contact with a clean carrier gas.

7. The sensor system of claim 1 , wherein the one or more noise values ​​comprise a variation in the sensor response when in contact with a clean carrier gas.

8. The sensor system of claim 1 , wherein the sensor system is configured to continuously monitor the concentration of the at least one component in the fluid.

9. The sensor system of claim 1 , wherein the sensor system comprises a primary sensor utilizing a metal-oxide-semiconductor (MOS) material interrogated with an impedance excitation / detection circuit.

10. providing, by a controller of the sensor system, one or more control signals to a sensing element of the sensor system to cause generation of a plurality of stimulus signals, each stimulus signal having a different frequency; receiving, by the controller, a plurality of sensor responses from the sensing element in response to applying the plurality of stimulus signals; determining, by the controller, one or more noise values, one or more baseline drift values, or both based on analyzing the plurality of sensor responses; determining, by the controller, at least one noise reduction value, at least one baseline drift reduction value, or both; reducing, by the controller, at least one noise value of the one or more noise values ​​based on the at least one noise reduction value, reducing at least one baseline drift value based on the baseline drift reduction value, or both; A method comprising:

11. The method of claim 10 , wherein analyzing the plurality of stimulus signal responses comprises applying a multivariate curve resolution algorithm.

12. The method of claim 10 , comprising analyzing a plurality of the plurality of stimulus signal responses with a first order, second order, or higher order sensor.

13. The method of claim 10 , wherein the sensor response comprises an impedance measurement of the sensing element based on applying the plurality of stimulus signals.

14. 11. The method of claim 10, wherein the one or more baseline drift values ​​comprise drift from a baseline value of the sensor when in contact with a clean carrier gas, the one or more noise values ​​comprise variation in the sensor response when in contact with a clean carrier gas, or both.

15. A non-transitory computer-readable medium containing computer-executable instructions that, when executed, cause a processor to: causing a sensing element of the sensor system to provide one or more control signals to an excitation circuit of the sensor system to generate a plurality of stimulus signals, each stimulus signal having a different frequency; receiving a plurality of sensor responses from the sensing element in response to applying the plurality of stimulus signals; determining one or more noise values, one or more baseline drift values, or both based on analyzing the plurality of sensor responses; determining at least one noise reduction value, at least one baseline drift reduction value, or both; reducing at least one noise value of the one or more noise values ​​based on the at least one noise reduction value, reducing at least one baseline drift value based on the baseline drift reduction value, or both. A non-transitory computer-readable medium configured to:

16. 16. The non-transitory computer-readable medium of claim 15, wherein analyzing the plurality of stimulus signal responses comprises applying a multivariate curve resolution algorithm.

17. 16. The non-transitory computer-readable medium of claim 15, wherein the sensor system is a first order, second order, or higher order analytical instrument for analyzing the plurality of responses thereof.

18. 16. The non-transitory computer-readable medium of claim 15, wherein the sensor response comprises an impedance measurement of the sensing element based on applying the plurality of stimulus signals.

19. 16. The non-transitory computer-readable medium of claim 15, wherein the one or more baseline drift values ​​comprise a drift from a baseline value of the sensor when in contact with a clean carrier gas, the one or more noise values ​​comprise a variation in the sensor response when in contact with a clean carrier gas, or both.

20. 16. The non-transitory computer-readable medium of claim 15, wherein the controller is configured to continuously monitor the concentration of the at least one component in the fluid.

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