Method and apparatus for estimating number of revolutions of bearing on object

Abstract

The present disclosure provides a method and apparatus for estimating the number of revolutions of a bearing on an object, the method comprising: receiving a plurality of measurement data from a sensor, each of the plurality of measurement data having a corresponding timestamp, the plurality of measurement data being awakened and measured by the sensor based on a first time interval, wherein during the operation period of the object, the first time interval is changed based on the operation state of the object; determining a total travel distance of the object based on the plurality of measurement data; determining a travel distance offset of the bearing, where the travel distance offset of the bearing is a distance that the object has traveled when the bearing is mounted on the object; and determining a number of revolutions of the bearing based on the determined total travel distance of the object and the determined travel distance offset of the bearing.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of data processing technology, and more particularly, to a method and device for estimating the number of bearing revolutions on an object. Background Art

[0002] In order to fully describe the usage of wheel bearings of objects (e.g., trains, subways, vehicles, etc.) or to achieve reliable remote diagnosis of bearings, recording the number of revolutions of the bearing (i.e., the cumulative number of revolutions since the bearing was installed) is a very critical input. In order to measure this cumulative metric, continuous monitoring is usually required. However, energy-constrained (e.g., battery-powered) IoT sensors (e.g., vibration and temperature sensors) usually wake up only a few times a day and perform measurements to save energy consumption. This means that it is difficult for such energy-constrained sensors to stay on and record the number of revolutions all the time. Therefore, there is a need for an effective method that can use energy-constrained sensors to infer or estimate the number of bearing revolutions on an object. Summary of the invention

[0003] This summary is provided to introduce concepts in a brief form that will be described in detail in the detailed description below. This summary is not intended to identify key features or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0004] An embodiment of the present disclosure provides a method for estimating the number of bearing revolutions on an object, comprising: receiving a plurality of measurement data from a sensor, wherein each of the plurality of measurement data has a corresponding timestamp, wherein the plurality of measurement data is awakened and measured by the sensor based on a first time interval, wherein during the operation of the object, the first time interval changes based on the operating state of the object; determining a total travel distance of the object based on the plurality of measurement data; determining a travel distance offset of the bearing, wherein the travel distance offset of the bearing is a distance that the object has traveled when the bearing is mounted on the object; and determining the number of revolutions of the bearing based on the determined total travel distance of the object and the determined travel distance offset of the bearing.

[0005] According to an embodiment of the present disclosure, the first time interval changes based on the operating state of the object, including: when the operating state of the object is a first state, reducing the first time interval according to a first change factor; and when the operating state of the object is a second state, increasing the first time interval according to a second change factor whose change rate is less than the first change factor.

[0006] According to an embodiment of the present disclosure, the first change factor is a multiplication factor, and the second change factor is an addition factor.

[0007] According to an embodiment of the present disclosure, the running state of the object includes one or more of the following: a fast running state, a slow running state, and a stopped state, wherein the first state is a fast running state, and the second state is a slow running state or a stopped state.

[0008] According to an embodiment of the present disclosure, each of the multiple measurement data includes position information of the object, and the position information is used to indicate the position of the object when the measurement data is measured, wherein, based on the multiple measurement data, determining the total travel distance of the object includes: determining a first incremental travel distance of the object based on the position information of the object and a corresponding timestamp; and adding the first incremental travel distance to a previous travel distance of the object to determine the total travel distance.

[0009] According to an embodiment of the present disclosure, the sensor includes a positioning module, wherein the position information of the object is acquired via the positioning module.

[0010] According to an embodiment of the present disclosure, each of the multiple measurement data includes running status information of the object, and the running status information is used to indicate the running status of the object when measuring the measurement data, wherein, based on the multiple measurement data, determining the total travel distance of the object includes: determining the running time of the object based on the running status information of the object and the corresponding timestamp; determining a second incremental travel distance of the object based on the running time and the running speed corresponding to the running time; and adding the second incremental travel distance to the previous travel distance of the object to determine the total travel distance.

[0011] According to an embodiment of the present disclosure, the sensor includes a speed acquisition module, and the running state information of the object is acquired via the speed acquisition module.

[0012] According to an embodiment of the present disclosure, the number of revolutions of the bearing is determined based on the determined total travel distance of the object and the determined travel distance offset of the bearing, including: subtracting the travel distance offset from the total travel distance to obtain a first travel distance of the bearing; and dividing the first travel distance by a second travel distance associated with the bearing to obtain the number of revolutions, wherein the second travel distance is the distance traveled by the object when the bearing rotates one circle.

[0013] An embodiment of the present disclosure provides a device for estimating the number of bearing revolutions on an object, the device comprising: a transceiver, configured to: receive a plurality of measurement data from a sensor, wherein each of the plurality of measurement data has a corresponding timestamp, wherein the plurality of measurement data is awakened and measured by the sensor based on a first time interval, wherein during the operation of the object, the first time interval changes based on the operating state of the object; and a processor, coupled to the transceiver and configured to: determine a total travel distance of the object based on the plurality of measurement data; determine a travel distance offset of the bearing, wherein the travel distance offset of the bearing is a distance that the object has traveled when the bearing is mounted on the object; and determine the number of revolutions of the bearing based on the determined total travel distance of the object and the determined travel distance offset of the bearing.

[0014] An embodiment of the present disclosure provides a device for estimating the number of bearing revolutions on an object, the device comprising: a communication module configured to receive a plurality of measurement data from a sensor, wherein each of the plurality of measurement data has a corresponding timestamp, wherein the plurality of measurement data is awakened and measured by the sensor based on a first time interval, wherein during the operation of the object, the first time interval changes based on the operating state of the object; a first determination module configured to determine the total travel distance of the object based on the plurality of measurement data; a second determination module configured to determine the travel distance offset of the bearing, wherein the travel distance offset of the bearing is the distance that the object has traveled when the bearing is mounted on the object; and a third determination module configured to determine the number of revolutions of the bearing based on the determined total travel distance of the object and the determined travel distance offset of the bearing.

[0015] An embodiment of the present disclosure provides a computer-readable storage medium having instructions stored thereon, which, when executed, cause a processor to perform any method for estimating the number of bearing revolutions on an object and / or any method for changing the wake-up time interval of a sensor based on the motion state of the object according to an embodiment of the present disclosure.

[0016] The method, device and apparatus provided by the present disclosure have at least one or more of the following advantages: 1) By making full use of one or several energy-constrained sensors (rather than relying on any wired-powered always-on devices), the number of revolutions of the wheel bearing can be estimated. 2) By using the method provided by the present disclosure, the trajectory of objects equipped with these one or several sensors can also be potentially depicted. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0018] Figure 1 A schematic diagram showing a method of determining a travel distance of an object based on position information received from a sensor according to an embodiment of the present disclosure;

[0019] Figure 2 A schematic diagram showing how to correct distance using a GIS method according to an embodiment of the present disclosure is shown;

[0020] Figure 3 A schematic diagram showing a method of determining a travel distance of an object based on operating status information received from a sensor according to an embodiment of the present disclosure;

[0021] Figure 4 An example process of a method for estimating the number of bearing revolutions on an object executed on a computing device according to an embodiment of the present disclosure is shown;

[0022] Figure 5 A schematic diagram of a scenario in which a wake-up time interval of a sensor is changed based on a motion state of an object according to an embodiment of the present disclosure is shown;

[0023] Figure 6 An example process of changing the wake-up time interval of a sensor based on the motion state of an object according to an embodiment of the present disclosure is shown;

[0024] Figure 7 A schematic diagram showing a method of performing measurement using multiple sensors according to an embodiment of the present disclosure is shown;

[0025] Figure 8 A schematic diagram showing a method for estimating the number of bearing revolutions on an object according to an embodiment of the present disclosure;

[0026] Fig. 9 A schematic diagram showing a device for estimating the number of bearing revolutions on an object according to an embodiment of the present disclosure; and

[0027] Fig.10 A schematic diagram of a device for estimating the number of bearing rotations on an object according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0028] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain 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 construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0029] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0030] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0031] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0032] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0033] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0034] In the present disclosure, an object may refer to any object that travels by wheels and is equipped with wheel bearings, such as a train, a subway, a vehicle (car, truck, etc.), a bicycle, etc.

[0035] In the present disclosure, an energy-constrained sensor may refer to a sensor that wakes up and performs measurements only once or a small number of times within a certain period of time to save energy consumption, for example, a battery-powered sensor.

[0036] In order to achieve reliable remote diagnosis of bearings through sensors (e.g., vibration and temperature sensors), one of the most commonly used inputs is to provide the cumulative number of revolutions since the bearing was installed. In order to measure this cumulative metric, continuous monitoring is usually required, which is a huge challenge for energy-constrained (e.g., battery-powered) Internet of Things (IoT) sensors to keep always on.

[0037] The present disclosure provides a method for inferring the number of revolutions of a wheel bearing by using one or (a small number of) several energy-constrained sensors installed in an object. The method can be implemented using a computing device and one or several energy-constrained sensors. The sensor wakes up to measure the measurement data of the object (e.g., position or operating status, etc.) and records the corresponding timestamp, and uploads the measurement data to a computing device (e.g., a server, a cloud server, or a gateway, etc.). The next wake-up time (or wake-up time interval) of the sensor can be determined by a scheduling mechanism based on the operating status of the object (e.g., speed, acceleration, or other equivalent measurements). The computing device can then infer the distance traveled by the object equipped with the sensor. Based on this, the number of revolutions of the wheel bearing can be further estimated or inferred. In the presence of several sensors, these sensors can be scheduled in turn (e.g., wake up in turn or wake up in time periods, etc.) to further save energy consumption.

[0038] In some embodiments, a sensor installed in an object (e.g., a train or subway, etc.) can provide the location information of the object (e.g., it can also include a moving direction, speed, etc.) and / or sense the running state of the object (e.g., fast running, slow running or stopped, etc.). Generally, the location information of the object can be obtained via a positioning module (e.g., a global positioning system (GPS) / global navigation satellite system (GNSS) module, etc.), and the running state of the object can be sensed via a speed acquisition module. In some embodiments, the speed acquisition module can be an accelerometer module, a gyroscope, and any other module that can be applied to the speed sensing of the object in the present or future. In some embodiments, the speed acquisition module can also be a receiving module that can receive external information input (e.g., the speed information of the object, etc.) from the outside or other modules. To simplify the description, the accelerometer module is used as an example for description below.

[0039] In some embodiments, the position information and / or operating status of the object can be obtained by one or more sensors (e.g., temperature sensors or vibration sensors) currently equipped on the object. For example, the position information and / or operating status of the object can be obtained by using an existing (or associated) positioning module and / or accelerometer module in one or more sensors currently equipped on the object, or the position information and / or operating status of the object can be obtained by integrating a positioning module and / or accelerometer module in one or more sensors currently equipped on the object. In addition, the position information and / or operating status of the object can also be obtained by one or more special sensors including a positioning module and / or an accelerometer module. In some cases, these sensors may be energy-constrained sensors.

[0040] In the following, a scenario of a sensor is used as an example for exemplary description. For example, in order to save energy, the sensor can be woken up periodically or at a specific time interval Δt to measure the measurement data of the object (e.g., position or operating status, etc.) and record the corresponding timestamp, and upload the measurement data to a computing device (e.g., a server, a cloud server, or a gateway, etc.). In some embodiments, the measurement data can be uploaded at a preconfigured time point. In some embodiments, the measurement data can be uploaded based on a request or trigger of a computing device. In some embodiments, the measurement data can be uploaded together with other data (e.g., temperature data, vibration data, etc.).

[0041] Figure 1 FIG. 1 is a schematic diagram showing a method of determining the travel distance of an object based on the position information received from a sensor according to an embodiment of the present disclosure. For application scenarios where position information is easily available (e.g., train application scenarios), as shown in FIG. Figure 1 As shown, the position information recorded by the sensor (e.g., the object position recorded at time T1, T2, T3, T4, etc.) can be mapped in a computing device (e.g., a cloud server, etc.). The distance between two position sample points (e.g., the distance between the position sample points at T1 and T2) can be obtained by To simply estimate, where X and Y (i.e., X1, Y1, X2, Y2) represent the position coordinates (e.g., latitude and longitude) of the object. In order to simplify the problem, the more specific conversion process between the longitude and latitude position coordinates and the distance is omitted here. If higher accuracy is desired, the time interval (or wake-up cycle) Δt between adjacent sampling time points (e.g., the time interval between T1 and T2) can be shortened or the distance can be corrected by utilizing a geographic information system (GIS) method. In some embodiments, the time interval Δt can be a preset constant. In some embodiments, the initial value of the time interval Δt can be a preset constant and can be changed based on the operating state of the object (e.g., further, based on the operating speed, etc.) during the operation of the object.

[0042] Figure 2 FIG. 2 shows a schematic diagram of using a GIS method to correct distance according to an embodiment of the present disclosure. Figure 2 As shown, a railway line corresponding to two adjacent position sample points can be selected on a specific map and the length distance between the two adjacent position sample points on the railway line can be calculated. The distance simply estimated based on the above formula can be expressed as And as Figure 2 The distance further corrected based on the GIS method can be expressed as D GIS (X1, Y1, X2, Y2). Furthermore, based on the distance between every two adjacent position sample points, the distance traveled by the object in any time period or between any two position sample points can be calculated by adding or other methods.

[0043] Figure 3 A schematic diagram is shown of determining a travel distance of an object based on operating status information received from a sensor according to an embodiment of the present disclosure.

[0044] For application scenarios where it is not easy to obtain location information but easy to obtain average speed (for example, subway application scenarios), Figure 3As shown, the running state of an object (e.g., a subway) can be measured or recorded. In some embodiments, the running state of an object may include one or more of the following: a fast running state, a slow running state, or a stopped state. In this way, the running time of the object can be estimated in a computing device based on the running state information of the object and the corresponding timestamp, and the distance traveled by the object can be inferred by multiplying the running time by the corresponding average speed. In some embodiments, a corresponding average speed can be estimated or configured in advance for each running state of the object. For example, a fast running state can correspond to a first speed, a slow running state can correspond to a second speed lower than the first speed, and a stopped state can correspond to a zero speed. In other embodiments, the average speed of the object in different running states can also be obtained or estimated by any other means, which is not limited herein. Figure 3 Only two operating states, the fast running state and the stopped state, are shown. In the present disclosure, it can be assumed that the operating state of the object will not change within a time interval Δt. Figure 3 In the example, it can be considered that the object is in a fast running state during the time period from T1 to T3, and is in a stopped state during the time period from T3 to T4.

[0045] In addition, the location information and / or operating status of the object recorded by the sensor can be sent or uploaded to the computing device immediately after recording, or can be Figure 1 or Figure 3 As shown in the shaded rectangle in the figure, all data are uploaded at a scheduled time. This article does not limit the specific time or method of data uploading.

[0046] Figure 4 An example flow of a method 400 for estimating the number of bearing revolutions on an object executed on a computing device according to an embodiment of the present disclosure is shown.

[0047] like Figure 4 As shown, method 400 may start at step S401 , where a computing device (eg, a server, a cloud server, etc.) may receive data including location information or operating status information of an object from a sensor.

[0048] In step S402, the received data may be sorted in time order (eg, according to the timestamps corresponding to the measurement data) to obtain sorted data D sorted .

[0049] In step S403, it can be determined whether the data includes location information or running status information. If the data includes location information (for example, in a train scenario), the method 400 can proceed to step S404. In step S404, the above Figure 1 and / or Figure 2The method described above is used to calculate the first incremental travel distance of the object. Figure 1 As shown, the computing device can calculate the distance between two adjacent position sample points sorted in time order in the manner described above, for example, the segment distance corresponding to each time interval Δt, and then accumulate the segment distances corresponding to all time intervals Δt to obtain the first incremental travel distance traveled by the object in the time period corresponding to these position information.

[0050] If the data includes running status information (for example, in a subway scenario), the method 400 may proceed to step S405. In step S405, Figure 3 The method described above is used to calculate the second incremental travel distance of the object. Figure 3 As shown, as described above, assuming that the running state of the object does not change within a time interval Δt, the running time of the object in each running state can be easily determined based on multiple running state information and corresponding timestamps. By multiplying the running time of the object in each running state with the predetermined average speed corresponding to each running state, the second incremental travel distance traveled by the object in the time period corresponding to these running state information can be determined.

[0051] Then, in step S406, the first incremental travel distance d determined in step S404 or the second incremental travel distance d determined in step S405 may be added to the total distance d that the object has previously traveled. prevous_total Add together to get the total travel distance d of the object total .

[0052] Next, in step S407, for a scenario with K (for example, K is an integer greater than or equal to 1) wheel bearings, all wheel bearings may be traversed to perform the operations of steps S408-S411.

[0053] For example, in step S408, it can be determined whether the i-th wheel bearing among the K wheel bearings is newly installed. If the bearing is newly installed, then in step S409, the total travel distance d of the object can be first calculated. total Subtract the travel distance offset d of the bearing offset Then divide it by the circumference of the wheel corresponding to the bearing Φ*pi (where Φ represents the diameter of the wheel) to determine the bearing revolution Revolution i As mentioned above, the travel distance of this bearing is offset by offsetIt can be the distance that the object has traveled when the bearing is installed on the object. If the bearing is not newly installed, for example, it has been installed before the object starts to travel, the method 400 can proceed to step S410. In step S410, the total travel distance d of the object can be directly calculated. total Divide by the circumference of the wheel corresponding to the bearing Φ*pi to determine the bearing revolution i .

[0054] In step S411, it can be determined whether all wheel bearings have been traversed based on the sequence number i of the current wheel bearing. If all wheel bearings have not been traversed, the method can return to step S407 and execute steps S408-S411 again. If all wheel bearings have been traversed, the method 400 can end in step S412.

[0055] It should be understood that Figure 4 The flowchart shown is merely an example of a method for estimating the number of bearing revolutions on an object according to an embodiment of the present disclosure. Figure 4 The steps in may be performed in any other order. Figure 4 One or more steps in the method may be omitted or combined with each other, or any other method or step according to an embodiment of the present disclosure may be added thereto.

[0056] In some embodiments, in order to improve the estimation accuracy and further save energy consumption at the same time, multiple measurement data can be obtained by waking up and measuring the sensor based on the wake-up time interval ΔT (herein, it can be referred to as the first time interval), and during the operation of the object, the wake-up time interval ΔT can be changed based on the operation state of the object (for example, further, based on the operation speed, etc.). For example, when the object runs quickly (that is, in a fast operation state), the sensor can wake up more frequently and perform measurements, for example, the wake-up time interval ΔT of the sensor can be multiplicatively (for example, by a multiplication factor). When the object runs slowly (that is, in a slow operation state) or is stationary, the sensor can wake up less frequently and perform measurements, for example, the wake-up time interval of the sensor can be additively (for example, by an addition factor).

[0057] More specifically, Figure 5 A schematic diagram of a scenario in which a wake-up time interval of a sensor is changed based on a motion state of an object according to an embodiment of the present disclosure is shown.

[0058] like Figure 5As shown, assuming that the initial state of the object (e.g., the running state at T1) is a slow running state, an initial value Δt corresponding to the slow running state can be set for the wake-up time interval ΔT of the sensor. That is, the next wake-up time of the sensor is T2, and the initial time interval between T2 and T1 is Δt.

[0059] When the object is detected to be in a fast-running state at time T2, a multiplicative reduction operation can be performed on the current time interval Δt to obtain an updated / changed wake-up time interval. For example, the current time interval Δt can be multiplied by a multiplication factor, such as 1 / 2, to obtain an updated wake-up time interval ΔT=Δt / 2. At this time, the next wake-up time T3=T2+Δt / 2, instead of T2+Δt at a fixed time interval. Similarly, if the object continues to be detected to be in a fast-running state at time T3, the next wake-up time T4=T3+Δt / 4. In some embodiments, when the object is detected to be in a fast-running state, a multiplicative reduction operation can be performed until a preset minimum wake-up time interval is reached, such as Figure 5 The wake-up time intervals Δt / 4 between T3 and T4 and between T4 and T5 are shown.

[0060] Continue back Figure 5 , when the object is detected to be in a slow running state at time T5, an additive increase operation can be performed on the current time interval Δt / 4 to obtain an updated / changed wake-up time interval. For example, the current time interval Δt / 4 can be added with an addition factor, such as t' (for example, 60 seconds, etc.), to obtain an updated wake-up time interval ΔT=Δt / 4+t'. At this time, the next wake-up time T6=T5+Δt / 4+t'. Similarly, if the object continues to be detected to be in a slow running state at time T6, the next wake-up time T7=T6+Δt / 4+2t'. In some embodiments, when the object is detected to be in a slow running state, the additive increase operation can be performed until a preset maximum wake-up time interval is reached.

[0061] It should be understood that the multiplication factor 1 / 2, the addition factor t', the minimum wake-up time interval and the maximum wake-up time interval described here are only examples, and they can have any other suitable values ​​depending on the actual situation. Figure 5Only two running states, namely, the fast running state and the slow running state, are shown in FIG. It should be understood that, in order to improve the estimation accuracy, the running state of the object may also include one or more other running states, such as a stationary state or a stopped state, a first speed running state, a second speed running state, a third speed running state, a fourth speed running state, etc., and each running state may have a corresponding addition factor or multiplication factor, and the addition factors or multiplication factors corresponding to different running states may be the same or different.

[0062] Figure 6 An example process 600 of changing a wake-up time interval of a sensor based on a motion state of an object according to an embodiment of the present disclosure is shown.

[0063] like Figure 6 As shown, the example process 600 may start at step S601. In step S601, the running state of the object may be detected, for example, a fast running state, or a slow running or stopping state. In this example, to simplify the description, the fast running state may be used as the first state, and the slow running or stopping state may be used as the second state.

[0064] In step S602, it can be determined whether the wake-up time interval IW is initialized. If it is not initialized, the process 600 can proceed to step S6036 to initialize IW, for example, IW can be initialized to a minimum wake-up time interval MIN_INTERVAL. In other embodiments, it can also be initialized to a maximum wake-up time interval MAX_INTERVAL, or any other suitable initial value IW_INITIAL, which is not limited herein. If IW has been initialized, the process 600 proceeds to step S604.

[0065] In step S604, it can be determined whether the running state of the current or most recently detected object is the first state (i.e., the fast running state) or the second state (i.e., the slow running or stopped state). If it is the first state, as described above, it is expected that the sensor can wake up more frequently, so the process 600 can proceed to step S605 to reduce the wake-up time interval. Assuming that the multiplication factor corresponding to the first state is 1 / 2, it can be first determined in step S605 whether the product IW / 2 of the current wake-up time interval IW and the multiplication factor 1 / 2 is less than the minimum wake-up time interval MIN_INTERVAL. If the product IW / 2 of the current wake-up time interval IW and the multiplication factor 1 / 2 is already less than the minimum wake-up time interval MIN_INTERVAL, that is, the minimum wake-up time interval MIN_INTERVAL has been reached, IW can be set to the minimum wake-up time interval MIN_INTERVAL in step S606. If the product IW / 2 of the current wake-up time interval IW and the multiplication factor 1 / 2 is not less than the minimum wake-up time interval MIN_INTERVAL, IW may be set to the product IW / 2 of the current wake-up time interval IW and the multiplication factor 1 / 2 in step S607.

[0066] In step S604, if it is determined that the running state of the object is the second state, it is expected that the sensor can wake up less frequently at this time, so the process 600 can proceed to step S608 to increase the wake-up time interval. Assuming that the addition factor corresponding to the second state is t', it can be first determined in step S608 whether the sum IW+t' of the current wake-up time interval IW and the addition factor t' is greater than the maximum wake-up time interval MAX_INTERVAL. If the sum IW+t' of the current wake-up time interval IW and the addition factor t' is already greater than the maximum wake-up time interval MAX_INTERVAL, that is, the maximum wake-up time interval MAX_INTERVAL has been reached, IW can be set to the maximum wake-up time interval MAX_INTERVAL in step S610. If the sum IW+t' of the current wake-up time interval IW and the addition factor t' is not greater than the maximum wake-up time interval MAX_INTERVAL, IW can be set to the sum IW+t' of the current wake-up time interval IW and the addition factor t' in step S609.

[0067] The updated or changed current wake-up time interval IW may be determined through step S606 , S607 , S609 or S610 , and then the process 600 may end at step S611 .

[0068] In some embodiments, the example process or method described herein for changing the wake-up time interval of a sensor based on the motion state of an object may be executed at a computing device or on a sensor, for example, by a scheduler running on the sensor. Figure 6 The flowchart shown is only an example of a method for changing the wake-up time interval of a sensor based on the motion state of an object according to an embodiment of the present disclosure. Figure 6 The steps in may be performed in any other order. Figure 6 One or more steps in the method may be omitted or combined with each other, or any other method or step according to an embodiment of the present disclosure may be added thereto.

[0069] When multiple sensors are installed on an object and can be used to perform the method for estimating the number of bearing rotations on the object and / or the method for changing the wake-up time interval of the sensor based on the motion state of the object according to an embodiment of the present disclosure, these multiple sensors can further save energy by working in a time-sharing manner.

[0070] Figure 7 FIG. 1 is a schematic diagram showing a method of using multiple sensors to perform measurements according to an embodiment of the present disclosure. Figure 7 FIG. 2 shows two sensors, namely sensor #1 and sensor #2. Sensor #1 and sensor #2 do not need to be awakened at the same time to measure information such as the position and / or operating status of an object, but can work in time division. For example, sensor #1 can be awakened from T1 to T2. N During the time period, the sensor #2 is awakened and measured according to the method described above. At this time, the sensor #2 does not need to work. The sensor #2 can be N After T N+1 To T N+N During the time period, the sensor #1 is awakened and measured according to the method described above, and at this time, the sensor #1 does not need to work. Afterwards, the two sensors can work alternately according to the set working time period in this way, thereby further saving energy consumption.

[0071] Next, Figure 8 A schematic diagram of a method 800 for estimating the number of bearing revolutions on an object according to an embodiment of the present disclosure is shown.

[0072] like Figure 8As shown, the method 800 for estimating the number of bearing revolutions on an object according to an embodiment of the present disclosure may include: in step S801, receiving a plurality of measurement data from a sensor; in step S802, determining the total travel distance of the object based on the plurality of measurement data; in step S803, determining the travel distance offset of the bearing, wherein the travel distance offset of the bearing is the distance that the object has traveled when the bearing is mounted on the object; and in step S804, determining the number of bearing revolutions based on the determined total travel distance of the object and the determined travel distance offset of the bearing. In some embodiments, each of the plurality of measurement data may have a corresponding timestamp. In some embodiments, as described above, the plurality of measurement data may be awakened and measured by the sensor based on a first time interval, and during the operation of the object, the first time interval may change based on the operating state of the object (e.g., further, based on the operating speed of the object, etc.).

[0073] In some embodiments, when the running state of the object is the first state, the first time interval can be reduced according to the first change factor. When the running state of the object is the second state, the first time interval can be increased according to the second change factor whose change rate is less than the first change factor. For example, in some embodiments, as described above, the first change factor can be a multiplication factor, and the second change factor can be an addition factor. Usually, the change rate of the addition factor is less than the change rate of the multiplication factor. In some embodiments, the first change factor can also be an addition factor with a larger absolute value, such as -60s, and the second change factor can be an addition factor with a smaller absolute value, such as 30s, so that the faster speed reduction and slower speed increase of the first time interval can still be achieved. Similarly, the first change factor and the second change factor can also be implemented by multiplication factors with different values, for example, the first change factor can be a multiplication factor of 1 / 10, and the second change factor can be a multiplication factor of 5.

[0074] In some embodiments, the running state of the object may include one or more of the following: a fast running state, a slow running state, and a stopped state.

[0075] In some embodiments, the fast running state may be used as the first state, and the slow running state and / or the stop state may be used as the second state.

[0076] In some embodiments, each of the plurality of measurement data may include position information of the object, which may be used to indicate the position of the object when the measurement data is measured. In some embodiments, determining the total travel distance of the object based on the plurality of measurement data in step S802 may further include: determining a first incremental travel distance of the object based on the position information of the object and a corresponding timestamp; and adding the first incremental travel distance to a previous travel distance of the object to determine the total travel distance of the object.

[0077] For example, Figure 1 As shown, the computing device may receive multiple measurement data including the location information of the object from the sensor, and sort the multiple location information according to the corresponding timestamps. The computing device may calculate the distance between two adjacent location samples sorted in time order in the manner described above, for example, the segment distance corresponding to each time interval Δt, and then accumulate the segment distances corresponding to all time intervals Δt to obtain the first incremental travel distance traveled by the object in the time period corresponding to these location information. Then, by adding the first incremental travel distance to the total distance that the object has previously traveled, the total travel distance of the object can be obtained.

[0078] In some embodiments, each of the plurality of measurement data may include running status information of the object, which can be used to indicate the running status of the object when the measurement data is measured. In some embodiments, determining the total travel distance of the object based on the plurality of measurement data in step S802 may further include: determining the running time of the object based on the running status information of the object and the corresponding timestamp; determining a second incremental travel distance of the object based on the running time and the running speed corresponding to the running time; and adding the second incremental travel distance to the previous travel distance of the object to determine the total travel distance of the object.

[0079] For example, Figure 3 As shown, the computing device can receive multiple measurement data including the running state information of the object from the sensor, and sort the multiple running state information according to the corresponding timestamps. As described above, it is assumed that the running state of the object will not change within a time interval Δt. Therefore, the running time of the object in each running state can be easily determined based on the multiple running state information and the corresponding timestamps. By multiplying the running time of the object in each running state with the average speed corresponding to each predetermined running state, the second incremental travel distance traveled by the object in the time period corresponding to these running state information can be determined. Then, by adding the second incremental travel distance to the total distance that the object has previously traveled, the total travel distance of the object can be obtained.

[0080] In some embodiments, determining the number of revolutions of the bearing based on the determined total travel distance of the object and the determined travel distance offset of the bearing in step S804 may further include: subtracting the travel distance offset of the bearing from the total travel distance of the object to obtain a first travel distance of the bearing; and dividing the first travel distance by a second travel distance associated with the bearing to obtain the number of revolutions, wherein the second travel distance may be a distance traveled by the object when the bearing rotates one circle. For example, the second travel distance may be the circumference of the wheel corresponding to the bearing. In addition, as described above, the travel distance offset of the bearing may be a distance that the object has traveled when the bearing is mounted on the object.

[0081] Fig. 9 A schematic diagram of a device 900 for estimating the number of bearing revolutions on an object according to an embodiment of the present disclosure is shown.

[0082] Device 900 may be any computing device capable of performing data processing, such as a local server, a cloud server, or a data processing center. Fig. 9 As shown, the device 900 may include a transceiver 910 and a processor 920. The transceiver 910 may be configured to: receive a plurality of measurement data from a sensor. In some embodiments, each of the plurality of measurement data may have a corresponding timestamp. In some embodiments, as described above, the plurality of measurement data may be awakened and measured by the sensor based on a first time interval, and during the operation of the object, the first time interval may be changed based on the operating state of the object (e.g., further, based on the operating speed of the object, etc.). The processor 920 may be communicatively coupled to the transceiver 910 and may be configured to: determine the total travel distance of the object based on the plurality of measurement data; determine the travel distance offset of the bearing, wherein the travel distance offset of the bearing is the distance that the object has traveled when the bearing is mounted on the object; and determine the number of revolutions of the bearing based on the determined total travel distance of the object and the determined travel distance offset of the bearing.

[0083] In addition, the device 900 may also execute any other methods or steps described above according to the embodiments of the present disclosure, which will not be described in detail here.

[0084] Fig.10 A schematic diagram of a device 1000 for estimating the number of bearing revolutions on an object according to an embodiment of the present disclosure is shown.

[0085] like Fig.10As shown, the device 1000 may include a communication module 1001, a first determination module 1002, a second determination module 1003, and a third determination module 1004. The communication module 1001 may be configured to receive a plurality of measurement data from a sensor. In some embodiments, each of the plurality of measurement data may have a corresponding timestamp. In some embodiments, as described above, a plurality of measurement data may be awakened and measured by a sensor based on a first time interval, and during the operation of the object, the first time interval may be changed based on the operating state of the object (e.g., further, based on the operating speed of the object, etc.). The first determination module 1002 may be configured to determine the total travel distance of the object based on the plurality of measurement data. The second determination module 1003 may be configured to determine the travel distance offset of the bearing, wherein the travel distance offset of the bearing is the distance that the object has traveled when the bearing is mounted on the object. The third determination module 1004 may be configured to determine the number of revolutions of the bearing based on the determined total travel distance of the object and the determined travel distance offset of the bearing.

[0086] In addition, the device 1000 may also include other modules for executing any other methods or steps according to the embodiments of the present disclosure as described above, which will not be repeated here.

[0087] In particular, according to an embodiment of the present disclosure, the method or process described above in conjunction with the embodiment of the present disclosure or the accompanying drawings can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device, or installed from a ROM. When the computer program is executed by a processing device, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0088] In addition, an embodiment of the present disclosure provides a computer-readable storage medium having instructions stored thereon, which, when executed, cause a processor to perform any method for estimating the number of bearing revolutions on an object and / or any method for changing the wake-up time interval of a sensor based on the motion state of the object according to an embodiment of the present disclosure.

[0089] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0090] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, limit the unit itself.

[0091] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0092] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0093] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

[0094] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0095] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A method for estimating the number of bearing revolutions on an object, comprising: Receiving a plurality of measurement data from a sensor, wherein each of the plurality of measurement data has a corresponding time stamp, wherein the plurality of measurement data is obtained by the sensor being awakened and measured based on a first time interval, wherein during operation of the object, the first time interval changes based on an operation state of the object; determining a total travel distance of the object based on the plurality of measurements; determining a travel distance offset of a bearing, wherein the travel distance offset of the bearing is the distance the object has traveled when the bearing is mounted on the object; and Based on the determined total travel distance of the object and the determined travel distance offset of the bearing, a number of revolutions of the bearing is determined.

2. The method according to claim 1, wherein: The first time interval is changed based on the running state of the object, comprising: When the running state of the object is a first state, reducing the first time interval according to a first change factor; and When the running state of the object is the second state, the first time interval is increased according to a second change factor having a change rate smaller than the first change factor.

3. The method according to claim 2, wherein: The first change factor is a multiplication factor and the second change factor is an addition factor.

4. The method according to claim 2, wherein: The running state of the object includes one or more of the following: fast running state, slow running state, and stop state. The first state is a fast running state, and the second state is a slow running state or a stopped state.

5. The method according to claim 1, wherein: Each of the plurality of measurement data includes position information of the object, wherein the position information is used to indicate the position of the object when the measurement data is measured. Wherein, determining the total travel distance of the object based on the plurality of measurement data comprises: Determining a first incremental travel distance of the object based on the position information of the object and the corresponding timestamp; and The first incremental travel distance is added to a previous travel distance of the object to determine the total travel distance.

6. The method according to claim 5, wherein: The sensor includes a positioning module, wherein the position information of the object is acquired via the positioning module.

7. The method according to claim 1, wherein: Each of the plurality of measurement data includes operation status information of the object, wherein the operation status information is used to indicate the operation status of the object when the measurement data is measured. Wherein, determining the total travel distance of the object based on the plurality of measurement data comprises: Determining the running time of the object based on the running state information of the object and the corresponding timestamp; determining a second incremental travel distance of the object based on the elapsed time and a travel speed corresponding to the elapsed time; and The second incremental travel distance is added to a previous travel distance of the object to determine the total travel distance.

8. The method according to claim 7, wherein: The sensor comprises a speed acquisition module, and the running state information of the object is acquired via the speed acquisition module.

9. The method according to claim 1, wherein: Determining the number of revolutions of the bearing based on the determined total travel distance of the object and the determined travel distance offset of the bearing includes: subtracting the travel distance offset from the total travel distance to obtain a first travel distance of the bearing; and dividing the first travel distance by a second travel distance associated with the bearing to obtain the number of revolutions, The second travel distance is the distance traveled by the object when the bearing rotates one circle.

10. An apparatus for estimating the number of bearing revolutions on an object, the apparatus comprising: The transceiver is configured as: Receiving a plurality of measurement data from a sensor, wherein each of the plurality of measurement data has a corresponding time stamp, wherein the plurality of measurement data is measured by the sensor upon waking up based on a first time interval, wherein during operation of the object, the first time interval changes based on an operation state of the object; and A processor is coupled to the transceiver and is configured to: determining a total travel distance of the object based on the plurality of measurements; determining a travel distance offset of a bearing, wherein the travel distance offset of the bearing is the distance the object has traveled when the bearing is mounted on the object; and Based on the determined total travel distance of the object and the determined travel distance offset of the bearing, a number of revolutions of the bearing is determined.

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