Sensor data processing method and apparatus, electronic device, and storage medium

Abstract

A sensor data processing method, comprising: acquiring a sensor data set (S201); determining N sensor input sampling values (S202); and on the basis of each sensor input sampling value, determining from the sensor data set a sensor output sampling value corresponding to each sensor input sampling value, so as to obtain N pieces of sampling data (S203). Also provided are a sensor data processing apparatus, an electronic device, and a computer readable storage medium.

Description

Sensor data processing method, device, electronic device and storage medium

[0001] [Corrected 27.12.2024 according to Rule 91] This application claims priority to Chinese patent application No. CN 202410122441.2, filed with the State Intellectual Property Office on January 29, 2024, entitled “A sensor data processing method, device, electronic device and storage medium”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] The present application relates to the field of sensor technology, and in particular to a sensor data processing method, device, electronic device, and storage medium. Background Art

[0003] A sensor is a device that can directly sense the measured quantity and output an electrical signal or other signal that has a definite relationship with the measured quantity. During the actual use of the vehicle, there are sensors that collect relevant signals for the vehicle's Electronic Power Steering System (EPS). As one of the key devices of the electronic power steering system, the performance of the sensor directly determines the performance of the electronic power steering system, so it is necessary to conduct relevant analysis on the performance of the sensor. In general, the performance of the sensor is analyzed based on the corresponding curve between the sensor input value and the sensor output value. In order to determine the corresponding curve between the sensor input value and the sensor output value, it is necessary to determine the corresponding data set of the sensor input value and the sensor output value.

[0004] In the prior art, after receiving sensor output waveforms and sensor input waveforms and correlating them, a sensor data set consisting of sensor output values ​​and corresponding sensor input values ​​can be determined. This sensor data set is organized into a table, and the sensor input values ​​and corresponding sensor output values ​​are sorted. N sensor input values ​​and corresponding sensor output values ​​are evenly selected to ultimately determine N sampled data.

[0005] However, organizing and sorting the sensor data set into a table and manually selecting N sensor input values ​​and corresponding sensor output values ​​may result in low accuracy of the determined N sampled data and low efficiency in the process of determining the N sampled data.

[0006] It should be pointed out that the information disclosed in the background technology section of this application is only intended to deepen the understanding of the general background technology of this application, and should not be regarded as an admission or any form of implication that the information constitutes prior art already known to those skilled in the art. Summary of the Invention

[0007] In view of this, the present application provides a sensor data processing method, device, electronic device and storage medium, so as to solve the problem in the prior art that by organizing the sensor data set into a table and sorting it, manually selecting N sensor input values ​​and corresponding sensor output values, the final determination of the N sampling data may result in low accuracy and low efficiency of the determination process of the final determination of the N sampling data.

[0008] In a first aspect, an embodiment of the present application provides a sensor data processing method, comprising:

[0009] Acquire a sensor data set, the sensor data set including M sensor data, each of the sensor data including a sensor input value and a sensor output value;

[0010] Determine N sensor input sampling values, where M>N>1;

[0011] According to each of the sensor input sampling values, determining a sensor output sampling value corresponding to each of the sensor input sampling values ​​in the sensor data set to obtain N sampling data;

[0012] The sensor output sampling value is a sensor output value corresponding to a sensor input value adjacent to the sensor input sampling value in the sensor data set.

[0013] In a possible implementation, after acquiring the sensor data set, the method further includes:

[0014] Positive travel sensor data and negative travel sensor data in the sensor data set are determined.

[0015] In a possible implementation, determining the forward travel sensor data and the reverse travel sensor data in the sensor data set includes:

[0016] According to a change trend of the sensor output value in the sensor data set, the forward stroke sensor data and the reverse stroke sensor data in the sensor data set are determined.

[0017] In a possible implementation, determining the forward travel sensor data and the reverse travel sensor data in the sensor data set according to a change trend of the sensor output value in the sensor data set includes:

[0018] Determining sensor data in the sensor data set whose sensor output values ​​are in an increasing interval as positive stroke sensor data;

[0019] The sensor data in the sensor data set whose sensor output value is in a decreasing interval is determined as the reverse stroke sensor data.

[0020] In a possible implementation, determining the forward travel sensor data and the reverse travel sensor data in the sensor data set according to a change trend of the sensor output value in the sensor data set includes:

[0021] Determining sensor data in the sensor data set whose sensor output values ​​are in an increasing interval as reverse stroke sensor data;

[0022] The sensor data in the sensor data set whose sensor output value is in a decreasing interval is determined as positive stroke sensor data.

[0023] In a possible implementation, determining, in a sensor data set, a sensor output sampling value corresponding to each sensor input sampling value to obtain N sampling data includes:

[0024] According to each of the sensor input sampling values, determining a forward stroke sensor output sampling value and a reverse stroke sensor output sampling value corresponding to each of the sensor input sampling values ​​in the sensor data set, to obtain N forward stroke sampling data and N reverse stroke sampling data;

[0025] Among them, the positive stroke sensor output sampling value is the positive stroke sensor output value corresponding to the positive stroke sensor input value adjacent to the sensor input sampling value in the sensor data set; the reverse stroke sensor output sampling value is the reverse stroke sensor output value corresponding to the reverse stroke sensor input value adjacent to the sensor input sampling value in the sensor data set.

[0026] In a possible implementation, the minimum value and the maximum value of the N sensor input sampling values ​​are respectively the minimum value and the maximum value of the sensor range.

[0027] In a possible implementation, the difference between any two adjacent sensor input sampling values ​​among the N sensor input sampling values ​​is equal.

[0028] In a second aspect, an embodiment of the present application provides a sensor data processing device, including:

[0029] A sensor data set acquisition module, configured to acquire a sensor data set, wherein the sensor data set includes M sensor data, each of which includes a sensor input value and a sensor output value;

[0030] A sensor input sampling value determination module, configured to determine N sensor input sampling values, where M>N>1;

[0031] a sampling data acquisition module, configured to determine, in a sensor data set, a sensor output sampling value corresponding to each sensor input sampling value, and obtain N sampling data;

[0032] The sensor output sampling value is a sensor output value corresponding to a sensor input value adjacent to the sensor input sampling value in the sensor data set.

[0033] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0034] processor;

[0035] Memory;

[0036] and a computer program, wherein the computer program is stored in the memory, and the computer program includes instructions, which, when executed by the processor, enable the electronic device to perform any one of the methods according to the first aspect.

[0037] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the methods in the first aspect.

[0038] In an embodiment of the present application, a sensor data processing device acquires a sensor data set and determines N sensor input sample values. Simultaneously, the sensor data processing device determines, based on each sensor input sample value, a sensor output sample value corresponding to each sensor input sample value within the sensor data set, thereby obtaining N sample data. This process does not involve complex manual operations, resulting in a high degree of accuracy in the final determined N sample data, and a high efficiency in the process of determining the N sample data. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0040] FIG1 is a schematic diagram of an application scenario of EPS provided by related technology.

[0041] FIG2 is a flow chart of a sensor data processing method provided in an embodiment of the present application.

[0042] FIG3 is a schematic diagram of an application scenario of a sensor data processing device provided by related technology.

[0043] FIG4 is a flow chart of another sensor data processing method provided in an embodiment of the present application.

[0044] FIG5 is a schematic structural diagram of a sensor data processing device provided in an embodiment of the present application.

[0045] FIG6 is a schematic structural diagram of another sensor data processing device provided in an embodiment of the present application.

[0046] FIG7 is a schematic structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0047] In order to better understand the technical solution of the present application, the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0048] It should be clear that the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0049] The terms used in the embodiments of the present application are for the purpose of describing specific embodiments only and are not intended to limit the present application. The singular forms "a", "an", "the" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise.

[0050] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. Furthermore, the character " / " in this document generally indicates an "or" relationship between the associated objects.

[0051] An electric power steering system (EPS) relies directly on an electric motor to provide assist torque. During vehicle use, various sensors collect the driver's steering wheel torque and steering wheel angle, and transmit the steering wheel angle to the EPS. The EPS calculates the assist torque based on the steering wheel torque and angle, converting it into a current command for the power-assisted motor, which then controls the motor to generate the corresponding assist torque. This assist torque is amplified by a gear reduction mechanism and applied to the steering gear, ultimately assisting the driver in overcoming steering resistance and steering the vehicle.

[0052] For ease of understanding, a detailed description is given below with reference to the accompanying drawings and specific embodiments.

[0053] Figure 1 illustrates an EPS application scenario. This scenario depicts a steering wheel 101, an electronic power steering system 102, a steering shaft 103, a rack-and-pinion steering gear 104, and a tire 105. The electronic power steering system 102 specifically includes an electronic control unit (ECU) 1021, a sensor 1022, a power-assisted motor 1023, and a gear reduction mechanism 1024.

[0054] As shown in Figure 1, the steering wheel 101 controls the steering of the tire 105 through the steering shaft 103 and the rack and pinion steering gear 104; the sensor 1022 is used to collect the sensor signal on the steering shaft 103; the ECU 1021 outputs the corresponding power-assisted motor control instruction according to the received sensor signal; the power-assisted motor 1023 applies the auxiliary torque to the steering shaft 103 through the power-assisted gear reduction mechanism 1024, thereby assisting the steering shaft 103 to rotate.

[0055] In actual use, when the driver turns the steering wheel 101, the steering wheel 101 drives the steering shaft 103 to rotate. At this time, the sensor 1022 transmits the sensor signal collected from the steering shaft 103 to the ECU 1021. Based on the received sensor signal, the ECU 1021 controls the power-assisting motor 1023 to drive the gear reduction mechanism 1024 to rotate, thereby assisting the steering shaft 103 to rotate, and ultimately drives the rack and pinion steering gear 104 to control the tire steering.

[0056] It should be noted that Figure 1 is merely an illustrative example of an application scenario involved in the embodiments of this application and should not be construed as limiting the scope of protection of this application. Furthermore, it should be understood that sensor 1022 is merely an illustrative example and may specifically be a torque sensor, an angle sensor, or a torque-angle sensor (a torque-angle sensor is an integrated combination of a torque sensor and an angle sensor). This application does not specifically limit the sensor type.

[0057] As a key component of an electronic power steering system, the performance of the sensor directly determines its effectiveness. Therefore, sensor performance analysis is essential. Generally, sensor performance analysis is performed based on a corresponding curve between sensor input and output values. To determine this corresponding curve, a data set of corresponding sensor input and output values ​​is required.

[0058] In related technologies, after receiving sensor output waveforms and sensor input waveforms and correlating them, a sensor data set consisting of sensor output values ​​and corresponding sensor input values ​​can be determined. This sensor data set is organized into a table, and the sensor input values ​​and corresponding sensor output values ​​are sorted. N sensor input values ​​and corresponding sensor output values ​​are evenly selected to ultimately determine N sampled data.

[0059] For example, when the sensor to be tested is an angle sensor, the organized sensor data set is shown in Table 1. It can be understood that six evenly selected sensor input values ​​and corresponding sensor output values ​​are (0°, 0.1°), (179.5°, 180.2°), (360°, 360.8°), ... (1080.4°, 1079.6°) to form six sampled data. The N sampled data are expressed as coordinate points, with the angle sensor input value on the left and the angle sensor output value on the right, i.e., (sensor input value, sensor output value).

[0060] Table 1:

[0061] Of course, those skilled in the art may uniformly select other numbers of sensor input values ​​and corresponding sensor output values ​​to form the N sampled data, depending on actual needs. For example, when the accuracy of the fitted curve corresponding to the sensor input values ​​and sensor output values ​​is required to be high, a larger number of sensor input values ​​and corresponding sensor output values ​​may be selected to form the N sampled data; when the computing level of the sensor data processing device is low and the efficiency requirement is high, a smaller number of sensor input values ​​and corresponding sensor output values ​​may be selected to form the N sampled data. This application does not impose specific limitations on this.

[0062] However, by arranging the sensor data set into a table and sorting it, and manually selecting N sensor input values ​​and corresponding sensor output values, the accuracy of the determined N sampling data may be low, and the efficiency of the sample data determination process may be low.

[0063] To address the above issues, in an embodiment of the present application, a sensor data processing device acquires a sensor data set and determines N sensor input sample values. Simultaneously, the sensor data processing device determines, based on each sensor input sample value, the sensor output sample value corresponding to each sensor input sample value within the sensor data set, thereby obtaining N sample data. This process does not involve complex manual operations, resulting in a high degree of accuracy in the final determination of the N sample data, and a high efficiency in the process of determining the N sample data. Specifically, this process is described in detail below with reference to the accompanying drawings and specific embodiments.

[0064] Referring to Figure 2, there is shown a flow chart of a sensor data processing method provided in an embodiment of the present application. As shown in Figure 2, the method specifically includes the following steps.

[0065] Step S201: Acquire a sensor data set.

[0066] In an embodiment of the present application, a sensor data processing device obtains a sensor data set comprising M sensor data, wherein each sensor data comprises a sensor input value and a sensor output value. It is understood that the sensor data set comprises the M sensor input values ​​and the sensor output value corresponding to each sensor input value.

[0067] In practical applications, the sensor data processing device receives a raw sensor data set. Therefore, the raw sensor data set must be processed before the sensor data set is acquired. For a clearer description, this application also provides an application scenario for the sensor data processing device. Specifically, this is described in detail below with reference to the accompanying drawings and specific embodiments.

[0068] See Figure 3, which illustrates an application scenario for a sensor data processing device according to related art. As shown in Figure 3, a motor module 301, a sensor 302, a sensor data acquisition device 303, and a sensor data processing device 304 are shown. Motor module 301 is electrically connected to sensor data acquisition device 303; sensor 302 is used to collect data from motor module 301; sensor 302 is electrically connected to sensor data acquisition device 303; and sensor data acquisition device 303 is electrically connected to sensor data processing device 304.

[0069] In actual applications, the sensor collects relevant actions of the motor module and outputs the collected sensor output signal; the sensor data acquisition device receives the sensor output signal output by the sensor and the sensor input signal sent by the motor module; the sensor data acquisition device receives the sensor input signal and the sensor output signal, and performs relevant processing on the sensor input signal and the sensor output signal to generate sensor raw input data and sensor raw output data corresponding to the sensor input signal and the sensor output signal respectively, and then sends the generated sensor raw input data and sensor raw output data, that is, the sensor raw data set, to the sensor data processing device; the sensor data processing device obtains the sensor data set based on the sensor raw data set.

[0070] It should be noted that the sensor output signal and sensor input signal are generally pulse width modulated (PWM) signals, while the sensor raw data set is the corresponding sensor raw input data and sensor raw output data. It can be understood that the sensor output signal and sensor input signal are analog signals, while the sensor raw input data and sensor raw output data are digital signals. It can be understood that in this case, the "sensor raw input data" and "sensor raw output data" are intermediate quantities, and their units are not the corresponding torque units or angle units. Therefore, the sensor data processing device performs relevant processing on the sensor raw data set to obtain the sensor data set.

[0071] Of course, in a possible implementation, the sensor data acquisition device sends the processed sensor data set to the sensor data processing device, and this application does not impose any specific restrictions on this.

[0072] In one possible implementation, the sensor corresponding to the "sensor data set" described above may be a torque angle sensor. Of course, it may also be a torque sensor or an angle sensor, and this application does not impose specific limitations on this.

[0073] Step S202: Determine N sensor input sampling values.

[0074] In the embodiment of the present application, N sensor input sampling values ​​are determined, where M>N>1.

[0075] It is understood that the number of determined sensor input sample values ​​should be smaller than the number of sensor input values ​​or sensor output values ​​in the sensor data. This is because when the number of sensor input sample values ​​is greater than the number of sensor input values ​​or sensor output values ​​in the sensor data, the data determined based on the sensor input sample values ​​will inevitably have different sensor input sample values ​​corresponding to the same sensor output value, which will make the determined N sample data less accurate, thereby affecting the performance analysis of the sensor.

[0076] In one possible implementation, six sensor input sampling values ​​are determined. Of course, those skilled in the art may determine other numbers of sensor input sampling values ​​based on actual needs. For example, when the accuracy of the fitted corresponding curve is required to be high, more sensor input sampling values ​​may be selected; when the computing level of the sensor data processing device is low and the efficiency requirement is high, fewer sensor input sampling values ​​may be selected. This application does not impose specific limitations on this.

[0077] In one possible implementation, N sensor input sampling values ​​are determined in response to a user-triggered operation. It is understood that the user can input N sensor input sampling values ​​into the sensor data processing device. For example, the user can input six torque sensor input sampling values, namely, 0 N·M, 3 N·M, 6 N·M, 9 N·M, 12 N·M, and 15 N·M, into the sensor data processing device. Similarly, the user can input seven angle sensor input sampling values, namely, 0°, 180°, 360°, 540°, 720°, 900°, and 1080°, into the sensor data processing device.

[0078] In one possible implementation, the sensor input sampling values ​​are pre-stored. After the sensor data processing device acquires the sensor data set, it determines the pre-stored sensor input sampling values ​​based on the type of the sensor data set. For example, the pre-stored torque sensor output sampling values ​​are 0 N·M, 3 N·M, 6 N·M, 9 N·M, 12 N·M, and 15 N·M; and the pre-stored angle sensor output sampling values ​​are 0°, 180°, 360°, 540°, 720°, 900°, and 1080°. When the sensor data processing device obtains the torque sensor data set, it will determine the pre-stored sensor input sampling values ​​as 0N·M, 3N·M, 6N·M, 9N·M, 12N·M and 15N·M according to the type of the sensor data set; similarly, when the sensor data processing device obtains the angle sensor data set, it will determine the pre-stored sensor input sampling values ​​as 0°, 180°, 360°, 540°, 720°, 900° and 1080° according to the type of the sensor data set.

[0079] In one possible implementation, the minimum and maximum values ​​of the N sensor input sample values ​​are the minimum and maximum values ​​of the sensor's range, respectively. For example, when the range of an angle sensor is [0°, 1080°], the minimum and maximum values ​​of the N sensor input sample values ​​are determined to be 0° and 1080°, respectively. Similarly, when the range of a torque sensor is [0 N·M, 15 N·M], the minimum and maximum values ​​of the N sensor input sample values ​​are determined to be 0 N·M and 15 N·M, respectively.

[0080] It can be understood that in the application embodiment, by setting the minimum value and maximum value of the N sensor input sampling values ​​to be the minimum value and maximum value of the sensor range respectively, the data in the sensor data set can be obtained to the maximum extent, thereby making the data information contained in the determined N sampling data more comprehensive, and ultimately making the N sampling data better reflect the relevant performance of the sensor.

[0081] In one possible implementation, the difference between any two adjacent sensor input sampling values ​​among the N sensor input sampling values ​​is equal, that is, the sensor input sampling values ​​are evenly distributed. For example, when setting six torque sensor input sampling values, they can be set to 0N·M, 3N·M, 6N·M, 9N·M, 12N·M, and 15N·M; similarly, when setting seven angle sensor input sampling values, they can be set to 0°, 180°, 360°, 540°, 720°, 900°, and 1080°. This application does not impose specific limitations on this.

[0082] It can be understood that in the application embodiment, by evenly setting N sensor input sampling values, the determined N sampling data can carry more information in the sensor data set, thereby making the N sampling data better reflect the relevant performance of the sensor.

[0083] Step S203: According to each sensor input sampling value, determine the sensor output sampling value corresponding to each sensor input sampling value in the sensor data set to obtain N sampling data.

[0084] In an embodiment of the present application, a sensor data processing device determines, based on each sensor input sample value, a sensor output sample value corresponding to each sensor input sample value in a sensor data set, thereby obtaining N sample data. The sensor output sample value is a sensor output value corresponding to a sensor input value adjacent to the sensor input sample value in the sensor data set.

[0085] It can be understood that when there is a sensor input value that is identical to the sensor input sampling value in the sensor data set, the determined sensor output sampling value is the sensor output value corresponding to the sensor input sampling value that is identical to the sensor input sampling value in the sensor data set; when there is no sensor input value that is identical to the sensor input sampling value in the sensor data set, the sensor output value corresponding to the sensor input value adjacent to the sensor input sampling value in the sensor data set is used as the sensor output sampling value according to size.

[0086] It should be noted that, generally, when there is no sensor input value identical to the sensor input sample value in the sensor data set, each sensor input sample value is adjacent to two sensor input values. In one possible implementation, the sensor output value corresponding to the sensor input value that is closer to the sensor input sample value of the two sensor input values ​​is used as the sensor output sample value.

[0087] For example, when there is no sensor input value identical to the sensor input sampling value in the sensor data set, the sensor input sampling value is 180°, and the two sensor input values ​​adjacent to the sensor input sampling value are 180.1° and 179.8°, and the sensor output value corresponding to the sensor input value of 180.1° is selected as the sensor output sampling value.

[0088] It is understood that the "sampled data" described above includes a sensor input sample value and a sensor output sample value corresponding to the sensor input sample value. After the sensor data processing method described above, i.e., steps S201 to S203, N sampled data are ultimately obtained. The N sampled data constitute a set of sampled data.

[0089] In one possible implementation, to ensure that the sensor has more accurate sample data, the sensor data processing method described above, i.e., steps S201 to S203, is often repeated multiple times, performing 3-5 cycles, thereby determining 3-5 sample data. It is understood that by calculating the average value of the 3-5 sample data, the determined sample data has a higher accuracy.

[0090] In an embodiment of the present application, a sensor data processing device acquires a sensor data set and determines N sensor input sample values. Simultaneously, the sensor data processing device determines, based on each sensor input sample value, a sensor output sample value corresponding to each sensor input sample value within the sensor data set, thereby obtaining N sample data. This process does not involve complex manual operations, resulting in a high degree of accuracy in the final determination of the N sample data sets, and a high efficiency in determining the N sample data sets.

[0091] In practical applications, since it is necessary to distinguish between forward and reverse travel when analyzing sensor performance, it is necessary to obtain both forward and reverse travel sensor data. In embodiments of the present application, to obtain both forward and reverse travel sensor data, after acquiring a sensor data set, the sensor data set can be split into forward and reverse travel sensor data according to relevant rules. This is described in detail below with reference to the accompanying drawings and specific embodiments.

[0092] For example, using the angle sensor to collect steering wheel angle information, the forward stroke refers to the process of controlling the steering wheel to the left or right from its original position, while the reverse stroke refers to the process of controlling the steering wheel to return to its original position. The original position refers to the position of the steering wheel when the vehicle is traveling in a straight line.

[0093] Referring to Figure 4, which is a flow chart of another sensor data processing method provided in an embodiment of the present application, as shown in Figure 4, based on Figure 2, the following steps are also included.

[0094] Step S401: Determine the forward travel sensor data and the reverse travel sensor data in the sensor data set.

[0095] In an embodiment of the present application, after acquiring the sensor data set, the forward travel sensor data and the reverse travel sensor data in the sensor data set are determined. Specifically, after acquiring the sensor data set, the forward travel sensor data and the reverse travel sensor data in the sensor data set are determined based on a changing trend of sensor output values ​​in the sensor data set.

[0096] In one possible implementation, sensor data in a sensor data set whose sensor output values ​​are in an increasing range are determined as positive stroke sensor data; and sensor data in a sensor data set whose sensor output values ​​are in a decreasing range are determined as negative stroke sensor data. Specifically, in an embodiment of the present application, after a sensor output value is acquired, the acquired sensor output value is compared with the last acquired sensor output value. When the acquired sensor output value is greater than the last acquired sensor output value, the acquired sensor output value and the sensor input value corresponding to the sensor output value are positive stroke sensor data; when the acquired sensor output value is less than the last acquired sensor output value, the acquired sensor output value and the sensor input value corresponding to the sensor output value are negative stroke sensor data.

[0097] It is understood that, generally, the waveform of the sensor output value over time is similar to a sine wave. When a trough value of the sensor output value is identified, it indicates the start of the forward stroke; when a peak value of the sensor output value is identified, it indicates the start of the reverse stroke. For example, the peak value of the sensor output value is A, and the trough value of the sensor output value is B. When the sensor output value is identified as A and the next sensor output value determined is less than A, the reverse stroke is determined to have begun, and the sensor output value determined at this time and the sensor input value corresponding to the sensor output value are the reverse stroke sensor data. When the sensor output value is identified as B and the next sensor output value determined is greater than B, the forward stroke is determined to have begun, and the sensor output value determined at this time and the sensor input value corresponding to the sensor output value are the forward stroke sensor data.

[0098] It is understood that the peak and trough values ​​described above correspond to the maximum and minimum values ​​of the sensor's full-scale output value, respectively. It should be noted that since the waveform of the sensor's output value over time is actually a digital signal, trough and peak values ​​may not exist during the conversion process between forward and reverse strokes. Therefore, a first preset value close to the sensor's full-scale maximum output value can be set, and a second preset value close to the sensor's full-scale minimum output value can be set. For example, when the sensor output's peak value is 6° and the sensor output's trough value is -6°, the first preset value can be set to 5.8° and the second preset value can be set to -5.8°.

[0099] Specifically, when it is identified that the sensor output value is a first preset value, or is greater than the first preset value, it is determined whether the next sensor output value is less than the sensor output value at this time. When the next sensor output value is less than the sensor output value at this time, it is determined that the reverse stroke starts at this time, and the sensor output value determined at this time and the sensor input value corresponding to the sensor output value are reverse stroke sensor data; when it is identified that the sensor output value is a second preset value, or is less than the second preset value, it is determined whether the next sensor output value is greater than the sensor output value at this time. When the next sensor output value is greater than the sensor output value at this time, it is determined that the positive stroke starts at this time, and the sensor output value determined at this time and the sensor input value corresponding to the sensor output value are positive stroke sensor data.

[0100] Of course, in one possible implementation, sensor data in the sensor data set whose sensor output values ​​are in a decreasing range are determined as positive stroke sensor data; and sensor data in the sensor data set whose sensor output values ​​are in an increasing range are determined as negative stroke sensor data. Specifically, in an embodiment of the present application, after obtaining a sensor output value, the obtained sensor output value is compared with the last obtained sensor output value. When the obtained sensor output value is greater than the last obtained sensor output value, the sensor output value obtained at this moment and the sensor input value corresponding to the sensor output value are negative stroke sensor data; when the obtained sensor output value is less than the last obtained sensor output value, the sensor output value obtained at this moment and the sensor input value corresponding to the sensor output value are positive stroke sensor data.

[0101] It is understood that, under normal circumstances, the waveform of the sensor output value over time is similar to a sine wave. When a trough value of the sensor output value is identified, it indicates the start of the reverse stroke; when a peak value of the sensor output value is identified, it indicates the start of the forward stroke. For example, the peak value of the sensor output value is A, and the trough value of the sensor output value is B. When the sensor output value is identified as A and the next sensor output value determined is less than A, the forward stroke is determined to have begun, and the sensor output value determined at this time and the sensor input value corresponding to the sensor output value are the forward stroke sensor data. When the sensor output value is identified as B and the next sensor output value determined is greater than B, the reverse stroke is determined to have begun, and the sensor output value determined at this time and the sensor input value corresponding to the sensor output value are the reverse stroke sensor data.

[0102] It is understood that the peak and trough values ​​described above correspond to the maximum and minimum values ​​of the sensor's full-scale output value, respectively. It should be noted that since the waveform of the sensor's output value over time is actually a digital signal, trough and peak values ​​may not exist during the conversion process between forward and reverse strokes. Therefore, a first preset value close to the sensor's full-scale maximum output value can be set, and a second preset value close to the sensor's full-scale minimum output value can be set. For example, when the sensor output's peak value is 6° and the sensor output's trough value is -6°, the first preset value can be set to 5.8° and the second preset value can be set to -5.8°.

[0103] Specifically, when it is identified that the sensor output value is a first preset value, or is greater than the first preset value, it is determined whether the next sensor output value is less than the sensor output value at this time. When the next sensor output value is less than the sensor output value at this time, it is determined that the positive stroke starts at this time, and the sensor output value determined at this time and the sensor input value corresponding to the sensor output value are positive stroke sensor data; when it is identified that the sensor output value is a second preset value, or is less than the second preset value, it is determined whether the next sensor output value is greater than the sensor output value at this time. When the next sensor output value is greater than the sensor output value at this time, it is determined that the reverse stroke starts at this time, and the sensor output value determined at this time and the sensor input value corresponding to the sensor output value are reverse stroke sensor data.

[0104] As shown in FIG4 , based on FIG2 , step S203 specifically includes the following steps.

[0105] Step S2031: According to each sensor input sampling value, determine the positive stroke sensor output sampling value and the negative stroke sensor output sampling value corresponding to each sensor input sampling value in the sensor data set, and obtain N positive stroke sampling data and N negative stroke sampling data.

[0106] In this embodiment of the present application, the sensor data processing device determines, based on each sensor input sample value, the forward travel sensor output sample value and the reverse travel sensor output sample value corresponding to each sensor input sample value in the sensor data set, thereby obtaining N forward travel sample data and N reverse travel sample data. The forward travel sensor output sample value is the forward travel sensor output value corresponding to the forward travel sensor input value adjacent to the sensor input sample value in the sensor data set; the reverse travel sensor output sample value is the reverse travel sensor output value corresponding to the reverse travel sensor input value adjacent to the sensor input sample value in the sensor data set. The specific process is described in step S203 of the method above; for the sake of brevity, this application will not elaborate on this process.

[0107] Corresponding to the above embodiments, the present application also provides a sensor data processing device.

[0108] Referring to Figure 5 , a schematic diagram of the structure of a sensor data processing device provided in an embodiment of the present application is shown. As shown in Figure 5 , a sensor data set acquisition module 501, a sensor input sample value determination module 503, and a sample data acquisition module 502 are shown. Sample data acquisition module 502 is electrically connected to sensor data set acquisition module 501; sample data acquisition module 502 is also electrically connected to sensor input sample value determination module 503.

[0109] In an embodiment of the present application, a sensor data set acquisition module is used to acquire a sensor data set, wherein the sensor data set includes M sensor data, each of which includes a sensor input value and a sensor output value; a sensor input sampling value determination module is used to determine N sensor input sampling values, wherein M>N>1; and a sampling data acquisition module is used to determine, based on each sensor input sampling value, a sensor output sampling value corresponding to each sensor input sampling value in the sensor data set, thereby obtaining N sampling data, wherein the sensor output sampling value is a sensor output value corresponding to a sensor input value adjacent to the sensor input sampling value in the sensor data set. The specific contents of the embodiments of the present application can be found in the description of the above-mentioned method embodiments, and for the sake of brevity, this will not be repeated here.

[0110] Referring to Figure 6 , a schematic diagram of the structure of another sensor data processing device provided in an embodiment of the present application is shown. As shown in Figure 6 , the sensor data processing device, based on the sensor data processing device shown in Figure 5 , further includes a forward and reverse sensor data determination module 604. Forward and reverse sensor data determination module 604 is electrically connected to sensor data set acquisition module 501; forward and reverse sensor data determination module 604 is also electrically connected to sampled data acquisition module 502.

[0111] In an embodiment of the present application, the forward and reverse travel sensor data determining module is used to determine the forward and reverse travel sensor data in the sensor data set. Specifically, the forward and reverse travel sensor data determining module is used to determine the forward and reverse travel sensor data in the sensor data set based on a changing trend of sensor output values ​​in the sensor data set.

[0112] In one possible implementation, the forward stroke sensor data and reverse stroke sensor data determination module is used to determine the sensor data in the sensor data set whose sensor output values ​​are in an increasing range as forward stroke sensor data; and to determine the sensor data in the sensor data set whose sensor output values ​​are in a decreasing range as reverse stroke sensor data.

[0113] In one possible implementation, the forward stroke sensor data and reverse stroke sensor data determination module is used to determine the sensor data in the sensor data set whose sensor output values ​​are in an increasing range as reverse stroke sensor data; and to determine the sensor data in the sensor data set whose sensor output values ​​are in a decreasing range as forward stroke sensor data.

[0114] In an embodiment of the present application, the sampling data acquisition module is further configured to determine, based on each sensor input sampling value, a forward travel sensor output sampling value and a reverse travel sensor output sampling value corresponding to each sensor input sampling value in the sensor data set, thereby obtaining N forward travel sampling data and N reverse travel sampling data; wherein the forward travel sensor output sampling value is the forward travel sensor output value corresponding to the forward travel sensor input value adjacent to the sensor input sampling value in the sensor data set; and the reverse travel sensor output sampling value is the reverse travel sensor output value corresponding to the reverse travel sensor input value adjacent to the sensor input sampling value in the sensor data set. The specific contents of the embodiments of the present application can be found in the description of the above-mentioned method embodiments, and for the sake of brevity, they will not be further elaborated.

[0115] Corresponding to the above embodiments, the present application also provides an electronic device.

[0116] Referring to FIG7 , a schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown. The electronic device 700 may include: a processor 701, a memory 702, and a communication unit 703. These components communicate via one or more buses. Those skilled in the art will appreciate that the structure of the electronic device shown in the figure does not limit the embodiments of the present invention. It may be a bus structure or a star structure, and may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0117] The communication unit 703 is configured to establish a communication channel so that the electronic device can communicate with other devices, receive user data sent by other devices, or send user data to other devices.

[0118] The processor 701 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. It runs or executes software programs, instructions, and / or modules stored in the memory 702, and calls data stored in the memory to perform various functions of the electronic device and / or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of multiple packaged ICs with the same or different functions. For example, the processor 701 can only include a central processing unit (CPU). In an embodiment of the present invention, the CPU can be a single computing core or multiple computing cores.

[0119] The memory 702 is used to store execution instructions of the processor 701. The memory 702 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0120] When the execution instructions in the memory 702 are executed by the processor 701 , the electronic device 700 is enabled to execute part or all of the steps in the embodiment shown in FIG. 1 .

[0121] In a specific implementation, the present application further provides a computer storage medium, wherein the computer storage medium may store a program, and when the program is executed, the program may include some or all of the steps of each embodiment of the simulation scene generation method provided by the present invention. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0122] In the embodiments of the present application, "at least one" refers to one or more, and "more" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0123] Those skilled in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented using a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0124] Those skilled in the art will 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.

[0125] In the several embodiments provided in this application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of this application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program code.

[0126] In this specification, reference can be made to the same or similar parts between the various embodiments. In particular, for the device embodiment and the terminal embodiment, since they are basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.

Claims

1. A sensor data processing method, characterized in that: include: Acquire a sensor data set, the sensor data set including M sensor data, each of the sensor data including a sensor input value and a sensor output value; Determine N sensor input sampling values, where M>N>1; According to each of the sensor input sampling values, determining a sensor output sampling value corresponding to each of the sensor input sampling values in the sensor data set to obtain N sampling data; The sensor output sampling value is a sensor output value corresponding to a sensor input value adjacent to the sensor input sampling value in the sensor data set.

2. The sensor data processing method according to claim 1, wherein: After acquiring the sensor data set, the method further includes: Positive travel sensor data and negative travel sensor data in the sensor data set are determined.

3. The sensor data processing method according to claim 2, wherein: The determining of the forward travel sensor data and the reverse travel sensor data in the sensor data set includes: According to a change trend of the sensor output value in the sensor data set, the forward stroke sensor data and the reverse stroke sensor data in the sensor data set are determined.

4. The sensor data processing method according to claim 3, wherein: The determining, based on a change trend of a sensor output value in the sensor data set, the forward travel sensor data and the reverse travel sensor data in the sensor data set comprises: Determining sensor data in the sensor data set whose sensor output values are in an increasing interval as positive stroke sensor data; The sensor data in the sensor data set whose sensor output value is in a decreasing interval is determined as the reverse stroke sensor data.

5. The sensor data processing method according to claim 3, wherein: The determining, based on a change trend of a sensor output value in the sensor data set, the forward travel sensor data and the reverse travel sensor data in the sensor data set comprises: Determining sensor data in the sensor data set whose sensor output values are in an increasing interval as reverse stroke sensor data; The sensor data in the sensor data set whose sensor output value is in a decreasing interval is determined as positive stroke sensor data.

6. The sensor data processing method according to any one of claims 2 to 5, characterized in that: The step of determining, in a sensor data set according to each of the sensor input sampling values, a sensor output sampling value corresponding to each of the sensor input sampling values to obtain N sampling data includes: According to each of the sensor input sampling values, determining a forward stroke sensor output sampling value and a reverse stroke sensor output sampling value corresponding to each of the sensor input sampling values in the sensor data set, to obtain N forward stroke sampling data and N reverse stroke sampling data; Among them, the positive stroke sensor output sampling value is the positive stroke sensor output value corresponding to the positive stroke sensor input value adjacent to the sensor input sampling value in the sensor data set; the reverse stroke sensor output sampling value is the reverse stroke sensor output value corresponding to the reverse stroke sensor input value adjacent to the sensor input sampling value in the sensor data set.

7. The sensor data processing method according to claim 1, wherein: The minimum value and the maximum value of the N sensor input sampling values are the minimum value and the maximum value of the sensor range respectively.

8. The sensor data processing method according to claim 7, characterized in that: The difference between any two adjacent sensor input sampling values among the N sensor input sampling values is equal.

9. A sensor data processing device, characterized in that: include: A sensor data set acquisition module, configured to acquire a sensor data set, wherein the sensor data set includes M sensor data, each of which includes a sensor input value and a sensor output value; A sensor input sampling value determination module, configured to determine N sensor input sampling values, where M>N>1; a sampling data acquisition module, configured to determine, in a sensor data set, a sensor output sampling value corresponding to each sensor input sampling value, and obtain N sampling data; The sensor output sampling value is a sensor output value corresponding to a sensor input value adjacent to the sensor input sampling value in the sensor data set.

10. An electronic device, characterized in that: include: processor; Memory; and a computer program, wherein the computer program is stored in the memory, and the computer program includes instructions, which, when executed by the processor, cause the electronic device to perform the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 8.

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