Train speed and distance measuring method and device

Abstract

The invention discloses a speed and distance measuring method and device for a train, relates to the technical field of rail transit, and mainly aims to improve the precision of a speed and distance measuring result of the train. According to the main technical scheme, the method comprises the steps of obtaining first speed and distance measurement data corresponding to a wheel shaft speed sensor, second speed and distance measurement data corresponding to a Doppler radar and acceleration data corresponding to an accelerometer in a current period; judging whether the train is in an idling or slipping state or not according to a preset judgment method; if not, obtaining output speed and distance measurement data of the train according to the first speed and distance measurement data and the second speed and distance measurement data; if so, obtaining compensation speed and distance measurement data corresponding to a wheel shaft speed sensor according to the acceleration data; and according to the compensation speed measurement and distance measurement data and the second speed measurement and distance measurement data, obtaining output speed measurement and distance measurement data of the train. The method is used for measuring the speed and the distance of the train.

Description

Technical Field

[0001] The present invention relates to the field of rail transportation technology, and in particular to a method and device for measuring speed and distance of a train. Background Art

[0002] In the era of high-speed rail, speed and distance measurement technology of high-speed rail trains is the key to ensuring efficient and safe operation of trains. By real-time monitoring of train speed, it can ensure that the train runs stably within the prescribed speed range and effectively avoid safety risks caused by speeding. At the same time, distance measurement technology enables the train to obtain its own location information in real time and maintain real-time communication with the dispatching center to ensure that the train runs strictly according to the scheduled route and timetable.

[0003] Most current train speed and distance measurement methods use a combination of wheel axle speed sensors and Doppler radars to measure speed and distance. In rainy and snowy weather, radar waves will be scattered by raindrops or snowflakes, thereby interfering with the accuracy of the output signal. However, wheel axle speed sensors will not be affected to the same extent in this case. Therefore, by fusing the signals collected by wheel axle speed sensors and Doppler radars, the limited accuracy of Doppler radars in bad weather can be compensated.

[0004] However, in rainy and snowy weather or when the train is over-hauled or the braking force is too large, the train is prone to idling or slipping, resulting in a decrease in the accuracy of the signal output by the axle speed sensor. This means that even if signal fusion technology is used, the current train speed and distance measurement method will still reduce the accuracy of speed and distance measurement due to the decrease in the accuracy of the signal output by the axle speed sensor. Summary of the invention

[0005] In view of the above problems, the present invention provides a method and device for measuring speed and distance of a train, the main purpose of which is to improve the accuracy of the results of measuring speed and distance of the train.

[0006] In order to solve the above technical problems, the present invention proposes the following solutions:

[0007] In a first aspect, the present invention provides a method for measuring speed and distance of a train, the method comprising:

[0008] Obtaining first speed and distance measurement data corresponding to the wheel axle speed sensor, second speed and distance measurement data corresponding to the Doppler radar, and acceleration data corresponding to the accelerometer in the current cycle;

[0009] Determine whether the train is in an idling or slipping state according to a preset determination method;

[0010] If not, obtaining the output speed and distance measurement data of the train according to the first speed and distance measurement data and the second speed and distance measurement data;

[0011] If yes, then obtain the compensated speed and distance measurement data corresponding to the wheel axle speed sensor according to the acceleration data;

[0012] The output speed and distance measurement data of the train is obtained according to the compensated speed and distance measurement data and the second speed and distance measurement data.

[0013] In a second aspect, the present invention provides a train speed and distance measuring device, the device comprising:

[0014] A data acquisition unit, used to acquire first speed and distance measurement data corresponding to the wheel axle speed sensor, second speed and distance measurement data corresponding to the Doppler radar, and acceleration data corresponding to the accelerometer in the current cycle;

[0015] A state judgment unit, used to judge whether the train is in an idling or slipping state according to a preset judgment method;

[0016] a first data determining unit, configured to obtain output speed and distance measurement data of the train according to the first speed and distance measurement data and the second speed and distance measurement data acquired by the data acquiring unit if the judgment result of the state judging unit is not in the state;

[0017] a second data determining unit, configured to obtain compensated speed and distance measurement data corresponding to the wheel axle speed sensor according to the acceleration data acquired by the data acquiring unit if the determination result of the state determining unit is in;

[0018] The third data determination unit is used to obtain the output speed and distance measurement data of the train according to the compensated speed and distance measurement data determined by the second data determination unit and the second speed and distance measurement data.

[0019] In order to achieve the above-mentioned purpose, according to a third aspect of the present invention, a storage medium is provided, wherein the storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the train speed and distance measurement method of the first aspect mentioned above.

[0020] In order to achieve the above-mentioned object, according to a fourth aspect of the present invention, a processor is provided, wherein the processor is used to run a program, wherein when the program is run, the method for measuring speed and distance of a train according to the first aspect is executed.

[0021] By means of the above technical solution, the present invention provides a method and device for measuring speed and distance of a train, which can first obtain the first speed and distance data provided by the axle speed sensor, the second speed and distance data provided by the Doppler radar, and the acceleration data provided by the accelerometer in the current cycle. Subsequently, it should be determined whether the train is in an idling or slipping state. If the train is not in an idling or slipping state, the output speed and distance data of the train can be directly combined with the first speed and distance data of the axle speed sensor and the second speed and distance data of the Doppler radar to determine. On the contrary, if the train is indeed in an idling or slipping state, this indicates that the first speed and distance data of the axle speed sensor has become inaccurate. In this case, the acceleration data needs to be used to calculate the compensated speed and distance data of the axle speed sensor. Afterwards, the output speed and distance data of the train is comprehensively obtained based on the compensated speed and distance data and the second speed and distance data. In this way, the problem of insufficient accuracy of the axle speed sensor of the train in an idling or slipping state is effectively solved, and the accuracy of the overall speed and distance measurement is improved compared with the existing technical solutions.

[0022] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0024] Figure 1 A flow chart of a method for measuring speed and distance of a train provided by an embodiment of the present invention is shown;

[0025] Figure 2 A flow chart of another method for measuring speed and distance of a train provided by an embodiment of the present invention is shown;

[0026] Figure 3 A block diagram showing a train speed and distance measuring device provided by an embodiment of the present invention;

[0027] Figure 4 A block diagram showing the composition of another train speed and distance measuring device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0029] Aiming at the problem that the accuracy of the axle speed sensor signal decreases in the existing train speed and distance measurement methods, resulting in a decrease in the overall speed and distance measurement accuracy, the inventors have proposed a train speed and distance measurement method after in-depth research and innovative practice. The method first determines whether the train is in an idling or slipping state through a preset judgment logic. Once the train is detected as being in any state of idling or slipping, the acceleration data is used to calculate the compensated speed and distance measurement data of the axle speed sensor. Then, the compensated speed and distance measurement data is combined with the second speed and distance measurement data provided by the Doppler radar to calculate the final output distance measurement data of the train. Such processing not only makes up for the deficiency of the Doppler radar's limited accuracy in bad weather conditions such as rain and snow, but also solves the problem of the decrease in the accuracy of the axle speed sensor when the train is idling or slipping. By effectively combining these two types of data, the obtained train output speed and distance measurement data has higher accuracy.

[0030] Next, a train speed and distance measurement method provided by the present invention is described in detail. The specific execution steps are as follows: Figure 1 As shown, including:

[0031] 101. Obtain first speed and distance measurement data corresponding to the wheel axle speed sensor, second speed and distance measurement data corresponding to the Doppler radar, and acceleration data corresponding to the accelerometer in a current cycle.

[0032] In this step, the wheel axle speed sensor, Doppler radar and accelerometer will collect corresponding signals in real time, and these signals will be divided into different periods for subsequent processing.

[0033] When the wheel axle speed sensor and the Doppler radar collect real-time signals, the signal collected by the wheel axle speed sensor in the current cycle can be used to calculate the first typical speed value corresponding to the wheel axle speed sensor in the current cycle; at the same time, the signal collected by the Doppler radar in the current cycle can be used to calculate the second typical speed value corresponding to the Doppler radar in the current cycle.

[0034] In order to ensure the accuracy of the data, the maximum speed value and the minimum speed value of the speed confidence interval corresponding to the wheel axle speed sensor and the Doppler radar can be further calculated.

[0035] For the wheel axle speed sensor, a 1% error rate is used to calculate the confidence interval corresponding to the first typical speed value. Specifically, 1% is added and subtracted respectively on the basis of the first typical speed value to obtain the confidence interval of the speed (i.e., the first maximum speed value and the first minimum speed value). On this basis, the first typical speed value, the first maximum speed value, and the first minimum speed value can be integrated respectively to obtain the corresponding first typical running distance value, the first maximum running distance value, and the first minimum running distance value, and these values ​​are determined as the first speed and distance measurement data.

[0036] For Doppler radar, in view of the performance characteristics of its sensor, a 2% error rate is used to calculate the confidence interval corresponding to the second typical speed value. Specifically, 2% is added and subtracted respectively on the basis of the second typical speed value to obtain the confidence interval of the speed (i.e., the second maximum speed value and the second minimum speed value). Similarly, the second typical speed value, the second maximum speed value and the second minimum speed value can be integrated respectively to obtain the corresponding second typical running distance value, the second maximum running distance value and the second minimum running distance value, and these values ​​are determined as the second speed and distance measurement data.

[0037] For accelerometers, the signals collected are generally analog signals, which are converted into digital signals through the analog-to-digital conversion process. Subsequently, these digital signals are processed and converted into acceleration measurement values. In addition, the acceleration data also includes some preset acceleration parameter values, which can be pre-calculated or pre-defined by the manufacturer, including: the component of gravity acceleration in the direction of the maximum slope of the train running path; the accelerometer measurement deviation caused by the maximum installation horizontal deviation, which is usually set to 0.17m / s^2; the maximum zero offset of the accelerometer, which is usually set to 0.01m / s^2.

[0038] 102. Determine whether the train is in an idling or slipping state according to a preset judgment method.

[0039] In this step, the first pulse count in the signal collected by the axle speed sensor (first data, where the first data is the data obtained by filtering the collected signal) and the second pulse count in the previous cycle corresponding to the current cycle can be obtained, where the first pulse count and the second pulse count both have corresponding time values, and the second pulse count is the pulse count after the idling slip compensation process. Then the preset wheel diameter, the number of teeth corresponding to the axle speed sensor, and the preset constant can be obtained. Wherein, the preset constant is π3.14159265358979.

[0040] Subsequently, the acceleration threshold can be determined based on the acceleration measurement value and the preset acceleration parameter value. The specific formula is as follows:

[0041] acc slip =|acc out |+AccMaxGradient+AccMaxPitch+AccMaxZero(Formula 1)

[0042] Among them, acc out is the acceleration measurement value, AccMaxGradient is the component of gravity acceleration in the direction of the maximum slope of the train running path, AccMaxPitch is the accelerometer measurement deviation caused by the maximum installation horizontal deviation, 0.17m / s^2, and AccMaxZero is the maximum zero point offset of the accelerometer, 0.01m / s^2.

[0043] Then, a first ratio between the first pulse count and the corresponding time value and a second ratio between the second pulse count and the corresponding time value can be calculated, and then the difference between the first ratio and the second ratio is calculated. At the same time, a first product value between the number of teeth and the time value corresponding to the first pulse count is calculated, and a third ratio between the wheel diameter and the first product value is calculated. Then, a second product value between the difference, a preset constant and the third ratio is calculated. Finally, if the second product value is greater than the acceleration threshold, it is considered that the train is in an idling state; if the second product value is less than the acceleration threshold, it is considered that the train is in a slipping state.

[0044] The formula for judging whether it is in idling state is as follows:

[0045]

[0046] The formula for judging whether it is in a slipping state is as follows:

[0047]

[0048] D is the wheel diameter, PPR is the number of teeth. s2 is the first pulse count, Δt2 is the time value corresponding to the first pulse count (a specific time period), wherein the first pulse count includes the original pulse count of the current cycle, and Δt2≥SLIP_SLIDE_TIME. s1 is the second pulse count, Δt1 is the time value corresponding to the second pulse count, and Δt1≥SLIP_SLI_DTEIME. The preset constant π is 3.14159265358979.

[0049] Among them, SLIP_SLIDE_TIME can be 150ms in actual calculation.

[0050] That is, if the above formula 2 or formula 3 is satisfied, it is considered that the train is in an idling or slipping state, and step 104 can be executed.

[0051] If the train does not satisfy the above formula 2 or formula 3, it is considered that the train is not in an idling or slipping state, and step 103 can be executed.

[0052] 103. If not, obtaining the output speed and distance measurement data of the train according to the first speed and distance measurement data and the second speed and distance measurement data.

[0053] In this step, the second maximum speed value, the second minimum speed value, the second typical speed value, the second maximum distance value, the second minimum distance value and the second typical distance value in the second speed and distance measurement data corresponding to the Doppler radar can be first obtained; as well as the first typical speed value, the first maximum speed value and the first minimum speed value, the first typical distance value, the first maximum distance value and the first minimum distance value in the first speed and distance measurement data of the wheel axle speed sensor.

[0054] Then, according to the second optimal value algorithm, the speed confidence interval of the train is obtained based on the second maximum speed value, the second minimum speed value, the first maximum speed value and the first minimum speed value. Specifically, the smaller one is selected between the second maximum speed value and the first maximum speed value as the maximum speed value of the speed confidence interval; the larger one is selected between the second minimum speed value and the first minimum speed value as the minimum speed value of the speed confidence interval.

[0055] According to the second optimal value algorithm, the confidence interval of the train's running distance is obtained based on the first maximum running distance value, the first minimum running distance value, the second maximum running distance value, and the second minimum running distance value. Specifically, the smaller one is selected from the first maximum running distance value and the second maximum running distance value as the maximum running distance value of the running distance confidence interval; the larger one is selected from the first minimum running distance value and the second minimum running distance value as the minimum running distance value of the running distance confidence interval.

[0056] Finally, the first typical speed value and the second typical speed value are weighted averaged according to the weighted average algorithm to obtain the speed output value of the train; at the same time, the first typical running distance value and the second typical running distance value are weighted averaged according to the weighted average algorithm to obtain the running distance output value of the train. Finally, the speed confidence interval, running distance confidence interval, speed output value and running distance output value are determined as the output speed and distance measurement data of the train and output.

[0057] When performing weighted averaging, the weight distribution can be dynamically adjusted according to environmental conditions. For example, in rainy and snowy weather conditions, the wheel axle speed sensor can be given a higher weight, while the Doppler radar has a relatively lower weight. In contrast, in normal weather conditions, the wheel axle speed sensor and the Doppler radar can be given the same weight. In this way, the weight of the sensor can be flexibly adjusted according to different environmental conditions, which can better ensure the accuracy of speed and distance measurement.

[0058] 104. If so, obtain the compensated speed and distance measurement data corresponding to the wheel axle speed sensor according to the acceleration data.

[0059] In this step, multiple methods can be used to determine the compensated speed and distance measurement data. The first method is:

[0060] The acceleration data can be used to compensate the first speed and distance measurement data. The specific method is as follows: First, use the acceleration measurement value in the acceleration data to update the first typical speed value in the first speed and distance measurement data, so as to obtain the compensated typical speed value. Then, based on the compensated typical speed value, the compensated maximum speed value and minimum speed value are calculated according to the error rate of 1%. Next, the compensated typical speed value, maximum speed value and minimum speed value can be integrated respectively to obtain the corresponding compensated typical running distance value, compensated maximum running distance value and compensated minimum running distance value. These values ​​together constitute the compensated speed and distance measurement data.

[0061] The second method is to iteratively update the specified speed measurement data (including the specified maximum speed value, minimum speed value and typical speed value) in the previous cycle according to the acceleration data, so as to obtain the compensated speed and distance measurement data in the current cycle. This method ensures that the speed and distance measurement data can maintain high accuracy even under adverse conditions.

[0062] 105. Obtain output speed and distance measurement data of the train according to the compensated speed and distance measurement data and the second speed and distance measurement data.

[0063] In this step, after obtaining the second maximum speed value, the second minimum speed value and the second typical speed value, the second maximum running distance value, the second minimum running distance value and the second typical running distance value in the second speed and ranging data corresponding to the Doppler radar and the compensated maximum speed value, the compensated minimum speed value and the compensated typical speed value, the compensated maximum running distance value, the compensated minimum running distance value and the compensated typical running distance value in the compensated speed and ranging data corresponding to the axle speed sensor, the speed confidence interval of the train can be obtained based on the second maximum speed value, the second minimum speed value, the compensated maximum speed value and the compensated minimum speed value according to the second optimal value algorithm.

[0064] At the same time, according to the second optimal value algorithm, the confidence interval of the train's running distance is obtained based on the compensated maximum running distance value, the compensated minimum running distance value, the second maximum running distance value, and the second minimum running distance value.

[0065] Furthermore, the compensated typical speed value and the second typical speed value can be processed according to a weighted average algorithm to obtain a speed output value of the train; at the same time, the compensated typical running distance value and the second typical running distance value can be processed according to a weighted average algorithm to obtain a running distance output value of the train.

[0066] Finally, the speed confidence interval, the travel distance confidence interval, the speed output value and the travel distance output value are determined as the output speed and distance measurement data of the train and output.

[0067] Based on the above Figure 1 It can be seen from the implementation method that the present invention provides a method for measuring speed and distance of a train, which can first obtain the first speed and distance data provided by the axle speed sensor, the second speed and distance data provided by the Doppler radar, and the acceleration data provided by the accelerometer in the current cycle. Subsequently, it should be determined whether the train is in an idling or slipping state. If the train is not in an idling or slipping state, the output speed and distance data of the train can be directly combined with the first speed and distance data of the axle speed sensor and the second speed and distance data of the Doppler radar to determine. On the contrary, if the train is indeed in an idling or slipping state, this indicates that the first speed and distance data of the axle speed sensor has become inaccurate. In this case, the acceleration data needs to be used to calculate the compensated speed and distance data of the axle speed sensor. Afterwards, the output speed and distance data of the train is comprehensively obtained based on the compensated speed and distance data and the second speed and distance data. In this way, the problem of insufficient accuracy of the axle speed sensor of the train in an idling or slipping state is effectively solved, and the accuracy of the overall speed and distance measurement is improved compared with the existing technical solutions.

[0068] Furthermore, as a Figure 1 The embodiment shown in the figure is refined and expanded. The embodiment of the present invention also provides another method for measuring the speed and distance of a train, such as Figure 2 As shown, the specific steps are as follows:

[0069] 201. Obtain first speed and distance measurement data corresponding to the wheel axle speed sensor, second speed and distance measurement data corresponding to the Doppler radar, and acceleration data corresponding to the accelerometer in a current cycle.

[0070] In this embodiment, the first raw data (i.e., pulse count) collected by the wheel axle speed sensor, the second raw data collected by the Doppler radar, and the third raw data collected by the accelerometer in the current cycle can be obtained first. Then, the first raw data, the second raw data, and the third raw data are processed respectively according to the mean filtering algorithm to obtain the first data, the second data, and the third data, so that high-frequency noise can be filtered out to reduce the measurement error caused by train vibration and electromagnetic interference.

[0071] Subsequently, the first speed and distance measurement data corresponding to the wheel axle speed sensor can be obtained according to the first data (the implementation method of this step is the same as the step mentioned in step 101, and will not be repeated here); the second speed and distance measurement data corresponding to the Doppler radar can be obtained according to the second data (the implementation method of this step is the same as the step mentioned in step 101, and will not be repeated here); the acceleration measurement value in the acceleration data corresponding to the accelerometer can be obtained according to the third data (the implementation method of this step is the same as the step mentioned in step 101, and will not be repeated here).

[0072] 202. Determine whether the train is in an idling or slipping state according to a preset judgment method.

[0073] 203. If not, obtaining the output speed and distance measurement data of the train according to the first speed and distance measurement data and the second speed and distance measurement data.

[0074] Among them, the implementation method of step 202-step 203 is the same as that of step 102-step 103, and can achieve the same technical effect and solve the same technical problem, and will not be repeated here.

[0075] 204. If yes, obtain the designated speed measurement data corresponding to the wheel axle speed sensor in the previous cycle.

[0076] 205. Obtain compensated speed and distance measurement data corresponding to the wheel axle speed sensor according to the acceleration data and the specified speed measurement data.

[0077] In this embodiment, steps 204-205 preferably use acceleration data to update the specified speed and distance measurement data in the previous cycle.

[0078] In this method, the specified speed measurement data corresponding to the wheel axle speed sensor in the previous cycle can be obtained first, and the specified speed measurement data includes a specified maximum speed value, a specified minimum speed value, and a specified typical speed value.

[0079] Then, the sum of the acceleration measurement value in the acceleration data and the preset acceleration parameter value is determined as the maximum acceleration value. The specific formula is as follows:

[0080] acc slip_correct_max=acc out +AccMaxGradient+AccMaxPitch+AccMaxZero (Formula 4)

[0082] Among them, acc out is the acceleration measurement value, AccMaxGradient is the component of gravity acceleration in the direction of the maximum slope of the train running path, AccMaxPitch is the accelerometer measurement deviation caused by the maximum installation horizontal deviation, 0.17m / s^2, and AccMaxZero is the maximum zero point offset of the accelerometer, 0.01m / s^2.

[0083] At the same time, the difference between the acceleration measurement value and the preset acceleration parameter value is determined as the minimum acceleration value. The specific formula is as follows:

[0084] acc slip_correct_min =acc out -AccMaxGradient-AccMaxPitch-AccMaxZero (Formula 5)

[0086] Then, the time interval between the current cycle and the previous cycle can be calculated. Then, the maximum product value between the maximum acceleration value and the time interval value is calculated; the minimum product value between the minimum acceleration value and the time interval value is calculated; and the measurement product value between the acceleration measurement value and the time interval value is calculated.

[0087] Then, the sum of the maximum product value and the specified maximum speed value is determined as the compensated maximum speed value in the compensated speed and distance measurement data. The specific formula is as follows:

[0088] Speed_Max i =Speed_Max i-1 +acc slip_correct_max *Δt i (Formula 6)

[0089] Among them, Speed ​​Max i-1 To specify the maximum speed value, Δt i The interval value is the interval value.

[0090] The sum of the minimum product value and the specified minimum speed value is determined as the compensated minimum speed value in the compensated speed and distance measurement data. The specific formula is as follows:

[0091] Speed_Min i =Speed_Min i-1 +acc slip_correct_min *Δt i (Formula 7)

[0092] The sum of the measured product value and the specified typical speed value is determined as the compensated typical speed value in the compensated speed and distance measurement data. The specific formula is as follows:

[0093] Speed_Nor i =Speed_Nor i-1 +acc slip_correct_nor *Δt i (Formula 8)

[0094] Finally, the maximum compensated running distance value, the minimum compensated running distance value and the typical compensated running distance value in the compensated speed and distance measurement can be obtained according to the maximum compensated speed value, the minimum compensated speed value and the typical compensated speed value.

[0095] 206. Obtain output speed and distance measurement data of the train according to the compensated speed and distance measurement data and the second speed and distance measurement data.

[0096] Among them, the implementation method of step 206 is the same as that of step 105, and can achieve the same technical effect and solve the same technical problem, and will not be repeated here.

[0097] Finally, it should be noted that in each cycle, it is necessary to re-judge whether the train is in an idling or slipping state, and to determine in real time whether the train has exited this state. Because when it is detected that the train has exited the idling or slipping state, it can be confirmed that the first speed and distance measurement data provided by the axle speed sensor is accurate. At this time, the final speed and distance measurement data of the train can be output based on the first speed and distance measurement data and the second speed and distance measurement data provided by the Doppler radar. This method ensures that the accuracy of the speed and distance measurement data is timely corrected and guaranteed during the entire operation process.

[0098] The train is considered to have exited the idling state when the following conditions are met:

[0099] (1)

[0100] (2) The speed difference between this wheel axle speed sensor and the wheel axle speed sensor that is not in an idling slip state does not exceed 4 km / h (if there is no speed sensor that is not in an idling slip state, this condition does not need to be met)

[0101] The train is considered to have exited the skidding state when the following conditions are met:

[0102] (1)

[0103] (2) The speed difference between this wheel axle speed sensor and the wheel axle speed sensor that is not in an idling slip state does not exceed 4 km / h (if there is no speed sensor that is not in an idling slip state, this condition does not need to be met)

[0104] Furthermore, as a response to the above Figure 1 In order to realize the method shown in the figure, the embodiment of the present invention also provides a train speed and distance measuring device for the above Figure 1 The device embodiment corresponds to the aforementioned method embodiment. For ease of reading, this device embodiment will not repeat the details of the aforementioned method embodiment one by one, but it should be clear that the device in this embodiment can correspond to all the contents of the aforementioned method embodiment. Figure 3 As shown, the device comprises:

[0105] The data acquisition unit 301 is used to acquire the first speed and distance measurement data corresponding to the wheel axle speed sensor, the second speed and distance measurement data corresponding to the Doppler radar, and the acceleration data corresponding to the accelerometer in the current cycle;

[0106] A state determination unit 302 is used to determine whether the train is in an idling or slipping state according to a preset determination method;

[0107] A first data determining unit 303 is configured to obtain output speed and distance measurement data of the train according to the first speed and distance measurement data and the second speed and distance measurement data obtained by the data obtaining unit 301 if the judgment result of the state judging unit 302 is not in the state;

[0108] A second data determination unit 304 is configured to obtain compensated speed and distance measurement data corresponding to the wheel axle speed sensor according to the acceleration data obtained by the data acquisition unit 301 if the judgment result of the state judgment unit 302 is in;

[0109] The third data determination unit 305 is used to obtain the output speed and distance measurement data of the train according to the compensated speed and distance measurement data determined by the second data determination unit 304 and the second speed and distance measurement data.

[0110] Furthermore, as a response to the above Figure 2 In order to realize the method shown in the figure, the embodiment of the present invention also provides another train speed and distance measuring device for the above Figure 2 The device embodiment corresponds to the aforementioned method embodiment. For ease of reading, this device embodiment will not repeat the details of the aforementioned method embodiment one by one, but it should be clear that the device in this embodiment can correspond to all the contents of the aforementioned method embodiment. Figure 4 As shown, the device comprises:

[0111] The data acquisition unit 301 is used to acquire the first speed and distance measurement data corresponding to the wheel axle speed sensor, the second speed and distance measurement data corresponding to the Doppler radar, and the acceleration data corresponding to the accelerometer in the current cycle;

[0112] A state determination unit 302 is used to determine whether the train is in an idling or slipping state according to a preset determination method;

[0113] A first data determining unit 303 is configured to obtain output speed and distance measurement data of the train according to the first speed and distance measurement data and the second speed and distance measurement data obtained by the data obtaining unit 301 if the judgment result of the state judging unit 302 is not in the state;

[0114] A second data determination unit 304 is configured to obtain compensated speed and distance measurement data corresponding to the wheel axle speed sensor according to the acceleration data obtained by the data acquisition unit 301 if the judgment result of the state judgment unit 302 is in;

[0115] The third data determination unit 305 is used to obtain the output speed and distance measurement data of the train according to the compensated speed and distance measurement data determined by the second data determination unit 304 and the second speed and distance measurement data.

[0116] In an optional implementation manner, before the data acquisition unit 301, the device further includes a data filtering unit 306, and the data filtering unit 306 is specifically used to:

[0117] Acquire the first original data collected by the wheel axle speed sensor, the second original data collected by the Doppler radar, and the third original data collected by the accelerometer in the current cycle;

[0118] The first original data, the second original data and the third original data are processed respectively according to a mean filtering algorithm to obtain first data, second data and third data;

[0119] Obtaining first speed and distance measurement data corresponding to the wheel axle speed sensor according to the first data;

[0120] Obtaining second speed and distance measurement data corresponding to the Doppler radar according to the second data;

[0121] The acceleration measurement value in the acceleration data corresponding to the accelerometer is obtained according to the third data.

[0122] In an optional implementation manner, the state determination unit 302 is specifically configured to:

[0123] Acquire a first pulse count in the first data and a second pulse count in a previous cycle corresponding to a current cycle, wherein the first pulse count and the second pulse count both have corresponding time values, and the second pulse count is a pulse count after idling slip compensation processing;

[0124] Obtaining a preset wheel diameter, the number of teeth corresponding to the wheel axle speed sensor, and a preset constant;

[0125] Whether the train is in an idling or slipping state is determined based on the acceleration measurement value and the preset acceleration parameter value in the acceleration data, the first pulse count and the corresponding time value, the second pulse count and the corresponding time value, the wheel diameter, the number of teeth and the preset constant.

[0126] In an optional implementation manner, the state judgment unit 302 is specifically used to judge whether the train is in an idling or slipping state according to the acceleration measurement value and the preset acceleration parameter value in the acceleration data, the first pulse count and the corresponding time value, the second pulse count and the corresponding time value, the wheel diameter, the number of teeth and the preset constant:

[0127] Determining an acceleration threshold value according to the acceleration measurement value and the preset acceleration parameter value;

[0128] calculating a first ratio between the first pulse count and a corresponding time value and a second ratio between the second pulse count and a corresponding time value;

[0129] calculating a difference between the first ratio and the second ratio;

[0130] calculating a first product value between the number of teeth and the time value corresponding to the first pulse count, and calculating a third ratio between the wheel diameter and the first product value;

[0131] Calculating a second product value between the difference, the preset constant and the third ratio;

[0132] If the second product value is greater than the acceleration threshold, it is considered that the train is in an idling state;

[0133] If the second product value is less than the acceleration threshold, it is considered that the train is in a slipping state.

[0134] In an optional implementation manner, the second data determination unit 304 is specifically configured to:

[0135] Acquire designated speed measurement data corresponding to the wheel axle speed sensor in the previous cycle, wherein the designated speed measurement data includes a designated maximum speed value, a designated minimum speed value, and a designated typical speed value;

[0136] Determine the sum of the acceleration measurement value and the preset acceleration parameter value in the acceleration data as the maximum acceleration value, and determine the difference between the acceleration measurement value and the preset acceleration parameter value as the minimum acceleration value;

[0137] Calculate the time interval between the current cycle and the previous cycle;

[0138] The compensated speed and distance measurement data is obtained according to the time interval value, the maximum acceleration value, the minimum acceleration value, the acceleration measurement value, the specified maximum speed value, the specified minimum speed value and the specified typical speed value.

[0139] In an optional implementation manner, when the second data determination unit 304 obtains the compensated speed and distance measurement data according to the time interval value, the maximum acceleration value, the minimum acceleration value, the acceleration measurement value, the specified maximum speed value, the specified minimum speed value, and the specified typical speed value, it is specifically used to:

[0140] Calculating a maximum product value between the maximum acceleration value and the time interval value;

[0141] Calculating a minimum product value between the minimum acceleration value and the time interval value;

[0142] Calculating a measurement product value between the acceleration measurement value and the time interval value;

[0143] Determine the sum of the maximum product value and the specified maximum speed value as the compensated maximum speed value in the compensated speed and distance measurement data;

[0144] Determine the sum of the minimum product value and the specified minimum speed value as the compensated minimum speed value in the compensated speed and distance measurement data;

[0145] Determine the sum of the measured product value and the specified typical speed value as the compensated typical speed value in the compensated speed and distance measurement data;

[0146] The compensated maximum running distance value, the compensated minimum running distance value and the compensated typical running distance value in the compensated speed and distance measurement are obtained according to the compensated maximum speed value, the compensated minimum speed value and the compensated typical speed value.

[0147] In an optional implementation manner, the third data determination unit 305 is specifically configured to:

[0148] Obtaining a second maximum speed value, a second minimum speed value, a second typical speed value, a second maximum running distance value, a second minimum running distance value, and a second typical running distance value in the second speed and distance measurement data corresponding to the Doppler radar;

[0149] According to a second optimal value algorithm, a speed confidence interval of the train is obtained based on the second maximum speed value, the second minimum speed value, the compensated maximum speed value and the compensated minimum speed value;

[0150] According to the second optimal value algorithm, a confidence interval of the running distance of the train is obtained based on the compensated maximum running distance value, the compensated minimum running distance value, the second maximum running distance value, and the second minimum running distance value;

[0151] Processing the compensated typical speed value and the second typical speed value according to a weighted average algorithm to obtain a speed output value of the train;

[0152] Processing the compensated typical running distance value and the second typical running distance value according to a weighted average algorithm to obtain a running distance output value of the train;

[0153] The speed confidence interval, the travel distance confidence interval, the speed output value and the travel distance output value are determined as the output speed and distance measurement data of the train and outputted.

[0154] Furthermore, an embodiment of the present invention further provides a storage medium, wherein the storage medium is used to store a computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the above Figure 1-2 The train speed and distance measurement method described in .

[0155] Furthermore, an embodiment of the present invention further provides a processor, the processor is used to run a program, wherein the program executes the above Figure 1-2 The train speed and distance measurement method described in .

[0156] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0157] It is understandable that the related features in the above methods and devices can be referenced to each other. In addition, the "first", "second" and the like in the above embodiments are used to distinguish the embodiments, but do not represent the advantages and disadvantages of the embodiments.

[0158] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0159] The algorithm and display provided herein are not inherently related to any particular computer, virtual system or other device. Various general purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious that the structure required for constructing such systems. In addition, the present invention is not directed to any specific programming language either. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the description of the above specific languages ​​is for disclosing the best mode of the present invention.

[0160] In addition, the memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0161] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0162] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes 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 generate 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.

[0163] 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 including 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.

[0164] 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 in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0165] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0166] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0167] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0168] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0169] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0170] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for measuring speed and distance of a train, characterized in that: The method comprises: Obtaining first speed and distance measurement data corresponding to the wheel axle speed sensor, second speed and distance measurement data corresponding to the Doppler radar, and acceleration data corresponding to the accelerometer in the current cycle; Determine whether the train is in an idling or slipping state according to a preset determination method; If not, obtaining the output speed and distance measurement data of the train according to the first speed and distance measurement data and the second speed and distance measurement data; If yes, then obtain the compensated speed and distance measurement data corresponding to the wheel axle speed sensor according to the acceleration data; The output speed and distance measurement data of the train is obtained according to the compensated speed and distance measurement data and the second speed and distance measurement data.

2. The method according to claim 1, characterized in that: Before obtaining the first speed and distance measurement data corresponding to the wheel axle speed sensor, the second speed and distance measurement data corresponding to the Doppler radar, and the acceleration data corresponding to the accelerometer in the current cycle, the method further includes: Acquire the first original data collected by the wheel axle speed sensor, the second original data collected by the Doppler radar, and the third original data collected by the accelerometer in the current cycle; The first original data, the second original data and the third original data are processed respectively according to a mean filtering algorithm to obtain first data, second data and third data; Obtaining first speed and distance measurement data corresponding to the wheel axle speed sensor according to the first data; Obtaining second speed and distance measurement data corresponding to the Doppler radar according to the second data; The acceleration measurement value in the acceleration data corresponding to the accelerometer is obtained according to the third data.

3. The method according to claim 1, characterized in that: Determine whether the train is in an idling or slipping state according to a preset judgment method, including: Acquire a first pulse count in the first data and a second pulse count in a previous cycle corresponding to a current cycle, wherein the first pulse count and the second pulse count both have corresponding time values, and the second pulse count is a pulse count after idling slip compensation processing; Obtaining a preset wheel diameter, the number of teeth corresponding to the wheel axle speed sensor, and a preset constant; Whether the train is in an idling or slipping state is determined based on the acceleration measurement value and the preset acceleration parameter value in the acceleration data, the first pulse count and the corresponding time value, the second pulse count and the corresponding time value, the wheel diameter, the number of teeth and the preset constant.

4. The method according to claim 3, characterized in that Judging whether the train is in an idling or slipping state according to the acceleration measurement value and the preset acceleration parameter value in the acceleration data, the first pulse count and the corresponding time value, the second pulse count and the corresponding time value, the wheel diameter, the number of teeth and the preset constant, includes: Determining an acceleration threshold value according to the acceleration measurement value and the preset acceleration parameter value; calculating a first ratio between the first pulse count and a corresponding time value and a second ratio between the second pulse count and a corresponding time value; calculating a difference between the first ratio and the second ratio; calculating a first product value between the number of teeth and the time value corresponding to the first pulse count, and calculating a third ratio between the wheel diameter and the first product value; Calculating a second product value between the difference, the preset constant and the third ratio; If the second product value is greater than the acceleration threshold, it is considered that the train is in an idling state; If the second product value is less than the acceleration threshold, it is considered that the train is in a slipping state.

5. The method according to claim 1, characterized in that Obtaining compensated speed and distance measurement data corresponding to the wheel axle speed sensor according to the acceleration data, including: Acquire designated speed measurement data corresponding to the wheel axle speed sensor in the previous cycle, wherein the designated speed measurement data includes a designated maximum speed value, a designated minimum speed value, and a designated typical speed value; Determine the sum of the acceleration measurement value and the preset acceleration parameter value in the acceleration data as the maximum acceleration value, and determine the difference between the acceleration measurement value and the preset acceleration parameter value as the minimum acceleration value; Calculate the time interval between the current cycle and the previous cycle; The compensated speed and distance measurement data is obtained according to the time interval value, the maximum acceleration value, the minimum acceleration value, the acceleration measurement value, the specified maximum speed value, the specified minimum speed value and the specified typical speed value.

6. The method according to claim 5, characterized in that The compensated speed and distance measurement data is obtained according to the time interval value, the maximum acceleration value, the minimum acceleration value, the acceleration measurement value, the specified maximum speed value, the specified minimum speed value and the specified typical speed value, including: Calculating a maximum product value between the maximum acceleration value and the time interval value; Calculating a minimum product value between the minimum acceleration value and the time interval value; Calculating a measurement product value between the acceleration measurement value and the time interval value; Determine the sum of the maximum product value and the specified maximum speed value as the compensated maximum speed value in the compensated speed and distance measurement data; Determine the sum of the minimum product value and the specified minimum speed value as the compensated minimum speed value in the compensated speed and distance measurement data; Determine the sum of the measured product value and the specified typical speed value as the compensated typical speed value in the compensated speed and distance measurement data; The compensated maximum running distance value, the compensated minimum running distance value and the compensated typical running distance value in the compensated speed and distance measurement are obtained according to the compensated maximum speed value, the compensated minimum speed value and the compensated typical speed value.

7. The method according to claim 1, characterized in that Obtaining output speed and distance measurement data of the train according to the compensated speed and distance measurement data and the second speed and distance measurement data, including: Obtaining a second maximum speed value, a second minimum speed value, a second typical speed value, a second maximum running distance value, a second minimum running distance value, and a second typical running distance value in the second speed and distance measurement data corresponding to the Doppler radar; According to a second optimal value algorithm, a speed confidence interval of the train is obtained based on the second maximum speed value, the second minimum speed value, the compensated maximum speed value and the compensated minimum speed value; According to the second optimal value algorithm, a confidence interval of the running distance of the train is obtained based on the compensated maximum running distance value, the compensated minimum running distance value, the second maximum running distance value, and the second minimum running distance value; Processing the compensated typical speed value and the second typical speed value according to a weighted average algorithm to obtain a speed output value of the train; Processing the compensated typical running distance value and the second typical running distance value according to a weighted average algorithm to obtain a running distance output value of the train; The speed confidence interval, the travel distance confidence interval, the speed output value and the travel distance output value are determined as the output speed and distance measurement data of the train and outputted.

8. A train speed and distance measuring device, characterized in that: The device comprises: A data acquisition unit, used to acquire first speed and distance measurement data corresponding to the wheel axle speed sensor, second speed and distance measurement data corresponding to the Doppler radar, and acceleration data corresponding to the accelerometer in the current cycle; A state judgment unit, used to judge whether the train is in an idling or slipping state according to a preset judgment method; a first data determining unit, configured to obtain output speed and distance measurement data of the train according to the first speed and distance measurement data and the second speed and distance measurement data acquired by the data acquiring unit if the judgment result of the state judging unit is not in the state; a second data determining unit, configured to obtain compensated speed and distance measurement data corresponding to the wheel axle speed sensor according to the acceleration data acquired by the data acquiring unit if the determination result of the state determining unit is in; The third data determination unit is used to obtain the output speed and distance measurement data of the train according to the compensated speed and distance measurement data determined by the second data determination unit and the second speed and distance measurement data.

9. A storage medium, characterized in that: The storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the train speed and distance measurement method as described in any one of claims 1 to 7.

10. A processor, characterized in that: The processor is used to run a program, wherein the program, when running, executes the train speed and distance measurement method as described in any one of claims 1 to claim 7.

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