CN110914719A

CN110914719A - Pneumatic instrument and method

Info

Publication number: CN110914719A
Application number: CN201880047451.7A
Authority: CN
Inventors: 川口見作; 丹野嘉信; 黃德欽
Original assignee: National University of Singapore
Current assignee: National University of Singapore
Priority date: 2017-08-01
Filing date: 2018-07-30
Publication date: 2020-03-24
Anticipated expiration: 2038-07-30
Also published as: WO2019027367A1; CN110914719B; JP2020530114A; SG11202000257VA

Abstract

The present disclosure generally relates to a pneumatic instrument (100) and method (200). A pneumatic instrument (100) comprises: a base (102); a plurality of pressure sensors (104) distributed on the base (102), each pressure sensor (104) representing a sensor location and configured to measure a set of atmospheric pressure values at the respective sensor location; a gimbal assembly coupled to the base (102) for horizontally holding the pressure sensor (104); and a processor (106) communicatively linked to the pressure sensor (104), the processor (106) configured for determining an atmospheric pressure profile at the sensor location based on the set of measured atmospheric pressure values, the atmospheric pressure profile comprising a pressure gradient directed horizontally along the sensor location.

Description

Pneumatic instrument and method

Technical Field

The present disclosure relates generally to a pneumatic instrument and method. More specifically, the present disclosure describes various embodiments of a barometric pressure instrument and a barometric pressure measurement method for determining a pressure gradient and a barometric pressure profile based on a set of measured barometric pressure values.

Background

Our daily activities are often affected by the weather conditions of the day, and we can reduce the risk of activity interruption by predicting the weather conditions. Weather forecasting is performed by calculating the probability of weather change based on current weather parameters, such as temperature, humidity, wind, cloud, rain, etc. Although weather parameters may be measured by various environmental sensors, these sensors cannot predict future weather conditions from the measured weather parameters. Other existing weather forecasting techniques rely on satellites (references [1], [2] and [3]) and weather stations to estimate weather conditions by measuring the distribution of atmospheric pressure.

The satellite is able to globally perceive weather conditions from images of visible light, infrared light, water vapor, and temperature. The atmospheric pressure can be estimated from the image. If the position information at the desired viewing position is known, e.g. latitude and longitude coordinates, the atmospheric pressure at the viewing position can be estimated by tracking the cloud referenced from the image. To effectively track the cloud, it is necessary to model the cloud flow and estimate the different types of clouds. Such simulation is very complicated and it is difficult to predict weather conditions in real time in every place. Furthermore, atmospheric pressure cannot be estimated at the observation location if there are not enough clouds for tracking. The satellite is also unlikely to provide real-time updates because the update interval for the images is about an hour.

Another method of estimating atmospheric pressure without tracking clouds is to use weather information from weather stations or stations located around the world (reference [6 ]). Measurement data from weather station sensors can be shared online and individuals can search for local weather information based on their location. However, the update intervals of the weather stations are not consistent and may not provide real-time updates. Furthermore, since the number of weather sensors placed at a seaside location is smaller than on continents, it is more difficult to acquire weather information at a seaside location.

Another method of predicting weather relies on Doppler radars (references [4] and [5 ]). Doppler radar uses ultrasound to measure wind speed and direction on a moving cloud, which is useful for estimating the distribution of atmospheric pressure. However, this method cannot estimate the wind behavior without clouds.

As mentioned above, some existing methods for weather forecasting are based on barometric pressure distributions estimated from satellite images or weather observations. These methods can estimate the barometric pressure distribution over a wide area, such as an entire city or state, or even globally. However, these methods are difficult to implement if the cloud cover in the satellite image is limited or needs to be updated in real time.

U.S. patent publication 20120084005 describes a weather change prediction information providing system that measures and processes barometric pressure data to calculate a barometric pressure gradient vector. The system requires three or more barometric pressure measurement devices to be placed at different locations in the local area, and separated by hundreds of meters. Therefore, the system needs to span a large network in which the atmospheric pressure measurement device is provided, thereby limiting the practical application of the system.

Accordingly, it is desirable to provide an improved pneumatic apparatus and method to address or mitigate at least one of the above-mentioned problems and/or disadvantages.

Disclosure of Invention

According to a first aspect of the present disclosure, there is a pneumatic instrument comprising: a base; a plurality of pressure sensors distributed on the base, each pressure sensor representing a sensor location and configured to measure a set of atmospheric pressure values at the respective sensor location; a gimbal assembly coupled to the base for horizontally holding the pressure sensor; and a processor communicatively linked to the pressure sensor, the processor configured for determining an atmospheric pressure profile at the sensor location based on the set of measured atmospheric pressure values, the atmospheric pressure profile comprising a pressure gradient directed horizontally along the sensor location.

According to a second aspect of the present disclosure, there is an air pressure measurement method performed by an air pressure instrument. The method comprises the following steps: holding a plurality of pressure sensors horizontally on a base of a barometer, the pressure sensors being distributed on the base and each pressure sensor representing a sensor location; measuring, by each pressure sensor, a set of atmospheric pressure values at each sensor location; and determining, by a processor communicatively linked to the pressure sensor, an atmospheric pressure profile at the sensor location based on the set of measured atmospheric pressure values, the atmospheric pressure profile including a pressure gradient directed horizontally along the sensor location.

An advantage of the present disclosure is that the pressure gradient and barometric pressure profile can be determined by a barometric instrument without the need for large weather systems, such as weather stations or satellite networks. Recent weather information for the local area of the barometer can be predicted by identifying weather conditions from the pressure gradient and barometric pressure profile of the local area, thereby helping local residents to better plan activities and potentially improve quality of life.

Accordingly, pneumatic pressure instruments and methods according to the present disclosure are disclosed herein. Various features, aspects and advantages of the present disclosure will become more apparent from the following detailed description of embodiments thereof, taken in conjunction with the accompanying drawings, by way of non-limiting example only.

Drawings

FIGS. 1A and 1B are diagrammatic views of a pneumatic instrument;

FIG. 2 is a flow chart of a method of air pressure measurement;

FIGS. 3A and 3B are graphical representations of experimental studies conducted in an indoor wind tunnel environment;

FIG. 4 is a graphical representation of an experimental study conducted in an outdoor environment;

FIG. 5A is a graphical representation of the atmospheric pressure values measured by a pneumatic instrument;

FIG. 5B is a graphical representation of sensor positions for a pneumatic instrument;

FIG. 5C is a graphical representation of the generation of a filtered atmospheric pressure value;

fig. 5D-5F are graphical representations of filtered atmospheric pressure values;

FIG. 6 is a graphical representation of a method for determining a pressure gradient and barometric pressure profile;

FIGS. 7A and 7B are graphical representations of patterns from experimental studies;

fig. 8A to 8C are illustrations of applications of the pneumatic instrument.

Detailed Description

In the present disclosure, a description of a given element or a consideration or use of a particular number of elements in a particular figure or reference thereto in a corresponding descriptive material may encompass the same, equivalent or similar elements or numbers of elements identified in another figure or the descriptive material associated therewith. Unless otherwise indicated, the use of "/" in the drawings or in the associated text should be understood to mean "and/or". Recitation of specific values or ranges of values herein are understood to include or be a recitation of approximate values or ranges of values.

For the sake of brevity and clarity, the description of the embodiments of the present disclosure is directed to pneumatic instruments and methods in accordance with the accompanying drawings. While aspects of the disclosure will be described in conjunction with the embodiments provided herein, it will be understood that they are not intended to limit the disclosure to these embodiments. On the contrary, the present disclosure is intended to cover alternatives, modifications, and equivalents of the embodiments described herein, which are included within the scope of the present disclosure as defined by the appended claims. Furthermore, in the following detailed description, specific details are set forth in order to provide a thorough understanding of the present disclosure. However, one of ordinary skill in the art, i.e., one of ordinary skill in the art, will recognize that the present disclosure can be practiced without the specific details and/or with numerous details resulting from combinations of aspects of particular embodiments. In many instances, well-known systems, methods, procedures, and components have not been described in detail so as not to unnecessarily obscure aspects of the embodiments of the present disclosure.

References to "one embodiment/example," "another embodiment/example," "some embodiments/examples," and "some other embodiments/examples," etc., indicate that the embodiment (s)/example(s) so described may include a particular feature, structure, characteristic, element, or limitation, but every embodiment/example need not necessarily include the particular feature, structure, characteristic, element, or limitation. Moreover, repeated use of the phrases "in one embodiment/example" or "in another embodiment/example" does not necessarily refer to the same embodiment/example.

In a representative or exemplary embodiment of the present disclosure, there is a pneumatic instrument 100 as shown in fig. 1A and 1B. In general, the barometric pressure instrument 100 is a scientific device or tool for obtaining measurements related to atmospheric pressure. The pneumatic instrument 100 includes a base 102 and a plurality of pressure sensors 104 distributed on the base 102. Thus, the base 102 provides a support body for supporting the pressure sensor 104. Each pressure sensor 104 represents a sensor location and is configured to measure a set of atmospheric pressure values at the respective sensor location.

The pneumatic instrument 100 also includes a gimbal assembly coupled to the base 102 for horizontally holding the pressure sensor 104. The gimbal assembly includes a set of gimbals rotatably or pivotably coupled to the base 102. As used herein, a gimbal is defined as a pivoting structure that allows an object to rotate about a single axis. The base 102 and the gimbal assembly may be angularly movable relative to each other such that the base 102 may be held or stabilized horizontally, i.e., held in a horizontal orientation at a common altitude, when the pneumatic instrument 100 is manipulated or moved. As will be readily understood by those skilled in the art, the base 102 supporting the pressure sensor 104 is weighted to facilitate the base 102 remaining in a horizontal orientation. Optionally, the air pressure apparatus 100 includes a cover, such as a waterproof cover, attached to the base 102 for protecting the pressure sensor 104 from weather elements, such as rain.

The pneumatic instrument 100 also includes a processor 106 communicatively linked to the pressure sensor 104. The processor 106 is configured for determining an atmospheric pressure profile at the sensor location on the base 102 based on the set of measured atmospheric pressure values. The atmospheric pressure profile includes a pressure gradient on the base 102 that is directed horizontally along the sensor location. In particular, the pressure gradient is directed horizontally across a distribution of sensor locations represented by the plurality of pressure sensors 104, and the pressure gradient may or may not coincide with one or more sensor locations.

Referring to fig. 2, there is a barometric pressure measurement method 200 performed by the barometric pressure instrument 100. The method 200 includes the step 202 of holding the plurality of pressure sensors 104 horizontally on the base 102. As described herein, the pressure sensors 104 are distributed on the base 102, each pressure sensor 104 representing a sensor location, and the maintaining is accomplished by a gimbal assembly. The method 200 also includes the step 204 of measuring a set of atmospheric pressure values at respective sensor locations by each of the pressure sensors 104. The method 200 further includes a step 206 of determining, by the processor 106 communicatively linked to the pressure sensor, an atmospheric pressure profile at the sensor location based on the set of measured atmospheric pressure values, wherein the atmospheric pressure profile includes a pressure gradient directed horizontally along the sensor location on the base 102. Specifically, the atmospheric pressure distribution is determined by estimation from the pressure gradient. The processor 106 includes suitable logic/algorithms for performing the steps of the method 200 and is responsive to non-transitory instructions operated on or executed by the processor 106.

In the embodiment shown in fig. 1A and 1B, the pressure sensors 104 are distributed on the base 102 in an ordered arrangement, such as an array. The array has a plurality of rows and a like plurality of columns. Specifically, 25 pressure sensors 104 are arranged in 5 rows and 5 columns. In another embodiment, the pressure sensors 104 may be arranged differently, such as in a rectangular array having a different number of rows and columns. In another embodiment, the pressure sensors 104 may be arranged in a circular array, with the pressure sensors 104 positioned radially outward from a central location. In some other embodiments, the pressure sensors 104 are randomly distributed on the base 102. Those skilled in the art will appreciate that the number and arrangement of the pressure sensors 104 affects the accuracy of the pressure gradient of the barometric pressure profile determined based on the set of measured barometric pressure values. The number and placement of the pressure sensors 104 on the base 102 may be adjusted according to the accuracy required.

It is known that atmospheric pressure at an altitude is the pressure exerted by the weight of air in the atmosphere above the altitude. Atmospheric pressure varies from region to region. The gas flow descends in a region of higher atmospheric pressure (high-pressure region) and ascends in a region of lower atmospheric pressure (low-pressure region). The airflow or wind direction between the high pressure area and the low pressure area depends on the altitude, and the wind blows at different heights occur simultaneously. For example, on the ground, air flows from a high pressure area to a low pressure area, while at higher altitudes, air flows in the opposite direction, i.e., from the low pressure area to the high pressure area. In addition, air flow at moderate altitudes is complex and exhibits different behaviors.

The atmospheric pressure decreases from the high pressure region to the low pressure region, and the rate of decrease is represented by the pressure gradient. The pressure gradient causes the wind to be generated, and the steeper the pressure gradient, the stronger the wind. In addition, the direction of the wind can be estimated from the pressure gradient. Although wind is generated by a pressure gradient, wind does not affect atmospheric pressure. Thus, barometric instrument 100 may be used in high wind conditions or in still air to determine a pressure gradient and barometric pressure profile based on a set of measured barometric pressure values. The pressure gradient and barometric pressure profile at the sensor location represented by pressure sensor 104 may be analyzed to predict recent weather information in the local area where barometric pressure tool 100 is located.

In the embodiment shown in fig. 1A and 1B, the pneumatic instrument 100 has 25 pressure sensors 104 arranged in an array of 5 rows and 5 columns. Ideally, the type of pressure sensor 104 should be sensitive to small changes in atmospheric pressure. A non-limiting example of a type of pressure sensor 104 is an MPL3115a2 type or model. The MPL3115a2 pressure sensor 104 may measure in the range of 20kPa to 110kPa with a relative accuracy of ± 50Pa and a resolution of 1.5 Pa. Because the MPL3115a2 pressure sensor 104 measures atmospheric pressure by piezoresistive effect, there may be some noise between-400 Pa and 400 Pa. The MPL3115a2 pressure sensor 104 may be capable of measuring other parameters such as temperature and altitude.

Each pressure sensor 104 represents one sensor location on the base 102 and may include an aperture 108 at each sensor location. The pressure sensors 104 are aligned with the apertures 108, and each aperture 108 may be coincident with or offset from the center of the respective pressure sensor 104. Each pressure sensor 104 has dimensions of about 3mm by 5mm, and the spacing between pressure sensors 104 is about 5.5 mm. An array of 25 pressure sensors 104 is arranged over an area of approximately 25mm by 27mm in size. Referring to fig. 1A, a pneumatic instrument 100 is shown that is small enough to be a hand-held instrument and/or a wearable instrument, for example, worn on a watch device, as compared to the hand.

The pressure sensor 104 transmits a set of measured atmospheric pressure values over an inter-integrated circuit (I2C) computer bus. In one embodiment, the method 200 includes a further step of repeating the measurement process of the set of atmospheric pressure values at predefined intervals. For example, pressure sensor 104 measures a set of atmospheric pressure values at predetermined intervals of 400ms (milliseconds), which may be adjusted on barometric instrument 100. The processor 106 takes about 0.6ms to receive the set of atmospheric pressure values measured by one pressure sensor 104, and a total of about 12ms to receive and aggregate the set of atmospheric pressure values measured by all 25 pressure sensors 104. Thus, the processor 106 collects a set of all measured atmospheric pressure values over 400ms before the pressure sensor 104 repeats the measurement.

Several experimental studies were performed to evaluate the performance of the pneumatic instrument 100 and method 200. As shown in fig. 3A, a first experimental study was conducted in an indoor wind tunnel setup 300 and, as shown in fig. 4, a second experimental study was conducted in an outdoor environment setup 400. Indoor wind tunnel setting 300 presents a simulated environment for this evaluation, while outdoor environment setting 400 presents actual conditions for use of air pressure instrument 100.

Referring to fig. 3A, an indoor wind tunnel arrangement 300 includes a wind tunnel 302 that generates an airflow or wind in an enclosed space to study the effects of the airflow through a pneumatic instrument 100 placed horizontally in the center of the wind tunnel 302. The benefit of the wind tunnel 302 is that wind and pressure conditions are stable. The wind tunnel 302 generates wind by a cooling fan 304 for the computer. A fan 304 is mounted at one end of the wind tunnel 302 and generates wind through the wind tunnel 302. The speed of the wind may be controlled by adjusting the speed of the fan 304, which in turn is dependent on the voltage supplied to the fan 304. Wind speed and direction were measured using a wind meter. The maximum wind speed reached by the fan 304 is 14 km/h.

For a first experimental study in an indoor wind tunnel setup 300, a fan 304 generates wind in a wind tunnel 302 at a wind speed of 12 km/h. No measurements were made during the initial period of 30 minutes to calibrate and stabilize the barometric pressure instrument 100. The atmospheric pressure value is then measured over a first period of 30s (seconds) after the initial period. After the first period of time, the wind speed dropped to 10km/h in an interval of 10 s. The atmospheric pressure value was then measured over a second period of 30s at a wind speed of 10 km/h. After the second period of time, the wind speed dropped to 8km/h in an interval of 10 s. The atmospheric pressure value was then measured over a third period of 30s at a wind speed of 8 km/h.

Fig. 3B shows a graph of a set of atmospheric pressure values averaged from all pressure sensors 104 during the first, second, and third time periods of the first experimental study. The vertical axis represents the atmospheric pressure value, and the horizontal axis represents the number of sets of average atmospheric pressure values. Each unit along the horizontal axis represents 10s, totaling 110s throughout the first experimental study. Assuming that the pressure sensor 104 measures every 400ms, the number of sets of atmospheric pressure values obtained is about 275. It can be seen that the atmospheric pressure values in each 30s period are similar. However, in the 10s interval during the wind speed reduction, the average atmospheric pressure value significantly increased. Thus, as the wind speed decreases, the atmospheric pressure value increases. When the wind speed is stable, the atmospheric pressure value remains stable. Although the presence of wind may affect the pressure sensors 104, this applies to all pressure sensors 104 because they are subjected to the same wind. Thus, the atmospheric pressure values measured by the pressure sensor 104 tend to be similar. From the first experimental study, it can be concluded that the pressure sensors 104 have similar sensor characteristics and do not differ significantly from each other, and that it is feasible to use the barometric pressure instrument 100 in an actual outdoor environment.

Referring to fig. 4, the outdoor environment setup 400 includes a table 402 having a size of 120cm × 120cm, and the air pressure instrument 100 is horizontally placed at the center of the table 402. The horizontal orientation of the pneumatic pressure instrument 100 on the table 402 is verified by the level. No other obstacles or objects on table 402 may cast a shadow on pressure sensor 104. A camera 404 is placed in front of table 402 to capture an image of the sky, and an anemometer 406 is placed on the ground near table 402 to measure the surrounding wind speed and direction. Camera 404 and anemometer 406 are positioned away from table 402 to avoid shadows from being cast on pressure sensor 104.

For the second experimental study in the outdoor environment setting 400, no measurements were taken to calibrate and stabilize the barometric pressure instrument 100 for an initial period of 30 minutes. The atmospheric pressure value was then measured over a first period of 30 minutes after the initial period. Meanwhile, during a first period of time, the camera 404 captures an image of the sky, and the anemometer 406 measures the surrounding wind speed and direction.

It is worth noting that there is data from the sky image and the surrounding wind speed and direction, which is not sufficient to accurately determine the pressure gradient and barometric pressure profile. In particular, the surrounding wind direction is opposite or different from the trajectory of the cloud motion. The moving direction of the cloud is different according to the different altitudes. Thus, it is difficult to determine the pressure gradient and barometric pressure profile from the data obtained by the camera 404 and anemometer 406. It was also determined from the first experimental study that any effects from ambient wind can be ignored as ambient wind affects all pressure sensors 104.

Fig. 5A shows a graph 500 of a set of raw atmospheric pressure values measured from all pressure sensors 104 during a first time period of a second experimental study. The vertical axis represents the atmospheric pressure value, and the horizontal axis represents the number of sets of atmospheric pressure values. Each unit along the horizontal axis represents 200s, and the entire course of the first experimental study amounted to a first period of 30 minutes. Assuming that the pressure sensors 104 measure every 400ms, the number of sets of atmospheric pressure values measured by each pressure sensor 104 is approximately 4500. Each of the 25 graphs 500 shows a set of raw atmospheric pressure values measured from a respective one of the 25 pressure sensors 104, and the graphs 500 have the same arrangement as the sensor locations on the base 102. As shown in fig. 5B, the sensor positions represented by the pressure sensor 104 are represented as S (x, y) cells from S (0,0) to S (4, 4). The graph 500 in fig. 5A represents the original set P (1) of original atmospheric pressure values.

When the second experimental study is conducted in the outdoor environment setting 400, the atmospheric pressure value is affected by actual weather conditions, such as atmospheric pressure changes, temperature, and humidity. These conditions introduce noise in the measured atmospheric pressure values. A smoothing filter is applied to filter and reduce/remove noise in the measured atmospheric pressure value. Thus, during use of the pneumatic instrument 100, step 206 of the method 200 includes generating a set of at least one set of atmospheric pressure values filtered from a set of measured atmospheric pressure values.

Fig. 5C shows an example of generating at least one set P (n) of atmospheric pressure values filtered from the measured set of atmospheric pressure values, i.e. from the original set P (1), where n is an integer from 2. Each group P (n), i.e. P (2), P (3), P (4), or even more, is generated from the original group P (1). For each group P (n), each set of atmospheric pressure values thereof is generated based on a set of multiple measured atmospheric pressure values of the original group P (1). Specifically, for each group P (n), each cell or set of atmospheric pressure values is the average of the n × n cells of the original group P (1). The cells of group P (n) are part of the n × n cells of the original group P (1). The S (i, j) cells in group P (n) can be calculated from the original group P (1) by the following formula.

Fig. 5D shows a graph 502 of a set of atmospheric pressure values for group P (2) generated from original group P (1). Each graph 502 shows a set of cell or atmospheric pressure values generated from 2 × 2 cells of the original set P (1). Each cell of group P (2) is generated from 4 cells of the original group P (1), such that group P (2) has in total 4 × 4 or 16 cells or a set of 4 × 4 or 16 atmospheric pressure values.

Fig. 5E shows a graph 504 of a set of atmospheric pressure values for group P (3) generated from original group P (1). Each graph 504 shows a set of cell or atmospheric pressure values generated from the 3 × 3 cells of the original set P (1). Each cell of group P (3) is generated from 9 cells of the original group P (1), such that group P (3) has in total 3 × 3 or 9 cells or a set of 3 × 3 or 9 atmospheric pressure values.

Fig. 5F shows a graph 506 of a set of atmospheric pressure values for group P (4) generated from original group P (1). Each graph 506 shows a set of cell or atmospheric pressure values generated from 4 × 4 cells of the original set P (1). Each cell of group P (4) is generated from 16 cells of the original group P (1), such that group P (4) has in total 2 × 2 or 4 cells or a set of 4 × 4 or 16 atmospheric pressure values.

Comparing the original group P (1) with the generated groups P (2) to P (4), it can be seen that each of the groups P (2) to P (4) has a set of atmospheric pressure values which is less than the original group P (1) of the set of measured atmospheric pressure values. In addition, the groups P (2) to P (4) are consecutive, and the first group has a larger set of atmospheric pressure values than the second group following the first group. Each set of atmospheric pressure values in the first and second sets is generated based on a first plurality of measured sets of atmospheric pressure values and a second plurality of measured sets of atmospheric pressure values, respectively, and wherein the first complex number is less than the second complex number. For example, the first group P (2) and the second group P (3) following the first group P (2) have sets of 16 and 9 atmospheric pressure values, respectively. Each set of atmospheric pressure values of the first group P (2) is generated based on a set of 4 measured atmospheric pressure values, and each set of atmospheric pressure values of the second group P (3) is generated based on a set of 9 measured atmospheric pressure values.

Referring to raw set P (1) and graph 500 in fig. 5A, it can be seen that the set of raw atmospheric pressure values measured in outdoor ambient setting 400 is irregular, while the atmospheric pressure values measured in indoor wind tunnel setting 300 are stable. Furthermore, statistical calculations on the graph 500 indicate that the minimum correlation coefficient between the S (0,0) cell and the other cells is 0.10. The set of irregular atmospheric pressure values of the original set P (1) is likely due to the effect of actual weather conditions, which introduce noise in the atmospheric pressure values.

The generated sets P (2) to P (4) have reduced or even eliminated the noise concentrated at their atmospheric pressure values, respectively, as can be seen in the

graphs

502, 504 and 506, respectively. Similar statistical calculations on

graphs

502, 504, and 506 indicate minimum correlation coefficients of 0.78, 0.94, and 0.98, respectively. After filtering the set of original atmospheric pressure values to reduce or even eliminate noise, the minimum correlation coefficient increases significantly, and the minimum correlation coefficient of each group P (2) to P (4) is significantly higher than the original P group (1). The high correlation coefficient indicates that each of the cells in groups P (2) to P (4) exhibit similar behavior to the first experimental study in the indoor wind tunnel setup 300. In repeated experimental studies, high correlation coefficients were further verified. Therefore, it would be feasible to use the barometric pressure instrument 100 in an actual outdoor environment to determine the pressure gradient and barometric pressure profile from the filtered barometric pressure values of groups P (2) to P (4).

Step 206 of the method 200 of determining an atmospheric pressure profile includes identifying a minimum value and a maximum value of a set of atmospheric pressure values for each of the groups P (2) to P (4) to determine a pressure gradient. In one embodiment, the pressure gradient is determined based on the set of minimum atmospheric pressure values and the set of maximum atmospheric pressure values for one of the groups (2) to P (4) since each of the groups P (2) to P (4) has a better correlation coefficient with respect to P (1). The barometric pressure profile is then determined by an estimation from the pressure gradient.

In another embodiment, all sets P (2) to P (4) are used to determine the pressure gradient and the barometric pressure profile. Specifically, in step 206, the determination of the pressure gradient includes determining an intermediate pressure gradient for each of the groups P (2) to P (4) based on the set of minimum atmospheric pressure values and the set of maximum atmospheric pressure values for each of the groups P (2) to P (4). The pressure gradient is then determined by the aggregation/combination of the intermediate pressure gradients of groups P (2) to P (4). For aggregation, various algorithms may be employed. For example, the pressure gradient may be determined by vector addition of intermediate pressure gradients. The barometric pressure distribution is then determined by an estimation from the resulting pressure gradient. The intermediate pressure gradient improves the accuracy of the resulting pressure gradient and barometric pressure profile, since more sets of barometric pressure values are considered.

A computerized method 600 implemented on the processor 106 for determining the pressure gradient and barometric pressure profile is described with reference to fig. 6. The method 600 comprises a first stage 602 of processing the original set P (1). Specifically, in the first stage 602, groups P (2) to P (4) are generated from the original group P (1), wherein each of the groups P (2) to P (4) has a set of atmospheric pressure values filtered out of a set of measured atmospheric pressure values of the original group P (1) to reduce/remove noise.

The method 600 includes a second stage 604 of determining an intermediate pressure gradient for the groups P (2) through P (4). Specifically, in the second stage 604, for each of the groups P (2) through P (4), the set of atmospheric pressure values is sorted. For each of the groups P (2) to P (4), a number of sets of minimum or lowest ranked atmospheric pressure values and a maximum or highest ranked atmospheric pressure value are determined. In one embodiment, for each of the groups P (2) to P (4), there is one set of minimum atmospheric pressure values and one set of maximum atmospheric pressure values. In another embodiment, there are different numbers of minimum and maximum sets for different groups P (2) to P (4). For a particular set p (N), a set of (N-N) minimum barometric pressure values and a set of (N-N) maximum barometric pressure values are identified, where N-5 corresponds to the number of rows/columns in the array of pressure sensors 104. Taking group P (2) as an example, a set of 3 lowest atmospheric pressure values and a set of 3 highest atmospheric pressure values are identified. Thereafter, for each of the groups P (2) to P (4), a minimum center position is calculated based on the sensor position corresponding to the set of lowest atmospheric pressure values, and a maximum center position is calculated based on the sensor position corresponding to the set of highest atmospheric pressure values. For each of the groups P (2) to P (4), the intermediate pressure gradient 110 is generated as a straight line vector from the maximum center position to the minimum center position.

The method 600 includes a third stage 604 of determining the pressure gradient 112. Specifically, in the third stage 604, the intermediate pressure gradients 110 of the sets P (2) through P (4) are aggregated/combined, such as by vector addition, to generate the pressure gradient 112. The barometric pressure profile is then determined by an estimation from the pressure gradient 112. The atmospheric pressure distribution is then represented by an image map 114 generated from the estimation of the pressure gradient 112. Pressure gradient 112 is shown on image map 114, with pressure gradient 112 pointing from the maximum center location of the cluster to the minimum center location of the cluster. Pressure gradient 112 and image map 114 may be analyzed for predicting recent weather information at the local area where barometric pressure instrument 100 is located.

A third experimental study was conducted to evaluate the performance of the pneumatic instrument 100 and method 200, and in particular to evaluate the accuracy of the pressure gradient 112. The third experimental study was conducted in two stages outdoors similar to the outdoor environment setup 400. In the first stage, two pneumatic instruments 100 are placed horizontally in the same orientation on the table, i.e. pointing in the same horizontal direction. In the second stage, the two pneumatic devices 100 are placed horizontally on the table in different orientations, i.e., pointing in different horizontal directions. The first and second phases are performed on different dates at the same location. The measurement of the atmospheric pressure value is repeated several times in both phases. The pressure gradients 112 from each pneumatic instrument 100 in each stage are then averaged.

Fig. 7A shows a pattern 700 from the first stage of the third experimental study. Fig. 7B shows the pattern 702 from the second phase of the third experimental study. Each of

patterns

700 and 702 shows

average pressure gradients

112a and 112b, respectively, determined from first and second pneumatic instruments 100a and 100 b. The

average pressure gradients

112a and 112b are shown relative to the forward axis 704. The

pressure gradients

112a and 112b from the first stage are directed at about 0 and 31.7, respectively, relative to the forward axis 704, thereby forming a 31.7 gap between the

pressure gradients

112a and 112 b. The

pressure gradients

112a and 112b from the second stage are directed at approximately 76.7 and 45, respectively, relative to the forward axis 704, thereby forming a 31.7 gap between the

pressure gradients

112a and 112 b.

For the first and second stages, the

pressure gradients

112a and 112b determined by the pneumatic instruments 100a and 100b, respectively, tend to approach each other with a gap or margin of error of about 30 °. Both pneumatic instruments 100a and 100b

exhibit pressure gradients

112a and 112b that are similar to each other regardless of whether the pneumatic instruments 100a and 100b are positioned in the same or different orientations. The results of the third experimental study show that the pressure gradient determined by the pneumatic instrument 100 is sufficiently accurate.

The pressure gradient determined by the barometer 100 via the method 200 is a weather condition calculated from an atmospheric pressure value measured by the pressure sensor 104 of the barometer 100. As evaluated in the second experimental study in the outdoor environment setting 400, the pressure gradient is neither a result of the characteristics of the pressure sensor 104 nor the wind effect. As described above, the pressure gradient is determined from a calculation performed on the measured atmospheric pressure value.

One possible way to improve the accuracy of the pressure gradient is to supplement the determined pressure gradient with a predefined threshold. Another way to improve accuracy is to further reduce the noise in the atmospheric pressure value. To achieve further noise reduction, more inventive components may be required in the pneumatic instrument 100. The pressure sensor 104 of the pneumatic instrument 100 measures the atmospheric pressure value by the piezoresistive effect causing noise. In the embodiments described above, a smoothing filter may be applied to compress, filter, and reduce/remove noise from the measured atmospheric pressure value. In some embodiments, one skilled in the art will readily appreciate that other methods may be used for noise reduction. Some non-limiting examples include fourier transform algorithms and expectation-maximization algorithms.

The accuracy of the pressure gradient may be affected by the performance of the individual pressure sensors 104, such as the shape and sensor location on the base 102. This accuracy may be improved by improving the quality of the barometer 100, and in particular the quality of the array of pressure sensors 104. For example, adjusting the sensor locations on the base 102, and the better accuracy achieved during the manufacturing process of distributing the pressure sensors 104 over the base 102, may improve the quality of the pneumatic instrument 100.

As described in various embodiments above, the pneumatic instrument 100 is configured to determine a pressure gradient and an atmospheric pressure profile by the method 200. Data associated with the location of the pneumatic instrument 100 and the pressure gradient and barometric pressure profile at that location may be stored on a memory or storage device of the pneumatic instrument 100 for monitoring and tracking. Alternatively or additionally, the data may be communicated from the pneumatic instrument 100 to a remote computer system for storage thereon.

The pressure gradient and barometric pressure profile are determined by a barometric instrument 100, and the barometric instrument 100 can be hand-held in size without the need for a large weather system, such as a weather station or a satellite network. Recent weather information in the local area of the barometric pressure instrument 100 can be predicted by identifying surrounding weather conditions from the pressure gradient and barometric pressure profile of the local area. In particular, the pressure gradient extends from a high pressure region to a low pressure region in a local region, and the pressure gradient has a midpoint that may be referred to as a boundary. The boundary movement means the change of the atmospheric pressure distribution at a local area, and the analysis of the boundary movement can estimate the progress of the change of the atmospheric pressure distribution. Predicting recent weather information helps local residents to better plan activities and potentially improve quality of life.

In one example, it is more difficult to form clouds in high pressure regions than in low pressure regions. Recent weather information can be predicted by analyzing the proportion and progress of the high pressure area and the low pressure area from the atmospheric pressure distribution change. Accordingly, the barometric pressure instrument 100 can predict whether the current weather conditions in the local area will be maintained or weather changes are expected. In another example, the pneumatic instrument 100 may detect a particular sign before a catastrophic weather, such as a cyclone/typhoon/hurricane/tornado, occurs. For typhoons, the typhoon center pressure is lowest and the typhoon cloud rotates around the center. Depending on the direction of rotation of the typhoon, the pressure gradient and the gap between the high-pressure area and the low-pressure area will vary accordingly. These particular patterns of changes can be seen on an image map representing the barometric pressure distribution. Barometric pressure instrument 100 may be able to estimate the occurrence of an impending typhoon earlier than current weather forecast systems.

The pneumatic instrument 100 may be used in various other applications. The gas pressure instrument 100 may include an attachment mechanism coupled to the gimbal assembly for attaching the gas pressure instrument 100 to, for example, a body of a micro-aircraft. In one example, the barometer 100 may be used as an anemometer or wind sensor. As the wind speed decreases, the atmospheric pressure value increases, as evaluated in the first experimental study in the indoor wind tunnel setup 300. This relationship may be extrapolated to configure barometer 100 as an anemometer or wind sensor for measuring wind speed and direction. Conventional ultrasonic wind sensors require more space for airflow between the sensors and are larger than the air pressure instrument 100. The pneumatic instrument 100 is small enough to be installed in a space-constrained location.

In another example with reference to fig. 8A, pneumatic instrument 100 may be used for paraglider maneuvers 800. Paraglider sports 800 involves the use of a paraglider 802 and a parachute 804 attached to paraglider 802. The flight of glider 802 relies on wind power and does not require a powered motor. One technique in paraglider sports 800 is to achieve soaring flight by utilizing the wind directed upwards. To maintain flight during the paraglider movement 800, the driver needs to find windy areas for the user or driver of the paraglider 802, which are difficult for a novice to find. Barometric instrument 100 can be used with glider 802 to determine a pressure gradient that helps estimate wind direction. The barometric instrument 100 can be attached to the glider 802 and can be aligned with the glider 802 such that the pressure gradient, and thus the wind direction, is determined relative to the glider 802.

Similar to a glider and referring to fig. 8B, the barometric instrument 100 can be attached to a flying drone 806, such as an airplane or quad/quad type unmanned flying machine. Flying drone 806 is an autonomous robot that can fly without human hand control. Flying drone 806 flies by utilizing wind instead of powered motors, which would be difficult to operate continuously to maintain flight. Flying with wind energy solves the problems associated with power motors, while the use of the pneumatic instrument 100 helps estimate wind direction to guide the flying drone 806. One benefit of using flying drones 806 is that smaller platforms or temporary base stations can be built under space constraints to launch flying drones 806 for various purposes. For example, the flying drone 806 may be configured to improve mobile contact during a disaster, for observing weather at sea or for spraying pesticides in fields in mountainous areas. The flying drone 806 may also be fitted with other components such as gyroscopic sensors and accelerometers to aid in its flight.

In another example with reference to fig. 8C, the barometric pressure instrument 100 may be used to estimate the location of the fire point or origin of the fire. A firefighter can wear a helmet 808 with the pneumatic pressure instrument 100 attached thereto. The pneumatic instrument 100 can be aligned with the helmet 808 to determine a pressure gradient relative to the helmet 808. Locating the origin or source in a building may be difficult with a camera because smoke in a fire can affect visibility. Although thermal sensors and/or thermal imagers may be used to help detect the source of the fire, it takes time to locate the source of the fire due to temperature changes caused by the discharge of the fire-extinguishing water. A fire can raise the ambient temperature and affect the atmospheric pressure. In particular, the hallway of the building had a similar structure to the wind tunnel 302 used in the first experimental study. In a similar manner, since the area around the fire has a high atmospheric pressure, the pneumatic instrument 100 can locate the area having the high atmospheric pressure. The barometric pressure instrument 100 can thus be used to estimate the location of a fire source in a building and help people avoid this location.

In the foregoing detailed description, embodiments of the present disclosure relating to pneumatic pressure instruments and methods are described with reference to the provided figures. The description of various embodiments herein is not intended to be indicative of, or limited to, the particular or specific teachings of the disclosure, but is merely illustrative of non-limiting examples of the disclosure. The present disclosure is directed to solving at least one of the mentioned problems associated with the prior art. Although only a few embodiments of the present disclosure have been disclosed herein, it will be apparent to those of ordinary skill in the art in view of this disclosure that various changes and/or modifications may be made to the disclosed embodiments without departing from the scope of the present disclosure. Accordingly, the scope of the present disclosure and the scope of the appended claims are not limited to the embodiments described herein.

Reference to the literature

[1] Bennett, j.j., cun, m. (7 months 1985.) middle atmosphere reference model derived from satellite data, international union of science, middle atmosphere program council, MAP handbook, volume 16, pages 47-85 (see N86-1281403-46) (volume 16, pages 47-85).

[2] Koffman, y.j., senddela, c. (1988) algorithm for atmospheric autocorrection of visible and near-infrared satellite images, international journal of remote sensing, 9(8),1357-1381.

[3] Petarov, l., and boy, J.P, (2004) study of atmospheric pressure loading signals in even long baseline interferometry geophysical research journal, solid earth, 109(B3).

[4] Kaning, m.l., chenille, a., hauch cohn, a., and porteuff, j. (1989) a doppler lidar for measuring wind in the middle atmosphere.

[5] Green, j.l., cover, k.s., and mao, prant, T.E, (1979) atmospheric measurements by uhf pulse doppler radar, IEEE science electronics, 17(4), 262-.

[6] Augusted, j.a., deluxe, j.j., and lang, C.N, (2000) SURFRAD-national surface radiation budget network for atmospheric research american society of meteorology, bulletin 81(10), 2341-.

Claims

1. A pneumatic instrument, comprising:

a base;

a plurality of pressure sensors distributed on the base, each pressure sensor representing a sensor location and configured to measure a set of atmospheric pressure values at the respective sensor location;

a gimbal assembly coupled to the base for horizontally holding the pressure sensor; and

a processor communicatively linked to the pressure sensor, the processor configured for determining an atmospheric pressure profile at the sensor location based on a set of measured atmospheric pressure values, the atmospheric pressure profile comprising a pressure gradient directed horizontally along the sensor location.

2. The instrument of claim 1, the determination of the barometric pressure profile comprising generating a set of at least one set of barometric pressure values filtered from a set of measured barometric pressure values.

3. The instrument of claim 2, wherein for each group, each set of atmospheric pressure values thereof is generated based on a set of multiple measured atmospheric pressure values.

4. An instrument according to claim 2 or 3, wherein each group has a set of atmospheric pressure values less than the set of measured atmospheric pressure values.

5. An instrument according to any one of claims 2 to 4, wherein the groups are consecutive and a first group has a greater set of atmospheric pressure values than a second group following the first group.

6. The instrument of claim 5, wherein each set of atmospheric pressure values of the first and second sets is generated based on a first plurality of measured sets of atmospheric pressure values and a second plurality of measured sets of atmospheric pressure values, respectively, and wherein the first complex number is less than the second complex number.

7. The instrument of any one of claims 2 to 6, the determination of the barometric pressure profile further comprising identifying a minimum and a maximum of a set of barometric pressure values for each group for determining the pressure gradient.

8. The instrument of claim 7, wherein the barometric pressure profile is determined by the pressure gradient determined based on a set of minimum barometric pressure values and a set of maximum barometric pressure values for one of the groups.

9. The instrument of claim 7, the determination of the pressure gradient comprising determining an intermediate pressure gradient for each group based on a set of minimum atmospheric pressure values and a set of maximum atmospheric pressure values in each group.

10. The apparatus of claim 9, wherein the atmospheric pressure profile is determined from a pressure gradient resulting from the polymerization of the intermediate pressure gradient.

11. An instrument as claimed in any one of claims 1 to 10 wherein said pressure sensors are distributed in an array on said base.

12. The instrument of any one of claims 1 to 11, further comprising an attachment mechanism coupled to the gimbal assembly for attaching the instrument to a body, wherein the instrument is alignable with the body such that the pressure gradient is determined relative to the body.

13. The apparatus of any one of claims 1 to 12, wherein the apparatus is a handheld apparatus and/or a wearable apparatus.

14. A method of barometric pressure measurement performed by a barometric instrument, the method comprising:

holding a plurality of pressure sensors horizontally on a base of the barometer, the pressure sensors being distributed on the base and each pressure sensor representing a sensor location;

measuring, by each pressure sensor, a set of atmospheric pressure values at each of the sensor locations; and

determining, by a processor communicatively linked to the pressure sensor, an atmospheric pressure profile at the sensor location based on a set of measured atmospheric pressure values, the atmospheric pressure profile including a pressure gradient directed horizontally along the sensor location.

15. The method of claim 14, the determining of the barometric pressure profile comprising generating a set of at least one set of barometric pressure values filtered from a set of measured barometric pressure values.

16. The method of claim 15, wherein for each group, each set of atmospheric pressure values thereof is generated based on a set of multiple measured atmospheric pressure values.

17. The method of claim 15 or 16, the determining of the barometric pressure profile further comprising identifying a minimum and a maximum of a set of barometric pressure values for each group for determining the pressure gradient.

18. The method of any of claims 15 to 17, the determining of the pressure gradient comprising determining an intermediate pressure gradient for each group based on a set of minimum atmospheric pressure values and a set of maximum atmospheric pressure values in each group.

19. The method of claim 18, wherein the atmospheric pressure profile is determined from a pressure gradient resulting from the polymerization of the intermediate pressure gradient.

20. The method of any of claims 14 to 20, further comprising repeating the measurement of the set of atmospheric pressure values at predefined intervals.