CN116105614B - Method for detecting ice thickness based on optical fiber icing sensor, sensor and medium - Google Patents
Method for detecting ice thickness based on optical fiber icing sensor, sensor and medium Download PDFInfo
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- CN116105614B CN116105614B CN202310375099.2A CN202310375099A CN116105614B CN 116105614 B CN116105614 B CN 116105614B CN 202310375099 A CN202310375099 A CN 202310375099A CN 116105614 B CN116105614 B CN 116105614B
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- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
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Abstract
The utility model belongs to the technical field of aircraft icing detection, and particularly relates to a method, a sensor and a medium for detecting ice thickness based on an optical fiber icing sensor. The present application firstAcquiring the current ambient temperature T, and acquiring the received light intensity of a first receiving optical fiber of an optical fiber icing sensor of the optical fiber icing sensor
The second receiving optical fiber receives the light intensity
And discriminating the received light intensity of the optical fiber
The method comprises the steps of carrying out a first treatment on the surface of the Then the received light intensity of the optical fiber is judged
Inputting the current environmental temperature T into an ice type prediction model library to obtain an ice type, wherein the ice type comprises open ice, mixed ice and frost ice; then, inputting the ice type and the temperature value T into an ice type-temperature-fitting function library to obtain the corresponding ice type and temperature
Fitting a function; finally, the first receiving optical fiber receives the light intensity
And the second receiving optical fiber receives the light intensity
Carry-in
In the fitting function, the thickness h of the ice layer is calculated. The method introduces the environmental temperature as an important basis for judging the ice type and selecting the fitting function, and has the advantages of accurate ice type judgment and small error in calculating the ice thickness.
Description
Technical Field
The utility model belongs to the technical field of aircraft icing detection, and particularly relates to a method, a sensor and a medium for detecting ice thickness based on an optical fiber icing sensor.
Background
Icing of aircraft and wind turbines is a common natural phenomenon. Icing can influence flight safety, and aircraft icing leads to lift drop, resistance increase, pneumatic performance worsen, and the ice that drops strikes engine blade and can lead to the engine to stop. Wind turbines, which are often installed in cold areas and mountainous areas where wind resources are abundant, are frozen to reduce the operating efficiency, and these wind turbines may be frozen to different extents in cold climates. Icing can alter the aerodynamic properties of the wind turbine blades, resulting in a 50% reduction in power generation efficiency. Icing can also lead to mechanical failure of the wind power plant. Therefore, it is very important and necessary to detect ice on heavy equipment such as aircraft and wind turbines.
At present, icing detection is still a major scientific difficulty. Firstly, too many icing influencing factors are difficult to improve the measurement accuracy and range of the sensor, and the influencing factors comprise parameters such as icing environment temperature (T), air flow speed, ambient air pressure, liquid Water Content (LWC), droplet average volume diameter (MVD) and the like, so that the ice type is very complex under the combined action of a plurality of factors. There are typically three types of bright ice, frost ice and mixed ice. The measurement accuracy of the icing sensor is seriously affected by the great difference of different types of ice physical properties, such as density, dielectric constant, optical properties, adhesiveness and the like.
For example, the difference in the dielectric constant of ice causes the piezoelectric icing sensor to output different signals at the same ice thickness, and the difference in the ice density makes the resonance frequency detected when the icing sensor vibrates very different, which are all the reasons for affecting the measurement accuracy of the icing sensor. Secondly, the protruding structure of the overhanging type icing sensor arranged on the surface of the airplane or the surface of the wind turbine can cause the flow field of the airplane or the wind turbine to be influenced, and the aerodynamic characteristics of the airplane or the wind turbine can be influenced. Therefore, the icing sensor is usually installed on the aircraft nose and the hub of the wind turbine, and these parts are not real icing parts, and must be installed on the parts which are really easy to freeze so as to truly reflect the icing condition of the parts.
As an optical fiber icing sensor at the technological front, the optical fiber icing sensor has the advantages of small size and the like, can be installed at the tip of a wind turbine blade or a wing, can acquire accurate icing information through ice type identification, and brings hopes to the solution of icing detection.
Aris A Ikiades et al in 2007 proposed a method of measuring ice thickness and its type in real time using scattering and reflection of light by ice, aris A Ikiades et al developed an array fiber optic icing sensor in 2022 with a measurement accuracy of 0.5mm, but the array fiber optic icing sensor was oversized and flush mounted on a smaller curvature airfoil.
University of science and technology in 2011 detects the type and thickness of ice by using a transmitting fiber bundle with an end face inclined to the axis, patent CN202075225U and patent CN 112697055B are filed and published with papers Ge J, lin Y, zou j.a novel fiber-optic ice sensor capable of identifying ice type accurately [ J ]. Sensors & Actuators A Physical, 2012, 175 (none): 35-42. Because of the small size of the probe, the sensor can be flush mounted on the surface of the blade with the curvature of the wind turbine being changed, but the principle of distinguishing ice types by the sensor is that an air gap between an ice layer and the probe is utilized, and the air gap is usually formed between frost ice and a large-size probe. When the ice is frost ice, the emergent light can generate total reflection at the frost ice interface, and an air gap is not generally formed between the bright ice and the probe, so that total reflection can not occur. However, the trend of the probe toward miniaturization is gradually increasing, and the miniaturized probe cannot guarantee that an air gap is necessarily formed between frost ice and the probe. The ice-type recognition capability of the sensor may fail when there is no air gap between the frost ice and the probe.
The 2022 electronic technology university adds a discriminating optical fiber capable of discriminating ice type on the basis of the traditional two receiving optical fibers, and applies for an utility model patent CN114839163A, and the utility model well solves the technical problem that an optical fiber icing sensor cannot accurately identify ice type.
However, it should be appreciated that a good fiber optic icing sensor should not stop at an accurate determination of ice type. The thickness of the ice layer is also an important parameter affecting the flight and deicing of the aircraft, and an excellent optical fiber icing sensor should also be capable of accurately detecting the thickness of the ice layer.
For the application method of the utility model patent CN114839163A applied by the university of electronics technology in 2022, the related research is very little, and how to accurately judge the ice type and detect the thickness of the ice layer based on the optical fiber icing sensor is also a technical problem faced by the person skilled in the art.
Disclosure of Invention
In order to solve the technical problems that an optical fiber icing sensor in the prior art is inaccurate in ice type discrimination and cannot accurately detect the thickness of an ice layer, the utility model firstly provides a method for detecting the thickness of ice based on the optical fiber icing sensor, then provides an optical fiber icing sensor capable of realizing the method, and finally provides a storage medium for storing the method. The method comprises the following steps:
the application provides a method for detecting ice thickness based on an optical fiber icing sensor, wherein the optical fiber icing sensor is arranged on an object plane to be detected and comprises a transmitting optical fiber, a first receiving optical fiber, a second receiving optical fiber and a judging optical fiber, and one ends of the transmitting optical fiber, the first receiving optical fiber, the second receiving optical fiber and the judging optical fiber are clustered to form a detection end; at the detection end, the first receiving optical fiber, the second receiving optical fiber, the sending optical fiber and the judging optical fiber are sequentially arranged; the light receiving end face of the first receiving optical fiber and the light receiving end face of the second receiving optical fiber are perpendicular to the respective axes of the first receiving optical fiber and the second receiving optical fiber; the other end of the transmitting optical fiber is provided with a light-emitting element, and the other ends of the first receiving optical fiber, the second receiving optical fiber and the judging optical fiber are provided with photoelectric detection devices;
the method comprises the following steps:
s100, acquiring the current ambient temperature T, and acquiring the received light intensity of a first receiving optical fiber of the optical fiber icing sensor
The second receiving optical fiber receives the light intensity +.>
And discriminating the received light intensity of the optical fiber>
；
S200, judging the received light intensity of the optical fiber
And the current ambient temperature T is input into an ice type prediction modeIn the model library, an ice model is obtained, wherein the ice model comprises open ice, mixed ice and frost ice;
s300, inputting the ice type and the current environment temperature T into an ice type-temperature-fitting function library to obtain the corresponding ice type and temperature
Fitting function, wherein the light intensity modulation function +.>
，/>
Is the thickness of the ice layer;
s400, receiving the light intensity of the first receiving optical fiber
And the second receiving optical fiber receives the light intensity +.>
Carry-in
In the fitting function, the thickness h of the ice layer is calculated.
Further, in step S200, the ice type discrimination rule of the ice type prediction model library is:
under the condition that the ambient temperature is T, the received light intensity of the optical fiber is judged
When less than A mV, the crystal is open ice; discriminating the light intensity of the optical fiber>
When the value is more than B mV, the ice is frost ice, and the ice which does not meet the two conditions is mixed ice; a is the light intensity of the optical fiber received light which is judged according to the change of the ice thickness under the condition that the ambient temperature is T and the ice is frozen>
Is the maximum value of (2); b is that under the condition that the ambient temperature is T, the frost ice is frozen, and the light intensity of the optical fiber received light is judged according to the change of the ice thickness +.>
Is a minimum of (2).
Further, the establishment of the ice type prediction model library comprises the following steps:
s201, simulating each temperature in a laboratory simulation environment to freeze the ice, measuring and recording the thickness of the ice along with the ice at each temperature
Change discriminating optical fiber receiving light intensity +.>
A maximum value a of (a);
simulating the frost formation of each temperature in a laboratory simulation environment, measuring and recording the thickness of the frost-associated ice under each temperature
Change discriminating optical fiber receiving light intensity +.>
A minimum value B of (2);
the ice thickness of the bright ice
And frost ice thickness->
Is consistent with the variation range of (2);
s202, judging the light intensity received by the optical fiber when the open ice is frozen at each temperature
Obtaining ice, temperature and discriminating optical fiber received light intensity +.>
A list of maxima a;
when the frost and ice are frozen at each temperature, the light intensity received by the optical fiber is judged
Is the most significant of (3)A small value B to obtain frost ice, temperature and distinguish the light intensity of the optical fiber>
A list of minimum values B;
and S203, integrating the two lists in the step S202 to obtain an ice type prediction model library.
Further, in step S300, the establishment of the ice-type-temperature-fitting function library includes the following steps:
s301, simulating each temperature in a laboratory simulation environment to freeze open ice, and measuring and recording different ice thickness of the open ice
At the time, the first receiving fiber receives the light intensity +.>
And the second receiving optical fiber receives the light intensity +.>
Is a value of (2);
simulating each temperature in a laboratory simulation environment to freeze mixed ice, and measuring and recording different mixed ice thickness
At the time, the first receiving fiber receives the light intensity +.>
And the second receiving optical fiber receives the light intensity +.>
Is a value of (2);
simulating frozen frost ice at each temperature in a laboratory simulation environment, measuring and recording different frost ice thicknesses
At the time, the first receiving fiber receives the light intensity +.>
And the second receiving optical fiber receives the light intensity +.>
Is a value of (2);
s302, drawing a light intensity modulation function when frozen ice is frozen at each temperature according to the data recorded in S301
Iced with +.>
Curve of variation, light intensity modulation function->
；
When the frozen mixed ice at each temperature is drawn, the light intensity modulation function
Iced with +.>
Curve of variation, light intensity modulation function->
；
When the frozen frost ice at each temperature is drawn, the light intensity modulation function
Iced with +.>
Curve of variation, light intensity modulation function->
；
S303, performing function fitting on all curves in the step S302 to obtain fitting functions
And->
。
S304, recording each fitting function, and recording the temperature and the ice type corresponding to each fitting function to obtain an ice type-temperature-fitting function library.
Further, in step S303, when the open ice is frozen, a quadratic function is adopted to fit a curve; when freezing mixed ice or frost ice, a gaussian function is used to fit the curve.
Further, before step S100 is performed, it is determined whether the optical fiber icing sensor is iced, and if any one of the first receiving optical fiber, the second receiving optical fiber and the discriminating optical fiber receives the light sent by the sending optical fiber, the position of the optical fiber icing sensor is iced.
The application also provides an optical fiber icing sensor, which is used for executing the method for detecting the ice thickness based on the optical fiber icing sensor, and comprises a transmitting optical fiber, a first receiving optical fiber, a second receiving optical fiber and a judging optical fiber, wherein one ends of the transmitting optical fiber, the first receiving optical fiber, the second receiving optical fiber and the judging optical fiber are clustered to form a detection end; at the detection end, the first receiving optical fiber, the second receiving optical fiber, the sending optical fiber and the judging optical fiber are sequentially arranged; the light receiving end face of the first receiving optical fiber and the light receiving end face of the second receiving optical fiber are perpendicular to the respective axes of the first receiving optical fiber and the second receiving optical fiber; the other end of the transmitting optical fiber is provided with a light-emitting element, and the other ends of the first receiving optical fiber, the second receiving optical fiber and the judging optical fiber are provided with photoelectric detection devices;
the system also comprises a judging module and a calculating module;
the judging module performs steps S200 and S300, and the calculating module performs step S400.
Further, the device also comprises a temperature sensor arranged at the detection end and used for detecting the ambient temperature.
The application also provides a storage medium storing a computer program for executing the method for detecting ice thickness based on the optical fiber icing sensor.
The beneficial effects of the utility model are as follows:
the method for detecting the ice thickness is clear in level and mainly comprises three steps, namely determining ice type categories according to the current environment temperature and the judging optical fiber received light intensity, matching adaptive fitting functions according to the current environment temperature and the ice type categories, bringing the first receiving optical fiber received light intensity and the second receiving optical fiber received light intensity into the fitting functions, and calculating to obtain the ice layer thickness.
The distinguishing optical fiber and the two receiving optical fibers have complementary interference, and unlike the traditional scheme, the two receiving optical fibers do not serve as the effect of distinguishing the ice type any more, and the problems of ice type identification accuracy and ice thickness forecasting accuracy caused by the fact that signals for distinguishing the ice type and signals for forecasting the ice thickness come from the same optical path are avoided.
Importantly, the method creatively introduces the environmental temperature as an important basis for judging the ice type and selecting the fitting function, and has the advantages of accurate ice type judgment and small error in calculating the ice thickness.
Drawings
FIG. 1 is a flow chart of the method of the present application;
FIG. 2 is a schematic diagram of a fiber optic icing sensor configuration;
FIG. 3 is a schematic end view of the fiber optic icing sensor of FIG. 2;
FIG. 4 is a graph showing the intensity modulation function when frozen ice at-5℃
A curve varying with ice thickness h;
FIG. 5 is a graph showing the light intensity modulation function when the mixed ice is frozen at-20 ℃C
A curve varying with ice thickness h;
FIG. 6 is a graph showing the light intensity modulation function when frost ice is frozen at-40 DEG C
A curve varying with ice thickness h;
FIG. 7 is a graph showing the received light intensity of an optical fiber for discriminating frozen bright ice at-5℃and frozen mixed ice at-20℃and frozen frost ice at-40℃respectively
Curve as a function of ice thickness h.
Marked in the figure as: 1-transmitting optical fiber, 2-first receiving optical fiber, 3-second receiving optical fiber, 4-discriminating optical fiber and 5-temperature sensor.
Detailed Description
The following description of the specific embodiments of the present utility model will be given with reference to the accompanying drawings, so as to further understand the concept of the present utility model, the technical problems to be solved, the technical features constituting the technical solutions, and the technical effects to be brought about. However, the description of these embodiments is illustrative, and does not constitute a specific limitation on the present utility model.
In conventional approaches, fiber optic icing sensors typically have 3 bundles of optical fibers, one bundle being the transmitting fiber and the other two bundles being the receiving fibers, as shown for example in patent publication nos. CN202075225U and CN 112697055B.
The principle of distinguishing ice types according to the utility model of patent publication number CN202075225U can be summarized as: with the air gap between the ice layer and the probe, there is mostly an air gap between the frost ice and the large-sized probe. When the ice is frost ice, the emergent light can generate total reflection at the frost ice interface, and an air gap is not generally formed between the bright ice and the probe, so that total reflection can not occur. However, the trend of the light icing detection sensor probe towards miniaturization is gradually aggravated, and the miniaturized probe cannot guarantee that an air gap is necessarily formed between frost ice and the probe. The ice identification capability of the light icing sensor provided by this patent may fail when there is no air gap between the frost ice and the probe.
By the day of 2022 electronic technology university application, patent CN114839163a, all optical fiber icing sensors disclosed and reported are almost the same as CN202075225U, and the icing type is judged by increasing the difference of the light intensity modulation function curves of different types of ice received by the receiving optical fiber as much as possible, so that the influence of the ambient temperature on ice type judgment and ice thickness prediction is ignored. Meanwhile, the signals for judging the ice type and the signals for forecasting the ice thickness come from the same optical path, so that the ice type identification accuracy and the ice thickness forecasting accuracy cannot be met at the same time, and meanwhile, the difficulty of structural design is increased.
The university of electronics technology in 2022 originally added a discriminating optical fiber capable of discriminating ice type based on two conventional receiving optical fibers, and the ice type was identified by the discriminating optical fiber, and patent CN114839163a was filed. The utility model well solves the technical problems that the ice type identification accuracy and the ice thickness forecasting accuracy cannot be met simultaneously and the difficulty of structural design is increased at the same time because the ice type distinguishing signal and the ice thickness forecasting signal come from the same optical path. However, the use of the fiber optic icing sensor has been rarely studied in the prior art.
The application innovatively provides a method for detecting ice thickness based on an optical fiber icing sensor.
In order to facilitate understanding of the design concept of the present application, the design concept is first introduced as follows:
the method for detecting the ice thickness comprises the following steps of firstly, judging the light intensity received by an optical fiber through the current ambient temperature T
To determine the ice type, the application takes the ambient temperature into account at the step of determining the ice type, and the application considers that the received light intensity is just +.>
The accuracy of judging the ice type is not high because freezing different types of ice at different temperatures discriminates the light intensity of the optical fiber reception +.>
There may be cases where the values are the same, resulting in erroneous judgment. The application introduces the environment temperature to assist in judging the ice type, so that the misjudgment condition can be avoided, and the accuracy of ice type judgment is improved.
Secondly, the ice layer thickness is solved by combining the environment temperature to match an adaptive fitting function on the basis of judging the ice type. It should be understood that even if the same ice type is frozen, the change condition of the ice thickness is different under different environmental temperatures, and the fitting of the same ice type under different temperatures by the same fitting function is inaccurate.
And finally, after the adaptive fitting function is determined, the thickness of the ice layer can be solved by bringing the received light intensity values of the first receiving optical fiber and the second receiving optical fiber.
In summary, the method and the device for determining the ice type accurately determine the ice type according to the ambient temperature, accurately select the fitting function according to the ambient temperature again on the basis of accurately determining the ice type, and finally solve the thickness of the ice layer.
The method comprises the following steps:
the structure of the optical fiber icing sensor is shown in fig. 2, and the optical fiber icing sensor comprises a transmitting optical fiber 1, a first receiving optical fiber 2, a second receiving optical fiber 3 and a discriminating optical fiber 4, wherein one ends of the transmitting optical fiber 1, the first receiving optical fiber 2, the second receiving optical fiber 3 and the discriminating optical fiber 4 are clustered to form a detection end; at the detection end, a first receiving optical fiber 2, a second receiving optical fiber 3, a transmitting optical fiber 1 and a discriminating optical fiber 4 are arranged in sequence; the light-facing end surfaces of the discriminating optical fibers 4 are inclined with the axes of the discriminating optical fibers, and the light-facing end surfaces of the first receiving optical fibers 2 and the second receiving optical fibers 3 are perpendicular to the respective axes; the other end of the transmitting optical fiber 1 is provided with a light-emitting element, and the other ends of the first receiving optical fiber 2, the second receiving optical fiber 3 and the distinguishing optical fiber 4 are provided with photoelectric detection devices.
The discriminating fiber 4 is also a bundle of receiving fibers, and functions to determine the type of icing. It will be appreciated by those skilled in the art that a glass housing is also typically provided around the periphery of the probe end for holding the optical fibers and transmitting light, as shown in fig. 2. The outermost layer of the discriminating fiber 4 is typically coated to prevent ambient light from entering the inside of the discriminating fiber 4, thereby affecting the ice interface and the intensity of light reflected and scattered back into the discriminating fiber. The first receiving optical fiber 2 and the second receiving optical fiber 3 are different in distance from the transmitting optical fiber 1 and different in position, so that the first receiving optical fiber 2 and the second receiving optical fiber 3 receive different light intensities. In order to ensure that the optical fiber icing sensor can be flush-mounted on an aircraft airfoil with a small radius of curvature, the optical fiber icing sensor probe structure is generally not more than 6mm.
It should be understood by those skilled in the art that ice types are generally classified into open ice, frost ice and mixed ice. The application is used for detecting the three ice types and detecting the icing thickness of the three ice types.
Specifically, the method provided by the application comprises the following steps:
firstly, S100, the current ambient temperature T is obtained, and the received light intensity of a first receiving optical fiber of the optical fiber icing sensor is obtained
The second receiving optical fiber receives the light intensity +.>
And discriminating the received light intensity of the optical fiber>
。
Then S200, the received light intensity of the optical fiber is judged
And inputting the current environmental temperature T into an ice type prediction model library to obtain an ice type, wherein the ice type comprises open ice, mixed ice and frost ice. The application is provided with the optical fiber receiving light intensity discriminating part for storing the ambient temperature>
And an ice type prediction model library for ice type matching, when +.>
And T can be matched with ice type.
Next, S300, after the ice type is obtained, inputting the ice type and the current environment temperature T into an ice type-temperature-fitting function library to obtain the corresponding ice type and temperature
Fitting function, wherein the light intensity modulation function +.>
，/>
Is ice thick.
Finally, S400, the first receiving fiber receives the light intensity
And the second receiving optical fiber receives the light intensity +.>
Is brought into
And in the fitting function, the thickness h of the ice layer can be calculated.
Different from the existing methods for judging the ice type and measuring the ice thickness by independently using the values of the two receiving optical fibers, in the application, not only the light intensity values received by the two receiving optical fibers and the light intensity values received by the optical fibers are considered, but also the ambient temperature is considered, the ice type is finally judged through the ambient temperature and the light intensity received by the judging optical fibers, and the ice thickness is solved through a fitting function suitable for the selection and judgment of the ice type and the ambient temperature.
In step S200, the ice type discrimination rule of the ice type prediction model library is: under the condition that the ambient temperature is T, the received light intensity of the optical fiber is judged
When less than A mV, the crystal is open ice; discriminating the light intensity of the optical fiber>
When B mV is greater than B mV, the ice is frost, and when the above two conditions are not satisfied, the ice is mixed. A is the light intensity of the optical fiber received light which is judged according to the change of the ice thickness under the condition that the ambient temperature of frozen open ice is T>
Is the maximum value of (2); b is that under the condition that the ambient temperature of frozen frost ice is T, the received light intensity of the optical fiber is judged according to the change of the ice thickness
Is a minimum of (2).
For ease of understanding, the following rules are provided in the ice prediction model library:
when the ambient temperature is-10 ℃, if the received light intensity of the optical fiber is judged
When the value of (2 mV) is smaller than 2mV, it is the ice, when the received light intensity of the optical fiber is judged +.>
If the value of (2) is greater than 5mV, the ice is frost ice, and if both the two requirements are not met, the ice is mixed ice.
When the ambient temperature is-20 ℃, if the received light intensity of the optical fiber is judged
If the value of (2) is less than 2.1mV, it is the bright ice to determine the light intensity of the optical fiber>
If the value of (2) is greater than 5.1mV, the ice is frost ice, and if both the two requirements are not met, the ice is mixed ice.
When the ambient temperature is-25 ℃, if the received light intensity of the optical fiber is judged
If the value of (2) is less than 2.5mV, it is the bright ice to determine the light intensity of the optical fiber>
If the value of (2) is greater than 5.2mV, the ice is frost ice, and if both the two requirements are not met, the ice is mixed ice.
........
At a certain time, if the detected ambient temperature is-20 ℃, the received light intensity of the optical fiber is judged
3mV, then mixed ice can be judged according to the above rules.
At a certain time, if the ambient temperature is detected as-Judging the received light intensity of the optical fiber at 25 DEG C
2.4mV, then it can be judged to be open ice according to the above rule.
It will be appreciated by those skilled in the art that the above values are not actual values measured truly, but are chosen randomly to illustrate the principle of the present solution for discriminating ice types.
From the above, it can be seen that, when the discrimination rules under each temperature condition should be stored in the ice-type prediction model library, how to obtain the a and B in the discrimination rules can be achieved by the following steps:
firstly, S201, freezing open ice at each temperature in a laboratory simulation environment, measuring and recording the thickness of the open ice at each temperature
Change discriminating optical fiber receiving light intensity +.>
Is a maximum value a of (a).
Simulating the frost formation of each temperature in a laboratory simulation environment, measuring and recording the thickness of the frost-associated ice under each temperature
Change discriminating optical fiber receiving light intensity +.>
Is a minimum value B of (B).
The ice thickness of the bright ice
And frost ice thickness->
Is consistent with the variation range of (c).
Then S202, when the open ice is frozen at each temperature, the received light intensity of the optical fiber is judged
Is obtained by the maximum value A ofTo ice, temperature and discriminating the light intensity of the optical fiber>
List of maximum values a.
When the frost and ice are frozen at each temperature, the light intensity received by the optical fiber is judged
Obtaining frost ice, temperature and discriminating optical fiber receiving light intensity +.>
List of minima B.
Finally, S203, integrating the two lists in the step S202 to obtain an ice type prediction model library.
The method for detecting the ice thickness based on the optical fiber icing sensor provided by the application can detect the ice layer to be 0-5mm, so that the ice thickness of the ice is made to be open in the step S201
And frost ice thickness->
The variation range of (2) is 0-5 mm.
It will be appreciated by those skilled in the art that temperature values are endless, e.g. -1 ℃, -1.1 ℃, -1.11 ℃, and that it is very labor intensive and difficult to measure each temperature value completely, so that it is preferred in the present application to measure integer temperature values, e.g. -1 ℃, -2 ℃, -3 ℃. It will also be appreciated by those skilled in the art that when an aircraft is flying in the air, the air temperature is typically between 0 ℃ and-40 ℃ and therefore it is often sufficient to measure this interval to ensure that the error is within an acceptable range to reduce the effort. The specific temperature measuring interval is selected by a user according to the use condition. When the measured temperature is an integer, but the actual ambient temperature may have a non-integer condition, the ambient temperature may be rounded to be converted into an integer temperature or an interpolation method may be adopted to match the corresponding ice type discrimination rule.
In step S300, the ice-temperature-fitting function library stores function libraries applicable to different ice types at different temperatures, and the function library construction includes the following steps:
s301, simulating each temperature in a laboratory simulation environment to freeze open ice, and measuring and recording different ice thickness of the open ice
At the time, the first receiving fiber receives the light intensity +.>
And the second receiving optical fiber receives the light intensity +.>
Is a value of (2);
simulating each temperature in a laboratory simulation environment to freeze mixed ice, and measuring and recording different mixed ice thickness
At the time, the first receiving fiber receives the light intensity +.>
And the second receiving optical fiber receives the light intensity +.>
Is a value of (2);
simulating frozen frost ice at each temperature in a laboratory simulation environment, measuring and recording different frost ice thicknesses
At the time, the first receiving fiber receives the light intensity +.>
And the second receiving optical fiber receives the light intensity +.>
Is a value of (2);
s302, drawing a light intensity modulation function when frozen ice is frozen at each temperature according to the data recorded in S301
Iced with +.>
Curve of variation, light intensity modulation function->
；
When the frozen mixed ice at each temperature is drawn, the light intensity modulation function
Iced with +.>
Curve of variation, light intensity modulation function->
；
When the frozen frost ice at each temperature is drawn, the light intensity modulation function
Iced with +.>
Curve of variation, light intensity modulation function->
；
S303, performing function fitting on all curves in the step S302 to obtain fitting functions
And->
；
S304, recording each fitting function, and recording the temperature and the ice type corresponding to each fitting function to obtain an ice type-temperature-fitting function library.
In keeping with the foregoing, it will be appreciated by those skilled in the art that the temperature values are endless, e.g., -1 ℃, -1.1 ℃, -1.11 ℃, and that it is desired to achieve an ice thickness at each temperature value, the first receiving fiber receiving light intensity
And the second receiving optical fiber receives the light intensity +.>
The work load is huge and difficult to achieve by fitting the function, so the application preferably only measures integer temperature values, for example, -1 ℃, -2 ℃, -3 ℃. The air temperature is typically between 0 ℃ and-40 ℃ when the aircraft is flying in the air, so it is often sufficient to measure this interval to reduce the work load within an acceptable range of assurance errors. The specific temperature measuring interval is selected by a user according to the use condition. When the measured temperature is an integer, but there may be non-integer cases in the actual ambient temperature, the ambient temperature may be rounded to an integer temperature or interpolated to match the corresponding fitting function.
To explain the establishment of ice-type prediction model library and ice-type-temperature-fitting function library, the application is exemplified by-5 ℃, -20 ℃, -40 ℃ as follows:
embedding an optical fiber icing sensor on an acrylic plate with a through hole in a high-low temperature test box with model WD6005 in a low-temperature environment required by a laboratory building experiment, setting the temperature in the high-low temperature test box to be-5 ℃ after the sensor is installed, then opening a spraying device to spray simulated water drop impact process to the surface of the icing sensor, and measuring the output voltage and real-time ice thickness corresponding to three paths of receiving optical fibers, recording, wherein the ice thickness measurement can be performed by adopting a micrometer, opening spraying again after the measurement is finished, repeating the process until the ice thickness is accumulated to 5mm, and repeating the experiment for 1-3 times finally for verifying the accuracy.
The temperature in the high-bottom temperature box is respectively set to be minus 20 ℃ for freezing mixed ice and minus 40 ℃ for freezing frost ice, and the steps are repeated.
Then, a graph between the received light intensity of the receiving optical fiber and the ice thickness is drawn, as shown in fig. 7, the received light intensity of the receiving optical fiber is smaller than 2.45 and mV when the frozen bright ice is frozen at the temperature of minus 5 ℃, the received light intensity of the receiving optical fiber is between 2.45 and mV to 5.3 and mV when the mixed ice is frozen at the temperature of minus 20 ℃, and the received light intensity of the receiving optical fiber is larger than 5.3 and mV when the frozen ice is frozen at the temperature of minus 40 ℃.
At-5 ℃, -20 ℃ and-40 ℃,
graph with ice thickness as shown in fig. 4, 5 and 6. The curves shown in fig. 4, 5 and 6 are then fitted to obtain a fitted function.
As shown in FIG. 4, the frozen ice at-5℃is plotted as the ice thickness
Variation->
The resulting fitting function is:
the function can measure the thickness range of the open ice to be 1-5mm.
As shown in FIG. 5, the frozen mixed ice at-20℃is plotted as the thickness of the mixed ice
Variation->
The resulting fitting function is:
the function can measure the thickness range of the mixed ice to be 0.5-5mm.
As shown in FIG. 6, the freezing of the frost ice at-40℃is plotted as the thickness of the frost ice
Variation->
The resulting fitting function is:
the function can measure the thickness range of frost ice to be 0.5-5mm.
The applicant found in several experiments that when freezing open ice, the curve fitting was optimized using a quadratic function, and when freezing mixed ice or frost ice, the curve fitting was optimized using a gaussian function. When the curve is fitted by adopting a quadratic function, two values related to the thickness h of the ice layer can be finally obtained by solving, and if the solved value is positive and negative, the positive value is the final thickness value of the ice layer; if both the solved values are positive values, one unsuitable value can be eliminated according to the approximate interval of the ice thickness condensed at the current temperature, and the rest value is the final ice layer thickness value.
It should be understood by those skilled in the art that, in order to save the program and avoid the situation that the optical fiber icing sensor is iced, it is determined whether the optical fiber icing sensor is iced before step S100 is performed, the transmitting optical fiber 1 in the optical fiber icing sensor emits an optical signal, and any one of the first receiving optical fiber 2, the second receiving optical fiber 3 and the determining optical fiber 4 receives the light transmitted by the transmitting optical fiber 1, so that the position where the optical fiber icing sensor is located is iced.
In order to better execute the method provided by the application, the application also provides an optical fiber icing sensor, which is used for executing the method for detecting the ice thickness based on the optical fiber icing sensor, and comprises a transmitting optical fiber 1, a first receiving optical fiber 2, a second receiving optical fiber 3 and a judging optical fiber 4, wherein one ends of the transmitting optical fiber 1, the first receiving optical fiber 2, the second receiving optical fiber 3 and the judging optical fiber 4 are clustered to form a detection end; at the detection end, a first receiving optical fiber 2, a second receiving optical fiber 3, a transmitting optical fiber 1 and a discriminating optical fiber 4 are arranged in sequence; the light-facing end surfaces of the discriminating optical fibers 4 are inclined with the axes of the discriminating optical fibers, and the light-facing end surfaces of the first receiving optical fibers 2 and the second receiving optical fibers 3 are perpendicular to the respective axes; the other end of the transmitting optical fiber 1 is provided with a light-emitting element, and the other ends of the first receiving optical fiber 2, the second receiving optical fiber 3 and the distinguishing optical fiber 4 are provided with photoelectric detection devices.
The specific arrangement and selection of the light emitting elements and the photodetection devices described above are well known to those skilled in the art, and are not described in detail in this application.
Unlike the utility model patent CN114839163a of the university of electronic technology, the optical fiber icing sensor provided by the present application further comprises a judging module and a calculating module; the judging module performs steps S200 and S300, and the calculating module performs step S400. The determination module and the implementation module are designed by combining the above-mentioned objects to be achieved by the present application and the related design knowledge of the modules, and thus, the present application is not repeated herein.
Preferably, in the method of the present application, the ambient temperature needs to be acquired, and the ambient temperature needs to be acquired by a related temperature detector, thermometer and the like, and in order to integrate the optical fiber icing sensor provided by the present application, it is preferable that the optical fiber icing sensor further comprises a temperature sensor 5 arranged at a detection end for detecting the ambient temperature. Having a temperature sensor 5 an optical fiber icing sensor is more advantageous for implementing the method provided herein. In the specific embodiment of the present utility model, the temperature sensor 5 is a thermocouple temperature sensor.
The application also provides a storage medium storing a computer program for executing the method for detecting ice thickness based on the optical fiber icing sensor. The storage medium is a computer-readable storage medium, and may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read only memory), an EPROM, a hard disk, or a ROM. Optionally, the computer readable storage medium comprises a non-volatile computer readable medium (non-transitory computer-readable storage medium). The computer readable storage medium has storage space for program code to perform any of the method steps described above. The program code can be read from or written to one or more computer program products. The program code may be compressed, for example, in a suitable form.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present utility model, and are not limiting; while the utility model has been described in detail with reference to the foregoing embodiments, it will be appreciated by those skilled in the art that variations may be made in the techniques described in the foregoing embodiments, or equivalents may be substituted for elements thereof; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present utility model.
Claims (9)
1. The method for detecting the ice thickness based on the optical fiber icing sensor is characterized in that the optical fiber icing sensor is arranged on an object plane to be detected, the optical fiber icing sensor comprises a transmitting optical fiber (1), a first receiving optical fiber (2), a second receiving optical fiber (3) and a distinguishing optical fiber (4), and one ends of the transmitting optical fiber (1), the first receiving optical fiber (2), the second receiving optical fiber (3) and the distinguishing optical fiber (4) are clustered to form a detection end; at the detection end, a first receiving optical fiber (2), a second receiving optical fiber (3), a transmitting optical fiber (1) and a discriminating optical fiber (4) are sequentially arranged; the light-facing end surface of the discriminating optical fiber (4) is inclined with the axis of the discriminating optical fiber, and the light-facing end surfaces of the first receiving optical fiber (2) and the second receiving optical fiber (3) are vertical to the respective axes; the other end of the transmitting optical fiber (1) is provided with a light-emitting element, and the other ends of the first receiving optical fiber (2), the second receiving optical fiber (3) and the judging optical fiber (4) are provided with photoelectric detection devices;
the method comprises the following steps:
s100, acquiring the current ambient temperature T, and acquiring the received light intensity of a first receiving optical fiber of the optical fiber icing sensor
The second receiving optical fiber receives the light intensity +.>
And discriminating the received light intensity of the optical fiber>
；
S200, judging the received light intensity of the optical fiber
Inputting the current environmental temperature T into an ice type prediction model library to obtain an ice type, wherein the ice type comprises open ice, mixed ice and frost ice;
s300, inputting the ice type and the current environment temperature T into an ice type-temperature-fitting function library to obtain the corresponding ice type and temperature
Fitting function, wherein the light intensity modulation function +.>
，/>
Is the thickness of the ice layer;
s400, receiving the light intensity of the first receiving optical fiber
And the second receiving optical fiber receives the light intensity +.>
Carry in->
In the fitting function, the thickness h of the ice layer is calculated.
2. The method for detecting ice thickness based on an optical fiber icing sensor according to claim 1, wherein in step S200, the ice type discrimination rule of the ice type prediction model library is:
under the condition that the ambient temperature is T, the received light intensity of the optical fiber is judged
When less than A mV, the crystal is open ice; discriminating the light intensity of the optical fiber>
When the value is more than B mV, the ice is frost ice, and the ice which does not meet the two conditions is mixed ice; a is the light intensity of the optical fiber received light which is judged according to the change of the ice thickness under the condition that the ambient temperature is T and the ice is frozen>
Is the maximum value of (2); b is that under the condition that the ambient temperature is T, the frost ice is frozen, and the light intensity of the optical fiber received light is judged according to the change of the ice thickness +.>
Is a minimum of (2).
3. The method for detecting ice thickness based on an optical fiber icing sensor according to claim 2, wherein the establishment of the ice prediction model library comprises the steps of:
s201, simulating each temperature in a laboratory simulation environment to freeze the ice, measuring and recording the thickness of the ice along with the ice at each temperature
Change discriminating optical fiber receiving light intensity +.>
A maximum value a of (a);
simulating the frost formation of each temperature in a laboratory simulation environment, measuring and recording the thickness of the frost-associated ice under each temperature
Change discriminating optical fiber receiving light intensity +.>
A minimum value B of (2);
the ice thickness of the bright ice
And frost ice thickness->
Is consistent with the variation range of (2);
s202, judging the light intensity received by the optical fiber when the open ice is frozen at each temperature
Obtaining ice, temperature and discriminating optical fiber received light intensity +.>
A list of maxima a;
when the frost and ice are frozen at each temperature, the light intensity received by the optical fiber is judged
Obtaining frost ice, temperature and discriminating optical fiber receiving light intensity +.>
A list of minimum values B;
and S203, integrating the two lists in the step S202 to obtain an ice type prediction model library.
4. The method for detecting ice thickness based on an optical fiber icing sensor according to claim 1, wherein in step S300, the establishment of the ice-type-temperature-fitting function library comprises the steps of:
s301, simulating each temperature in a laboratory simulation environment to freeze open ice, and measuring and recording different ice thickness of the open ice
At the time, the first receiving fiber receives the light intensity +.>
And the second receiving optical fiber receives the light intensity +.>
Is a value of (2);
simulating each temperature in a laboratory simulation environment to freeze mixed ice, and measuring and recording different mixed ice thickness
At the time, the first receiving fiber receives the light intensity +.>
And the second receiving optical fiber receives the light intensity +.>
Is a value of (2);
simulating frozen frost ice at each temperature in a laboratory simulation environment, measuring and recording different frost ice thicknesses
At the time, the first receiving fiber receives the light intensity +.>
And the second receiving optical fiber receives the light intensity +.>
Is a value of (2);
s302, drawing a light intensity modulation function when frozen ice is frozen at each temperature according to the data recorded in S301
With ice thickness
Curve of variation, light intensity modulation function->
；
When the frozen mixed ice at each temperature is drawn, the light intensity modulation function
Along with iceThickness->
Curve of variation, light intensity modulation function->
；
When the frozen frost ice at each temperature is drawn, the light intensity modulation function
Iced with +.>
Varying curve, light intensity modulation function
；
S303, performing function fitting on all curves in the step S302 to obtain fitting functions
And->
；
S304, recording each fitting function, and recording the temperature and the ice type corresponding to each fitting function to obtain an ice type-temperature-fitting function library.
5. The method for detecting ice thickness based on an optical fiber icing sensor according to claim 4, wherein in step S303, when frozen open ice, a quadratic function is used for curve fitting; when freezing mixed ice or frost ice, a gaussian function is used to fit the curve.
6. The method for detecting ice thickness based on the optical fiber icing sensor according to claim 1, wherein before step S100 is performed, it is determined whether the optical fiber icing sensor is iced, the transmitting optical fiber (1) in the optical fiber icing sensor emits an optical signal, and any one of the first receiving optical fiber (2), the second receiving optical fiber (3) and the discriminating optical fiber (4) receives the light transmitted by the transmitting optical fiber (1), so that the position where the optical fiber icing sensor is located is iced.
7. An optical fiber icing sensor, characterized in that: a method for executing the optical fiber icing sensor-based ice thickness detection according to any one of claims 1 to 6, comprising a transmitting optical fiber (1), a first receiving optical fiber (2), a second receiving optical fiber (3) and a discriminating optical fiber (4), wherein one ends of the transmitting optical fiber (1), the first receiving optical fiber (2), the second receiving optical fiber (3) and the discriminating optical fiber (4) are clustered to form a detection end; at the detection end, a first receiving optical fiber (2), a second receiving optical fiber (3), a transmitting optical fiber (1) and a discriminating optical fiber (4) are sequentially arranged; the light-facing end surface of the discriminating optical fiber (4) is inclined with the axis of the discriminating optical fiber, and the light-facing end surfaces of the first receiving optical fiber (2) and the second receiving optical fiber (3) are vertical to the respective axes; the other end of the transmitting optical fiber (1) is provided with a light-emitting element, and the other ends of the first receiving optical fiber (2), the second receiving optical fiber (3) and the judging optical fiber (4) are provided with photoelectric detection devices;
the system also comprises a judging module and a calculating module;
the judging module performs steps S200 and S300, and the calculating module performs step S400.
8. An optical fiber icing sensor according to claim 7 wherein: the device also comprises a temperature sensor (5) arranged at the detection end and used for detecting the ambient temperature.
9. A storage medium, characterized in that a computer program for executing the method for detecting ice thickness based on an optical fiber icing sensor according to any of claims 1 to 6 is stored.
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