JP2016126007A - Sensing method and system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a sensing method and system.SOLUTION: A system includes a sensor for measuring a resonant impedance spectral response of an inductor-capacitor-resistor (LCR) resonator and correlating the measured response of one or more spectral parameters to one or more characteristics of a fluid. Such characteristics may be the age or health of the fluid and/or the identification of and concentration of components in the fluid.SELECTED DRAWING: Figure 1

Description

  Embodiments relating to detection methods and systems are disclosed. Sensors such as resonant sensors can include inductor-capacitor-resistor (LCR) sensors that can be used as sensors or transducers to detect fluids.

  Fluid robust detection may be useful in mobile and stationary equipment applications. As an example, if the equipment is a vehicle engine and the fluid is engine oil, knowledge of oil health will reduce or prevent unexpected downtime and provide unnecessary oil change savings, It can be used to help improve service interval planning for locomotives, heavy and light trucks, and vehicles such as mining, construction, and agricultural vehicles. Other examples of stationary equipment applications can include wind turbines and power generation sets. In addition, knowledge about the health of engine oil can prevent or reduce the total lifetime cost of passenger cars, improve control of driving intervals, and extend engine life.

  Standard (traditional) impedance spectroscopy is a technique used to characterize aspects of material performance. In traditional impedance spectroscopy, material can be placed between electrodes and probed over a wide frequency range (from a fraction of a Hz to tens of GHz) to extract basic information about the dielectric properties of the material. However, standard impedance spectroscopy may be limited due to low sensitivity in the reported measurement configuration and very long acquisition times over a wide frequency range.

  It may be desirable to have a system and method that differs from those currently available.

U.S. Pat. No. 8,468,871

  One embodiment of the present disclosure provides a system for analyzing a fluid. The system can include a sensor. The sensor can include a resonant inductor-capacitor-resistor (LCR) circuit, a detection region that includes at least a portion of the LCR circuit, and a controller coupled to the detection region. The detection region can be placed in operative contact with the fluid of interest. The controller can receive an electrical signal from the sensor. The signal can represent the resonant impedance spectrum of the detection region in operative contact with the fluid over the measured spectral frequency range. The signal can be used to analyze a resonant impedance spectrum and determine one or more characteristics of the fluid based on the analyzed resonant impedance spectrum.

  In one embodiment, the method includes exciting a sensor that contacts the fluid. The sensor can include an LCR resonant circuit that operates at one or more frequencies in the frequency range of analysis. A signal can be received from the sensor over the frequency range of the analysis. The signal includes information about the sensor in contact with the fluid. One or more characteristics of the fluid may be determined based at least in part on the resonant impedance spectrum.

  In one embodiment, a system is provided that includes a resonant sensor and a controller. The sensor can detect the complex dielectric constant of the fluid. The controller can be coupled to the sensor and can receive electrical signals from the sensor. The signal can represent the resonant impedance spectrum of the fluid over the measured spectral frequency range. The controller can determine the complex dielectric constant of the fluid based at least in part on the resonant impedance spectrum.

  These and other features can be understood by reading the following detailed description with reference to the accompanying drawings. In the accompanying drawings, like reference numerals designate like parts throughout the views.

1 is a block diagram of a system for evaluating fluid according to one embodiment of the present disclosure. FIG. 1 is a schematic diagram of a resonant sensor according to an embodiment of the present disclosure. FIG. 1 is a schematic diagram of a portion of an example sensor system that uses a sensor assembly configured to detect fluid using multiple frequencies, in accordance with an embodiment of the present disclosure. FIG. FIG. 3 is a diagram illustrating an example of an equivalent circuit of a resonance sensor according to an embodiment of the present disclosure. FIG. 3 illustrates an example of an RFID tag adapted for resonance detection, where a detection region comprises all or part of a resonant antenna, according to one embodiment of the present disclosure. FIG. 3 is a diagram illustrating an example of an RFID tag adapted for resonance detection in which a detection region is in direct contact with an antenna and a memory chip according to an embodiment of the present disclosure. 4 is a graph of measured resonant impedance parameters of one embodiment of a resonant sensor, according to an embodiment of the present technology. FIG. 3 is a diagram illustrating an example of a resonant sensor in which a detection region is disposed parallel to a sensor axis insertion into a fluid to be measured, and thus perpendicular to an insertion port of the sensor, according to an embodiment of the present disclosure. FIG. 3 is a diagram illustrating an example of a resonant sensor in which a detection region is disposed perpendicular to a sensor axis insertion into a fluid to be measured and therefore parallel to an insertion port of the sensor, according to an embodiment of the present disclosure. A fluid reservoir when the sensor is incorporated in a reservoir, the detection region of the sensor is exposed to fluid, and the sensor reader is located near the sensor and connected to the sensor by a cable, according to one embodiment of the present disclosure It is a figure which shows an example of the detection of the fluid characteristic by the sensor inside. Detection of fluid properties by a sensor in a fluid reservoir when the sensor is incorporated into the reservoir, the detection region of the sensor is exposed to fluid, and the sensor reader is directly connected to the sensor, according to one embodiment of the present disclosure It is a figure which shows an example. 6 is a flow chart of fluid evaluation according to an embodiment of the present disclosure. FIG. 6 is a plot of resonant impedance data for detecting engine oil, water, and fuel with highlighted water leakage. FIG. 5 is a plot of resonant impedance data for detecting engine oil, water, and fuel with highlighted fuel leaks. It is a figure which shows the principal component analysis of the resonance impedance spectrum parameter. FIG. 4 is a correlation plot of actual (measured) and predicted concentrations of water in a water / fuel / oil mixture using a single resonant sensor. FIG. 6 is a correlation plot of actual (measured) concentration and predicted concentration of fuel in a water / fuel / oil mixture using a single resonant sensor. It is a plot of spectral parameters showing the resolution of the resonant sensor for distinguishing between hexane and toluene. Figure 5 is a spectral parameter plot showing the resolution of water added to dioxane. It is a plot of the real part of the resonance impedance spectrum after adding soot and water. It is a plot of the imaginary part of the resonance impedance spectrum after adding soot and water. It is a figure which shows the PCA score plot of PC1 vs. PC2 when a sensor is exposed to 5 types of solutions and resonance impedance measurement is performed. FIG. 4 shows a plot of four resonant spectral profiles from a single sensor for uncontaminated dioxane. It is a figure which shows the plot of the resonance spectrum profile from a single sensor at the time of adding water to a dioxane. FIG. 6 is a plot of the effect of sensor design on Fp measurement sensitivity. FIG. It is a figure which shows the influence of the sensor design with respect to the measurement sensitivity of Zp. It is a plot of the measurement result of the water in oil by two multivariable resonance sensors. FIG. 3 is a score plot of the developed PCA model of the response of a resonant sensor to the addition of water at different temperatures, showing different response directions. FIG. 6 is a plot of the results of a multivariate linear regression model using a partial least squares approach to quantify the concentration of water in oil using a single sensor response. FIG. 3 is a plot of actual (measured) concentration of water in oil (solid line) and predicted concentration (open circles) over time at three temperatures. FIG. 3 is a plot of predicted error between actual and predicted concentration of water in oil over time at three temperatures. FIG. 4 is a plot of the correlation between the actual (measured) concentration of water in oil at three temperatures and the predicted concentration. FIG. 6 is a plot of actual (measured) concentration of water in oil (solid line) and predicted concentration (open circle) over time at three temperatures using multivariable resonance sensor and oil temperature sensor responses. FIG. 5 is a plot of the predicted error between the actual and predicted concentration of water in oil over time at three temperatures using the multivariable resonant sensor and oil temperature sensor response. FIG. 5 is a plot of the correlation between the actual (measured) concentration of water in oil at three temperatures and the predicted concentration using the multivariable resonance sensor and oil temperature sensor responses. Response of the developed resonant sensor to water leakage into engine oil at levels of 25, 25, and 50 ppm, respectively. Reference capacitance sensor response to water leakage into engine oil at levels of 25, 25, 50, 100, 200, 500, and 1000 ppm, respectively. The inset shows the response to the initial water leak. Response of the developed resonant sensor to water leakage into engine oil at levels of 25, 25, 50, 100, 200, 500, and 1000 ppm, respectively. The inset shows the response to the initial water leak. Fig. 4 shows ~ 34 days operation of a developed resonance sensor in a single cylinder locomotive engine. It shows oil temperature and sensor response. The correlation between the response of the developed resonance sensor in the single cylinder locomotive engine for ˜34 days and the oil temperature is shown. 1 is a schematic view of a dynamic signature of a leak in a typical part of an internal combustion engine.

  Embodiments relating to detection methods and systems are disclosed. Sensors such as resonant sensors can include inductor-capacitor-resistor (LCR) sensors that can be used as sensors or transducers to detect fluids. Provided herein are sensors having portions that are resonant structures that exhibit analyzable changes in the presence of fluids and various components or contaminants within the fluids.

  In one embodiment, the sensor can include an inductor-capacitor-resistor (LCR) resonator circuit, which has a resonant frequency response given by the resonant impedance (Z) of this circuit. The sensor provided herein is capable of detecting a target characteristic in the presence of a varying noise source and can operate under varying temperature conditions and is stable over time. Can provide performance. Disclosed herein is a sensor that includes an inductor-capacitor-resistor (LCR) resonator, which can function as a sensor or a transducer. The resonant impedance spectrum of the sensor can be measured via inductive coupling between the pickup coil and the sensor, or can be measured directly by connecting to a sensor reader. The electrical response of the sensor can be translated into a change in the resonant impedance of the sensor.

  Non-limiting examples of individual sensor signal changes can include coupled simultaneous resonant impedance changes, inductance changes, resistance changes, and capacitance changes. The preferred sensors and systems disclosed herein can increase the ability to measure changes in fluids such as engine oil or fuel by contacting the sensor between the electrodes that make up the resonant circuit of the sensor. The resonant circuit of the sensor can be an electrical resonant circuit. Other resonant circuits may include mechanical resonators, in which case changes in fluid viscosity and / or density affect the response of the mechanical resonator.

  Examples of suitable mechanical resonators include tuning fork resonators, thickness-slip mode resonators, crystal resonator microbalance resonators, surface acoustic wave resonators, and bulk acoustic wave resonators. Unlike these and other mechanical resonators, the effects of changes in fluid viscosity and / or density may not be predictable in electrical resonators. Instead, in an electrical resonator, the effect of changes in the complex permittivity of the fluid can be predictable. Electrical resonators can be very complex in design, for example marginal oscillators require complex multi-part circuits.

  Degradation of at least some oils and lubricants may produce molecules and / or other components that may be more polar than the oils and lubricants from which they are formed. The base oil or lubricant can contain long chain hydrocarbon molecules with weak polarity. Thus, the presence of polar contaminants can increase one or more portions of the complex permittivity of the oil.

  According to one aspect, the resonant transducer operates as a reconfigurable resonant structure and is configured with multiple frequencies to monitor fluid conditions (eg, the health of equipment in contact with such fluid). Probing the dielectric properties of any sample more accurately where there is an uncontrolled ambient noise contribution. Monitoring fluid health includes determining the composition or contamination of such fluids.

  Non-limiting examples of the contribution of interfering substances and ambient environmental noise can include the presence of temperature or interference in the sample. The term “interference” includes undesirable environmental parameters that adversely affect the accuracy and accuracy of sensor measurements. The term “interfering substance” refers to a material or environmental condition that can potentially cause a false sensor response. Filters (physical, chemical, and / or electronic) can be used based on application specific parameters to reduce, eliminate, or take into account the presence and / or concentration of such interfering substances. .

  Referring to FIG. 1, a system 10 that is useful for evaluating contacting fluid is shown. For illustrative purposes, the representative fluid may be engine oil. The system can include a fluid reservoir 12 for fluid and sensor 14. Alternatively, the sensor may be disposed in the fluid flow path. The sensor may be a resonant sensor disposed in or on the reservoir, or may be coupled to an in-line connector in fluid communication with a fluid reservoir defining a flow path. In one embodiment, the sensor can provide continuous monitoring of fluid in the reservoir or flow path.

  Suitable fluids may include hydrocarbon fuels and lubricants. Suitable lubricants include engine oil, gear oil, working fluid, lubricating oil, synthetic lubricant, lubricating fluid, grease, silicone, and the like. Suitable fuels can include gasoline, diesel fuel, jet fuel or kerosene, biofuel, petroleum diesel biodiesel fuel mixture, natural gas (liquid or compressed), and fuel oil. Still other fluids may be insulating oil in the transformer, a solvent, or a mixture of solvents. Still other fluids may include correspondingly suitable sensor parameters such as water, air, engine exhaust, biological fluids, and organic and / or vegetable oils. The fluid may be a liquid or a gas phase. In addition, multiphase compositions are envisioned.

  Non-limiting examples of various fluid components can include unintentional leakage from proximity systems (eg, radiator fluid into engine oil or water condensation in diesel fuel or transformer oil). Other detectable fluid components may include fluid degradation products due to high temperature operation or contact with an oxidant (such as air). The operation of the system may introduce fluid components such as dirt, salt, soot or carbon, wear metal particles, wear products. In some environments, dirt from bacteria or the like may be a fluid component. In all cases, indirect measurements such as an increase in pH indicating the presence of acidic components may be useful.

  The sensor can detect the characteristics of the fluid by the resonant impedance spectral response. One or more of the LCR resonators can measure the resonant impedance spectral response. In contrast to simple resonant impedance measurements, the disclosed embodiments probe the sample with at least one resonant electrical circuit. The resonant impedance spectrum of a sensor in proximity to the sample (a sensor in operative contact with the fluid) varies based on the sample composition and / or composition and / or temperature. The measured resonant impedance values Z ′ (which may be the real part Zre of the resonant impedance) and Z ″ (which may be the imaginary part Zim of the resonant impedance) are fluids (eg, to the sensor) for stimulation of the electric field of the resonant circuit. Reflects the response of the adjacent fluid part).

  The electric field can be applied by the sensor via the electrode. The electrode can be in direct or indirect electrical contact with the sample. For example, a sensor may be a combination of a detection region and related circuitry. The detection area may be bare or coated with a protective dielectric layer. In either case, the detection region can be considered in operative contact with the fluid. In such embodiments, the tuning circuit is not in direct contact with the fluid. An example of indirect electrical contact with the sample is when the electrode structure to be detected is coated with a dielectric protective coating, and after an electric field that can be generated between the electrodes penetrates the dielectric protective coating. This may be the case when interacting with the fluid. A suitable dielectric protective coating can be applied consistently to the electrodes.

  Suitable sensors can include single use or multiple use sensors. A suitable multi-use resonant sensor may be a reusable sensor that can be used during the lifetime of the system that can be incorporated. In one embodiment, the resonant sensor may be a disposable sensor that can be used during all or part of the reaction or process. For example, the resonant sensor includes one or more electrode pairs and one or more tuning elements that are, for example, resistors, capacitors, inductors, resonators, impedance transformers, or combinations of two or more thereof. And an inductor-capacitor-resistor (LCR) resonant circuit operating at at least one resonant frequency can be formed. In certain embodiments, different resonant circuits of the plurality of resonant circuits of the resonant sensor can be configured to resonate at different frequencies. The different frequencies can be selected to traverse the dispersion profile of the fluid composition being measured. The dispersion profile may be a dependence of the dielectric properties of the fluid composition on the probe frequency. Various components of the fluid have different dispersion profiles. When measured at multiple resonance frequencies, the concentration of different components of the fluid can be determined.

  Data from the resonant sensor can be obtained by a data collection circuit 16 that may be associated with the sensor or a control system such as a controller or workstation 22 that includes a data processing circuit. The control system can perform additional processing and analysis. A controller or workstation can include one or more wireless or wired components and can communicate with other components of the system. Suitable communication models include wireless or wired. At least one suitable radio model includes a radio frequency device, such as RFID radio communications. Other wireless communication modes can be used based on application specific parameters. For example, if there can be EMF interference, a particular aspect can function when other aspects do not function. The data collection circuit can be placed in the fluid reservoir as shown in FIG. Other suitable locations may include placement within the workstation. In addition, the workstation can be replaced with an overall process control system, in which case the resonant sensor and its data acquisition circuitry can be connected to the process control system.

  In operation, the monitoring process includes, inter alia, internal combustion engines, oil-filled transformers, chemical reaction processes, biological reaction processes, purification and / or separation processes, catalyst processes, general combustion processes, raw oil production, It can be coupled to raw gas production, material extraction, and other industrial process operations. The data collection circuit may be in the form of a sensor reader and can be configured to communicate wirelessly or wired with a fluid reservoir and / or workstation. For example, the sensor reader may be a battery operated device and / or use energy available from the main control system or from an ambient source (light, vibration, heat, or electromagnetic energy). Power may be supplied using the collection of energy.

  Further, the data collection circuit receives data from one or more resonant sensors 14 (eg, a plurality of sensors formed in an array, or a plurality of sensors disposed at different locations in or around the fluid reservoir). be able to. Data can be stored in short-term or long-term memory storage, such as an archival communication system, which can be located in or away from the system and / or reconfigured for an operator, such as at an operator workstation Can be displayed. Non-limiting examples of the placement and installation of sensors and sensor systems of the present technology can include fuel or fluid reservoirs, associated piping components, connectors, flow-through components, and any other associated processing components. .

  In addition to displaying data, the operator workstation can control the above-described operations and functions of the system. The operator workstation may include one or more processor-based components, such as a general purpose or special purpose computer 24. In addition to processor-based components, computers can include a variety of memory and / or storage components, including internal memories such as magnetic and optical mass storage devices, RAM chips, and the like. The memory and / or storage components can be used to store programs and routines for performing the techniques described herein, which are executed by associated components of an operator workstation or system. Can do. Alternatively, the programs and routines can be stored in computer-accessible storage and / or memory that is remote from the operator workstation but can be accessed by a network and / or communication interface present on the computer. The computer may also include various input / output (I / O) interfaces, as well as various network or communication interfaces. Various I / O interfaces can enable communication with user interface devices such as display 26, keyboard 28, mouse 30, and printer 32, which are used to view and enter configuration information and / or Or it can be used to operate an imaging system. Other devices such as touchpads, head-up displays, microphones, etc., not shown, may be useful for interfacing. Various networks and communication interfaces can allow connections to both local and wide area intranets, as well as storage networks and the Internet. The various I / O and communication interfaces may use wires, lines, or suitable wireless interfaces as appropriate or required.

  The sensor can include a plurality of resonant circuits that can be configured to probe the fluid in the fluid reservoir at a plurality of frequencies. The fluid reservoir is surrounded by a designed fluid impermeable wall, by a naturally formed fluid impermeable wall, or by a distance of electromagnetic energy emitted from the sensor area to probe the fluid It may be a reservoir. In addition, different frequencies can be used to probe fluid samples at different depths. In certain embodiments, an integrated circuit memory chip can be DC coupled to a resonant sensor. Integrated circuit memory chips can contain different types of information. Non-limiting examples of such information in the memory of the integrated circuit chip include sensor calibration factor, sensor lot number, date of manufacture, and end user information. In another embodiment, the resonant sensor can be a comb structure that can be part of a resonator and has a detection region.

  In certain embodiments, when the integrated circuit memory chip can be dc coupled to the resonant sensor, reading the sensor response uses a sensor reader that includes circuitry operable to read the analog portion of the sensor. Can be done. The analog portion of the sensor may include a resonant impedance. The digital portion of the sensor may include information from the integrated circuit memory chip.

  FIG. 2 shows a non-limiting example of a resonant sensor design. The sensing electrode structure 34 of the sensor can be connected to a tuning circuit and a data acquisition circuit. The sensing electrode structure 34 is bare and can be in direct contact with the fluid. Alternatively, the detection electrode structure may be coated with a protective coating 36. The detection electrode structure forms a detection region 38 with or without a protective coating. The coating can be deposited consistently and can be a dielectric material. The detection electrode structure can operatively contact the fluid with or without a protective coating that forms the detection region. The fluid contains an analyte or contaminant. The detection electrode structure may or may not have a protective coating (bare). The bare sensing electrode structure can generate an electric field that interacts directly with the fluid between the electrodes. A sensing electrode structure having a dielectric protective coating can generate an electric field between the electrodes that interacts with the fluid after penetrating the dielectric protective coating. In one embodiment, the coating can be deposited on the electrodes so as to form a conformal protective layer having the same thickness on all electrode surfaces and between the electrodes on the substrate. If a coating is deposited on the electrode to form a protective layer, the coating may have a final thickness that is substantially constant or variable across the substrate and the sensor electrode on the substrate. In another embodiment, the substrate simultaneously functions as a protective layer when the electrode is separated from the fluid by the substrate. In this scenario, the substrate has an electrode that may not be in direct contact with the fluid on one side, and the other side of the substrate does not have an electrode that faces the fluid. The detection of the fluid can be performed when the electric field from the electrode penetrates the substrate and enters the fluid. Preferable examples of such a substrate material include ceramic, aluminum oxide, and zirconium oxide.

  FIG. 3 shows a portion of a resonant sensor system having a single detection region 38 that is used in a sensor assembly 40 useful for probing a fluid sample using multiple frequencies. The detection region can be disposed on the substrate and can include a suitable detection material. In some embodiments, the sensor substrate may be a dielectric substrate. In some embodiments, the sensor assembly can include a plurality of tuning elements 42. Multiple tuning elements can be operably coupled to a single detection region so as to define multiple resonant circuits. The tuning element can define multiple resonant circuits with a single detection region. Each resonant circuit of the plurality of resonant circuits may include one or more tuning elements of the plurality of tuning elements. Semi-permeable membranes, semi-permeable membranes, or semi-permeable inorganic barriers (collectively “selective barriers” that allow (or prevent) selective analytes or contaminants through the selective barrier and into the detection region ") Is not shown.

  Suitable comb electrode structures include two and four electrode structures. Suitable materials for the electrode include stainless steel, platinum, gold, noble metals and the like. Suitable materials for the substrate and / or dielectric protective layer include silicon dioxide, silicon nitride, parylene, silicone, fluorinated polymer, alumina, ceramic, and the like. Suitable electrodes can be formed using metal etching, screen printing, ink jet printing, and mask-based metal deposition techniques. The thickness of the electrode fabricated on the substrate can range from about 10 nanometers to about 1000 micrometers. The comb electrode structure, substrate, dielectric protective layer material, and electrode formation method can be selected based at least in part on application specific parameters.

  As shown in the illustrated embodiment, the plurality of tuning elements may be located outside the sensor. However, in one embodiment, the tuning element may be located on the sensor substrate. In another embodiment, some of the plurality of tuning elements may be external to the sensor substrate and other tuning elements may be disposed on the substrate. The tuning element can include a resistor, a capacitor, an inductor, a resonator, an impedance transformer, or a combination thereof.

  The sensor assembly 40 can include a controller having a multiplexer 44. The multiplexer can facilitate electronic switching between multiple tuning elements. The multiplexer can select one or more signals related to the probe frequency and transfer the selected signals to an output device or reader. In one embodiment, the multiplexer can selectively send a signal to an output device or reader. The multiplexer can send multiple signals simultaneously to the sensor reader. The multiplexer can facilitate electronic switching between multiple detection regions.

  During operation, each resonant circuit can resonate at a defined frequency. At least one resonant circuit can resonate at a frequency that can be different from the resonant frequency of the other resonant circuit. As an example, if the detection region includes a pair of electrodes, the tuning element can be a resistor, a capacitor, and an inductor that form an inductor-capacitor-resistor (LCR) resonant circuit. The tuning element can be electrically coupled to the detection region. In one embodiment, the tuning element may be connected in parallel to the detection region. In certain embodiments, different resonant circuits of the plurality of resonant circuits can be configured to resonate at different frequencies. Different resonant circuits can be configured to probe the fluid sample with multiple resonant frequencies. Different resonant frequencies can be used to probe the fluid sample over a frequency range of spectral dispersion. The spectral dispersion that can be monitored with the sensors of the present disclosure can range from about 0.1 Hz to about 100 GHz, with spectral dispersion limited by alpha, beta, gamma, delta, and application specific parameters. Other types can be included.

  FIG. 4 shows another sensor circuit 10. A sensing region 38 (indicated by a variable resistor and a variable capacitor) is coupled to the tuning component 42 (indicated by a variable inductance and a variable capacitance). Additional circuit elements can be used to tune the frequency range to achieve sensor response at different frequency ranges. Thus, the sensor can operate in multiple frequency ranges by using a defined or selected combination of additional circuit components such as inductors, capacitors, and impedance transformers. These components can be connected in parallel or in series with the sensor as needed to change the operating frequency range. The controller can control the impedance conversion ratio that affects the sensitivity. The frequency response of the sensor and its magnitude may be based at least in part on changes in the overall input resonant impedance due to the response of the sensor to the state of the cell, its behavior, etc. Therefore, the sensitivity of the sensor can be controlled by the possibility of dynamic adjustment of the conversion ratio. Adjusting the response of each channel can be accomplished, for example, using one or more inductors. In one embodiment, wireless readout from the electrodes can improve response selectivity and sensitivity. In one embodiment, transformer based coupling can eliminate parasitic LCR components from instrumentation (especially analyzers, cables). The LCR resonator of FIG. 4 is relatively low compared to other resonators, for example, compared to a marginal oscillator that requires a complex multi-component circuit for operation including, for example, a current feedback amplifier and other components. Has a simple design.

  As described herein, a suitable wireless sensor may be a radio frequency identification (RFID) sensor, and a passive RFID tag can be adapted to perform a detection function. 5A and 5B show one embodiment where the resonant sensor can be a compatible RFID tag. In FIG. 5A, the resonant antenna 50 and the memory chip 52 can be coated with a protective or sensing material 56. The detection material may be a detection region of the RFID tag. In FIG. 5B, detection regions (which can optionally include protective or detection material) can be attached to both ends of the antenna. In both cases (FIGS. 5A and 5B), the electrical response of the detection region can be translated into a change in the resonant impedance response of the sensor. An RFID sensor having a memory chip can operate at a frequency determined at least in part by the operating frequency used by the memory chip. That is, several operating frequencies (sensor and chip) may interfere with each other and, although less desirable, may have destructive harmonics or destructive waveforms. Further, the sensor can have a detection area and / or antenna that is circular, square, cylindrical, rectangular, or other suitable shape.

  The resonance frequency of the antenna circuit can be set to a frequency higher than the resonance frequency of the sensor circuit. The frequency difference may be, for example, in a range from about 4 times to about 1000 times. In one embodiment, the sensor circuit may have a resonant frequency that can respond to the determined detected environmental conditions. Two resonant circuits can be connected, and thus direct current energy can be applied to the sensor resonant circuit when alternating current (AC) energy is received by the antenna resonant circuit. AC energy can be supplied using diodes and capacitors, and AC energy is sensor resonant via the LC tank circuit, either by a tap in L of the LC tank circuit or a tap in C of the LC tank circuit. Can be transmitted to the circuit. In addition, two resonant circuits can be combined so that the voltage from the sensor resonant circuit changes the impedance of the antenna resonant circuit. The modulation of the impedance of the antenna circuit can be achieved using transistors, for example FETs (field effect transistors).

  The memory chip of the RFID sensor may be arbitrary. An RFID sensor without a memory chip can be a resonant LCR sensor and can operate in different frequency ranges from kilohertz to gigahertz. That is, the absence of a memory chip can widen the usable frequency range.

  Preferred detection materials and detection films disclosed herein include materials deposited on the sensor to perform functions that predictably and reproducibly affect the resonant impedance sensor response when interacting with the environment. Can be included. For example, conducting polymers such as polyaniline change their conductivity when exposed to solutions of different pH. That is, when such a conductive polymer film is deposited on the surface of an RFID sensor, the resonant impedance sensor response changes as a function of pH. Therefore, such an RFID sensor works as a pH sensor.

As an example of gaseous fluid detection, when such a polyaniline film is deposited on an RFID sensor for detection in the gas phase, the composite resonant impedance sensor response is also basic (eg, NH ₃ ). Or it changes when exposed to acidic (eg, HCl) gas. Suitable sensor films include polymer films, organic films, inorganic films, biological films, composite films, and nanocomposite films whose electrical and / or dielectric properties change based on the environment in which they are placed. . Other examples of sensor films include commercially available sulfonated polymers such as Nafion, adhesive polymers such as silicone adhesives, inorganic films such as sol-gel films, composite films such as carbon black and polyisobutylene films, and carbon nanotubes and Nafion films. Such as nanocomposite film, gold nanoparticle polymer film, metal nanoparticle polymer film, zeolite, organometallic structure, cage compound, clathrate, clathrate compound, electrospun polymer nanofiber, electro Spinned inorganic nanofibers, electrospun composite nanofibers, and other sensor materials selected based on application specific parameters may be used. In order to reduce or prevent the sensor membrane material from leaking into the liquid environment, the sensor material can be attached to the sensor surface using standard techniques such as covalent bonding, electrostatic bonding, and other techniques. .

  In one embodiment, the system includes a resonant impedance of the sensor

(Represented by formula (1)) can be measured.

Here, Z _re (f) may be a real part of resonance impedance, and Z _im (f) may be an imaginary part of resonance impedance. In one embodiment, the resonant impedance response of the sensor can be a multivariable response because multiple frequencies can be used to measure the sensor response across the resonance of the sensor. In some embodiments, multiple frequencies can be used to measure the sensor response outside the sensor's resonant peak, so the resonant impedance response of the sensor can be a multivariable response. In some embodiments, the sensor response can be measured at multiple frequencies across the resonance of the sensor. For example, if the sensor resonates at about 1 MHz, the measured frequency and associated sensor response can be measured from about 0.25 MHz to about 2 MHz. Multivariate responses can be analyzed by multivariate analysis. The multivariable response of the sensor is measured by several independent measurements such as, but not limited to, the sensor's full resonant impedance spectrum and F _p , Z _p , F _z , F ₁ , F ₂ , Z ₁ and Z _2. Including the specified characteristics.

FIG. 6 shows a graph of measured resonant impedance parameters of one embodiment of a resonant sensor, according to an embodiment of the present technology. These and other measured characteristics can be “spectral parameters”. These characteristics are the maximum frequency (F _p , resonance peak position) of the real part of the resonance impedance, the size (Z _p , peak height) of the real part of the resonance impedance, the zero reactance frequency (F _z , the resonance impedance). Imaginary part of resonance impedance (F ₁ ), anti-resonance frequency (F ₂ ) of imaginary part of resonance impedance, resonance frequency (F ₁ ) of imaginary part of resonance impedance Signal magnitude (Z ₁ ), and the signal magnitude (Z ₂ ) at the antiresonance frequency (F ₂ ) of the imaginary part of the resonance impedance. Other parameters can be measured using the overall resonant impedance spectrum, such as the quality factor of the resonance, the phase angle, and the magnitude of the resonant impedance.

  In order to measure fluid properties in a fluid reservoir, sensors with their detection areas can be designed to fit standard ports or ports specially made in the reservoir. A preferred design example is shown in FIGS. 7A and 7B. An embodiment of a resonant sensor 50 having an aligned detection area 51 is shown. The detection region defines a first axis A, which is perpendicular to the horizontal axis labeled axis B. The insertion port structure 53 defines an elongated insertion opening 54 along the axis A. The detection area is then placed parallel to the elongated opening in the port, and translation along axis B allows the sensor area to be inserted into the port and contact the fluid under measurement. An alternative resonant sensor 55 embodiment is shown in FIG. 7B where the sensing material 56 is not constrained by the shape relative to the opening 57 defined by the port structure 58. The alignment pins are not shown, but can be used as desired to align the sensor and detection area with respect to the port opening.

  Measurement of fluid properties in the fluid reservoir can be performed using a sensor having a detection region exposed to the fluid, as shown in FIGS. 8A and 8B. The sensor shown in FIG. 7B is installed in a fluid transfer pipe 59A and coupled to a sensor reader 59B. As shown in FIG. 8A, the sensor reading device is coupled by a wire or a cable, and can be arranged close to the sensor. In another embodiment, the sensor reader can be connected directly to the sensor without using a cable, as shown in FIG. 8B. In operation, fluid flows through the pipe and contacts the detection area. When the detection area detects the target analyte, it sends a signal to the sensor reader.

  A flowchart of the method 60 is shown in FIG. In one embodiment, a method for monitoring the health of oil includes immersing the sensor in a fluid such as oil (step 62), and electrical resonances of the resonance spectrum at several resonances of a single sensor. Measuring parameters (step 64). In order to use the sensor to quantify water, fuel leakage, and soot contamination of the engine oil, the sensor can be placed in operative contact with the fluid at step 62. In a specific embodiment, the resonant impedance spectrum of a sensor such as a sensor

Can be determined at step 64. For example, the frequency position F _p and the magnitude Z _p of Z _re (f), and the resonance frequency F ₁ and anti-resonance frequency F ₂ , and the magnitudes Z ₁ and Z _{2 of} Z _im (f), and Z _im ( f) measured zero reactance frequency F _z etc.

Parameters from the spectrum can be calculated.

  The method 60 classifies the electrical resonance parameters at step 70. This can be done, for example, using the determined classification model 72 for evaluating one or more of the water effect 74, the fuel effect 75, and the temperature effect 76. The quantification of the electrical resonance parameters includes a predetermined, previously stored quantification model 82, determination of components 86 in the oil, such as water, fuel, soot, and wear metal particles 90 and temperature 92; This can be done in step 80 by using soundness 98 and engine soundness 100 predictions. This can be done by using one or more of the determined engine health descriptor 102 and oil health descriptor 104 and inputs from any additional sensors 108. Suitable additional sensors may include those that detect erosion, temperature, pressure, system (engine) load, system location (eg, via GPS signals), equipment age calculator, and pH.

For example, in one embodiment, the sensor system may be an electrical resonator that can be excited by wired or wireless excitation, in which case the resonance spectrum is collected and analyzed to automatically scale or average the parameters. Extracting at least four parameters that can be further processed in a centered manner, quantitatively predicting water and fuel concentrations in engine oil, and predicting engine oil remaining life and / or engine remaining life it can. Spectral responses of resonant spectra such as F _p , Z _p , F _z , F ₁ , F ₂ , Z ₁ and Z ₂ , or the overall resonant spectrum of single or multiple resonators are used for data processing. be able to.

  The classification model (see model 72 in FIG. 9) uses the predicted contribution of the spectral parameters for uncontaminated fluid and the previously determined component effects and their corresponding spectral parameters for fluid contamination. Can be used to build. Such an effect can be quantified to predict whether the measured or detected fluid has a water effect, a fuel leakage effect, or a temperature effect (eg, the quantification model 82 of FIG. reference). That is, based on previously or empirically determined effects of a particular fluid component, if the desired component is present, both real and imaginary parts of the resonance parameter are affected so that they can be quantified. It is possible to receive. Furthermore, based on the measured parameters, the concentration of a specific component can also be predicted, and a multi-component model can be generated. The disclosed techniques can be used to detect appropriate fluids and build component and environmental effect models.

  In one embodiment, the measurement of fluid properties can be made at more than one temperature of the fluid. Measurements at different temperatures relate to the species of interest and other species (chemical constituents) in the fluid when measured as a frequency dispersion profile over a wide frequency range or as a frequency response over a relatively narrow frequency range. Provide information. Analyzing the resonance impedance spectrum of sensors collected at different temperatures and determining two or more characteristics of the fluid per temperature based on the analyzed resonance impedance spectrum, thereby determining the characteristics of the target chemical species Accuracy can be improved. This improvement may be due to differences in the frequency response of the species of interest and other species in the fluid as a function of temperature due to the molecular structure of these different species. Measurements at different temperatures can be performed using a resonance sensor having a thermal element in thermal contact with the detection area of the resonance sensor. The thermal element produces a local change in the temperature of the fluid that can be proximate to the detection region. This local temperature change can be above or below the temperature of the bulk of the fluid in the container with the sensor. Non-limiting examples of thermal elements include Peltier elements, thin film heaters, and pencil heaters. The thermal element can produce a local change in the temperature of the fluid in the range of about 1 ° C to about 50 ° C.

  In one embodiment, measurement of the properties of the fluid can be performed to determine a dynamic signature of a change in chemical composition in the fluid. The time scale of these dynamic signatures can vary greatly. A suitable time scale ranging from about 1 second to about 200 days may be useful for determining various types of fluid leaks in the engine. Such a determination allows the identification of a dynamic signature of leaks in the engine, the relationship between the identified signatures and known leak signatures from a particular engine component, and the determination of the leak location based on the signatures. .

  Measurement of fluid properties can be performed under extreme temperature conditions. Depending on the application, these conditions may be in the temperature range from about −260 ° C. below to about + 260 ° C. above. Such harsh temperature conditions of negative temperatures up to about −260 ° C. can be useful in connection with liquefied natural gas (LNG) and for the storage of biological and other types of samples. Severe temperature conditions with positive temperatures up to about + 260 ° C. can be useful for monitoring equipment where the temperature of the operating parts of the device can reach about + 260 ° C. Examples of such equipment include, for example, drilling equipment in oil and gas production, and internal combustion engines (diesel, natural gas, hydrogen (direct combustion or fuel cells) for one or more fuels. ), Gasoline, and combinations thereof), lubrication systems, and cooling / heat dissipation system operations. Another example of such equipment is an oil-filled transformer.

  The applicability of multivariable electrical resonators can be demonstrated by detecting contamination of engine oil with water and diesel fuel and determining water in model fluids such as dioxane, which has a dielectric constant similar to oil . The resolution of sensor measurement can be determined using hexane and toluene as a model system. Some engine oil samples were obtained from GE Transportation, but other chemicals can be purchased from Aldrich.

  The resonance impedance of the sensor can be measured using a network analyzer (Agilent) or a precision impedance analyzer (Agilent) under computer control using LabVIEW. The collected resonant impedance data is run by Matlab (Mathworks, Natick, Mass.), KaleidaGraph (Reading, PA) Synergy Software, Inc. and PLS_Toolbox (Eicharvector, Manson, WA).

  Different amounts of fuel leaks and water leaks to oil can be determined quantitatively and experimentally using a single multivariable resonant sensor. A suitable oil may be a railway internal combustion engine oil. A suitable fuel may be diesel fuel. Binary and ternary mixtures of water and fuel in oil can be produced in various proportions. The concentration of water may be 0, 0.1%, and 0.2% (volume%). The concentration of fuel may be 0, 3%, and 6% (volume%).

  Resonance spectra from measured samples could be processed, and the processed data served as input to a principal component analysis (PCA) tool. PCA may be a pattern recognition method that describes the distribution of data as a weighted sum of original variables known as principal components (PC). The highlight of detecting water in a mixture of engine oil, water, and fuel can be seen in FIG. 10, which shows a score plot of the developed PCA model. The highlight of the detection of fuel in a mixture of engine oil, water, and fuel can be seen in FIG. 11, which shows a score plot of the developed PCA model. In FIGS. 10 and 11, the 0.1% and 0.2% water concentrations are labeled as W0.1 and W0.2, respectively. The fuel concentrations of 3% and 6% are labeled as D3 and D6, respectively. The multivariable response of the resonant transducer is generated from the entire measured resonant spectrum of the transducer by processing these spectra using a multivariate analysis tool. Resonance impedance spectrum of resonant transducer to quantify engine oil contamination due to water and fuel leaks using a single multi-variable sensor

Can be measured. Measured as shown in FIG.

Can calculate a number of parameters from the spectral, it frequency location F _p, and Z _re (f) the size of Z _p, and the resonant frequency F ₁ and the anti-resonance frequency F _2, and Z _im (f) size Z ₁ and Z _2, as well as zero-reactance frequency F _z of Z _im (f).

By using multivariate analysis of the calculated parameters of the spectrum, the analytes can be classified. Analysis techniques suitable for multivariate analysis of spectral data from multivariable sensors include principal component analysis (PCA), independent component analysis (ICA), linear discriminant analysis (LDA), and flexibility discriminant analysis (FDA). Can do. PCA can be used to distinguish various vapors using peptide-based detection materials. The addition amount plot of the PCA model is shown in FIG. This plot shows the contribution of individual components from the resonance spectrum. The plot shows that _{F p, F 1, F 2} , F z, Z p, all components, such as Z _1, and Z ₂ had contributed to the sensor response.

  Quantification of water and fuel in binary and ternary mixture oils was performed using a single PLS toolbox (Eigenvector Research, Manson, WA) operating in Matlab (Mathworks, Natick, Mass.). This can be further done with a multivariable resonant sensor. FIG. 13 shows a correlation plot of the actual (measured) concentration of water in the water / fuel / oil mixture and the predicted concentration using a single resonant sensor. FIG. 14 shows a correlation plot of measured and predicted concentrations of fuel in a water / fuel / oil mixture using a single resonant sensor. The predicted error of the simultaneous quantification of water and fuel in oil with a single sensor can be 0.02% for water and 1.3% for fuel.

  In another example, the resolution of the sensor can be determined in a multipart experiment. In the first experiment, hexane and toluene can be used as model chemicals to determine the ability of the sensor to analyze the difference in dielectric constant. Hexane has a dielectric constant of 1.88 and toluene has a dielectric constant of 2.38. The developed sensor can analyze these two liquids with a dielectric constant resolution of 0.0004-0.0012. Expected results are shown in FIG. 15A. In the second experiment, 1,4-dioxane can be used as a model chemical for oil because it has a dielectric constant similar to oil and can be easily miscible with water. The sensor can analyze water addition in dioxane up to 7-20 ppm. The expected results are shown in FIG. 15B, where the developed sensor adds water in units of 200 ppm and analyzes the water addition in dioxane (model system for oil) to 7-20 ppm. It shows what you can do.

In another example, water and soot (carbon black) can be added to dioxane and measured using a sensor. Water addition can be performed as 500 ppm, 1000 ppm, 2500 ppm addition. Soot (carbon black) can be added as 100 ppm carbon black with 2500 ppm water. The resonance spectrum of an exemplary sensor is shown in FIGS. 16A and 16B. The results of multivariate analysis are shown in FIG. 16A shows the real part Z _re (f) of the resonant impedance, and FIG. 16B shows the imaginary part Z _im (f) of the resonant impedance. Samples measured were (0) clean model oil (dioxane), (1) 500ppm water added, (2) 1000ppm water added, (3) 2500ppm water added, 4) What added 2500 ppm water and 100 ppm soot (carbon black) may be used. FIG. 17 shows a score plot of principal component 1 vs. principal component 2 showing the spectral relationship between sensor responses to different types of contamination. Samples are (0) clean model oil (dioxane), (1) 500ppm water added, (2) 1000ppm water added, (3) 2500ppm water added, (4) What added 2500 ppm of water and 100 ppm of soot (carbon black) may be used.

  In another example, a composite resonant sensor system having four resonant frequencies can be constructed. 1,4-Dioxane can be used as a model chemical for oil, because its dielectric constant is somewhat similar to oil and miscible with water. Water addition is performed on dioxane and can be measured using a sensor. Four exemplary resonance spectra of the sensor are shown in FIGS. 18A and 18B. These values indicate that the dispersion profile of the sensor in uncontaminated dioxane (FIG. 18A) changed its shape with the addition of water (FIG. 18B). In addition, the width and size of the resonance peak are changed by adding water.

In another example, the sensor electrode shape and resonant frequency can be optimized to maximize the response of F _p , Z _{p to} water. The two-factor design of the experiment can be performed by changing the interval D and the electrode width W of the comb electrode (IDE) and changing the resonance frequency F _p , where D = W = 150, 300, 450 micrometers (μm) and F _p = 20, 35, 50 MHz (in air). The measurement can be performed by adding water to dioxane at a concentration of 5000 ppm. Figure 19 shows the effect of sensor design on the sensitivity of F _p measurement. Figure 20 shows the effect of sensor design on the sensitivity of the Z _p measured. With an IDE spacing of 300 μm and an operating frequency of 50 MHz, both strong F _p and Z _p signals were obtained.

In another example shown in FIG. 21, the determination of water in oil circulates oil in a test loop and adds water in increments of 2000 ppm to produce water concentrations in the oil of 2000 ppm, 4000 ppm, and 6000 ppm. Can be executed. Measurements can be made using two resonant sensors. Sensor 1 had an area of 2 cm ² , electrode width / interval of 0.4 mm / 0.4 mm, and resonated at 80 MHz in air. The sensor 2 may be one of the geometric shapes according to the design of the experiment, it has an area of 4 cm ² , the electrode width / spacing is 0.15 mm / 0.15 mm, in air at ~ 50 MHz. Resonated. The detection limit for water in oil is 3-12 ppm (sensor 1) and 0.6-2.6 ppm (sensor 2) based on the measured sensor noise level and the signal level when 2000 ppm of water is added. Three signal-to-noise levels can be determined.

  In another example, the determination of water in oil at different oil temperatures is accomplished by circulating the oil in a test loop and adding water in 400 ppm increments to give water concentrations in the oil of 400 ppm, 800 ppm, 1200 ppm, and 1600 ppm. It can be executed by generating. The nominal temperature of the oil is generated by a hot bath and can be T1 = 80 ° C., T2 = 100 ° C., and T3 = 120 ° C. FIG. 22 shows a score plot of the developed PCA model, indicating that the response of the resonant sensor to the addition of water at different temperatures may be in different directions. The individual arrows in FIG. 22 indicate the direction in which the water concentration at the oil temperatures T1, T2, and T3 is increased. FIG. 23 can represent the results of a multivariate linear regression model using a partial least squares (PLS) approach to quantify the concentration of water in oil using a single sensor response. The PLS technique can determine the correlation between the independent variable and the sensor response by determining the direction in the multidimensional space of the sensor response that explains the maximum variance of the independent variable. FIG. 24 shows that such multivariate linear regression can predict water concentration independent of oil temperature.

  The analysis of this sensor data to determine the water (0 ppm, 400 ppm, 800 ppm, 1200 ppm, and 1600 ppm) in the oil at different nominal temperatures of the oil (80 ° C., 100 ° C., and 120 ° C.) is a multivariate nonlinear (second order) Can be done using regression. FIG. 24A shows the actual (measured) concentration (solid line) and the predicted concentration (open circles) of water in oil at three temperatures. FIG. 24B shows the predicted error between the actual and predicted concentration of water in the oil at three temperatures. FIG. 24C shows a correlation plot of the actual (measured) concentration of water in the oil at three temperatures and the predicted concentration.

  Analysis of this sensor data to determine the water (0 ppm, 400 ppm, 800 ppm, 1200 ppm, 1600 ppm) in the oil at different nominal temperatures (80 ° C., 100 ° C., 120 ° C.) was placed in the measured oil Further can be done using multivariate nonlinear (second order) regression with additional inputs from the temperature sensor. FIG. 25A shows the actual (measured) concentration (solid line) and the predicted concentration (open circles) of water in oil at three temperatures. FIG. 25B shows the predicted error between the actual and predicted concentration of water in the oil at three temperatures. FIG. 25C shows a correlation plot of the actual (measured) concentration of water in the oil at three temperatures and the predicted concentration.

One of the developed multivariate sensors having an area of 4 cm ² , electrode width / spacing of 0.15 mm / 0.15 mm and resonating in air at ˜50 MHz is a low concentration in oil Water leakage can be measured. FIG. 26 shows the response of this developed resonant sensor to water leaks into engine oil at levels of 25 ppm, 25 ppm, and 50 ppm, respectively. The data in the figure shows that this sensor can detect at least the lowest test level of 25 ppm water leak with high signal-to-noise quality.

  The performance of this developed resonant sensor can be compared to the performance of a standard non-resonant capacitance sensor that serves as a reference capacitance sensor. The comparison can be made by placing both sensors in the same oil circulation loop and introducing and presenting a water leak to both sensors. Water leakage levels can be 25, 25, 50, 100, 200, 500, and 1000 ppm. FIG. 27A shows the response of a reference capacitance sensor to water leaks into engine oil at levels of 25, 25, 50, 100, 200, 500, and 1000 ppm, respectively. This figure shows that the reference capacitance sensor did not show measurable signal changes from its noise until 25, 25, 50, 100, and 200 ppm water leaks could be introduced. On the other hand, FIG. 27B shows the response of a resonant sensor according to one embodiment to a water leak into engine oil, which can detect a minimum water leak of 25 ppm and was presented to both sensors. All other water leaks can be detected.

  This resonant sensor can be tested on an engine test bench of a single cylinder locomotive for about 34 days. FIG. 28A can show the results of operation of a developed resonant sensor in a single cylinder locomotive engine for oil temperature and sensor response. FIG. 28B shows the correlation between the response of the developed resonance sensor in the single cylinder locomotive engine for about 34 days and the oil temperature.

  In another embodiment, by identifying a dynamic signature of a leak, correlating the identified signature with a known leak signature from a particular engine component, and determining the location of the leak based on the signature, The source of leakage can be determined. Such an approach can provide proactive maintenance capabilities, can replace responsive maintenance, and increase the usage time of assets with lubrication systems or with internal combustion engines be able to.

  Non-limiting examples of such assets with an internal combustion engine can include various vehicle types, each having its own set of operating parameters. Embodiments disclosed herein can provide a prognostic sensor tool for early determination of leak components with a dynamic leak signature. These sensors can be applied at multiple locations within the engine to identify the source of the leak. FIG. 29 shows a turbocharger (1-2 turbochargers per engine), an intercooler (2 intercoolers per engine), a water pump (1 water pump per engine), and a cylinder head (12-16 cylinders per engine). FIG. 3 shows a schematic diagram of a dynamic signature of a head) leak.

  Technical effects can include techniques for assessing fluid health, such as engine oil health. Such techniques can determine if the fluid is likely to be contaminated or need to be replaced, providing business and overall processing benefits, such as fluids used in engines In the case of providing improved engine health.

  This specification uses examples to disclose the invention and to enable those skilled in the art to practice embodiments of the invention, and includes making and using an apparatus or system and performing a method. It is out. The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. If such other embodiments have structural elements that do not differ from the literal language of the claims, or if they contain equivalent structural elements that do not differ substantially from the language of the claims, this Such other embodiments are intended to be within the scope of the claims.

10 System 12 Fluid Reservoir 14 Resonant Sensor 16 Data Acquisition Circuit 22 Controller / Workstation 24 General Purpose or Application Specific Computer 26 Display 28 Keyboard 30 Mouse 32 Printer 34 Detection Electrode Structure 36 Protective Coating 38 Single Detection Area 40 Sensor Assembly 42 Tuning element / tuning component 44 Multiplexer 50 Resonant antenna 51 Aligned detection area 52 Memory chip 53 Insertion port structure 54 Insertion opening 55 Resonance sensor 56 Protection material / detection material 57 Opening 58 Port structure 59A Fluid transfer pipe 59B Sensor reading Apparatus 60 method 62 step 64 step 70 step 72 determined classification model 74 water effect 75 fuel effect 76 temperature effect 80 step 82 quantification model 86 component 92 temperature 98 oil Health 100 Engine health 102 Engine health descriptor 104 Oil health descriptor 108 Additional sensors

Claims (23)

Sensors (14, 55, 108),
A resonant inductor-capacitor-resistor (LCR) circuit;
A detection region (38, 51) including at least a part of the LCR circuit,
The detection region (38, 51) is configured to be placed in operative contact with a fluid of interest (14, 55, 108);
A controller (22) coupled to the detection region (38, 51),
An electrical signal is received from the sensor (14, 55, 108), the signal representing a resonant impedance spectrum of the detection region (38, 51) in operative contact with the fluid over a measured spectral frequency range. ,
Analyzing the resonance impedance spectrum;
A system (10) comprising: a controller (22) configured to determine one or more characteristics of the fluid based on the analyzed resonant impedance spectrum.   The system (10) of claim 1, wherein the operable contact is a direct contact with the fluid.   Dielectric protection configured to isolate the detection region (38, 51) from direct contact with the fluid while maintaining operable contact between the fluid and the detection region (38, 51). The system (10) of claim 1, further comprising a layer.   The system (10) of claim 1, wherein the detection region (38, 51) comprises a detection material (56).   The sensing material (56) is a dielectric and is chemically inert to the fluid or resistant to degradation by the fluid at temperatures ranging from about 1 ° C. to about 260 ° C. The system (10) of claim 4, wherein the system (10) is chemically resistant.   The sensing material (56) is a dielectric and is chemically inert or chemically resistant to the fluid at temperatures ranging from about 0 ° C. to about −260 ° C. The system (10) according to claim 4,.   The controller (22) is configured to determine the characteristic of the fluid by identifying the one or more components based on a characteristic change of the resonance parameter associated with the one or more components. The system (10) of claim 1, wherein:   The controller (22) is configured to determine the property of the fluid by quantifying the one or more components based on a property change of the resonance parameter associated with the one or more components. The system (10) of claim 1, wherein:   The system (10) of claim 8, wherein the one or more components comprise one or more of water, soot, wear products, or hydrocarbons.   The system (10) of claim 1, wherein the fluid comprises one or more of oil, water, a solvent, a mixture of solvents, or a fuel.   The system (10) of claim 1, wherein the sensor (14, 55, 108) is a passive RFID sensor.   The system (10) of claim 1, wherein the controller (22) is configured to analyze the resonant impedance spectrum by analyzing at least four spectral parameters of each of the resonant impedance spectra. Wherein the controller (22), said resonant parameter F _p, by _{Z p, F 1, Z 1} , F 2, or if further analyzing at least one or more of Z _2, analyzes the resonance impedance spectrum The system (10) of claim 12, wherein the system (10) is configured as follows.   The tuning component further comprises one or more tuning components (42) coupled to each LCR circuit configured to couple or separate each LCR circuit to the detection region (38, 51) based on a tuning input. The system (10) of claim 1.   The system (10) of claim 14, wherein the tuning input is based on a desired frequency range of the sensor (14, 55, 108).   The system (10) of claim 14, wherein the tuning component (42) comprises one or more variable inductors or capacitors.   Thermal contact with the detection area (38, 51) of the sensor (14, 55, 108) and supply at least one of local heating or local cooling adjacent to the detection area (38, 51) The system (10) of claim 14, further comprising a thermal element configured as described above.   A resonance impedance spectrum of the sensor (14, 55, 108) is analyzed based on the signal and configured to determine one or more characteristics of the fluid based on the analyzed resonance impedance spectrum. The system (10) of claim 1, further comprising a processing circuit.   The sensor (14, 55, 108) is operably coupled to a memory chip (52), and the sensor (14, 55, 108) is at least partially due to the operating frequency used by the memory chip (52). The system (10) of claim 1, wherein the system (10) operates at a determined frequency. Exciting sensor (14, 55, 108) in contact with a fluid, including an LCR resonant circuit configured to operate at one or more frequencies in the frequency range of analysis And steps to
Receiving a signal containing information about a resonant impedance spectrum of the fluid from the sensor (14, 55, 108) over the frequency range of the analysis;
Determining one or more characteristics of the fluid based at least in part on the resonant impedance spectrum.   21. The method (60) of claim 20, further comprising determining a dynamic signature for a change in chemical composition of the fluid over time or under determined conditions.   Obtaining one or more signatures of the fluid based at least in part on the resonant impedance spectrum of the fluid at one or both of a fluid temperature and a fluid complex permittivity. 21. The method (60) of claim 20, further comprising responding to one or both changes. A resonant sensor (14, 55, 108) configured to detect a complex permittivity of the fluid;
A controller (22) coupled to the sensor (14, 55, 108),
Receiving an electrical signal from the sensor (14, 55, 108), the signal representing a resonant impedance spectrum of the fluid over a measured spectral frequency range;
A system (10) comprising: a controller (22) configured to determine a complex dielectric constant of the fluid based at least in part on the resonant impedance spectrum.