WO2008129561A2

WO2008129561A2 - Real-time system and method for designing structures

Info

Publication number: WO2008129561A2
Application number: PCT/IN2008/000243
Authority: WO
Inventors: Dhanushkodi D. Mariappan
Original assignee: Techpassion Technologies Pvt. Limited
Priority date: 2007-04-19
Filing date: 2008-04-15
Publication date: 2008-10-30
Also published as: WO2008129561A3

Abstract

This invention consists of a system and method for real-time designing and analysis of structures using the measured physical properties. The measured physical properties are mapped on to the geometry and the mapped data is correlated with the simulation results. This correlation is performed with algorithms that identify the differences between simulation and experimental measurement with precision and accuracy and map the differences onto the location on the geometry of the structure. This correlation is followed by automated modification of simulation model based on experimental results. This invention fills the existing gap between simulation and experimental testing and can lead to significant reduction in the number of iterations required in design and analysis and ensures that the simulation model is a true representation of the real world product thereby increasing the confidence in the simulation model. This can be extended to chemical property measurements.

Description

Description REAL-TIME SYSTEM AND METHOD FOR DESIGNING

STRUCTURES

Technical Field

[1] The present invention relates to methods and apparatus for designing structures.

This invention maps the simulation and experimental data of physical properties on geometry in real time to design structures.

[2] This invention can be used in automotive, aerospace, energy, healthcare, oil and gas, marine, offshore and infrastructure. This invention can be used to do new product design, maintenance on existing systems, diagnosis and for structural health monitoring and machinery condition monitoring.

Background Art

[3] In the industries like automotive, aerospace, energy, heavy equipment, marine, offshore and civil structures, there is a constant need for performing designs of new products. With the developments in simulation tools, virtual prototyping is used extensively to design new products. With the market needs changing rapidly, there is always a need to reduce the time to market. Similarly, when products are in service and diagnostics are to be performed, experimental methods are used a lot. But in such scenarios, simulation results if combined with experimentation will help the maintenance team fix the problem quickly reducing the downtime and providing greater productivity. Also, simulation models need validation based on experimentation. There is a need for a method and system that combines simulation and experimental results for use in design and analysis. There is a clearly identifiable gap in the tools that bridge simulation and physical testing and enable deterministic design. In the area of vibration, there has been some work performed in the area of algorithms for post processing experimental measurements and relating them to structures.

[4] In proceedings of IMAC 96 (1996) 204 , Balmes describes a CMS sub-structuring method whereby solutions for a complex system are obtained in a reduced sub-space corresponding to a reduction basis described by reduced DOFs. The difficulty is to choose the reduction basis such that for the qualities of interest similar results are obtained as far full models.

[5] European Patent No. EP1715435A1 describes the methods for performing a dynamic analysis of complex systems. The dynamic analysis of complex systems is performed by sub-structuring of the system. Performing such a dynamic analysis allows studying characteristics such as e.g. vibration and/or acoustical effects in a computationally efficient way.

[6] In Computers and Structures 79 (2001) 209 , Tran describes a method for reducing the number of interface co-ordinates in a component mode synthesis method. The method is based on the use of a truncated basis of interface modes instead of the constraint modes and is illustrated for both free and hybrid interface methods. The obtained basis thereby is determined based on a statically reduced system model.

[7] In the American Institute of Aeronautics and Astronautics Journal 39 (2001) 1182 ,

Castanier et al. describe a technique for reducing the size of a model generated by a Craig-Bampton method. The method is based on performing an eigen analysis on the constraint-mode partitions of the mass and stiffness matrices that correspond to the Craig-Bampton constraint modes. The method seems especially suited to predict power flow in complex structures.

[8] The above mentioned references are only algorithms and do not relate to physical testing and correlation. These works talk about dynamic analysis of complex systems and the algorithms to do the same. The prior art only indicates continuous improvements in the individual fields of simulation or experimentation. The field of simulation is vastly explored and improved to cater to the needs of multi-physics simulation requirements.

[9] Further, no attempt is observed to combine the advantages of simulation and experimentation by bringing the respective results and using them through an effective means of comparison, to validate the predictability of simulation. Hence, there is a need for a system in the design process that will bridge the gap between virtual simulation and experimental testing of prototypes. This invention provides a way of correlating experimental measurement on a physical prototype with that of the virtual prototype simulated using a computer algorithm.

[10] To give the example of the design and development of a generator, the design needs to take into consideration the electrical performance along with mechanical and thermal performance. This is a classical Multiphysics problem that can be solved more accurately and faster with this invention.

[11] However, there is a need for a method and a system that correlates the simulation results with experimentation and does an automatic modification of simulation models based on real-world experimentation. This method and system needs to be extendable to various physical and chemical properties.

[12] The existing products are concentrated in the fields of vibration and noise and there are no product platforms for solving multiphysics problems involving several physical properties - vibration, noise, strain, load, temperature, pressure, flow etc. Hence there is a need for a platform that combines simulation and experimental testing which can map experimental and simulation data simultaneously on a structure's virtual model. There is a need for a tool to provide correlation between simulation and experimental data which can provide automatic modification of simulation model using experimental data.

[13] Object of the invention

[14] It is an object of the present invention to provide a system and method for efficiently studying the performance of a structure under operational conditions. [15] Such system and method can be e.g. advantageously used for performing design and analysis of structures.

[16] It is another object of the present invention to provide a system and method for real-time comparison of simulation and experiments

[17] It is another object of the present invention to automatically modify the simulation model using the experimental results.

[18] It is another object of the present invention to provide a system and method for increased productivity in product testing.

[19] It is another object of the present invention to provide a system and method for efficient visualization of experiments.

[20] The invention further relates to a computer system and method for effective visualization of structures.

[21] The invention furthermore relates to a computer system and method for designing improvements in structures.

[22] It is another object of the invention to provide a unified platform for measuring different physical properties and chemical properties.

[23] The invention is used not just for designing mechanical or civil structures. The invention is used for designing various systems and subsystems - eg motors, generators, wind turbines that are used in different industries.

[24] The invention furthermore relates to a computer system and method for eliminating or controlling undesired functionalities of a structure

[25] The above objective is accomplished by a method according to the present invention. The invention relates to a method for performing real-time analysis and correlation of a system. For any of the embodiments of the present invention the system to be analysed can be a mechanical system involving stationary or moving parts, e.g. may be an automotive vehicle.

[26] Although there has been constant improvement, and evolution of measurement devices, techniques on one hand, and simulation algorithms on other hand, a common interface platform has been missing, where, the inputs from both forms of system identification can be brought together for comparison, correlation and validation. The present concepts are believed to represent new and novel improvements in this respect, resulting in more efficient, and quick process of design and development

[27] The teachings of the present invention permit the design of improved methods and systems for performing system identification of a complex system and improved methods and systems for optimising the physical properties of structures.

[28] Summary of the invention

[29] The current invention provides a method for performing real time designing of a structure. The method shall include the steps of creating the virtual model of the structure, and then receive the experimental inputs from the structure using sensors instrumented on the structure, and then, mapping the measured sensor data on the virtual model of the structure. This method also provides the visual mapping of the performance of the structure based on experimental results and receiving inputs and performance of the said structure from the simulation results. The method further does the correlation on the simulation with experimentation using the vectors representing physical properties. The invention further provides the automatic modification of the structure through an optimization method.

[30] The current invention further provides a method for correlating simulation and experimental data of a structure. A vector representing the physical property of the structure at all points is obtained based on experimental measurement. Then the vector representing the physical property based on simulation is obtained. The above mentioned vectors are compared using a mathematical operation. This mathematical operation is selected depending on the geometry, physical property being measured, derived property to be compared. A correlation coefficient is the output of the mathematical operation and this quantifies the extent of similarities and differences between simulation and experimentation

[31] The current invention further provides a method for effective product designing using the correlation coefficient for the simulation and experimentation data which helps in identifying the design variables of the structure under operating conditions. A n optimization function based on the correlation coefficient and the design variables is established. This provides the scope for maximizing or minimizing the optimization function by selection of a suitable algorithm. Then the values of the relevant design variables which increase the coefficient of correlation based on the maximization or minimization of the optimization function is obtained. This process helps in modifying the simulation model with the new values of design variables obtained from optimization. This process is repeated till the coefficient of correlation reaches the limits of acceptance. The details of optimization process and iteration values of the design variables are s tored and integrated into the test results and optimization results with the product life cycle management tools and systems.

[32] The current invention provides a computer implemented system for performing real time correlation analysis and product design. The system comprising of a

[33] structure, actuators for creating excitation in the structure, sensor for sensing various physical parameters, virtual model of the structure, and a controller means for controlling the excitation of the said structures using the said actuators.

[34]

Description of Drawings

[35] The present invention will now be described by way of example only and with reference to the accompanying drawings.

[36] FlG. 1 is the overall architecture of the invention.

[37] FIG. 2 shows the process flow diagram of the invention.

[38] FIG. 3 depicts the geometric representation of a turbine. [39] FIG.4 is the graphical representation of the measured data.

[40] FIG. 5 is graphical representation of the circle fit.

[41] FIG. 6 is a computer model of the automotive wheel rim.

[42] FIG. 7 is a test setup showing sensor mounting on the wheel rim.

[43] FIG. 8 shows the sensor response.

[44] FIG. 9 is the comparison of deflection shapes (simulation on left Vs test on right) for the wheel rim.

[45] FIG. 10 is the computer model of exhaust pipe model.

[46] FIG. 11 shows the sensor response.

[47] FIG. 12 is the comparison of deflection shapes for the pipe.

[48] FIG. 13 shows the shift in resonance frequency from 660 Hz to 1040 Hz.

Best Mode for Carrying Out the Invention

[49] Detailed Description of the invention

[50] The present invention will be described with respect to particular embodiments and with reference to certain drawings but the invention is not limited thereto but only by the claims. The drawings described are only schematic and are non-limiting. In the drawings, the size of some of the elements may be exaggerated and not drawn on scale for illustrative purposes. The dimensions and the relative dimensions do not correspond to actual reductions to practice of the invention.

[51] It is to be noticed that the term 'comprising', used in the claims, should not be interpreted as being restricted to the means/steps listed thereafter; it does not exclude other elements or steps. It is thus to be interpreted as specifying the presence of the stated features, integers, steps or components as referred to, but does not preclude the presence or addition of one or more other features, integers, steps or components, or groups thereof. Thus, the scope of the expression 'a device comprising means A and B' should not be limited to devices consisting only of components A and B. It means that with respect to the present invention, the only relevant components of the device are A and B.

[52] The invention will now be described by a detailed description of several embodiments of the invention. It is clear that other embodiments of the invention can be configured according to the knowledge of persons skilled in the art without departing from the true spirit or technical teaching of the invention, the invention being limited only by the terms of the appended claims.

[53] FIG. 1 depicts the overall architecture of the system and method of current invention. Structure 101 is connected with Actuator 105. These Actuators can be of but not limited to hammer or any device to create vibration or pressure or temperature or noise or any other form of excitation in the Structure 101. Structure 101 is connected with sensors 110. The structure can be of electromechanical or purely mechanical in nature. Sensors can be of different types and could be meant for sensing various parameters. The sensors are further connected to a computer 115 having the virtual model of the structure 101. The computer 115 can provide virtual model for any structure 101. The computer 115 is further connected to controller 120 which is further connected with actuator 105.

[54] FIG. 2 provides the process flow diagram of the invention. The current process starts with the designing of structures 125 with the help of the virtual model 130 created using the computer 115. Then the actual control output from computer to structure is provided 135. Sensor 110 provides inputs 140 from the structure 101 to the computer 115. After this, it is possible to visualize performance 145 of the structure 101 using the virtual model in computer 115. Once the performance is mapped, the comparison between the virtual model's experimental performances 150 with simulation results is available. Based on the results it is decided whether the good correlation between the data 155 is available, if there is a proper and acceptable correlation then it is decided that the structure 101 is of no physical abnormalities and no control action is required 160. If we there is no good correlation 155, then it is recommended for redesigning the structure 101. This process is performed till the optimal properties are achieved.

[55] The current invention provides a single system and method to perform all of the above. The various steps involved in the current invention shall include geometric modeling, data measurement, data processing, correlation and validation, visualization of physical property, and automatic modification of simulation model.

[56] One embodiment of the invention provides the geometric modelling of the structures which is the starting point of any test analysis experiment. The structure 101 system on which the test analysis is conducted is represented in a very simple yet functional form. This is enabled by empowering the user to pick points in a three dimensional grid or by loading a file containing the indices and the coordinates of the points or any other relevant file as depicted in FIG.3. These points may also be the points in which the measurements are made. In other words, sensors 110 will be mounted on these points during the experiment.

[57] The other embodiment of the invention provides, the data measurement. The data measurement as shown in FIG. 4 is achieved using a simple, plug and play hardware. This may consist of a minimum of four channels, but can be scaled to more channels if simultaneous acquisition form several channels are required. Any one of the above mentioned channel can be used for imparting the excitation to the p,hys.ipa^ structure by means and control from a computer. The other channels can be used to, read sensor signals (single or multi dimension) into the computer. The user pan change the settings such as physical property to be measured, static or dynamic measurements, range of frequencies, sensor sensitivities, and channel configuration, The data measurement process has been designed to achieve maximum productivity in testing without compromising on the accuracy of the acquired data.

[58] The other embodiment of the invention provides the data processing. The measured data is processed to obtain the ratio of system response with respect to the excitation. This ratio is further modified with the help of curve fitting algorithms. One of the curve fitting algorithms plots the measured data to obtain a best possible circle fit as depicted in FIG. 5. This curve fitting algorithm minimises the noise to signal ratio. One or more of the physical properties are directly measured or subsequently calculated from the measured data.

[59] The measured or the modified data may then be used to superimpose the relevant physical properties on the geometric model of the structure at the respective locations of measurement. This allows the visualisation of the physical property of the structure and relative behaviour of the physical properties at various locations on the structure. Further, more resolution can also be obtained by use of an interpolation method operating on the measured data for better comparison. The measured or processed physical properties may then be used for obtaining any relevant response behaviour of the structure such as deflection shapes, expansion, pressure, etc.

[60] The other embodiment of the invention provides the correlation and validation. The measured data and the modified data can be compared with the results of relevant simulation process. The results of the simulation process are read into the computer. The comparison of results is more direct and relevant if the simulation process is performed on the same geometry model as used in the experimentation process. The relevant physical properties that are read into the computer are superimposed on the geometry model. The superimposed simulation property data can now be compared with the property data that is directly measured or interpolated. The comparison is done using specific algorithms which result in deterministic numbers indicating the extent of closeness or deviation between the measured data and simulation data. Further, comparison of the data can result in correlation of individual structural physical properties or response behaviours. Comparison of the data can also be done on a collection of data sets which may yield a unique number or a collection of numbers that indicate the deviation of the simulation data from the measurement data

[61] The correlation numbers obtained above may be used to identify relevant areas of computer modelling which will affect the simulation behaviour. At these identified areas of computer modelling, additional inputs that may be obtained from measurement data can be fed hi to improve the computer model, which makes the simulation more accurate.

[62] A vector representing the physical property of the structure at all points is obtained based on experimental measurement. Similarly a vector representing the physical property based on simulation is obtained. These two vectors are compared using a mathematical operation. This mathematical operation is selected depending on the geometry, physical property being measured, derived property to be compared. The vector that is constructed completely represents the behaviour or performance of the entire structure and is designed to be independent of the points of inputs and mea- surement points.

[63] The other embodiment of the invention provides the visualization of the product performance under the operating conditions. The measured data and the simulated data can be superimposed on the geometry model inside the computer. The superimposed data can be used for visualization of their variation across the geometry model, by means of display of movements of various points of the models. Visualization can also be done by means of display of colour variations of the measured physical properties with respect to a predetermined scale. For example, the deflection mode of a given structure at a particular resonant frequency can be visualized as a deflection shape of the structure or as a colour variation at various points on the structure

[64] The physical property measured may also be visualized in the form of various types of graphs and charts which display variation of one of the physical properties measured and/ or response with respect to the variation of another physical property and/ or response. These graphs and charts can be 2 dimensional or 3 dimensional in nature. Further, visualization of the above mentioned graphs and charts can be enhanced by using various colours as an effective means of displaying the variation of physical properties or responses.

[65] The computer generated model of the physical structure is opened in the computer.

The sensor is mounted on a particular point on the structure. By using a computer mouse, the specific point where the sensor is mounted is selected. This selection process maps the physical property measured to the point on the computer model. This process is repeated for all the points where the measurement is done. The measurement points are selected based on the results obtained from the simulation model. Using a criterion which represents critical behaviour of the structure, such as failure mode, the measurement points are chosen and data is obtained and mapped.

[66] The measurement is done on a few points in the structure. But to compare the measurement with simulation, it is important to know the value of the physical property on a lot of points in the structure. Using an interpolation technique, the value at all the points of the structure are obtained by using the few measurement points.

[67] The other embodiment of the invention provides the automatic modification of simulation model. The comparison of the simulation vector and the experiment vector yields a coefficient of correlation which quantifies the differences between simulation and experimentation model. A convergence number is used and this is used as an objective function that is to be minimised or maximised in an optimization problem. The optimization problem is solved by varying different parameters of the simulation model such as geometry, boundary conditions and material properties. The best solution is the one for which the coefficient of correlation with experiment is the maximum. The solution which is a simulation model that is validated based on experimental results can be used as the final product design and this truly represents the performance of the structure under operating conditions. This algorithm for opti- mization is selected depending on the structure being designed and the physical property being measured. T he test results and optimization results are integrated with the product life cycle management tools and systems.

[68] Examples:

[69] 1. Shock response spectrum of oil tankers:

[70] Oil tanks that are used to transport oil in the ships are to be tested according to International Maritime codes. This testing is to simulate the shock loads that are applied to the oil tank when it engages with a locomotive. The challenge is to model the system to arrive at the right set of parameters (that are critical to quality of the product) to be monitored during the test. This 'Design of Experiments' approach reduces considerable time and cost involved in setting up field trials which could be time consuming and expensive otherwise. The virtual model of the oil container is created inside the computer. The oil container is instrumented with vibration measuring sensors at various points. This data is compared with simulation results. This reduced the time taken in testing and simulation and dramatically increases the productivity in product development and certification.

[71] 2. Validation of an Automotive wheel model

[72] A typical automotive wheel is subjected to a variety of random load conditions during the drive. Thus, it is important to design the wheel, so as to with stand the pertinent load cases. A final version of the designed wheel, however lacks the confidence of validation unless, a prototype is tested in a test run, which will involve a lot of test setup and run time. A time effective way of validating the design can be done by conducting a modal test on the prototype. The virtual model of the component is created in the computer and a modal test can be performed, to measure the various natural frequencies and the respective deflection shapes which can be used to validate the corresponding natural frequencies and the deflection shapes as obtained from simulation. Necessary modifications on the design of the component can then be added to match the test results with those of the simulation results.

[73] A commercially available automotive wheel rim is modelled in the computer as shown in FIG. 6 . This model is then used to perform finite element simulation for modal analysis. The results obtained are categorized as natural frequencies and mode shapes. The first natural frequency of the wheel rim model is noted and its respective deflection shape is recorded.

[74] An experiment is done on the above mentioned wheel rim to find out the actual natural frequencies at which it undergoes maximum vibration. The wheel 701 is supported in a free condition as depicted in FIG. 7, and then excited using a actuator. The subjective response is then recorded using a sensor 705, which is mounted on the specimen at a given location. The acceleration response 801 of the sensor is measured and stored. Acceleration responses of the sensor are also collected at various others points spanning over the specimen. The measured and analysed responses as shown in FIG. 8 are further used to obtain the deflection shape of the specimen at various frequencies. From the analysed responses, the first natural frequency of the specimen is then identified, and the respective deflection shape 901 is compared with the corresponding deflection shape obtained from the simulation 902 as provided in FIG. 9. It is noted that the first natural frequencies as measured from simulation and experimentation (316 Hz and 283 Hz respectively), are different which indicates the gaps of the computer modelling.

[75] The comparison of the simulation and test results indicate a scope of improvement with respect to certain design parameters of the specimen such as, material thickness, material properties, and damping coefficient.

[76] The above seen difference is eliminated by modification of the thickness and density used in the simulation model and the resultant natural frequencies of the modified model were in close conformity with those of experiment results.

[77] 3. Design validation of an exhaust system

[78] An automotive exhaust pipe is subjected to dynamically varying pitch, yaw and roll vibrations of the vehicle. These vibrations often deteriorate the strength of the exhaust pipe and results in either diminished life or unpredictable failures. This can be avoided by accurately modelling the exhaust pipe in the computer in the design phase, taking care of the details of the clamping methodology.

[79] An exhaust pipe is modelled in computer as shown in FIG. 10. A simulation is performed on the above said computer model is read into the computer. The simulation results thus read comprise of the first and second natural frequencies of the model and their corresponding deflection shapes.

[80] An experiment is performed on the exhaust pipe, with two different clamping methodologies. The first test is conducted by suspending the exhaust pipe by two flexible cords. The suspended exhaust pipe is then excited by an exciter. The vibration response is measured using a sensor, mounted on the exhaust pipe at a specific location. The acceleration responses (as depicted in FIG. 11) at various other locations on the exhaust pipe are also measured by exciting the exhaust pipe. The measured acceleration response are analysed and stored as acceleration data mapping to the respective locations. These analysed acceleration data is used to obtain the deflection shapes 1202, at the first and second natural frequencies, and is compared with the corresponding deflection shapes 1201 obtained from simulation. The comparison as shown in FIG. 12 provides the similarity of the deflection shapes occurring at different frequencies. This deviation is identified and relevant suggestions are inferred with respect to the following modelling specifications:

[81] 1) modelling of clamping methodologies

[82] 2) modelling of stiffness and damping coefficients at clamping locations

[83] 4. System characterization and performance enhancement of a milling machine [84] A milling machine used for machining operation is observed to make concerning noises at the operational rotation speeds. Such noises are potential indication of machine failure or deterioration. The identification of relevant system characteristic properties would greatly enhance the design process and improve the operation process.

[85] A simulation done on the computer model of the machine indicates a resonant frequency close to the operational speed of the machine. However, sufficient confidence is needed to make suitable design modifications on the machine architecture. Also, necessary inputs are required to come up with suitable design modifications.

[86] An experimental modal test is performed on the milling machine. A solid model of the machine is read into the computer, which then is used for locating the various measurement points on the machine. The machine is excited with an exciter, and the corresponding acceleration response is measured from the sensor kept at a specific location. Acceleration responses are also collected from other locations on the milling machine. The measured responses are analysed with respect to the given excitation. This analysed data is used to obtain the resonant frequency and the respective deflection shape of the milling machine. The measured resonant frequency 1301 (660Hz) is found to be close to the operation speeds, as also identified by simulation. The machine design was hence modified by inducing a preloading at a specific location of the machine, in order to arrest the large deflections of the part. This modification resulted in a significant shift of the resonant frequency 1302 of the machine from 660 Hz to 1040 Hz. (as depicted in FIG. 13) Thus, the resonant frequency of the machine is pushed out of the operational speed range, which helped in preventing any damage that may have otherwise occurred in the machine.

[87] 5. Boundary condition identification of a thin plate structure

[88] A thin plate structure is used as a generator cover. It was desired to model the cover of the generator in order to assess the vibration properties of the covering structure. The cover model is read in to the computer, and pertinent structural properties are imposed on the computer model to perform simulation. With reference to the above said modelling, certain vibration characteristics of the plate structure were noted, and registered. However, to have more confidence on the assessed vibration characteristics mentioned above, an experimental test was conducted. The plate structure was excited by a known excitation, and the vibration response is measured by the sensor at a specific location. The measured data was analysed to obtain the natural frequencies of the structure. It was observed that the first natural frequency of the plate was different from the predictions of the simulation. A modification of the boundary condition in the simulation model based on the experimental results ensured that the first natural frequency as predicted by the simulation closely matched with the measured frequency, during experimentation. The comparison of simulation results with experimental results before and after modification in the analysis model is given in Table 1.

[89]

[90] Table 1: Comparison of results before and after modification in boundary conditions (case 5) [91] This invention can be used in automotive, aerospace, energy, healthcare, oil and gas, marine, offshore and infrastructure. This invention can be used to do new product design, maintenance on existing systems, diagnosis and for structural health monitoring and machinery condition monitoring.

[92] It is to be understood that although preferred embodiments, specific constructions and configurations, as well as materials, have been discussed herein for devices according to the present invention, various changes or modifications in form and detail may be made without departing from me scope and spirit of this invention. While the invention has been shown and described with reference to preferred embodiments, it will be understood by those skilled in the art that various changes or modifications in form and detail may be made without departing from the scope and spirit of this invention.

[93] [94] This invention can be used in automotive, aerospace, energy, healthcare, oil and gas, marine, offshore and infrastructure. This invention can be used to do new product design, maintenance on existing systems, diagnosis and for structural health monitoring and machinery condition monitoring.

Claims

Claims[1] It is understood that the present invention is by no means limited to the particular steps herein disclosed and/or shown in the drawings, but also comprise modifications or equivalents within the scope of the claims. We claim,

1. A method for performing real time designing of a structure, the method comprising of:

- creating the virtual model of the said structure;

- receiving experimental results from the said structure using sensors instrumented on the said structure;

- mapping of the measured sensor data on the said virtual model of the said structure;

- visual mapping of the performance of the said structure based on experimental results;

- receiving inputs and performance of the said structure from the simulation results;

- correlating the said simulation and said experimental results using a vector representing physical properties; and

- automatic modification of the said structure through an optimization method.

2. A method according to claim 1, wherein the creation of the virtual model of the structure can be done comprising of:

- selecting specific nodes from an array or grid of points;

- connecting the selected nodes to form lines or faces; and

- creating the model based on the said nodes, lines or faces by means of reading one or more files.

3. A method according to claim 1, wherein sensor can be an electric, electronic, magnetic type sensor or resistance based sensors.

4. A method according to claim 1, wherein the visual mapping of the performance of the structure can be done comprising the steps of:

- reading the data measured and associating it to the point of measurement on the geometry model;

- visualizing a physical property using the said measured data at each of the said points of measurement on the geometry model by means of deflection, shape, color, texture or sound; and

- modifying the means for visualization of the geometry model based on the said measured data.

5. A method according to claim 1, wherein the simulation results can be of stress, strain, displacement, temperature, pressure, flow, velocity, acceleration, force, current, voltage, or any other related properties.

6. A method according to claim 1, wherein the process is performed till the optimal properties of the structure is achieved.

7. A method according to claim 1, wherein structure can be of any structure but not limited only to civil structures, automotive, aerospace, energy, heavy machineries, semiconductor, biomedical instruments, healthcare systems, marine, and offshore structures.

8. A computer program product for executing the method as claimed in any of claims 1 to 7.

9. A machine-readable data storage device storing the computer program product of claim 1 to 7.

10. Transmission of the computer program product of claim 8 over a local or wide area telecommunications network.

11. A method for correlating simulation and experimental results of a structure, the method comprise the steps of:

- obtaining a vector representing the physical property of the said structure at all points based on experimental measurement;

- obtaining a vector representing the physical property based on simulation;

- comparing the above mentioned vectors using a mathematical operation;

- depending on the geometry, physical property being measured, derived property to be compared; and

- calculation of a correlation coefficient from mathematical operation which quantifies the extent of similarities and differences between simulation and experimentation.

12. A method according to claim 11, wherein the simulation results can be of stress, strain, displacement, temperature, pressure, flow, velocity, acceleration, force, current, voltage and/or related properties.

13. A method according to claim 11, wherein structure can be of any structure but not limited only to civil structures, automotive, aerospace, energy, heavy machineries, semiconductor, biomedical instruments, healthcare systems, marine, and offshore structures.

14. A computer program product for executing the method as claimed in any of claims 11 to 13

15. A machine-readable data storage device storing the computer program product of claim 11 to 13

16. Transmission of the computer program product of claim 14 over a local or wide area telecommunications network.

17. A method for effective product designing, the method comprising the steps of:

- reading the correlation coefficient for the simulation and experimentation data;

- identifying the design variables of the structure under operating conditions; - establishing an optimization function based on the correlation coefficient and the design variables;

- maximizing or minimizing the optimization function by selection of a suitable algorithm;

- obtaining the values of the relevant design variables which increase the coefficient of correlation based on the maximization or minimization of the optimization function;

- modifying the simulation model with the new values of design variables obtained from optimization;

- repeating the above steps till the coefficient of correlation reaches the limits of acceptance;

- storing the details of optimization process and iteration values of the design variables; and

- integrating the test results and optimization results with the product life cycle management tools and systems.

18. A method according to claim 17, where in the design variables can be of geometry variables, operation properties, physical properties, performance properties, or control properties

19. A method according to claim 17, where in, the optimization function can be of shape optimization, material optimization, cost optimization, performance optimization, control optimization, process optimization or combinations there of.

20. A method of claim 17, wherein the experimentation and simulation data can be of stress, strain, displacement, temperature, pressure, flow, velocity, acceleration, force, current, voltage and/or related properties.

21. A method according to claim 17, wherein the process is performed till the optimal properties of the structure is achieved.

22. A method according to claim 17, wherein structure can be of any structure but not limited only to Civil structures, automotive, aerospace, energy, heavy machineries, semiconductor, biomedical instruments, healthcare systems, marine, and offshore structures.

23. A computer program product for executing the method as claimed in any of claims 17 to 22.

24. A machine-readable data storage device storing the computer program product of claim 17 to 22.

25. Transmission of the computer program product of claim 23 over a local or wide area telecommunications network.

26. A computer implemented system for performing real time correlation analysis and product design, the system comprising

- a structure;

- an actuator means for creating excitation in the structure; - a sensor means for sensing various physical parameters;

- a modelling means for providing virtual model of the said structure; and

- a controller means for controlling the excitation of the said structures using the said actuators.

27. A system according to claim 26, wherein the structure can be any structure but not limited only to civil structures, automotive, aerospace, energy, heavy machineries, semiconductor, biomedical instruments, healthcare systems, marine, and offshore structures.

28. A system according to claim 26, wherein actuators can be of electromagnetic, hydraulic or pneumatic type.

29. A system according to claim 26, wherein sensor can be an electric, electronic or magnetic type sensor, resistance based sensors.

30. A system according to claim 26, wherein the controller can be model based.