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

Abstract

The present disclosure provides a method and apparatus for estimating a number of revolutions of a bearing on an object, the method comprising: receiving a plurality of measurement data from a plurality of sensors, where each of the plurality of measurement data has a respective timestamp; 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 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 multiple measurement data from multiple sensors, wherein each of the multiple measurement data has a corresponding timestamp; determining a total travel distance of the object based on the multiple 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, each of the multiple sensors is an energy-limited sensor, wherein the multiple measurement data are obtained by waking up and measuring the multiple sensors in sequence according to a predetermined order and time interval for measuring the measurement data.

[0006] According to an embodiment of the present disclosure, each of the multiple sensors is an energy-limited sensor, wherein the multiple measurement data are awakened and measured by at least one of the multiple sensors at a wake-up time for a second measurement, wherein the second measurement is other measurement different from the measurement data.

[0007] 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.

[0008] According to an embodiment of the present disclosure, each of the plurality of sensors includes a positioning module, wherein the position information of the object is acquired via the positioning module.

[0009] 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.

[0010] According to an embodiment of the present disclosure, each of the plurality of sensors includes a speed acquisition module, and the running state information of the object is acquired via the speed acquisition module.

[0011] 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.

[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 multiple measurement data from multiple sensors, wherein each of the multiple measurement data has a corresponding timestamp; and a processor, coupled to the transceiver and configured to: determine a total travel distance of the object based on the multiple 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 rotations of a bearing on an object, the device comprising: a communication module configured to receive multiple measurement data from multiple sensors, wherein each of the multiple measurement data has a corresponding timestamp; a first determination module configured to determine the total travel distance of the object based on the multiple 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 rotations 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. When the instructions are executed, the instructions cause a processor to perform a method for estimating the number of bearing revolutions on an 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 distributed energy-constrained sensors (rather than relying on any wired-powered always-on devices), the number of revolutions of the wheel bearings can be inferred. 2) By using the method provided by the present disclosure, the trajectory of objects equipped with these 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 plurality of sensors 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 plurality of sensors according to an embodiment of the present disclosure is shown;

[0021] Figure 4 A schematic diagram showing a method for estimating the number of bearing revolutions on an object according to an embodiment of the present disclosure;

[0022] Figure 5 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;

[0023] Figure 6 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

[0024] Figure 7 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

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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".

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] The present disclosure provides a method for inferring the number of revolutions of a wheel bearing by using a plurality of energy-constrained sensors installed in an object. The method can be implemented using a computing device and a group of energy-constrained sensors. The sensors wake up sequentially or successively, 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.). The computing device can then infer the distance traveled by the object equipped with these sensors. Based on this, the number of revolutions of the wheel bearing can be further estimated or inferred.

[0035] In some embodiments, a sensor installed in an object (e.g., a train or subway, etc.) can provide the location information of the object and / or sense the running state of the object (e.g., fast running, slow running or stopping, 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), 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. In some embodiments, the location information and / or running state of the object can be obtained by multiple sensors currently equipped on the object (e.g., a temperature sensor or a vibration sensor). For example, the location information and / or operating status of the object can be obtained by using the existing (or associated) positioning module and / or accelerometer module in the multiple sensors currently equipped on the object, or the location information and / or operating status of the object can be obtained by integrating the positioning module and / or accelerometer module in the multiple sensors currently equipped on the object. In addition, the location information and / or operating status of the object can also be obtained by a dedicated sensor including a positioning module and / or an accelerometer module. In some cases, these sensors may be energy-constrained sensors.

[0036] In some embodiments, all (e.g., N, where N is an integer greater than or equal to 2) energy-limited sensors can be awakened in sequence or successively. In some embodiments, the N sensors can be awakened in turn according to a preset number and order and / or time interval. In some embodiments, one or more of the N sensors can also perform wake-up and measurement according to their own state. For example, when the sensor detects that its own power is lower than a first threshold, the sensor can choose to wake up once every other round, and so on. After waking up, the sensor can measure the location information and / or operating status of the object, and can record a timestamp corresponding to the measurement. Multiple measurement data (e.g., location information and / or operating status with timestamps) can be uploaded 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.).

[0037] Figure 1 FIG. 1 is a schematic diagram showing a method of determining the travel distance of an object based on location information received from multiple sensors according to an embodiment of the present disclosure. For application scenarios where location information is easily available (e.g., train application scenarios), as shown in FIG. Figure 1 As shown, the position information recorded by multiple (eg, N) sensors (eg, at time T 1 、T 2 ,…,T N+N The recorded object positions) can be plotted in the cloud server. The distance between two position samples (e.g., T 1 and T 2 The distance between the sample points at the location) can be obtained by To simply estimate, where X and Y (i.e., X 1 , Y 1 , X 2 , Y 2 ) represents the location coordinates of the object (e.g., latitude and longitude). To simplify the problem, the more specific conversion process between the longitude and latitude location coordinates and the distance is omitted here. If higher accuracy is desired, the time interval Δt between adjacent sampling time points can be shortened (e.g., T 1 and T 2 The distance can be corrected by using the time interval between the two locations) or by using the Geographic Information System (GIS) method.

[0038] For example, 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 (X 1 ,Y 1 ,X 2 ,Y 2 ). 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.

[0039] Thus, by utilizing N sensors installed in the object, it is possible to achieve The position sampling rate of each sensor is The sensor can be woken up at a rate of , thereby significantly reducing energy consumption. It should be noted that the time interval Δt does not need to be a constant, because each measurement data has a corresponding timestamp, which means that, especially for a larger N, one or more of the N sensors can even perform wake-up and measurement according to their own schedule rather than in a dedicated manner. For example, in the case where the sensor is a temperature or vibration sensor integrated with (or associated with) a positioning module and / or an accelerometer module as described above, one or more of the N sensors can perform wake-up and position and / or operating state measurements according to a schedule for other measurements (which may be referred to as second measurements in this article) other than the position and / or operating state of the object, without having to specifically configure the wake-up time for the measurement of the position and / or operating state of the object. For example, the sensor can wake up at the wake-up time for measuring temperature and / or vibration information, and complete the measurement of the position and / or operating state of the object during this period. In some embodiments, the time interval Δt between different adjacent position samples may be the same or different.

[0040] Figure 3 A schematic diagram is shown of determining a travel distance of an object based on operating status information received from a plurality of sensors according to an embodiment of the present disclosure.

[0041] For application scenarios where it is not easy to obtain location information but easy to obtain average speed (for example, subway application scenarios), Figure 3 As 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, we can think of the object in T 1 To T N+2 It is in a fast running state during the time period, and in T N+2 To T N+N The system is in a stopped state during the time period.

[0042] 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.

[0043] Next, Figure 4 A schematic diagram of a method 400 for estimating the number of bearing revolutions on an object according to an embodiment of the present disclosure is shown.

[0044] like Figure 4 As shown, the method 400 for estimating the number of bearing revolutions on an object according to an embodiment of the present disclosure may include: in step S401, receiving multiple measurement data from multiple sensors, wherein each of the multiple measurement data has a corresponding timestamp; in step S402, determining the total travel distance of the object based on the multiple measurement data; in step S403, 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 installed on the object; and in step S404, 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.

[0045] Specifically, in some embodiments, as described above, each of the multiple sensors may be an energy-limited sensor. In some embodiments, the multiple measurement data may be obtained by waking up and measuring the multiple sensors in sequence according to a predetermined order and time interval for measuring measurement data such as the position and / or operating state of an object. For example, N sensors may be woken up in turn in accordance with a preset number and order and / or time interval.

[0046] In some embodiments, multiple measurement data can be obtained by waking up and measuring at least one of the multiple sensors at a wake-up time for a second measurement, wherein the second measurement can be other measurements different from the measurement data. For example, in the case where the sensor is a temperature or vibration sensor integrated with (or associated with) a positioning module and / or an accelerometer module as described above, one or more of the N sensors can perform wake-up and position and / or operating state measurements according to a schedule for other measurements (which may be referred to as second measurements in this article) other than the position and / or operating state of the object. For example, a sensor can wake up at a wake-up time for measuring temperature and / or vibration information, and complete the measurement of the position and / or operating state of the object during this period, without having to specifically configure a wake-up time for measuring the position and / or operating state of the object.

[0047] 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 S402 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.

[0048] 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.

[0049] 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 S402 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.

[0050] 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.

[0051] 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.

[0052] 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 S404 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.

[0053] Figure 5 An example flow of a method 500 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.

[0054] like Figure 5 As shown, method 500 may start at step S501 , 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.

[0055] In step S502, the received data may be sorted in chronological order to obtain sorted data D sorted .

[0056] In step S503, it can be determined whether the data specifically includes the location information and the running status information. If the data includes the location information (for example, in a train scenario), the method 500 can proceed to step S504. In step S504, the first incremental travel distance of the object can be calculated in combination with the method described above. If the data includes the running status information (for example, in a subway scenario), the method 500 can proceed to step S505. In step S505, the second incremental travel distance of the object can be calculated in combination with the method described above.

[0057] Then, in step S506, the first incremental travel distance d determined in step S504 or the second incremental travel distance d determined in step S505 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 .

[0058] Next, in step S507, 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 S508-S511.

[0059] For example, in step S508, it can be determined whether the i-th wheel bearing among the K wheel bearings is newly installed. If the bearing is newly installed, in step S509, 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 offset It 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 500 can proceed to step S510. In step S510, 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 .

[0060] In step S511, 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 S507 and execute steps S508-S511 again. If all wheel bearings have been traversed, the method 500 can end in step S512.

[0061] It should be understood that Figure 5 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 5 The steps in may be performed in any other order. Figure 5 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.

[0062] Figure 6 A schematic diagram of a device 600 for estimating the number of bearing revolutions on an object according to an embodiment of the present disclosure is shown.

[0063] Device 600 may be any computing device capable of performing data processing, such as a local server, a cloud server, or a data processing center. Figure 6As shown, the device 600 may include a transceiver 610 and a processor 620. The transceiver 610 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 processor 620 may be communicatively coupled to the transceiver 610 and may be 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 rotations of the bearing based on the determined total travel distance of the object and the determined travel distance offset of the bearing.

[0064] In addition, the device 600 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.

[0065] Figure 7 A schematic diagram of a device 700 for estimating the number of bearing rotations on an object according to an embodiment of the present disclosure is shown.

[0066] like Figure 7 As shown, 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 the total travel distance of the object based on the plurality of measurement data. The second determination module 703 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 704 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.

[0067] In addition, the device 700 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.

[0068] 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.

[0069] Furthermore, 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 according to an embodiment of the present disclosure.

[0070] 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.

[0071] 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.

[0072] 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.

[0073] 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.

[0074] 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.

[0075] 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.

[0076] 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 plurality of sensors, wherein each of the plurality of measurement data has a corresponding time stamp; 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: Each of the multiple sensors is an energy-limited sensor, wherein the multiple measurement data are obtained by waking up and measuring the multiple sensors in sequence according to a predetermined order and time interval for measuring the measurement data.

3. The method according to claim 1, wherein: Each of the plurality of sensors is an energy-limited sensor, wherein the plurality of measurement data is obtained by waking up and measuring at least one of the plurality of sensors at a wake-up time for a second measurement, The second measurement is another measurement different from the measurement data.

4. 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.

5. The method according to claim 4, wherein: Each of the plurality of sensors includes a positioning module, wherein the position information of the object is acquired via the positioning module.

6. 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.

7. The method according to claim 6, wherein: Each of the plurality of sensors includes a speed acquisition module, and the running state information of the object is acquired via the speed acquisition module.

8. The method according to claim 6, wherein: 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.

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 plurality of sensors, wherein each of the plurality of measurement data has a corresponding time stamp; 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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