FIELD OF INVENTION

[0001] The present disclosure relates to combustion instability in a combustion chamber, and more specifically to a method and system for determining onset of combustion instability in a combustion system. The present application is based on, and claims priority from an Indian Application Number 202041015927 filed on 13 ^th April, 2020 the disclosure of which is hereby incorporated by reference herein.

BACKGROUND

[0002] Combustion or thermo-acoustic instability is a major concern in gas turbines initiated by mutual coupling of flame dynamics and acoustics of a combustion chamber in a combustion system. It poses a negative impact on the efficient performance and structural durability of combustors. Hence a lot of research has been undertaken to come up with different prediction methods especially to derive precursors for the combustion instability by observing the combustion dynamics.

[0003] Most of the conventional techniques rely on single sensor data, preferably pressure signals. But since the combustion instability is a consequence of the positive interaction between heat release and acoustics of the chamber, it is better to use data from sensors that monitor the above physical parameters to make more robust, accurate and fast predictions.

[0004] Thus, it is desired to address the above mentioned disadvantages or other shortcomings or at least provide a useful alternative.

OBJECT OF INVENTION

[0005] The principal object of the embodiments herein is to provide a method for determining onset of combustion instability in a combustion system. [0006] Another object of the embodiments herein is to obtain first time series data indicating heat release in the combustion system.

[0007] Another object of the embodiment herein is to obtain second time series data indicating acoustics of the combustion system.

[0008] Another object of the embodiments herein is to calculate entropy based on the first time series data and the second time series date.

[0009] Another object of the embodiment herein is to determine that the calculated entropy meets an instability criteria, and predicting the combustion instability based on the criteria.

SUMMARY

[0010] Accordingly, embodiments herein disclose a system and method for determining onset of combustion instability in a combustion system. The proposed invention is based on fiber optic sensors, namely fiber optic bundles and Fiber Bragg Gratings (FBG) to simultaneously sense chemiluminescence and pressure respectively which are a measure of heat release and acoustics of the combustors, thereby providing a robust mechanism for detecting the onset of combustion instability in combustion engines.

[0011] The present invention is based on a fast symbolic time-series analysis approach built upon a generalized D-Markov machine which models co-dependence among time series from both sensors to generate data-driven precursor called cross D-Markov entropy rate.

[0012] Entropy refers to the predictability of an outcome and more predictable the outcome is, lower will be the entropy. Combustion instability is characterized by self-sustained high amplitude periodic oscillations, which are less noisy or less random. Thus as soon as a decay in entropy rate is noted, the impending instability is predicted and appropriate control measures are initiated so that the instability is avoided.

[0013] Accordingly, the embodiments herein disclose a combustion system for predicting an onset of combustion instability in the combustor. The combustion system comprises a first fiber optic sensor for obtaining a first time series data indicating chemiluminescence in the combustion system and a second fiber optic sensor for obtaining a second time series data indicating the pressure in the combustion system. The combustion system further comprises a combustion instability prediction unit. The unit comprises a memory, a processor and the communicator. The processor is configured to determine an entropy based on the first time series data and the second time series data, determine that the entropy meets a instability criteria, wherein the instability criteria is derived based on a change in slope of the entropy with respect to flow conditions in the combustion system and predict the onset of combustion instability in response to determining that the entropy meets the instability criteria.

[0014] These and other aspects of the embodiments herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions, while indicating preferred embodiments and numerous specific details thereof, are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the embodiments herein without departing from the spirit thereof, and the embodiments herein include all such modifications.

BRIEF DESCRIPTION OF FIGURES

[0015] The method and system is illustrated in the accompanying drawings, throughout which; like reference letters indicate corresponding parts in the various figures. The embodiments herein will be better understood from the following description with reference to the drawings, in which:

[0016] Fig. 1 is a block diagram of a combustion system for determining onset of combustion instability inside a combustion system, according to an embodiment as disclosed herein; [0017] Fig. 2 is a block diagram of a combustion instability prediction unit for determining onset of combustion instability inside the combustion system according to the embodiments as disclosed herein;

[0018] Fig. 3 is a flow diagram illustrating the flow for determining onset of combustion instability inside the combustion system, according to an embodiment as disclosed herein;

[0019] Fig.4a is a graphical diagram, illustrating reflectivity of the FBG during annealing process as a function of time and temperature, according to an embodiment as disclosed herein; [0020] Fig. 4b is a graphical diagram, illustrating reflectivity of FBG during and after annealing at 700 degree Celsius, according to an embodiment as disclosed herein;

[0021] Fig. 5a is a schematic diagram, illustrating the placing of the first fiber optic sensor and the second fiber optic sensor in the combustion system, according to the embodiments as disclosed herein;

[0022] Fig. 5b is a schematic diagram, illustrating a second fiber optic sensor probe used in the combustor, according to the embodiments as disclosed herein;

[0023] Fig. 5c is a schematic diagram, illustrating the first fiber optic sensor probe housed inside the cooling chamber in the combustion system, according to the embodiments as disclosed herein;

[0024] Fig. 6 is a graphical diagram, illustrating entropy derived using the first time series data and the second time series data, according to an embodiment as disclosed herein.

DETAILED DESCRIPTION OF INVENTION

[0025] The embodiments herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. Also, the various embodiments described herein are not necessarily mutually exclusive, as some embodiments can be combined with one or more other embodiments to form new embodiments. The term “or” as used herein, refers to a non-exclusive or, unless otherwise indicated. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein can be practiced and to further enable those skilled in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.

[0026] As is traditional in the field, embodiments may be described and illustrated in terms of blocks which carry out a described function or functions. These blocks, which may be referred to herein as managers, units, modules, hardware components or the like, are physically implemented by analog and/or digital circuits such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hardwired circuits and the like, and may optionally be driven by firmware and software. The circuits may, for example, be embodied in one or more semiconductor chips, or on substrate supports such as printed circuit boards and the like. The circuits constituting a block may be implemented by dedicated hardware, or by a processor (e.g., one or more programmed microprocessors and associated circuitry), or by a combination of dedicated hardware to perform some functions of the block and a processor to perform other functions of the block. Each block of the embodiments may be physically separated into two or more interacting and discrete blocks without departing from the scope of the disclosure. Likewise, the blocks of the embodiments may be physically combined into more complex blocks without departing from the scope of the disclosure.

[0027] The accompanying drawings are used to help easily understand various technical features and it should be understood that the embodiments presented herein are not limited by the accompanying drawings. As such, the present disclosure should be construed to extend to any alterations, equivalents and substitutes in addition to those which are particularly set out in the accompanying drawings. Although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are generally only used to distinguish one element from another.

[0028] Accordingly, the embodiments herein disclose a method for determining onset of combustion instability in the combustion system. The proposed invention is based on fiber optic bundles and Fiber Bragg Gratings (FBG) to simultaneously sense chemiluminescence and pressure respectively which are a measure of heat release and acoustics of the combustors, thereby providing a robust mechanism for detecting the onset of combustion instability in combustion engines. Fiber optic sensors offer advantages like like immunity to electromagnetic interference (EMI), compact footprint which makes it superior to the other conventional sensors while implementing in a practical application. Specifically, the conventional chemiluminescence sensors require a bulky optical window in the combustion system, which makes it challenging to implement in real world applications. But the present invention described here uses a compact fiber optic probe which can be attached directly on to the combustion system and occupies much lesser footprint compared to conventional imaging apparatus.

[0029] The present invention is based on a fast symbolic time- series analysis approach built upon a generalized D-Markov machine which models co-dependence among time series from both sensors to generate data-driven precursor called cross D-Markov entropy rate. [0030] Entropy refers to the predictability of an outcome and more predictable the outcome is, lower will be the entropy. Combustion instability is characterized by self-sustained high amplitude periodic oscillations which are less noisy or less random hence associated with a lower entropy value. Thus as soon as a decay in entropy rate is noted, the impending instability can be predicted and appropriate control measures can be initiated so that the instability is avoided.

[0031] Referring now to the drawings, and more particularly to Fig. 1-Fig.6, where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments.

[0032] Fig.l is a block diagram of the combustion system 100, according to the embodiments as disclosed herein. In an embodiment, the combustion system 100 includes a first fiber optic sensor 110, a second fiber optic sensor 120, and a combustion instability prediction unit 130. The first fiber optic sensor 110 and the second fiber optic sensor 120 are mounted on to the combustion system 100.

[0033] In an embodiment, the first fiber optic sensor 110 is used to sense chemiluminescence which in turn indicates the heat release in the combustion system 100, thus the first fiber optic sensor 110 acts as a chemiluminescence sensor. Chemiluminescence is the electromagnetic radiation emitted from the de-excitation of electronically excited species formed by chemical reactions in the combustion system. CH*, OH*, and C2* are the most common contributors of chemiluminescence in typical hydrocarbon-air-flames. Chemiluminescence emission spectrum mainly falls in the visible-uv region. The first fiber optic sensor 110 comprises a fiber optic bundle consisting of multiple multimode optical fibers with excellent transmission in visible region, a numerical aperture up to 0.6 and a long lifetime which makes it suitable for this application.

[0034] In yet another embodiment, the first fiber optic sensor 110 is positioned in the combustion system 100 such that the first fiber optic sensor views different sections of the flame or the entire flame directly to monitor the chemilumine scence . [0035] In an embodiment, at least one fiber optic bundle is connected to a camera in the combustion system 100, wherein the camera captures images of the flame in the combustion system 100 to monitor the chemiluminescence.

[0036] The fiber optic bundle are packaged into a probe by mounting in a cooling chamber as shown in Fig. 5c. The cooling chamber consist of a quartz disc to isolate the high temperature from the probe without limiting the viewing angle of the fiber optic bundle. In addition to that options for water cooling is provided to keep a constant temperature on the fiber optic sensor throughout the combustion. This novel packaging enables use of the fiber optic bundle in a harsh and high temperature environment in the combustor.

[0037] In an embodiment the heat release data received from the first fiber optic sensor 110 is converted to the first time series data.

[0038] In another embodiment, the second fiber optic sensor 120 is used to sense pressure which in turn indicates the acoustics in the combustor, thus the second fiber optic sensor 120 acts as a pressure sensor. The second fiber optic sensor 120 uses Fiber Bragg Gratings (FBG) for determination of the pressure. FBG consist of periodic modulation of the refractive index in the core of the optical fiber. When broadband light is incident on them, they reflect a narrow band of wavelength around a center wavelength known as the Bragg wavelength. Strain and temperature variations can modify the refractive index and period of the grating resulting in a shift of the Bragg wavelength.

[0039] For the present invention, the development of the gratings should be such that they are able to withstand relatively high temperature (up to 1000 Deg Celsius), which is typical in combustion chambers. This can be achieved by using FBGs having good thermal stability at high temperatures. In the present invention, such a special type of FBG called annealed FBG is used because of its satisfactory performance at the required temperature range. In annealed FBGs, thermal stability is enhanced after heating it to high temperatures through intermediate temperature levels. Alternatively, other thermally stable FBG such as femtosecond laser-based gratings and regenerated gratings may also be used for this purpose.

[0040] Fig 4a exhibits reflectivity of the FBG, which is a measure of the strength of the grating as a function of time along with the temperature profile of the annealing process. It can be observed that the reflectivity of the grating is falling off at high temperature.

[0041] Fig 4b verifies the fact that the reflectivity of the grating is stable at even high temperature after annealing process. It plots reflectivity of the FBG with respect to temperature during annealing and two trials done after annealing.

[0042] In another embodiment, the combustion instability prediction unit 130 determines the entropy in the combustion system 100 based on the data from the first fiber optic sensor 110 and the second fiber optic sensor 120. After determining the entropy, the combustion instability prediction unit 1430 predicts the onset of instability using the determined cross-entropy value.

[0043] Although the Fig. 1 shows various components of the combustion system 100 but it is to be understood that other embodiments are not limited thereon. In other embodiments, the combustion system 100 may include less or more number of components. Further, the labels or names of the components are used only for illustrative purpose and does not limit the scope of the invention.

[0044] Fig.2 is a block diagram of the combustion instability prediction unit 130, according to an embodiment as disclosed herein. The combustion instability prediction unit 130 is responsible for predicting the onset of combustion instability in the combustion system 100. The combustion instability prediction unit 130 comprises a memory 132, a processor 134, and a communicator 136.

[0045] The processor 134 may be configured to execute instructions stored in the memory 132 and to perform various processes. The communicator 136 may be configured for communicating internally between internal hardware components and with external devices via one or more networks. [0046] The memory 132 may store instructions to be executed by the processors. The memory may include non-volatile storage elements. Examples of such non-volatile storage elements may include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of erasable programmable memories (EPROM) or electrically erasable and programmable read only memories (EEPROM). In addition, the memory may, in some examples, be considered a non- transitory storage medium. The term “non-transitory” may indicate that the storage medium is not embodied in a carrier wave or a propagated signal. However, the term “non-transitory” should not be interpreted that the memory is non-movable. In some examples, the memory can be configured to store larger amounts of information than the memory. In certain examples, a non-transitory storage medium may store data that can, over time, change (e.g., in Random Access Memory (RAM) or cache).

[0047] In an embodiment the combustion instability prediction unit 130 uses fast, data driven symbolic time series analysis approach based on a D-Markov machine for determining the onset of combustion instability.

[0048] In an embodiment the combustion instability prediction unit 130, receives first time series data and second time series data associated with heat and pressure of the combustion system 100 data from the first fiber optic sensor 110 and the second fiber optic sensor 120 respectively. The first time series data and the second time series data is then partitioned and converted into a first symbol of strings and a second symbol of string respectively. Each partition of the first symbol of strings and the second symbol of strings is assigned a symbol.

[0049] After assigning symbols, a finite set of states is generated from the symbol string using probabilistic finite state automata. The concept of probabilistic finite state automata is well known in the art. The transitions between the states corresponds to a symbol. The consecutive symbol depends on a previous symbol D, wherein D is a depth of the D-Markov machine.

[0050] The states are then split based on a criteria of minimization of entropy. Splitting the states increases the number of states and results in a better representation of the information from the first fiber optic sensor 110 and the second fiber optic sensor 120. State splitting also effectively reduces the entropy rate, thereby focusing in the important states with more information.

[0051] The states having similar statistical behavior form in the split states are then merged. Further the states merging reduces the number of states in the D- Markov machine. Thus a combination of state splitting and state merging leads to a final D-Markov machine. The D-Markov machine constructed from plurality of sensors is called xD-Markov machine. Further the entropy also termed as xD-Markov entropy is derived by calculating the probability functions which is well known in the art.

[0052] The xD-Markov entropy shows co-dependence of the first symbol string with the second symbol string. Hence in the present invention, the xD-Markov machine models the dependence of chemiluminescence data with pressure data.

[0053] After determination of the entropy, the combustion instability prediction unit 130 determines whether the entropy meets an instability criteria. The instability criteria is derived through the slope of the entropy with respect to flow conditions in the combustion system. The combustion instability prediction unit 130 determines that the determined entropy meets the instability criteria, and hence predicts the beginning of the combustion instability.

[0054] Thus the proposed method leads to a more robust and faster prediction of onset of combustion instability.

[0055] Although the Fig. 2 shows various components of the wireless system 130 but it is to be understood that other embodiments are not limited thereon. In other embodiments, the combustion instability prediction unit 130 may include less or more number of components. Further, the labels or names of the components are used only for illustrative purpose and does not limit the scope of the invention.

[0056] Fig. 3 is a flow diagram illustrating a flow 300 for determining onset of combustion instability in a combustor, according to an embodiment as disclosed herein. [0057] At 302 the method includes obtaining the first time series data from the first fiber optic sensor 110. The first time series data indicates the heat release in the combustion system 100. In an embodiment, the combustion instability prediction unit 130 receives the first time series data from the first fiber optic sensor 110 and the flow proceeds to 304.

[0058] At 304 the method includes obtaining the second time series data from the second fiber optic sensor 120. The second time series data indicates pressure in the combustion system 100. In an embodiment, the combustion instability prediction unit 130 receives the second time series data from the second fiber optic sensor 120 and the flow proceeds to 306.

[0059] At 306, the entropy is determines based on the first time series data and the second time series date. The entropy is also termed as xD-Markov entropy and is derived by calculating the probability functions which is well known in the art. In an embodiment, the combustion instability prediction unit 130 determines the entropy and the flow proceeds to 308.

[0060] In an embodiment, the first time series data and the second time series data are portioned and converted into a first symbol of strings and a second symbol of string respectively. Each partition of the first symbol of strings and the second symbol of strings is assigned a symbol. After assigning symbols, a finite set of states is generated from the symbol string using probabilistic finite state automata. The concept of probabilistic finite state automata is well known in the art. The transitions between the states corresponds to a symbol. The states are then split based on a criteria of minimization of entropy. The states having similar statistical behavior form the split states are then merged. Thus a combination of state splitting and state merging leads to a final D-Markov machine. Further, the entropy also termed as xD- Markov entropy is derived by calculating the probability functions which is well known in the art. The entropy may be calculated by other known method in the art.

[0061] At 308, the method includes determining that the calculated entropy meets the instability criteria. In an embodiment, the combustion instability prediction unit 130 determines that the entropy meets the instability criteria and the flow proceeds to 310. At 310, the method includes determining that the combustion instability in the combustion system 100 has begun. In an embodiment, the combustion instability prediction unit 130 determines the onset of the combustion instability.

[0062] The various actions, acts, blocks, steps, or the like in the method flow 300 may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some of the actions, acts, blocks, steps, or the like may be omitted, added, modified, skipped, or the like without departing from the scope of the invention.

[0063] Fig. 4a is a schematic diagram illustrating reflectivity of FBG during annealing process as a function of time. The present invention uses annealed FBG to withstand the high temperature inside the combustion system 100. As illustrated in fig.4a, in the present invention a conventional FBG is annealed at 700 degree Celsius in steps of 100 degrees Celsius with a settling time of 30 minutes with the aim of stabilizing the FBG reflectivity. The reflectivity of the FBG is observed to be unchanged even at 700 degree Celsius after the annealing procedure as shown in fig.4b.

[0064] Fig.4b indicates the reflectivity of FBG during and after annealing at 700 degrees Celsius. Thus as seen in fig.4a and fig. 4b, a viable pressure sensor is provided based on FBG for high temperature environments.

[0065] Fig. 5a is a schematic diagram, illustrating the experimental setup for the combustion system 100. The figure shows the placing of the fiber optic sensors 110 and 120 in the combustion system 100. The combustion system 100 is a swirl combustor and LPG is used as fuel for the results shown here. It should be noted that since the present invention is irrespective of the combustor and its geometry, it is applicable across different combustors. The sensor needs to be positioned suitably in each of the combustor based on its geometry and mechanism. The fiber optic bundle along with a photo detector is used as the first fiber optic sensor 110 for determining chemiluminescence (heat release) of the flame in the combustion system 100. Since the chemi-luminescene requires a line of sight measurement, the first fiber optic sensor 110 needs to be placed such that it can view the flame in the combustor. The FBG based sensor probe which is the second fiber optic sensor probe is inserted between two flanges of the combustor duct. The FBG based sensor probe is inserted far downstream in the combustor duct to keep the temperature as low as possible by taking advantage of the fact that the acoustics of the combustor can be monitored anywhere along the combustor. A compact spectrometer is used to record change in Bragg wavelength as a function of time. Thermo- acoustic instability is induced by changing air flow rate at constant fuel flow rate. Fig.5b and 5c shows the sensor probe of the second fiber optic sensor 120 and first fiber optic sensor 110 respectively.

[0066] Fig. 6 illustrates the entropy derived using the first fiber optic sensor 110 and the second fiber optic sensor 120. The entropy is plotted as a function of a parameter called equivalence ratio, which indicates the flow conditions of the combustion system 100. As seen in fig.6, the cross entropy value decays when the combustion system 100 approaches instability. Thus based on change in slope of entropy, the onset of combustion instability can be predicted.

[0067] In another possible embodiment the fiber optic bundle sensor may be modified to capture images which can be used in the various prediction techniques involving imaging of the flame.

[0068] In yet another embodiment, the proposed method is further used to initiate control measures for mitigation of the combustion instability.

[0069] In yet another embodiment, the proposed method is used for plurality of combustion system 100 to initiate a coupling between the plurality of combustion system 100 for mitigation of the combustion instability.

[0070] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.