阅读说明：本技术 一种风力机叶片损伤定位检测方法 (Method for positioning and detecting damage of wind turbine blade ) 是由 梅东升 孟超 毛永清 蔡来生 徐伟 石敏 温向炜 呼木吉乐图 谢正和 张博洋 梁 于 2021-05-27 设计创作，主要内容包括：本发明实施例提供了一种风力机叶片损伤定位检测方法,包括以下步骤：在风机叶片上设置多组呈三角形排布的传感器；通过多组所述传感器接收声音信号；通过所述声音信号和传感器的位置坐标,获得叶片损伤或缺陷的定位。能大大缩短发现叶片损伤位置所耗费的时间,快速完成定位并开展检测。能够通过叶片损伤位置产生的声音信号快速、有效的定位叶片损伤位置,对该位置进行检测,快速识别叶片内部损伤。(The embodiment of the invention provides a method for positioning and detecting damage of a wind turbine blade, which comprises the following steps: a plurality of groups of sensors which are arranged in a triangular shape are arranged on the fan blade; receiving sound signals through a plurality of groups of the sensors; and obtaining the location of the damage or defect of the blade through the sound signal and the position coordinates of the sensor. The time consumed for finding the damaged position of the blade can be greatly shortened, and the positioning and detection can be rapidly completed. Can damage the position through the quick, effectual location blade of the sound signal that the position produced, detect this position, the inside damage of quick discernment blade.)

1. A method for positioning and detecting damage of a wind turbine blade is characterized by comprising the following steps:

a plurality of groups of sensors which are arranged in a triangular shape are arranged on the fan blade;

receiving sound signals through a plurality of groups of the sensors;

and obtaining the location of the damage or defect of the blade through the sound signal and the position coordinates of the sensor.

2. The method for detecting damage location of a wind turbine blade as claimed in claim 1, further comprising: after the location of the blade damage or defect is obtained,

scanning a damaged or defective part of a blade to obtain a scanning result, wherein the scanning result comprises the size and the type of the damaged or defective part of the blade;

and comparing and classifying the sound signals and the scanning results to obtain a wind turbine blade damage sound classification and identification model database.

3. The method for positioning and detecting the damage of the wind turbine blade as claimed in claim 1, wherein a plurality of groups of sensors arranged in a triangular shape are arranged on the wind turbine blade, and specifically comprises the following steps;

the arrangement of the first set of sensors is: a first sensor is arranged in the center of a main beam cap area at the root of the fan blade and serves as the vertex of a first triangle, a second sensor is arranged in an area close to the tail edge of the fan blade in sequence along the spanwise direction or the length direction of the fan blade, and a third sensor is arranged in an area close to the front edge of the fan blade.

4. The method as claimed in claim 3, wherein the first sensor, the second sensor and the third sensor are arranged in an acute triangle.

5. The method as claimed in claim 3, wherein after the first sensor, the second sensor and the third sensor are arranged, a second group of sensors is arranged, and the second group of sensors is arranged as follows: the fourth sensor is arranged in the center of the area of the main beam cap of the fan and serves as a second triangle vertex, the fifth sensor and the sixth sensor are sequentially arranged, the second triangle and the first triangle are arranged at intervals, the fourth sensor is positioned outside the first triangle, the rest is done in the same way, n groups of sensors are arranged, n is larger than 2, and the vertex of each group of sensors is positioned outside the last triangle.

6. The method for positioning and detecting wind turbine blade damage according to claim 5, wherein a connecting line of the second sensor and the third sensor is perpendicular to the length direction of the wind turbine blade, and a linear distance between the first sensor and the fourth sensor is set to be 5m to 7 m.

7. The method for positioning and detecting damage to a wind turbine blade according to claim 3, wherein the positioning of the damage or defect to the blade is obtained by the sound signal and the position coordinates of the sensor, and specifically comprises:

the coordinates of the first sensor A, the second sensor B and the third sensor C are A (a) respectively₁,b₁)、B(a₂,b₂)、C(a₃,b₃) Unknown coordinates D (x, y) of the damage point can be obtained by the formula:

wherein: v is the propagation speed of sound, and the unit is meter/second; Δ t₁For the time difference of arrival of the sound signal at the first sensor and the second sensor, Δ t₂For the time difference between the arrival of the sound signal at the first sensor and the arrival of the sound signal at the third sensor, the unit: second;

Δ B is the distance difference between the sound emission source D and the sensor B and the sensor a, and has the unit: rice;

Δ C is the distance difference between the sound emission source D and the sensor C and the sensor a, and has the unit: rice;

coordinate system unit: and (4) rice.

8. The method for positioning and detecting wind turbine blade damage according to claim 3, wherein the second sensor is set to be 150mm to 300mm away from the edge of the trailing edge of the wind turbine blade.

9. The method for positioning and detecting wind turbine blade damage according to claim 3, wherein the third sensor is set to be 100mm to 200mm from the edge of the trailing edge of the wind turbine blade.

10. The method as claimed in claim 1, wherein each set of sensors are evenly spaced.

Technical Field

The invention relates to the technical field of wind power generation, in particular to a method for positioning and detecting damage of a wind turbine blade.

Background

The method for the nondestructive testing of the blade is widely applied at present, the damage position and size of the blade are found through an ultrasonic nondestructive testing method, the damage condition of the blade generated in the type testing process is required to be known, professional personnel are required to carry out all-around scanning from the blade root to the blade tip, the blade is required to be repeatedly scanned at different time points, a large amount of time is required to be consumed to complete the work, the efficiency is extremely low, and a method for quickly positioning the defect position and carrying out the blade detection is urgently needed.

The applicant has found that at least the following problems exist in the prior art: the damage of the wind turbine blade cannot be quickly and accurately positioned and detected, and the detection efficiency is low.

Disclosure of Invention

The technical problem solved by the embodiment of the invention is that the damage of the wind turbine blade cannot be quickly and accurately positioned and detected, and the detection efficiency is low.

In order to achieve the purpose, the invention provides a method for positioning and detecting damage of a wind turbine blade, which comprises the following steps:

a plurality of groups of sensors which are arranged in a triangular shape are arranged on the fan blade;

receiving sound signals through a plurality of groups of the sensors;

and obtaining the location of the damage or defect of the blade through the sound signal and the position coordinates of the sensor.

Specifically, the method further comprises: after the location of the blade damage or defect is obtained,

scanning a damaged or defective part of a blade to obtain a scanning result, wherein the scanning result comprises the size and the type of the damaged or defective part of the blade;

and comparing and classifying the sound signals and the scanning results to obtain a wind turbine blade damage sound classification and identification model database.

Specifically, the fan blade is provided with a plurality of groups of sensors which are arranged in a triangular shape, and the method specifically comprises the following steps of;

the arrangement of the first set of sensors is: a first sensor is arranged in the center of a main beam cap area at the root of the fan blade and serves as the vertex of a first triangle, a second sensor is arranged in an area close to the tail edge of the fan blade in sequence along the spanwise direction or the length direction of the fan blade, and a third sensor is arranged in an area close to the front edge of the fan blade.

Specifically, the first sensor, the second sensor and the third sensor are arranged in an acute triangle.

Specifically, after the first sensor, the second sensor and the third sensor are arranged, a second group of sensors is arranged, and the arrangement of the second group of sensors is as follows: the fourth sensor is arranged in the center of the area of the main beam cap of the fan and serves as a second triangle vertex, the fifth sensor and the sixth sensor are sequentially arranged, the second triangle and the first triangle are arranged at intervals, the fourth sensor is positioned outside the first triangle, the rest is done in the same way, n groups of sensors are arranged, n is larger than 2, and the vertex of each group of sensors is positioned outside the last triangle.

Specifically, a connecting line of the second sensor and the third sensor is perpendicular to the length direction of the fan blade, and the linear distance between the first sensor and the fourth sensor is set to be 5-7 m.

Specifically, the obtaining of the location of the blade damage or defect through the sound signal and the position coordinates of the sensor specifically includes:

the coordinates of the first sensor A, the second sensor B and the third sensor C are A (a) respectively₁,b₁)、B(a₂,b₂)、C(a₃,b₃) Unknown coordinates D (x, y) of the damage point can be obtained by the formula:

wherein: v is the propagation speed of sound, and the unit is meter/second; Δ t₁For the time difference of arrival of the sound signal at the first sensor and the second sensor, Δ t₂For the time difference between the arrival of the sound signal at the first sensor and the arrival of the sound signal at the third sensor, the unit: second;

Δ B is the distance difference between the sound emission source D and the sensor B and the sensor a, and has the unit: rice;

Δ C is the distance difference between the sound emission source D and the sensor C and the sensor a, and has the unit: rice;

coordinate system unit: and (4) rice.

Specifically, the distance between the second sensor and the edge of the tail edge of the fan blade is set to be 150-300 mm.

Specifically, the distance between the third sensor and the edge of the tail edge of the fan blade is 100-200 mm.

Specifically, each set of sensors is evenly spaced.

The technical scheme has the following beneficial effects: by the method for positioning and detecting the damage of the wind turbine blade, the damage can be positioned under the condition that the wind turbine operates, the time consumed for finding the damaged position of the blade can be greatly shortened when the wind turbine stops and the defect type is determined by using nondestructive testing equipment, and the positioning and the detection can be quickly completed. Can damage the position through the quick, effectual location blade of the sound signal that the position produced, detect this position, the inside damage of quick discernment blade corresponds sound signal and damage type and classifies types, through machine learning, can establish blade damage sound database, has improved detection efficiency. Meanwhile, the design of the blade can be optimized by technicians conveniently, and a basis is provided for the full life cycle management of the blade in the later period.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

FIG. 1 is a flow chart of a method for locating and detecting damage to a wind turbine blade according to an embodiment of the present invention;

FIG. 2 is a schematic structural diagram of a wind turbine blade with sensors according to an embodiment of the present invention;

FIG. 3 is a schematic diagram illustrating a set of coordinates of a first embodiment of a sensor and coordinates of an unknown damage point on a wind turbine blade according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of a second embodiment set of sensors and unknown damage point locations on a wind turbine blade according to an embodiment of the present invention.

The reference numbers illustrate:

1. a first sensor; 2. a second sensor; 3. a third sensor; 4. a fourth sensor; 5. a fifth sensor; 6. a sixth sensor; 10. a suction surface; 11. a root of a fan blade; 12. a spar cap region center; 21. and (4) damage points.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The invention provides a method for positioning and detecting damage of a wind turbine blade, which comprises the following steps of:

s11: a plurality of groups of sensors which are arranged in a triangular shape are arranged on the fan blade;

step S11 specifically includes;

the arrangement of the first set of sensors is: as shown in fig. 2, a first sensor 1 is arranged at the center 12 of a spar cap region at the root 11 of a fan blade as the vertex of a first triangle, and a second sensor 2 is arranged at a region close to the trailing edge of the fan blade and a third sensor 3 is arranged at a region close to the leading edge of the blade in sequence along the spanwise direction or the length direction of the fan blade.

Arranging the first sensor, the second sensor, and the third sensor in a triangle.

As shown in fig. 2, after arranging the first sensor 1, the second sensor 2, and the third sensor 3, a second group of sensors is arranged, the arrangement of the second group of sensors being: the fourth sensor 4 is arranged in the center 12 of the area of the main beam cap of the fan and serves as a vertex of a second triangle, a fifth sensor 5 and a sixth sensor 6 are sequentially arranged, the second triangle and the first triangle are arranged at intervals, the fourth sensor 4 is positioned outside the first triangle, the rest is done in the same way, n groups of sensors are arranged, n is larger than 2, and the vertex of each group of sensors is positioned outside the last triangle. No space for cross detection is generated to avoid wasting resources.

The applicant found that: the frequency of the normal position of the blade is generally lower than the frequency of the damage noise, when a sound signal with higher frequency is found, particularly when three sensors of a triangle all emit sound signals with higher frequency, the possibility of determining the position of the damage in the detection range of the triangle can be greatly increased. When the lesion position is located between the first triangle and the second triangle, the triangle formed by the three sensors closest to the sound source position is used, that is, when the lesion position (lesion point 21) is located between the first triangle and the second triangle, as shown in fig. 4, the triangle formed by the second sensor, the third sensor, and the fourth sensor is used to determine the lesion point position. At this time, the damage point 21 is surrounded by a triangle formed by the second sensor, the third sensor, and the fourth sensor. By analogy, most of the damage points can be surrounded by a triangle consisting of the three sensors that are closest.

When the damage point cannot be surrounded by a triangle formed by some three sensors, the position coordinates of the damage point are determined by the triangle formed by the three sensors closest to the sound source position.

S12: receiving sound signals through a plurality of groups of the sensors;

in the process of rotating the fan blade, begin to gather (receive) sound signal, adopt variable gain amplifier to carry out amplification processing to the sound signal that the damage position produced next, then carry out filtering process to the noise, through filtering, the noise can be filtered out, and the frequency of other sounds is all less than damage noise frequency generally, because the acoustic emission frequency of combined material self is generally less than 100HZ, so set up filtering threshold 100Hz, filter out the interference noise. Performing noise filtering on the amplified sound signal; and noise which possibly influences the analysis result is removed, and the accurate judgment of the damage position is facilitated.

S13: and obtaining the location of the damage or defect of the blade through the sound signal and the position coordinates of the sensor.

The device processes the incoming sound signal in combination with the position coordinates of the sensor, and can obtain accurate localization of a blade damage or defect sound source. Can damage the position through the quick, effectual location blade of the sound signal that the position produced, detect this position, the inside damage of quick discernment blade.

The method further comprises the following steps: after the blade damage or defect positioning is obtained, the fan blade is made to be static, and in the static state, the blade damage or defect part is scanned to obtain a scanning result, wherein the scanning result comprises the size and the type of the blade damage or defect part; the time consumed for finding the damaged position of the blade is greatly shortened, and the positioning and detection are rapidly completed.

And comparing and classifying the sound signals and the scanning results to obtain a wind turbine blade damage sound classification and identification model database. The centralized management of the data is convenient, the redundancy is controlled, and the utilization rate and the consistency of the data are improved.

That is to say: according to the damage sound source coordinates of the wind turbine blades, the positions of damage or defects of the blades (the wind turbine blades) can be found, phased array ultrasonic nondestructive testing equipment is adopted to scan sound source positions, the size and the type of the damage can be conveniently obtained, the detection results are compared with sound signals, the defect sound source signals are classified, machine learning is carried out on the sound signals and the corresponding damage types of the sound signals, and a model database for identifying the damage and the sound classification of the wind turbine blades is constructed.

The connecting line of the second sensor and the third sensor is vertical to the length direction of the fan blade, and the linear distance between the first sensor and the fourth sensor is set to be 5-7 m, for example: the linear distances between the first sensor and the fourth sensor are set to be 5m, 6m, 7m, 5.5m and 6.5 m. In order to distribute the sensors as evenly as possible over the blades, no overlap occurs. The detection range of the sound sensor is basically met.

The second sensor is arranged to be 150 mm-300 mm, such as 150mm, 200mm, 250mm, 300mm, away from the edge of the trailing edge of the fan blade. The space is used as much as possible near the trailing edge of the fan blade. Ensuring that all internal angles of a triangle formed by the three sensors are acute angles as much as possible

And the distance between the third sensor and the edge of the front edge of the fan blade is set to be 100-200 mm. The inner angles of the triangle formed by the three sensors are all acute angles.

Each set of sensors is evenly spaced.

The upper and lower two sides of fan blade set up a plurality ofly the sensor, every can all obtain the damage and detect, wherein, every 3 the sensor is a set of, and every group sensor is triangular distribution, every group sensor can evenly spaced.

The obtaining of the location of the blade damage or defect through the sound signal and the position coordinates of the sensor, as shown in fig. 3, specifically includes:

the coordinates of the first sensor A, the second sensor B and the third sensor C are A (a) respectively₁,b₁)、B(a₂,b₂)、C(a₃,b₃) Unknown coordinates D (x, y) of the damage point can be obtained by the formula:

wherein: v is the propagation speed of sound, and the unit is meter/second; Δ t₁For the time difference of arrival of the sound signal at the first sensor and the second sensor, Δ t₂For the time difference between the arrival of the sound signal at the first sensor and the arrival of the sound signal at the third sensor, the unit: second;

Δ B is the distance difference between the sound emission source D and the sensor B and the sensor a, and has the unit: rice;

Δ C is the distance difference between the sound emission source D and the sensor C and the sensor a, and has the unit: rice;

coordinate system unit: and (4) rice. The origin of coordinates is the center of the intersection line of the test bed and the blade root and the beam cap.

Taking a tangent circle of a blade root of a wind turbine blade as an X axis, taking a central line of a main beam of the blade as a Y axis, respectively establishing two planes, namely a suction surface plane and a pressure surface plane, and recording projection coordinates of a sensor on the suction surface 10 on the planes; the projected coordinates of the sensor on the pressure surface on the plane are recorded. Take the sensor on the suction side 10 as an example (the pressure side is the same as the pressure side, and the pressure side is the back side of the suction side): a first sensor, the second sensor and the third sensorThe coordinates of the sensors are respectively A (a)₁,b₁)、B(a₂,b₂)、C(a₃,b₃) The unknown coordinates D (x, y) of the damage point can be obtained by the following formula:

the sound source coordinates (x, y) can be determined and the lesion location known.

The time synchronization calibration of the sound sensor is needed before sound collection, so that the time difference delta t between the collected sound signal D in a formula and the first sensor and the second sensor can be conveniently obtained₁And the time difference delta t of the sound signal reaching the first sensor and the third sensor₂. The sound velocity (v) is measured by averaging multiple in-situ lead breaking methods.

By the method for positioning and detecting the damage of the wind turbine blade, the damage can be positioned under the condition that the wind turbine operates, the time consumed for finding the damaged position of the blade can be greatly shortened when the wind turbine stops and the defect type is determined by using nondestructive testing equipment, and the positioning and the detection can be quickly completed. Can damage the position through the quick, effectual location blade of the sound signal that the position produced, detect this position, the inside damage of quick discernment blade corresponds sound signal and damage type and classifies types, through machine learning, can establish blade damage sound database, has improved detection efficiency. Meanwhile, the design of the blade can be optimized by technicians conveniently, and a basis is provided for the full life cycle management of the blade in the later period.

The above technical solutions of the embodiments of the present invention are described in detail below with reference to specific application examples, and reference may be made to the foregoing related descriptions for technical details that are not described in the implementation process.

Example 1:

a method for positioning and detecting damage of a wind turbine blade can quickly position the position of the damage or defect by collecting and processing sound generated by the damage or defect in the moving process of the blade. The damaged part produces sound and is gathered by sound sensor among the blade motion process to obtain the location of damage position, then, use phased array ultrasonic testing equipment to scan the blade surface of positioning area when fan blade is static and detect, know the defect type and the damage condition of blade fast, compare with sound signal according to the testing result simultaneously, classify the sound source signal according to the defect type, establish defect sound database. Taking the suction side of the blade as an example, the pressure side method is the same. The sensors are arranged on the suction surface of the blade in a triangular mode, every three sensors are required to be in a group from the blade root to 90% of the total length of the blade, a first sensor is arranged at the center 12 of a main beam cap area of the blade and serves as a vertex of a triangle, a second sensor and a third sensor are sequentially arranged at the area close to the tail edge of the blade and the area close to the front edge of the blade along the spanwise direction of the blade, the distance between the second sensor and the tail edge is preferably 150 mm-300 mm, the distance between the third sensor and the front edge is preferably 100 mm-200 mm, and the inner angles of the triangle formed by the three sensors are all ensured to be as far as possible. The vertical distance between the first sensor and the connecting line of the second sensor and the third sensor is 2.5-3.5 meters, such as 2.5 meters, 3 meters and 3.5 meters. The sensor adopts a wireless noise sensor, and the model can adopt an M401 model.

And taking the intersection point of the connecting line of the second sensor and the third sensor and the central line of the main beam as a starting point, and arranging a fourth sensor on the central line of the main beam as the vertex of a second triangle at a position 3 meters along the spanwise direction of the blade. The second triangle and the first triangle are arranged at intervals, the fourth sensor is positioned outside the first triangle, and the like, n groups of sensors are arranged, n is more than 2, and the vertex of each group of sensors is positioned outside the last triangle.

Whether a sound signal sent by a sensor on a blade has a sound signal with higher frequency is detected firstly, if so, the sound signal is a signal of damage noise or a damage point, then the position of the damage or defect of the blade can be found according to the coordinate of a damage sound source of the blade, furthermore, phased array ultrasonic nondestructive testing equipment is adopted to scan the sound source part, the size and the type of the damage can be conveniently obtained, the detection result is compared with the sound signal, the defect sound source signal is classified, machine learning is carried out on the sound signal and the damage type corresponding to the sound signal, and a model database for wind turbine blade damage and sound classification and identification is constructed.

The implementation object of the invention is a certain 1.5MW wind driven generator blade, the length of the blade is 35-45 meters, for example 37 meters, and 7 groups of the blades are arranged in total, and the total number of the blades is 21. After the blade is fixed on the test bed, the following methods are adopted to position and detect the damage of the blade:

1. arrangement of the sound sensor:

the method comprises the steps of measuring and positioning the placement position of a sound sensor, adopting a tape measure for measurement, firstly determining a coordinate system and a coordinate plane before measurement, taking the center of an intersection line of a blade test bed and a blade root beam cap as a coordinate origin (0, 0) point, pasting a first sound sensor, measuring the direction along the spanwise direction of a blade by using the tape measure, and sequentially arranging a second sound sensor and a third sound sensor at the positions close to the tail edge area and the front edge area of the blade respectively, wherein the distance between the second sound sensor and the tail edge is 300mm, and the distance between the third sound sensor and the front edge is 200 mm. The distance between the first sound sensor and the third sound sensor is 3m measured by a scale. And measuring the projection coordinates of the second sound sensor and the third sound sensor on the coordinate plane by using an infrared distance meter, and recording. The arrangement of the other sensors and the coordinate measuring method are the same.

2. Positioning and collecting and analyzing a sound source:

and measuring the average value of the sound velocities of the first sound sensor and the second sound sensor, the first sound sensor and the third sound sensor, and the second sound sensor and the third sound sensor by adopting an in-situ lead breaking method for multiple times, wherein the sound velocities between different adjacent sensors at other positions are referred to the value. Time synchronization is carried out on all sensors, after fatigue or static test begins, sound signal collection begins, sound signals are amplified by a variable gain amplifier, noise signals below 100Hz are filtered, and the signals reach a first sound sensor in combination with a sound source DTime difference from the second sound sensor, Δ t₁For the time difference of arrival of the sound signal at the first sensor and the second sensor, Δ t₂For the time difference between the arrival of the sound signal at the first sensor and the arrival of the sound signal at the third sensor, the unit: second; the speed of sound (v) and the coordinates of each sensor, as shown in fig. 3, can locate the coordinate position of the sound source.

3. Detection of damage and sound database establishment:

according to the sound source coordinate position, the position of damage on the blade can be obtained, and the type and size of the damage or defect can be obtained by detecting the damaged area by using phased array ultrasonic testing equipment; comparing the detection result with the sound signal, and dividing the defect sound source signal into: and carrying out machine learning on the sound signals and the corresponding damage types thereof by four types of layering, cracking, folding and inclusion, and constructing a wind turbine blade damage-sound classification identification model database.

It should be understood that the specific order or hierarchy of steps in the processes disclosed is an example of exemplary approaches. Based upon design preferences, it is understood that the specific order or hierarchy of steps in the processes may be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in a sample order, and are not intended to be limited to the specific order or hierarchy presented.

In the foregoing detailed description, various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments of the subject matter require more features than are expressly recited in each claim. Rather, as the following claims reflect, invention lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate preferred embodiment of the invention.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. To those skilled in the art; various modifications to these embodiments will be readily apparent, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

What has been described above includes examples of one or more embodiments. It is, of course, not possible to describe every conceivable combination of components or methodologies for purposes of describing the aforementioned embodiments, but one of ordinary skill in the art may recognize that many further combinations and permutations of various embodiments are possible. Accordingly, the embodiments described herein are intended to embrace all such alterations, modifications and variations that fall within the scope of the appended claims. Furthermore, to the extent that the term "includes" is used in either the detailed description or the claims, such term is intended to be inclusive in a manner similar to the term "comprising" as "comprising" is interpreted when employed as a transitional word in a claim. Furthermore, any use of the term "or" in the specification of the claims is intended to mean a "non-exclusive or".

Those of skill in the art will further appreciate that the various illustrative logical blocks, units, and steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate the interchangeability of hardware and software, various illustrative components, elements, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design requirements of the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present embodiments.

The various illustrative logical blocks, or elements, described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be located in a user terminal. In the alternative, the processor and the storage medium may reside in different components in a user terminal.

In one or more exemplary designs, the functions described above in connection with the embodiments of the invention may be implemented in hardware, software, firmware, or any combination of the three. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media that facilitate transfer of a computer program from one place to another. Storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, such computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store program code in the form of instructions or data structures and which can be read by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Additionally, any connection is properly termed a computer-readable medium, and, thus, is included if the software is transmitted from a website, server, or other remote source via a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wirelessly, e.g., infrared, radio, and microwave. Such discs (disk) and disks (disc) include compact disks, laser disks, optical disks, DVDs, floppy disks and blu-ray disks where disks usually reproduce data magnetically, while disks usually reproduce data optically with lasers. Combinations of the above may also be included in the computer-readable medium.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.