Method and device for estimating the revolutions of a bearing on an object

Abstract

The present disclosure provides a method and an apparatus for estimating the revolutions of a bearing on an object, the method comprising: receiving multiple measurement data from multiple sensors, each of the multiple measurement data having a corresponding timestamp; determining a total distance traveled by the object based on the multiple measurement data; determining an offset of the bearing's distance traveled, wherein the offset of the bearing's distance traveled is a distance traveled by the object when the bearing is installed on the object; and determining the revolutions of the bearing based on the determined total distance traveled by the object and the determined offset of the bearing's distance traveled.

Description

TECHNICAL FIELD

[0001] Embodiments of the present disclosure relate to a technical field of data processing, and more particularly to a method and apparatus for estimating revolutions of a bearing on an object. BACKGROUND

[0002] To create a comprehensive profile of the wheel bearing usage of an object (e.g., a train, a subway, a vehicle, etc.) or to realize reliable remote diagnostics of the bearings, recording the bearing revolutions (i.e., the accumulated revolutions since the bearings were installed) is a very important input. Measuring such an accumulated metric generally requires continuous monitoring. However, an energy-constrained (e.g., battery-powered) IoT sensor (e.g., vibration and temperature sensors) typically only wakes up and takes a measurement a few times a day, thus saving energy. This means that it is difficult for such an energy-constrained sensor to be constantly powered on to record revolutions. Therefore, there is a need for an effective method that can be used with energy-constrained sensors to guess or estimate the revolutions of a bearing on an object. SUMMARY

[0003] The SUMMARY section is provided to briefly introduce concepts that are described in detail in the subsequent DETAILED DESCRIPTION section. The SUMMARY section is not intended to reveal key features or essential characteristics of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0004] Embodiments of the present disclosure provide a method for estimating revolutions of a bearing on an object, comprising: receiving a plurality of measurement data from a plurality of sensors, each of the plurality of measurement data having a corresponding timestamp; determining a total distance traveled by the object based on the plurality of measurement data; determining a traveled distance offset of the bearing, wherein the traveled distance offset of the bearing is a distance traveled by the object when the bearing is installed on the object; and determining the revolutions of the bearing based on the determined total distance traveled by the object and the determined traveled distance offset of the bearing.

[0005] According to embodiments of the present disclosure, each of the plurality of sensors is a power-limited sensor, wherein the plurality of measurement data is measured by the plurality of sensors sequentially waking up according to a preset order and a preset time interval for measuring the measurement data.

[0006] According to embodiments of the present disclosure, each of the plurality of sensors is a power-limited sensor, wherein the plurality of measurement data is measured by at least one of the plurality of sensors that wakes up at a wake-up time for a second measurement, and wherein the second measurement is a different measurement than a measurement for the measurement data.

[0007] According to embodiments of the present disclosure, each of the plurality of measurement data includes position information of the object, wherein the position information is used to indicate a position of the object when the measurement data is measured, and wherein determining a total traveled distance of the object based on the plurality of measurement data comprises: determining a first incremental traveled distance of the object based on the position information of the object and the corresponding timestamp; and adding the first incremental traveled distance to a previously traveled distance of the object to determine the total traveled distance.

[0008] According to embodiments of the present disclosure, each of the plurality of sensors comprises a location module, wherein the position information of the object is acquired via the location module.

[0009] According to embodiments of the present disclosure, each of the plurality of measurement data includes running state information of the object, wherein the running state information is used to indicate a running state of the object when the measurement data is measured, and wherein determining a total traveled distance of the object based on the plurality of measurement data comprises: determining a running time of the object based on the running state information of the object and the corresponding timestamp; determining a second incremental traveled distance of the object based on the running time and a running speed corresponding to the running time; and adding the second incremental traveled distance to a previously traveled distance of the object to determine the total traveled distance.

[0010] According to embodiments of the present disclosure, each of the plurality of sensors includes a speed detection module, wherein the running state information of the object is detected via the speed detection module.

[0011] According to embodiments 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.

[0012] According to embodiments of the present disclosure, determining the revolutions of the bearing based on the determined total distance traveled by the object and the determined offset of the bearing comprises: subtracting the offset of the traveled distance from the total distance traveled to obtain a first distance traveled by the bearing; and dividing the first distance traveled by a second distance traveled associated with the bearing to obtain the revolutions, wherein the second distance traveled is a distance traveled by the object when the bearing rotates one revolution.

[0013] Embodiments of the present disclosure provide an apparatus for estimating revolutions of a bearing on an object, comprising: a transceiver configured to receive a plurality of measurement data from a plurality of sensors, each of the plurality of measurement data having a corresponding timestamp; and a processor coupled to the transceiver and configured to determine a total distance traveled by the object based on the plurality of measurement data; determine a traveled distance offset of the bearing, wherein the traveled distance offset of the bearing is a distance traveled by the object when the bearing is installed on the object; and determine the revolutions of the bearing based on the determined total distance traveled by the object and the determined traveled distance offset of the bearing.

[0014] Embodiments of the present disclosure provide an apparatus for estimating revolutions of a bearing on an object, comprising: a communication module configured to receive a plurality of measurement data from a plurality of sensors, each of the plurality of measurement data having a corresponding timestamp; a first determination module configured to determine a total distance traveled by the object based on the plurality of measurement data; a second determination module configured to determine a traveled distance offset of the bearing, wherein the traveled distance offset of the bearing is a distance traveled by the object when the bearing is installed on the object;and a third determination module configured to determine the revolutions of the bearing based on the determined total distance traveled by the object and the determined offset of the distance traveled by the bearing;

[0015] Embodiments of the present disclosure provide a computer-readable storage medium having stored thereon instructions that, when executed, cause a processor to perform a method for estimating the revolutions of a bearing on an object in accordance with embodiments of the present disclosure.

[0016] The method, apparatus, and device provided by the present disclosure have at least one or more of the following advantages: 1) by utilizing distributed energy-limited sensors (rather than relying on any wire-powered "always-on" devices), the revolutions of a wheel bearing can be assumed, and 2) by applying the method provided by the present disclosure, the track of the object equipped with the sensors can also potentially be profiled. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description taken in conjunction with the accompanying drawings. Throughout the drawings, like or similar reference numerals designate like or similar elements. It should be understood that the drawings are schematic, and the original and elements are not necessarily drawn to scale. Fig. 1 shows a schematic diagram for determining a distance traveled by an object based on position information received from a plurality of sensors according to embodiments of the present disclosure; Fig. 2 shows a schematic representation of the revision of a distance using a GIS method according to embodiments of the present disclosure; Fig. 3 shows a schematic diagram for determining a distance traveled by an object based on running state information received from a plurality of sensors according to embodiments of the present disclosure; Fig. 4 shows a schematic representation of a method for estimating the revolutions of a bearing on an object according to embodiments of the present disclosure; Fig. 5 shows an example of the flow of a method for estimating the revolutions of a bearing on an object performed on a computing device according to embodiments of the present disclosure; Fig. 6 shows a schematic representation of an apparatus for estimating the revolutions of a bearing on an object according to embodiments of the present disclosure; and Fig. 7 shows a schematic representation of an apparatus for estimating the revolutions of a bearing on an object according to embodiments of the present disclosure. DETAILED DESCRIPTION

[0018] Embodiments of the present disclosure are described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are illustrated in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments shown herein, but these embodiments are 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 for illustrative purposes only and should not be used to limit the scope of the present disclosure.

[0019] It should be understood that the steps described in the method implementations of the present disclosure may be performed in a different order and / or in parallel. Furthermore, method implementations may include additional steps and / or omit the illustrated steps. The scope of the present disclosure is not limited in this regard.

[0020] As used herein, the term "comprising" and its variants are open-ended, meaning "including, but not limited to." The term "based on" means "based at least in part on." The term "an embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments." Related definitions of some other terms are provided in the following description.

[0021] It should be understood that the terms "first" and "second" mentioned in the present disclosure are used only to distinguish different means, modules or units and are not intended to limit the order or interdependence of the functions performed by those means, modules or units.

[0022] It should be understood that the modifications of "a" and "a plurality" mentioned in the present disclosure are schematic but not limiting, and those skilled in the art should understand that they are to be understood as "one or more" unless the context clearly indicates otherwise.

[0023] The names of the messages or information exchanged between multiple devices in the implementations of the present disclosure are used for illustrative purposes only and are not intended to limit the scope of those messages or information.

[0024] In the present disclosure, an object may refer to any object that moves with wheels and is equipped with wheel bearings, such as a train, a subway, a vehicle (a car, a truck, etc.), a bicycle, etc.

[0025] In the present disclosure, a power-constrained sensor may refer to a sensor that wakes up and takes measurements only once or a few times in a given period of time to conserve power, e.g., a battery-powered sensor.

[0026] To realize reliable remote diagnostics of bearings through sensors (e.g., vibration and temperature sensors) as one of the most commonly used inputs, it is expected that the accumulated revolutions since the bearings were installed are provided. Measuring such an accumulated metric generally requires continuous monitoring, which poses a significant challenge for energy-constrained (e.g., battery-powered) Internet of Things (IoT) sensors that must be constantly powered on.

[0027] The present disclosure provides a method for estimating the rotations of a wheel bearing using multiple energy-limited sensors installed in an object. The method can be implemented using a computing device and a group of energy-limited sensors. The sensors wake up sequentially or one after the other, measure measurement data of the object (e.g., position or running state, etc.), record corresponding timestamps, and upload the measurement data to the computing device (e.g., a server, a cloud server, or a gateway, etc.). The computing device can then estimate a distance traveled by the object equipped with these sensors. Based on this, the rotations of the wheel bearings can be further estimated or estimated.

[0028] In some embodiments, a sensor installed in an object (e.g., a train or subway, etc.) may provide position information of the object and / or detect the object's running state (e.g., fast-moving, slow-moving, or stopped, etc.). Generally, the object's position information may be obtained via a positioning module (e.g., a Global Position System (GPS) / Global Navigation Satellite System (GNSS) module), and the object's running state may be detected via a velocity detection module. In some embodiments, the velocity detection module may be an accelerometer module, a gyroscope, or any other existing or future module that can be used to detect the velocity of an object. In some embodiments, the velocity detection module may also be a receiving module capable of receiving external information (e.g.,Speed ​​information of the object, etc.) from outside or from other modules. To simplify the description, an accelerometer module is described below as an example. In some embodiments, the position information and / or running state of the object may be obtained by multiple sensors (e.g., temperature sensors or vibration sensors) already present on the object. For example, an existing (or associated) positioning module and / or accelerometer module may be used in a plurality of sensors already present on the object to obtain the position information and / or running state of the object, or a positioning module and / or accelerometer module may be integrated into multiple sensors already present on the object to obtain the position information and / or running state of the object.In addition, the position information and / or the running state of the object can also be obtained by a specific sensor comprising a tracking module and / or an accelerometer module. In some cases, these sensors may be energy-limited sensors.

[0029] In some embodiments, all (e.g., N, where N is an integer greater than or equal to 2) power-constrained sensors may wake up sequentially or one after the other. In some embodiments, N sensors may wake up sequentially according to a preset number, order, and / or time period. In some embodiments, one or more of the N sensors may also wake up and take measurements according to their own state. For example, if a sensor detects that its power is below a first threshold, it may choose to wake up every other lap, and so on. After waking up, the sensor may measure the position information and / or the walking state of the object, recording a timestamp for the measurement. Multiple measurement data (e.g., position information and / or walking state with a timestamp) may be uploaded to a computing device (e.g., a server, a cloud server, or a gateway, etc.).In some embodiments, the measurement data may be uploaded at a preconfigured time. In some embodiments, the measurement data may be uploaded based on a request or trigger from the computing device. In some embodiments, the measurement data may be uploaded along with other data (e.g., temperature data, vibration data, etc.).

[0030] Fig. Figure 1 shows a schematic representation of determining a distance traveled by an object based on position information received from multiple sensors according to embodiments of the present disclosure. For an application (e.g., a train application) where position information is readily available, as in Fig. 1, position information (e.g. object positions at times T1, T2, ..., T N+Nrecorded by multiple (e.g., N) sensors are recorded in a cloud server. The distance between two position samples (e.g., the distance between position samples at T1 and T2) can be easily estimated by (X1−X2)2+(Y1−Y2)2, where X and Y (i.e., X1, Y1, X2, Y2) represent the position coordinates of the object (e.g., latitude and longitude). To simplify the topic, a more precise conversion of the coordinates of latitude and longitude into distance is omitted here. If higher accuracy is expected, a time interval Δt between adjacent sampling points (e.g., the time interval between T1 and T2) can be shortened, or the distance can be verified using a geographic information system (GIS).

[0031] Fig. For example, Figure 2 shows a schematic representation of the revision of a distance using a GIS method according to embodiments of the present disclosure. As in Fig. As shown in Figure 2, a trajectory line corresponding to two adjacent position samples can be selected on a given map, and the longitudinal distance of the two adjacent position samples on the trajectory line can be calculated. The distance simply estimated based on the above equation can be expressed as Dsimple=(X1−X2)2+(Y1−Y2)2 while the figures based on the figures in Fig. 2 presented GIS method further revised distance as D GIS(X1, Y1, X2, Y2). Furthermore, based on the distance between any two adjacent position samples, the distance traveled by the object in any given period of time or between any two position samples can be calculated by summing them.

[0032] In this way, when using N sensors installed in the object, a position sampling rate of 1ΔT be realized, while each sensor only operates at a rate of 1Δt×N wake up, significantly reducing energy consumption. Note that the time interval Δt does not need to be constant, since each measurement date has a corresponding timestamp. This means that, especially with a larger N, one or more of the N sensors may even wake up and perform the measurement according to their own schedule, rather than in a specific way.For example, if the sensors are temperature or vibration sensors integrated with (or associated with) positioning modules and / or accelerometer modules as described above, one or more of the N sensors may wake up and perform a measurement of the position and / or running state of the object according to a schedule for measurements other than the position and / or running state measurement (which may be referred to herein as a second measurement), without configuring a specific wake-up time for the measurement of the position and / or running state of the object. For example, the sensor may wake up at a wake-up time for the measurement of temperature and / or vibration information and complete the measurement of the position and / or running state of the object during that time. In some embodiments, the time interval Δt between different adjacent position samples may be the same or different.

[0033] Fig. 3 shows a schematic diagram for determining a distance traveled by an object based on running state information received from a plurality of sensors according to embodiments of the present disclosure.

[0034] For an application (e.g., a subway application) where position information is not readily available, but an average speed may be readily available, as in Fig. As shown in Figure 3, a running state of an object (e.g., a subway train) may be measured or recorded. In some embodiments, the running state of the object may include one or more of the following states: a fast running state, a slow running state, or a stopped state. In this way, a running time of the object may be estimated in a computing device based on the information about the running state of the object and the corresponding timestamps, and the distance traveled by the object may be estimated by multiplying the running time by corresponding average speeds. In some embodiments, a corresponding average speed may be estimated or configured in advance for each running state of the object.For example, a fast running state may correspond to a first speed, a slow running state may correspond to a second speed that is lower than the first speed, and a stopped state may correspond to a zero speed. In other embodiments, the average speed of the object in different running states may be obtained or estimated in any other way, not limited here. Fig. 3 shows only two running states, namely a fast running state and a stop state. In the present disclosure, it can be assumed that the running state of the object does not change within a time interval Δt. Therefore, in the example of Fig. 3 it can be assumed that the object is in the state of emergency during the period from T1 to T N+2 in a high-speed state and during the period of T N+2 are N+N is in a stop state.

[0035] In addition, the position information and / or the running state of the object recorded by the sensors can be sent or uploaded to the computing device immediately after recording, or they can be uploaded evenly at a preset time, as indicated by the shaded rectangle in Fig. 1 or Fig. 3. There are no restrictions regarding the timing or method of uploading the data.

[0036] Fig. 4 shows a schematic representation of a method 400 for estimating the revolutions of a bearing on an object according to embodiments of the present disclosure.

[0037] As in Fig. 4, the method 400 for estimating revolutions of a bearing on an object according to embodiments of the present disclosure may include: in step S401, receiving a plurality of measurement data from a plurality of sensors, each of the plurality of measurement data having a corresponding timestamp; in step S402, determining a total traveled distance of the object based on the plurality of measurement data; in step S403, determining a traveled distance offset of the bearing, wherein the bearing traveled distance offset is a distance traveled by the object when the bearing is installed on the object; and in step S404, determining the revolutions of the bearing based on the determined total traveled distance of the object and the determined bearing traveled distance offset.

[0038] In particular, in some embodiments, as described above, each of the plurality of sensors may be a power-limited sensor. In some embodiments, the plurality of measurement data may be measured by sequentially waking up the plurality of sensors according to a predetermined order and time interval to measure measurement data such as the position and / or running state of the object. For example, N sensors may wake up sequentially according to a preset number, order, and / or time interval.

[0039] In some embodiments, the plurality of measurement data may be measured by at least one of the plurality of sensors waking up at a wake-up time for a second measurement, where the second measurement may be a different measurement than a measurement for the measurement data. For example, if the sensors are temperature or vibration sensors integrated with (or associated with) positioning modules and / or accelerometer modules as described above, one or more of the N sensors may wake up and perform a measurement of the position and / or running state of the object according to a scheduling for measurements other than the position and / or running state measurement (which may be referred to herein as a second measurement).For example, the sensor may wake up at a wake-up time for measuring temperature and / or vibration information and complete the measurement of the position and / or running state of the object during that time without specifically configuring the wake-up time for measuring the position and / or running state of the object.

[0040] In some embodiments, each of the plurality of measurement data may include position information of an object, which may be used to indicate the position of the object when the measurement data is measured. In some embodiments, determining a total distance traveled by the object based on the plurality of measurement data in step S402 may further comprise: determining a first incremental distance traveled by the object based on the position information of the object and the corresponding timestamp; and adding the first incremental distance traveled to a previously traveled distance of the object to determine the total distance traveled.

[0041] For example, a computing device as in Fig. 1, receive multiple measurement data comprising position information of an object from sensors and sort the multiple pieces of position information according to the corresponding timestamps. The computing device can calculate the distance (e.g., the segment distance corresponding to each time interval Δt) between two adjacent position samples sorted in time order in the manner described above, and then accumulate the segment distances corresponding to all time intervals Δt to obtain the first incremental distance traveled by the object in the time period corresponding to this position information. Subsequently, the total distance traveled by the object is obtained by adding the first incremental distance to the total distance previously traveled by the object.

[0042] In some embodiments, each of the plurality of measurement data may include running state information of the object, which may be used to indicate a running state of the object when the measurement data is measured. In some embodiments, determining a total distance traveled by the object based on the plurality of measurement data in step S402 may further comprise: determining a running time of the object based on the running state information of the object and the corresponding timestamp; determining a second incremental distance traveled by the object based on the running time and a running speed corresponding to the running time; and adding the second incremental distance traveled to a previously traveled distance of the object to determine the total distance traveled.

[0043] For example, in Fig. 3, a computing device may, for example, receive multiple measurement data including information about the running state of the object from the sensors and sort the multiple pieces of running state information according to the corresponding timestamps. As mentioned above, it is assumed that the running state of the object does not change within a time interval Δt, so that the running time of the object in each running state can be easily determined based on the multiple pieces of running state information and the corresponding timestamps. By multiplying the running time of the object in each running state by a predetermined average speed corresponding to the respective running state, the second incremental distance traveled by the object in the time period corresponding to this running state information can be determined.The total distance traveled by the object is then obtained by adding the second incremental distance traveled to the total distance previously traveled by the object.

[0044] In some embodiments, the running state of the object may include one or more of the following states: a fast running state, a slow running state, and a stopped state.

[0045] In some embodiments, determining the revolutions of the bearing based on the determined total distance traveled by the object and the determined offset of the bearing in step S404 may further comprise: subtracting the offset of the traveled distance from the total distance traveled to obtain a first traveled distance of the bearing; and dividing the first traveled distance by a second traveled distance associated with the bearing to obtain the revolutions, where the second traveled distance may be a distance traveled by the object when the bearing rotates one revolution. The second traveled distance may be, for example, the circumference of a wheel corresponding to the bearing.In addition, as described above, the offset of the traveled distance of the bearing can be the distance that the object has already traveled when the bearing is installed on the object.

[0046] Fig. 5 shows an example of the flow of a method 500 for estimating the revolutions of a bearing on an object performed on a computing device according to embodiments of the present disclosure.

[0047] As in Fig. 5, the method 500 may begin with a step S501 in which a computing device (e.g., a server, a cloud server, etc.) may receive data including position information or information about the running state of an object from sensors.

[0048] In step S502, the received data may be sorted in a chronological order to generate sorted data D sorted to obtain.

[0049] In step S503, it may be determined what information (e.g., position information and / or running state information) the data includes. If the data includes position information (e.g., in a train application), the method 500 may proceed to step S504. In step S504, a first incremental distance traveled by the object may be calculated in combination with the methods described above. If the data includes running state information (e.g., in a subway application), the method 500 may proceed to step S505. In step S505, a second incremental distance traveled by the object may be calculated in combination with the methods described above.

[0050] Then, in step S506, the first incremental distance d determined in step S504 or the second incremental distance d determined in step S505 can be added to the total distance d prevous_totalthat the object has previously traveled, thus determining the total distance traveled d total of the object.

[0051] Next, in step S507, for an application with K wheel bearings (e.g., K is an integer greater than or equal to 1), all wheel bearings can be run through, performing steps S508-S511.

[0052] For example, in step S508, it may be determined whether an i-th wheel bearing among the K wheel bearings is newly installed. If the bearing is newly installed, an offset of the traveled distance d offset of the camp from the total distance covered d total of the object, and then the result is divided by the circumference Φ*pi of the wheel corresponding to the bearing (where Φ is the diameter of the wheel) to find the revolutions of the bearing, revolution i , to determine. As described above, the distance traveled d offsetof the bearing may be the distance the object has already traveled when the bearing is installed on the object. If the bearing is not newly installed, but was installed, for example, before the object began to move, the method 500 may continue with step S510. In step S510, the revolutions of the bearing, revolution i , can be determined directly by calculating the total distance travelled d total of the object is divided by the circumference Φ*pi of the wheel corresponding to the bearing.

[0053] In step S511, it can be determined whether all wheel bearings have been traversed based on the number i of the current wheel bearing. If not all wheel bearings have been traversed yet, the method can return to step S507 and steps S508-S511 can be performed again. If all wheel bearings have been traversed, method 500 can end in step S512.

[0054] It should be understood that the Fig. 5 is only one example of a method for estimating the revolutions of a bearing on an object according to embodiments of the present disclosure, and the steps in Fig. 5 can be performed in any other order. In addition, one or more steps can be Fig. 5 may be omitted or combined with each other, or any other method or step according to the embodiments of the present disclosure may be added.

[0055] Fig. 6 shows a schematic representation of an apparatus 600 for estimating the revolutions of a bearing on an object according to embodiments of the present disclosure.

[0056] The device 600 may be any computing device suitable for data processing, e.g., a local server, a cloud server, a data processing center, etc. As in Fig. 6, the apparatus 600 may include a transceiver 610 and a processor 620. The transceiver 610 may be configured to receive a plurality of measurement data items from a plurality of sensors, each of the plurality of measurement data items having a corresponding timestamp. The processor 620 may be communicatively coupled to the transceiver 610 and may be configured to determine a total distance traveled by the object based on the plurality of measurement data items; determine a traveled distance offset of the bearing, where the traveled distance offset is a distance traveled by the object when the bearing is installed on the object; and determine the revolutions of the bearing based on the determined total distance traveled by the object and the determined traveled distance offset of the bearing.

[0057] Moreover, the apparatus 600 may also perform any other method or step according to the above-described embodiments of the present disclosure, which are not repeated in detail here.

[0058] Fig. 7 shows a schematic representation of an apparatus 700 for estimating the revolutions of a bearing on an object according to embodiments of the present disclosure.

[0059] As in Fig.As shown in Figure 7, the device 700 may include a communication module 701, a first determination module 702, a second determination module 703, and a third determination module 704. The communication module 701 may be configured to receive a plurality of measurement data from a plurality of sensors, wherein each of the plurality of measurement data has a corresponding timestamp. The first determination module 702 may be configured to determine a total distance traveled by the object based on the plurality of measurement data. The second determination module 703 may be configured to determine an offset of the traveled distance of the bearing, wherein the offset of the traveled distance of the bearing is a distance traveled by the object when the bearing is installed on the object.The third determination module 704 may be configured to determine the revolutions of the bearing based on the determined total distance traveled by the object and the determined offset of the distance traveled by the bearing.

[0060] In addition, the device 700 may also include other modules that perform other methods or steps according to the above-described embodiments of the present disclosure, which are not repeated in detail here.

[0061] In particular, according to embodiments of the present disclosure, the methods or processes described above in connection with the embodiments of the present disclosure or the drawings may be implemented as a computer software program. For example, one embodiment of the present disclosure includes a computer program product comprising computer programs on a non-transitory, computer-readable medium that includes program codes for carrying out the methods depicted in the flowcharts. In such an embodiment, the computer programs may be downloaded and installed from the network via a communication device, or they may be installed from a storage device or from a read-only memory.When the computer programs are executed by a processing device, the above-mentioned functions defined in the methods of the embodiments of the present disclosure are performed.

[0062] Furthermore, embodiments of the present disclosure are provided with a computer-readable storage medium having stored thereon instructions that, when executed, cause a processor to perform any method for estimating the revolutions of a bearing on an object according to embodiments of the present disclosure.

[0063] The flowcharts and block diagrams in the drawings illustrate the architecture, functions, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this context, each block in the flowchart or block diagram may represent a module, program segment, or portion of code containing one or more executable instructions for implementing specific logical functions. It should also be noted that in some alternative implementations, the functions represented in the blocks may occur in a different order than that shown in the drawings. For example, two blocks shown one after the other may actually execute substantially in parallel, and sometimes they may execute in reverse order, depending on the functions involved.It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a special purpose hardware-based system that performs specific functions or operations, or may be implemented by a combination of special purpose hardware and computer instructions.

[0064] The units involved in the embodiments described herein may be implemented in software or hardware. In some cases, the names of the units do not imply any limitation on the units themselves.

[0065] The functions described herein may be performed, at least in part, by one or more hardware logic components. Example types of hardware logic components that may be used include, for example, but are not limited to, Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC), Application Specific Standard Product (ASSP), System on Chip (SOC), Complex Programmable Logic Device (CPLD), etc.

[0066] In the context of the present disclosure, a machine-readable medium may be a tangible medium that can contain or store programs for use by or in connection with an instruction execution system, device, or apparatus. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the above.More specific examples of the machine-readable storage medium may include an electrical connection based on one or more wires, 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 convenient compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0067] The above description merely describes preferred embodiments of the present disclosure and explains the technical principles employed. It should be understood by those skilled in the art that the scope of the present disclosure is not limited to the technical schemes formed by the specific combination of the above technical features, but also includes other technical schemes formed by any combination of the above technical features or their equivalent features without departing from the above disclosure concept, for example, technical schemes formed by replacing the above features with technical features (but not limited to) having similar functions to those disclosed in the present disclosure.

[0068] Although the operations are presented in a particular order, this should not be understood to mean that these operations must be performed in the order presented or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Although several specific implementation details are included above, they should not be understood as limiting the scope of the present disclosure. Some features described in connection with individual embodiments may also be combined in a single embodiment. Conversely, various features described in connection with a single embodiment may also be implemented in multiple embodiments individually or in any suitable subcombination.

[0069] Although the subject matter has been described in language referring to structural features and / or methodological-logical acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. On the contrary, the specific features and acts described above are merely exemplary forms for implementing the claims.

Claims

[1] A method for estimating the revolutions of a bearing on an object, comprising: Receiving a plurality of measurement data from a plurality of sensors, each of the plurality of measurement data having a corresponding timestamp; Determining a total distance traveled by the object based on the plurality of measurement data; Determining a bearing traveled distance offset, wherein the bearing traveled distance offset is a distance traveled by the object when the bearing is installed on the object; and Determining the revolutions of the bearing based on the determined total distance traveled by the object and the determined offset of the distance traveled by the bearing. [2] The method of claim 1, wherein each of the plurality of sensors is a power-limited sensor, and wherein the plurality of measurement data is measured by the plurality of sensors sequentially waking up according to a predetermined order and a predetermined time interval for measuring the measurement data. [3] The method of claim 1, wherein each of the plurality of sensors is a power-limited sensor, wherein the plurality of measurement data is measured by at least one of the plurality of sensors that wakes up at a wake-up time for a second measurement, and wherein the second measurement is another measurement that is different from a measurement for the measurement data. [4] The method according to claim 1, wherein each of the plurality of measurement data comprises position information of the object, the position information being used to indicate a position of the object when the measurement data is measured, and wherein determining a total distance traveled by the object based on the plurality of measurement data comprises: Determining a first incremental distance traveled by the object based on the position information of the object and the corresponding timestamp; and Adding the first incremental distance traveled to a previously traveled distance of the object to determine the total distance traveled. [5] The method of claim 4, wherein each of the plurality of sensors comprises a locating module, and wherein the position information of the object is acquired via the locating module. [6] The method according to claim 1, wherein each of the plurality of measurement data comprises running state information of the object, the running state information being used to indicate a running state of the object when the measurement data is measured, and wherein determining a total distance traveled by the object based on the plurality of measurement data comprises: Determining a runtime of the object based on the run state information of the object and the corresponding timestamp; Determining a second incremental distance traveled by the object based on the travel time and a travel speed corresponding to the travel time; and Adding the second incremental distance traveled to a previously traveled distance of the object to determine the total distance traveled. [7] The method according to claim 6, wherein each of the plurality of sensors comprises a speed detection module, and wherein the running state information of the object is detected via the speed detection module. [8] The method of claim 6, wherein the running state of the object comprises one or more of the following: a fast running state, a slow running state, and a stop state. [9] The method of claim 1, wherein determining the revolutions of the bearing based on the determined total distance traveled by the object and the determined offset of the distance traveled by the bearing comprises: Subtracting the offset of the distance traveled from the total distance traveled to obtain a first distance traveled by the bearing; and Dividing the first distance traveled by a second distance traveled associated with the bearing to obtain the revolutions, where the second distance traveled is a distance the object travels when the bearing makes one revolution. [10] A device for estimating the revolutions of a bearing on an object, comprising: a transceiver designed to: receive multiple measurement data from multiple sensors, each of the multiple measurement data having a corresponding timestamp; and a processor coupled to the transceiver and configured to: to determine a total distance traveled by the object based on the multiple measurement data; determine a bearing traveled distance offset, where the bearing traveled distance offset is a distance traveled by the object when the bearing is installed on the object; and to determine the revolutions of the bearing based on the determined total distance traveled by the object and the determined offset of the distance traveled by the bearing.

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