Description:FORM 2

THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENT RULES, 2003

COMPLETE SPECIFICATION
(See Section 10 and Rule 13)

Title of invention:

METHOD AND SYSTEM FOR MEASURING VISCOSITY OF NON-NEWTONIAN FLUIDS

Applicant

Tata Consultancy Services Limited
A company Incorporated in India under the Companies Act, 1956
Having address:
Nirmal Building, 9th floor,
Nariman point, Mumbai 400021,
Maharashtra, India

Preamble to the description:

The following specification particularly describes the invention and the manner in which it is to be performed.
CROSS-REFERENCE TO RELATED APPLICATIONS AND PRIORITY
The present application is a patent of addition to Indian Patent Application No. 202121052119, filed on November 13, 2021, the entire content of which is hereby incorporated herein by way of reference.
TECHNICAL FIELD
The disclosure herein generally relates to viscosity measurement and, more particularly, to method and system for measuring viscosity of Non-Newtonian fluids.
BACKGROUND
Viscosity is a mechanical property of a fluid. It is a measure of resistance to fluid flow. Viscosity measurements are commonly used in the medical field to measure blood viscosity. One of the critical industrial requirements for viscosity measurement or monitoring viscosities is for Non-Newtonian fluids such as example in paint manufacturing. There are various methods and markers that can be used to measure changes in sample viscosity. However, these methods are generally very time-consuming, laboratory-scale, and involve many complex calculations. Recently, a highly sensitive and non-invasive sensing method known as Photo Acoustic (PA) sensing technique is widely used to determine the viscosity of fluid samples. This is done by determining the full-width-at-half-maximum (FWHM) of the PA spectra.
Conventionally, viscosity is consistently monitored throughout the paint manufacturing process. To measure viscosity, a paint sample is extracted from a paint batch and transferred to a quality check (QC) laboratory. This process is repeated until a definite value of viscosity is reached.
In a laboratory setting, viscosity is usually measured using a viscometer or a cup based method such as a Zahn-4 cup. In certain cases, operators may rely on their own experience to measure viscosity during the painting process. However, these methods are tedious, time-consuming, and error-prone. Therefore, a fast and accurate viscosity measurement system is required.
The Applicant has addressed concerns and limitations in the art, in applicant’s Indian patent application No. 202121052119, filed on November 13, 2021, titled method and system for non-invasive mechanism providing simultaneous determination of viscosity-temperature variation of lubricant for predicting machine health provides viscosity measurement system that can be conveniently installed near the manufacturing tank to simplify the painting process. However, the Indian patent application No. 202121052119 is limited to Newtonian fluids such as lubricants. Applying the method and system of the Indian patent application No. 202121052119 to Non-Newtonian fluids requires enhancements in accordance with characteristics of Non-Newtonian fluids.
SUMMARY
Embodiments of the present disclosure present technological improvements as solutions to one or more of the above-mentioned technical problems recognized by the inventors in conventional systems.
For example, in one embodiment, a method for measuring viscosity of Non-Newtonian fluids is provided. The method includes triggering an excitation signal for generating a plurality of sweep frequency intensity modulated Continuous-Wave (CW) laser beam via a plurality of CW laser diodes placed in an excitation circuit incident on a Non-Newtonian fluid held in an optically transparent container. An ultrasound sensor placed in contact with the optically transparent container having the Non-Newtonian fluids using an acoustic coupling gel receives a plurality of Photo Acoustic (PA) signals generated within the Non-Newtonian fluids irradiated with each CW laser diode.
Further, a Vector Network Analyzer (VNA) processes the plurality of PA signals with reference to the excitation signal received from each CW laser diode to generate an in-phase (I) component and a quadrature phase (Q) component for each PA signal of each CW laser diode in a frequency domain to obtain a PA magnitude spectra in the frequency domain for each PA signal from each CW laser diode by applying a swept frequency acoustic interferometry principle.
Further, a signal to noise ratio (SNR) for each PA signal of corresponding CW laser diode is computed to select a PA signal with highest SNR from among the plurality of PA signals of the plurality of CW laser diodes. Then, an Inverse Fourier Transform is applied over the PA magnitude spectra of the selected PA signal to obtain an equivalent time domain PA signal to identify a first peak and a second peak of the time domain PA signal using a time windowing.
Furthermore, the amplitude of the time domain PA signal is normalized with respect to the maximum amplitude of the same signal to calculate an PA attenuation in the Non-Newtonian fluids by obtaining a ratio of maximum amplitude of the first peak and the second peak. Then, viscosity ? of the Non-Newtonian fluids is measured by plotting a calibration curve based on the PA attenuation and ground truth values.
In another aspect, a system for measuring viscosity of Non-Newtonian fluids is provided. The system includes triggering an excitation signal for generating a plurality of sweep frequency intensity modulated Continuous-Wave (CW) laser beam via a plurality of CW laser diodes placed in an excitation circuit incident on a Non-Newtonian fluid held in an optically transparent container. An ultrasound sensor placed in contact with the optically transparent container having the Non-Newtonian fluids using an acoustic coupling gel receives a plurality of Photo Acoustic (PA) signals generated within the Non-Newtonian fluids irradiated with each CW laser diode.
Further, a Vector Network Analyzer (VNA) processes the plurality of PA signals with reference to the excitation signal received from each CW laser diode to generate an in-phase (I) component and a quadrature phase (Q) component for each PA signal of each CW laser diode in a frequency domain to obtain a PA magnitude spectra in the frequency domain for each PA signal from each CW laser diode by applying a swept frequency acoustic interferometry principle.
Further, a signal to noise ratio (SNR) for each PA signal of corresponding CW laser diode is computed to select a PA signal with highest SNR from among the plurality of PA signals of the plurality of CW laser diodes. Then, an Inverse Fourier Transform is applied over the PA magnitude spectra of the selected PA signal to obtain an equivalent time domain PA signal to identify a first peak and a second peak of the time domain PA signal using a time windowing.
Furthermore, the amplitude of the time domain PA signal is normalized with respect to the maximum amplitude of the same signal to calculate an PA attenuation in the Non-Newtonian fluids by obtaining a ratio of maximum amplitude of the first peak and the second peak. Then, viscosity ? of the Non-Newtonian fluids is measured by plotting a calibration curve based on the PA attenuation and ground truth values.
In yet another aspect, a non-transitory computer readable medium for measuring viscosity of Non-Newtonian fluids is provided. The system includes triggering an excitation signal for generating a plurality of sweep frequency intensity modulated Continuous-Wave (CW) laser beam via a plurality of CW laser diodes placed in an excitation circuit incident on a Non-Newtonian fluid held in an optically transparent container. An ultrasound sensor placed in contact with the optically transparent container having the Non-Newtonian fluids using an acoustic coupling gel receives a plurality of Photo Acoustic (PA) signals generated within the Non-Newtonian fluids irradiated with each CW laser diode.
Further, a Vector Network Analyzer (VNA) processes the plurality of PA signals with reference to the excitation signal received from each CW laser diode to generate an in-phase (I) component and a quadrature phase (Q) component for each PA signal of each CW laser diode in a frequency domain to obtain a PA magnitude spectra in the frequency domain for each PA signal from each CW laser diode by applying a swept frequency acoustic interferometry principle.
Further, a signal to noise ratio (SNR) for each PA signal of corresponding CW laser diode is computed to select a PA signal with highest SNR from among the plurality of PA signals of the plurality of CW laser diodes. Then, an Inverse Fourier Transform is applied over the PA magnitude spectra of the selected PA signal to obtain an equivalent time domain PA signal to identify a first peak and a second peak of the time domain PA signal using a time windowing.
Furthermore, the amplitude of the time domain PA signal is normalized with respect to the maximum amplitude of the same signal to calculate an PA attenuation in the Non-Newtonian fluids by obtaining a ratio of maximum amplitude of the first peak and the second peak. Then, viscosity ? of the Non-Newtonian fluids is measured by plotting a calibration curve based on the PA attenuation and ground truth values.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
BRIEF DESCRIPTION OF THE DRAWINGS
The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles:
FIG.1 illustrates is a functional block diagram of a system implemented for measuring viscosity of Non-Newtonian fluids using the system of FIG.1, in accordance with some embodiments of the present disclosure.
FIG.2 illustrates a viscosity measurement module of the system of FIG.1, in accordance with some embodiments of the present disclosure.
FIG.3A and FIG.3B illustrates a flow diagram illustrating a method for measuring viscosity of Non-Newtonian fluids using the system of FIG. 1, in accordance with some embodiments of the present disclosure.
FIG.4 depicts a time domain Photo Acoustic (PA) signal obtained by processing the PA signal using the system of FIG.1, in accordance with some embodiments of the present disclosure.
FIG.5 depicts a calibration curve plotted based on PA attenuation and ground truth values using the system of FIG.1, in accordance with some embodiments of the present disclosure.
DETAILED DESCRIPTION OF EMBODIMENTS
Exemplary embodiments are described with reference to the accompanying drawings. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. Wherever convenient, the same reference numbers are used throughout the drawings to refer to the same or like parts. While examples and features of disclosed principles are described herein, modifications, adaptations, and other implementations are possible without departing from the scope of the disclosed embodiments.
Paint is a complex colloidal Non-Newtonian fluid that is applied to various substrates such as walls, metals, plastic, glass, and the like. In addition to providing aesthetic value, the finished paint layer protects the substrate from weather, corrosion, wear, and other factors. Paint solutions usually consists of binders, solvents, pigments, and additives in proportions appropriate to the task. Paint manufacturers utilize these different components of paint in a large tank and blend then in various stages until a certain rheology is achieved. One of the critical rheological boundaries in the paint manufacturing is its viscosity.
Conventional techniques have explored ultrasound, micro-electro-mechanical-system (MEMS) based sensors, and vibration spectroscopy for rapid viscosity measurement. Moreover, vibrational spectroscopy techniques such as Raman spectroscopy or infrared are or limited applicability in manufacturing settings because these techniques are only effective in the absence of external light. Some other viscosity sensors, such as capillary, falling ball, and oscillating sensors, require the sensor to be immersed in the fluid, making them less suitable for paint applications. Therefore, these limitations highlight the need for a rapid, non-invasive, accurate, scalable, efficient, and field-deployable method for viscosity measurement in paint manufacturing.
The Applicant has addressed concerns and limitations in the art of Indian patent application No.202121052119, titled filed on November 13, 2021, by providing a compact Photo Acoustic (PA) sensing technique for viscosity measurement in paints which are water and solvent based. The applicants Indian patent application No.202121052119 focusses only on Newtonian fluids to provides an non-invasive mechanism to determine the temperature change of lubricant viscosity to predict health of the machine by using a Laser-enabled swept frequency acoustic interferometry (LE-SFAI). However, Non-Newtonian fluids such as paint is complex colloidal substrate where viscosity depends on shear rate and further additions and improvements to the system are appreciated that may improve the accuracy of viscosity measurement in light of Newtonian fluids.
Thus, in order to provide an accurate, time efficient and cost efficient system, the embodiments herein provide a method and system for measuring viscosity in Non-Netwonian fluids. The method of the present disclosure is a Photo Acoustic hybrid sensing modality that includes optical excitation and acoustic acquisition. Laser pulse or the intensity modulated continuous wave (CW) laser irradiates the Non-Newtonian fluid such as paint sample under test, causing a small temperature excursion. Subsequently, the Non-Newtonian fluids rests in a non-radiative manner to generate a plurality of Photo Acoustic (PA) signals. These plurality of PA signals are acquired using an ultrasound sensor which is placed in contact with the paint sample container through an acoustic coupling gel.
Referring now to the drawings, and more particularly to FIG. 1 through FIG.5, where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments and these embodiments are described in the context of the following exemplary system and/or method.
FIG.1 illustrates is a functional block diagram of a system implemented for measuring viscosity of Non-Newtonian fluids using the system of FIG.1, in accordance with some embodiments of the present disclosure. A set up for measuring viscosity in Non-Newtonian fluids is depicted in FIG.1. A Vector Network Analyzer (VNA) 112, for example, Bode-100™, provides excitation for generating a plurality of sweep frequency intensity modulated Continuous-Wave (CW) laser beam via a plurality of CW laser diodes (106a, 106b…106n) placed in an excitation circuit incident on a Non-Newtonian fluid held in an optically transparent container 108.
The optically transparent container 108 may contain sample Non-Newtonian fluid such as standard paint sample from Asian Paints™ for viscosity measurement. Since the frequency sweep signal current from the VNA 112 is low, a CW laser driver 114 connected to the DC power supply unit 104 provides adequate current modulation to the excitation circuit. The intensity of each CW laser diode 106a, 106b…106n is modulated using a custom laser driver 114. The laser driver 114 supplies a swept frequency of about (from 100 kHz to 1.2 MHz) modulated current to each CW laser diode 106a, 106b…106n which in turn modulate its intensity. Each CW laser driver 114 with the power supply unit 104 described herein can provide the sinusoidal current modulation for each CW laser diode at a wavelength of about 450nm and a maximum peak power of 0.5W. The power supply unit 104 is used to provide a proper bias and DC offset to the laser driver 114 using the DC power supply unit 104.This sweep frequency intensity modulated CW laser beam irradiates the paint sample placed in the optically transparent container.
An ultrasound sensor 110 used here is an Olympus™ (V-303 SU) which is placed in contact to the sample optically transparent container 108 using the acoustic coupling gel. Subsequently, the ultrasound sensor 110 then receives a plurality of Photo Acoustic (PA) signals generated within the Non-Newtonian fluids paint sample held by the optically transparent container 108 irradiated with each CW laser diode 106a, 106b…106n. Here, the plurality of Photo Acoustic (PA) signals are generated by the sample Non-Newtonian fluids which propagates within the optically transparent container 108 and are acquired by the ultrasound sensor 110 (Olympus™, V-303 SU).
The Vector Network Analyzer (VNA) 112 processes the plurality of PA signals with reference to the excitation signal received from each CW laser diode 106a, 106b…106n to generate an in-phase (I) component and a quadrature phase (Q) component for each PA signal of each CW laser diode in a frequency domain.
Each CW laser diode is placed in an excitation circuit emitting light at different respective wavelengths.
Then, PA magnitude spectra is obtained in the frequency domain for each PA signal from each CW laser diode 106a, 106b…106n by applying a swept frequency acoustic interferometry principle.
Further, a Signal to Noise Ratio (SNR) is computed for each PA signal of corresponding CW laser diode to select a PA signal with highest SNR from among the plurality of PA signals of the plurality of CW laser diodes 106a, 106b…106n.
Then, Inverse Fourier Transform is applied over the PA magnitude spectra of the selected PA signal to obtain an equivalent time domain PA signal.
The selected PA signal is processed to identify a first peak and a second peak of the time domain PA signal using a time windowing. The amplitude of the time domain PA signal is normalized with respect to the maximum amplitude of the same PA signal. A ratio of maximum amplitude of the first peak and the second peak by calculating an PA attenuation in the Non-Newtonian fluid(s). The viscosity ? of the Non-Newtonian fluid(s) is measured by plotting a calibration curve based on the PA attenuation and ground truth values. For analysis and viscosity measurement, each PA signal from the ultrasound sensor 110 is retrieved into the computer’s memory through the Vector Network Analyzer 112 (VNA, Bode™-100 from Omicron Lab). Immediately to the PA data retrieval, the paint sample is used with Zahn-4 cup to measure the viscosity. This viscosity value function as a ground truth for calibration.
The viscosity ? is measured from the time domain PA signal which is processed through the PA magnitude spectra.
The viscosity ? is a function of the slope of the calibration curve and the PA attenuation.
In one implementation, the paint being a high viscosity Non-Newtonian fluid possesses high acoustic attenuation. Therefore, ultrasound (PA) signals require a very high Signal to Noise Ratio (SNR). The plurality of PA signals with a high Signal to Noise Ratio (SNR) can be generated using a high-energy laser pulses, but this requires complex and bulky pulsed laser system, which limits their application in manufacturing plants.
Moreover, the instinctive power of the continuous wave (CW) laser diode is limited, so it is extremely difficult to generate high SNR PA signal using the CWPA. Therefore, the method of the present disclosure utilizes CW laser diode enabled sweep frequency acoustic interferometry to generate the high SNR PA signal using a compact CW laser diode based PA system.
As shown in FIG.1, in one implementation a fundamental time variant wave equation for a Photo Acoustic pressure wave is given in Equation 1,
(?^2- 1/(c_s^2 ) ?^2/??t?^2 )P= (-ß)/C_p dQ/dt ---- Equation 1
Where, P is a PA pressure wave, Q is a laser enabled heating function, c_s is a speed of sound in the medium, ß is a thermal expansion coefficient, c_p is a specific heat at constant pressure for a given medium. Here, the intensity of each CW laser diode 106a, 106b…106n is sinusoidally modulated with the frequency sweep f. Following to the CW laser intensity modulation, the heating function modulates at the same frequency and is expressed in Equation 2,
Q= µ_a I_0 e^(-i?t) ---- Equation 2
In Equation 2, µ_a is an optical absorption coefficient of the sample, I_0 is a intensity of modulation, ? is a angular frequency given as ? = 2pf. Here, f is a frequency sweep from f1 Hz to f2 Hz. Considering the above depicted Non-Newtonian fluid paint sample is optically thin spherical absorber of radius a, and r is a radial coordinate, the PA wave in frequency domain can be expressed in Equation 3,
P=P (i.µ_a.ß.c_s.I_0.a)/( C_p (r/a)) [([sin (q)-q cos?(q) ]/q^2)/((1-?)?(sin???(q)/q)+i?c_s sin?(q)-cos?(q)? )] exp??(-iqt)? --- Equation 3
Where q= ?.a/c_s and ? is a density of the medium. Equation 3 signifies the generated PA pressure is the sinusoidal function of time with the same frequency as that of laser excitation. It is proportional to the intensity of the laser modulation and proportional to the optical absorption of the sample.
In the present experimental setup Non-Newtonian fluid sample paint were prepared for viscosity measurement. A total of five samples (50ml each) of the same paint having distinct colours placed in five different optically transparent containers. In addition, the viscosity of these paint samples S1, S2,S3,S4 and S5 are varied by adding a thinner solution to the paint in a definite proportion. Table 1 shows different proportions of thinners to the paint samples S1,S2,S3,S4 and S5 mixed to produce paints of different viscosities. The total volume of all paint samples is kept identical (50ml each).
Table 1 - Different proportion of thinner solution and paint
Sample Paint (ml) Thinner (ml) Total solution (ml)
S1 50 0 50
S2 47.5 2.5 50
S3 45 5 50
S4 42.5 7.5 50
S5 40 10 50

The paint and thinner are combined and mixed for a duration of about 2-3 minutes to ensure uniformity in each paint sample. Subsequently, the paint samples are utilized in the PA experimental setup to collect data, and the viscosity is measured with a Zahn-4 cup. Once the measurements of paint sample S1 is completed, subsequent paint samples are prepared and utilized for viscosity measurement. This process is repeated for all the paint samples, with the PA and Zahn-4 cup accordingly.
Ground truth measurement: To measure the viscosity of the paint samples (as shown in Table 1), this study utilizes the Zahn-4 cup. In the Zahn-4 cup, each paint sample is poured one by one. When pouring the paint sample the orifice of the Zahn-4 cup is blocked by using a human finger.
Once the Zahn-4 cup is fully filled the finger is removed, and the paint sample begin to fall into the optically transparent container 108. The time ‘t’ required for the paint sample to completely flow out of the Zahn-4 cup is used with the below equation to calculate the viscosity as shown in Equation 6,
?=14.8*(t-5) --- Equation 6
Where ? is the viscosity in c_st and t is time second. For measuring the viscosity in c_p (Centipoise), density of the paint sample is assumed to be 1200 Kg/m3. Thus, Equation 6 can be rewritten as represented in Equation 7,
?'= (?*density)/1000 ----- Equation 7
Where ?’ is the viscosity in c_p. After measuring the viscosity of one paint sample, the Zahn-4 cup is thoroughly cleaned and dried before pouring the other sample. Table 2 shows the viscosity value for samples S1 to S5. These viscosity values function as the ground truth for establishing a calibration curve with the PA measured viscosity feature.
Table 2 - Viscosity for sample S1 to S5 measured using Zahn-4 cup
Sample no. Viscosity (Cp)
S1 906
S2 515
S3 391
S4 284
S5 178

Immediately after the paint samples are prepared, each paint viscosity is measured using the Zahn cup (type-4) and also, the selected PA signal is obtained using the above steps to determine the PA attenuation. Graph is plotted between Viscosity measured using Zahn cup (on Y-axis) and PA attenuation on X-axis.
FIG.2 illustrates a viscosity measurement module 102 of the system 100 of FIG.1, in accordance with some embodiments of the present disclosure. In an embodiment, the viscosity measurement module 102 includes a processor(s) 204, communication interface device(s), alternatively referred as input/output (I/O) interface(s) 206, and one or more data storage devices or a memory 202 operatively coupled to the processor(s) 204. The viscosity measurement module 102 with one or more hardware processors 204 is configured to execute functions of one or more functional blocks of the viscosity measurement module 102.
Referring to the components of the viscosity measurement module 102, in an embodiment, the processor(s) 204, can be one or more hardware processors 204. In an embodiment, the one or more hardware processors 204 can be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the one or more hardware processors 204 are configured to fetch and execute computer-readable instructions stored in the memory 102. In an embodiment, the viscosity measurement module 102 can be implemented in a variety of computing systems including laptop computers, notebooks, hand-held devices such as mobile phones, workstations, mainframe computers, servers, and the like.
The I/O interface(s) 206 can include a variety of software and hardware interfaces, for example, a web interface, a graphical user interface to display the generated target images and the like and can facilitate multiple communications within a wide variety of networks N/W and protocol types, including wired networks, for example, LAN, cable, etc., and wireless networks, such as WLAN, cellular and the like. In an embodiment, the I/O interface (s) 106 can include one or more ports for connecting to a number of external devices or to another server or devices.
The memory 202 may include any computer-readable medium known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes.
Further, the memory 102 includes a database 208 that stores the plurality of PA signals, the PA signal with highest SNR, converted time domain PA signal, the first peak information, a second peak information and so on. Further, the memory 102 may comprise information pertaining to input(s)/output(s) of each step performed by the processor(s) 204 of the viscosity-temperature computation module 102 and methods of the present disclosure. In an embodiment, the database 208 may be external (not shown) to the viscosity measurement module 102 and coupled to the viscosity measurement module 102 via the I/O interface 206. Functions of the components of the system 100 and the viscosity measurement module 102 are explained in conjunction with flow diagram of FIG. 3 and experimental analysis depicted in FIG.4 and FIG.5 .
FIG.3A and FIG.3B illustrates a flow diagram illustrating a method 300 for measuring viscosity of Non-Newtonian fluids using the system of FIG. 1, in accordance with some embodiments of the present disclosure. In an embodiment, the system 100 comprises the viscosity measurement module 102, which comprises one or more data storage devices or the memory 202 operatively coupled to the processor(s) 204 and is configured to store instructions for execution of steps of the method 300 by the processor(s) or one or more hardware processors 204. The steps of the method 300 of the present disclosure will now be explained with reference to the components or blocks of the system 100 as depicted in FIG.1 and FIG.2 and the steps of flow diagram as depicted in FIG.3A and FIG.3B. Although process steps, method steps, techniques or the like may be described in a sequential order, such processes, methods, and techniques may be configured to work in alternate orders. In other words, any sequence or order of steps that may be described does not necessarily indicate a requirement that the steps to be performed in that order. The steps of processes described herein may be performed in any order practical. Further, some steps may be performed simultaneously.
Referring to the steps of the method 300, at step 302 of the method 300, the one or more hardware processors 204 trigger an excitation signal for generating a plurality of sweep frequency intensity modulated Continuous-Wave (CW) laser beam via a plurality of CW laser diodes placed in an excitation circuit incident on a Non-Newtonian fluid held in an optically transparent container.
At step 304 of the method 300, the one or more hardware processors 204 receive by an ultrasound sensor a plurality of Photo Acoustic (PA) signals generated within the Non-Newtonian fluids irradiated with each CW laser diode.
At step 306 of the method 300, the one or more hardware processors 204 process by a Vector Network Analyzer (VNA) the plurality of PA signals with reference to the excitation signal received from each CW laser diode to generate an in-phase (I) component and a quadrature phase (Q) component for each PA signal of each CW laser diode in a frequency domain.
At step 308 of the method 300, the one or more hardware processors 204 obtain a PA magnitude spectra in the frequency for each PA signal from each CW laser diode by applying a swept frequency acoustic interferometry principle.
At step 310 of the method 300 compute a signal to noise ratio (SNR) for each PA signal of corresponding CW laser diode.
At step 312 of the method 300, the one or more hardware processors 204 select a PA signal with highest SNR from among the plurality of PA signals of the plurality of CW laser diodes.
At step 314 of the method 300, the one or more hardware processors 204 apply an Inverse Fourier Transform over the PA magnitude spectra of the selected PA signal to obtain an equivalent time domain PA signal.
At step 316 of the method 300, the one or more hardware processors 204 identify a first peak and a second peak of the time domain PA signal using a time windowing.
At step 318 of the method 300, the one or more hardware processors 204 normalize the amplitude of the time domain PA signal with respect to the maximum amplitude of the same signal.
At step 320 of the method 300, the one or more hardware processors 204 calculate an PA attenuation in the Non-Newtonian fluids by obtaining a ratio of maximum amplitude of the first peak and the second peak.
At step 322 of the method 300, the one or more hardware processors 204 measure a viscosity ? of the Non-Newtonian fluids by plotting a calibration curve based on the PA attenuation and ground truth values.
FIG.4 depicts a time domain PA signal obtained by processing the PA signal using the system of FIG.1, in accordance with some embodiments of the present disclosure.To measure the viscosity of the sample Non-Newtonian fluid sample paint with the PA sensing technique first, the calibration is performed. For calibration, the time-domain PA signal is used to obtain the PA signal attenuation in the paint medium. FIG.4 shows the time-domain PA signals for only three samples S1, S2 and S3. The viscosity values measured via Zahn-4 cup are plotted with respect to the attenuation values to attain the calibration plot.
FIG.5 depicts a linearly fitted calibration curve plotted based on PA attenuation and ground truth values using the system of FIG.1, in accordance with some embodiments of the present disclosure. FIG.5 shows the linearly fitted calibration (regression) curve. Equation 8 is the calibration equation derived from FIG.4 and is used for further analysis which establishes relation between the viscosity and PA attenuation. The goodness of calibration fit curve is of about 95.28 % as obtained by its coefficient of determination. Linear fitting is applied to the data points on the graph and equation of straight line is obtained as shown in Equation 8,
V= |(a*m)-b| ------- Equation 8
Where, V is the viscosity of the paint sample, a and b are the slopes of the calibration curve and intercept respectively, and m is the PA attenuation. The values of a and b are 2296 c_p and 2790 c_p respectively. In Equation 8 modulus is taken to ensure the viscosity values are always positive. In general, the values of a and b can be determined from the calibration curve and m is determined using PA experiment and hence the viscosity V is calculated. Like S1-S3 in Table 1 three paint samples (S’1 through S’3) are prepared and the time domain PA signal is obtained. Subsequently, the viscosity is also assessed using the Zahn-4 cup. Table 3 shows the viscosity values measured through PA and the Zahn-4 cup and the error in the measurement is reported.
Table 3: Comparison of viscosity for S’1- S’3 using PA and Zahn-4 cup measurement
Sample No. Viscosity Measurement in Cp Error (%)
PA Zahn-4 cup
S’1 788 835 5.6
S’2 533 497 7.24
S’3 329 355 7.32

The error in Table 3 is calculated using the following Equation 9,

Error (%)= |((Measured value-True value))/(True value)|×100 ----- Equation 9

The error can further be reduced by rigorous experimentation to fit the calibration curve. However, the error less than 8% motivates to apply this compact PA sensing technique to different paint samples.
The written description describes the subject matter herein to enable any person skilled in the art to make and use the embodiments. The scope of the subject matter embodiments is defined by the claims and may include other modifications that occur to those skilled in the art. Such other modifications are intended to be within the scope of the claims if they have similar elements that do not differ from the literal language of the claims or if they include equivalent elements with insubstantial differences from the literal language of the claims.
It is to be understood that the scope of the protection is extended to such a program and in addition to a computer-readable means having a message therein; such computer-readable storage means contain program-code means for implementation of one or more steps of the method, when the program runs on a server or mobile device or any suitable programmable device. The hardware device can be any kind of device which can be programmed including e.g., any kind of computer like a server or a personal computer, or the like, or any combination thereof. The device may also include means which could be e.g., hardware means like e.g., an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination of hardware and software means, e.g., an ASIC and an FPGA, or at least one microprocessor and at least one memory with software processing components located therein. Thus, the means can include both hardware means and software means. The method embodiments described herein could be implemented in hardware and software. The device may also include software means. Alternatively, the embodiments may be implemented on different hardware devices, e.g., using a plurality of CPUs.
The embodiments herein can comprise hardware and software elements. The embodiments that are implemented in software include but are not limited to, firmware, resident software, microcode, etc. The functions performed by various components described herein may be implemented in other components or combinations of other components. For the purposes of this description, a computer-usable or computer readable medium can be any apparatus that can comprise, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
The illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope of the disclosed embodiments. Also, the words “comprising,” “having,” “containing,” and “including,” and other similar forms are intended to be equivalent in meaning and be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise.
Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., be non-transitory. Examples include random access memory (RAM), read-only memory (ROM), volatile memory, nonvolatile memory, hard drives, CD ROMs, DVDs, flash drives, disks, and any other known physical storage media.
It is intended that the disclosure and examples be considered as exemplary only, with a true scope of disclosed embodiments being indicated by the following claims.
, Claims:We Claim:
1. A processor implemented method (300) for measuring viscosity of Non-Newtonian fluids, comprising:
triggering (302), an excitation signal, via one or more hardware processor, for generating a plurality of sweep frequency intensity modulated Continuous-Wave (CW) laser beam via a plurality of CW laser diodes placed in an excitation circuit incident on a Non-Newtonian fluid held in an optically transparent container;
receiving (304), by an ultrasound sensor, via the one or more hardware processors, a plurality of Photo Acoustic (PA) signals generated within the Non-Newtonian fluid irradiated with each CW laser diode;
processing (306), by a Vector Network Analyzer (VNA) via the one or more hardware processors the plurality of PA signals with reference to the excitation signal received from each CW laser diode to generate an in-phase (I) component and a quadrature phase (Q) component for each PA signal of each CW laser diode in a frequency domain;
obtaining (308), a PA magnitude spectra in the frequency domain, via the one or more hardware processors, for each PA signal from each CW laser diode by applying a swept frequency acoustic interferometry principle;
computing (310), via the one or more hardware processors, a signal to noise ratio (SNR) for each PA signal of corresponding CW laser diode;
selecting, (312) via the one or more hardware processors, a PA signal with highest SNR from among the plurality of PA signals of the plurality of CW laser diodes;
applying (314), via the one or more hardware processors, an Inverse Fourier Transform over the PA magnitude spectra of the selected PA signal to obtain an equivalent time domain PA signal;
identifying (316), via the one or more hardware processors, a first peak and a second peak of the time domain PA signal using a time windowing;
normalizing (318), via the one or more hardware processors, the amplitude of the time domain PA signal with respect to the maximum amplitude of the same signal;
calculating (320), via the one or more hardware processors, an PA attenuation in the Non-Newtonian fluid by obtaining a ratio of maximum amplitude of the first peak and the second peak; and
measuring (322) via the one or more hardware processors a viscosity ? of the Non-Newtonian fluid by plotting a calibration curve based on the PA attenuation and ground truth values.

2. The processor implemented method as claimed in claim 1, wherein the viscosity ? is measured from the time domain PA signal which is processed through the PA magnitude spectra.

3. The processor implemented method as claimed in claim 1, wherein the viscosity ? is a function of the slope of the calibration curve and the PA attenuation.

4. The processor implemented method as claimed in claim 1, wherein each CW laser diode placed in an excitation circuit emitting light at different respective wavelengths.

5. The processor implemented method as claimed in claim 1, wherein the ground truth values are measured using a Zahn cup.

6. The processor implemented method as claimed in claim 1, wherein the ultrasound sensor is placed in contact with the optically transparent container having the Non-Newtonian fluids using an acoustic coupling gel.

7. A system (100) for measuring viscosity of Non-Newtonian fluids comprising:
Explain the set up here
the viscosity measurement module comrisisng
a memory (102) storing instructions;
one or more communication interfaces (106); and
one or more hardware processors (104) coupled to the memory (102) via the one or more communication interfaces (106), wherein the one or more hardware processors (104) are configured by the instructions to:
trigger an excitation signal for generating a plurality of sweep frequency intensity modulated Continuous-Wave (CW) laser beam via a plurality of CW laser diodes placed in an excitation circuit incident on a Non-Newtonian fluid held in an optically transparent container;
receive by an ultrasound sensor a plurality of Photo Acoustic (PA) signals generated within the Non-Newtonian fluids irradiated with each CW laser diode;
process by a Vector Network Analyzer (VNA) the plurality of PA signals with reference to the excitation signal received from each CW laser diode to generate an in-phase (I) component and a quadrature phase (Q) component for each PA signal of each CW laser diode in a frequency domain;
obtain a PA magnitude spectra in the frequency domain for each PA signal from each CW laser diode by applying a swept frequency acoustic interferometry principle;
compute a signal to noise ratio (SNR) for each PA signal of corresponding CW laser diode;
select a PA signal with highest SNR from among the plurality of PA signals of the plurality of CW laser diodes;
apply an Inverse Fourier Transform over the PA magnitude spectra of the selected PA signal to obtain an equivalent time domain PA signal;
identify a first peak and a second peak of the time domain PA signal using a time windowing;
normalize the amplitude of the time domain PA signal with respect to the maximum amplitude of the same signal;
calculate an PA attenuation in the Non-Newtonian fluids by obtaining a ratio of maximum amplitude of the first peak and the second peak; and
measure viscosity ? of the Non-Newtonian fluids by plotting a calibration curve based on the PA attenuation and ground truth values.

8. The system as claimed in claim 7, wherein the viscosity ? is measured from the time domain PA signal which is processed through the PA magnitude spectra.

9. The system as claimed in claim 7, wherein the viscosity ? is a function of the slope of the calibration curve and the PA attenuation.

10. The system as claimed in claim 7, wherein each CW laser diode is placed in an excitation circuit emitting light at different respective wavelengths.

11. The system as claimed in claim 7, wherein the ground truth values are measured using a Zahn cup.

12. The system as claimed in claim 7, wherein the ultrasound sensor is placed in contact with the optically transparent container having the Non-Newtonian fluids using an acoustic coupling gel.

Dated this 19th Day of July 2023
Tata Consultancy Services Limited
By their Agent & Attorney

(Adheesh Nargolkar)
of Khaitan & Co
Reg No IN-PA-1086