Optical particulate sensor using multi-line lasers to improve measurement accuracy

Abstract

To improve the accuracy of measuring the content of volcanic ash, sand, and dust. [Solution] The system comprises a particulate sensor unit, which includes a light source that directs at least two light beams towards an inspection area where portions of the light beams overlap. An optical detector captures scattered or reflected light from aerosol particles in the inspection area passing through the light beams. A processor performs a particle size determination method for aerosol particles in the inspection area where the optical response of the scattered or reflected light is detected. If the detected optical response has two peaks, the method includes determining a first optical response value for a particle located near the center of one of the light beams, determining a second optical response value for a particle located between the light beams, identifying the ratio between the first and second optical response values, and estimating the particle size based on the identified ratio.

Description

[[Technical Field]]

[0001] (Statement of Federally Sponsored Research and Development) This invention was made with government support under S0176492 / 101102008 awarded by CAJU. The government has certain rights in this invention. [[Background Art]]

[0002] High concentrations of supercooled water droplets or ice crystals in the atmosphere cause ice accretion on aircraft frames or inside aircraft engines, leading to multiple problems such as increased drag, reduced lift, reduced thrust, and other issues. Furthermore, volcanic ash is hard and abrasive, and high concentrations of volcanic ash in the atmosphere cause significant wear to propellers and turbo compressor blades, leading to engine flameout and other problems.

[0003] Since water droplets are spherical and ice crystals are non-spherical, in conventional particle sensors, the distinction between water droplets and ice crystals can be based on depolarization signal analysis. Also, since water droplets are spherical while volcanic ash, sand, and dust are non-spherical, the discrimination between water droplets and volcanic ash, sand, or dust particles can be based on depolarization signal analysis.

[0004] In the aircraft industry, there is a need for a sensor that can monitor icing conditions as well as the conditions of volcanic ash, sand, and dust in the atmosphere. Existing minimum operational performance specification (MOPS) standards require that the sensor measurement accuracy be less than 30% in estimating liquid water content and ice water content. However, current sensor measurement accuracy does not meet the target performance. The measurement accuracy of the content of volcanic ash, sand, and dust is not sufficient to meet user requirements, and it needs to be improved to support engine maintenance and optimization of flight routes near volcanic ash events. [[Summary of the Invention]]

[0005] The system comprises a particulate sensor unit for a vehicle, which comprises at least one light source configured to direct at least two light beams toward an inspection area outside the vehicle, with portions of the light beams overlapping. An optical detector is configured to capture scattered or reflected light from aerosol particles in the inspection area passing through at least two light beams, and a processor communicates operably with the optical detector. The processor hosts a program module having instructions executable by the processor to implement a particle size determination method for aerosol particles in the inspection area. The method includes detecting the optical response of scattered or reflected light from the inspection area, and if the detected optical response has two peaks, the method includes determining a first optical response value of a particle when located near the center of one of the light beams, determining a second optical response value of a particle when located between the light beams, identifying a ratio value between the first optical response value of the particle and the second optical response value of the particle, and estimating the size of the particle based on the identified ratio value. [Brief explanation of the drawing]

[0006] The features of the present invention will become apparent to those skilled in the art from the following description with reference to the drawings. It should be understood that the drawings only show typical embodiments and are therefore not limiting in scope. The present invention will be described more specifically and in detail with reference to the attached drawings. [Figure 1] This is a block diagram of a system for enhanced particle detection for use in vehicles, according to one embodiment. [Figure 2A] This is a schematic simulation diagram showing the dependence of the optical response of ice crystals on their orientation relative to the sensor. [Figure 2B] This is a schematic simulation diagram showing the dependence of the optical response of ice crystals on their orientation relative to the sensor. [Figure 2C] This is a simulation graph showing the dependence of the optical response of ice crystals on the orientation of ice crystals relative to the sensor. [Figure 3A]This is a schematic diagram illustrating an example of the optical response type of aerosol particles. [Figure 3B] This is a schematic diagram illustrating an example of the optical response type of aerosol particles. [Figure 3C] This is a schematic diagram illustrating an example of the optical response type of aerosol particles. [Figure 3D] This is a schematic diagram illustrating an example of the optical response type of aerosol particles. [Figure 3E] This is a schematic diagram illustrating an example of the optical response type of aerosol particles. [Figure 3F] This is a schematic diagram illustrating an example of the optical response type of aerosol particles. [Figure 4A] This is a simulation graph displaying the optical response of water droplets and ice crystals, showing multiple optical response types of aerosol particles. [Figure 4B] This is a simulation graph displaying the optical response of water droplets and ice crystals, showing multiple optical response types of aerosol particles. [Figure 4C] This is a simulation graph displaying the optical response of water droplets and ice crystals, showing multiple optical response types of aerosol particles. [Figure 4D] This is a simulation graph displaying the optical response of water droplets and ice crystals, showing multiple optical response types of aerosol particles. [Figure 4E] This is a simulation graph displaying the optical response of water droplets and ice crystals, showing multiple optical response types of aerosol particles. [Figure 5] A-C are simulated displays of two laser beams with Gaussian beam profiles, where ice crystals pass through the Gaussian beam profile along the airflow direction. [Figure 6] This is a graphical representation of the aerosol optical response within a single-line laser beam profile. [Figure 7A] This is a graphical representation of the aerosol optical response within a multi-line laser beam profile. [Figure 7B] This is a graphical representation of the aerosol optical response within a multi-line laser beam profile. [Figure 8] This graph represents two Gaussian beam scenarios and demonstrates that the size of the ice crystals can be estimated using the ratio between the optical response peak amplitude and the optical response minimum between the two amplitude peaks (MIN / MAX ratio). [Figure 9] This graph represents two Gaussian beam scenarios and demonstrates that the size of the water droplet can be estimated using the MIN / MAX ratio. [Figure 10A] The histogram distribution of optical response peak amplitude and MIN / MAX ratio values ​​for different types and shapes of aerosol particles is shown. [Figure 10B] The histogram distribution of optical response peak amplitude and MIN / MAX ratio values ​​for different types and shapes of aerosol particles is shown. [Figure 10C] The histogram distribution of optical response peak amplitude and MIN / MAX ratio values ​​for different types and shapes of aerosol particles is shown. [Figure 11] This is a simulated display of three light beam patterns, one of which is asymmetrical. [Figure 12] This is a simulated optical response of an ice crystal, where the ice crystal is larger than the light beam width and has only one type of optical response. [Figure 13] This is a simulated optical response of a water droplet when the droplet is larger than the width of the light beam. [Figure 14] This is a simulated optical response of an ice crystal with a beam width greater than that of a single light beam and possessing multiple types of optical response characteristics. [Figure 15] This is a flowchart of a method for determining particle size according to one embodiment, which may be used in the system shown in Figure 1. [Figure 16] An exemplary embodiment of a system for generating a two-line optical signal beam pattern is shown. [Modes for carrying out the invention]

[0007] In the following detailed description, embodiments are described in sufficient detail to enable those skilled in the art to carry out the invention. It should be understood that other embodiments may be utilized without departing from the scope of the invention. Therefore, the following detailed description should not be construed as restrictive.

[0008] This specification describes a system and method for implementing an optical particulate sensor using a multi-line laser, which provides improved measurement accuracy.

[0009] Generally, this system uses at least two light beams located in close proximity to each other, with portions of the light beams overlapping. When aerosol particles pass through the light beams, they reflect or scatter light in the direction of the sensor's optical system, and the optical response is measured by the sensor, and the measured signal is normalized. Although the light beams may have multiple types of profiles, in the following text, it is assumed that each light beam has a Gaussian profile.

[0010] If the particle size is smaller than the distance between the centers of two consecutive Gaussian peaks, the optical response will include two peaks with approximately the same amplitude and one minimum value between the peaks with approximately the same amplitude. The ratio between the optical response peak amplitude ("MAX") and the optical response minimum ("MIN") between the two amplitude peaks is determined. The particle size is estimated based on the value of the identified ratio.

[0011] If the particle size is similar to or greater than the distance between the centers of two consecutive Gaussian peaks, the optical response may contain a number of peaks different from two, and the amplitude of the peaks may vary. In this case, a composite peak shape analysis method is performed, and the particle size is estimated based on its similarity to a reference peak shape and its duration.

[0012] If a particle crosses two light beams and the measured optical response has two peaks, each with approximately the same amplitude, then the air velocity in the sensor-tested volume can be calculated if the sampling period is known.

[0013] This method is more tolerant of differences in particle optical responsiveness compared to particle size estimation using only optical response amplitude. For example, in the case of water droplets, the optical response depends on particle size because the droplets are spherical. In the case of non-spherical particles such as ice crystals and volcanic ash, the optical response depends on particle size, shape, orientation in space, surface optical properties, and material optical properties. By using the method of the present invention for such non-spherical particles, higher measurement accuracy can be achieved. This method can be combined with other particle size determination methods to achieve even higher measurement accuracy.

[0014] This method uses differential measurement to detect particle size, thereby reducing not only the dependence of particle size measurement on the optical responsiveness of the particles but also on the transmittance of the optical window. Therefore, it significantly reduces measurement errors caused by disturbances in the transparency of the optical window (e.g., dirt, wear, effects of aging of the window material, insects colliding with the sensor window, etc.). This method can provide significantly higher measurement accuracy for ice crystals, as well as volcanic ash / sand / dust particles. This method is expected to work optimally when the particle shape is not highly asymmetrical, which is likely to apply to most ash particles and composite ice crystals.

[0015] Further details of various embodiments will be described below with reference to the drawings.

[0016] Optical particle sensor design Figure 1 shows a system 100 for enhanced particle sensing, according to one embodiment, for use in a vehicle 102 such as an aircraft. The system 100 includes a particulate sensor unit 110 within the vehicle 102, which comprises at least one light source 112, such as a laser device, configured to direct at least two light beams toward an inspection area 120 outside the vehicle 102. The system 100 also includes an optical detector 114 and a processor 130 that operably communicates with the optical detector 114. The optical detector 114 is configured to capture scattered or reflected light from aerosol particles in the inspection area 120 passing through at least two light beams. The particulate sensor unit 110 also includes a pair of photoreceiving optics 116 configured to provide at least one receiving channel.

[0017] In one embodiment, the light source 112 and the light-receiving optical system 116 may be implemented in an optical transceiver that is part of a light detection and ranging (LiDAR) device. The light-receiving optical system 116 couples the received light to an optical detector 114, which may include one or more photodetectors such as avalanche photodiodes. In one embodiment, the light source 112 is configured to generate a multi-line laser pattern in which each line is parallel to the other. In another embodiment, the light source 112 is configured to generate multiple light beams, each having a flat-top profile in one axis and a Gaussian profile in the vertical axis.

[0018] The processor 130 hosts a program module having instructions executable by the processor 130, and executes a particle size determination algorithm 132 for aerosol particles in the inspection area 120 based on measurement data from the optical detector 114. At least one memory unit 140 communicates operably with the processor 130. A database 142 may be stored in the memory unit 140. The database 142 may store calibration lookup tables, parameters describing the shape of the reference optical response, and the like.

[0019] In an exemplary operation, the light source 112 transmits two light beams 150, 152 into an inspection area 120 outside the vehicle 102, with portions of the light beams 150, 152 overlapping. The light-receiving optics 116 collects scattered or reflected portions 154, 156 of the light beams 150, 152 from at least one aerosol particle 160 within the inspection area 120. The optical detector 114 receives the collected scattered or reflected portions 154, 156 through a light-receiving channel provided by the light-receiving optics 116. The optical detector 114 converts the light from the scattered or reflected portions 154, 156 into an electrical signal proportional to the light intensity. This allows the optical detector 114 to measure the optical response as a function of time to generate measurement data, which is sent to a processor 130 to be used by a particle size determination algorithm 132 to generate particle size data, which can use data stored in a database 142. The particle size data can be output from the processor 130 to other vehicle systems, such as a vehicle computer, for use in further vehicle data processing.

[0020] As will be described in more detail below, the particle size determination algorithm 132 is carried out based on detecting the optical responses of collected scattered or reflected portions 154, 156 of the light beams 150, 152. In one embodiment, if the light source 112 transmits two light beams and the detected optical response has two peaks of approximately the same amplitude and a single minimum value between the two peaks, the particle size determination algorithm 132 determines a first optical response value of the particle when it is located near the center of one of the light beams, determines a second optical response value of the particle when it is located near the area between the two light beams, identifies a ratio value between the first optical response value of the particle and the second optical response value of the particle, and estimates the size of the particle based on the identified ratio value.

[0021] In one example, if a light source transmits two light beams and the detected optical response has two peaks with nearly the same amplitude, and one minimum value is detected between the two peaks, particle size estimation can be performed using a calibration lookup table.

[0022] In another exemplary embodiment, if a light source transmits two light beams and the detected optical response has two different numbers of peaks or the amplitudes of each of the two peaks are significantly different, the particle size analysis method may be performed using optical response peak shape analysis, in which the amount of light scattered or reflected from the particle is analyzed over time, and the particle size is determined based on the shape of the optical response signal, the duration of the optical response signal, and the amplitude of each of the optical response peaks.

[0023] Optical response of aerosols General Information: When the equivalent diameter of a non-spherical particle is mentioned in the following text, it can be understood as the equivalent diameter of a water droplet having the same volume as the non-spherical particle. When a Gaussian beam width of a certain value is mentioned in the following text, the Gaussian beam width is 1 / e 2 It is thought to be defined as having a diameter of [value].

[0024] In conventional particle sizing methods that use optical response peak amplitudes, the size of aerosol particles is determined based on the peak amplitude of scattered or reflected optical signals and is highly dependent on the optical responsiveness of the particles. Calibration lookup tables are used to convert the measured optical response peak amplitudes into particle sizes.

[0025] For example, water droplets in the atmosphere are spherical or nearly spherical in shape up to about 2,000 microns in diameter, their surfaces are smooth, and their material composition is known. The spatial orientation of the droplets does not affect the optical response because the particle shape is spherical. Therefore, the optical response of water droplets is highly deterministic, and conventional particle size determination methods can be used. However, the optical response of ice crystals or volcanic ash particles depends heavily on their shape, orientation relative to the sensor, surface properties, and material properties. Using conventional particle size determination methods for ice crystals or volcanic ash particles increases sensor measurement errors.

[0026] Assume that a water droplet with a diameter of 20 microns is measured by an optical particulate sensor. Since the shape of the water droplet is spherical, its optical response is the same for any random orientation of the water droplet, and the same optical response is measured by the sensor. Therefore, the sensor achieves high measurement accuracy for water droplet particles. In the case of ice crystals, the situation is quite different, and the optical response depends on the shape of the particle and its orientation relative to the sensor. Examples of such situations are shown in Figures 2A, 2B, and 2C, which are described below.

[0027] Figures 2A and 2B are schematic diagrams illustrating the ice crystal optical response, demonstrating that the ice crystal optical response differs from the water droplet optical response. This example utilizes light beam 210, which has a Gaussian beam profile, and its 1 / e 2 The beam diameter is 100 microns.

[0028] In the example shown in Figure 2A, an ice crystal 212 (with orientation A) having a size of 20 microns passes through the light beam 210 and has a peak amplitude of 3.0E-05, as shown in plot 220. In the example shown in Figure 2B, an ice crystal 214, which is the same shape and size as ice crystal 212 but differs only in orientation (orientation B) relative to the sensor, passes through the light beam 210 and has a peak amplitude of 1.3E-05, as shown in plot 222. The particles move horizontally through the laser beam, with the Gaussian axis perpendicular to the fat-top axis, and the vertical displacement is shown to provide better visibility of the particle position.

[0029] Figure 2C is graph 230 showing the optical response of ice crystals with a size of 20 microns, where all ice crystals are the same size and shape but have different orientations relative to the sensor. The vertical axis of graph 230 is the optical response (AU), and the horizontal axis is the distance of the particle from the center of the Gaussian beam (microns). As shown, the optical response curve 232 for ice crystals with orientation A has a higher peak amplitude and longer peak duration than the optical response curve 234 for ice crystals with orientation B. The ice crystals with orientation B have a higher peak amplitude and longer peak duration than the optical response curve 236 for ice crystals with orientation C.

[0030] Ice crystals and ash / sand / dust particles of the same size and shape can produce optical responses with different peak amplitudes and peak durations. This is different from water droplets, where each size produces unique values ​​for peak amplitude and peak duration.

[0031] Water droplets and ice crystal particles exhibit very low optical signal attenuation within the material. Therefore, atmospheric water droplets and ice crystals can be considered transparent. Volcanic ash particles exhibit higher optical signal attenuation, which can allow optical signals to travel only a few tens of microns within the particle without significant attenuation. For small volcanic ash particles, the material can be considered transparent or translucent, while larger particles can be considered opaque.

[0032] Figures 3A to 3F show the optical responses of water droplets and hexagonal ice crystals, which have diameters significantly larger than the Gaussian width of the light beam. As shown in the figures, the aerosol particles move from top to bottom in the direction of the airflow.

[0033] Figures 3A to 3C illustrate three types of optical responses of a water droplet 302 detected by a particulate sensor 310, which includes a light source 312 transmitting a beam 314 and a set of photoreceiving optics 316. Figure 3A shows the secondary rainbow optical response of the water droplet 302, which is caused by two internal reflections and two refractions from the beam 314. Figure 3B shows the direct optical signal reflection of the water droplet 302, which is caused by the reflection of the optical signal from the surface of the water droplet 302. Figure 3C shows the primary rainbow optical response of the water droplet 302, which is caused by one internal reflection and two refractions.

[0034] The intensities of the three optical responses shown in Figures 3A to 3C can differ significantly. For example, the optical response caused by the primary rainbow effect may be higher than the optical response caused by the secondary rainbow effect, and the secondary rainbow effect may be higher than the direct optical signal reflection.

[0035] Figures 3D to 3F illustrate three types of optical responses of hexagonal ice crystals 304 detected by the particle sensor 310. Figure 3D shows the optical response of an ice crystal 304 having a first orientation relative to the sensor 310. In this scenario, the ice crystal 304 provides only a directional response to the light-receiving optical system 316, caused by two reflections and two refractions. In the ice crystal orientation shown in Figure 3D, the ice crystal 304 has only a single type of optical response.

[0036] Figures 3E and 3F show the optical response of ice crystals 304 having a second orientation relative to the sensor 310. In Figure 3E, ice crystals 304 provide a first optical response caused by direct reflection of the beam 314. In Figure 3F, ice crystals 304 provide a second optical response caused by one reflection and two refractions. In the ice crystal orientations shown in Figures 3E and 3F, ice crystals 304 have two types of optical responses.

[0037] Generally, ice crystals and volcanic ash / sand / dust particles exhibit multiple types of optical responses, and the intensity of each type of optical response can vary depending on the optical properties of the particle surface, the optical properties of the material, its shape, and its orientation relative to the sensor.

[0038] The optical transmitter is 1 / e 2 Assume that a light beam with a Gaussian profile having a defined width is generated. If the longest diameter of the aerosol particles is shorter than the light beam width, all types of optical signal responses are generated simultaneously, and the measured optical signal responses can be considered to be linearly proportional to the light beam energy density profile.

[0039] If the longest diameter of an aerosol particle is similar in size to or greater than the light beam width, individual optical response types may be generated separately, and therefore the optical response is no longer linearly proportional to the energy density of the light beam profile. A method for evaluating the size of such particles is described below under the heading "Multiline Measurement Method of the Invention for Large Particles".

[0040] Figures 4A to 4C show the Gaussian profile and 1 / e of 100 microns. 2 These are graphs of the optical response of a water droplet in a beam of light with width. In the graphs in Figures 4A to 4C, the vertical axis represents the optical response (AU), and the horizontal axis represents the distance of the particle from the center of the Gaussian beam (microns).

[0041] Figure 4A is a graph showing the optical response of a water droplet with a diameter of 50 microns. Since the droplet is smaller than the width of the light beam, all individual optical response types occur simultaneously, and the response is linearly proportional to the energy density of the light beam profile. Since the light beam profile is Gaussian, the optical response also has a Gaussian profile.

[0042] Figure 4B is a graph showing the optical response of a water droplet with a diameter of 150 microns. The droplet diameter is 1 / e of the light beam. 2Since the width is greater than the Gaussian width, the optical response includes two peaks: the first peak 422 is caused by direct reflection and secondary rainbow effect, and the second peak 424 is caused by primary rainbow effect. Figure 4C is graph 430 showing the optical response of a water droplet with a diameter of 300 microns. The droplet size is 1 / e of the light beam. 2 Because it is significantly larger than the Gaussian width, the optical response includes three peaks: the first peak 432 is caused by the secondary rainbow effect, the second peak 434 is caused by direct reflection, and the third peak 436 is caused by the primary rainbow effect. The scenarios in Figures 4B and 4C show an optical response that is not linearly proportional to the energy density of the light beam profile.

[0043] As shown in Figures 4A to 4C, increasing the droplet diameter results in more complex optical responses being detected by the sensor. Ice crystals and volcanic ash / sand / dust particles can also have multiple types of optical responses. The maximum diameter of the ice crystal or ash particle is 1 / e of the light beam. 2 When the width is shorter than the Gaussian width, the optical response can be considered to be linearly proportional to the energy density of the optical beam profile, as shown in Figure 4A.

[0044] The maximum diameter of ice crystals or ash particles is 1 / e of the light beam. 2 When the size is similar to or larger than the Gaussian width, the optical response may include multiple individual responses of varying intensities. This is shown in the graphs of Figures 4D and 4E, where the vertical axis is the optical response (AU) and the horizontal axis is the distance of the particle from the center of the Gaussian beam (microns).

[0045] FIG. 4D is a graph 440 showing that a cubic-shaped ice crystal with an equivalent diameter of 150 microns produces an optical response 442 that does not conform to the Gaussian profile of the light beam. FIG. 4E is a graph 450 showing that more complex ice crystals can produce more complex optical responses. Here, intersecting hexagonal ice crystals produce an optical response having two peaks at 452 and 454. The two peaks are produced by the symmetry of the intersecting hexagonal particles, and the two peaks are produced under a specific spatial orientation of the set of particles relative to the sensor.

[0046] In summary, particles having a maximum diameter smaller than the light beam width produce an optical response linearly proportional to the light beam energy density. Particles having a maximum diameter similar to or larger than the light beam width produce an optical response that may be composed of multiple types of optical responses, and the measured optical signal may not be linearly proportional to the energy density of the light beam profile.

[0047] Multi-line laser beam FIGS. 5A to 5C show a 1 / e of a 160 micron light beam 2 It is an exemplary schematic diagram of multi-line light beams 510 and 512 having a Gaussian width. The light beams 510 and 512 are separated from each other by a distance of 160 microns. This configuration can be used in the present method to measure particles of different sizes. In these examples, simulated optical responses of small aerosol particles, medium aerosol particles, and large aerosol particles traveling through a pair of beams are shown relative to the airflow direction. The optical response of the particles is normalized (e.g., the maximum value is set to 1.0). The simulated particle shape is an ice crystal having a cubic shape, and the orientation thereof is selected such that it only has a single type of optical response. The particles move horizontally through the laser beam, and vertical displacement is shown to allow better visualization of the position of large particles.

[0048] As shown in Figure 5A, the small particle 520 passes through the light beams 510, 512. For small particles such as particle 520, two distinct peaks are observed when the particle size is significantly smaller compared to the Gaussian width of the light beam. This is shown in plot 522, where two distinct peak amplitudes are observed at 524 and 526, and a weak optical response 525 is detected between the two peaks.

[0049] In the example shown in Figure 5B, a medium-sized particle 530 passes through light beams 510 and 512. For a medium particle like particle 530, as the particle moves between the two beams, it simultaneously reflects or scatters some of the light from both beams, and therefore a stronger optical signal is detected when the particle is between the beams. This is shown in plot 532, where a stronger optical signal is detected at peak amplitude 535 between 534 and 536 when particle 530 is between light beams 510 and 512.

[0050] In the example shown in Figure 5C, a large particle 540 passes through light beams 510 and 512. For large particles such as particle 540, the particle is larger than the distance between the two beams, so the particle reflects or scatters most of the light from both beams simultaneously, and therefore a higher peak is detected while the particle is between the two beams. This is shown in plot 542, where a higher peak is detected at 544 while the particle is between light beams 510 and 512.

[0051] The strongest optical response of aerosol particles may not occur when the particle's center of mass is within the center of the light beam. This effect is shown in Figures 3A, 3B, and 3C above. The horizontal coordinate of the peak center of the light beam is 0 microns. In Figure 3A, when a water droplet enters the light beam, a secondary rainbow is detected by the sensor. Next, the water droplet moves with the airflow, as shown in Figure 3B, and the light beam collides with the center of the water droplet. Direct reflection is detected by sensor 310. Next, as shown in Figure 3C, the water droplet 302 moves with the airflow, and a primary rainbow is generated before the water droplet 302 leaves the light beam 314.

[0052] In the sensor setup described, the strongest optical response of the water droplet is caused by the primary rainbow, and therefore the strongest optical response occurs when the center of gravity of the water droplet is not within the peak position of the light beam. Thus, amplitude of the optical response can occur when the particle is at or near the center of the light beam. Also, the minimum signal between the two amplitudes can be generated between the two light beams or in the vicinity between the centers of the two light beams.

[0053] The present invention's multi-line measurement method for small aerosol particles Assume the light beam has a Gaussian profile and the maximum size of the aerosol particles is smaller than the beam width. The Gaussian width is 1 / e 2 It can be defined as follows: In such a scenario, the particle size can be considered small compared to the width of the light beam profile, and even if the particles have multiple optical responses, they are generated simultaneously. Optical particulate sensors typically measure data in laminar high-speed airflow that is stable on the timescale of particles flying through the sensor's measurement volume. The rotation speed of the particles is too slow compared to the transition time of the particles through the measurement volume. Therefore, the spatial orientation of the particles does not change as the particles pass through the sensor's measurement volume.

[0054] Figure 6 shows the conventional particle size determination method described above under the heading "Aerosol Optical Response". In one example, the optical beam profile is 1 / e50 microns. 2 If the aerosol particles 610 have a Gaussian width, they are in the beam and the measurement is performed at position 612. This example is simplified for clarity. The following equation, LBAED * A *The optical response of a particle is determined using OPR. Here, LBAED is the average energy density of the light beam in which the particle resides, A is the particle area, and OPR is the optical response of the particle. The average energy density of the light beam changes with particle size; if the particle size is very small, its volume resides within a region of the light beam with a nearly uniform energy density. If the particle is large, its volume may be in regions with different energy densities, and therefore the average energy density of the light beam is the average of multiple energy densities in which the particle resides.

[0055] As shown in the plot in Figure 6, in the first orientation relative to the sensor, the average energy density of the light beam in which the particles are present is 98 [AU]. The particle area is 100 μm². 2 The particles reflect 0.3% of the light power in the direction of the sensor's optical system. The amplitude of the measured optical response is 98 * 100 * 0.003 = 29.4 [AU * μm 2 ]. In the second orientation relative to the sensor, the average energy density of the light beam in which the particles are present is 98 [AU], and the particle area is 100 μm². 2 The particles reflect 0.1% of the light power in the direction of the sensor's optical system. The amplitude of the measured optical response is 98 * 100 * 0.001 = 9.8 [AU] * μm 2 ] When determining particle diameter using the measured optical signal amplitude, different sizes result from the same particle having different orientations.

[0056] This system utilizes multi-line optical beam profiles to reduce measurement errors caused by differences in the optical responsiveness of aerosol particles. Examples of such methods are shown in Figures 7A and 7B. These examples are 1 / e of 50 microns. 2Two light beams with Gaussian widths are used, separated by a distance of 50 microns. The Gaussian width and light beam separation values ​​are specified for illustrative purposes only. Both values ​​may differ in actual use cases.

[0057] In Figure 7A, irregularly shaped aerosol particles 710 are present in the laser beam, and the measurement is performed at the first position 720. In the first orientation relative to the sensor, the average energy density of the light beam in which the particles 710 are present is 98 [AU], and the particle area is 100 μm². 2 The particles reflect 0.3% of the light power in the direction of the sensor's optical system. The amplitude of the measured optical response ("MAX") is 98 * 100 * 0.003 = 29.4 [AU * μm 2 In the second orientation relative to the sensor, the average energy density of the light beam containing particle 710 is 98 [AU], and the particle area is 100 μm². 2 The particles reflect 0.1% of the light power in the direction of the sensor's optical system. The amplitude of the measured optical response ("MAX") is 98 * 100 * 0.001 = 9.8 [AU] * μm 2 ]

[0058] The optical response of the particle is also measured at the second position 722. In the first orientation relative to the sensor, the average energy density of the light beam in which particle 710 is present is 12 [AU], and the particle area is 100 μm². 2 The particle reflects 0.3% of the light power in the direction of the sensor's optical system. The measured optical response value ("MIN") in this case is 12 * 100 * 0.003 = 3.6 [AU] * μm 2 ]. In the second orientation relative to the sensor, the average energy density of the light beam in which the particles are present is 12 [AU], and the particle area is 100 μm². 2The particles reflect 0.1% of the light power in the direction of the sensor's optical system. The measured optical response value ("MIN") is 12 * 100 * 0.001 = 1.2 [AU * μm 2 ]

[0059] When calculating the ratio of the optical response of the particles at the second measurement position to the first measurement position for the first particle orientation, the result is 3.6 / 29.4 = 0.12. When calculating the ratio of the optical response of the particles at the second measurement position to the first measurement position for the second particle orientation, the result is 1.2 / 9.8 = 0.12.

[0060] This example demonstrates that particle size determination based on ratios is less sensitive to differences in the optical responsiveness of particles. In the following text, the calculation of the ratio between the second optical response and the first optical response is referred to as the "MIN / MAX ratio".

[0061] In Figure 7B, an irregularly shaped aerosol particle 730, larger than particle 710 in Figure 7A, is present in the laser beam, and the measurement is performed at the first position 740. In the first orientation relative to the sensor, the average energy density of the light beam in which the particle exists is 75 [AU], and the particle area is 1,600 μm². 2 The particles reflect 0.3% of the light power in the direction of the sensor's optical system. The amplitude of the measured optical response ("MAX") is 75 * 1,600 * 0.003 = 360 [AU * μm 2 The optical response of the particle is also measured at the second position 742. In the first orientation relative to the sensor, the average energy density of the light beam in which the particle is present is 20 [AU], and the particle area is 1,600 μm². 2 The particles reflect 0.3% of the light power in the direction of the sensor's optical system. The amplitude of the measured optical response ("MIN") is 20 * 1600 * 0.003 = 96 [AU * μm 2The result is ]. Calculating the MIN / MAX ratio of the particle's optical response at the second measurement position and the first measurement position, the result is 96 / 360 = 0.27. As the particle size increases, the particle collects energy from both optical beams, and the MIN / MAX ratio increases.

[0062] For very small particles, the MIN / MAX ratio value will be a small number. As particle size increases, the MIN / MAX ratio value increases. The MIN / MAX ratio value can range from 0.0 (smaller particles) to 1.0 (larger particles). The MIN / MAX ratio value is size-dependent, and a calibration look-up table (LUT) can be created to estimate particle size based on the identified MIN / MAX ratio values.

[0063] If the optical response generated by an aerosol particle is at position 1, but the optical response at position 2 is below the noise level, the particle size determination algorithm will use a special calibration lookup table to estimate the particle size, using the optical signal response amplitude and the duration of the below-noise level signal between the two peaks. The duration of the below-noise level signal must be corrected based on the airspeed value.

[0064] The airspeed value can be provided by other aircraft systems or by measuring the duration between two optical response signal peaks. The duration of the optical response signal can be measured as the number of optical signal digital samples. The number of digital samples depends on the airspeed, with lower numbers of digital samples measured at higher airspeeds. Knowing the airspeed (provided to the particulate sensor by other vehicle systems) allows for resampling (signal upsampling, signal downsampling, signal interpolation) of the particle's optical response, making it independent of airspeed.

[0065] A resampling method can be used to make the optical response independent of airspeed. Assume the sensor supports an aircraft airspeed range of 50–300 meters per second (mps). Also assume the sensor's digital sampling frequency is 50 MHz. For an airspeed of 50 meters per second, the particle position relative to the vehicle shifts by 1 micron between the two resulting digital samples (distance = 50 mps). * (20 ns). At an airspeed of 300 meters / second, the particle position relative to the vehicle position shifts by only 6 microns between the two resulting digital samples (distance = 300 mps). * (20 ns). The sensor can use resampling methods (upsampling / downsampling / interpolation) to make the optical response of particles independent of air velocity. For example, if an optical response of 300 m / s is upsampled 6 times, an optical response with the same number of digital samples as an optical response of 50 m / s is provided.

[0066] Alternatively, if it is not necessary to measure the peak shape of the optical response, a correction factor is applied to the duration of the measured optical response peak.

[0067]

number

[0068] Figure 8 shows that the light source generates two optical beams, each of which has a 50-micron 1 / e 2Graph 800 shows a scenario in which two beams have a Gaussian width and are separated by a distance of 50 microns. Graph 800 shows the normalized optical response of an ice crystal with a cubic shape to the particle position relative to the two beams. From Graph 800, it can be seen that the MIN / MAX ratio depends on the particle size. This optical analysis suggests that the particle size can be estimated by analyzing the MIN / MAX ratio between the amplitude of the optical response and the minimum value between the peak centers of the two optical responses. From Graph 800, it can also be seen that as the particle size increases, the peak of the optical response is not generated precisely at the peak center of the light beam with a horizontal coordinate value of 0.0, but rather in its vicinity.

[0069] Figure 9 shows that the light source generates two light beams, each of which has a 50-micron 1 / e 2 Graph 900 shows a scenario in which two light beams with a Gaussian width are separated by a distance of 50 microns. Graph 900 shows the normalized optical response of the droplet-particle position with respect to the two light beams. From Graph 900, it can be seen that the MIN / MAX ratio depends on the particle size. This optical analysis suggests that the particle size can be estimated by analyzing the MIN / MAX ratio. From Graph 900, it can also be seen that as the particle size increases, the peak of the optical response is generated not precisely at the peak center of the light beam, but in its vicinity.

[0070] This multi-line particle size determination method, which uses a ratio signal, can reduce sensitivity to the optical responsiveness of particles; however, this method has several defined measurement errors. A single aerosol particle of a single size and shape can produce different MIN / MAX ratio values ​​depending on the orientation of the particle relative to the sensor. The ratio signal also depends on the particle shape, surface optical properties, and material optical properties.

[0071] The measurement accuracy of this multi-line particle size determination method using ratio signals can be improved by adding additional inputs to the particle size estimation algorithm. For example, the following parameters, namely identified particle type (water droplet, ice crystal, volcanic ash / sand / dust particles), optical response amplitude, peak duration, and other peak shape parameters such as symmetry and slope, can be used along with the MIN / MAX ratio value to estimate particle size with greater accuracy. Furthermore, the relative positions of each peak in the optical response, the values ​​of each optical response minimum between each peak, and the relative positions of each optical response minimum can be used. Rule-based systems, machine learning, or other data processing techniques can also be used to improve the accuracy of particle size determination.

[0072] Particle asymmetry can be determined by analyzing the dependence of the MIN / MAX ratio signal and the optical signal amplitude (MAX). Spherical particles exhibit a unique dependence of the MIN / MAX ratio signal and the optical amplitude signal (MAX), while higher variability in the MIN / MAX ratio and optical response amplitude (MAX) signals will be observed for asymmetric particles. Particle asymmetry analysis may also be used to determine additional information regarding possible particle shapes, which may be used to correct particle size estimates.

[0073] Figures 10A, 10B, and 10C illustrate the two-dimensional histogram data distribution of the MIN / MAX ratio and optical response peak amplitude (MAX) for water droplets, ice crystal cubes of size "AxAxA", and ice crystal blocks of size "AxAx3A". The first axis of the histogram represents the MIN / MAX ratio, and the second axis represents the optical response peak amplitude (MAX). The variance of the optical response amplitude for each histogram column (bin) of the MIN / MAX ratio is also calculated.

[0074] Figure 10A shows the simulated data distribution 1010 for a water droplet. Since the optical response is independent of its orientation relative to the sensor and its shape is always spherical, the measured distribution closely follows a single curve. Some variation may exist due to sensor measurement errors and noise. In the case of a water droplet, the dispersion is very small.

[0075] Figure 10B shows the simulated data distribution 1020 for ice crystals with a cubic shape. Analyzing the variance within each of the MIN / MAX ratio histogram bins clearly shows that the optical response peak amplitude (MAX) variance is higher than that for water droplets.

[0076] Figure 10C shows the simulated data distribution 1030 for ice crystals with a block shape. Because the particles are highly asymmetric, the dispersion within each of the MIN / MAX ratio histogram bins is higher than in the case of ice crystals with a cubic shape.

[0077] Therefore, variance analysis can be used to obtain additional information about particle asymmetry, which can then be used to enhance particle size estimations for ice crystals and volcanic ash / sand / dust particles. This approach requires statistical analysis. Therefore, a sufficient amount of particle measurements must be performed to obtain reliable statistics.

[0078] Figure 11 shows how additional adjacent light beams can be added to this system configuration. The first light beam 1110 is 1 / e of A 2 Having a width, the second light beam 1112 has a width of 1 / e² of A microns in its left region. 2 The width is 1 / e of B microns in the area to its right. 2 Having a width, the third light beam 1114 is 1 / e of B microns. 2 It has a width. The first and second light beams are separated by a distance of D microns. The second and third light beams are separated by a distance of E microns. The first MIN / MAX ratio can be calculated from the optical response in position (2) / (1). The second MIN / MAX ratio can be calculated from the optical response in position (4) / (5). The signal value of the first MIN / MAX ratio is 1 / e from which the second MIN / MAX ratio is calculated. 2 1 / e is smaller than the width. 2It is calculated from the width. Therefore, the first MIN / MAX ratio can be used to estimate the size of smaller particles, and the second MIN / MAX ratio can be used to estimate the size of larger particles.

[0079] In the scenario described in Figure 11, the energy density profile between the first and second optical beams is created in the same way as if both beams were made with the parameters of the first optical beam. The energy density between the second and third optical beams is created in the same way as if both beams were made with the parameters of the third optical beam. However, since the energy density of the second optical beam is not symmetrical and differs in the left and right regions, the optical response amplitude occurring near the center of the second optical beam results in a different amplitude compared to the first and third optical beams. Therefore, the amplitudes of the two consecutive responses are different, and the MIN / MAX ratio is valid only for the defined positions (2) and (1), (4) and (5).

[0080] Simulation example The following example demonstrates the determination of particle sizes with different optical responses using two beams. Note that the optical response of water droplets is significantly larger than that of gray particles. When water droplets and gray particles are the same size, the optical response of water droplets in one of the Gaussian peaks of the beam is, for example, 29.4 [AU]. * μm 2 The optical response of water droplets between the Gaussian peaks of the beam is, for example, 3.6 [AU]. * μm 2 Under the same conditions, the optical response of gray particles within the Gaussian peak is 13.4 [AU]. * μm 2 The optical response of gray particles between Gaussian peaks is 1.6 [AU]. * μm 2Based on the amplitude of the particle response, it is not possible to accurately distinguish the sizes of both particles. However, based on the MIN / MAX ratio of the optical response within the Gaussian peak and the optical response between the Gaussian peaks, the particle size can be accurately determined. In this example, the optical response ratio for the water droplet is 3.6 / 29.4=0.12, and the optical response ratio for the gray particle is 1.6 / 13.4=0.12. Therefore, this approach provides a reliable particle size determination method for different types of particles having the same size.

[0081] The transmittance of the sensor's optical window can be reduced by contamination from insects, dirt, and de-icing fluid. In some scenarios, the sensor is installed in the nose of an aircraft (due to high collection efficiency – boundary layer effect), but this also tends to collect insects, dirt, etc. The light power passing through the sensor's optical window can be reduced by approximately 20% due to dirt and insects present on the optical window.

[0082] The following example demonstrates determining particle size through a dirty optical window using two beams. In this example, the optical response of the water droplet through the clear window within one of the beam's Gaussian peaks is 29.4. The optical response of the water droplet through the clear window between the beam's Gaussian peaks is 3.6. The optical response of the water droplet through the dirty window within the Gaussian peak is 29.4. * 0.8 = 23.5, and the optical response of the water droplet-dirty window between the Gaussian peaks is 3.6. *0.8 = 2.9. Based on the amplitude of the particle response, different particle sizes can be obtained for the same size water droplets in the clear window and the contaminated window. However, the particle sizes in the clear and contaminated optical windows can be accurately determined based on the ratio of the optical response within the Gaussian peak to the optical response between the Gaussian peaks. In this example, the optical response ratio of the water droplet in the clear window is 3.6 / 29.4 = 0.12, and the optical response ratio of the water droplet in the contaminated window is 2.9 / 23.5 = 0.12. Therefore, this measurement method is resistant to contamination of the optical window. Specifically, in the case of water droplets, the amplitude and optical response ratio signals are deterministic, and therefore, any discrepancies between the data can be used to detect contamination of the optical window.

[0083] The following example shows how additional light beams can be added to this system configuration. The first light beam (left) is 50 microns 1 / e 2 It has a width, and the second light beam (center) has a 50 micron 1 / e² region to its left. 2 It has a width of 160 microns in its right region, and 1 / e 2 It has width. The third light beam (right) is 1 / e² of 160 microns. 2 It has width. The first and second light beams are separated by a distance of 50 microns. The second and third beams are separated by a distance of 160 microns. The first MIN / MAX ratio can be calculated from the optical response in position (2) / (1), and the second MIN / MAX ratio can be calculated from the optical response in position (4) / (5). (See Figure 11). The signal value of the first MIN / MAX ratio is 1 / e of 50 microns. 2 Since it is calculated from the width, 1 / e of 160 microns 2 This method may be more efficient for estimating the size of smaller particles than a second MIN / MAX ratio signal value calculated from the width of the light beam.

[0084] This multi-line measurement method for large particles Assume that the light beam has a Gaussian profile, and that the aerosol particle with the largest diameter is similar in size to or larger than the Gaussian width of the light beam. In such a scenario, the particle size may be considered large relative to the width of the light beam, and individual types of optical responses may not make the optical response linearly dependent on the light beam energy density profile.

[0085] This system utilizes multi-line optical beam profiles to reduce measurement errors caused by differences in the optical responsiveness of aerosol particles. Examples of such approaches are shown in Figures 7A and 7B. In these examples, each of the two optical beams is 1 / e² of 50 microns. 2 The two light beams have a Gaussian width and are separated by a distance of 50 microns. The Gaussian width and light beam separation values ​​are specified for illustrative purposes only, as both values ​​may differ in actual use cases.

[0086] Figure 12 shows that the light source generates two light beams, each of which has a 50-micron 1 / e 2Graph 1200 shows a scenario where two light beams are separated by a distance of 50 microns and have a Gaussian width. Ice crystal cubes with equivalent diameters of 50, 70, 100, and 150 microns have side lengths of 40, 56, 80, and 120 microns, and body diagonals of 70, 97, 140, and 209 microns. In this example, we selected specific ice crystal cube orientations that have only a single type of optical response. The optical response of such particles is shown on Graph 1200. When the particle is similar in size to the distance between the two Gaussian peaks, its optical response is produced using both light beams when the particle is between the two Gaussian peaks. Thus, the optical response is stronger between the two light beams than at the centers of each of the two light beams. Graph 1200 shows the optical response of ice crystal cubes, and it is clearly visible that as its equivalent diameter increases beyond 100 microns, only a single peak is produced by the particle. If a particle generates only a single peak, the particle size can be determined using only the optical response amplitude, optical response shape, and optical response duration.

[0087] Figure 13 shows that the light source generates two light beams, each of which has a 50-micron 1 / e 2Graph 1300 shows a scenario in which two light beams with a Gaussian width are separated by a distance of 50 microns. Large particles with multiple types of optical responses can produce complex optical responses that need to be analyzed by different approaches. Figure 13 shows the optical responses of water droplets with diameters of 50 to 100 microns. As the diameter of the water droplet increases, the types of optical responses become separated, and the optical response measured by the sensor differs from the energy density profile of the light beam. Since water droplets always have a spherical shape, each optical response shape produced can be compared to a reference water droplet of a specific diameter stored in a database such as database 142 (Figure 1). Therefore, in order to determine the water droplet diameter, it is necessary to find similarity between the measured optical signal and the reference optical signal. In this case, a pattern matching method can be used, or a comparison of optical response parameters can be used. For example, parameters such as the number of peaks in the optical response, the amplitude ratio of each peak, the optical response duration, and the optical response shape can be used.

[0088] Ice crystals and volcanic ash / sand / dust particles exhibit multiple types of optical responses, and compared to water droplets, the intensity of individual responses varies depending on particle size, shape, orientation, surface optical properties, and material optical properties. Therefore, the optical responses caused by ice crystals and ash / sand / dust particles produce multiple different optical response shapes. This is illustrated in Figure 14 and Graph 1400. This exemplary scenario involves 1 / e of 50 microns. 2 This test involved hexagonal cross-ice crystals with an equivalent diameter of 125 microns passing through two light beams with Gaussian width, separated by a distance of only 50 microns. It was clearly observed that there were three optical response peaks, and therefore, the MIN / MAX ratio method could not be used, requiring a more complex signal analysis.

[0089] High-level algorithms Figure 15 is a flowchart of a method 1500 for particle size determination according to one embodiment. Method 1500 may be implemented, for example, by a particle size determination algorithm 132 in system 100 (Figure 1). Method 1500 includes transmitting two light beams from a light source on the vehicle to an inspection area outside the vehicle (block 1510), collecting a portion of scattered or reflected light from the inspection area based on the transmitted light beams (block 1512), and detecting the optical response of the collected portion of reflected or scattered light from the inspection area (block 1514).

[0090] The optical response peak shape is analyzed, and specifically, the data processing algorithm identifies whether the optical response has two peaks and a single minimum value (block 1516), and whether the amplitudes of the two peaks do not differ by more than a defined threshold (block 1518). The maximum absolute difference may be, for example, 20%. If the answer to both of the preceding statements in blocks 1516 and 1518 is true (yes), the algorithm determines that the particle size is 1 / e of the light beam. 2 Having identified that it is small compared to the width, method 1500 then proceeds to execute block 1520 (described below). If either of the previous statements in blocks 1516 and 1518 is false (no), the algorithm determines that the particle size is 1 / e of the light beam. 2 Having identified that it is equal to or greater than the width, method 1500 then proceeds to perform block 1530 (described below).

[0091] Particle size is 1 / e 2If it is determined that the width is smaller than the light beam width, method 1500 further includes determining a first optical response value of the particle in the inspection area when the particle is located near the center of one of the light beams (block 1520), determining a second optical response value of the particle when the particle is located between two light beams (block 1522), identifying a ratio value between the first optical response value of the particle and the second optical response value of the particle (block 1524), and estimating the size of the particle based on the identified ratio value (block 1526).

[0092] Particle size is 1 / e of the light beam 2 If it is determined that the width is similar to or greater than the width, method 1500 further includes correcting the optical response duration using the airspeed value and calculating the peak shape parameter (block 1530). This makes it possible to compare the measured peak shape with reference water droplets, ice crystals, and volcanic ash / sand / dust particles stored in the database, and the particle size is estimated using the closest match with a pattern matching algorithm (block 1532).

[0093] The data generated by block 1526, namely the MIN / MAX ratio and the estimated particle size, can be used as input to a computer model, and other parameters such as the identified particle type, peak amplitude signal, and airspeed-corrected optical response duration can also be analyzed. The computer model (including expert systems, probabilistic models, or machine learning systems) operates to determine the most likely particle size.

[0094] The data generated by blocks 1530 and 1532, namely the identified reference optical response match, estimated particle size, and parameters describing the optical response peak shape, can be used as input to a computer model, and other parameters such as the identified particle type, peak amplitude signal, and airspeed-corrected optical response duration can also be analyzed. The computer model (including expert systems, probabilistic models, or machine learning systems) operates to determine the most likely particle size.

[0095] Multiline laser generation There are various methods for creating a laser beam profile having at least two beams, where at least two Gaussian beam profiles are adjacent to each other. For example, Figure 16 shows a system 1600 for creating a two-line laser beam profile using polarization beam coupling of optical beams. System 1600 includes a first laser module 1610 configured to emit a horizontally polarized first beam 1612 and a second laser module 1620 configured to emit a vertically polarized second beam 1622. System 1600 also includes a mirror 1630 and a polarization combiner 1632.

[0096] During operation, the first laser module 1610 transmits the first beam 1612 to the mirror 1630, which reflects the first beam 1612 to the polarizing combiner 1632, and the second laser module 1620 transmits the second beam 1622 to the polarizing combiner 1632. The polarizing combiner 1632 reflects the first beam 1612 toward the sampling volume and transmits the second beam 1622 toward the sampling volume. The output beam profile of the polarizing combiner 1632 includes a two-line laser beam profile.

[0097] The multi-line laser beam profile may also be created by other mechanisms, such as by the use of diffraction and refractive optical systems.

[0098] In further alternative embodiments, the laser beam profile having multiple beams may be created using a dedicated beam shaping machine to form various laser beam patterns, such as periodic patterns or complex patterns, in order to provide extended particle size range detection.

[0099] In another alternative embodiment, the optical beam profile having multiple beams may be created using a light-emitting diode (LED) with a dedicated focusing optical system, thereby avoiding the effects of optical interference and speckle distortion in the measurement volume and sensor optical system.

[0100] The processing units and / or other computing devices used in the systems and methods described herein may be implemented using software, firmware, hardware, or an appropriate combination thereof. The processing units and / or other computing devices may be complemented by or incorporated into application-specific integrated circuits (ASICs) or field-programmable gate arrays (FPGAs). In some implementations, the processing units and / or other computing devices may communicate via transceivers with other computing devices outside the navigation system, such as those associated with a management system, or with computing devices associated with other subsystems controlled by the management system. The processing units and / or other computing devices may also include, or function by, software programs, firmware, or other computer-readable instructions for performing the various process tasks, calculations, and control functions used in the methods and systems described herein.

[0101] The methods described herein can be implemented by computer executable instructions, such as program modules or components, which are executed by at least one processor or processing unit. Generally, program modules include routines, programs, objects, data components, data structures, algorithms, and the like, which perform a particular task or implement a particular abstract data type.

[0102] Instructions for performing various process tasks, calculations, and the generation of other data used in the operation of the methods described herein can be implemented in software, firmware, or other computer-readable instructions. These instructions are typically stored in a suitable computer program product, including a computer or processor-readable medium used for storing computer-readable instructions or data structures. Such a computer-readable medium can be any available medium that can be accessed by a general-purpose or specialized computer or processor, or any programmable logic device.

[0103] Suitable computer or processor-readable storage media include, for example, non-volatile memory devices including semiconductor memory devices such as random access memory (RAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), or flash memory devices; magnetic disks such as internal hard disks or removable disks; optical storage devices such as compact discs (CDs), digital versatile discs (DVDs), and Blu-ray discs; or any other media that can be used to carry or store desired program code in the form of computer executable instructions or data structures. [Examples]

[0104] Exemplary Embodiments Embodiment 1 includes a system comprising a particulate sensor unit for a vehicle, the particulate sensor unit comprising: at least one light source configured to direct at least two light beams toward an inspection area outside the vehicle, wherein portions of the light beams overlap; an optical detector configured to capture scattered or reflected light from aerosol particles in the inspection area passing through the at least two light beams; and a processor operably communicating with the optical detector, the processor hosting a program module having instructions executable by the processor for carrying out a particle size determination method for aerosol particles in the inspection area, the method comprising detecting the optical response of scattered or reflected light from the inspection area, and if the detected optical response has two peaks, the method comprising determining a first optical response value of a particle when located near the center of one of the light beams; determining a second optical response value of a particle when located between the light beams; identifying a ratio value between the first optical response value of a particle and the second optical response value of a particle; and estimating the size of a particle based on the identified ratio value.

[0105] Example 2 includes the system of Example 1, and if the detected optical response has two peaks, particle size estimation is performed using a calibration lookup table.

[0106] Example 3 comprises the system of either Example 1 or 2, wherein each of the light beams has a flat-top profile in one axis and a Gaussian profile in the vertical axis.

[0107] Example 4 includes any of the systems from Examples 1 to 3, wherein at least two light beams create a multi-line laser pattern, and each line is parallel to the others.

[0108] Example 5 includes any of the systems from Examples 1 to 4, and the air velocity in the inspection area is calculated from the particle transition time between the two light beams.

[0109] Example 6 includes any system from Examples 1 to 5, and a two-dimensional histogram is generated, the first axis of the histogram representing the optical response ratio signal (MIN / MAX ratio), where MIN is the minimum optical response between two amplitude peaks and MAX is the optical response peak amplitude, the second axis of the histogram representing the optical response peak amplitude, and the variance of the optical response peak amplitude for each histogram column of the MIN / MAX ratio is calculated.

[0110] Example 7 includes the system of Example 6, where the dispersion of each histogram column is compared to a reference dispersion value for water droplets, ice crystals of multiple shapes, or volcanic ash / sand / dust particles of multiple shapes. Based on the difference between the measured dispersion and the expected dispersion for each particle type, the system generates probabilities for each particle type and its shape, determining the most likely particle type and its shape.

[0111] Example 8 includes the system of Example 7, wherein the processor uses the MIN / MAX ratio and additional signal parameters as input to a computer model including an expert system, a probabilistic model, or a machine learning system, the additional signal parameters including optical response amplitude, corrected optical response duration, optical response symmetry, estimated particle type, or estimated particle shape, and the computer model operates to determine the most likely particle type.

[0112] Example 9 includes any system from Examples 1 to 8, and if the detected optical response has a number of peaks different from 2, or if the amplitude difference between two peaks differs by a greater than defined threshold, a particle size analysis method is performed, which includes correcting the duration of the optical response peaks based on the airspeed of the vehicle, performing an optical response signal analysis in which the amount of scattered or reflected light from the particle is analyzed over time, and determining the size of the particle based on a comparison of the optical response signal parameters with a reference optical response stored in a sensor database.

[0113] Example 10 includes the system of Example 9, wherein the optical response signal parameters are calculated and include the corrected duration of the optical response, the amplitude of each optical response peak, the relative position of each optical response peak, the minimum value between each amplitude, the relative position of each optical response minimum, the symmetry of the optical response, or the gradient of the optical response.

[0114] Example 11 includes the system of Example 10, wherein the optical response signal parameters are compared to a reference optical response stored in a sensor database by determining the particle size using an expert system or machine learning algorithm.

[0115] Example 12 comprises any system from Examples 1 to 11, wherein three or more light beams are emitted from at least one light source, the light beam profiles have different widths, the light beams do not have to be symmetrical in the direction of airflow, the particle size is estimated from the signal ratio between the maximum and minimum for each of two adjacent light beams, the first particle size range of the particles is estimated using a first calibration lookup table and a first MIN / MAX ratio value calculated when the particles pass between the first and second light beams, and the second particle size range of the particles is estimated using a second calibration lookup table and a second MIN / MAX ratio value calculated when the particles pass between the second and third light beams.

[0116] Example 13 includes the system described in any of Examples 1 to 12, wherein the vehicle is an aircraft.

[0117] Example 14 includes transmitting multiple light beams from a light source on the vehicle to an inspection area outside the vehicle; collecting a portion of scattered or reflected light from the inspection area based on the transmitted light beams; detecting the optical response of the collected portion of scattered or reflected light from the inspection area to determine whether the detected optical response has at least two peaks; if the detected optical response has at least two peaks, determining a first maximum optical response value of a particle in the inspection area; determining a first minimum optical response value of a particle; identifying a ratio value between the first maximum optical response value of a particle and the first minimum optical response value of a particle; and estimating the size of a particle based on the identified ratio value.

[0118] Example 15 includes the method of Example 14, wherein if the detected optical response has two peaks, particle size estimation is performed using a calibration lookup table.

[0119] Example 16 comprises the method of either Example 14 or 15, and further comprises generating a two-dimensional histogram having a first axis of optical response ratio signals (MIN / MAX ratio) and a second axis of optical response peak amplitudes, where MIN is the minimum optical response between two amplitude peaks and MAX is the optical response peak amplitude, and calculating the variance of the optical response peak amplitudes for each column in the histogram of the MIN / MAX ratio.

[0120] Example 17 comprises the method of Example 16, further comprising comparing the dispersion of each histogram series with a reference dispersion value for water droplets, ice crystals of multiple shapes, or volcanic ash / sand / dust particles of multiple shapes, and generating a probability of each particle type and its shape based on the difference between the measured dispersion and the expected dispersion of each particle type, thereby determining the most likely type of particle and its shape.

[0121] Example 18 comprises any of the methods of Examples 14 to 17, wherein the particles include water droplets, ice crystals, volcanic ash, sand, or dust.

[0122] Example 19 comprises any of the methods of Examples 14 to 18, wherein the vehicle is an aircraft.

[0123] The present invention may be embodied in other specific forms without departing from its essential features. The embodiments described are to be considered in all respects only as illustrative and not limiting. Accordingly, the scope of the present invention is indicated by the appended claims rather than by the foregoing description. All modifications within the meaning and equivalent scope of the claims shall be encompassed within those scopes.

Claims

1. It is a system, A particulate sensor unit for vehicles, At least one light source configured to direct at least two light beams toward an inspection area outside the vehicle, wherein portions of the light beams overlap each other, An optical detector configured to capture scattered or reflected light from aerosol particles in the inspection area passing through at least two of the aforementioned light beams, A particulate sensor unit for a vehicle comprises a processor that is operably communicating with the optical detector, The processor hosts a program module having instructions executable by the processor in order to carry out a particle size determination method for aerosol particles in the inspection area, and the method is This includes detecting the optical response of scattered or reflected light from the inspection area, If the detected optical response has two peaks, the method is as follows: Determining a first optical response value of a particle located near one of the centers of the aforementioned light beam, Determining the second optical response value of the particle when it is located between the two light beams, Identifying the ratio value between the first optical response value of the particle and the second optical response value of the particle, A system comprising estimating the size of the particles based on the identified ratio values.

2. A two-dimensional histogram is generated, the first axis of the histogram representing the optical response ratio signal (MIN / MAX ratio), where MIN is the minimum optical response between two amplitude peaks and MAX is the optical response peak amplitude, and the second axis of the histogram representing the optical response peak amplitude. The variance of the optical response peak amplitude for each histogram column of the MIN / MAX ratio is calculated. The dispersion of each histogram column is compared to the reference dispersion value of water droplets, ice crystals of multiple forms, or volcanic ash / sand / dust particles of multiple forms. The system according to claim 1, wherein, based on the difference between the measured dispersion and the expected dispersion for each particle type, the system generates probabilities for each type of particle and its shape, and determines the most likely type of particle and its shape.

3. Transmitting multiple light beams from a light source on the vehicle to an inspection area outside the vehicle, Based on the transmitted light beam, a portion of the scattered or reflected light from the inspection area is collected, The optical response of the collected portion of scattered or reflected light from the inspection area is detected, and it is determined whether the detected optical response has at least two peaks. If the detected optical response has at least two peaks, the first maximum optical response value of the particles in the inspection area is determined. To determine the first minimum optical response value of the particle, Identifying the ratio value between the first maximum optical response value of the particle and the first minimum optical response value of the particle, A method comprising estimating the size of the particles based on the identified ratio value.

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