Simulation method, test method and data processing device for analog measurement

Abstract

The present disclosure proposes a simulation method, system and storage medium for simulation measurement, and relates to the field of computer technology. The present disclosure provides a simulation method for simulation measurement, including: generating measurement part configuration parameters of a measurement object; generating measurement tool configuration parameters; generating motion feature configuration parameters of the measurement object; generating fault configuration parameters; simulating the mutual motion between the measurement object and the measurement tool according to the measurement part configuration parameters, the measurement tool configuration parameters and the motion feature configuration parameters, and obtaining measurement data; adjusting the measurement data according to the fault configuration parameters, and obtaining simulation results.

Description

Technical Field

[0001] The present disclosure relates to the field of simulation technology, and in particular to a simulation method, a test method and a data processing device for analog measurement. Background Art

[0002] In the fully automatic train scanning system, the train wheel sensor signals are collected through the train measurement system to measure the train speed and wheelbase.

[0003] In the related art, when testing the train measurement system and train scanning system, it is necessary to arrange sensors on the actual rails, install the measurement system, and wait for the train to arrive. When the train passes by, the sensor generates data, and the test and debugging are performed online. However, renting a train is costly, time-consuming, and very inconvenient to debug. Summary of the invention

[0004] One purpose of the present disclosure is to provide a solution that uses simulation to replace measurement objects and measurement tools, thereby reducing test costs and improving test efficiency and convenience.

[0005] According to one aspect of some embodiments of the present disclosure, a simulation method for simulating measurement is proposed, including: generating measurement part configuration parameters of a measurement object; generating configuration parameters of a measurement tool; generating motion feature configuration parameters of the measurement object; generating fault configuration parameters; simulating the mutual motion between the measurement object and the measurement tool according to the measurement part configuration parameters, the measurement tool configuration parameters, and the motion feature configuration parameters to obtain measurement data; adjusting the measurement data according to the fault configuration parameters to obtain simulation results.

[0006] In some embodiments, the measurement object is a vehicle, the measurement part is a running mechanism of the vehicle, and the measurement tool includes a sensor.

[0007] In some embodiments, the measurement location configuration parameters include the wheelbase of the traveling mechanism; the measurement tool configuration parameters include the distance information between adjacent sensors; the motion feature configuration parameters include the speed of the traveling mechanism when it passes through the measurement area of ​​the sensor, or at least one of the speed change information of the traveling mechanism.

[0008] In some embodiments, the speed change information includes the initial speed, the intermediate speed, the end speed of the speed change, the position of the traveling mechanism at the intermediate speed moment, and the position of the sensor measuring the traveling mechanism.

[0009] In some embodiments, the measurement object is a train, the running mechanism is a wheel, and the wheelbase of the running mechanism includes the wheelbase between every two adjacent wheels in the driving direction.

[0010] In some embodiments, the measurement location configuration parameters are a first array consisting of wheelbases, and the wheelbases in the first array are sorted in order of the associated wheels from the front to the rear of the vehicle; the measurement tool configuration parameters are a second array consisting of distance information between adjacent sensors, and the distance information in the second array is sorted in order of the direction of movement of the associated sensors from the measurement object; the speed of the traveling mechanism when passing through the measurement area of ​​the sensor includes a multidimensional third array consisting of speed information when each wheel reaches each sensor; the speed change information of the traveling mechanism includes a fourth array and a fifth array, the fourth array includes the initial speed, intermediate speed, and end speed of the speed change, and the fifth array includes the position of the specified wheel at the intermediate speed moment and the position of the sensor measuring the specified wheel.

[0011] In some embodiments, the fault configuration parameter includes at least one of a missed detection parameter and a repeated detection parameter.

[0012] In some embodiments, the fault configuration parameters include at least one of a missed detection parameter and a repeated detection parameter, wherein the missed detection parameter includes: the correspondence between the wheel axle identifier of a wheel missed by at least one sensor and the sensor identifier of the wheel corresponding to the missed-detected wheel axle identifier, and the repeated detection parameter includes: the correspondence between the wheel axle identifier of a wheel repeatedly detected by the same sensor and the sensor identifier of the wheel corresponding to the repeatedly-detected wheel axle identifier.

[0013] In some embodiments, the mutual motion between the measurement object and the measurement tool is simulated according to the measurement part configuration parameters, the measurement tool configuration parameters, and the motion feature configuration parameters, and the measurement data is obtained, including: determining the coordinate information of the measurement part and the measurement tool according to the measurement part configuration parameters and the measurement tool configuration parameters; simulating the motion of the measurement object based on a predetermined time step and the motion feature configuration parameters, and updating the coordinate information of the measurement part; generating a measurement signal according to the coordinate information of the measurement part and the coordinate information of the measurement tool, the measurement signal including an identification of the measurement part, an identification of the measurement tool, and measurement time information; and determining the measurement data according to each measurement signal generated during the simulation process.

[0014] In some embodiments, the measurement data is adjusted according to the fault configuration parameters, and obtaining the simulation results includes: when the fault configuration parameters include a missed detection parameter, deleting the measurement signal corresponding to the missed detection parameter in the measurement data; when the fault configuration parameters include a repeated detection parameter, adding the measurement signal corresponding to the repeated detection parameter in the measurement data.

[0015] According to one aspect of some embodiments of the present disclosure, a testing method is proposed, comprising: obtaining a simulation result according to any one of the simulation methods for simulating measurement mentioned above; outputting the simulation result to a measurement system to be tested, wherein the measurement system is used to measure an entity of a measurement object and output the measurement result of the entity.

[0016] According to one aspect of some embodiments of the present disclosure, a data generating device for simulation measurement is proposed, comprising: a measurement parameter generating unit, configured to generate measurement part configuration parameters of a measurement object, generate configuration parameters of a measurement tool, and generate motion feature configuration parameters of the measurement object; a fault parameter generating unit, configured to generate fault configuration parameters; a simulation running unit, configured to simulate the mutual motion between the measurement object and the measurement tool according to the measurement part configuration parameters, the measurement tool configuration parameters, and the motion feature configuration parameters, and obtain measurement data; and a data adjustment unit, configured to adjust the measurement data according to the fault configuration parameters, and obtain a simulation result.

[0017] In some embodiments, the simulation operation unit is configured to: determine the coordinate information of the measurement part and the measurement tool according to the measurement part configuration parameters and the measurement tool configuration parameters; simulate the movement of the measurement object based on a predetermined time step and motion feature configuration parameters, and update the coordinate information of the measurement part; generate a measurement signal according to the coordinate information of the measurement part and the coordinate information of the measurement tool, the measurement signal including the identification of the measurement part, the identification of the measurement tool and the measurement time information; determine the measurement data according to each measurement signal generated during the simulation process.

[0018] In some embodiments, the data adjustment unit is configured to: when the fault configuration parameters include a missed detection parameter, delete the measurement signal corresponding to the missed detection parameter in the measurement data; when the fault configuration parameters include a repeated detection parameter, add the measurement signal corresponding to the repeated detection parameter in the measurement data.

[0019] According to one aspect of some embodiments of the present disclosure, a data processing device is provided, comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to execute any one of the above methods based on instructions stored in the memory.

[0020] According to one aspect of some embodiments of the present disclosure, a computer-readable storage medium is provided, on which computer instructions are stored, and when the instructions are executed by a processor, any one of the above methods is implemented.

[0021] According to one aspect of some embodiments of the present disclosure, a computer program product is provided, including a computer program or instructions, and when the computer program or instructions are executed by a processor, any one of the above methods is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings described herein are used to provide further understanding of the present disclosure and constitute a part of the present disclosure. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute improper limitations on the present disclosure.

[0023] Figure 1 The present invention is a flowchart of some embodiments of the simulation method for simulating measurement.

[0024] Figure 2 Flow charts of other embodiments of the simulation method for simulating measurement disclosed in the present invention.

[0025] Figure 3 The present invention is a flowchart of some embodiments of the simulation running process in the simulation method for simulation measurement disclosed in the present invention.

[0026] Figure 4 Flowcharts of some embodiments of the testing method disclosed herein.

[0027] Figure 5 Schematic diagrams of some embodiments of the data generating device for simulation measurement disclosed in the present invention.

[0028] Figure 6 Schematic diagrams of some embodiments of the data processing device disclosed herein.

[0029] Figure 7 Schematic diagrams of other embodiments of the data processing device disclosed in the present invention.

[0030] Figure 8 Schematic diagrams of some embodiments of application scenarios of the data generating device for simulation measurement disclosed in the present invention. DETAILED DESCRIPTION

[0031] The technical solution of the present disclosure is further described in detail below through the accompanying drawings and embodiments.

[0032] During the field test using a real train, when the wheels of the train pass the sensors deployed on the rails, a detection signal can be generated. Information including the sensor distance and the sensor detection signal is transmitted to the train measurement system, which is then sent to the train identification system for identification, and the identification result is transmitted to the train scanning system for use.

[0033] In addition to using real trains for field testing, in order to realize the testing of train measurement systems and train scanning systems, it is also possible to purchase existing general simulation software, configure a high-performance PC system and carry out further development. However, this method is costly on the one hand, and difficult and time-consuming to develop on the other.

[0034] In response to the above problems, the present invention proposes a simulation method, a test method and a data processing device for analog measurement, which have low requirements on the performance of hardware equipment, are conducive to the use of general-purpose computers or embedded systems for solutions, and the development and application process is flexible and convenient, thereby improving the efficiency and convenience of testing.

[0035] The simulation method for simulated measurement proposed in the present disclosure can be used to simulate and generate a variety of sensor detection data for moving objects, such as sensor detection data for vehicles. In some embodiments, the measurement object is a vehicle, the measurement part is the running mechanism (such as wheels) of the vehicle, and the measurement tool includes a sensor for detecting whether the measurement part of the measurement object appears at the target position. For example, for a train scanning system, the measurement object of the simulation method for simulated measurement disclosed in the present disclosure is a train, and its running mechanism is a wheel.

[0036] The flowcharts of some embodiments of the simulation method for simulation measurement disclosed in the present invention are as follows Figure 1 shown.

[0037] In step S11, the configuration parameters of the measurement part of the measurement object are generated. The measurement object is a mobile object, such as a vehicle. The measurement part is the running mechanism of the mobile object, such as a wheel.

[0038] In some embodiments, the measurement location configuration parameter includes the wheelbase of the running mechanism. Taking a vehicle (including a car, a train) as an example, the wheelbase of the running mechanism includes the wheelbase between every two adjacent wheels in the driving direction.

[0039] In some embodiments, the measurement location configuration parameter is a first array of wheelbases, and the wheelbases in the first array are sorted in order from the front to the rear of the vehicle according to the associated wheels. The array can facilitate the generation of a vehicle travel mechanism model and determine the relative position of the measurement object that can be measured by the sensor during the simulation operation. The sorting from the front to the rear of the vehicle can facilitate the sequential use of data when simulating the vehicle's driving process, reducing the difficulty of simulation.

[0040] For example, a train model includes the information about the locomotive and the wheelbase of each carriage. By configuring different values, different trains can be simulated. The settings are as follows.

[0041] Train model = [wheelbase 1, wheelbase 2, wheelbase 3…]

[0042] The wheelbase 1 mentioned above refers to the distance between the first and second wheels of the train, the wheelbase 2 refers to the distance between the second and third wheels of the train, and so on. The number of wheelbases is the number of wheels on one side of the train minus 1.

[0043] In step S12, the configuration parameters of the measuring tool are generated. In some embodiments, the configuration parameters of the measuring tool include the position information of the sensors. For example, the position of one of the sensors can be set to 0 (e.g., the position of the coordinate origin), and then the position of each sensor can be inferred based on the distance between the sensors. In some embodiments, the configuration parameters of the measuring tool include the distance information between adjacent sensors.

[0044] In some embodiments, taking a vehicle as an example, the configuration parameter of the measuring tool is a second array consisting of distance information between adjacent sensors. The distance information in the second array is sorted in the order of the related sensors from the front to the rear of the measuring object (or from the rear to the front). In some embodiments, it can be sorted according to the direction of movement of the measuring object (i.e., from the rear to the front) so as to facilitate the extraction of data simulating the process of the running mechanism of the measuring object passing through the sensor positions one by one during the simulation process.

[0045] For example, the sensor model includes the distance information of the sensor arrangement. By configuring different values, different sensor arrangements can be simulated. The configuration of the sensor distance is in the following form.

[0046] Sensor distance = [distance 1, distance 2, distance 3, ...]

[0047] Arrange the sensors in the order of the direction of the measured object's movement. The above distance 1 represents the distance between the first sensor and the second sensor, distance 2 represents the distance between the second sensor and the third sensor, and so on. The number of distances is the number of sensors minus 1.

[0048] In step S13, motion feature configuration parameters of the measurement object are generated.

[0049] The motion feature configuration parameters can be expressed in the form of the speed of each traveling mechanism when it passes through the measurement area of ​​the sensor, forming a multi-dimensional array, wherein a single-dimensional array can be the speed of the same traveling mechanism when it passes through each sensor respectively, sorted according to the order of the sensors, or the same sensor can measure the movement speed of the object when it detects different traveling mechanisms in chronological order.

[0050] For example, considering that the train's measurement system only measures speed when the wheels pass through the sensor, set up an array to represent the speed of a certain wheel when it passes through a certain sensor, and set it in the following form.

[0051]

[0052] Among them, speed 11 represents the speed of the train when the first wheel passes the first sensor, speed 12 represents the speed of the train when the first wheel passes the second sensor, and so on; similarly, speed ij represents the speed of the train when the i-th wheel passes the j-th sensor, i is a positive integer, and the maximum value is the number of wheels on one side of the train, j is a positive integer, and the maximum value is the number of sensors.

[0053] The above motion feature configuration parameters can be determined by point-by-point marking to determine the speed of each wheel when passing each sensor during the simulation process. During the simulation process, only the corresponding speed data needs to be extracted and used according to the relative position state between the train and the sensor. The data processing difficulty is low, which reduces the requirements on the computing power of the simulation equipment.

[0054] In some embodiments, the motion feature configuration parameters can be expressed in the form of speed change information of the traveling mechanism. For example, the speed change information includes the initial speed, intermediate speed, and end speed of the speed change, as well as the position of the traveling mechanism at the intermediate speed moment and the position of the sensor measuring the traveling mechanism. Since the speed of a train passing through a channel normally does not change suddenly, and most of them are a uniform speed or a uniform deceleration (acceleration) or two speeds, the initial speed, intermediate speed, and end speed, and the data that can reflect the acceleration are provided, that is, the speed change in the process can be fully represented.

[0055] In some embodiments, the speed change information of the traveling mechanism can be represented by two arrays, wherein the fourth array includes the initial speed, intermediate speed, and end speed of the speed change, and the fifth array includes the position of the specified wheel at the intermediate speed moment and the position of the sensor measuring the specified wheel.

[0056] For example, speed table = [speed 1, speed 2, speed 3]

[0057] Speed ​​change position = [wheel position, sensor position]

[0058] Among them, speed 1 and 3 are the initial speed and the end speed respectively. Speed ​​2 is the intermediate speed. When the train reaches the "speed change position", the speed changes to speed 2. Through these two tables, the acceleration of the train in the two intervals of speed 1 and speed 2, and speed 2 and speed 3 can be calculated. The real-time speed of each wheel of the train when passing through each sensor can be calculated through the acceleration. The above-mentioned speed change position can be information that can reflect the distance the train runs from speed 1 to speed 2. For example, the wheel position is the identifier of the specified wheel, and the sensor position is the position of the sensor that detects the specified wheel. Combined with the wheelbase information in the above text, the information of the distance the train runs from speed 1 to speed 2 can be determined; or, the sensor position is the identifier of the specified sensor, and the wheel position is the identifier of the wheel detected by the specified sensor. Combined with the wheelbase information and sensor distance in the above text, the information of the distance the train runs from speed 1 to speed 2 can be determined.

[0059] In some embodiments, the above steps S11, S12, and S13 do not have a fixed execution order and can be executed flexibly.

[0060] In step S14, a fault configuration parameter is generated. In some embodiments, the fault configuration parameter includes at least one of a missed detection parameter and a repeated detection parameter.

[0061] Taking the train measurement scenario as an example, the missed detection parameter includes: the correspondence between the wheel axle identifier of the wheel missed by at least one sensor and the sensor identifier of the wheel sensor corresponding to the missed detection wheel axle identifier. The repeated detection parameter includes: the correspondence between the wheel axle identifier of the wheel repeatedly detected by the same sensor and the sensor identifier of the wheel sensor corresponding to the repeatedly detected wheel axle identifier.

[0062] For example, set the train wheel to have multiple axes or lost axes at a certain sensor. By configuring different values, you can simulate different multiple axes and lost axes of the train. You can set it as follows. The corresponding position of the lost axis two-dimensional array is set to 1 to indicate that the axis number of the sensor with the number is lost, and 0 to indicate that the axis is not lost. The same applies to multiple axes.

[0063] Lost axis 2D array [axis ID][sensor ID] = 1 or 0

[0064] Multi-axis 2D array [axis ID][sensor ID] = 1 or 0

[0065] The above-mentioned axis identification can be the number of the wheel corresponding to the axis sorted from the front to the rear of the vehicle; the above-mentioned sensor identification can be the number of the sensor sorted in the order of the direction of movement of the sensor from the measurement object.

[0066] In step S15, the mutual motion between the measurement object and the measurement tool is simulated according to the measurement part configuration parameters, the measurement tool configuration parameters, and the motion feature configuration parameters to obtain measurement data.

[0067] In some embodiments, step S14 may not be limited to being performed before step S15, and step S14 may be performed after step S15, or synchronously with step S15. Step S14 only needs to be completed before step S16 is performed. Through such a method, it is convenient to set different fault configuration parameters based on the same measurement data, without repeating the simulation process, thereby improving the reuse rate of test data, improving the flexibility of fault configuration, and also facilitating providing more abundant sample data for subsequent test systems.

[0068] In some embodiments, a time step can be set, and the time step is used as the time period for updating the relative position state of the measurement object and the measurement tool. A measurement signal is generated according to the change of the relative position state of the measurement object and the measurement tool, and then after updating the position of the measurement object to the moving end position, the measurement signal is summarized to generate measurement data. In some embodiments, the simulation operation process is as follows Figure 2 as shown in .

[0069] In step 251, the coordinate information of the measuring part and the measuring tool is determined according to the configuration parameters of the measuring part and the configuration parameters of the measuring tool. For example, a one-dimensional coordinate system is set, and an arbitrary point is set as the coordinate origin on the one-dimensional coordinate system (for example, the position of the last wheel axle of the train is set as the coordinate origin, and the train movement direction is the positive direction of the coordinate system, so as to ensure that all position data during the movement are positive numbers, reducing the difficulty of data processing; or the position of the first sensor can be set as the coordinate origin, and the train movement direction is the positive direction of the coordinate system, and when the first wheel reaches the first sensor, the calculation starts from the positive position, etc.), and the initial coordinates of each measuring part and the fixed coordinates of each measuring tool are determined according to the parameters configured in the above steps S11 and S12.

[0070] In step 252, based on the predetermined time step and motion feature configuration parameters, the motion of the measured object is simulated and the coordinate information of the measured part is updated. For example, the coordinate information of the measured part is updated once each time the time is increased by a predetermined time step, with the predetermined time step as the granularity.

[0071] In step 253, a measurement signal is generated according to the coordinate information of the measurement part and the coordinate information of the measurement tool. The measurement signal includes the identification of the measurement part, the identification of the measurement tool and the measurement time information. The measurement time information may be the time determined by adding a predetermined time step in the above step 252. For example, when the coordinate information of the measurement tool coincides with the coordinate information of the measurement part, it is determined that the sensor detects the measurement part and generates a measurement signal, then the measurement signal is measured. In the measurement signal, the identification of the measurement part and the identification of the measurement tool are the identification of the measurement part and the identification of the measurement tool where the coordinate information coincides, respectively, and the measurement time information is the current measurement time.

[0072] In some embodiments, considering that the coordinate information of the measuring tool and the coordinate information of the measuring part may overlap between the last measurement moment and the current measurement moment, it can be determined whether to generate a measurement signal based on the size change of the coordinate information of the measuring tool and the coordinate information of the measuring part at two adjacent measurement moments. For example, if the size relationship between the coordinate information of the measuring tool and the coordinate information of the measuring part at two adjacent measurement moments changes, a measurement signal is generated, and the measuring tool and the measuring part corresponding to the coordinate information of the measuring tool and the coordinate information of the measuring part whose size relationship has changed are used as the identification of the measuring part and the identification of the measuring tool in the generated measurement signal, and the current measurement moment or the last measurement moment, or the average of the current measurement moment and the last measurement moment, is used as the measurement moment information in the measurement signal.

[0073] In step 254, measurement data is determined based on each measurement signal generated during the simulation process. In some embodiments, the measurement signals are summarized as measurement data in the order in which the measurement signals occur. The measurement data may include a correspondence between the measurement site identifier and the measurement tool identifier, such as [wheel identifier, sensor identifier]. In some embodiments, the measurement data may also include time information for generating corresponding measurement information, such as [wheel identifier, sensor identifier, time information], to increase the amount of information provided for subsequent data processing.

[0074] In step S16, the measurement data is adjusted according to the fault configuration parameters to obtain simulation results. The fault configuration parameters may include at least one of missed detection or repeated detection, wherein missed detection refers to the fact that no measurement signal is generated when the measurement tool should detect the measurement location; repeated detection refers to the fact that a single measurement tool generates multiple measurement signals for the same measurement location, both of which are abnormal measurement states.

[0075] When the fault configuration parameters include a missed detection parameter, the measurement signal corresponding to the missed detection parameter is deleted from the measurement data. When the fault configuration parameters include a repeated detection parameter, the measurement signal corresponding to the repeated detection parameter is added to the measurement data.

[0076] Based on the method in the embodiment shown above, simulation data applied to the measurement system can be generated through convenient simulation parameter configuration and fault parameter configuration, and the simulation process has low requirements on the performance of hardware equipment, which is conducive to the use of general-purpose computers or embedded systems for solutions. The development and application process is flexible and convenient, which improves the efficiency and convenience of testing.

[0077] In some embodiments, taking train scanning as an example, the simulation operation and fault adding operation of steps S15 and S16 can be performed as follows: Figure 3 as shown in .

[0078] In step 351, configuration parameters are read. The configuration parameters may be the configuration parameters of the train wheelbase and sensor distance in the embodiments shown in steps S11 and S12 above. In some embodiments, the motion feature configuration parameters in step S13 above may also be read in this step for standby use.

[0079] In step 352 , a coordinate model is generated, that is, a coordinate model is generated according to the train wheelbase and sensor arrangement.

[0080] In step 353, a time step is set. In some embodiments, the time step may be the minimum processing time granularity of the device currently used to run the simulation, so as to avoid the situation where the measurement signal is missed and improve the accuracy of the simulation. In some embodiments, the time step may be appropriately increased according to the simulation time length limit, the amount of computation required, and the running speed of the train to improve the simulation efficiency.

[0081] In step 354, the coordinates of the wheels are updated according to the current moment, combined with the coordinate information of the wheels at the previous moment and the speed of the train. The speed of the train is determined according to the motion feature configuration parameters in step S13. Further, it is determined whether the last axle of the train passes the last sensor. If the last axle of the train passes the last sensor, step 3510 is executed; if the last axle of the train has not passed the last sensor, step 355 is executed.

[0082] In step 355 , the simulation time axis is increased by one time step according to the time step set in step 353 , and then step 356 is executed.

[0083] In step 356, it is determined whether a wheel has passed the sensor. For example, when the wheel coordinates coincide with the sensor coordinates, it is determined that the wheel has passed the sensor. In some embodiments, if the size relationship between the wheel coordinates and the sensor coordinates has changed between the last cycle and the current cycle, it can be considered that the wheel has passed the sensor. However, due to the excessively large time step, the moment when the coordinates are completely consistent cannot be captured. The current moment can be used as the time information of the wheel being measured. If the size relationship between the wheel coordinates and the sensor coordinates has not changed between the last cycle and the current cycle, the wheel has not passed the sensor.

[0084] In step 357 , a measurement signal is generated and saved, the measurement signal including the axis, sensor and time information generating the signal.

[0085] In step 358, based on the motion feature configuration parameters generated in step S13, it is determined whether the speed of the train needs to be changed at the current moment. If the speed needs to be changed, step 359 is executed. If the speed does not need to be changed, the process returns to step 354.

[0086] In step 359, the speed of the train is updated according to the motion characteristic configuration parameters.

[0087] In step 3510, the simulation of the train's movement process is completed, and the measurement signals are summarized to obtain measurement data, which can be saved in the form of a simulation signal table.

[0088] In step 361, the measurement data is adjusted according to the fault configuration, and the fault configuration parameters may be as shown in the embodiment of step S14 above. For example, according to the fault configuration parameters, the axis loss signal is deleted and the multi-axis signal is added to obtain the final simulation data.

[0089] Based on the method in the embodiment shown above, the measurement data required in the test process of the train scanning system or the train measurement system is obtained by simulation, avoiding reliance on field testing, reducing costs, and improving implementation efficiency; the development difficulty is low, the cycle is short, and the performance requirements for hardware equipment are low, which improves the efficiency and convenience of data acquisition.

[0090] The flowcharts of some embodiments of the testing method disclosed herein are as follows Figure 4 shown.

[0091] In step S41, any one of the above simulation methods for simulation measurement is used to obtain simulation results.

[0092] In step S42, the simulation result is output to a measurement system to be tested, wherein the measurement system is used to measure an entity of a measurement object and output a measurement result of the entity.

[0093] In some embodiments, a corresponding transmission signal can be generated based on the simulation results, and the transmission signal meets the requirements of the downstream device. For example, if the downstream measurement system requires a hardware IO signal, the IO signal can be generated by the corresponding hardware. If the measurement system requires a software signal, the simulation result can be sent to the measurement system through a protocol, and the measurement system will then generate the required software signal.

[0094] In some embodiments, if the measurement system is a PC system with relatively good performance, the simulation method for analog measurement shown above can be embedded in the measurement system for execution; if the measurement system resources are insufficient to embed and execute the simulation method for analog measurement, an external PC system or embedded system can be used to execute the simulation method for analog measurement, generate simulation results, and then send them to the measurement system through communication protocols or hardware IO.

[0095] Based on the method in the embodiment shown above, the measurement system can use simulation data to perform subsequent operations, such as testing itself or testing the scanning system downstream of data processing, which reduces costs and improves implementation efficiency; it has low performance requirements for hardware equipment and improves the efficiency and convenience of the testing process.

[0096] Schematic diagrams of some embodiments of the data generation device for simulation measurement disclosed in the present invention are as follows Figure 5 shown.

[0097] The measurement parameter generating unit 511 can be configured by the user to generate various configuration parameters required in the simulation process, including generating measurement part configuration parameters of the measurement object, generating measurement tool configuration parameters, and generating motion feature configuration parameters of the measurement object.

[0098] The measurement object is a mobile object, such as a vehicle. The measurement part is the running mechanism of the mobile object, such as a wheel. In some embodiments, the measurement part configuration parameter includes the wheelbase of the running mechanism. Taking a vehicle (including a car, a train) as an example, the wheelbase of the running mechanism includes the wheelbase between every two adjacent wheels in the driving direction.

[0099] In some embodiments, the measurement location configuration parameter is a first array of wheelbases, and the wheelbases in the first array are sorted in order from the front to the rear of the vehicle according to the associated wheels. The array can facilitate the generation of a vehicle travel mechanism model and determine the relative position of the measurement object that can be measured by the sensor during the simulation operation. The sorting from the front to the rear of the vehicle can facilitate the sequential use of data when simulating the vehicle's driving process, reducing the difficulty of simulation.

[0100] The configuration parameters of the measuring tool include the position information of the sensors. For example, the position of one of the sensors can be set to 0 (eg, the position of the coordinate origin), and then the position of each sensor can be inferred based on the distance between the sensors. In some embodiments, the configuration parameters of the measuring tool include the distance information between adjacent sensors.

[0101] In some embodiments, taking a vehicle as an example, the configuration parameter of the measuring tool is a second array consisting of distance information between adjacent sensors. The distance information in the second array is sorted in the order of the related sensors from the front to the rear of the measuring object (or from the rear to the front). In some embodiments, it can be sorted according to the direction of movement of the measuring object (i.e., from the rear to the front) so as to facilitate the extraction of data simulating the process of the running mechanism of the measuring object passing through the sensor positions one by one during the simulation process.

[0102] The motion feature configuration parameters can be expressed in the form of the speed of each traveling mechanism when it passes through the measurement area of ​​the sensor, forming a multi-dimensional array, wherein a single-dimensional array can be the speed of the same traveling mechanism when it passes through each sensor respectively, sorted according to the order of the sensors, or the same sensor can measure the movement speed of the object when it detects different traveling mechanisms in chronological order.

[0103] The motion characteristic configuration parameters can be expressed in the form of speed change information of the traveling mechanism. For example, the speed change information includes the initial speed, intermediate speed, and end speed of the speed change, as well as the position of the traveling mechanism at the intermediate speed moment and the position of the sensor measuring the traveling mechanism. Since the speed of a train passing through a channel normally does not change suddenly, and most of them are a uniform speed or a uniform deceleration (acceleration) or two speeds, the initial speed, intermediate speed, and end speed, and the data that can reflect the acceleration are provided, that is, the speed change in the process can be fully represented.

[0104] In some embodiments, the measurement parameter generating unit 511 can execute the method in any of the above steps S11 , S12 , and S13 .

[0105] The fault parameter generation unit 512 can generate fault configuration parameters. In some embodiments, the fault configuration parameters include at least one of a missed detection parameter and a repeated detection parameter. Taking the train measurement scenario as an example, the missed detection parameter includes: the correspondence between the wheel axle identifier of a wheel missed by at least one sensor and the sensor identifier of the wheel corresponding to the missed detection wheel axle identifier. The repeated detection parameter includes: the correspondence between the wheel axle identifier of a wheel repeatedly detected by the same sensor and the sensor identifier of the wheel corresponding to the repeated detection wheel axle identifier.

[0106] For example, set the train wheel to have multiple axes or lost axes at a certain sensor. By configuring different values, you can simulate different multiple axes and lost axes of the train. You can set it as follows. The corresponding position of the lost axis two-dimensional array is set to 1 to indicate that the axis number of the sensor with the number is lost, and 0 to indicate that the axis is not lost. The same applies to multiple axes.

[0107] Lost axis 2D array [axis ID][sensor ID] = 1 or 0

[0108] Multi-axis 2D array [axis ID][sensor ID] = 1 or 0

[0109] The above-mentioned axis identification can be the number of the wheel corresponding to the axis sorted from the front to the rear of the vehicle; the above-mentioned sensor identification can be the number of the sensor sorted in the order of the direction of movement of the sensor from the measurement object.

[0110] The simulation operation unit 513 can simulate the mutual movement between the measurement object and the measurement tool according to the measurement part configuration parameters, the measurement tool configuration parameters, and the motion feature configuration parameters to obtain measurement data. In some embodiments, the simulation operation unit 513 can execute the above steps S15, Figure 2 The method of any embodiment shown, and the method that can be performed Figure 3 The method in any embodiment of the simulation running process in the illustrated embodiment.

[0111] The data adjustment unit 514 can adjust the measurement data according to the fault configuration parameters to obtain the simulation results. The fault configuration parameters may include at least one of missed detection or repeated detection, wherein missed detection refers to the fact that no measurement signal is generated when the measurement tool should detect the measurement part; repeated detection refers to the fact that a single measurement tool generates multiple measurement signals for the same measurement part, both of which are abnormal measurement states.

[0112] When the fault configuration parameters include a missed detection parameter, the measurement signal corresponding to the missed detection parameter is deleted from the measurement data. When the fault configuration parameters include a repeated detection parameter, the measurement signal corresponding to the repeated detection parameter is added to the measurement data.

[0113] Based on the device in the embodiment shown above, it is possible to generate simulation data for use in the measurement system through convenient simulation parameter configuration and fault parameter configuration, and the simulation process has low requirements on the performance of the hardware equipment, which is conducive to the use of general-purpose computers or embedded systems for solutions. The development and application process is flexible and convenient, which improves the efficiency and convenience of testing.

[0114] The structural schematic diagrams of some embodiments of the data processing device disclosed in the present invention are as follows: Figure 6The data processing device disclosed in the present invention may be the data generating device for simulation measurement mentioned above, or may be a test system including a simulation method capable of running simulation measurement.

[0115] The data processing device includes a memory 601 and a processor 602. The memory 601 may be a disk, a flash memory, or any other non-volatile storage medium. The memory is used to store instructions in the corresponding embodiments of the simulation method or the test method for analog measurement described above. The processor 602 is coupled to the memory 601 and may be implemented as one or more integrated circuits, such as a microprocessor or a microcontroller. The processor 602 is used to execute instructions stored in the memory, which can reduce the cost of testing and improve the efficiency and convenience of testing.

[0116] In one embodiment, it is also possible to Figure 7 As shown, the data processing device 700 includes a memory 701 and a processor 702. The processor 702 is coupled to the memory 701 via a BUS bus 703. The data processing device 700 can also be connected to an external storage device 705 via a storage interface 704 to call external data, and can also be connected to a network or another computer system (not shown) via a network interface 706. No further detailed description will be given here.

[0117] In this embodiment, by storing data instructions in a memory and then processing the instructions through a processor, the cost of testing can be reduced and the efficiency and convenience of testing can be improved.

[0118] In another embodiment, a computer-readable storage medium stores thereon computer program instructions, which are executed by a processor to implement the steps of the method in the corresponding embodiment of the simulation method or test method for analog measurement. It should be understood by those skilled in the art that the embodiments of the present disclosure can be provided as methods, devices, or computer program products. Therefore, the present disclosure can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present disclosure can adopt the form of a computer program product implemented on one or more computer-usable non-transient storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0119] Schematic diagrams of some embodiments of application scenarios of the data generation device for simulation measurement disclosed in the present invention are as follows Figure 8 shown.

[0120] The data generating device 81 for analog measurement can implement any of the above simulation methods for analog measurement, generate simulation results, and serve as input signals for the measurement system that subsequently processes the simulation results. In some embodiments, the data generating device 81 for analog measurement has various parameter configuration, simulation operation, and functional modules for sending simulation results through signals, as well as corresponding hardware.

[0121] The signal processing / measurement system 82 is signal-connected to the data generating device 81 for analog measurement, and has a communication receiving module and a message parsing output module, wherein the communication receiving module receives the signal of the simulation result output from the data generating device 81 for analog measurement, and the message parsing output module performs message parsing on the signal to obtain the simulation result and sends it to the target identification system 83 for use.

[0122] Taking the train scanning scenario as an example, a data generation device 81 and a signal processing / measurement system 82 for simulation measurement can be implemented on a general-purpose computer. The output module is divided into a communication sending module, a communication receiving module and a message parsing output module. The communication sending module is in the general-purpose computer (host computer) system, and the communication receiving module and the message parsing output module are embedded in the measurement system. The generated simulation signal table is sent to the FPGA-based measurement system through the protocol. The output module is implemented in the signal processing system: the simulation signal table is parsed, and the soft signal required by the output system is output to replace the actual wheel sensor signal to realize system simulation.

[0123] Based on the embodiments shown above, it is possible to easily realize the arrangement of various trains and various wheel sensors, and simulate various speed conditions and various fault conditions, thereby improving the flexibility and efficiency of the obtained measurement data and improving the matching degree with the needs; the requirements for software and hardware resources are low, and the implementation cost is low; the development difficulty is low, it is easy to implement, and the operation process is efficient, which can improve the efficiency of the development, testing and simulation process of the measurement system.

[0124] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram and the combination of processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0125] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0126] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0127] So far, the present disclosure has been described in detail. In order to avoid obscuring the concept of the present disclosure, some details known in the art are not described. Based on the above description, those skilled in the art can fully understand how to implement the technical solution disclosed here.

[0128] The method and apparatus of the present disclosure may be implemented in many ways. For example, the method and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above, unless otherwise specifically stated. In addition, in some embodiments, the present disclosure may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present disclosure. Therefore, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.

[0129] It should be noted that the terms "first", "second", etc. in the specification, claims, and drawings of the present disclosure are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0130] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present disclosure rather than to limit it. Although the present disclosure has been described in detail with reference to the preferred embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present disclosure can still be modified or some technical features can be replaced by equivalents without departing from the spirit of the technical solution of the present disclosure, which should be included in the scope of the technical solution for protection of the present disclosure.

Claims

1. A simulation method for simulation measurement, comprising: Generate measurement location configuration parameters of the measurement object; Generate configuration parameters for measurement tools; generating motion characteristic configuration parameters of the measurement object; Generate fault configuration parameters; According to the measurement part configuration parameters, the measurement tool configuration parameters, and the motion feature configuration parameters, simulate the mutual motion between the measurement object and the measurement tool to obtain measurement data; The measurement data is adjusted according to the fault configuration parameters to obtain simulation results.

2. The simulation method according to claim 1, wherein: The measurement object is a vehicle, the measurement part is a running mechanism of the vehicle, and the measurement tool includes a sensor.

3. The simulation method according to claim 2, wherein: The measurement location configuration parameters include the wheelbase of the traveling mechanism; The configuration parameters of the measuring tool include distance information between adjacent sensors; The motion characteristic configuration parameter includes at least one of the speed of the traveling mechanism when the traveling mechanism passes through the measurement area of ​​the sensor, or the speed change information of the traveling mechanism.

4. The simulation method according to claim 3, wherein: The speed change information includes an initial speed, an intermediate speed, and an end speed of the speed change, as well as a position of a traveling mechanism at the intermediate speed and a position of a sensor for measuring the traveling mechanism.

5. The simulation method according to claim 3 or 4, wherein: The measuring object is a train, the running mechanism is a wheel, and the wheelbase of the running mechanism includes the wheelbase between every two adjacent wheels in the traveling direction.

6. The simulation method according to claim 5, wherein: The measurement location configuration parameter is a first array consisting of wheelbases, and the wheelbases in the first array are sorted in order from the front to the rear of the vehicle according to the order of the associated wheels; The configuration parameter of the measuring tool is a second array consisting of the distance information of adjacent sensors, and the distance information in the second array is sorted in the order of the direction of movement of the related sensors from the measuring object; The speed of the traveling mechanism when passing through the measuring area of ​​the sensor includes a multi-dimensional third array formed by the speed information of each wheel when reaching each sensor; The speed change information of the traveling mechanism includes a fourth array and a fifth array. The fourth array includes the initial speed, intermediate speed, and end speed of the speed change. The fifth array includes the position of the specified wheel at the intermediate speed moment and the position of the sensor measuring the specified wheel.

7. The simulation method according to claim 1, wherein: The fault configuration parameter includes at least one of a missed detection parameter and a repeated detection parameter.

8. The simulation method according to claim 5, wherein: The fault configuration parameter includes at least one of a missed detection parameter and a repeated detection parameter. The missed detection parameter includes: a correspondence between a wheel axle identifier of a wheel missed by at least one sensor and a sensor identifier of a wheel corresponding to the missed detection wheel axle identifier, The repeated detection parameter includes: a correspondence between a wheel axle identifier of a wheel repeatedly detected by a same sensor and a sensor identifier of a sensor that repeatedly detects a wheel corresponding to the wheel axle identifier.

9. The simulation method according to any one of claims 1 to 8, wherein: The step of simulating the mutual motion between the measurement object and the measurement tool according to the measurement part configuration parameter, the measurement tool configuration parameter, and the motion feature configuration parameter to obtain the measurement data comprises: Determining coordinate information of the measurement part and the measurement tool according to the measurement part configuration parameters and the configuration parameters of the measurement tool; Based on a predetermined time step and the motion feature configuration parameters, simulating the motion of the measurement object and updating the coordinate information of the measurement part; generating a measurement signal according to the coordinate information of the measurement part and the coordinate information of the measurement tool, wherein the measurement signal includes an identifier of the measurement part, an identifier of the measurement tool and measurement time information; Based on each of the measurement signals generated during the simulation, the measurement data is determined.

10. The simulation method according to claim 9, wherein: Adjusting the measurement data according to the fault configuration parameters to obtain the simulation results includes: In a case where the fault configuration parameters include a leakage detection parameter, deleting a measurement signal corresponding to the leakage detection parameter in the measurement data; In a case where the fault configuration parameters include a repeated detection parameter, a measurement signal corresponding to the repeated detection parameter is added to the measurement data.

11. A testing method comprising: According to the simulation method for simulation measurement according to any one of claims 1 to 10, obtaining a simulation result; The simulation result is output to a measurement system to be tested, wherein the measurement system is used to measure an entity of the measurement object and output a measurement result for the entity.

12. A data generation device for simulation measurement, comprising: A measurement parameter generating unit, configured to generate measurement part configuration parameters of the measurement object, generate configuration parameters of the measurement tool, and generate motion feature configuration parameters of the measurement object; A fault parameter generating unit is configured to generate a fault configuration parameter; a simulation operation unit configured to simulate the mutual motion between the measurement object and the measurement tool according to the measurement part configuration parameters, the measurement tool configuration parameters, and the motion feature configuration parameters, and obtain measurement data; The data adjustment unit is configured to adjust the measurement data according to the fault configuration parameters to obtain a simulation result.

13. The data generating device according to claim 12, wherein: The simulation operation unit is configured as follows: Determining coordinate information of the measurement part and the measurement tool according to the measurement part configuration parameters and the measurement tool configuration parameters; Based on a predetermined time step and the motion feature configuration parameters, simulating the motion of the measurement object and updating the coordinate information of the measurement part; generating a measurement signal according to the coordinate information of the measurement part and the coordinate information of the measurement tool, wherein the measurement signal includes an identifier of the measurement part, an identifier of the measurement tool and measurement time information; Based on each of the measurement signals generated during the simulation, the measurement data is determined.

14. The data generating device according to claim 13, wherein: The data adjustment unit is configured to: In a case where the fault configuration parameters include a leakage detection parameter, deleting a measurement signal corresponding to the leakage detection parameter in the measurement data; In a case where the fault configuration parameters include a repeated detection parameter, a measurement signal corresponding to the repeated detection parameter is added to the measurement data.

15. A data processing device, comprising: Memory; as well as A processor coupled to the memory, the processor being configured to execute the method according to any one of claims 1 to 11 based on instructions stored in the memory.

16. A computer-readable storage medium having computer instructions stored thereon, wherein when the instructions are executed by a processor, the method according to any one of claims 1 to 11 is implemented.

17. A computer program product, comprising a computer program or instructions, wherein when the computer program or instructions are executed by a processor, the method according to any one of claims 1 to 11 is implemented.

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