WO2024051501A1 - 基于光纤的多目标定位方法、处理器、装置及存储介质 - Google Patents

基于光纤的多目标定位方法、处理器、装置及存储介质 Download PDF

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Publication number
WO2024051501A1
WO2024051501A1 PCT/CN2023/114818 CN2023114818W WO2024051501A1 WO 2024051501 A1 WO2024051501 A1 WO 2024051501A1 CN 2023114818 W CN2023114818 W CN 2023114818W WO 2024051501 A1 WO2024051501 A1 WO 2024051501A1
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Prior art keywords
target
vibration
tracking target
tracking
data
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PCT/CN2023/114818
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English (en)
French (fr)
Inventor
陈朋超
蔡永军
李秋娟
王海明
孟佳
张弢甲
周琰
张丽稳
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国家石油天然气管网集团有限公司
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Publication of WO2024051501A1 publication Critical patent/WO2024051501A1/zh

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    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F17STORING OR DISTRIBUTING GASES OR LIQUIDS
    • F17DPIPE-LINE SYSTEMS; PIPE-LINES
    • F17D5/00Protection or supervision of installations
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01HMEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H9/00Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by using radiation-sensitive means, e.g. optical means

Definitions

  • the present application relates to the field of optical fiber positioning, and specifically to an optical fiber-based multi-target positioning method, processor, device and storage medium.
  • the oil pipeline system that is, the pipeline system used to transport oil and petroleum products, mainly consists of oil pipelines, oil pipelines and other auxiliary related equipment. It is one of the main equipment in the petroleum storage and transportation industry, and is also the most important equipment for crude oil and petroleum products. Compared with railway and road oil transportation, which are both land transportation methods, pipeline oil transportation has the characteristics of large transportation capacity, good sealing, low cost and high safety factor.
  • the purpose of the embodiments of the present application is to provide an optical fiber-based multi-target positioning method, processor, device and storage medium that can track multiple vibration sources and identify overlapping vibration sources.
  • embodiments of the present application provide a multi-target positioning method based on optical fiber.
  • a sampling section to be monitored is set on the ground above the optical fiber.
  • the method includes:
  • the displacement data of multiple tracking targets within a preset time period are processed to generate a visual waterfall chart, which shows the position change data of each tracking target in each unit time.
  • the tracking targets located at the same location at the same time point within the preset time period are determined based on the waterfall chart.
  • multiple sampling points are set up in the sampling road section, and obtaining the displacement data of each tracking target in the sampling road section includes: obtaining the displacement data collected at each sampling point at the same time point according to the preset frequency.
  • determining multiple tracking targets to be monitored based on vibration signals collected at the first endpoint and the second endpoint includes: performing feature extraction on the vibration signals to obtain vibration features corresponding to the vibration signals.
  • the vibration characteristics include at least one of vibration intensity, influence length and vibration time; the target vibration signal in the vibration signal is determined according to the vibration characteristics; the vibration source corresponding to the target vibration signal is determined as the tracking target.
  • the historical average movement speed of each tracking target is determined according to the waterfall chart; the historical average movement speed of each tracking target is predicted to be at a preset time point for each tracking target. Predicted position; obtain the actual position and actual movement speed of each tracking target at a preset time point; in the case where the difference between the actual movement speed of the tracking target and the historical average movement speed is greater than the preset difference , determine the abnormal motion of the tracking target.
  • the vibration characteristics of the target vibration signal are extracted to obtain the target vibration characteristics; the target vibration characteristics are matched with the preset reference characteristics to determine the target type of each tracking target, and/or, according to each The historical average movement speed of the tracking target determines the target type of the tracking target; according to the target type of each tracking target Determine the displacement markers displayed on the waterfall plot for each tracked target.
  • the displacement mark includes a variety of shapes, and the shape corresponds to the target type of the tracking target. The greater the vibration intensity of the target vibration signal corresponding to the tracking target, the darker the color of the displacement mark corresponding to the tracking target. deep.
  • the displacement mark corresponding to the tracking target is recovered; when the duration after the target vibration signal disappears exceeds the preset multiple of the occurrence duration of the target vibration signal , release the recovered displacement markers to mark the displacement data of other tracking targets.
  • a second aspect of the present application provides a processor configured to perform any of the above fiber-based multi-target positioning methods.
  • the third aspect of this application provides an optical fiber-based multi-target positioning device, including the above-mentioned processor.
  • a fourth aspect of the present application provides a machine-readable storage medium. Instructions are stored on the machine-readable storage medium. When executed by a processor, the instructions cause the processor to be configured to perform any of the above fiber-based multiplexing. Targeting methods.
  • the fifth aspect of this application provides a fiber-based multi-target positioning method, including:
  • the displacement data of each tracking target within the sampling road section is obtained.
  • the displacement data includes time data and position data corresponding to the time;
  • the displacement data of each tracking target within a preset time period is processed to generate a visual waterfall chart.
  • the waterfall chart displays the position change data of each tracking target in each unit time.
  • the sixth aspect of this application provides an optical fiber-based multi-target positioning device, including a vibration data collection device and a server;
  • the data acquisition device is used to: obtain vibration data of each sampling point on the sampling road section through optical fiber;
  • the server is used for:
  • the displacement data of each tracking target within the sampling road section is obtained.
  • the displacement data includes time data and position data corresponding to the time;
  • the waterfall chart displays the position change data of each tracking target in each unit time.
  • the vibration signals of multiple vibration sources are collected in the sampling road section to determine the tracking targets to be monitored, and each tracking target is tracked to obtain unique data for each tracking target, and the displacement data is processed , generate a visual waterfall chart.
  • the resulting visual waterfall chart can be used to mark, display and distinguish multiple targets.
  • Figure 1 schematically shows one of the flow diagrams of an optical fiber-based multi-target positioning method according to an embodiment of the present application
  • Figure 2 schematically shows an example diagram of an optical fiber-based multi-target positioning method according to an embodiment of the present application
  • Figure 3 schematically shows an example diagram of an optical fiber-based multi-target positioning method according to an embodiment of the present application
  • Figure 4 schematically shows an example diagram of an optical fiber-based multi-target positioning method according to an embodiment of the present application
  • Figure 5 schematically shows an internal structure diagram of a computer device according to an embodiment of the present application
  • Figure 6 schematically shows one of the flow charts of the optical fiber-based multi-target positioning method according to an embodiment of the present application. two;
  • Figure 7 schematically shows a structural diagram of an optical fiber-based multi-target positioning device according to an embodiment of the present application
  • Displacement data corresponding to the first tracking target 1. Displacement data corresponding to the first tracking target; 2. Displacement data corresponding to the second tracking target; 3. Displacement data corresponding to the third tracking target; 4. Displacement data corresponding to the fourth tracking target; 5. Displacement data corresponding to the fifth tracking target; 6. Displacement data corresponding to the sixth tracking target; 7. Displacement data corresponding to the seventh tracking target; 8. Displacement data corresponding to the eighth tracking target; 9. Ninth tracking target Displacement data corresponding to a tracking target; A. Overlapping point of displacement data corresponding to the second tracking target and displacement data corresponding to the fourth tracking target; B. Displacement data corresponding to the third tracking target and the fourth tracking target The overlapping points of the corresponding displacement data; a.
  • FIG. 1 a schematic flow chart of an optical fiber-based multi-target positioning method according to an embodiment of the present application is schematically shown.
  • Figure 2 in one embodiment of the present application, a fiber-based multi-target positioning method is provided, including the following steps:
  • S102 Collect vibration signals from multiple vibration sources at the first endpoint and the second endpoint;
  • S105 Process the displacement data of multiple tracking targets within a preset time period to generate a visual waterfall chart.
  • the waterfall chart shows the position change data of each tracking target in each unit time.
  • the processor can set the section to be monitored as a sampling section above the ground where the optical fiber is laid. After the processor sets the sampling road segment, it can determine the two ends of the sampling road segment as the first endpoint and the second endpoint of the sampling road segment. After the processor determines the first endpoint and the second endpoint of the sampling road segment, the processor can set the sub-sampling road segment at the first endpoint and the second endpoint of the sampling road segment.
  • the sub-sampling road section collects vibration signals from multiple vibration sources, and determines multiple tracking targets to be monitored among the multiple vibration sources based on the collected vibration signals.
  • the processor determines the tracking targets to be monitored, it can be obtained Displacement data of each tracking target within the sampling road section, where the displacement data of the tracking target may include time data of the tracking target and position data corresponding to the time.
  • the processor obtains the displacement data corresponding to each tracking target, it can obtain the preset time period set by the processor, obtain all tracking targets within the preset time period and the displacement data corresponding to the tracking target, and perform The corresponding displacement data is processed to obtain a visual waterfall chart of the displacement data corresponding to each tracking target within the preset time period.
  • the visual waterfall chart can show the performance of each tracking target in each unit time within the preset time period. location change data.
  • the tracking targets located at the same location at the same time point within the preset time period are determined according to the waterfall chart.
  • the visual waterfall chart can be used to determine the tracking targets that are displaced at the same position at the same time point within the preset time period, that is, within the preset time period. Tracking target when vibration sources overlap at the same time.
  • multiple sampling points are set up in the sampling road section, and obtaining the displacement data of each tracking target in the sampling road section includes: according to a preset frequency, obtaining each data collected at each sampling point at the same time point. Track the vibration intensity of the target; for each time point, filter and identify the vibration intensity collected at each sampling point to determine the target position of each tracking target at each time point.
  • the processor can set multiple sampling points within the set sampling section, and each sampling point includes a vibration sensor.
  • the vibration signal collected at the sampling point can be determined by the vibration sensor.
  • the processor can control the vibration sensor to obtain the vibration intensity of each tracking target collected at each sampling point at the same time point according to the preset frequency. That is, for the same tracking target, the vibration sensor at each sampling point collects the sampling point.
  • the vibration signal that can be received at different locations. Since the location of the tracking target is different, the vibration intensity of the vibration signal collected at each sampling point is also different.
  • the vibration intensity of each tracking target is collected according to the preset frequency.
  • the processor can obtain the vibration intensity collected at each sampling point for the same tracking target.
  • the processor can filter and identify the vibration intensity collected at each sampling point to determine each tracking target. The target position at each time point.
  • the vibration intensity of the vibration signal collected at each sampling point is as shown in the histogram of Figure 2
  • the origin of Figure 2 is the first endpoint of the sampling road section
  • the abscissa in the histogram of Figure 2 represents the location distance of the sampling point
  • the ordinate represents the vibration intensity of the vibration signal
  • each individual column represents the sampling Point the vibration intensity of the same tracking target collected at the same time. Since the position of the tracking target is different, the vibration intensity of the vibration signal collected at each sampling point at the same time is different.
  • the processor can process the vibration signal obtained at each sampling point and filter the second strongest signal to determine the strongest point.
  • the strongest point of the vibration signal Determine the vibration source at the sampling point, thereby determining the target position of the tracking target corresponding to the vibration source in the sampling section, and determine the corresponding time when the tracking target is at the target position, specifically:
  • the optical fiber collects the vibration signal of each vibration source.
  • the signal collected by the optical cable at the location of the vibration source is the strongest.
  • the signal slightly farther away shows exponential attenuation.
  • the signal strength presents an isosceles triangle.
  • the apex position of the triangle is the vibration signal. Location.
  • Signal characteristics include vibration frequency, vibration intensity, impact length, moving speed, time, etc.
  • determining multiple tracking targets to be monitored based on vibration signals collected at the first endpoint and the second endpoint includes: performing feature extraction on the vibration signals to obtain vibration features corresponding to the vibration signals, where , the vibration characteristics include at least one of vibration intensity, influence length and vibration time; determine the target vibration signal in the vibration signal according to the vibration characteristics; determine the vibration source corresponding to the target vibration signal as the tracking target.
  • the processor can set a subsampling road section at the first endpoint and the second endpoint, and collect the data through the subsampling road section.
  • the vibration signals determine multiple tracking targets to be monitored.
  • the processor can collect vibration signals at the first endpoint and the second endpoint, and perform feature extraction on the collected vibration signals to obtain vibration features corresponding to the vibration signals, where the vibration features can include vibration intensity of the vibration signal, Vibration affects length as well as vibration time.
  • the processor can determine the target vibration signal in the acquired vibration signal based on the vibration characteristics, and determine the vibration source corresponding to the target vibration signal as the tracking target.
  • the historical average movement speed of each tracking target after generating a visual waterfall chart, determine the historical average movement speed of each tracking target based on the waterfall chart; predict the location of each tracking target at a preset time point based on the historical average movement speed of each tracking target. Predict position; obtain the actual position and actual movement speed of each tracking target at a preset time point; in In the case where the difference between the actual movement speed of the tracking target and the historical average movement speed is greater than the preset difference, it is determined that the movement of the tracking target is abnormal.
  • the processor can determine the historical average movement speed of each tracking target based on the waterfall chart. After obtaining each tracking After obtaining the historical average movement speed of the target, the processor can predict the predicted position of each tracking target at a preset time point based on the historical average movement speed of each tracking target. The processor can obtain the actual position of the tracking target at a preset time point and the corresponding actual movement speed. And compare the actual movement speed with the historical average movement speed. If the difference between the two is greater than the preset difference set by the processor, the processor can determine that the tracking target movement is abnormal.
  • the processor can determine that the historical average movement speed of target A is 15km/h. Based on the historical average movement speed and the displacement data of target A, the processor predicts that target A should be located in ten minutes. Predict the position. After ten minutes, the processor can obtain the actual position of target A, determine the actual movement speed of target A at the actual location based on the actual location, and compare the actual movement speed with the historical average movement speed. In comparison, if the difference between the two is greater than the preset difference set by the processor, the processor can determine that the tracking target motion is abnormal.
  • the vibration characteristics of the target vibration signal are extracted to obtain the target vibration characteristics; the target vibration characteristics are matched with preset reference characteristics to determine the target type of each tracking target, and/or, according to each tracking target
  • the historical average movement speed determines the target type of the tracking target; the displacement mark displayed on the waterfall chart for each tracking target is determined based on the target type of each tracking target.
  • the processor can extract the vibration characteristics of the target vibration signal corresponding to each tracking target to obtain the corresponding target vibration characteristics.
  • the processor can store the vibration characteristics corresponding to different target types and determine the vibration characteristics corresponding to different target types as predetermined values. Set reference features. After extracting the target vibration features, the processor can match the target vibration features with preset reference features stored by the processor to determine the target type of each tracking target.
  • the processor may also determine the target type of each tracking target based on the historical average movement speed of each tracking target. After the processor determines the target type of each tracking target, it can determine the displacement mark corresponding to the target type, and determine the displacement mark of each tracking target displayed on the waterfall chart according to the target type of each tracking target.
  • the displacement markers include multiple shapes, and the shapes correspond to the target types of the tracking targets. The greater the vibration intensity of the target vibration signal corresponding to the tracking target, the darker the color of the displacement markers corresponding to the tracking target.
  • Displacement markers can include a variety of shapes, each corresponding to the target type of the tracked target.
  • the processor can obtain the vibration intensity of the target vibration signal corresponding to the tracking target. The greater the vibration intensity of the target vibration signal corresponding to the tracking target, the darker the color of the unique mark corresponding to the tracking target.
  • the displacement mark corresponding to the tracking target is recovered; when the duration after the target vibration signal disappears exceeds a preset multiple of the occurrence duration of the target vibration signal, the displacement marker is released Recycled displacement markers to mark the displacement data of other tracking targets.
  • the processor can recover the displacement mark corresponding to the tracking target, and determine the duration of the appearance of the target vibration signal and the duration after the target vibration signal disappears. After the processor determines that the target vibration signal disappears, When the duration exceeds the preset multiple of the occurrence duration of the target vibration signal, the recovered unique marker is released to mark the displacement data of other tracking targets. For example, assume that the displacement mark of target A is a triangle, and the target vibration signal corresponding to target A appears for ten minutes. Assume that the processor sets the preset multiple to 5 times. After the target vibration signal corresponding to target A disappears, the processing The processor can recycle the corresponding triangle's displacement mark. After the target vibration signal corresponding to target A disappears for more than fifty minutes, the processor can release the triangle's displacement mark as a displacement mark corresponding to the displacement data of other tracking targets.
  • a processor configured to perform the above-mentioned optical fiber-based multi-target positioning method.
  • the processor can set the section to be monitored as a sampling section above the ground where the optical fiber is laid. Processor settings After the sampling road section is set, the two ends of the sampling road section can be determined as the first endpoint and the second endpoint of the sampling road section. After the processor determines the first endpoint and the second endpoint of the sampling road segment, the processor can set the sub-sampling road segment at the first endpoint and the second endpoint of the sampling road segment.
  • the sub-sampling section collects vibration signals from multiple vibration sources.
  • the processor may perform feature extraction on the vibration signals to obtain vibration features corresponding to the vibration signals, where the vibration features may include vibration The signal's vibration intensity, vibration influence length, and vibration time.
  • the processor can determine the target vibration signal in the acquired vibration signal based on the vibration characteristics, and determine the vibration source corresponding to the target vibration signal as the tracking target. For example, the processor can set a standard threshold for vibration characteristics. After determining that the vibration characteristics of the vibration signal exceed the set standard threshold, the processor determines that the vibration signal corresponding to the vibration characteristic is a valid vibration signal, and assigns the vibration signal corresponding to the vibration signal to a valid vibration signal.
  • the vibration source is determined as the tracking target.
  • the processor extracts vibration features of the collected vibration signals at the first endpoint and the second endpoint, thereby screening the vibration signals and determining the tracking target to be monitored.
  • Each vibration source has characteristics. Different vehicles will have different vibration intensity on the ground surface, which can be separated by vibration frequency, vibration intensity, impact length, moving speed, time, etc. Determined based on vibration characteristics and the position at the last moment. Like video tracking, tracking is achieved by determining the target in the current video and comparing it with the target at the previous moment.
  • the processor After the processor determines the tracking target to be monitored, it can obtain the displacement data of each tracking target, where the displacement data of the tracking target can include time data of the tracking target and position data corresponding to the time.
  • the processor can set multiple sampling points within the set sampling section, and each sampling point includes a vibration sensor.
  • the vibration signal collected at the sampling point can be determined by the vibration sensor.
  • the processor can control the vibration sensor to obtain the vibration intensity of each tracking target collected at each sampling point at the same time point according to the preset frequency. That is, for the same tracking target, the vibration sensor at each sampling point collects the sampling point.
  • the vibration signal that can be received at different locations. Since the location of the tracking target is different, the vibration intensity of the vibration signal collected at each sampling point is also different.
  • the vibration intensity of each tracking target is collected according to the preset frequency.
  • the processor can obtain the vibration intensity collected at each sampling point for the same tracking target.
  • the processor can filter and identify the vibration intensity collected at each sampling point to determine each tracking target. The target position at each time point.
  • the processor can process the displacement data and generate a visual waterfall chart.
  • the processor can extract the vibration characteristics of the target vibration signal corresponding to each tracking target to obtain the corresponding target vibration characteristics.
  • the processor can store the vibration characteristics corresponding to different target types and determine the vibration characteristics corresponding to different target types as predetermined values. Set reference features.
  • the processor can match the target vibration features with preset reference features stored by the processor to determine the target type of each tracking target.
  • the processor may also determine the target type of each tracking target based on the historical average movement speed of each tracking target.
  • the processor After the processor determines the target type of each tracking target, it can determine the displacement mark corresponding to the target type, and determine the displacement mark of each tracking target displayed on the waterfall chart according to the target type of each tracking target. After the processor generates a visual waterfall chart within a preset time period based on the displacement data corresponding to each tracking target, the visual waterfall chart can be used to determine the tracking targets that are displaced at the same position at the same time point within the preset time period, that is, within the preset time period. Tracking target when vibration sources overlap at the same time.
  • the speed can be calculated by dividing the distance by the time. Displayed on the position and time two-digit waterfall chart is the slope corresponding to each tracking target.
  • the tracking process predicts the speed of the next moment based on the historical speed. If it is not at the predicted position at the next moment, it is judged that the motion state of the vibration source has changed, and the next prediction is made again based on the actual position and actual speed.
  • the displacement data of different tracking targets are marked with different displacement markers.
  • the displacement data of the first tracking target 1 is marked with a solid circle, and the second one is marked with an open circle.
  • the displacement data of tracking target 2 is marked with a solid square
  • the displacement data of the third tracking target 3 is marked
  • the displacement data of the fourth tracking target 4 is marked with a diamond.
  • the abscissa axis represents position distance
  • the ordinate axis represents time.
  • the original coordinate is one of the endpoints of the sampling road section and the current time.
  • the ordinate represents the historical moment, as shown in Figure 3, which represents the historical time from 5 o'clock to 6:30.
  • the abscissa represents the distance from the first endpoint of the sampling road section. .
  • the unique data of the tracking target is marked with different displacement markers to obtain a visual waterfall chart of the tracking target, as shown in Figure 3.
  • the visual waterfall chart it can be determined that the displacement data overlaps in 4 places, namely the fourth one.
  • Tracking target 4 overlaps with the first tracking target 1, the fourth tracking target 4 overlaps with the second tracking target 2, the second tracking target 2 overlaps with the third tracking target 3, the first The tracking target 1 overlaps with the third tracking target 3.
  • the waterfall chart we can determine the specific time and location when overlap occurs. Assume that the first endpoint of the sampling road section is determined as the origin.
  • By visualizing the waterfall chart we can determine the distance from the first sampling endpoint at 5:50.
  • An overlap of vibration signals occurs at 3KM, and the overlapping is the fourth tracking target 4 and the first tracking target 1.
  • the processor After the processor obtains the displacement data corresponding to each tracking target, it can obtain the preset time period set by the processor, obtain all tracking targets within the preset time period and the displacement data corresponding to the tracking target, and perform The corresponding displacement data is processed to obtain a visual waterfall chart of the displacement data corresponding to each tracking target within the preset time period.
  • the visual waterfall chart can show the position change data of each tracking target in each unit time within a preset time period.
  • the processor After the processor generates a visual waterfall chart within a preset time period based on the displacement data corresponding to each tracking target, the visual waterfall chart can be used to determine the tracking targets that are displaced at the same position at the same time point within the preset time period, that is, within the preset time period. Tracking target when vibration sources overlap at the same time.
  • the vertical axis is time/t
  • the origin is the current moment
  • the top is the historical moment.
  • the further up the further away in time.
  • the horizontal axis is distance/KM
  • the origin is the installation position of the vibration signal sampling equipment. The farther to the right, the farther away from the installation position of the vibration signal sampling equipment.
  • the displacement data represented by the numbers 1-9 in the figure respectively represent the displacement data corresponding to the first tracking target 1-9, and a, b, c, d, and e in the figure represent the sixth tracking target 6 at different times. Displacement data.
  • the first tracking target 1, the second tracking target 2, the third tracking target 3, and the fourth tracking target 4 are spatially located on the same section of road, where the first tracking target 1, The second tracking target 2 and the third tracking target 3 move in the same direction, and the fourth tracking target 4 moves in the opposite direction to the first tracking target 1, the second tracking target 2, and the third tracking target 3.
  • the processor can also determine the movement speed of each tracked target based on the waterfall chart. The slope of the third tracking target 3 is larger, indicating that the distance moved per unit time is shorter, and the speed is slower than the first tracking target 1 and the second tracking target 2.
  • the second tracking target 2, the third tracking target 3 and the fourth tracking target 4 overlap once at point A and point B respectively, happening simultaneously in time and space, and then leave respectively along their respective trajectories.
  • the fifth tracking target 5 and the ninth tracking target 9 are two events that continuously occur at different locations during the same time period, and are generally recorded as movements of the vertical sensing optical cable.
  • the eighth tracking target 8 uses the same bitmeter mark as the first tracking target 1, but since the time after the vibration signal of the eighth tracking target 8 disappears is five times longer than the time when the vibration signal of the eighth tracking target 8 appears, The displacement marker can therefore be used again.
  • the displacement data of each tracking target can be determined in the waterfall chart of time and position by tracking and recording the tracking target.
  • the identification of the movement trajectory and stay of the overlapping object in time and space in the waterfall chart Achieve marking, display and differentiation of multiple tracking targets.
  • an optical fiber-based multi-target positioning device including the above-mentioned processor.
  • the processor contains a core, which retrieves the corresponding program unit from the memory.
  • One or more kernels can be set, and the fiber-based multi-target positioning method can be implemented by adjusting the kernel parameters.
  • Memory may include non-permanent memory in computer-readable media, random access memory (RAM) and/or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM).
  • RAM random access memory
  • ROM read-only memory
  • flash RAM flash memory
  • Embodiments of the present application provide a storage medium on which a program is stored.
  • the program is executed by a processor, the above optical fiber-based multi-target positioning method is implemented.
  • a computer device is provided.
  • the computer device may be a server, and its internal structure
  • the composition can be shown in Figure 5.
  • the computer device includes a processor A01, a network interface A02, a memory (not shown in the figure) and a database (not shown in the figure) connected through a system bus.
  • the processor A01 of the computer device is used to provide computing and control capabilities.
  • the memory of the computer device includes internal memory A03 and non-volatile storage medium A04.
  • the non-volatile storage medium A04 stores an operating system B01, a computer program B02 and a database (not shown in the figure).
  • the internal memory A03 provides an environment for the execution of the operating system B01 and the computer program B02 in the non-volatile storage medium A04.
  • the computer device's database is used to store vibration signals received by the vibration sensor, as well as related data input by the operator.
  • the network interface A02 of the computer device is used to communicate with external terminals through a network connection.
  • the computer program B02 is executed by the processor A01 to implement an optical fiber-based multi-target positioning method.
  • FIG. 5 is only a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer equipment to which the solution of the present application is applied.
  • the specific computer equipment can May include more or fewer parts than shown, or combine certain parts, or have a different arrangement of parts.
  • Figure 1 is a schematic flowchart of an optical fiber-based multi-target positioning method in one embodiment. It should be understood that although various steps in the flowchart of FIG. 1 are shown in sequence as indicated by arrows, these steps are not necessarily executed in the order indicated by arrows. Unless explicitly stated in this article, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in Figure 1 may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but may be executed at different times. The execution of these sub-steps or stages The sequence is not necessarily sequential, but may be performed in turn or alternately with other steps or sub-steps of other steps or at least part of the stages.
  • the embodiment of the present application provides a device.
  • the device includes a processor, a memory, and a program stored in the memory and executable on the processor.
  • the processor executes the program, it implements the following steps: determine the first endpoint and the third endpoint of the sampling road section. Two endpoints; collect vibration signals from multiple vibration sources at the first endpoint and the second endpoint; determine multiple tracking targets to be monitored in multiple vibration sources based on the vibration signals; obtain the location of each tracking target within the sampling road section Displacement data, where the displacement data includes time data and position data corresponding to time; the displacement data of multiple tracking targets within a preset time period are processed to generate a visual waterfall chart, which indicates each tracking target. Position change data in each unit time.
  • the tracking targets located at the same location at the same time point within the preset time period are determined according to the waterfall chart.
  • multiple sampling points are set up in the sampling road section, and obtaining the displacement data of each tracking target in the sampling road section includes: according to a preset frequency, obtaining each data collected at each sampling point at the same time point. Track the vibration intensity of the target; for each time point, filter and identify the vibration intensity collected at each sampling point to determine the target position of each tracking target at each time point.
  • determining multiple tracking targets to be monitored based on vibration signals collected at the first endpoint and the second endpoint includes: performing feature extraction on the vibration signals to obtain vibration features corresponding to the vibration signals, where , the vibration characteristics include at least one of vibration intensity, influence length and vibration time; determine the target vibration signal in the vibration signal according to the vibration characteristics; determine the vibration source corresponding to the target vibration signal as the tracking target.
  • determining the historical average movement speed of each tracking target based on the waterfall chart after generating a visual waterfall chart, determine the historical average movement speed of each tracking target based on the waterfall chart; predict the location of each tracking target at a preset time point based on the historical average movement speed of each tracking target. Predict the position; obtain the actual position and actual movement speed of each tracking target at a preset time point; when the difference between the actual movement speed of the tracking target and the historical average movement speed is greater than the preset difference, determine Track target motion anomalies.
  • the vibration characteristics of the target vibration signal are extracted to obtain the target vibration characteristics; the target vibration characteristics are matched with preset reference characteristics to determine the target type of each tracking target, and/or, according to each tracking target
  • the historical average movement speed determines the target type of the tracking target; it is determined based on the target type of each tracking target. Displacement markers displayed on the waterfall chart for each tracked target.
  • the matching process is: using the data at the previous moment to predict the data at the next moment. Specifically, at the last moment, the front and back positions of the tracking target are tracked (the tracking target may change its movement direction and speed), and points that are the same as the aforementioned characteristics of the tracking target are found.
  • the displacement markers include multiple shapes, and the shapes correspond to the target types of the tracking targets. The greater the vibration intensity of the target vibration signal corresponding to the tracking target, the darker the color of the displacement markers corresponding to the tracking target.
  • the displacement mark corresponding to the tracking target is recovered; when the duration after the target vibration signal disappears exceeds a preset multiple of the occurrence duration of the target vibration signal, the displacement marker is released Recycled displacement markers to mark the displacement data of other tracking targets.
  • a fiber-based multi-target positioning method includes the following steps:
  • a redundant optical fiber in the communication optical cable laid in the same trench as the sampling road section is used to form a distributed optical fiber vibration sensor based on the coherent Rayleigh principle.
  • the optical cable is a distributed sensor. All points along the optical fiber can collect vibration signals. According to the actual situation, Multiple sampling points are set up on the sampling road section, and the vibration signal of each sampling point is collected using an optical fiber vibration signal detection device. The vibration signal of each sampling point is intelligently analyzed and identified by the signal analysis and identification device to obtain the vibration of each sampling point. data.
  • the optical fiber vibration signal detection device and the signal analysis and identification device are devices in the pipeline optical fiber safety early warning technology.
  • the displacement data includes time data and position data corresponding to the time;
  • S204 Process the displacement data of each tracking target within a preset time period to generate a visual waterfall chart.
  • the waterfall chart displays the position change data of each tracking target in each unit time.
  • At least one tracking target is determined based on all vibration data, including:
  • S2020 Perform feature extraction on all vibration data to obtain at least one vibration feature; wherein each vibration feature includes at least one of vibration intensity, influence length, and vibration time.
  • the first sampling point corresponds to 3 vibration characteristics
  • the second sampling point corresponds to 4 vibration characteristics
  • the third sampling point corresponds to 3 vibration characteristics
  • the preset similarity threshold is set based on actual experience.
  • the above technical solution also includes:
  • each vibration feature can be determined as a target vibration feature, or 9 of them can be selected as target vibration features.
  • the displacement mark includes a variety of shapes, and the target type of each tracking target corresponds to a different shape, and the vibration intensity displayed on the waterfall chart is set according to the vibration intensity of the target vibration characteristics corresponding to each tracking target.
  • the color of the displacement markers Specifically, the greater the vibration intensity of the target vibration signal corresponding to the tracking target, the darker the color of the displacement mark corresponding to the tracking target.
  • the above technical solution also includes:
  • the displacement data of each tracking target within the sampling road section is obtained based on all vibration data, including:
  • S2030 Filter and identify the target vibration data corresponding to each tracking target respectively, and determine the target position of each tracking target at each time point.
  • the above technical solution also includes:
  • the above technical solution also includes:
  • the vibration data of any sampling point includes: the vibration intensity at each sampling moment at the sampling point.
  • an optical fiber-based multi-target positioning device includes a vibration data collection device 201 and a server 202;
  • the data acquisition device 201 is used to obtain vibration data of each sampling point on the sampling road section through optical fiber; the data acquisition device 201 includes an optical fiber vibration signal detection device and a signal analysis and identification device.
  • Server 202 is used for:
  • the displacement data of each tracking target within the sampling road section is obtained.
  • the displacement data includes time data and position data corresponding to the time;
  • the displacement data of each tracking target within a preset time period is processed to generate a visual waterfall chart.
  • the waterfall chart displays the position change data of each tracking target in each unit time.
  • At least one tracking target is determined based on all vibration data, including:
  • each vibration feature includes at least one of vibration intensity, influence length, and vibration time;
  • At least one tracking target is determined from the vibration source corresponding to each target vibration data.
  • the above technical solution also includes:
  • the displacement markers displayed on the waterfall chart for each tracking target are determined based on the target type of each tracking target.
  • the displacement mark includes a variety of shapes, and the target type of each tracking target corresponds to a different shape, and the vibration intensity displayed on the waterfall chart is set according to the vibration intensity of the target vibration characteristics corresponding to each tracking target.
  • the color of the displacement mark specifically, the greater the vibration intensity of the target vibration signal corresponding to the tracking target, the darker the color of the displacement mark corresponding to the tracking target.
  • the above technical solution also includes:
  • the displacement mark corresponding to the tracking target is recovered, and when the duration after the target vibration data corresponding to any tracking target disappears exceeds the preset duration threshold, the displacement mark corresponding to the tracking target is released. Displacement markers for recall.
  • the displacement data of each tracking target within the sampling road section is obtained based on all vibration data, including:
  • the target vibration data corresponding to each tracking target is filtered and identified separately, and the target position of each tracking target at each time point is determined.
  • the above technical solution also includes:
  • the tracking targets located at the same location at the same time point are determined.
  • the above technical solution also includes:
  • a tracking target whose difference between the actual movement speed and the historical average movement speed is greater than the preset difference is determined as a tracking target with abnormal motion.
  • the vibration data of any sampling point includes: the vibration intensity at each sampling moment at the sampling point.
  • embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment that combines software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
  • computer-usable storage media including, but not limited to, disk storage, CD-ROM, optical storage, etc.
  • These computer program instructions may also be stored in a computer or other programmable data processing device that cause a computer or other programmable data processing device to perform a specific manner.
  • a computer-readable memory that operates in a manner such that instructions stored in the computer-readable memory produce an article of manufacture that includes instruction means that implements a process or processes in a flowchart and/or a block or blocks in a block diagram function specified in each box.
  • These computer program instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby executing on the computer or other programmable device.
  • Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.
  • a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
  • processors CPUs
  • input/output interfaces network interfaces
  • memory volatile and non-volatile memory
  • Memory may include non-volatile memory in computer-readable media, random access memory (RAM) and/or non-volatile memory in the form of read-only memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
  • RAM random access memory
  • ROM read-only memory
  • flash RAM flash memory
  • Computer-readable media includes both persistent and non-volatile, removable and non-removable media that can be implemented by any method or technology for storage of information.
  • Information may be computer-readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), and read-only memory.
  • PRAM phase change memory
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • RAM random access memory
  • read-only memory read-only memory
  • ROM read-only memory
  • EEPROM electrically erasable programmable read-only memory
  • flash memory or other memory technology
  • compact disc read-only memory CD-ROM
  • DVD digital versatile disc
  • Magnetic tape cassettes tape magnetic disk storage or other magnetic storage devices or any other non-transmission medium can be used to store information that can be accessed by a computing device.
  • computer-readable media does not include transitory media, such as modulated data signals and carrier waves.

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Abstract

本申请涉及光纤定位领域,具体地涉及一种基于光纤的多目标定位方法、处理器、装置及存储介质。方法包括:确定采样路段的第一端点和第二端点;在第一端点和第二端点处采集多个振动源的振动信号;根据振动信号确定出多个振动源中待监测的多个跟踪目标;获取每个跟踪目标在采样路段内的位移数据,其中,位移数据包括时间数据以及与时间对应的位置数据;对多个跟踪目标在预设时间段内的位移数据进行处理,以生成可视化的瀑布图,瀑布图表明了每个跟踪目标在每个单位时间内的位置变化数据。上述技术方案,通过对跟踪目标的位移数据进行可视化,可以实现对多目标的标记、显示与区分。

Description

基于光纤的多目标定位方法、处理器、装置及存储介质 技术领域
本申请涉及光纤定位领域,具体地涉及一种基于光纤的多目标定位方法、处理器、装置及存储介质。
背景技术
输油管道系统,即用于运送石油及石油产品的管道系统,主要由输油管线、输油站场及其他辅助相关设备组成,是石油储运行业的主要设备之一,也是原油和石油产品最主要的输送设备,与同属于陆上运输方式的铁路和公路输油相比,管道输油具有运量大、密闭性好、成本低和安全系数高等特点。
目前针对管道一般采用基于管道伴行光纤感知沿线振动信号的安全预警系统。管道沿线是开放空间,各种第三方活动频繁。与道路交叉、伴行,为基于管道伴行光缆的振动监测引入过多的振动信号。目前的主要识别方法是通过微观的频率信息进行目标识别,区分机械、人工等特征信息。但是该方法只能进行振动源的检测和定位,当多个振动源同时发生时,无法进行区分。
发明内容
本申请实施例的目的是提供一种可以对多个振动源进行跟踪,并对发生重叠的振动源进行识别的基于光纤的多目标定位方法、处理器、装置及存储介质。
为了实现上述目的,本申请实施例提供一种基于光纤的多目标定位方法,在光纤的上方地面设置待监测的采样路段,方法包括:
确定采样路段的第一端点和第二端点;
在第一端点和第二端点处采集多个振动源的振动信号;
根据振动信号确定出多个振动源中待监测的多个跟踪目标;
获取每个跟踪目标在采样路段内的位移数据,其中,位移数据包括时间数据以及与时间对应的位置数据;
对多个跟踪目标在预设时间段内的位移数据进行处理,以生成可视化的瀑布图,瀑布图表明了每个跟踪目标在每个单位时间内的位置变化数据。
在本申请的实施例中,在生成可视化的瀑布图之后,根据瀑布图确定在预设时间段内在同一时间点位于同一位置的跟踪目标。
在本申请的实施例中,在采样路段内设置多个采样点,获取每个跟踪目标在采样路段内的位移数据包括:按照预设频率,获取同一时间点在每个采样点处采集到的每个跟踪目标的振动强度;针对每个时间点,对每个采样点处采集到的振动强度进行过滤和识别,以确定每个跟踪目标在每个时间点时所处的目标位置。
在本申请的实施例中,根据在第一端点和第二端点处采集到的振动信号确定待监测的多个跟踪目标包括:对振动信号进行特征提取,以得到与振动信号对应的振动特征,其中,振动特征包括振动强度、影响长度以及振动时间中的至少一者;根据振动特征确定振动信号中的目标振动信号;将与目标振动信号对应的振动源确定为跟踪目标。
在本申请的实施例中,在生成可视化的瀑布图之后,根据瀑布图确定每个跟踪目标的历史平均运动速度;根据每个跟踪目标的历史平均运动速度预测每个跟踪目标在预设时间点所在的预测位置;获取每个跟踪目标在预设时间点的实际位置以及实际运动速度;在存在有跟踪目标的实际运动速度与历史平均运动速度之间的差值大于预设差值的情况下,确定跟踪目标运动异常。
在本申请的实施例中,提取目标振动信号的振动特征以得到目标振动特征;将目标振动特征与预设参考特征进行匹配,以确定每个跟踪目标的目标类型,和/或,根据每个跟踪目标的历史平均运动速度确定跟踪目标的目标类型;根据每个跟踪目标的目标类型 确定每个跟踪目标在瀑布图上显示的位移标记。
在本申请的实施例中,位移标记包括多种形状,形状与跟踪目标的目标类型对应,其中,与跟踪目标对应的目标振动信号的震动烈度越大,与跟踪目标对应的位移标记的颜色越深。
在本申请的实施例中,在跟踪目标对应的目标振动信号消失后,回收与跟踪目标对应的位移标记;在目标振动信号消失后的时长超过目标振动信号的出现时长的预设倍数的情况下,释放已回收的位移标记以标记其他的跟踪目标的位移数据。
本申请第二方面提供了一种处理器,被配置成执行上述任意一项的基于光纤的多目标定位方法。
本申请第三方面提供了一种基于光纤的多目标定位装置,包括上述的处理器。
本申请第四方面提供了一种机器可读存储介质,该机器可读存储介质上存储有指令,指令在被处理器执行时使得处理器被配置成执行上述中任一项的基于光纤的多目标定位方法。
本申请第五方面提供了一种基于光纤的多目标定位方法,包括:
通过光纤获取采样路段上每个采样点的振动数据;
根据所有的振动数据确定出至少一个跟踪目标;
根据所有的振动数据,获取每个跟踪目标在采样路段内的位移数据,位移数据包括时间数据以及与时间对应的位置数据;
对每个跟踪目标在预设时间段内的位移数据进行处理,生成可视化的瀑布图,瀑布图上显示每个跟踪目标在每个单位时间内的位置变化数据。
本申请第六方面提供了一种基于光纤的多目标定位装置,包括振动数据采集装置和服务器;
数据采集装置用于:通过光纤获取采样路段上每个采样点的振动数据;
服务器用于:
根据所有的振动数据确定出至少一个跟踪目标;
根据所有的振动数据,获取每个跟踪目标在采样路段内的位移数据,位移数据包括时间数据以及与时间对应的位置数据;
对每个跟踪目标在预设时间段内的位移数据进行处理,生成可视化的瀑布图,瀑布图上显示每个跟踪目标在每个单位时间内的位置变化数据。
通过上述技术方案,通过在采样路段采集多个振动源的振动信号从而确定待监测的跟踪目标,并对每个跟踪目标进行跟踪,从而得到每个跟踪目标的唯一数据,并将位移数据进行处理,生成可视化的瀑布图。通过得到的可视化瀑布图可以实现对多目标的标记、显示与区分。
本申请实施例的其它特征和优点将在随后的具体实施方式部分予以详细说明。
附图说明
附图是用来提供对本申请实施例的进一步理解,并且构成说明书的一部分,与下面的具体实施方式一起用于解释本申请实施例,但并不构成对本申请实施例的限制。在附图中:
图1示意性示出了根据本申请实施例的基于光纤的多目标定位方法的流程示意图之一;
图2示意性示出了根据本申请一实施例的基于光纤的多目标定位方法的示例图;
图3示意性示出了根据本申请一实施例的基于光纤的多目标定位方法的示例图;
图4示意性示出了根据本申请一实施例的基于光纤的多目标定位方法的示例图;
图5示意性示出了根据本申请实施例的计算机设备的内部结构图;
图6示意性示出了根据本申请实施例的基于光纤的多目标定位方法的流程示意图之 二;
图7示意性示出了根据本申请实施例的基于光纤的多目标定位装置的结构示意图;
附图标记说明:
1、第一个跟踪目标对应的位移数据;2、第二个跟踪目标对应的位移数据;3、第三
个跟踪目标对应的位移数据;4、第四个跟踪目标对应的位移数据;5、第五个跟踪目标对应的位移数据;6、第六个跟踪目标对应的位移数据;7、第七个跟踪目标对应的位移数据;8、第八个跟踪目标对应的位移数据;9、第九个跟踪目标对应的位移数据;A、第二个跟踪目标对应的位移数据与第四个跟踪目标对应的位移数据的重叠点;B、第三个跟踪目标对应的位移数据与第四个跟踪目标对应的位移数据的重叠点;a、第六个跟踪目标第一次出现的位移数据;b、第六个跟踪目标第二次出现的位移数据;c、第六个跟踪目标第三次出现的位移数据;d、第六个跟踪目标第四次出现的位移数据;e、第六个跟踪目标第五次出现的位移数据。
具体实施方式
以下结合附图对本申请的具体实施方式进行详细说明。应当理解的是,此处所描述的具体实施方式仅用于说明和解释本申请,并不用于限制本申请。
需要说明,若本申请实施例中有涉及方向性指示(诸如上、下、左、右、前、后……),则该方向性指示仅用于解释在某一特定姿态(如附图所示)下各部件之间的相对位置关系、运动情况等,如果该特定姿态发生改变时,则该方向性指示也相应地随之改变。
另外,若本申请实施例中有涉及“第一”、“第二”等的描述,则该“第一”、“第二”等的描述仅用于描述目的,而不能理解为指示或暗示其相对重要性或者隐含指明所指示的技术特征的数量。由此,限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。另外,各个实施例之间的技术方案可以相互结合,但是必须是以本领域普通技术人员能够实现为基础,当技术方案的结合出现相互矛盾或无法实现时应当认为这种技术方案的结合不存在,也不在本申请要求的保护范围之内。
在一个实施例中,如图1所示,示意性示出了根据本申请实施例的基于光纤的多目标定位方法的流程示意图。如图2所示,在本申请一实施例中,提供了基于光纤的多目标定位方法,包括以下步骤:
S101、确定采样路段的第一端点和第二端点;
S102、在第一端点和第二端点处采集多个振动源的振动信号;
S103、根据振动信号确定出多个振动源中待监测的多个跟踪目标;
S104、获取每个跟踪目标在采样路段内的位移数据,其中,位移数据包括时间数据以及与时间对应的位置数据;
S105、对多个跟踪目标在预设时间段内的位移数据进行处理,以生成可视化的瀑布图,瀑布图表明了每个跟踪目标在每个单位时间内的位置变化数据。
处理器可以在光纤敷设的地面上方设置待进行监测的路段作为采样路段。处理器设置了采样路段后,可以将采样路段的两端确定为采样路段的第一端点与第二端点。在处理器确定了采样路段的第一端点与第二端点后,处理器可以在采样路段的第一端点和第二端点处设置子采样路段,通过第一端点和第二端点处设置的子采样路段采集多个振动源的振动信号,根据采集到的振动源的振动信号确定多个振动源中待监测的多个跟踪目标,在处理器确定了待监测的跟踪目标后,可以获取每个跟踪目标在采样路段内的位移数据,其中,跟踪目标的位移数据可以包括跟踪目标的时间数据以及与时间对应的位置数据。在处理器获得每个跟踪目标对应的位移数据后,可以获取处理器设置的预设时间段,并获取预设时间段内的所有跟踪目标以及跟踪目标对应的位移数据,并对每个跟踪目标对应的位移数据进行处理,从而得到预设时间段内每个跟踪目标对应的位移数据的可视化的瀑布图。可视化瀑布图可以表明每个跟踪目标在预设时间段内每个单位时间内 的位置变化数据。
在一个实施例中,在生成可视化的瀑布图之后,根据瀑布图确定在预设时间段内在同一时间点位于同一位置的跟踪目标。
处理器根据每个跟踪目标对应的位移数据,生成预设时间段内的可视化瀑布图后,可以通过可视化瀑布图确定预设时间段内,在同一时间点位移同一位置的跟踪目标,也就是在同一时间振动源发生重叠时的跟踪目标。
在一个实施例中,在采样路段内设置多个采样点,获取每个跟踪目标在采样路段内的位移数据包括:按照预设频率,获取同一时间点在每个采样点处采集到的每个跟踪目标的振动强度;针对每个时间点,对每个采样点处采集到的振动强度进行过滤和识别,以确定每个跟踪目标在每个时间点时所处的目标位置。
处理器可以在设置的采样路段内设置多个采样点,每个采样点包括振动传感器,可以通过振动传感器确定该采样点采集到的振动信号。处理器可以控制振动传感器按照预设频率获取同一时间点每个采样点处采集到的每个跟踪目标的振动强度,也就是针对同一个跟踪目标,每个采样点的振动传感器采集到该采样点处可接收到的振动信号,由于跟踪目标所处的位置不同,因此,每个采样点采集到的振动信号的振动强度也不同,按照预设频率对每个跟踪目标的振动强度进行采集,针对每个时间点,处理器可以获取到每个采样点采集到的针对同一个跟踪目标的振动强度,处理器可以对每个采样点采集到的振动强度进行过滤和识别,从而确定每个跟踪目标在每个时间点时所处的目标位置。
如图2所示,假设处理器设置的预设频率为每秒1次,假设在第一秒时针对同一个跟踪目标,每个采样点采集到的振动信号的振动强度如图2的柱状图所示,假设图2的原点为采样路段的第一端点,图2的柱状图中横坐标表示采样点的位置距离,纵坐标表示振动信号的振动强度,每一个单独的柱形表示该采样点在同一时刻采集到的同一个跟踪目标的振动强度。由于跟踪目标的位置不同,因此同一时刻每个采样点采集到的振动信号的振动强度不同。获取了每个采样点的振动信号的振动强度后,处理器可以对每个采样点获取的振动信号进行处理,对次强信号进行过滤,从而确定最强点,通过采集到振动信号最强点的采样点对振动源进行确定,从而确定与振动源对应的跟踪目标在采样路段内的目标位置,并确定跟踪目标处于该目标位置时对应的时间,具体地:
光纤采集到每个振动源的振动信号,振动源所在位置的光缆采集到的信号最强,距离稍微远一点的信号呈现指数衰减,一般信号强度呈现等腰三角形,三角形的顶点位置就是振动信号的位置。信号的特征包括振动频率、振动强度、影响长度、移动速度、时间等。
在一个实施例中,根据在第一端点和第二端点处采集到的振动信号确定待监测的多个跟踪目标包括:对振动信号进行特征提取,以得到与振动信号对应的振动特征,其中,振动特征包括振动强度、影响长度以及振动时间中的至少一者;根据振动特征确定振动信号中的目标振动信号;将与目标振动信号对应的振动源确定为跟踪目标。
处理器根据设置的采样路段后,可以将采样路段的端点确定为第一端点和第二端点,处理器可以在第一端点与第二端点处设置子采样路段,通过子采样路段采集到的震动信号确定待监测的多个跟踪目标。处理器可以采集第一端点和第二端点处的振动信号,并对采集得到的振动信号进行特征提取,从而得到与振动信号对应的振动特征,其中,振动特征可以包括震动信号的振动强度、振动影响长度以及振动时间。通过对振动信号的振动特征的提取与识别,处理器可以根据振动特征确定获取的振动信号中的目标振动信号,并将目标振动信号对应的振动源确定为跟踪目标。
在一个实施例中,在生成可视化的瀑布图之后,根据瀑布图确定每个跟踪目标的历史平均运动速度;根据每个跟踪目标的历史平均运动速度预测每个跟踪目标在预设时间点所在的预测位置;获取每个跟踪目标在预设时间点的实际位置以及实际运动速度;在 存在有跟踪目标的实际运动速度与历史平均运动速度之间的差值大于预设差值的情况下,确定跟踪目标运动异常。
处理器对每个跟踪目标在预设时间段内的位移数据进行处理,并生成可视化的瀑布图后,处理器可以根据瀑布图确定每个跟踪目标的历史平均运动速度,在获取到每个跟踪目标的历史平均运动速度后,处理器可以根据每个跟踪目标的历史平均运动速度预测每个跟踪目标在预设时间点所在的预测位置。处理器可以获取跟踪目标在预设时间点的实际位置以及对应的实际运动速度。并将实际运动速度与历史平均运动速度进行对比,若是二者之间的差值大于处理器设置的预设差值,则处理器可以确定该跟踪目标运动异常。例如,假设根据可视化瀑布图,处理器可以确定A目标的历史平均运动速度为15km/h,根据历史平均运动速度,以及A目标的位移数据,处理器预测了A目标在十分钟后应该位于的预测位置,在十分钟后,处理器可以获取A目标的所处的实际位置,并根据所处的实际位置确定A目标在实际位置的实际运动速度,并将实际运动速度与历史平均运动速度进行对比,若是二者之间的差值大于处理器设置的预设差值,则处理器可以确定跟踪目标运动异常。
在一个实施例中,提取目标振动信号的振动特征以得到目标振动特征;将目标振动特征与预设参考特征进行匹配,以确定每个跟踪目标的目标类型,和/或,根据每个跟踪目标的历史平均运动速度确定跟踪目标的目标类型;根据每个跟踪目标的目标类型确定每个跟踪目标在瀑布图上显示的位移标记。
处理器可以对每个跟踪目标对应的目标振动信号的振动特征进行提取,以得到对应的目标振动特征,处理器可以存储不同目标类型对应的振动特征,将不同目标类型对应的振动特征确定为预设参考特征。处理器在提取了目标振动特征后,可以将目标振动特征与处理器存储的预设参考特征进行匹配,以确定每个跟踪目标的目标类型。处理器还可以根据每个跟踪目标的历史平均运动速度来确定每个跟踪目标的目标类型。处理器确定了每个跟踪目标的目标类型后,可以确定与目标类型对应的位移标记,根据每个跟踪目标的目标类型确定每个跟踪目标在瀑布图上显示的位移标记。
在一个实施例中,位移标记包括多种形状,形状与跟踪目标的目标类型对应,其中,与跟踪目标对应的目标振动信号的震动烈度越大,与跟踪目标对应的位移标记的颜色越深。
位移标记可以包括多种形状,每种形状与跟踪目标的目标类型对应。并且,处理器可以获取跟踪目标对应的目标振动信号的震动烈度,跟踪目标对应的目标振动信号的震动烈度越大,与跟踪目标对应的唯一标记的颜色越深。
在一个实施例中,在跟踪目标对应的目标振动信号消失后,回收与跟踪目标对应的位移标记;在目标振动信号消失后的时长超过目标振动信号的出现时长的预设倍数的情况下,释放已回收的位移标记以标记其他的跟踪目标的位移数据。
在跟踪目标对应的目标振动信号消失后,处理器可以回收与跟踪目标对应的位移标记,并确定目标振动信号的出现时长以及目标振动信号消失后的时长,在处理器确定目标振动信号消失后的时长超过目标振动信号的出现时长的预设倍数的情况下,释放已回收的唯一标记以标记其他的跟踪目标的位移数据。例如,假设A目标的位移标记为三角形,A目标对应的目标振动信号出现的时长为十分钟,假设处理器将预设倍数设置为5倍,那么在A目标对应的目标振动信号消失后,处理器可以将对应的三角形的位移标记回收,指导A目标对应的目标振动信号消失时间超过五十分钟后,处理器可以将三角形的位移标记进行释放作为其他跟踪目标的位移数据对应的位移标记。
在一个实施例中,提供了一种处理器,被配置成执行上述的基于光纤的多目标定位方法。
处理器可以在光纤敷设的地面上方设置待进行监测的路段作为采样路段。处理器设 置了采样路段后,可以将采样路段的两端确定为采样路段的第一端点与第二端点。在处理器确定了采样路段的第一端点与第二端点后,处理器可以在采样路段的第一端点和第二端点处设置子采样路段,通过第一端点和第二端点处设置的子采样路段采集多个振动源的振动信号。
对于在第一端点处和第二端点处采集到的多个振动源的振动信号,处理器可以对振动信号进行特征提取,从而得到与振动信号对应的振动特征,其中,振动特征可以包括振动信号的振动强度、振动影响长度以及振动时间。通过对振动信号的振动特征的提取与识别,处理器可以根据振动特征确定获取的振动信号中的目标振动信号,并将目标振动信号对应的振动源确定为跟踪目标。例如,处理器可以设置振动特征的标准阈值,在确定振动信号的振动特征超过了设置的标准阈值,处理器才确定与该振动特征对应的振动信号为有效振动信号,并将该振动信号对应的振动源确定为跟踪目标。处理器通过在第一端点处以及第二端点处对采集到的振动信号的振动特征进行提取,从而对振动信号进行筛选,可以确定了待监测的跟踪目标。
每个振动源都有特征,不同的车辆,其地表的振动强度会不太一样,通过振动频率、振动强度、影响长度、移动速度、时间等可以分开。根据振动特征和上一时刻的位置确定。和视频跟踪一样,确定当前视频中的目标,对比上一时刻的目标,从而实现跟踪。
处理器确定了待监测跟踪目标后,可以获取每个跟踪目标的位移数据,其中,跟踪目标的位移数据可以包括跟踪目标的时间数据以及与时间对应的位置数据。处理器可以在设置的采样路段内设置多个采样点,每个采样点包括振动传感器,可以通过振动传感器确定该采样点采集到的振动信号。处理器可以控制振动传感器按照预设频率获取同一时间点每个采样点处采集到的每个跟踪目标的振动强度,也就是针对同一个跟踪目标,每个采样点的振动传感器采集到该采样点处可接收到的振动信号,由于跟踪目标所处的位置不同,因此,每个采样点采集到的振动信号的振动强度也不同,按照预设频率对每个跟踪目标的振动强度进行采集,针对每个时间点,处理器可以获取到每个采样点采集到的针对同一个跟踪目标的振动强度,处理器可以对每个采样点采集到的振动强度进行过滤和识别,从而确定每个跟踪目标在每个时间点时所处的目标位置。
处理器在获得每个跟踪目标的位移数据后,可以对位移数据进行处理,生成可视化的瀑布图。处理器可以对每个跟踪目标对应的目标振动信号的振动特征进行提取,以得到对应的目标振动特征,处理器可以存储不同目标类型对应的振动特征,将不同目标类型对应的振动特征确定为预设参考特征。处理器在提取了目标振动特征后,可以将目标振动特征与处理器存储的预设参考特征进行匹配,以确定每个跟踪目标的目标类型。处理器还可以根据每个跟踪目标的历史平均运动速度来确定每个跟踪目标的目标类型。处理器确定了每个跟踪目标的目标类型后,可以确定与目标类型对应的位移标记,根据每个跟踪目标的目标类型确定每个跟踪目标在瀑布图上显示的位移标记。处理器根据每个跟踪目标对应的位移数据,生成预设时间段内的可视化瀑布图后,可以通过可视化瀑布图确定预设时间段内,在同一时间点位移同一位置的跟踪目标,也就是在同一时间振动源发生重叠时的跟踪目标。
根据每个跟踪目标在每一个时刻的位置,通过距离除以时间就可以算出速度。在位置和时间二位瀑布图上显示就是每一个跟踪目标对应的斜率。跟踪过程根据历史的速度预测下一个时刻的速度,如果在下一个时刻没有在预测位置则判断该振动源运动状态改变,以实际位置和实际速度重新进行下一次的预测。
如图3所示,针对不同的跟踪目标的位移数据,采用不同的位移标记进行标记,如图3所示,用实心圆标记第一个跟踪目标1的位移数据,用空心圆标记第二个跟踪目标2的位移数据,用实心正方形标记第三个跟踪目标3的位移数据,用菱形标记第四个跟踪目标4的位移数据。横坐标轴表示位置距离,纵坐标轴表示时间,如图3所示,坐标原 点为采样路段的其中一个端点以及当前时刻,纵坐标表示历史时刻,如图3所示,表示5点开始到6点半这段历史时间,横坐标表示距离采样路段的第一端点的距离。通过不同的位移标记对跟踪目标的唯一数据进行标记,以得到跟踪目标的可视化瀑布图,如图3所示,可以通过可视化瀑布图,确定位移数据有4处发生了重叠,分别是第四个跟踪目标4与第一个跟踪目标1发生了重叠,第四个跟踪目标4与第二个跟踪目标2发生了重叠,第二个跟踪目标2与第三个跟踪目标3发生了重叠,第一个跟踪目标1与第三个跟踪目标3发生了重叠。并且通过可视化瀑布图,可以确定发生重叠时的具体时间与位置,假设将采样路段的第一端点确定为原点,通过可视化瀑布图,可以确定在5点50的时刻,距离第一采样端点处3KM处发生了振动信号的重叠,并且发生重叠的是第四个跟踪目标4和第一个跟踪目标1。
在处理器获得每个跟踪目标对应的位移数据后,可以获取处理器设置的预设时间段,并获取预设时间段内的所有跟踪目标以及跟踪目标对应的位移数据,并对每个跟踪目标对应的位移数据进行处理,从而得到预设时间段内每个跟踪目标对应的位移数据的可视化的瀑布图。可视化瀑布图可以表明每个跟踪目标在预设时间段内每个单位时间内的位置变化数据。处理器根据每个跟踪目标对应的位移数据,生成预设时间段内的可视化瀑布图后,可以通过可视化瀑布图确定预设时间段内,在同一时间点位移同一位置的跟踪目标,也就是在同一时间振动源发生重叠时的跟踪目标。
例如图4所示,纵轴为时间/t,原点为当前时刻,上面为历史时刻,越往上距离的时间越远。横轴为距离/KM,原点为振动信号采样设备的安装位置,越往右表示距离设备振动信号采样设备的安装位置越远。图中的数字1-9所表示的位移数据分别表示第一个跟踪目标1-9对应的位移数据,图中的a、b、c、d、e表示第六个跟踪目标6在不同时刻的位移数据。如图4所示,第一个跟踪目标1、第二个跟踪目标2、第三个跟踪目标3、第四个跟踪目标4在空间上位于同一段道路上,其中第一个跟踪目标1、第二个跟踪目标2、第三个跟踪目标3移动方向相同,第四个跟踪目标4与第一个跟踪目标1、第二个跟踪目标2、第三个跟踪目标3的运动方向相反。处理器还可以根据瀑布图确定每个跟踪目标的运动速度。第三个跟踪目标3的斜率更大,表示在单位时间内移动的距离短,速度比第一个跟踪目标1、第二个跟踪目标2慢。同时第二个跟踪目标2、第三个跟踪目标3和第四个跟踪目标4,分别在A点和B点发生一次交叠,在时间上、空间上同时发生,随后沿各自的轨迹分别离开。第五个跟踪目标5和第九个跟踪目标9为同一时间段在不同位置持续发生的2个事件,一般记录为垂直传感光缆发生的运动。第八个跟踪目标8与第一个跟踪目标1使用的位仪标记相同,但是由于第八个跟踪目标8的震动信号消失后的时长超过第八个跟踪目标8出现振动信号的时长5倍,因此该位移标记可以再次使用。
通过上述技术方案,可以通过对跟踪目标进行跟踪、记录,实现在时间与位置的瀑布图中确定每个跟踪目标的位移数据,通过瀑布图中时间、空间交叠物体运动轨迹与停留的标识,实现对多个跟踪目标的标记、显示与区分。
在一个实施例中,提供了一种基于光纤的多目标定位装置,包括根上述的处理器。
处理器中包含内核,由内核去存储器中调取相应的程序单元。内核可以设置一个或以上,通过调整内核参数来实现基于光纤的多目标定位方法。
存储器可能包括计算机可读介质中的非永久性存储器,随机存取存储器(RAM)和/或非易失性内存等形式,如只读存储器(ROM)或闪存(flash RAM),存储器包括至少一个存储芯片。
本申请实施例提供了一种存储介质,其上存储有程序,该程序被处理器执行时实现上述基于光纤的多目标定位方法。
在一个实施例中,提供了一种计算机设备,该计算机设备可以是服务器,其内部结 构图可以如图5所示。该计算机设备包括通过系统总线连接的处理器A01、网络接口A02、存储器(图中未示出)和数据库(图中未示出)。其中,该计算机设备的处理器A01用于提供计算和控制能力。该计算机设备的存储器包括内存储器A03和非易失性存储介质A04。该非易失性存储介质A04存储有操作系统B01、计算机程序B02和数据库(图中未示出)。该内存储器A03为非易失性存储介质A04中的操作系统B01和计算机程序B02的运行提供环境。该计算机设备的数据库用于存储振动传感器接收到的振动信号,以及操作人员输入的相关数据。该计算机设备的网络接口A02用于与外部的终端通过网络连接通信。该计算机程序B02被处理器A01执行时以实现一种基于光纤的多目标定位方法。
本领域技术人员可以理解,图5中示出的结构,仅仅是与本申请方案相关的部分结构的框图,并不构成对本申请方案所应用于其上的计算机设备的限定,具体的计算机设备可以包括比图中所示更多或更少的部件,或者组合某些部件,或者具有不同的部件布置。
图1为一个实施例中基于光纤的多目标定位方法的流程示意图。应该理解的是,虽然图1的流程图中的各个步骤按照箭头的指示依次显示,但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明,这些步骤的执行并没有严格的顺序限制,这些步骤可以以其它的顺序执行。而且,图1中的至少一部分步骤可以包括多个子步骤或者多个阶段,这些子步骤或者阶段并不必然是在同一时刻执行完成,而是可以在不同的时刻执行,这些子步骤或者阶段的执行顺序也不必然是依次进行,而是可以与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。
本申请实施例提供了一种设备,设备包括处理器、存储器及存储在存储器上并可在处理器上运行的程序,处理器执行程序时实现以下步骤:确定采样路段的第一端点和第二端点;在第一端点和第二端点处采集多个振动源的振动信号;根据振动信号确定出多个振动源中待监测的多个跟踪目标;获取每个跟踪目标在采样路段内的位移数据,其中,位移数据包括时间数据以及与时间对应的位置数据;对多个跟踪目标在预设时间段内的位移数据进行处理,以生成可视化的瀑布图,瀑布图表明了每个跟踪目标在每个单位时间内的位置变化数据。
在一个实施例中,在生成可视化的瀑布图之后,根据瀑布图确定在预设时间段内在同一时间点位于同一位置的跟踪目标。
在一个实施例中,在采样路段内设置多个采样点,获取每个跟踪目标在采样路段内的位移数据包括:按照预设频率,获取同一时间点在每个采样点处采集到的每个跟踪目标的振动强度;针对每个时间点,对每个采样点处采集到的振动强度进行过滤和识别,以确定每个跟踪目标在每个时间点时所处的目标位置。
在一个实施例中,根据在第一端点和第二端点处采集到的振动信号确定待监测的多个跟踪目标包括:对振动信号进行特征提取,以得到与振动信号对应的振动特征,其中,振动特征包括振动强度、影响长度以及振动时间中的至少一者;根据振动特征确定振动信号中的目标振动信号;将与目标振动信号对应的振动源确定为跟踪目标。
在一个实施例中,在生成可视化的瀑布图之后,根据瀑布图确定每个跟踪目标的历史平均运动速度;根据每个跟踪目标的历史平均运动速度预测每个跟踪目标在预设时间点所在的预测位置;获取每个跟踪目标在预设时间点的实际位置以及实际运动速度;在存在有跟踪目标的实际运动速度与历史平均运动速度之间的差值大于预设差值的情况下,确定跟踪目标运动异常。
在一个实施例中,提取目标振动信号的振动特征以得到目标振动特征;将目标振动特征与预设参考特征进行匹配,以确定每个跟踪目标的目标类型,和/或,根据每个跟踪目标的历史平均运动速度确定跟踪目标的目标类型;根据每个跟踪目标的目标类型确定 每个跟踪目标在瀑布图上显示的位移标记。
匹配过程为:用前一个时刻的数据预测下一个时刻的数据。具体在上一时刻是跟踪目标的前后位置(跟踪目标可能改变运动方向和运动速度),找与该跟踪目标的前述特征相同的点。
在一个实施例中,位移标记包括多种形状,形状与跟踪目标的目标类型对应,其中,与跟踪目标对应的目标振动信号的震动烈度越大,与跟踪目标对应的位移标记的颜色越深。
在一个实施例中,在跟踪目标对应的目标振动信号消失后,回收与跟踪目标对应的位移标记;在目标振动信号消失后的时长超过目标振动信号的出现时长的预设倍数的情况下,释放已回收的位移标记以标记其他的跟踪目标的位移数据。
如图6所示,本发明实施例的一种基于光纤的多目标定位方法,包括如下步骤:
S201、通过光纤获取采样路段上每个采样点的振动数据,具体地:
利用与采样路段同沟敷设通信光缆中冗余的一根光纤,基于相干瑞利原理构成分布式光纤振动传感器,光缆是分布式传感器,光纤沿线所有的点都可以采集振动信号,根据实际情况在采样路段设置多个采样点,利用光纤振动信号检测装置采集每个采样点的振动信号,通过信号分析与识别装置对每个采样点的振动信号的智能分析和识别,得到每个采样点的振动数据。光纤振动信号检测装置和信号分析与识别装置为管道光纤安全预警技术中的装置。
S202、根据所有的振动数据确定出至少一个跟踪目标;
S203、根据所有的振动数据,获取每个跟踪目标在采样路段内的位移数据,位移数据包括时间数据以及与时间对应的位置数据;
S204、对每个跟踪目标在预设时间段内的位移数据进行处理,生成可视化的瀑布图,瀑布图上显示每个跟踪目标在每个单位时间内的位置变化数据。
可选地,在上述技术方案中,S202中,根据所有的振动数据确定出至少一个跟踪目标,包括:
S2020、对所有的振动数据进行特征提取,得到至少一个振动特征;其中,每个振动特征包括振动强度、影响长度以及振动时间中的至少一者。
例如,共设置3个采样点,第一个采样点对应的振动特征为3个,第二个采样点对应的振动特征为4个,第三个采样点对应的振动特征为3个,那么:
1)将这10个振动特征进行随机排序,计算第一个振动特征与第二个振动特征之间的相似度,判断该相似度是否大于预设相似度阈值,若是,则判断第一个振动特征与第二振动特征是相同的,去除第一个振动特征与第二个振动特征中的任意一个,然后,计算第一个振动特征与第二个振动特征中的剩余的振动特征与第三个振动特征之间的相似度,然后继续与预设相似度阈值进行比较,若否,则判定第一个振动特征与第二振动特征是不同的,则判定第一个振动特征与第二个振动特征是不同的,然后,计算第一个振动特征、第二个振动特征分别和第三个振动特征之间的相似度,然后继续与预设相似度阈值进行比较,依次类推,得到多个振动特征,即为所有的振动数据对应的振动特征。预设相似度阈值根据实际经验设置。
2)计算这10个振动特征中每两个振动特征之间的相似度,根据相似度的大小,将10个振动特征进行分组,每组中的每两个振动特征之间的相似度均大于预设相似度阈值,需要说明的是,可能出现只包括一个振动特征的组,将包括至少两个振动特征的组进行随机删除,最后每个组中只剩余一个振动特征,所有的振动数据对应的振动特征即为每个组中剩余的一个振动特征。
S2021、从所有振动数据中确定每个振动特征对应的目标振动数据;
S2022、将每个目标振动数据对应的振动源中确定出至少一个跟踪目标。
可选地,在上述技术方案中,还包括:
S205、从所有的振动特征中确定至少一个目标振动特征;
例如,S2020中,所有的振振动特征为10个,可将每个振动特征均确定为目标振动特征,也可选取其中9个作为目标振动特征。
S206、分别将每个目标振动特征与多个预设参考特征进行匹配,确定每个跟踪目标的目标类型,和/或,根据每个跟踪目标的历史平均运动速度确定跟踪目标的目标类型;
S207、根据每个跟踪目标的目标类型确定每个跟踪目标在瀑布图上显示的位移标记。
可选地,在上述技术方案中,位移标记包括多种形状,每个跟踪目标的目标类型对应不同形状,且根据每个跟踪目标对应的目标振动特征的震动烈度,设置在瀑布图上显示的位移标记的颜色。具体地,与跟踪目标对应的目标振动信号的震动烈度越大,与跟踪目标对应的位移标记的颜色越深。
可选地,在上述技术方案中,还包括:
S208、在任一跟踪目标对应的目标振动数据消失后,回收该跟踪目标对应的位移标记,且在该任一跟踪目标对应的目标振动数据消失后的时长超过预设时长阈值时,释放该跟踪目标对应的位移标记,以供重新调用。
可选地,在上述技术方案中,S203中,根据所有的振动数据,获取每个跟踪目标在采样路段内的位移数据,包括:
S2030、对每个跟踪目标对应的目标振动数据分别进行过滤和识别,确定每个跟踪目标在每个时间点时所处的目标位置。
可选地,在上述技术方案中,还包括:
S209、根据瀑布图,确定在同一时间点位于同一位置的跟踪目标。
可选地,在上述技术方案中,还包括:
S210、根据瀑布图,确定每个跟踪目标的历史平均运动速度;
S211、根据每个跟踪目标的历史平均运动速度预测每个跟踪目标在预设时间点所在的预测位置;
S212、获取每个跟踪目标在预设时间点的实际位置以及实际运动速度;
S213、将实际运动速度与历史平均运动速度之间的差值大于预设差值的跟踪目标,确定为运动异常的跟踪目标。
可选地,在上述技术方案中,任一采样点的振动数据包括:该采样点处的每个采样时刻的振动强度。
本发明实施例的一种基于光纤的多目标定位方法的具体实现过程,参见上文,在此不做赘述。
如图7所示,本发明实施例的一种基于光纤的多目标定位装置,包括振动数据采集装置201和服务器202;
数据采集装置201用于:通过光纤获取采样路段上每个采样点的振动数据;数据采集装置201包括光纤振动信号检测装置和信号分析与识别装置。
服务器202用于:
根据所有的振动数据确定出至少一个跟踪目标;
根据所有的振动数据,获取每个跟踪目标在采样路段内的位移数据,位移数据包括时间数据以及与时间对应的位置数据;
对每个跟踪目标在预设时间段内的位移数据进行处理,生成可视化的瀑布图,瀑布图上显示每个跟踪目标在每个单位时间内的位置变化数据。
可选地,在上述技术方案中,根据所有的振动数据确定出至少一个跟踪目标,包括:
对所有的振动数据进行特征提取,得到至少一个振动特征;其中,每个振动特征包括振动强度、影响长度以及振动时间中的至少一者;
从所有振动数据中确定每个振动特征对应的目标振动数据;
将每个目标振动数据对应的振动源中确定出至少一个跟踪目标。
可选地,在上述技术方案中,还包括:
从所有的振动特征中确定至少一个目标振动特征;
分别将每个目标振动特征与多个预设参考特征进行匹配,确定每个跟踪目标的目标类型,和/或,根据每个跟踪目标的历史平均运动速度确定跟踪目标的目标类型;
根据每个跟踪目标的目标类型确定每个跟踪目标在瀑布图上显示的位移标记。
可选地,在上述技术方案中,位移标记包括多种形状,每个跟踪目标的目标类型对应不同形状,且根据每个跟踪目标对应的目标振动特征的震动烈度,设置在瀑布图上显示的位移标记的颜色,具体地,与跟踪目标对应的目标振动信号的震动烈度越大,与跟踪目标对应的位移标记的颜色越深。
可选地,在上述技术方案中,还包括:
在任一跟踪目标对应的目标振动数据消失后,回收该跟踪目标对应的位移标记,且在该任一跟踪目标对应的目标振动数据消失后的时长超过预设时长阈值时,释放该跟踪目标对应的位移标记,以供重新调用。
可选地,在上述技术方案中,根据所有的振动数据,获取每个跟踪目标在采样路段内的位移数据,包括:
对每个跟踪目标对应的目标振动数据分别进行过滤和识别,确定每个跟踪目标在每个时间点时所处的目标位置。
可选地,在上述技术方案中,还包括:
根据瀑布图,确定在同一时间点位于同一位置的跟踪目标。
可选地,在上述技术方案中,还包括:
根据瀑布图,确定每个跟踪目标的历史平均运动速度;
根据每个跟踪目标的历史平均运动速度预测每个跟踪目标在预设时间点所在的预测位置;
获取每个跟踪目标在预设时间点的实际位置以及实际运动速度;
将实际运动速度与历史平均运动速度之间的差值大于预设差值的跟踪目标,确定为运动异常的跟踪目标。
可选地,在上述技术方案中,任一采样点的振动数据包括:该采样点处的每个采样时刻的振动强度。
本发明实施例的一种基于光纤的多目标定位装置的具体实现过程,参见上文,在此不做赘述。
本领域内的技术人员应明白,本申请的实施例可提供为方法、系统、或计算机程序产品。因此,本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且,本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本申请是参照根据本申请实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器,使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方 式工作的计算机可读存储器中,使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品,该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上,使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理,从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
在一个典型的配置中,计算设备包括一个或多个处理器(CPU)、输入/输出接口、网络接口和内存。
存储器可能包括计算机可读介质中的非永久性存储器,随机存取存储器(RAM)和/或非易失性内存等形式,如只读存储器(ROM)或闪存(flash RAM)。存储器是计算机可读介质的示例。
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括,但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带,磁带磁磁盘存储或其他磁性存储设备或任何其他非传输介质,可用于存储可以被计算设备访问的信息。按照本文中的界定,计算机可读介质不包括暂存电脑可读媒体(transitory media),如调制的数据信号和载波。
还需要说明的是,术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含,从而使得包括一系列要素的过程、方法、商品或者设备不仅包括那些要素,而且还包括没有明确列出的其他要素,或者是还包括为这种过程、方法、商品或者设备所固有的要素。在没有更多限制的情况下,由语句“包括一个……”限定的要素,并不排除在包括要素的过程、方法、商品或者设备中还存在另外的相同要素。
以上仅为本申请的实施例而已,并不用于限制本申请。对于本领域技术人员来说,本申请可以有各种更改和变化。凡在本申请的精神和原理之内所作的任何修改、等同替换、改进等,均应包含在本申请的权利要求范围之内。

Claims (29)

  1. 一种基于光纤的多目标定位方法,其特征在于,在所述光纤的上方地面设置待监测的采样路段,所述方法包括:
    确定所述采样路段的第一端点和第二端点;
    在所述第一端点和所述第二端点处采集多个振动源的振动信号;
    根据所述振动信号确定出所述多个振动源中待监测的多个跟踪目标;
    获取每个跟踪目标在所述采样路段内的位移数据,其中,所述位移数据包括时间数据以及与所述时间对应的位置数据;
    对所述多个跟踪目标在预设时间段内的位移数据进行处理,以生成可视化的瀑布图,所述瀑布图表明了每个跟踪目标在每个单位时间内的位置变化数据。
  2. 根据权利要求1所述的一种基于光纤的多目标定位方法,其特征在于,所述方法还包括:
    在生成可视化的瀑布图之后,根据所述瀑布图确定在所述预设时间段内在同一时间点位于同一位置的跟踪目标。
  3. 根据权利要求1所述的基于光纤的多目标定位方法,其特征在于,在所述采样路段内设置多个采样点,所述获取每个跟踪目标在所述采样路段内的位移数据包括:
    按照预设频率,获取同一时间点在每个采样点处采集到的每个跟踪目标的振动强度;
    针对每个时间点,对每个采样点处采集到的振动强度进行过滤和识别,以确定每个跟踪目标在每个时间点时所处的目标位置。
  4. 根据权利要求1所述的一种基于光纤的多目标定位方法,其特征在于,所述根据在所述第一端点和所述第二端点处采集到的振动信号确定待监测的多个跟踪目标包括:
    对所述振动信号进行特征提取,以得到与所述振动信号对应的振动特征,其中,所述振动特征包括振动强度、影响长度以及振动时间中的至少一者;
    根据所述振动特征确定所述振动信号中的目标振动信号;
    将与所述目标振动信号对应的振动源确定为跟踪目标。
  5. 根据权利要求1所述的一种基于光纤的多目标定位方法,其特征在于,所述方法还包括:
    在生成可视化的瀑布图之后,根据所述瀑布图确定每个跟踪目标的历史平均运动速度;
    根据每个跟踪目标的历史平均运动速度预测每个跟踪目标在预设时间点所在的预测位置;
    获取每个跟踪目标在所述预设时间点的实际位置以及实际运动速度;
    在存在有跟踪目标的实际运动速度与所述历史平均运动速度之间的差值大于预设差值的情况下,确定所述跟踪目标运动异常。
  6. 根据权利要求4或5所述的一种基于光纤的多目标定位方法,其特征在于,所述方法还包括:
    提取所述目标振动信号的振动特征以得到目标振动特征;
    将所述目标振动特征与预设参考特征进行匹配,以确定每个跟踪目标的目标类型,和/或,根据每个跟踪目标的历史平均运动速度确定所述跟踪目标的目标类型;
    根据每个跟踪目标的目标类型确定每个跟踪目标在所述瀑布图上显示的位移标记。
  7. 根据权利要求6所述的一种基于光纤的多目标定位方法,其特征在于,所述位移标记包括多种形状,所述形状与所述跟踪目标的目标类型对应,其中,与所述跟踪目标对应的目标振动信号的震动烈度越大,与所述跟踪目标对应的位移标记的颜色越深。
  8. 根据权利要求7所述的一种基于光纤的多目标定位方法,其特征在于,所述方 法还包括:
    在所述跟踪目标对应的目标振动信号消失后,回收与所述跟踪目标对应的位移标记;
    在所述目标振动信号消失后的时长超过所述目标振动信号的出现时长的预设倍数的情况下,释放已回收的位移标记以标记其他的跟踪目标的位移数据。
  9. 一种处理器,其特征在于,被配置成执行根据权利要求1至8中任意一项所述的基于光纤的多目标定位方法。
  10. 一种基于光纤的多目标定位装置,其特征在于,包括根据权利要求9所述的处理器。
  11. 一种机器可读存储介质,该机器可读存储介质上存储有指令,其特征在于,该指令在被处理器执行时使得所述处理器被配置成执行根据权利要求1至8中任一项所述的基于光纤的多目标定位方法。
  12. 一种基于光纤的多目标定位方法,其特征在于,包括:
    通过光纤获取采样路段上每个采样点的振动数据;
    根据所有的振动数据确定出至少一个跟踪目标;
    根据所有的振动数据,获取每个跟踪目标在所述采样路段内的位移数据,所述位移数据包括时间数据以及与所述时间对应的位置数据;
    对每个跟踪目标在预设时间段内的位移数据进行处理,生成可视化的瀑布图,所述瀑布图上显示每个跟踪目标在每个单位时间内的位置变化数据。
  13. 根据权利要求12所述的一种基于光纤的多目标定位方法,其特征在于,根据所有的振动数据确定出至少一个跟踪目标,包括:
    对所有的振动数据进行特征提取,得到至少一个振动特征;其中,每个振动特征包括振动强度、影响长度以及振动时间中的至少一者;
    从所有振动数据中确定每个振动特征对应的目标振动数据;
    将每个目标振动数据对应的振动源中确定出至少一个跟踪目标。
  14. 根据权利要求13所述的一种基于光纤的多目标定位方法,其特征在于,还包括:
    从所有的振动特征中确定至少一个目标振动特征;
    分别将每个目标振动特征与多个预设参考特征进行匹配,确定每个跟踪目标的目标类型,和/或,根据每个跟踪目标的历史平均运动速度确定所述跟踪目标的目标类型;
    根据每个跟踪目标的目标类型确定每个跟踪目标在所述瀑布图上显示的位移标记。
  15. 根据权利要求14所述的一种基于光纤的多目标定位方法,其特征在于,所述位移标记包括多种形状,每个跟踪目标的目标类型对应不同形状,且根据每个跟踪目标对应的目标振动特征的震动烈度,设置在所述瀑布图上显示的位移标记的颜色。
  16. 根据权利要求15所述的一种基于光纤的多目标定位方法,其特征在于,还包括:
    在任一跟踪目标对应的目标振动数据消失后,回收该跟踪目标对应的位移标记,且在该任一跟踪目标对应的目标振动数据消失后的时长超过预设时长阈值时,释放该跟踪目标对应的位移标记,以供重新调用。
  17. 根据权利要求12至16任一项所述的一种基于光纤的多目标定位方法,其特征在于,根据所有的振动数据,获取每个跟踪目标在所述采样路段内的位移数据,包括:
    对每个跟踪目标对应的目标振动数据分别进行过滤和识别,确定每个跟踪目标在每个时间点时所处的目标位置。
  18. 根据权利要求12至16任一项所述的一种基于光纤的多目标定位方法,其特征在于,还包括:
    根据所述瀑布图,确定在同一时间点位于同一位置的跟踪目标。
  19. 根据权利要求12至16任一项所述的一种基于光纤的多目标定位方法,其特征在于,还包括:
    根据所述瀑布图,确定每个跟踪目标的历史平均运动速度;
    根据每个跟踪目标的历史平均运动速度预测每个跟踪目标在预设时间点所在的预测位置;
    获取每个跟踪目标在所述预设时间点的实际位置以及实际运动速度;
    将实际运动速度与历史平均运动速度之间的差值大于预设差值的跟踪目标,确定为运动异常的跟踪目标。
  20. 根据权利要求12至16任一项所述的一种基于光纤的多目标定位方法,其特征在于,任一采样点的振动数据包括:该采样点处的每个采样时刻的振动强度。
  21. 一种基于光纤的多目标定位装置,其特征在于,包括振动数据采集装置和服务器;
    所述数据采集装置用于:通过光纤获取采样路段上每个采样点的振动数据;
    所述服务器用于:
    根据所有的振动数据确定出至少一个跟踪目标;
    根据所有的振动数据,获取每个跟踪目标在所述采样路段内的位移数据,所述位移数据包括时间数据以及与所述时间对应的位置数据;
    对每个跟踪目标在预设时间段内的位移数据进行处理,生成可视化的瀑布图,所述瀑布图上显示每个跟踪目标在每个单位时间内的位置变化数据。
  22. 根据权利要求21所述的一种基于光纤的多目标定位装置,其特征在于,根据所有的振动数据确定出至少一个跟踪目标,包括:
    对所有的振动数据进行特征提取,得到至少一个振动特征,其中,每个振动特征包括振动强度、影响长度以及振动时间中的至少一者;
    从所有振动数据中确定每个振动特征对应的目标振动数据;
    将每个目标振动数据对应的振动源中确定出至少一个跟踪目标。
  23. 根据权利要求22所述的一种基于光纤的多目标定位装置,其特征在于,还包括:
    从所有的振动特征中确定至少一个目标振动特征;
    分别将每个目标振动特征与多个预设参考特征进行匹配,确定每个跟踪目标的目标类型,和/或,根据每个跟踪目标的历史平均运动速度确定所述跟踪目标的目标类型;
    根据每个跟踪目标的目标类型确定每个跟踪目标在所述瀑布图上显示的位移标记。
  24. 根据权利要求23所述的一种基于光纤的多目标定位装置,其特征在于,所述位移标记包括多种形状,每个跟踪目标的目标类型对应不同形状,且根据每个跟踪目标对应的目标振动特征的震动烈度,设置在所述瀑布图上显示的位移标记的颜色。
  25. 根据权利要求24所述的一种基于光纤的多目标定位装置,其特征在于,还包括:
    在任一跟踪目标对应的目标振动数据消失后,回收该跟踪目标对应的位移标记,且在该任一跟踪目标对应的目标振动数据消失后的时长超过预设时长阈值时,释放该跟踪目标对应的位移标记,以供重新调用。
  26. 根据权利要求21至25任一项所述的一种基于光纤的多目标定位装置,其特征在于,根据所有的振动数据,获取每个跟踪目标在所述采样路段内的位移数据,包括:
    对每个跟踪目标对应的目标振动数据分别进行过滤和识别,确定每个跟踪目标在每个时间点时所处的目标位置。
  27. 根据权利要求21至25任一项所述的一种基于光纤的多目标定位装置,其特征在于,还包括:
    根据所述瀑布图,确定在同一时间点位于同一位置的跟踪目标。
  28. 根据权利要求21至25任一项所述的一种基于光纤的多目标定位装置,其特征在于,还包括:
    根据所述瀑布图,确定每个跟踪目标的历史平均运动速度;
    根据每个跟踪目标的历史平均运动速度预测每个跟踪目标在预设时间点所在的预测位置;
    获取每个跟踪目标在所述预设时间点的实际位置以及实际运动速度;
    将实际运动速度与历史平均运动速度之间的差值大于预设差值的跟踪目标,确定为运动异常的跟踪目标。
  29. 根据权利要求21至25任一项所述的一种基于光纤的多目标定位装置,其特征在于,任一采样点的振动数据包括:该采样点处的每个采样时刻的振动强度。
PCT/CN2023/114818 2022-09-05 2023-08-25 基于光纤的多目标定位方法、处理器、装置及存储介质 WO2024051501A1 (zh)

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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190227184A1 (en) * 2018-01-22 2019-07-25 Schlumberger Technology Corporation Gauge length optimization for signal preservation and gauge length processing for distributed vibration sensing
CN111147133A (zh) * 2019-12-24 2020-05-12 武汉理工光科股份有限公司 一种基于φ-OTDR的车流量实时监测系统及方法
CN111854921A (zh) * 2020-07-28 2020-10-30 武汉理工光科股份有限公司 一种分布式光纤减速带振动预警系统及方法
CN113531399A (zh) * 2020-04-16 2021-10-22 中国石油天然气股份有限公司 管道监测方法、管道监测装置、计算机设备及存储介质
CN113532619A (zh) * 2020-04-16 2021-10-22 中国石油天然气股份有限公司 管道监测方法、管道监测装置及计算机设备
CN115597698A (zh) * 2022-09-05 2023-01-13 国家石油天然气管网集团有限公司(Cn) 基于光纤的多目标定位方法、处理器、装置及存储介质

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190227184A1 (en) * 2018-01-22 2019-07-25 Schlumberger Technology Corporation Gauge length optimization for signal preservation and gauge length processing for distributed vibration sensing
CN111147133A (zh) * 2019-12-24 2020-05-12 武汉理工光科股份有限公司 一种基于φ-OTDR的车流量实时监测系统及方法
CN113531399A (zh) * 2020-04-16 2021-10-22 中国石油天然气股份有限公司 管道监测方法、管道监测装置、计算机设备及存储介质
CN113532619A (zh) * 2020-04-16 2021-10-22 中国石油天然气股份有限公司 管道监测方法、管道监测装置及计算机设备
CN111854921A (zh) * 2020-07-28 2020-10-30 武汉理工光科股份有限公司 一种分布式光纤减速带振动预警系统及方法
CN115597698A (zh) * 2022-09-05 2023-01-13 国家石油天然气管网集团有限公司(Cn) 基于光纤的多目标定位方法、处理器、装置及存储介质

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