DESC:FIELD
The present disclosure relates to the field of spectral analysis. More particularly, the present disclosure relates to a system and method for determining an operating parameter of a machine.
BACKGROUND
The background information herein below relates to the present disclosure but is not necessarily prior art.
It is always desirable to know whether a given machine, especially a rotating machine such as a motor or an IC engine, is performing well and up to its potential. The functioning of a rotating machine always depends on certain measureable parameters such as its RPM, load carrying capacity, and in certain cases health of an associated battery as a secondary power source. These parameters reflect the overall operating condition of the machine and therefore need to be checked on regularly.
Conventional machine health monitoring systems determine these operating parameter primarily by either individually measuring the RPM of the machine or by checking the health of a battery attached to the machine which is generally used to power an ancillary electrical system of the machine. For example, in an Internal Combustion (IC) engine based vehicle, a battery acts as a secondary source of power for an associated electrical system when the vehicle engine, which is the primary source of power, is not running. The engine, on the other hand, is used to charge the battery when the vehicle is running. The conventional health monitoring devices are therefore configured to measure the engine RPM and/or the battery health to determine the overall health of the vehicle.
For said purpose, conventional devices employ sophisticated sensors and processors to measure either the engine RPM or the battery condition. This makes the devices complex and costly.
There is therefore a need for a system for determining an operating parameter of a machine, which solves the problems as described herein above.
OBJECTS
Some of the objects of the present disclosure, which at least one embodiment herein satisfies, are as follows:
Some of the objects of the system of the present disclosure, which at least one embodiment herein satisfies, are as follows:
An object of the present disclosure is to provide a system that determines operating parameter of a machine in an easy and efficient manner.
Another object of the present disclosure is to provide a system that enables low cost chips which do not have sufficient ram or processing speed to perform intensive computation such as Fourier transform in real-time.
Yet another object of the present disclosure is to provide a system that facilitates a real-time health monitoring of a machine.
Other objects and advantages of the present disclosure will be more apparent from the following description, which is not intended to limit the scope of the present disclosure.
SUMMARY
The present disclosure envisages a system for determining an operating parameter of a machine, wherein the operating parameter is selected from the group consisting of engine RPM, engine speed, stroke length, mean piston speed, engine load, load carrying capacity, friction coefficients, motor speed, alternator speed and any other electrical signature on the alternator, such as switching on-off headlights, fuel injection, honking or use of any internal motors.

The system comprises a sensing unit, a signal conditioning unit, a first computation unit and a second computation unit.
The sensing unit is configured to sense at least one input parameter associated with the machine and generate a corresponding sensed signal. The input parameters include one of battery voltage or battery current. Further the input parameters can also include engine power, engine speed, motor speed, engine torque, and resistance of the stator winding.
The signal conditioning unit is configured to receive the sensed signal, and is further configured to condition the received sensed signal to generate a digital data stream.
In an embodiment, the signal conditioning unit comprises a sampling unit and an encoder. The sampling unit is configured to sample the received sensed signal at a pre-determined rate of frequency. The encoder is configured to cooperate with the sampling unit to receive the sampled signal, and is further configured to filter the received sampled signal to generate the digital data stream. In another embodiment, the signal conditioning unit is further configured to perform scaling and detrending operation on the received sampled signal to generate the digital data stream.
In an embodiment, the encoder is implemented using a combination of at least one band pass filter and at least one low pass filter.
The first computation unit comprises a memory and a processor. The memory is configured to store a pre-determined polynomial defining relationship between the operating parameter and at least one input parameter. The processor is configured to cooperate with the signal conditioning unit to receive the digital data stream, and is further configured to perform a computation operation on the received digital data stream to determine the operating parameter based on the polynomial. The computation operation includes at least one of Fourier Transform (FT), Fast Fourier Transform (FFT), Discrete Fourier transform (DFT), Inverse Discrete Fourier transform (IDFT) and any custom defined time series filter equation.
The second computation unit is located on a remote server communicatively coupled to the first computation unit. The second computation unit is configured to receive and analyse the sensed signal corresponding to the sensed input parameter and the determined operating parameter, and is further configured to update the polynomial stored in the memory based on the received sensed signal and the operating parameter. The second computation unit is further configured to use machine learning techniques to analyse the sensed signal corresponding to the sensed input parameter and the determined operating parameter.
The present disclosure also envisages method for determining an operating parameter of a machine.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWING
A system for determining an operating parameter of a machine and a method thereof, of the present disclosure will now be described with the help of the accompanying drawing, in which:
Figure 1 illustrates a block diagram of a system for determining an operating parameter of a machine; and
Figures 2a and 2b illustrate a flow diagram for a method determining an operating parameter of a machine.
LIST OF REFERENCE NUMERALS
100 system
102 sensing unit
104 signal conditioning unit
106 first computation unit
108 server
110 sampling unit
112 encoder
114 memory
116 processor
118 second computation unit

DETAILED DESCRIPTION
Embodiments, of the present disclosure, will now be described with reference to the accompanying drawing.
Embodiments are provided so as to thoroughly and fully convey the scope of the present disclosure to the person skilled in the art. Numerous details, are set forth, relating to specific components, and methods, to provide a complete understanding of embodiments of the present disclosure. It will be apparent to the person skilled in the art that the details provided in the embodiments should not be construed to limit the scope of the present disclosure. In some embodiments, well-known processes, well-known apparatus structures, and well-known techniques are not described in detail.
The terminology used, in the present disclosure, is only for the purpose of explaining a particular embodiment and such terminology shall not be considered to limit the scope of the present disclosure. As used in the present disclosure, the forms "a,” "an," and "the" may be intended to include the plural forms as well, unless the context clearly suggests otherwise. The terms "comprises," "comprising," “including,” and “having,” are open ended transitional phrases and therefore specify the presence of stated features, integers, steps, operations, elements, modules, units and/or components, but do not forbid the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. The particular order of steps disclosed in the method and process of the present disclosure is not to be construed as necessarily requiring their performance as described or illustrated. It is also to be understood that additional or alternative steps may be employed.
Typically, for determining operating parameters of a machine, intensive computational operations such as Fourier transform are required to be performed on various inputs. Conventional low cost microprocessors do not have sufficient RAM or processing speed to perform such intensive computational operations in real-time. To solve this problem, a system for determining an operating parameter of a machine and a method thereof of the present disclosure, is described with reference to Figure 1 through Figure 2b. The machine may be a rotating machine such as a motor or an alternator, a reciprocating machine such as a compressor, an engine or a pump, or a vibrating machine such as a vibratory feeder or an oscillating conveyor. The system facilitates analysis of a voltage or current signal of the machine at high frequency, thereby making it possible to extract information such as RPM of the machine or the load on the driving element. The system enables a low cost chip to perform computationally intensive operations in real-time by converting the input parameters into a stream of data that can be processed by a dedicated hardware block.
Referring to Figure 1, the system (hereinafter referred to as “system (100)”) for determining an operating parameter of a machine comprises a sensing unit (102), a signal conditioning unit (104), a first computation unit (106) and a second computation unit (118).
The sensing unit (102) is configured to sense at least one input parameter associated with the machine and generate a corresponding sensed signal.
The input parameters include at least one of battery voltage and battery current and can further include engine power, engine speed, motor speed, engine torque, resistance of the stator winding.
The signal conditioning unit (104) is configured to receive the sensed signal, and is further configured to condition the received sensed signal to generate a digital data stream.
In an embodiment, the signal conditioning unit (104) comprises a sampling unit (110) and an encoder (112). The sampling unit (110) is configured to sample the received sensed signal at a pre-determined rate of frequency. In an embodiment, the frequency rate of sampling is 44.1 KHz or any standard data rate used in audio file formats such as MP3 and AAC. The encoder (112) is configured to cooperate with the sampling unit (110) to receive the sampled signal, and is further configured to filter the received sampled signal to generate the digital data stream. In an embodiment, the encoder (112) may generate a compressed digital data in the form of a proxy audio file, such as a .MP3 file and store the compressed file in a repository.
In an embodiment, the encoder (112) is implemented using a combination of at least one band pass filter and at least one low pass filter.
In an embodiment, the signal conditioning unit (104) is further configured to perform scaling and detrending operation on the received sampled signal to generate the digital data stream. The signal conditioning unit (104) can also be employed to remove fluctuations caused by the electromagnetic effect of the machine from the received sampled signal. In an embodiment, the signal conditioning unit (104) can be configured to offer secure isolation and precise conversion of the received sampled signals.
The first computation unit (106) comprises a memory (114) and a processor (116). The memory (114) is configured to store a pre-determined polynomial defining relationship between the operating parameter and at least one input parameter. The processor (116) is configured to cooperate with the signal conditioning unit (104) to receive the digital data stream or a data stream associated with the store proxy audio file, and is further configured to perform a computation operation on the received digital data stream to determine the operating parameter based on the polynomial. The computation operation can include at least one of Fourier Transform (FT), Fast Fourier Transform (FFT), Discrete Fourier transform (DFT) and Inverse Discrete Fourier transform (IDFT).
In an embodiment, the processor (116) may be configured to analyze the harmonic content of the received digital data stream to determine the output. The processor (116) may be further configured to decompose the signal into its constituent frequencies to identify a frequency spectrum of the received proxy audio signal.
In an embodiment, the processor (116) may be configured to determine the value of the operating parameter based on, for example, a peak amplitude of the digital data signal. In an embodiment, to detect an RPM of the machine, the peak frequency in the range 400 to 4000 Hz may be used. In an embodiment, the digital data signal may be subjected to windowing to facilitate “smearing” or “smoothing” before analysis. In an embodiment, the various frequency ranges and corresponding rules for determining the value of the operating parameter may be stored in the memory (114).
The operating parameter to be determined can be selected from the group consisting of, but not limited to, engine RPM, engine speed, stroke length, mean piston speed, engine load, load carrying capacity, friction coefficients, motor speed and alternator speed. In an embodiment, the system (100) can be configured to determine multiple such parameters simultaneously.
Advantageously, the first computation unit (106) is implemented using a commercially available low cost chip, which typically has audio processing blocks or a DSP engine internally. Such a chip is capable of performing intensive computation operations such as Fourier Transform in real-time on high frequency (audio frequency range) digital signals. This eliminates the need of a sophisticated processor with high memory and processing abilities. Further, the cost of computation is also reduced.
Advantageously, the system (100) includes a display unit (not shown in figures) for displaying the value of the determined operating parameter to a user.
The second computation unit (118) is located on a remote server (108) communicatively coupled to the first computation unit (106). The second computation unit (118) is configured to receive and analyse the sensed signal corresponding to the sensed input parameter and the determined operating parameter, and is further configured to update the polynomial stored in the memory (114) based on the received sensed signal and the operating parameter. The second computation unit (118) is further configured to use machine learning techniques to analyse the sensed signal corresponding to the sensed input parameter and the determined operating parameter.
The second computation unit (118) may be implemented using one or more processor(s). The processors may be general-purpose processors, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), and/or the like. The processors may be configured to retrieve data from and/or write data to a memory/repository. The memory can be for example, a random access memory (RAM), a memory buffer, a hard drive, a database, an erasable programmable read only memory (EPROM), an electrically erasable programmable read only memory (EEPROM), a read only memory (ROM), a flash memory, a hard disk, a floppy disk, cloud storage, and/or so forth.
Figures 2a and 2b illustrate a flow diagram for a method determining an operating parameter of a machine. The method includes:
At Step 202: sensing, by a sensing unit (102), at least one input parameter associated with the machine;
At Step 204: generating, by the sensing unit (102), a sensed signal corresponding to the sensed input parameter;
At Step 206: receiving, by a signal conditioning unit (104), the sensed signal from the sensing unit (102);
At Step 208: conditioning, by the signal conditioning unit (104), the received sensed signal to generate a digital data stream;
At Step 210: storing, in a memory (114) of a first computation unit (106), a pre-determined polynomial defining relationship between the operating parameter and the at least one input parameter;
At Step 212: receiving, by a processor (116) of the first computation unit (106), the digital data stream from the signal conditioning unit (104);
At Step 214: performing, by the processor (116), a computation operation on the received digital data stream to determine the operating parameter based on the polynomial;
At Step 216: receiving and analysing, by a second computation unit (118) located on a remote server (108), the sensed signal corresponding to the sensed input parameter and the determined operating parameter; and
At Step 218: updating, by the second computation unit (118), the polynomial stored in the memory (114) based on the received sensed signal and operating parameter.
The step of conditioning (208), by the signal conditioning unit (104), the received sensed signal comprises the following sub-steps:
• sampling, by a sampling unit (110), the received sensed signal at a pre-determined rate of frequency;
• receiving, by an encoder (112), the sampled signal from the sampling unit (110); and
• filtering, by the encoder (112), the received sampled signal to generate the digital data stream.
In an embodiment, the system (100) may be configured to provide information about the battery SoH (State of Health), such as the number of charge/discharge cycles, the internal resistance, voltage, drained current, temperature, and the like.
The foregoing description of the embodiments has been provided for purposes of illustration and not intended to limit the scope of the present disclosure. Individual components of a particular embodiment are generally not limited to that particular embodiment, but, are interchangeable. Such variations are not to be regarded as a departure from the present disclosure, and all such modifications are considered to be within the scope of the present disclosure.
TECHNICAL ADVANCEMENTS
The present disclosure described herein above has several technical advantages including, but not limited to, the realization of a system for determining an operating parameter of a machine and a method thereof, which:
• determines operating parameter of a machine in an easy and efficient manner;
• enables a low cost chips which do not have sufficient ram or processing speed to perform intensive computation such as Fourier transform in real-time;
• provides a real-time health monitoring of a rotating machine;
• captures peripheral events associated with the rotating machines, which give some signature in time domain / frequency domain – like headlight flickering in a car or honking in a bike; and
• is cost effective.
The foregoing disclosure has been described with reference to the accompanying embodiments which do not limit the scope and ambit of the disclosure. The description provided is purely by way of example and illustration.
The embodiments herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
The foregoing description of the specific embodiments 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.
The use of the expression “at least” or “at least one” suggests the use of one or more elements or ingredients or quantities, as the use may be in the embodiment of the disclosure to achieve one or more of the desired objects or results.
Any discussion of documents, acts, materials, devices, articles or the like that has been included in this specification is solely for the purpose of providing a context for the disclosure. It is not to be taken as an admission that any or all of these matters form a part of the prior art base or were common general knowledge in the field relevant to the disclosure as it existed anywhere before the priority date of this application.
The numerical values mentioned for the various physical parameters, dimensions or quantities are only approximations and it is envisaged that the values higher/lower than the numerical values assigned to the parameters, dimensions or quantities fall within the scope of the disclosure, unless there is a statement in the specification specific to the contrary.
While considerable emphasis has been placed herein on the components and component parts of the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiment as well as other embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the disclosure and not as a limitation
,CLAIMS:WE CLAIM
1. A system (100) for determining an operating parameter of a machine, said system comprising:
• a sensing unit (102) configured to sense at least one input parameter associated with said machine and generate a corresponding sensed signal;
• a signal conditioning unit (104) configured to receive said sensed signal, and further configured to condition said received sensed signal to generate a digital data stream;
• a first computation unit (106) comprising:
i. a memory (114) configured to store a pre-determined polynomial defining relationship between said operating parameter and said at least one input parameter; and
ii. a processor (116) configured to cooperate with said signal conditioning unit (104) to receive said digital data stream, and further configured to perform a computation operation on said received digital data stream to determine said operating parameter based on said polynomial, and
• a second computation unit (118) located on a remote server (108) communicatively coupled to said first computation unit (106), said second computation unit (118) configured to receive and analyse the sensed signal corresponding to said sensed input parameter and said determined operating parameter, and further configured to update the polynomial stored in said memory (114) based on said received sensed signal and operating parameter.
2. The system (100) as claimed in claim 1, wherein said signal conditioning unit (104) comprises:
• a sampling unit (110) configured to sample said received sensed signal at a pre-determined rate of frequency; and
• an encoder (112) configured to cooperate with said sampling unit (110) to receive said sampled signal, and further configured to filter said received sampled signal to generate said digital data stream.
3. The system (100) as claimed in claim 2, wherein said encoder (112) is implemented using a combination of at least one band pass filter and at least one low pass filter.
4. The system (100) as claimed in claim 1, wherein said signal conditioning unit (104) is configured to perform scaling and detrending operation on said received sampled signal to generate said digital data stream.
5. The system (100) as claimed in claim 1, wherein said computation operation includes at least one of Fourier Transform (FT), Fast Fourier Transform (FFT), Discrete Fourier transform (DFT), and Inverse Discrete Fourier transform (IDFT).
6. The system (100) as claimed in claim 1, wherein said second computation unit (118) is configured to use machine learning techniques to analyse said sensed signal corresponding to said sensed input parameter and said determined operating parameter.
7. The system (100) as claimed in claim 1, wherein said operating parameter is selected from the group consisting of engine RPM, engine speed, stroke length, mean piston speed, engine load, load carrying capacity, friction coefficients, motor speed and alternator speed.
8. The system (100) as claimed in claim 1, wherein said input parameters include battery voltage, battery current, engine power, engine speed, motor speed, engine torque and resistance of the stator winding.
9. A method (200) for determining an operating parameter of a machine, said method comprising the following steps:
• sensing (202), by a sensing unit (102), at least one input parameter associated with said machine;
• generating (204), by said sensing unit (102), a sensed signal corresponding to said sensed input parameter;
• receiving (206), by a signal conditioning unit (104), said sensed signal from said sensing unit (102);
• conditioning (208), by said signal conditioning unit (104), said received sensed signal to generate a digital data stream;
• storing (210), in a memory (114) of a first computation unit (106), a pre-determined polynomial defining relationship between said operating parameter and said at least one input parameter;
• receiving (212), by a processor (116) of said first computation unit (106), said digital data stream from said signal conditioning unit (104);
• performing (214), by said processor (116), a computation operation on said received digital data stream to determine said operating parameter based on said polynomial;
• receiving and analysing (216), by a second computation unit (118) located on a remote server (108), the sensed signal corresponding to said sensed input parameter and said determined operating parameter; and
• updating (218), by said second computation unit (118), the polynomial stored in said memory (114) based on said received sensed signal and operating parameter.
10. The method as claimed in claim 9, wherein the step of conditioning, by said signal conditioning unit (104), said received sensed signal comprises the following sub-steps:
• sampling, by a sampling unit (110), said received sensed signal at a pre-determined rate of frequency;
• receiving, by an encoder (112), said sampled signal from said sampling unit (110); and
• filtering, by said encoder (112), said received sampled signal to generate said digital data stream.