Data processing method, device, equipment and medium based on pantograph-catenary detection device

Abstract

The present invention discloses a data processing method, device, equipment and medium based on a bow-net detection device; in this solution, the various devices in the bow-net detection device are divided into a hardware device group with the same data acquisition frequency, and an independent hardware device with an independent data acquisition frequency, and each device records the detection data based on a unified time reference. In this way, the detection data of various hardware devices can be effectively integrated and processed, and the bow-net detection device can better play a guiding role in the detection of the bow-net status of urban rail transit.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and more specifically, to a data processing method, device, equipment and medium based on a pantograph-catenary detection device. Background Art

[0002] In urban rail transit, the physical state of the vehicle pantograph and catenary, as well as their contact state, are crucial for safe and stable vehicle operation. To promptly understand and monitor the status of the line contact wire and vehicle pantograph, urban rail transit vehicles are increasingly using onboard pantograph-catenary detection devices to perform real-time detection, monitoring, and recording of pantograph-catenary status.

[0003] The pantograph-catenary inspection devices currently in use primarily include detection capabilities for catenary geometry, vehicle vibration, contact wire wear, hard spots, arcing, pantograph-catenary contact force, pantograph-catenary temperature, and pantograph anomalies. Existing pantograph-catenary inspection devices typically utilize hardware devices such as visible light cameras, infrared cameras, structured light cameras, and various sensors to implement these various inspection functions. However, due to the large number of hardware devices involved, each with its own distinct detection principles and frequencies, the data generated during operation differs in the form of data presented. This hinders the effectiveness of the pantograph-catenary inspection devices in guiding urban rail transit pantograph-catenary status monitoring. Summary of the Invention

[0004] The purpose of the present invention is to provide a data processing method, device, equipment and medium based on a bow-net detection device, so as to effectively process the detection data of various hardware devices.

[0005] To achieve the above-mentioned purpose, the present invention provides a data processing method based on a pantograph-catenary detection device, comprising:

[0006] Determining a hardware device group from the pantograph-catenary detection device, wherein each hardware device in each hardware device group has the same data acquisition frequency;

[0007] Determining independent hardware devices from the pantograph-catenary detection device, each independent hardware device having an independent data acquisition frequency;

[0008] When the pantograph-catenary detection device is in operation, each hardware device collects detection data according to a corresponding data collection frequency and records the data based on a unified time reference.

[0009] Wherein, determining the hardware device group from the pantograph-catenary detection device includes:

[0010] The visible light camera and the infrared camera in the pantograph-catenary detection device are set as a first group of hardware devices, and the first group of hardware devices are set to collect data according to the same first data collection frequency.

[0011] Among them, setting the first group of hardware devices to collect data according to the same first data collection frequency includes: setting a first trigger source corresponding to the first group of hardware devices, so as to control the first group of hardware devices to collect data according to the same first data collection frequency through the first trigger source.

[0012] Among them, determining the hardware equipment group from the bow-net detection device includes: setting the geometric parameter detection equipment and the vehicle body vibration detection equipment in the bow-net detection device as a second group of hardware equipment, and setting the second group of hardware equipment to collect data according to the same second data collection frequency.

[0013] Among them, setting the second group of hardware devices to collect data according to the same second data collection frequency includes: setting a second trigger source corresponding to the second group of hardware devices, so as to control the second group of hardware devices to collect data according to the same second data collection frequency through the second trigger source.

[0014] Wherein, determining the independent hardware device from the pantograph-catenary detection device includes: setting the wear detection device in the pantograph-catenary detection device as an independent hardware device; and setting the wear detection device to collect data through a third data collection frequency.

[0015] Wherein, the determining of the independent hardware device from the bow-catenary detection device includes: setting the ultraviolet sensor in the bow-catenary detection device as an independent hardware device, and the data acquisition frequency of the ultraviolet sensor is triggered according to the change of external parameters.

[0016] Wherein, determining the independent hardware device from the bow-catenary detection device includes: setting the optical fiber sensor in the bow-catenary detection device as an independent hardware device, and the data acquisition frequency of the optical fiber sensor is triggered according to the change of external parameters.

[0017] Each of the hardware devices collects detection data according to a corresponding data collection frequency and records the data based on a unified time reference, further comprising:

[0018] Performing interpolation processing on the detection data collected by the geometric parameter detection device to obtain geometric parameter detection data corresponding to each millisecond;

[0019] The wear detection data corresponding to each millisecond collected by the wear detection device is corrected using the geometric parameter detection data corresponding to each millisecond.

[0020] Among them, after each hardware device collects detection data according to the corresponding data collection frequency and records it based on a unified time base, it also includes: arranging the detection data collected by each hardware device in order according to the collection time and displaying it.

[0021] To achieve the above objectives, the present invention further provides a structural diagram of a data processing device based on a pantograph-catenary detection device, comprising:

[0022] A first determining module is used to determine a hardware device group from the pantograph-catenary detection device, wherein each hardware device in each hardware device group has the same data acquisition frequency;

[0023] A second determining module is used to determine independent hardware devices from the pantograph-catenary detection device, each independent hardware device having an independent data acquisition frequency;

[0024] The data recording module is used for collecting detection data according to the corresponding data collection frequency of each hardware device when the pantograph-catenary detection device is running, and recording the data based on a unified time reference.

[0025] The first determining module includes:

[0026] A first device setting unit, configured to set the visible light camera and the infrared camera in the pantograph-catenary detection device as a first set of hardware devices;

[0027] The first frequency setting unit is configured to set the first group of hardware devices to collect data at the same first data collection frequency.

[0028] The first determining module includes:

[0029] A second device setting unit is used to set the geometric parameter detection device and the vehicle body vibration detection device in the pantograph-catenary detection device as a second set of hardware devices;

[0030] The second frequency setting unit is configured to set the second group of hardware devices to collect data at the same second data collection frequency.

[0031] To achieve the above object, the present invention further provides an electronic device, comprising:

[0032] memory for storing computer programs;

[0033] A processor is used to implement the steps of the above-mentioned data processing method based on the bow-catenary detection device when executing the computer program.

[0034] To achieve the above objectives, the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned data processing method based on the bow-net detection device are implemented.

[0035] It can be seen from the above scheme that an embodiment of the present invention provides a data processing method based on a bow-net detection device, the method comprising: determining a hardware device group from the bow-net detection device, each hardware device in each hardware device group has the same data acquisition frequency; determining independent hardware devices from the bow-net detection device, each independent hardware device has an independent data acquisition frequency; when the bow-net detection device is running, each hardware device collects detection data according to the corresponding data acquisition frequency, and records it based on a unified time reference. It can be seen that this scheme divides the various devices in the bow-net detection device into hardware device groups with the same data acquisition frequency, and independent hardware devices with independent data acquisition frequencies, and each device records detection data based on a unified time reference. In this way, effective integration and processing of detection data of various hardware devices can be achieved, and the bow-net detection device can better play a guiding role in the detection of the bow-net status of urban rail transit; the present invention also discloses a data processing device, device and medium based on the bow-net detection device, which can also achieve the above-mentioned technical effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 This is a flow chart of a data processing method based on a pantograph-catenary detection device disclosed in an embodiment of the present invention;

[0038] Figure 2 A schematic diagram of the equipment installation structure of the geometric parameter detection equipment and the vehicle body vibration detection equipment disclosed in an embodiment of the present invention;

[0039] Figure 3 A schematic diagram of network time synchronization disclosed in an embodiment of the present invention;

[0040] Figure 4 A hardware association diagram disclosed in an embodiment of the present invention;

[0041] Figure 5a A schematic diagram of a wear image acquisition effect disclosed in an embodiment of the present invention;

[0042] Figure 5b A schematic diagram of a wear image acquisition effect disclosed in an embodiment of the present invention;

[0043] Figure 5c A schematic diagram of a wear image acquisition effect disclosed in an embodiment of the present invention;

[0044] Figure 6 This is a structural diagram of a data processing device based on a pantograph-catenary detection device disclosed in an embodiment of the present invention;

[0045] Figure 7 The figure is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0046] At present, the pantograph-catenary inspection device mainly includes the following hardware devices. Here we analyze and introduce the working characteristics of each hardware device:

[0047] 1. Visible light camera, which is mainly responsible for visible light image acquisition and video monitoring in the pantograph area. It needs to be turned on throughout the vehicle operation and acquire visible light image data at a fixed frequency;

[0048] 2. Infrared camera, which is mainly responsible for temperature detection in the pantograph area. It needs to be turned on during the operation of the vehicle and acquire infrared image data at a fixed frequency;

[0049] 3. The UV sensor is mainly responsible for arc detection in the pantograph-catenary area. It needs to be turned on throughout the vehicle operation to detect the occurrence and parameters of arcing. Due to the uncertainty of arcing, the detection of the UV sensor is triggered by external factors.

[0050] 4. Fiber optic sensor, which is mainly responsible for detecting hard points on the contact line. It is installed on the pantograph and is ready to obtain hard point parameters at any time through the pantograph-catenary contact. Due to the uncertainty of hard points, the detection of the fiber optic sensor is triggered by external factors;

[0051] 5. Structured light camera, which includes geometric parameter detection equipment, vehicle body vibration detection equipment, and wear detection equipment. It mainly scans the contact network and track, and obtains contact network geometric parameter data, vehicle body vibration data, and contact line wear data in real time during vehicle operation.

[0052] It can be seen that the detection data generated by the hardware equipment in the bow-net detection device during operation includes visible light image detection data, infrared image detection data, arc detection data, hard point detection data, geometric parameter detection data, vehicle body vibration detection data, and wear detection data. There are many data types and the operating frequencies are different. If there is no method to effectively control and integrate these detection data, it will be difficult to realize the guiding role of the bow-net detection device in the detection and maintenance of the bow-net status of urban rail transit.

[0053] Therefore, in this application, in view of the complexity of the detection data of the bow-net detection device, a data processing method, device, equipment and medium based on the bow-net detection device are disclosed to effectively integrate the detection data generated during the operation of the bow-net detection device to better play its role.

[0054] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0055] See also Figure 1 , a schematic flow chart of a data processing method based on a pantograph-catenary detection device provided by an embodiment of the present invention, the method specifically includes:

[0056] S101, determining a hardware device group from a pantograph-catenary detection device, wherein each hardware device in each hardware device group has the same data acquisition frequency;

[0057] It should be noted that since the bow-net detection device includes multiple hardware devices, and the working frequencies and working principles of each hardware device are different, in this solution, in order to effectively integrate the detection data of the bow-net detection device, after analyzing the working characteristics of the hardware devices, the hardware devices of the bow-net detection device are divided into two categories: one is a hardware device group with the same data acquisition frequency, and the other is an independent hardware device with an independent acquisition frequency. Among them, the hardware device group in this solution has at least two hardware devices, and the hardware devices belonging to the same hardware device group have the same acquisition frequency, that is, at the same time, each hardware device in the hardware device group collects corresponding detection data; the data acquisition frequency of the independent hardware device is different from the data acquisition frequency of the hardware device group, and the data acquisition frequencies between independent hardware devices are also different.

[0058] In this embodiment, the hardware device group determined from the bow-catcher detection device includes a first group of hardware devices and a second group of hardware devices. Specifically, this solution sets the visible light camera and infrared camera in the bow-catcher detection device as the first group of hardware devices, and sets the first group of hardware devices to collect data at the same first data collection frequency. The geometric parameter detection device and vehicle body vibration detection device in the bow-catcher detection device are set as the second group of hardware devices, and set the second group of hardware devices to collect data at the same second data collection frequency.

[0059] Specifically, since both the visible light camera and the infrared camera need to be turned on throughout the vehicle operation process and obtain corresponding detection data at a fixed frequency, this solution sets the visible light camera and the infrared camera as a group, and sets the visible light camera and the infrared camera to perform image acquisition at the same frequency, thereby obtaining visible light image detection data and infrared image detection data. This method is beneficial for the synchronization of the original detection data, and is also convenient for subsequent data processing and further use; wherein, the first data acquisition frequency of the first group of hardware equipment can be specifically 25HZ. Moreover, in order to accurately obtain the contact network geometric parameters, each initially obtained contact network geometric parameter data must be corrected according to a matching vehicle body vibration data. Therefore, this solution sets the geometric parameter detection equipment and the vehicle body vibration detection equipment as the second group of hardware equipment. The second data acquisition frequency of the second group of hardware equipment can be 66~200HZ. See. Figure 2 , is a schematic diagram of the device installation structure of the geometric parameter detection device and the vehicle body vibration detection device disclosed in the embodiment of the present invention; since in this embodiment, the vehicle body vibration detection device can be used to correct the geometric parameters, the vehicle body vibration detection device can also be called: a vehicle body posture compensation device. Figure 2 As shown in the figure, after the equipment is installed and fixed, the three devices are in a completely fixed state. During the measurement process, the contact line geometric parameters and the geometric position of the equipment relative to the track will be measured respectively; by stopping the vehicle at the known contact line standard guide height and pull-out value position, the position of the two vehicle body compensation devices relative to the track (X1 Y1 X2 Y2) and the contact line geometric parameter value (DG LCZ) can be obtained, and the actual contact line geometric parameter value is calibrated by the actual value; (X1 Y1 X2 Y2) is written into the configuration file as the initial point; when the vehicle body deflects, the (X1 Y1 X2 Y2) measurement value will change accordingly. By comparing the initial value, the change amount can be calculated, and the height of the center point and the left and right offset can be calculated based on the change amount. The offset is then compensated to the geometric parameter, thereby realizing the correction of the geometric parameter.

[0060] Furthermore, to ensure that the hardware devices within each hardware device group operate at the same frequency, this solution sets each hardware device group to be controlled by the same hardware trigger source. For example, a first trigger source is set corresponding to the first hardware device group to control the first hardware device group to collect data at the same first data acquisition frequency through the first trigger source; a second trigger source is set corresponding to the second hardware device group to control the second hardware device group to collect data at the same second data acquisition frequency through the second trigger source. In this solution, a PWM (Pulse Width Modulation) square wave emitted by a GPIO (General-purpose input / output) can be used as the trigger signal of the trigger source to control each hardware device group to perform data acquisition.

[0061] S102, determining independent hardware devices from the pantograph-catenary detection device, each independent hardware device having an independent data acquisition frequency;

[0062] It is understandable that the working frequency or working mode of some hardware devices in the bow-net detection device are significantly different from other hardware, such as wear detection equipment, ultraviolet sensors, and optical fiber sensors; among them, in order to achieve excellent detection effects, the working frequency of the wear detection device is often between 6KHz and 30KHz, which is significantly higher than other hardware devices in the bow-net detection device, so the wear detection device is independent in working frequency and can independently adjust the working frequency in software according to the operating environment or accuracy requirements. Therefore, this solution sets the wear detection device in the bow-net detection device as an independent hardware device, and sets the wear detection device to collect data through a third data acquisition frequency, which is 6KHz to 30KHz; it should be noted that the first data acquisition frequency, the second data acquisition frequency and the third data acquisition frequency can all be adjusted according to actual conditions, and are not specifically limited here.

[0063] Furthermore, since both the ultraviolet sensor and the optical fiber sensor are completely triggered by changes in external parameters and work independently, this solution sets the ultraviolet sensor in the bow-net detection device as an independent hardware device, and sets the optical fiber sensor in the bow-net detection device as an independent hardware device. The data acquisition frequency of the ultraviolet sensor and the optical fiber sensor is triggered according to changes in external parameters.

[0064] S103. When the pantograph-catenary detection device is running, each hardware device collects detection data according to a corresponding data collection frequency and records the data based on a unified time reference.

[0065] It is understandable that in order to ensure that each hardware device collects detection data on the same time basis, it is necessary to establish a unified benchmark in the software operation of the hardware device. Since the software of the bow network detection device runs on different boards, and these boards are in the local area network of the same processing host, they can also be connected to the Internet through the 3G / 4G network. Therefore, this solution can use the ntp (Network Time Protocol) timing protocol to establish a unified time standard. Select one of the boards in the processing host as the ntp server in the host to synchronize time with the Internet, and other boards as ntp clients to synchronize time with the ntp server in the host. In this way, the software of each hardware device in the bow network detection device can run on a unified time basis, see Figure 3 , which is a schematic diagram of network timing provided by an embodiment of the present invention, Figure 3 The ntp client and ntp server in the LAN are both boards running software. The ntp server in the LAN is synchronized with the Internet time server, and each ntp client in the LAN is synchronized with the ntp server in the LAN, thereby ensuring that each hardware device in the bow network detection device collects detection data based on a unified time standard.

[0066] See also Figure 4 , is a hardware association diagram provided by an embodiment of the present invention, through Figure 4 It can be seen that the first trigger source sends a trigger signal to the visible light camera and the infrared camera at the same time, and the visible light camera and the infrared camera collect detection data at the same frequency according to the trigger signal. The second trigger source sends a trigger signal to the geometric parameter detection equipment and the vehicle vibration detection equipment at the same time, and the geometric parameter detection equipment and the vehicle vibration detection equipment collect detection data at the same frequency according to the trigger signal. At the same time, the wear detection equipment, the ultraviolet sensor, and the optical fiber sensor collect detection data according to their respective data acquisition frequencies. Each hardware device sends the detection data to the data processing device through the network switching device, so that the data processing device processes the detection data of each hardware device, such as: correcting the detection data, displaying the detection data, etc.

[0067] From the above, it can be seen that this scheme divides the various devices in the bow-net detection device into hardware device groups with the same data acquisition frequency and independent hardware devices with independent data acquisition frequencies, and each device records the detection data based on a unified time base. In this way, the detection data of various hardware devices can be effectively integrated and processed, and the bow-net detection device can better play a guiding role in the bow-net status detection of urban rail transit.

[0068] Based on the above embodiment, in this embodiment, after each hardware device collects detection data according to a corresponding data collection frequency and records the data based on a unified time reference, the following steps are further included:

[0069] The detection data collected by the geometric parameter detection device is interpolated to obtain the geometric parameter detection data corresponding to each millisecond; the wear detection data corresponding to each millisecond collected by the wear detection device is corrected using the geometric parameter detection data corresponding to each millisecond.

[0070] It should be noted that when performing wear detection data processing, in order to be more in line with the actual situation of the vehicle operation route, it is necessary to use geometric parameter detection data to correct the wear detection data. However, the operating frequency of the geometric parameter detection equipment is only 66~200HZ, which is a huge difference from the 6KHz~30KHz operating frequency of the wear detection equipment. Therefore, the data processing equipment in this scheme needs to interpolate the geometric parameter detection data during data matching calculation.

[0071] See also Figure 5a , is a schematic diagram of the wear image acquisition effect provided by an embodiment of the present invention. The height from the device corresponding to FIG5 is 500 and the pull-out value is 0. Currently, the wear amount is calculated mainly by extracting the bus width and the wear position width through image processing. Based on the bus width as a fixed value, the wear width is calculated by the ratio of the extracted bus width to the wear position width, thereby calculating the wear amount. Since the bus and the wear position appear in different sizes in the image at different guide heights and pull-out value positions, see Figure 5b , is another wear image acquisition effect diagram provided by an embodiment of the present invention. The figure is at the edge position, the corresponding height from the device is 500, and the pull-out value is 200. Figure 5c , is another schematic diagram of the wear image acquisition effect provided by an embodiment of the present invention. This figure is at a lower position, corresponding to a height of 200 from the equipment and a pull-out value of 0. To avoid the impact of image differences caused by the different heights and pull-out value positions of the busbar on the accuracy of wear value measurement, this solution needs to verify the correspondence between the same wear amount and different heights and different pull-out values based on the actual image performance of the on-site test, and incorporate it into the wear amount calculation. During actual testing, the guide height and pull-out value information of the test position is first called, and the correspondence is confirmed before calculating the wear amount. By introducing the correspondence between the wear width and different positions, the calculation method directly based on the ratio of the wear position width to the busbar width is optimized and improved. The guide height and pull-out value information is the geometric parameter detection data.

[0072] Specifically, due to the extremely high frequency of wear detection data collection, there are at least 6 values per millisecond. When the vehicle is running at the maximum speed (such as 120km / h), it will travel 3.3cm per millisecond. On the actual line, the geometric parameter data of the contact network will not have a significant change within 3.3cm. Therefore, when interpolating the geometric parameter detection data, the goal of this application is to fill in a new value every millisecond within the original data interval. When correcting the wear detection data, the multiple wear data corresponding to each millisecond are corrected using the same geometric parameter data in milliseconds.

[0073] Furthermore, when selecting an interpolation method, this solution requires that the interpolation function must pass through all original data sample points, have good convergence properties at the endpoints, and require low computational power. Taking these requirements into consideration, this application selected the piecewise quadratic interpolation method. Each time, the original geometric parameter data within a fixed time period (e.g., 1 second) is selected, and every three adjacent points are used as an interval. The quadratic function p(x) of the interval is determined by these three points, and the new value of the supplementary point within the interval is calculated from p(x).

[0074] Among them, the piecewise interpolation function is expressed as:

[0075]

[0076] Among them, f(x) represents the interpolation function, which corresponds to a certain p according to the different domains of definition. The domain of definition is the interval determined in time by the three adjacent original data points of the geometric parameters. The value of f(x) is the geometric parameter value at a certain time obtained by the interpolation function. (0) ~p (n-2) Used to represent a quadratic function determined within a given interval, x0~x n It is the time corresponding to the original data of n geometric parameters within 1s.

[0077] Each interpolation function can be expressed as:

[0078]

[0079] Among them, p2 (i) (x) represents an interpolation function, which is determined by the original data of three known geometric parameters, x i 、x i+1 、x i+2 is the time corresponding to the data, f(x i )、f(x i+1 )、f(x i+2 ) is the geometric parameter value corresponding to time, x represents the independent variable time, which is x i to x i+2 At any point in the interval, f(xi ) represents the sequence number of the first of the three currently selected original data in the 1s time interval, arranged from 0 to n. In this way, by inputting an x, the geometric parameter value corresponding to this x can be solved, that is, the new value to be inserted.

[0080] For example, assuming that the acquisition time (t) and the geometric parameter values (v) of three geometric parameter data are known, namely (t1, v1), (t2, v2), and (t3, v3), a quadratic interpolation function can be determined from these three points:

[0081]

[0082] Among them, the independent variable x∈[t1,t3]. In this way, when a t is given, a corresponding v can be obtained as the new value inserted through the above method.

[0083] Furthermore, after processing the above-mentioned detection data, the present application can arrange the detection data collected by each hardware device in order according to the collection time and display it. After processing the detection data in this way, similar data can be completely synchronized, and data with dependencies can be processed more accurately and reasonably through interpolation calculation.

[0084] In summary, this solution effectively integrates and further processes the detection data generated by the bow-net detection device through the comprehensive use of hardware trigger sources, time synchronization within the local area network and segmented quadratic interpolation methods, which is more conducive to the guiding role of the bow-net detection device in the detection and maintenance of the bow-net status of urban rail transit. At the same time, the organically combined data also has good scalability, which is conducive to subsequent combination with other data or deep data mining.

[0085] The data processing apparatus, device, and medium provided by the embodiments of the present invention are introduced below. The data processing apparatus, device, and medium described below can be referenced with the data processing method described above.

[0086] See also Figure 6 , a schematic structural diagram of a data processing device based on a pantograph-catenary detection device provided by an embodiment of the present invention, the device comprising:

[0087] A first determining module 100 is configured to determine a hardware device group from the pantograph-catenary detection device, wherein each hardware device in each hardware device group has the same data acquisition frequency;

[0088] A second determining module 200 is configured to determine independent hardware devices from the pantograph-catenary detection device, each independent hardware device having an independent data acquisition frequency;

[0089] The data recording module 300 is used to collect data according to the corresponding data collection frequency of each hardware device when the pantograph-catenary detection device is running, and record the data based on a unified time reference.

[0090] The first determining module 100 includes:

[0091] A first device setting unit, configured to set the visible light camera and the infrared camera in the pantograph-catenary detection device as a first set of hardware devices;

[0092] A first frequency setting unit is configured to set the first group of hardware devices to collect data at the same first data collection frequency.

[0093] The first frequency setting unit is specifically configured to set a first trigger source corresponding to the first group of hardware devices, so as to control the first group of hardware devices to collect data at the same first data collection frequency through the first trigger source.

[0094] The first determining module 100 includes:

[0095] A second device setting unit is used to set the geometric parameter detection device and the vehicle body vibration detection device in the pantograph-catenary detection device as a second set of hardware devices;

[0096] The second frequency setting unit is configured to set the second group of hardware devices to collect data at the same second data collection frequency.

[0097] The second frequency setting unit is specifically configured to set a second trigger source corresponding to the second group of hardware devices, so as to control the second group of hardware devices to collect data at the same second data collection frequency through the second trigger source.

[0098] The second determining module 200 includes:

[0099] A third device setting unit is used to set the wear detection device in the pantograph-catenary detection device as an independent hardware device;

[0100] a third frequency setting unit, configured to set the wear detection device to collect data at a third data collection frequency;

[0101] The fourth device setting unit is used to set the ultraviolet sensor in the bow-net detection device as an independent hardware device, and the data acquisition frequency of the ultraviolet sensor is triggered according to the change of external parameters.

[0102] The fifth device setting unit is used to set the optical fiber sensor in the pantograph-catenary detection device as an independent hardware device, and the data acquisition frequency of the optical fiber sensor is triggered according to the change of external parameters.

[0103] Wherein, the device further includes:

[0104] A difference processing module, configured to perform interpolation processing on the data collected by the geometric parameter detection device to obtain geometric parameter detection data corresponding to each millisecond;

[0105] The correction module is used to correct the wear detection data corresponding to each millisecond collected by the wear detection device using the geometric parameter detection data corresponding to each millisecond.

[0106] The display module is used to arrange the data collected by each hardware device in order according to the collection time and display it.

[0107] See also Figure 7 , a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, the device includes:

[0108] Memory 11, for storing computer programs;

[0109] The processor 12 is configured to implement the steps of the data processing method based on the pantograph-catenary detection device described in any of the above method embodiments when executing the computer program.

[0110] In this embodiment, the device may specifically be a terminal device or a server.

[0111] The device may include a memory 11 , a processor 12 , and a bus 13 .

[0112] Among them, the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a hard disk, a multimedia card, a card-type memory (for example, an SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the device, such as the hard disk of the device. In other embodiments, the memory 11 can also be an external storage device of the device, such as a plug-in hard disk equipped on the device, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Furthermore, the memory 11 can also include both an internal storage unit of the device and an external storage device. The memory 11 can not only be used to store application software installed on the device and various types of data, such as program code for executing data processing methods, but can also be used to temporarily store data that has been output or is to be output.

[0113] In some embodiments, the processor 12 can be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip, used to run the program code stored in the memory 11 or process data, such as the program code for executing the data processing method.

[0114] The bus 13 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0115] Furthermore, the device may also include a network interface 14, which may optionally include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the device and other electronic devices.

[0116] Optionally, the device may further include a user interface 15, which may include a display and an input unit such as a keyboard. The optional user interface 15 may also include a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. The display may also be appropriately referred to as a display screen or display unit, and is used to display information processed in the device and to display a visual user interface.

[0117] Figure 7 Only the device with components 11-15 is shown, and it will be understood by those skilled in the art that Figure 7 The structure shown does not constitute a limitation of the device, and may include fewer or more components than shown, or combine certain components, or arrange the components differently.

[0118] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the data processing method based on the bow-net detection device described in any of the above method embodiments are implemented.

[0119] The storage medium may include any medium capable of storing program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0120] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0121] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A data processing method based on a pantograph-catenary detection device, characterized in that: include: Determining a hardware device group from the pantograph-catenary detection device, wherein each hardware device in each hardware device group has the same data acquisition frequency; Determining independent hardware devices from the pantograph-catenary detection device, each independent hardware device having an independent data acquisition frequency; When the pantograph-catenary detection device is in operation, each hardware device collects detection data according to a corresponding data collection frequency and records the data based on a unified time reference; After each hardware device collects detection data according to a corresponding data collection frequency and records the data based on a unified time reference, the following steps are also included: Performing interpolation processing on the detection data collected by the geometric parameter detection device to obtain geometric parameter detection data corresponding to each millisecond; Among them, the piecewise interpolation function of the interpolation processing is expressed as: ； Each interpolation function is expressed as: ； in, represents the interpolation function, to represents a certain quadratic function, to is the time corresponding to the detection data of n geometric parameters, is the new value to be inserted, 、 、 is the time corresponding to the parameter detection data, 、 、 is the geometric parameter detection data corresponding to time, x represents the independent variable time, which is arrive Any point in the interval; The wear detection data corresponding to each millisecond collected by the wear detection equipment is corrected using the geometric parameter detection data corresponding to each millisecond.

2. The data processing method according to claim 1, wherein: The determining of the hardware device group from the pantograph-catenary detection device includes: The visible light camera and the infrared camera in the pantograph-catenary detection device are set as a first group of hardware devices, and the first group of hardware devices are set to collect data according to the same first data collection frequency.

3. The data processing method according to claim 2, characterized in that: The step of setting the first group of hardware devices to collect data at the same first data collection frequency includes: A first trigger source corresponding to the first group of hardware devices is set, so as to control the first group of hardware devices to collect data at the same first data collection frequency through the first trigger source.

4. The data processing method according to claim 1, wherein: The determining of the hardware device group from the pantograph-catenary detection device includes: The geometric parameter detection equipment and the vehicle body vibration detection equipment in the bow-catenary detection device are set as a second group of hardware equipment, and the second group of hardware equipment is set to collect data according to the same second data collection frequency.

5. The data processing method according to claim 4, characterized in that: The setting the second group of hardware devices to collect data according to the same second data collection frequency includes: A second trigger source corresponding to the second group of hardware devices is set to control the second group of hardware devices to collect data according to the same second data collection frequency through the second trigger source.

6. The data processing method according to claim 1, wherein: The determining of the independent hardware device from the pantograph-catenary detection device includes: Setting the wear detection device in the pantograph-catenary detection device as an independent hardware device; The wear detection device is configured to collect data at a third data collection frequency.

7. The data processing method according to claim 1, wherein: The determining of the independent hardware device from the pantograph-catenary detection device includes: The ultraviolet sensor in the pantograph-catenary detection device is set as an independent hardware device, and the data acquisition frequency of the ultraviolet sensor is triggered according to the change of external parameters.

8. The data processing method according to claim 1, wherein: The determining of the independent hardware device from the pantograph-catenary detection device includes: The optical fiber sensor in the pantograph-catenary detection device is set as an independent hardware device, and the data acquisition frequency of the optical fiber sensor is triggered according to the change of external parameters.

9. The data processing method according to any one of claims 1 to 8, characterized in that: After each hardware device collects detection data according to a corresponding data collection frequency and records the data based on a unified time reference, the following steps are also included: The detection data collected by each hardware device is arranged in order according to the collection time and displayed.

10. A data processing device based on a pantograph-catenary detection device, characterized in that: include: A first determining module is used to determine a hardware device group from the pantograph-catenary detection device, wherein each hardware device in each hardware device group has the same data acquisition frequency; A second determining module is used to determine independent hardware devices from the pantograph-catenary detection device, each independent hardware device having an independent data acquisition frequency; A data recording module is used for collecting detection data from each hardware device according to a corresponding data collection frequency when the pantograph-catenary detection device is in operation, and recording the data based on a unified time reference; Also used for: Performing interpolation processing on the detection data collected by the geometric parameter detection device to obtain geometric parameter detection data corresponding to each millisecond; Among them, the piecewise interpolation function of the interpolation processing is expressed as: ； Each interpolation function is expressed as: ； in, represents the interpolation function, to represents a certain quadratic function, to is the time corresponding to the detection data of n geometric parameters, is the new value to be inserted, 、 、 is the time corresponding to the parameter detection data, 、 、 is the geometric parameter detection data corresponding to time, x represents the independent variable time, which is arrive Any point in the interval; The wear detection data corresponding to each millisecond collected by the wear detection equipment is corrected using the geometric parameter detection data corresponding to each millisecond.

11. The data processing device according to claim 10, characterized in that The first determining module includes: A first device setting unit, configured to set the visible light camera and the infrared camera in the pantograph-catenary detection device as a first set of hardware devices; The first frequency setting unit is configured to set the first group of hardware devices to collect data at the same first data collection frequency.

12. The data processing device according to claim 10, characterized in that The first determining module includes: A second device setting unit is used to set the geometric parameter detection device and the vehicle body vibration detection device in the pantograph-catenary detection device as a second set of hardware devices; The second frequency setting unit is configured to set the second group of hardware devices to collect data at the same second data collection frequency.

13. An electronic device, characterized in that: include: memory for storing computer programs; A processor is used to implement the steps of the data processing method based on the pantograph-catenary detection device as described in any one of claims 1 to 9 when executing the computer program.

14. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the data processing method based on the pantograph-catenary detection device according to any one of claims 1 to 9 are implemented.

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