Method for Generating Eight Square Diagram for Environmental Noise Measurement

Abstract

The present application relates to a method for generating an eight-direction diagram for measuring environmental noise. During the process of the noise detection device rotating at a uniform speed for one circle, an azimuth acquisition device of the noise detection device is started to acquire multiple yaw angles, and a camera device of the noise detection device is controlled to shoot a video. After eliminating the angle jump of the yaw angle and the data jitter, the yaw angle corresponding to each video frame image in the video is searched. By setting eight preset directions and traversing each video frame image in the video, when there is a yaw angle corresponding to a video frame image that matches any preset direction, the video frame image is extracted as a target video frame image corresponding to the preset direction. The target video frame image corresponding to each preset direction can be obtained, and the on-site direction of the location where the environmental noise is measured and the specific environment of the surrounding environmental noise measurement can be clearly described, thereby avoiding the situation where the eight-direction diagram is ultimately inaccurate due to artificial image shooting.

Description

Technical Field

[0001] The present application relates to the technical field of noise measurement, and in particular to a method for generating an octagonal diagram for measuring environmental noise. Background Art

[0002] When monitoring or measuring environmental noise, because the noise characteristics are closely related to the surrounding environment, in order to comprehensively study the relationship between noise and the surrounding environment, it is often necessary to record the surrounding environment of the monitoring site. The traditional way to obtain surrounding environment information is basically for on-site measurement personnel to use optical sensors to take different pictures of the surrounding environment in eight directions and make text notes on the picture directions. The photos taken by this traditional method often cannot accurately control the shooting direction, and the environmental information contained is highly random and incomplete, and it is easy to miss key direction information of the surrounding environment. Summary of the invention

[0003] Based on this, it is necessary to provide a method for generating an eight-direction diagram for environmental noise measurement in order to address the problem that when monitoring or measuring environmental noise, the photos taken by the traditional method of obtaining surrounding environment information are often unable to accurately control the shooting direction, the environmental information contained is highly random and incomplete, and it is easy to miss the key orientation information of the surrounding environment.

[0004] The present application provides a method for generating an environmental noise measurement eight-square diagram, comprising:

[0005] During the process of the noise detection device rotating at a uniform speed for one circle, starting the azimuth acquisition device of the noise detection device to acquire multiple yaw angles and incorporate them into the first yaw angle collection, and controlling the camera device of the noise detection device to shoot a video; the video includes multiple continuous video frame images;

[0006] Perform jump correction and data jitter correction on the yaw angles in the first yaw angle collection to form a second yaw angle collection;

[0007] Select a video frame image in the video;

[0008] Searching for a yaw angle corresponding to the video frame image from the second yaw angle collection;

[0009] Returning to selecting a video frame image in the video until all video frame images in the video are selected;

[0010] Define eight preset positions;

[0011] Traversing each video frame image in the video, when there is a video frame image corresponding to a flight angle that matches any preset orientation, extracting the video frame image as a target video frame image corresponding to the preset orientation, until a target video frame image corresponding to each preset orientation in eight preset orientations is obtained;

[0012] Eight target video frame images are placed at different positions and combined into one image, which is stored and output as an environmental noise measurement eight-way diagram.

[0013] The present application relates to a method for generating an eight-direction diagram for measuring environmental noise. During the process of the noise detection device rotating at a uniform speed for one circle, an azimuth acquisition device of the noise detection device is started to acquire multiple yaw angles, and a camera device of the noise detection device is controlled to shoot a video. After eliminating the angle jump of the yaw angle and the data jitter, the yaw angle corresponding to each video frame image in the video is searched. By setting eight preset directions and traversing each video frame image in the video, when there is a yaw angle corresponding to a video frame image that matches any preset direction, the video frame image is extracted as a target video frame image corresponding to the preset direction. The target video frame image corresponding to each preset direction can be obtained, and the on-site direction of the location where the environmental noise is measured and the specific environment of the surrounding environmental noise measurement can be clearly described, thereby avoiding the situation where the eight-direction diagram is ultimately inaccurate due to artificial image shooting. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A schematic diagram of a flow chart of a method for generating an eight-square diagram for environmental noise measurement provided in an embodiment of the present application.

[0015] Figure 2 A schematic diagram of the structure of a noise detection device provided in one embodiment of the present application at an angle.

[0016] Figure 3 A schematic diagram of the structure of a noise detection device provided in one embodiment of the present application at another angle.

[0017] Figure 4 A schematic diagram of the three-dimensional coordinates of the device for the method of generating an eight-square diagram for environmental noise measurement provided in one embodiment of the present application.

[0018] Figure 5 A schematic diagram of an environmental noise measurement eight-square diagram generated by a method for generating an environmental noise measurement eight-square diagram provided in an embodiment of the present application.

[0019] Figure 6 This is a physical picture of the environmental noise measurement eight-square diagram generated by the method for generating the environmental noise measurement eight-square diagram provided in an embodiment of the present application.

[0020] Reference numerals:

[0021] 100 - housing; 200 - orientation acquisition device; 300 - camera device. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0023] The present application provides a noise detection device.

[0024] like Figure 2 As shown, the noise detection device comprises a housing 100. The housing 100 is provided with a receiving space.

[0025] like Figure 2 and Figure 3 As shown, the noise detection device includes a position acquisition device 200. A position acquisition device 200 is installed in the accommodation space in the housing 100. The position acquisition device 200 can be a compass chip.

[0026] like Figure 2 and Figure 3 As shown, the noise detection device further includes a camera device 300. The camera device 300 may be an optical camera.

[0027] like Figure 2 , Figure 3 and Figure 4 As shown, a three-dimensional coordinate system of the noise detection device is set. With the physical center of the compass chip as the coordinate origin O, a three-dimensional coordinate system of the noise detection device is defined. The Y axis of the three-dimensional coordinate system of the noise detection device points to the physical center of the camera device 300, and the Z axis is perpendicular to the device plane of the noise detection device. The device plane of the noise detection device is Figure 4 The noise monitoring device obtains the yaw angle from the compass chip at equal time intervals. The yaw angle is the angle between the projection of the Y axis on the ground in the device's three-dimensional coordinate system and the earth's longitude line.

[0028] like Figure 4 As shown, the shooting direction (ie, the image capturing direction) of the camera device 300 is parallel to the Y axis.

[0029] The present application also provides a method for generating an octagonal diagram for measuring environmental noise.

[0030] like Figure 1 As shown, in one embodiment of the present application, the method for generating the environmental noise measurement eight-square diagram includes:

[0031] S100, during the process of the noise detection device rotating at a constant speed for one circle, the azimuth acquisition device 200 of the noise detection device is started to acquire multiple yaw angles and incorporate them into a first yaw angle collection, and the camera device 300 of the noise detection device is controlled to shoot a video. The video includes multiple continuous video frame images.

[0032] S200, performing jump correction and data jitter correction on the yaw angles in the first yaw angle collection to form a second yaw angle collection.

[0033] S300: Select a video frame image in the video.

[0034] S400, searching for a yaw angle corresponding to the video frame image from a second yaw angle collection.

[0035] S500, returning to S300, that is, returning to the step of selecting a video frame image in the video, until all video frame images in the video are selected.

[0036] S600: Define eight preset directions.

[0037] S700, traverse each video frame image in the video, and when there is a video frame image corresponding to a yaw angle that matches any preset orientation, extract the video frame image as the target video frame image corresponding to the preset orientation, until a target video frame image corresponding to each of the eight preset orientations is obtained.

[0038] S800, placing eight target video frame images at different positions respectively and combining them into one image, and storing and outputting the image as an eight-direction diagram for environmental noise measurement.

[0039] Specifically, in S100, when the noise detection device rotates, the XOY plane in the noise detection device is kept parallel to the ground, and the noise detection device can be at a certain distance from the ground. By manually rotating the noise detection device, the noise detection device rotates at a constant speed for one circle, that is, rotates 360 degrees. The manual rotation of the noise detection device can also be changed to a rotating bracket (not shown in the figure) that drives the noise detection device to rotate at a constant speed for one circle. The rotation direction is as follows: Figure 4 Once rotated, the X-axis and Y-axis of the three-dimensional coordinate system of the noise detection device will rotate accordingly, while the X-axis and Y-axis of the world coordinate system are constant because the world coordinate system belongs to the inherent properties of the earth.

[0040] When the rotation starts, the azimuth acquisition device 200 of the noise detection device is started to collect the yaw angle and the camera device 300 of the noise detection device is controlled to shoot a video. When the noise detection device rotates one circle, the collection of the yaw angle and the shooting of the video are stopped at the same time. By executing S100, N yaw angles and a video are finally obtained.

[0041] The N yaw angles are the yaw angles collected at N different collection time nodes.

[0042] The video includes M video frame images, where M is a positive integer and is greater than or equal to 30, so that continuity between different video frame images can be ensured.

[0043] In S200, since there is a high probability of angle jump and data jitter during the rotation process, S200 can effectively alleviate the problem of inaccurate yaw angle caused by angle jump and data jitter to the greatest extent.

[0044] Furthermore, the yaw angle corresponding to each video frame image in the video can be accurately found through S300 to S500 by aligning the shooting time of the video frame image and the acquisition time of the yaw angle, that is, aligning the two times to achieve the correspondence between the video frame image and the yaw angle.

[0045] Further, eight preset directions are customized by executing S600, and the eight preset directions may include due east, southeast, due south, southwest, due west, northwest, due north, and northeast.

[0046] By executing S700, the video frame image corresponding to each preset orientation is found as the target video frame image, and finally by executing S800, the eight target video frame images corresponding to the eight preset orientations are placed into a large image, and arranged according to the orientation correspondence to generate an environmental noise measurement eight-direction diagram, such as Figure 5 and Figure 6 The environmental noise measurement eight-square diagram can be stored locally on the noise detection device and can be uploaded to a remote host computer and cloud server for subsequent analysis.

[0047] In this embodiment, during the process of the noise detection device rotating at a uniform speed for one circle, the azimuth acquisition device 200 of the noise detection device is started to acquire multiple yaw angles, and the camera device 300 of the noise detection device is controlled to shoot a video. After eliminating the angle jump and data jitter of the yaw angle, the yaw angle corresponding to each video frame image in the video is searched, and eight preset azimuths are set, and each video frame image in the video is traversed. When there is a yaw angle corresponding to a video frame image that matches any preset azimuth, the video frame image is extracted as the target video frame image corresponding to the preset azimuth. The target video frame image corresponding to each preset azimuth can be obtained, and the on-site azimuth of the location where the environmental noise is measured and the specific environment of the surrounding environmental noise measurement can be clearly described, thereby avoiding the situation where the eight-direction diagram is ultimately inaccurate due to artificial image shooting.

[0048] In one embodiment of the present application, S200 includes, that is, performing jump correction and data jitter correction on the yaw angles in the first yaw angle set to form a second yaw angle set, including:

[0049] S210: Create a second yaw angle collection.

[0050] S220, sorting all the heading angles in the first heading angle collection in chronological order of acquisition time to obtain a heading angle sequence.

[0051] S230, calculating the angle difference between each two adjacent yaw angles in the yaw angle sequence, that is, calculating the angle difference between the n+1th yaw angle and the nth yaw angle, to obtain a yaw angle difference sequence. n is a positive integer and n=1, 2, 3, ..., N-1, N is a positive integer and N is the total number of yaw angles.

[0052] S240, obtaining a maximum yaw angle difference and a minimum yaw angle difference in a yaw angle difference sequence.

[0053] S250: Determine whether a yaw angle jump phenomenon occurs based on the maximum yaw angle difference and the minimum yaw angle difference in the yaw angle difference sequence.

[0054] S260: If a yaw angle jump phenomenon occurs, a jump correction is performed on the yaw angles in the first yaw angle collection, and all yaw angles after the jump correction are included in the second yaw angle collection.

[0055] S270: If no yaw angle jump occurs, all yaw angles in the first yaw angle set are transferred to the second yaw angle set.

[0056] S280, performing data jitter correction on the yaw angles in the second yaw angle collection.

[0057] Specifically, in the yaw angle sequence generated in S220, each yaw angle is arranged in order of collection time from early to late.

[0058] Under normal operating conditions, when the yaw angle sequence is converted into a line graph in a two-dimensional rectangular coordinate system, it should be a curve or straight line with a stable trend, or a continuous increase, or a continuous decrease, or a smooth curve (the horizontal axis is the acquisition time, and the vertical axis is the angle of the yaw angle). However, the yaw angle may jump during the acquisition process, which will appear as a broken line in the line graph.

[0059] The reason for the jump is that the noise detection device does not necessarily start rotating from the corresponding position of the absolute angle of 0 degrees, that is, it is not in the direction of due east, so a jump is possible, for example, a sudden jump from 0 degrees to 360 degrees, or a sudden jump from 360 degrees to 0 degrees. We can solve this problem by executing S260 in this embodiment to perform angle jump correction.

[0060] S270 is a case where no jump occurs, so the yaw angle does not need to be adjusted, and all yaw angle values ​​in the first yaw angle collection are maintained unchanged and included in the second yaw angle collection.

[0061] In one embodiment of the present application, S250 includes, that is, judging whether a yaw angle jump phenomenon occurs according to the maximum yaw angle difference and the minimum yaw angle difference in the yaw angle difference sequence, including:

[0062] S251, determining whether the maximum yaw angle difference is within a first jump angle difference range.

[0063] S252: If the maximum yaw angle difference is within the first jump angle difference range, it is determined that a yaw angle jump phenomenon occurs.

[0064] S253: If the maximum yaw angle difference is not within the first jump angle difference range, further obtain the minimum yaw angle difference in the yaw angle difference sequence.

[0065] S254: Determine whether the minimum yaw angle difference is within a second jump angle difference range.

[0066] S255: If the minimum yaw angle difference is within the second jump angle difference range, it is determined that a yaw angle jump phenomenon occurs.

[0067] Specifically, this embodiment introduces the subsequent processing steps when the yaw angle jumps. It is not necessary to adjust the yaw angle here. We judge whether it is necessary to adjust the angle of part of the yaw angle by judging whether the maximum yaw angle difference is within the first jump angle difference range and whether the minimum yaw angle difference is within the second jump angle difference range.

[0068] The first jump angle difference range corresponds to the maximum yaw angle difference, so the first jump angle difference range should be set to a range where both boundary angles are positive and close to the extreme value of 360 degrees. Therefore, the first jump angle interpolation range can be set to a range greater than or equal to 355 degrees and less than or equal to 365 degrees.

[0069] The second jump angle difference range corresponds to the minimum yaw angle difference, so the second jump angle difference range should be set to a range where both boundary angles are negative and close to the extreme value of -360 degrees. Therefore, the second jump angle interpolation range can be set to a range greater than or equal to -365 degrees and less than or equal to -355 degrees.

[0070] Because in this application, the rotation noise detection device rotates at a constant speed for one circle, and we default to the operating specification, and the collection time interval between two adjacent yaw angles is small, and the number of collected yaw angles is sufficient, then the density of collected yaw angles is large. Therefore, we ignore the extreme case of two jumps, which is more in line with the actual working conditions of environmental noise measurement. It can be understood that we ignore the situation where the maximum yaw angle difference in the yaw angle difference sequence is within the first jump angle difference range, and the minimum yaw angle difference is also within the second jump angle difference range, that is, we ignore the situation where two jumps occur, and only consider the situation where a single jump occurs.

[0071] Therefore, this embodiment only considers the following three situations:

[0072] Case 1): The maximum yaw angle difference is within the first jump angle difference range, and the minimum yaw angle difference is not within the second jump angle difference range. In this case, the conclusion is: it is determined that a yaw angle jump phenomenon occurs, and S260 is executed.

[0073] At this time, a jump from 0 degrees to 360 degrees occurs.

[0074] Case 2): The maximum yaw angle difference is not within the first jump angle difference range, and the minimum yaw angle difference is within the second jump angle difference range. At this time, the conclusion is: it is determined that the yaw angle jump phenomenon occurs, and S260 is executed.

[0075] At this time, a jump from 360 degrees to 0 degrees occurs.

[0076] Case 3): The maximum yaw angle difference is not within the first jump angle difference range, and the minimum yaw angle difference is not within the second jump angle difference range. At this time, the conclusion is: it is determined that no yaw angle jump phenomenon occurs, and S270 is executed.

[0077] In one embodiment of the present application, when it is determined that a yaw angle jump phenomenon occurs because the maximum yaw angle difference is within the first jump angle difference range, S260 includes, that is, performing a jump correction on the yaw angles in the first yaw angle collection, and incorporating all yaw angles after the jump correction into the second yaw angle collection, including:

[0078] S261a, obtain the nth yaw angle and the n+1th yaw angle corresponding to the maximum yaw angle difference, and use n+1 as a jump node.

[0079] S261b, determine whether n is greater than or equal to N / 2.

[0080] S261c1, if n is greater than or equal to N / 2, then for each heading deviation angle from the (n + 1)-th to the N-th in the heading deviation angle sequence, reduce its original angle value by 360 degrees, and incorporate the (n + 1)-th to the N-th heading deviation angles after the 360-degree reduction into the second set of combined heading deviation angles.

[0081] S261c2, keep the angles of the first to the n-th heading deviation angles unchanged, and incorporate the first to the n-th heading deviation angles into the second set of combined heading deviation angles.

[0082] S261d1, if n is less than N / 2, then for each heading deviation angle from the first to the n-th in the heading deviation angle sequence, increase its original angle value by 360 degrees, and incorporate the first to the n-th heading deviation angles after the 360-degree increase into the second set of combined heading deviation angles.

[0083] S261d2, keep the angles of the (n + 1)-th to the N-th heading deviation angles unchanged, and incorporate the (n + 1)-th to the N-th heading deviation angles into the second set of combined heading deviation angles.

[0084] Specifically, this embodiment is the step executed after case 1). In this embodiment, first, we need to further find the specific jump node, and then perform jump correction on some of the heading deviation angles based on the jump node.

[0085] When the maximum heading deviation angle difference is within the first jump angle difference range, that is, within the angle difference range of [355, 365], the subscript of the heading deviation angle corresponding to the maximum heading deviation angle difference is n, indicating that a 0-degree to 360-degree jump occurs in the heading deviation angle at the (n + 1)-th moment. Thus, we find the specific jump node.

[0086] If the jump subscript n < N / 2, it means the jump node is at a more forward position in the entire heading deviation angle sequence. Then, the first n heading deviation angles should be increased by 360 degrees on the original basis. By adjusting each of the first to the n-th heading deviation angles, the leveling of the heading deviation angle can be achieved.

[0087] If the jump subscript n ≥ N / 2, it means the jump node is at a more backward position in the entire heading deviation angle sequence. Then, the (n + 1)-th to the N-th heading deviation angles (i.e., the (n + 1)-th to the last heading deviation angle) should be reduced by 360 degrees on the original basis. By adjusting each of the (n + 1)-th to the N-th heading deviation angles, the leveling of the heading deviation angle can be achieved, as shown in formula 1.

[0088] Formula 1

[0089] in, It is a second yaw angle set generated after jump correction when it is determined that a yaw angle jump phenomenon occurs because the maximum yaw angle difference is within the first jump angle difference range. is the yaw angle sequence.

[0090] The purpose of increasing or decreasing 360 degrees is to restore the broken line to a curve or broken line with a consistent and stable trend. By increasing or decreasing 360 degrees, the yaw angle data can be leveled.

[0091] In one embodiment of the present application, when it is determined that a yaw angle jump phenomenon occurs because the minimum yaw angle difference is within the second jump angle difference range, S260 includes, that is, performing jump correction and data jitter correction on the yaw angles in the first yaw angle set to form a second yaw angle set, including:

[0092] S262a, obtaining the nth yaw angle and the n+1th yaw angle corresponding to the minimum yaw angle difference, and taking n+1 as a jump node.

[0093] S262b, determine whether n is greater than or equal to N / 2.

[0094] S262c1, if n is greater than or equal to N / 2, then each of the yaw angles from the n+1th to the Nth yaw angle in the yaw angle sequence is increased by 360 degrees on the basis of the original angle value, and the n+1th to the Nth yaw angles after the increase of 360 degrees are included in the second yaw angle collection.

[0095] S262c2, maintaining the angles from the first to the nth yaw angle unchanged, and including the first to the nth yaw angles into the second yaw angle set.

[0096] S262d1, if n is less than N / 2, each of the yaw angles from the first to the nth yaw angle in the yaw angle sequence is reduced by 360 degrees based on the original angle value, and the first to the nth yaw angles after being reduced by 360 degrees are included in the second yaw angle collection.

[0097] S262d2, maintaining the angles from the n+1th yaw angle to the Nth yaw angle unchanged, and including the first yaw angle to the nth yaw angle into the second yaw angle set.

[0098] Specifically, this embodiment is a step performed after situation 2). In this embodiment, first we need to further find a specific jump node, and then perform jump correction on part of the yaw angle according to the jump node.

[0099] When the minimum heading deviation angle difference is within the range of the second jump angle difference, that is, within the range of [-365, -355], the subscript of the heading deviation angle corresponding to the minimum heading deviation angle difference is n, indicating that a 360-degree to 0-degree jump occurs in the heading deviation angle at the (n + 1)th moment. In this way, we find the specific jump node.

[0100] If the jump subscript n < N / 2, it means that the jump node is at a more forward position in the entire heading deviation angle sequence. Then, the first n heading deviation angles should be reduced by 360 degrees on the original basis. By adjusting each of the heading deviation angles from the first one to the nth one, the leveling of the heading deviation angle can be achieved.

[0101] If the jump subscript n ≥ N / 2, it means that the jump node is at a more backward position in the entire heading deviation angle sequence. Then, the (n + 1)th heading deviation angle to the Nth heading deviation angle (i.e., the (n + 1)th heading deviation angle to the last one) should be increased by 360 degrees on the original basis. By adjusting each of the heading deviation angles from the (n + 1)th one to the Nth one, the leveling of the heading deviation angle can be achieved, as shown in Formula 2.

[0102] Formula 2

[0103] Among them, is the second set of heading deviation angles generated after jump correction when it is determined that a heading deviation angle jump phenomenon occurs because the minimum heading deviation angle difference is within the range of the second jump angle difference. represents the heading deviation angle sequence.

[0104] The purpose of increasing or decreasing by 360 degrees is to restore the broken line into a curve or broken line with a consistent and stable trend. By increasing or decreasing by 360 degrees, the leveling of the heading deviation angle data can be achieved.

[0105] In an embodiment of the present application, the S280 includes, that is, the data jitter correction for the heading deviation angles in the second set of heading deviation angles includes:

[0106] S281, take the median of all the heading deviation angles in the second set of heading deviation angles to obtain the median of the heading deviation angles.

[0107] S282, calculate the difference between each heading deviation angle in the second set of heading deviation angles and the median of the heading deviation angles, and take the absolute value of each difference to obtain an absolute value sequence.

[0108] S283, take the median of the absolute value sequence to obtain the median of the absolute values.

[0109] S284, scale the median of the absolute values according to a preset scaling factor to obtain the median absolute deviation.

[0110] S285, amplifying the median absolute deviation by a preset magnification factor, and using the amplified value as the outlier heading angle threshold.

[0111] S286, traverse each absolute value in the absolute value sequence to determine whether there is any absolute value greater than the outlier heading angle threshold.

[0112] S287a: If there is any absolute value greater than the outlier course deviation angle threshold, extract the course deviation angle corresponding to the absolute value and use the course deviation angle as the outlier course deviation angle.

[0113] S287b, deleting all outlier course angles in the second course angle sequence, and calculating the interpolated course angle corresponding to each outlier course angle by a linear interpolation method.

[0114] S287c, in the second yaw angle collection, each interpolated yaw angle replaces the original outlier yaw angle.

[0115] Specifically, this embodiment introduces a specific method for correcting data jitter, which specifically adopts the method of performing outlier detection on the data in the second yaw angle set and filling the outlier position with linear interpolation.

[0116] It should be noted that the aforementioned jump correction is to correct the jump, and this embodiment is to correct the data jitter. The reason for the jump is that the noise detection device does not necessarily start to rotate at the corresponding position of the absolute angle of 0 degrees, because the jump correction belongs to the definition of the angle that produces a detection cycle in one rotation, and the jump and error have nothing to do with human factors. Data jitter is related to errors and human factors. For example, if a handheld noise detection device rotates one circle, an error will occur. The yaw angle obtained by the compass chip is not absolutely accurate, and there will be certain errors. These are the causes of data jitter. The purpose of this embodiment is to correct these data jitters.

[0117] The execution process of S281 can be expressed by Formula 3.

[0118] Formula 3

[0119] in, is the median yaw angle, is the second yaw angle collection, The symbol for the median.

[0120] S281, the specific operation of obtaining the median of all the yaw angles in the second yaw angle set is:

[0121] S281a, sorting all the yaw angles in the second yaw angle collection from small to large to obtain a second yaw angle sequence.

[0122] S281b, determine whether the total number N of the yaw angles in the second yaw angle sequence is an odd number or an even number. Here, the number of yaw angles remains unchanged during the process from the first yaw angle collection to the second yaw angle collection, so N is still used to represent the total number of yaw angles.

[0123] S281c: If the total number N of the yaw angles in the second yaw angle sequence is an odd number, the yaw angle corresponding to the (N+1) / 2th subscript is used as the median of the yaw angles.

[0124] S281d, if the total number N of yaw angles in the second yaw angle sequence is an even number, calculate the average of the yaw angle corresponding to the (N+1) / 2th subscript and the yaw angle corresponding to the N / 2th subscript, and use the average as the median of the yaw angle.

[0125] The execution process of obtaining the median absolute deviation from S282 to S284 can be expressed by Formula 4.

[0126] Formula 4

[0127] in, is the median absolute deviation, is the preset zoom factor, is the symbol for the median, is the median yaw angle, is the mth heading angle in the second heading angle collection, m is the sequence number of the heading angle in the second heading angle collection, m=1, 2, 3, ..., N.

[0128] The execution process of S285 to S287a can be expressed by Formula 5.

[0129] In S284, the preset scaling factor may be 1.4826.

[0130] In S285, the preset magnification may be 3.

[0131] Formula 5

[0132] in, is the median absolute deviation, K is the preset magnification, is the median yaw angle, is the mth heading angle in the second heading angle collection, m is the sequence number of the heading angle in the second heading angle collection, m=1, 2, 3, ..., N.

[0133] The method and principle of taking the median of the absolute value sequence in S283 are consistent with the principle of taking the median of all yaw angles in the second yaw angle set in S281. Please refer to the description of S281a to S281d, which will not be repeated here.

[0134] An example of linear interpolation from S287b to S287c is shown below. For example, the second yaw angle set for , if the outlier heading angle is and , then the outlier heading angle The corresponding interpolated yaw angle is , outlier heading angle The corresponding interpolated yaw angle is It can be understood that after the interpolated yaw angle is used to replace the original outlier yaw angle, the second yaw angle set becomes .

[0135] In one embodiment of the present application, S400 includes, that is, searching for the yaw angle corresponding to the video frame image from the second yaw angle collection includes:

[0136] S410, obtaining the shooting time Tm of the video frame image.

[0137] S420, defining a preset time period Tw.

[0138] S430, searching the second yaw angle collection for the yaw angle corresponding to each shooting moment within the time range of [Tm-Tw, Tm+Tw] to obtain a plurality of yaw angles.

[0139] S440, performing straight line fitting using the plurality of yaw angles as a plurality of data points to generate a yaw angle fitting straight line.

[0140] S450, obtaining a mathematical expression of the yaw angle fitting line.

[0141] S460, substitute the shooting time Tm of the video frame image into the mathematical expression of the yaw angle fitting line to obtain the yaw angle corresponding to the shooting time Tm of the video frame image, and use the yaw angle corresponding to the shooting time Tm of the video frame image as the yaw angle corresponding to the video frame image.

[0142] Specifically, Tw may be 0.5 seconds. The time range in S430 may be [Tm-0.5, Tm+0.5].

[0143] The second set of yaw angles in S430 is formed by replacing the original outlier yaw angles with the interpolated yaw angles.

[0144] The expression of the yaw angle fitting straight line in S440 may be as shown in Formula 6.

[0145] Formula 6

[0146] in, is the ordinate of the yaw angle fitting line, which means the yaw angle after fitting. t is the abscissa of the yaw angle fitting line, which means the time. is the shooting time of the video frame image, is the slope of the yaw angle fitting line, is the intercept of the yaw angle fitting line.

[0147] In S460, the shooting time Tm of the video frame image is substituted into the mathematical expression of the third yaw angle fitting line, and then Tm is substituted into Formula 6 to obtain the yaw angle corresponding to the shooting time Tm of the video frame image, as shown in Formula 7.

[0148] Formula 7

[0149] in, is the yaw angle corresponding to the shooting time Tm of the video frame image, is the shooting time of the video frame image, is the slope of the yaw angle fitting line, is the intercept of the yaw angle fitting line.

[0150] In one embodiment of the present application, S400 further includes, that is, searching for the yaw angle corresponding to the video frame image from the second yaw angle collection, further includes:

[0151] S471, determining whether the yaw angle corresponding to the video frame image is greater than 360 degrees.

[0152] S472: If the yaw angle corresponding to the video frame image is greater than 360 degrees, the yaw angle corresponding to the video frame image is reduced by 360 degrees based on the original angle value.

[0153] S473: If the yaw angle corresponding to the video frame image is less than or equal to 360 degrees, further determine whether the yaw angle corresponding to the video frame image is less than 0 degrees.

[0154] S474: If it is determined that the yaw angle corresponding to the video frame image is less than 0 degrees, the yaw angle corresponding to the video frame image is increased by 360 degrees based on the original angle value.

[0155] Specifically, this embodiment restores the yaw angle through Formula 8.

[0156] Formula 8

[0157] in, is the yaw angle corresponding to the shooting time Tm of the video frame image, For The yaw angle obtained after restoration.

[0158] By adding or subtracting 360 degrees of adjustment, the yaw angle can correspond to the definition of the limited angle range of the eight-direction diagram.

[0159] Please continue reading Figure 5 In one embodiment of the present application, the eight preset directions include due east, southeast, due south, southwest, due west, northwest, due north, and northeast.

[0160] Specifically, the due east direction, southeast direction, due south direction, southwest direction, due west direction, northwest direction, due north direction, and northeast direction may comprehensively cover the key directions of the surrounding environment.

[0161] The X-axis of the world coordinate system corresponds to the due east direction, the Y-axis corresponds to the due north direction, and the Z-axis is vertically upward from the ground.

[0162] Eight preset positions:

[0163] Due east (+X axis): yaw angle theta = 0° ±5°.

[0164] Northeast: heading angle theta = 45° ±5°.

[0165] True north (+Y axis): heading angle theta = 90° ±5°.

[0166] Northwest: heading angle theta = 135°±5°.

[0167] Due west (-X axis): yaw angle theta = 180° ±5°.

[0168] Southeast: heading angle theta = 225° ±5°.

[0169] Due south (-Y axis): heading angle theta = 270° ±5°.

[0170] Southwest: heading angle theta = 315° ±5°.

[0171] In this embodiment, by setting eight preset directions including due east, southeast, due south, southwest, due west, northwest, due north, and northeast, the final generated eight-direction environmental noise measurement diagram can have all the key direction information of the environment around the noise detection point without omission.

[0172] In one embodiment of the present application, S700 includes, that is, traversing each video frame image in the video, when there is a flight angle corresponding to a video frame image that matches any preset orientation, extracting the video frame image as a target video frame image corresponding to the preset orientation, until a target video frame image corresponding to each preset orientation in eight preset orientations is obtained, including:

[0173] S710: Select a video frame image in the video in chronological order.

[0174] S720: Obtain a yaw angle corresponding to the video frame image.

[0175] S730, determining whether the yaw angle corresponding to the video frame image is within the angle range corresponding to any preset orientation [angle value corresponding to the preset orientation - preset angle value, angle value corresponding to the preset orientation + preset angle value].

[0176] S740, if the yaw angle of the video frame image is within the angle range corresponding to any preset orientation [angle value corresponding to the preset orientation - preset angle value, angle value corresponding to the preset orientation + preset angle value], then the video frame image is defined as a hit video frame image corresponding to the preset orientation.

[0177] S750, returning to S71, that is, returning to the step of selecting a video frame image in the video in chronological order, until every video frame image in the video has been selected.

[0178] S760, selecting the best hit video frame image from the hit video frame images corresponding to each preset orientation as the target video frame image corresponding to each preset orientation.

[0179] Specifically, the preset orientation may correspond to many hit video frame images. How to select a unique hit video frame image as the target video frame image is the key to the accuracy of the final generation of the eight-direction diagram. This embodiment achieves redundant settings by setting the angle range corresponding to the preset orientation [the angle value corresponding to the preset orientation - the preset angle value, the angle value corresponding to the preset orientation + the preset angle value], and judging whether the flight angle corresponding to the video frame image is within this angle range to judge whether the video frame image matches the preset orientation. The preset angle value can be 5 degrees. For example, if the preset orientation is 90 degrees east, then the video frame images that fall within the angle range of [85 degrees, 95 degrees] can be used as hit video frame images. The selection of the optimal hit video frame image has a selection range, which is more in line with the actual situation, because the actual situation may not necessarily find an accurate video frame image corresponding to the unique preset orientation angle.

[0180] In this embodiment, by setting the angle range corresponding to the preset orientation [angle value corresponding to the preset orientation - preset angle value, angle value corresponding to the preset orientation + preset angle value] and judging whether the yaw angle corresponding to the video frame image is within this angle range to judge whether the video frame image matches the preset orientation, sufficient alternative hit video frame images can be provided to select the best one.

[0181] In one embodiment of the present application, S760 includes, that is, selecting the best hit video frame image from the hit video frame images corresponding to each preset orientation as the target video frame image corresponding to each preset orientation, including:

[0182] S761, select a preset direction.

[0183] S762, determining whether the number of the hit video frame images corresponding to the preset orientation is 1.

[0184] S763: If the number of the hit video frame images corresponding to the preset orientation is not 1, determine whether the number of the hit video frame images corresponding to the preset orientation is greater than 1.

[0185] S764, if the number of the hit video frame images corresponding to the preset orientation is greater than 1, then the difference between the yaw angle of each hit video frame image and the angle value corresponding to the preset orientation is calculated.

[0186] S765, obtaining the minimum difference, and taking the hit video frame image corresponding to the minimum difference as the optimal hit video frame image.

[0187] S766: Use the best hit video frame image as the target video frame image corresponding to the preset orientation.

[0188] S767, return to S761, that is, return to the process of selecting a preset direction until all eight preset directions are selected.

[0189] Specifically, the aforementioned content mentioned that a preset orientation may correspond to many hit video frame images. How to select a unique hit video frame image as the target video frame image is the key to the accuracy of the final generation of the eight-direction diagram.

[0190] In this embodiment, by calculating the difference between the yaw angle of each hit video frame image and the angle value corresponding to the preset orientation, the hit video frame image corresponding to the minimum difference is used as the optimal hit video frame image, so that the video frame image that best matches the preset orientation can be found quickly and accurately.

[0191] In one embodiment of the present application, S760 further includes, that is, selecting the best hit video frame image from the hit video frame images corresponding to each preset orientation as the target video frame image corresponding to each preset orientation, and further includes:

[0192] S768: If the number of the hit video frame image corresponding to the preset orientation is 1, the hit video frame image is used as the optimal hit video frame image.

[0193] S769, taking the best hit video frame image as the target video frame image corresponding to the preset orientation, and returning to the step of selecting a preset orientation until all preset orientations are selected.

[0194] The resulting ambient noise measurement diagram is shown below: Figure 5 and Figure 6 shown.

[0195] Optionally, the environmental noise measurement eight-square diagram may include a GPS positioning diagram, which is set at the center of the eight target video frame images, that is, the eight target video frame images are arranged in an orderly manner around the GPS positioning diagram according to the corresponding directions, such as Figure 5 shown.

[0196] like Figure 5 As shown, each arrangement position of the eight target video frame images corresponds to its orientation in the entire picture. For example, the target video frame image corresponding to the due north orientation is also arranged in the due north position of the entire picture in the environmental noise measurement eight-direction diagram.

[0197] The technical features of the above-described embodiments may be arbitrarily combined, and the execution order of the method steps is not limited. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0198] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for generating an environmental noise measurement eight-square diagram, characterized in that: include: During the process of the noise detection device rotating at a uniform speed for one circle, starting the azimuth acquisition device of the noise detection device to acquire multiple yaw angles and incorporate them into the first yaw angle collection, and controlling the camera device of the noise detection device to shoot a video; the video includes multiple continuous video frame images; Perform jump correction and data jitter correction on the yaw angles in the first yaw angle collection to form a second yaw angle collection; Select a video frame image in the video; Searching for a yaw angle corresponding to the video frame image from the second yaw angle collection; Returning to selecting a video frame image in the video until all video frame images in the video are selected; Define eight preset positions; Traversing each video frame image in the video, when there is a video frame image corresponding to a flight angle that matches any preset orientation, extracting the video frame image as a target video frame image corresponding to the preset orientation, until a target video frame image corresponding to each preset orientation in eight preset orientations is obtained; Eight target video frame images are placed at different positions and combined into one image, which is stored and output as an environmental noise measurement eight-way diagram.

2. The method for generating an environmental noise measurement octagonal diagram according to claim 1, characterized in that: The step of performing jump correction and data jitter correction on the yaw angles in the first yaw angle set to form a second yaw angle set includes: Create a second yaw angle collection; All the heading angles in the first heading angle collection are sorted according to the order of collection time to obtain a heading angle sequence; Calculate the angle difference between each two adjacent yaw angles in the yaw angle sequence, that is, calculate the angle difference between the n+1th yaw angle and the nth yaw angle, to obtain a yaw angle difference sequence; n is a positive integer and n=1, 2, 3, ..., N-1, N is a positive integer and N is the total number of yaw angles in the first yaw angle set; Obtain the maximum yaw angle difference and the minimum yaw angle difference in the yaw angle difference sequence; According to the maximum yaw angle difference and the minimum yaw angle difference in the yaw angle difference sequence, it is determined whether a yaw angle jump phenomenon occurs; If a yaw angle jump occurs, the yaw angles in the first yaw angle set are corrected by a jump, and all yaw angles after the jump correction are included in the second yaw angle set; If the yaw angle jump phenomenon does not occur, all the yaw angles in the first yaw angle collection are transferred to the second yaw angle collection; Data jitter correction is performed on the yaw angles in the second yaw angle collection.

3. The method for generating an environmental noise measurement octagonal diagram according to claim 2, characterized in that: The determining whether a yaw angle jump phenomenon occurs according to the maximum yaw angle difference and the minimum yaw angle difference in the yaw angle difference sequence includes: Determine whether the maximum yaw angle difference is within the first jump angle difference range; If the maximum yaw angle difference is within the first jump angle difference range, it is determined that a yaw angle jump phenomenon occurs; If the maximum yaw angle difference is not within the first jump angle difference range, further obtaining the minimum yaw angle difference in the yaw angle difference sequence; Determine whether the minimum yaw angle difference is within the second jump angle difference range; If the minimum yaw angle difference is within the second jump angle difference range, it is determined that a yaw angle jump phenomenon occurs.

4. The method for generating an environmental noise measurement octagonal diagram according to claim 3, characterized in that: When it is determined that a yaw angle jump phenomenon occurs because the maximum yaw angle difference is within the first jump angle difference range, performing a jump correction on the yaw angles in the first yaw angle collection, and incorporating all yaw angles after the jump correction into the second yaw angle collection, includes: Obtain the nth yaw angle and the n+1th yaw angle corresponding to the maximum yaw angle difference, and use n+1 as the jump node; Determine whether n is greater than or equal to N / 2; If n is greater than or equal to N / 2, each of the yaw angles from the n+1th yaw angle to the Nth yaw angle in the yaw angle sequence is reduced by 360 degrees based on the original angle value, and the yaw angles from the n+1th yaw angle to the Nth yaw angle after being reduced by 360 degrees are included in the second yaw angle collection; The angles from the first yaw angle to the nth yaw angle are maintained unchanged, and the first yaw angle to the nth yaw angle are included in the second yaw angle collection; If n is less than N / 2, each of the yaw angles from the first yaw angle to the nth yaw angle in the yaw angle sequence is increased by 360 degrees on the basis of the original angle value, and the first yaw angle to the nth yaw angle after the increase of 360 degrees are included in the second yaw angle collection; The angles from the n+1th yaw angle to the Nth yaw angle are maintained unchanged, and the n+1th yaw angle to the Nth yaw angle are included in the second yaw angle collection.

5. The method for generating an environmental noise measurement octagonal diagram according to claim 4, characterized in that: When it is determined that a yaw angle jump phenomenon occurs because the minimum yaw angle difference is within the second jump angle difference range, performing jump correction and data jitter correction on the yaw angles in the first yaw angle set to form a second yaw angle set includes: Obtain the nth yaw angle and the n+1th yaw angle corresponding to the minimum yaw angle difference, and use n+1 as the jump node; Determine whether n is greater than or equal to N / 2; If n is greater than or equal to N / 2, each of the yaw angles from the n+1th yaw angle to the Nth yaw angle in the yaw angle sequence is increased by 360 degrees on the basis of the original angle value, and the yaw angles from the n+1th yaw angle to the Nth yaw angle after the increase of 360 degrees are included in the second yaw angle collection; The angles from the first yaw angle to the nth yaw angle are maintained unchanged, and the first yaw angle to the nth yaw angle are included in the second yaw angle collection; If n is less than N / 2, each of the yaw angles from the first yaw angle to the nth yaw angle in the yaw angle sequence is reduced by 360 degrees based on the original angle value, and the first yaw angle to the nth yaw angle after being reduced by 360 degrees are included in the second yaw angle collection; The angles from the n+1th yaw angle to the Nth yaw angle are maintained unchanged, and the first yaw angle to the nth yaw angle are included in the second yaw angle collection.

6. The method for generating an environmental noise measurement octagonal diagram according to claim 5, characterized in that: The performing data jitter correction on the yaw angles in the second yaw angle collection includes: Take the median of all the yaw angles in the second yaw angle set to obtain the median yaw angle; Calculate the difference between each yaw angle and the median of the yaw angle in the second yaw angle collection, and take the absolute value of each difference to obtain an absolute value sequence; Take the median of the absolute value sequence to get the absolute value median; The absolute median is scaled by a preset scaling factor to obtain the median absolute deviation; The median absolute deviation is amplified by a preset magnification factor, and the amplified value is used as the outlier heading angle threshold; Traverse each absolute value in the absolute value sequence to determine whether there is any absolute value greater than the outlier deviation angle threshold; If there is any absolute value greater than the outlier course deviation angle threshold, the course deviation angle corresponding to the absolute value is extracted and the course deviation angle is used as the outlier course deviation angle; All outlier course deviation angles in the second course deviation angle sequence are deleted, and the interpolated course deviation angle corresponding to each outlier course deviation angle is calculated by a linear interpolation method; In the second yaw angle collection, each interpolated yaw angle replaces the original outlier yaw angle.

7. The method for generating an environmental noise measurement octagonal diagram according to claim 6, characterized in that: The step of searching for the yaw angle corresponding to the video frame image from the second yaw angle collection includes: Obtaining the shooting time Tm of the video frame image; Define a preset time period Tw; Searching for the yaw angle corresponding to each shooting moment within the time range of [Tm-Tw, Tm+Tw] from the second yaw angle collection to obtain multiple yaw angles; Perform straight line fitting using the multiple yaw angles as multiple data points to generate a yaw angle fitting straight line; Get the mathematical expression of the yaw angle fitting line; Substitute the shooting time Tm of the video frame image into the mathematical expression of the yaw angle fitting line to obtain the yaw angle corresponding to the shooting time Tm of the video frame image, and use the yaw angle corresponding to the shooting time Tm of the video frame image as the yaw angle corresponding to the video frame image.

8. The method for generating an environmental noise measurement octagonal diagram according to claim 7, characterized in that: The step of searching for the yaw angle corresponding to the video frame image from the second yaw angle collection further includes: Determine whether the yaw angle corresponding to the video frame image is greater than 360 degrees; If the yaw angle corresponding to the video frame image is greater than 360 degrees, the yaw angle corresponding to the video frame image is reduced by 360 degrees based on the original angle value; If the yaw angle corresponding to the video frame image is less than or equal to 360 degrees, further determining whether the yaw angle corresponding to the video frame image is less than 0 degrees; If it is determined that the yaw angle corresponding to the video frame image is less than 0 degrees, the yaw angle corresponding to the video frame image is increased by 360 degrees on the basis of the original angle value.

9. The method for generating an environmental noise measurement octagonal diagram according to claim 8, characterized in that: The traversing each video frame image in the video, when there is a video frame image corresponding to a flight angle that matches any preset orientation, extracting the video frame image as a target video frame image corresponding to the preset orientation, until a target video frame image corresponding to each preset orientation in eight preset orientations is obtained, including: Selecting a video frame image in the video in chronological order; Obtaining the yaw angle corresponding to the video frame image; Determine whether the flight angle corresponding to the video frame image is within an angle range corresponding to any preset orientation [angle value corresponding to the preset orientation - preset angle value, angle value corresponding to the preset orientation + preset angle value]; If the flight angle of the video frame image is within the angle range corresponding to any preset orientation [angle value corresponding to the preset orientation - preset angle value, angle value corresponding to the preset orientation + preset angle value], the video frame image is defined as a hit video frame image corresponding to the preset orientation; Returning to selecting a video frame image in the video in chronological order until every video frame image in the video has been selected; The best hit video frame image is selected from the hit video frame images corresponding to each preset orientation as the target video frame image corresponding to each preset orientation.

10. The method for generating an environmental noise measurement octagonal diagram according to claim 9, characterized in that: The step of selecting the best hit video frame image from the hit video frame images corresponding to each preset orientation as the target video frame image corresponding to each preset orientation includes: Select a preset location; Determine whether the number of the hit video frame images corresponding to the preset orientation is 1; If the number of the hit video frame images corresponding to the preset orientation is not 1, determining whether the number of the hit video frame images corresponding to the preset orientation is greater than 1; If the number of the hit video frame images corresponding to the preset azimuth is greater than 1, then the difference between the flight angle of each hit video frame image and the angle value corresponding to the preset azimuth is calculated; Obtain the minimum difference, and use the hit video frame image corresponding to the minimum difference as the optimal hit video frame image; Taking the best hit video frame image as the target video frame image corresponding to the preset orientation; Return to selecting a preset position until all eight preset positions have been selected.

Images