RU2801635C1 - Methods and devices for determining parts wear using a limiting model - Google Patents

Abstract

FIELD: determination of wear.

SUBSTANCE: invention relates to methods and systems for determining the degree of wear of a part using data from a sensor of a used or worn part and patterns due to this part. A method is proposed for determining the wear of a part by using the degree of wear, which includes receiving data from a sensor (108, 110) representing the surface of the wear part (116). The method further includes determining deviations between measured points (310) in data from the sensor and points on one or more part models, where the part models (214, 216) may be new part models (214) and/or worn part models or parts with maximum allowable wear (216). The method further includes using a constraint model (222) that at least partially spans the part models (214, 216) and measured points (310) to determine the direction along which deviations are measured. The method may also include quantifying wear using measured deviations.

EFFECT: increase in the accuracy of determining the percentage of wear of a part.

15 cl, 7 dwg

Description

The technical field to which the invention belongs

The present invention generally relates to a method for determining the degree of wear of a part, and more particularly to methods and systems for determining the degree of wear of a part using sensor data from a used or worn part and patterns associated with the part.

Prerequisites for the creation of the invention

To facilitate earthworks (eg mining, construction, dredging, etc.), the machines are equipped with earthmoving tools. For example, tools include, but are not limited to, teeth, guards, and/or cutting edges that are typically designed to protect underlying equipment from excessive wear and/or perform other functions. As a non-limiting example, a dredging bucket may be provided with dredging teeth and/or guards attached to the cutting edge of the bucket to engage with the soil, such as ahead of the edge of the bucket. During operation, such earthmoving tools may be subjected to heavy loads and/or severe abrasion. These operating conditions cause earthmoving tools to wear out and eventually wear out or break. Excessive wear can lead to breakage and/or loss of earthmoving tools, resulting in decreased productivity, increased repair and/or maintenance costs, and other problems. Accordingly, there is a need to monitor the degree of wear of a part, for example, to understand and/or quantify the wear of a part, including the frequency of replacement of parts before they fail.

The systems were developed to determine the degree of wear caused by the part. For example, US Pat. No. 9,613,413 issued to Hasselbusch et al. (“'413 Patent”) discloses systems and methods for determining the degree of wear of parts using a mobile device. For example, the '413 patent discloses capturing digital images with a camera on a mobile device and determining deviations, for example, based on the number of pixels of wear surfaces of an imaged part relative to a modeled surface of a non-worn part and/or a used/worn part. In the examples in the '413 patent, wear was determined based on these variations.

Although the system disclosed in the '413 patent is capable of quantifying the amount of wear, deviations calculated in accordance with the methods described therein may not accurately reflect wear marks. For example, wear may occur unevenly on different surfaces, and the methods of the '413 patent may not adequately account for such wear. As a non-limiting example, the methods disclosed in the '413 patent can measure deviations not in the direction of wear and thus give an inaccurate percentage of wear.

The present invention is directed to the improvement of existing technology.

Brief summary of the invention

One aspect of the present invention is a computerized method including obtaining sensor data from a corresponding surface of a part. The data from the sensor is information about a plurality of points on a surface. The method may also include: obtaining a first model of a conditioned non-worn part corresponding to a given part; and obtaining a second model of the part due to the part with the maximum allowable wear for the given part. The first model defines the first contour of a non-worn part, and the second model defines the second contour of a given part with the maximum allowable wear. The method may also include: creating a boundary boundary, a first boundary, and a second boundary, spaced from the surface; and determining for a given point from a plurality of points, at least the first deviation between the given point and the first position on the first contour; or a second deviation between the given point and the second position on the second contour. The method may also include: determining, based on at least the first deviation or the second deviation, the degree of wear caused by a given part, wherein the first deviation and the second deviation are measured along a line extending from the bounding contour and through a given point.

Another aspect of the present invention is a system including one or more processors and a computer-readable medium storing instructions, the execution of which causes one or more processors to perform certain actions. Actions may include: obtaining information about the surface of the part; and generating, at least in part, a first model of the part based on this information. The actions may also include: comparing the first model with a second model including information about the surface of a non-worn part corresponding to a given part; with the third model, which includes information about the surface of the part with the maximum allowable wear corresponding to the given part; and a fourth pattern defined by a bounding surface at least partially enclosing the first pattern, the second pattern, and the third pattern. Actions may also include determining, based on comparison, the amount of wear caused by a given part.

Another aspect of the present invention is a computer-readable medium that stores instructions, the execution of which causes one or more processors to perform certain incremental actions. The steps may include obtaining information about the outer surface of the wear part. Information is a set of points in a three-dimensional coordinate system. The steps may also include: obtaining a first model, due to the first three-dimensional representation of the surface of a non-worn part corresponding to a given wear part; obtaining a second model, due to the second three-dimensional representation of the surface of the part with the maximum allowable wear, corresponding to a given wear part; moreover, the surface of the part with the maximum allowable wear corresponds to the maximum allowable wear due to a given part; and obtaining a third model, due to the bounding contour, at least partially enclosing the surface of a given non-worn part. The steps may also include: determining, for individual points from the plurality of points, at least a first deviation between the first position on the bounding contour and the individual point; a second deviation between the first position on the boundary contour and the second position on the surface of the unworn part; or a third deviation between the first position on the boundary contour and the third position on the surface of the part with the maximum allowable wear. The second deflection and the third deflection are measured along the direction from the first point on the bounding box and through a single point. The steps may also include determining, at least in part, based at least on the first deviation, the second deviation, or the third deviation, the degree of wear of a given part.

Brief description of the drawings

On fig. 1 depicts exemplary peripheral equipment for determining the degree of wear of a part, in accordance with embodiments of the present invention.

On fig. 2 are textual and graphical flowcharts describing and illustrating processes for determining the wear rate of a wear part in accordance with embodiments of the present invention.

On fig. 3 is a schematic diagram illustrating processes for determining the degree of wear of a wear part in accordance with embodiments of the present invention.

On fig. Figure 4 is a schematic representation of an example user interface showing the wear rates of the wear part shown in fig. 2, in accordance with additional embodiments of the present invention.

On fig. 5 shows an example of a computing environment for determining the degree of wear of a wear part in accordance with embodiments of the present invention.

On fig. 6 is a flow chart of an embodiment of a method for determining wear rate of a wear part in accordance with embodiments of the present invention.

On fig. 7 is an exemplary flowchart of a procedure after determining wear on a wear part, in accordance with embodiments of the present invention.

Detailed description of the invention

The present invention generally relates to methods, systems and equipment for determining the wear of parts. Although the specific parts described herein may be machine parts, such as earthmoving machines, earthmoving machines, and the like, the methods described herein are applicable to any number of parts that wear over time, for example, due to abrasive wear, corrosion, etc. To the extent possible, the same reference numbers will be used in all figures to refer to the same or similar parts.

On fig. 1 illustrates exemplary peripheral equipment 100 for determining the wear rate of a part based on data from a sensor or an image of the part, in accordance with embodiments of the present invention. Components of the peripheral equipment 100 can interact with each other, allowing a user, such as a machine driver, a worker, etc., to easily determine the degree of wear of a machine part, such as a wear part, based on data from a sensor determined by a given part, such as a fixed image sensor. As shown in the figure, the peripheral equipment 100 includes: a machine work station or work area 102 in which the machine 104 performs one or more functions, including, but not limited to, excavation or excavation. Also located in the workspace 102 of the machine is a user 106, a user device 108 associated with the user, and/or an image sensor 110 that is also associated with (or controlled by) the user 106. Machine work area 102 may be any location in which machine 104 and/or user 106 is located. For example, without limitation, work area 102 may be a work site, repair shop, dealership, residential building, mine, quarry, highway or road, etc. As detailed herein, the user 106 may capture data from a sensor, such as point cloud data representing a part, in the work area 102 using a sensor 110 that may be embedded in the user device 108 (although in some examples the sensor 110 or device imaging may be outside the user device 108).

Machine 104 can be any of a variety of machines, but is typically a machine that contains one or more parts that are subject to wear, such as from forces acting on such parts during operation of machine 104, and must be replaced over time. as a result of such wear. Machine 104 is a bucket loader with teeth attached near the cutting edge of the bucket. For example, in the enlarged view 112, next to the image of the machine 104, a new part 114 is shown, which is a tooth, and a worn part 116, which only looks like a new part 114 after some work done by the machine 104 (and the new part 114). In other words, a worn part 116 may represent a used part that is displayed by sensor 110, while a new part 114 can represent a "factory-made" or nominal part. As shown in fig. 1, a bucket loader is used as machine 104 and an earthmoving tool tooth is used as part 116, but other examples are possible. For example, but not limited to, machine 104 may be a work machine such as a crawler tractor, wheel loader, generator set, drilling rig, or any other type of machine that performs labour-intensive work operations. In addition to or instead of the teeth shown, work machines may contain other parts that are subjected to high loads, including tracks made up of individual track links, blades with edges for moving materials, and/or other parts that wear over time as the machine is used. in the performance of certain types of work. Another example of machine 104 may be an industrial vehicle, such as a locomotive, dump truck, truck, bus, aircraft, or the like, that moves people or payloads. By way of example, and not limitation, aircraft use turbine blades, exhaust nozzles, or other highly stressed parts that wear such parts over time and require periodic replacement. Machine 104 may also be a vehicle, such as a truck or car. Such machines also have parts subject to high loads, such as axles or tires, which wear out during operation and eventually need to be replaced. In other embodiments, machine 104 may be a work tool, such as a saw or drill, with one or more parts, such as teeth or drill bits, that wear out during use. In this disclosure, parts of machine 104 that are subjected to stresses that cause such parts to wear during operation are referred to as "wear parts". The methods described here make it possible to determine the wear of such wear parts.

User 106 may be any person or entity that owns machine 104. By way of example, and without limitation, user 106 may be the owner, operator, technician, repairer, customer service representative, dealer, or any other person associated with the machine. 104. As noted above and explained in more detail herein, the user 106 may operate the sensor 110 to capture data from the sensor on wear parts, such as wear part 116. In the examples, sensor 110 can be a 3D camera or distance sensor, including but not limited to radar sensor, LiDAR sensor, and the like. By way of example and without limitation, sensor 110 may be a transit time sensor capable of generating a layer thickness due to each captured pixel. In the examples, the sensor 110 may be installed, for example, together with the image capture station, and the worn part 116 may be placed relative to the sensor 110 to detect and/or capture the image. In other embodiments, sensor 110 may be controlled by user 106 to capture sensor data and/or image data about a worn part 116, such as a worn part installed on machine 104. By way of example, and without limitation, sensor 110 may be a manual or otherwise movable imaging device or sensor, and the user 106 can place the sensor 110, for example, in the work area 102 to capture images of the worn part 116.

User device 108 may be a mobile device carried by or otherwise accessible by user 106 in work area 102. In embodiments, user device 108 may be implemented as a smartphone, mobile phone, tablet computer, personal digital assistant, network camera, or sensor. or other computing device. In addition, as described herein, the user device 108 may have the function of determining the degree of wear of the worn part 116, for example, compared with the new part 114. As an example, without limitation, the user device 108 may receive data from the sensor, for example, data point clouds generated by sensor 110. In some examples, the functionality of sensor 110 and user device 108 may be integrated in the same device, for example, user device 108 may have an embedded sensor 110. In other examples, user device 108 may receive data from sensor 110 , for example, over a physical channel, a wireless channel, and/or network 118.

As also shown in fig. 1, peripheral equipment 100 may include one or more data processing systems 120 and one or more dealer computing devices 122. As shown in the figure, data processing system(s) 120 and dealer computing device(s) 122 are configured to communicate over network(s) 118 with one or more machines 104, user device 108, and/or sensor 110. Although data processing system(s) 120 and dealer computing devices 120 are shown separately from each other and from machine 104, user device 108 and sensor 110, however, in some examples, the functions of one or more of these components may be performed on fewer devices. By way of example, and not limitation, user device 108 may have some or all of the functions of data processing system(s) 120. Moreover, the functions described herein and attributed to one or more components shown may additionally be performed by one or more components and/or entirely different components.

The data processing system(s) 120 are typically configured to receive sensor data generated by the sensor 110 of the worn part 116 and determine its degree of wear. In the context of this document, the term "degree of wear" can refer to any amount of wear on a part. For example, a measure of wear could be percentage wear, such as relative to a new part, such as new part 114, and/or relative to a used or "worn" part, which may correspond to the maximum allowable wear before expected failure or some other wear limit. . The degree of wear may also, or alternatively, be measured as a deviation, for example corresponding to a deviation due to wear, as detailed below. As shown in fig. 1, data processing system(s) 120 may include a component 124 for determining wear, one or more part models 126, and a component 128 for determining a boundary surface.

In examples, the component 124 for determining wear can receive data from the sensor, for example, captured by the sensor 110, and compare the data from the sensor with the model(s) 126 of the part. For example, the wear component may receive data from a point cloud including a number of points based on layer thickness captured by sensor 110, such as when the sensor is a distance sensor. The wear detection component 124 is capable of determining axis positions according to the layer thickness. By way of example, and not limitation, the wear component 124 is capable of determining positions determined by the measured layer thickness in a three-dimensional (eg, x, y, z) coordinate system. For example, the measured layer thickness may be due to the surface of the worn part 114, and in some embodiments, the wear detection component 124 can generate a three-dimensional model of the measured worn part 114 and orient the model in a coordinate system.

The component 124 for determining wear may also be performed to match the data from the sensor with the model(s) 126 of the part. In the examples described herein, the part model(s) 126 may be one or more new part models, such as a new part model 114 and/or a maximum wear part model. As detailed herein, the new part model may have surface coordinates of a substantially new part and/or a part within the specification specified by the new part 114. The maximum wear model of the part may include surface coordinates, such as points on the surface. due to the most worn part. For example, a model of a part with maximum allowable wear may describe an external contour due to a part that is on the verge of breakage or, for other reasons, will inevitably fail. In other examples, the part pattern(s) 126 may include one or more additional patterns due to other stages of wear on the wear part. By way of example, and without limitation, the part model may describe surfaces corresponding to other degrees of wear, including, but not limited to, configurations due to a wear part that has 10% remaining life (i.e., the part is 90% worn), etc. . In the examples described herein, when the measured points on the worn part 116 correspond to the points on the maximum wear model, the worn part 116 must be replaced. As detailed below, the selection of the maximum wear part model may dictate when the parts are replaced and thus the selection of the maximum wear part model may be based at least in part on a predetermined condition that involves replacement.

The wear detection component 124 can compare data from the sensor, such as the position of measured points on the surface of the measured worn part 116 with the model(s) 126 of the part. In some embodiments, data processing system(s) 120 may match sensor data representing measured wear part 116, such as points generated by sensor 110, to one or more part models 126 to determine deviations between measured points and positions or positions. on the model(s) of the part 126. In one example, the degree of wear can be expressed as a percentage corresponding to the ratio of the first deviation between the position on the model of the new part and the measured position (for example, on the worn part 116) and the collinear second deviation between the position on the model of the new part and position on the model of the used part.

In accordance with embodiments of the present invention, the component 128 to determine the bounding surface can generate, receive, or otherwise access the bounding surface or bounding contour. As detailed below, the bounding surface or contour may be a model, similar to the part model(s) 126 used by component 124 to determine wear. In examples, the boundary surface determination component 128 may generate or select a boundary surface, model, or contour that at least partially covers an area, for example, larger than the part model(s) 126 and/or the measured worn part 116. As described herein, the bounding surface defined by the bounding surface determination component 128 may form orientations along which deviations are measured to determine wear. By way of example, and not limitation, the bounding loop can serve as an additional model that can be matched by the wear component 124 with the part model(s) 126 and the measured points of the worn part 116 (or the worn part model 116 based on the measured points). In some embodiments, lines that are perpendicular to the bounding surface can serve as directions along which deviations can be measured, such as deviations between a measured point and one or more points on the part model(s) 126 . Thus, the bounding surface can serve to orient the measurement directions. In accordance with the embodiments described herein, the orientation of the directions can thus give more accurate results compared to conventional models. For example, some conventional models are capable of measuring the distance between the measured point and the nearest point on the part model. However, such methods can lead to inaccurate wear calculations, which can lead to overuse of parts, such as breakage, and/or underutilization of parts, thereby increasing costs.

Depending on the configuration of the peripheral equipment 100, the data processing system(s) 120 may have different tasks or different degrees of involvement in the implementation of the disclosed methods. In embodiments, for example, peripheral equipment 100 may be configured as a server environment or cloud environment that performs the disclosed wear detection methods as part of a service of network(s) 118. In such a server or cloud environment, data processing system(s) 120 (e.g., , server, or cloud) may receive data from sensor 110 and/or from user device 108 (which may receive data from sensor 110). In this example, the data processing system(s) 120 may then process the data from the sensors to determine the degree of wear of the parts and return the processing results to the user device 108 over the network(s) 118. Thus, in a server or cloud environment, the system(s) 120 for data processing may perform the bulk of the computing steps, while the user's device 108 may function as a portal (for example, through an application or browser) that provides the user 106 with access to the services of the system (s) 120 for data processing over the network (s). ) 118. In some examples, as detailed below, the user device 108 may, for example, download a software application that will allow the user 106 to access the system(s) 120 to process data and/or work with data received from the system(s). ) 120 for data processing.

The peripheral equipment 100 also includes a dealer computing device(s) 122, which may be one or more computing systems connected to the equipment of the dealer who sells or leases the machine 104 and/or parts for the machine 104, including a new part. 114. In some embodiments, the dealer may interact with the user 106. For example, the user 106 may be a customer or potential customer and/or some other person interested in knowing the condition of the machine 104. In some embodiments, the dealer needs to know when a wear part of machine 104, such as the tooth shown, wears out enough to require it to inspect or service machine 104 and/or provide spare parts or services for machine 104. Like other items of peripheral equipment 100, the computing device(s) 122 dealer may contain any number or combination of computing elements that provide communication, storage and processing to perform the disclosed methods. Among other things, the computing device (s) 122 of the dealer may include a device 130 for processing orders, which is capable of automatically ordering a spare part, for example, a new part 114, and / or ordering a scheduled maintenance of the machine 104, in response to determining system (em) 120 for processing data that the wear part is worn to a certain threshold value. In some examples, at least the dealer computing device(s) 122 may also include data processing system(s) 120. For example, the dealer computing device(s) 122 may perform centralized service monitoring capable of detecting wear on parts and also taking some action in response to such wear detection, including providing spare parts. In some examples, at least the dealer computing device(s) 122 may receive notifications, such as emails or text messages, from other peripheral equipment components, such as the data processing system(s) 120 and/or 108 of the user, indicating that the wear part of the machine is sufficiently worn, for example, that the wear rate meets or exceeds the threshold wear rate. In response to such notifications, the dealer computing device(s) 122 may, for example, using the order processing device 130, select a suitable spare part and arrange for the delivery of the spare part to the user 106 in the work area 102. In other embodiments, the implementation of the computing The dealer device(s) 122 may send other instructions to the user device 108, such as instructing the user on actions to take in response to a certain degree of wear. Such instructions may be for the user 106 to provide the machine 104 for inspection, maintenance, or the like. and/or arranged for a consultation with a dealer technician in the work area 102 of the machine. The dealer computing device(s) 122 may also prompt the user, such as by a message or other means of communicating information to the user device 108, to order a replacement part.

On fig. 1, network(s) 118 is represented, which may be any combination of electronic communications networks capable of transmitting data between nodes connected to network(s) 118. For example, without limitation, network(s) 118 may be the Internet, Ethernet , local area network, wide area network, personal area network, cellular network, telephone network, or any combination thereof. In some embodiments, at least network(s) 118 may be a mobile network and associated infrastructure for connecting user device 108 to the Internet, such as a 2G, 3G, 4G, 5G, and/or LTE communications network.

On fig. 2 are textual and graphical flowcharts that describe and illustrate the methods of the present invention. In particular, in Fig. 2 is a description and drawings of a method 200 for determining the degree of wear for a wear part, such as wear part 116, shown enlarged 112 and shown in FIG. 1. For example, the method 200 described and illustrated in FIG. 2 may be wholly or partially implemented by components of peripheral equipment 100 comprising user device 108, sensor 110, and/or data processing system(s) 120 depicted in FIG. 1. However, the methods shown in fig. 2 are not limited to using these components, and these components are not limited to using the methods described and illustrated in FIG. 2.

At 202, method 200 includes receiving data from a sensor for a wear part. Thus, in the example of the peripheral equipment 100 described above, shown in Fig. 1, the user 106 may use the sensor 110 to generate sensor data indicative of a wear part, such as the wear part 116. As shown in the example 204 corresponding to step 202, the sensor data may indicate the surface 206 of the part, such as the wear part 116. For clarity, the worn part 116 is shown in profile, i. as a two-dimensional representation of the worn part 116. However, although it is shown in a two-dimensional coordinate system, the methods described in connection with fig. 2 are equally applicable to alternative coordinate systems, including, but not limited to, three-dimensional coordinate systems. It will be appreciated by one skilled in the art that data from a sensor, such as that received by sensor 110, may be a plurality of measurement points, of which first measurement point 208a, second measurement point 208b, third measurement point 208c, fourth measurement point 208d, and fifth measurement point 208e (together referred to as "measured points 208") are shown in example 204. In the examples, measured points 208 may be a point cloud or other set of layer thickness or position measurements generated by sensor 110. Although additional surfaces due to worn part 116 are also shown in example 204 , it will be appreciated by those skilled in the art that part sensor data may only include measured points 208 describing surface 206. Additional surfaces are shown in example 204 for reference and to illustrate the contour of worn part 116. By way of example, and not limitation, one would expect that surfaces opposite the measured surface 206, such as the seating surfaces of the wear part 116, will experience minimal wear and therefore will not be read by the sensor in the embodiments described herein.

At 210, method 200 includes obtaining one or more part models. For example, part models can be a new part model, a worn part model, or a part model with maximum wear. The new part model may be due to a new or unused part, such as a new part 114. The worn part model or the maximum allowable wear part model may correspond to the minimum allowable surface due to the worn part 114. In example 212 of step 210, the new part model 214 and the model 216 parts with maximum allowable wear. As with example 204, the new part model 214 and the maximum wear model 216 are shown as a two-dimensional model for clarity. However, it should be understood, in embodiments of the present invention, that the new part model 214 and the maximum wear part model 216 can be performed as three-dimensional models. Each new part model 214 and the maximum wear part model 216 typically describe surfaces or surface contours caused by the same part but at different parts useful life periods. For example, a new part model 214 typically corresponds to a completely new part or part within specification. For example, surfaces driven by or defined by a new part model can be derived from datasheets and/or renderings of the part. In contrast, the maximum wear part model 216 typically describes the contours of the corresponding worn part. In embodiments, the maximum wear model 216 may describe a used or completely worn part, such as describing the contour or surface of a part that is expected to fail in the near future. In other embodiments, the model 216 of the maximum wear part may correspond to some other contour with some other degree of wear of the original part. By way of example, and not limitation, a model 216 of a wearable part may be made by a user 106 or another person servicing machine 104 to create a contour that corresponds to the end of the useful life of the part. In a simplified example, a new part model 214 may correspond to a spare part from an individual spare parts kit, while a maximum wear part model 216 may correspond to a part that is expected to fail soon and therefore needs to be replaced immediately. In some examples, a new part model 214 may conform to manufacturing specifications or a description of a new part within a specification, such as a new part 114. In contrast, a maximum wear part model 216 may correspond to a contour where each point on a surface in contact with ground, e.g. on the outside, must not be subjected to further wear.

At 218, method 200 may include creating a constraint model. As detailed below, embodiments of the present invention allow the use of a constraint model to determine orientations and/or directions along which wear can be measured. In example 220 of step 218, a number of representative limiting models are schematically depicted. More specifically, example 220 represents a first constraint model 222a, a second constraint model 220b, and a third constraint model 222c. Collectively, the first constraint model 222a, the second constraint model 222b, and the third constraint model 222c are referred to here as constraint models 222. Typically, constraint models 222 are surfaces that at least partially enclose the part models, such as the new part model 214 and the maximum wear model 216; and the measured surface 206 of the worn part 116. In embodiments, the bounding surfaces 222 depend on the type of part being measured, expected wear marks due to the part being measured, and/or other factors.

At 224, method 200 includes determining wear by comparing part data with models of the part using a constraint model. Example 226 of step 224 shows how to determine the degree of wear using the received data, part model(s), and constraint models. As shown in example 226, step 224 may include aligning the new part model 214, the maximum wear part model 216, the surface 206 of the worn part 116, and the bounding model 222. For example, such alignment can be performed using a common model element, such as a mounting holes, mounting surface, etc. Example 226 uses the first constraint model 222a, and Example 226 specifically demonstrates determining the amount of wear caused by the third measured point 208c on the surface 206. As described above, the third measured point 208c has a known layer thickness, i. measured by the sensor 110, and the layer thickness due to the third measured point 208c located in the coordinate system. Positions including position 228 along new part model 214, positions including position 230 on maximum wear part model 216, and positions including position 232 on bounding model 222a may also be defined in the coordinate system. In example 226, line 234 extends from position 232 on limiting model 222a to position 230 on the maximum wear model. In this example, line 234 is perpendicular or at right angles to bounding model 222a at position 232.

In some examples, the degree of wear due to the third measured point 208c may be based, at least in part, on deviations between the third measured point 208c and one or both positions 228 on the model 214 of the new part and/or position 230 on the model 216 of the part with the maximum allowable wear. Thus, in example 226, the first deviation d1 is shown as the deviation between position 228 on the model 214 of the new part and the measured point 208c, and the second deviation d2 is shown as the deviation between the measured point 208c and position 230 on the model 216 of the part with the maximum allowable wear. In embodiments, the degree of wear due to the third measured point 208c may be the ratio of the first deviation d1 to the total deviation d1 plus d2. This ratio may correspond to the percentage wear of the part, since it is the ratio of the worn material (at the third measured point 208c) to the total material. It is obvious to the specialist, since the sum of d1 and d2 is constant, and the model 214 of the new part and the model 216 of the part with the maximum allowable wear are constant models with a predetermined level, then with a relatively smaller d1, the percentage of wear will be relatively smaller, i.e. a smaller part of the part will be worn out, and with a relatively large d1, the percentage of wear will be relatively higher, i.e. most of the part will be worn out. Other indicators of the degree of wear are also considered. For example, in other embodiments, the ratio of d2 to the sum of d1 and d2 may be the percentage of detail (at measured point 208c) that remains intact. In additional embodiments, the degree of wear may be another quantification due to (or determined by) deviations d1, d2. For example, the proportion of the remaining (or worn) part may be due to the time of continuous use of the part. For example, the life of a wear part can be measured in hours, and the percentage of the life of the part remaining (for example, the ratio of d2 to d1 plus d2) can be expressed in terms of the number of hours of expected use of the part 116 remaining. Although the examples described herein may consider the ratio as a way to determine the degree of wear, but other methods can also be used. For example, empirical data related to certain wear parts may provide information about wear characteristics or other wear marks, and one or both of the deviations d1, d2 may be used to determine a wear percentage or other indicator of wear based on such empirical data. Although some of the examples shown in Fig. 2, both the new part model 214 and the maximum wear part model 216 are used, however, in other embodiments, only one of these models may be used. By way of example, and not limitation, the wear rate can be defined as the deviation from the measured point to one new point 228 or to the maximum allowable wear point 230. For example, when the deviation from the new point 228 to the maximum allowable wear point 230 is known, then the wear percentage can be determined using only one of the values of d1 or d2.

In example 226, the orientation of line 234 is based on the characteristics of bounding model 222a. Thus, in some examples, line 234 is at right angles to constraint model 222a at point 232. In embodiments, the constraint model may be selected based on expected wear marks on the part. By way of example, and not limitation, constraint model 222 may be selected to orient lines, such as line 234, to best reflect part wear, as described later herein.

On fig. 3 shows an additional example of determining the degree of wear, similar to example 226 step 224. In particular, in fig. 3 shows an alignment simulation 300 of a measured wear part surface 302: relative to a new part model 304, which may be a new part model 214; with respect to the maximum wear part model 306, which may be the maximum wear part model 216; and with respect to the constraining model 308. As already noted, the simulation 300 is very similar to the simulation in the example 226 shown in Fig. 2. However, during simulation 300, constraint model 308 may have a different profile. In some examples, constraint model 308 may be similar to third constraint model 222c as in example 220 shown in FIG. 2. As shown in fig. 2, in fig. 3, the part is shown in two dimensions for clarity and ease of explanation, but in some embodiments, each of the measured surfaces 302, new part model 304, maximum wear part model 306, and/or constraint model 308 may be three dimensional.

As additionally shown in Fig. 3, the first measured point 310a, the second measured point 310b, the third measured point 310c, and the fourth measured point 310d (collectively measured points 310) are exemplary points on the measured surface 302. The measured points 310 may correspond to data from the sensor 110 detecting the worn part 116 and/or may correspond to points on the model surface generated from sensor data. The deviation between each of the measured points 310 and the corresponding point on the outer surface of the maximum wear part model 306 may represent the remaining layer thickness of the used part (eg, worn part 116) in the vicinity of the measured point. For example, in fig. 3 also shows the first maximum wear point 312a, the second maximum wear point 312b, the third maximum wear point 312c, and the fourth maximum wear point 312d (together the maximum wear points 312) corresponding to the measured points 310. .As also shown in fig. 3, the deviation between each of the measured points 310 and the corresponding point on the outer surface of the model 304 of the new maximum wear part may represent the proportion of material that has been abraded, broken, worn, or otherwise removed from the new part. For example, in fig. 3 also shows the first new point 314a, the second new point 314b, the third new point 314c, and the fourth new point 314d (collectively new points 314) corresponding to the measured points 310. Of course, the measured points 310, the maximum wear points 312, and the new points 314 are for example only. In embodiments, each measured point 310 will have a corresponding maximum wear point 312 and a corresponding new point 314, where the associated measured points 310, maximum wear points 312, and new points 314 lie on a straight line, as described herein.

As also described herein, the correspondence of the points is determined at least in part based on the constraint model 308. In particular, the constraint model 308 may provide information about the orientation of the lines passing through the measured points 310, which in turn determine the points 312 with the maximum allowable wear and new points 314, which should be taken into account when determining the degree of wear. In the example, the first limit point 316a, the second limit point 316b, the third limit point 316c, and the fourth limit point 316d (collectively the limit points 316) are shown on the limit model 308. The first line 318a extends from the first limit point 316a through the first measured point 310a, the second line 318b extends from the second limit point 316b through the second measured point 310b, the third line 318c extends from the third limit point 316c through the third measured point 310c, and the fourth line 318d extends from the fourth limit point 318d through the fourth measured point 310d. Collectively, the first line 318a, the second line 318b, the third line 318c, and the fourth line 318d may be referred to as lines 318. In the example shown, each of the lines 318 extends at right angles to the bounding surface defined by the bounding model 308. In some examples, by the methods described herein, positions (e.g., point positions) along lines 318 can be determined and those positions compared to measured points 310 to determine whether measured points 310 correspond to limit points 316. Maximum wear points 312 and new points 314 can be determined similarly in as a result of identifying points on the model 306 with maximum allowable wear and the new model 304 parts that lie on lines 318, respectively. Although in this example, each of the lines 318 is perpendicular or at right angles to the bounding model 308, however, in other embodiments, the lines 318 may be oriented differently. By way of example, and without limitation, the lines 318 may be inclined at some angle relative to the bounding surface, defined by the bounding model 308, other than 90 degrees.

As noted here, the constraint model 308 may orient each of the lines 318 to more accurately estimate part wear. For example, some methods may use models, such as a new part model 304 and/or a maximum wear model 306, to determine the amount of wear, however, such models are only able to calculate wear deviation (e.g., the deviation from one of the measured points 302 to points on the new part model 304) as the deviation between the corresponding one of the measured points 310 and the nearest point on the new part model 308. Consider, for example, the third measured point 310c. As shown in fig. 3, the wear deviation may be a deviation between the third point 314c on the new part model 304, such as along the third line 318c. However, in examples that do not use the constraint model 308, the measured point is closer to some other points on the new part model 304 than to the third new point 314c. By way of example, and not limitation, the third measured point 310c is closer to the second new point 314b than to the third new point 314c. Other methods that use the "nearest" point to determine wear will give a much lower wear value than the present methods that use constraint model 308 to orient the direction of line 318c and thus determine a third new point 314c and a third point 312c with a maximum allowable wear as wear measuring points.

In addition, a different result may be obtained by identifying the profile and/or contour of the constraint model 308. For some examples, it is desirable that any line at right angles to the limiting model pass through each of the measured surfaces 302, the new model 304, and the maximum wear model 306. To this end, the limiting pattern 308 may have substantially the same profile as the maximum wear pattern 306. Of course, and as discussed here, other contemplated profiles may be used, including hemispheres and/or other concave profiles.

As shown above in fig. 2, the wear rate of the part may be based on deviations along the lines 318. Thus, in the example shown, the wear rate for the first measured point 310a may be based at least in part on one or more deviations between the first measured point 310a and the first new point 314a, between the first measured point 310a and the first maximum wear point 312a and/or between the first new point 314a and the first maximum wear point 312a. For example, in fig. 3 is a wear rate table 320 that visually displays the wear rates or values due to each of the measured points. In the table, the degree of wear is quantified as a percentage of wear (% wear), which can be the number (in percent) of the (1)th ratio of deviation from one of the measured points 310 to the corresponding one of the new points 316 to the (2)th deviation from the corresponding one of the new points 316 to the corresponding one of the points 312 with the maximum allowable wear. Using the first measured point 310a as an example, the deviation from the first measured point to the first new point 314a may be about 55% of the deviation from the first new point 314a to the first maximum wear point 312a. Thus, as shown in table 320, the wear rate due to the first measured point 310a may be 55%. Similarly, the wear at the second measured point 310b can be quantified at about 65% (i.e., the deviation between the second measured point 310b and the second new point 314b is about 65% of the deviation from the second new point 314b to the second maximum allowable wear point 312b) , wear at the third measured point 310c can be quantified at about 85% (for example, as the deviation between the third measured point 310c and the third new point 314c is about 85% of the deviation from the third new point 314c to the third point 312c with the maximum allowable wear), and wear at the fourth measured point can be quantified at about 45% (for example, as the deviation between the fourth measured point 310d and the fourth new point 314d is about 45% of the deviation from the fourth new point 314d to the fourth point 312d with the maximum allowable wear) . The four measured points 310 are for illustration only, and the wear table 320 may contain any number of points, including additional and/or other points on the measured surface 302. Moreover, although referred to herein as "measured points", in some In examples, points can be any points on the measured surface 302 measured directly, extrapolated, or otherwise derived from sensor data.

In addition, although wear rate table 320 shows wear as a percentage of wear, table 320 may include additional or alternative indicators. For example, the reciprocal of the percentage shown is "percentage remaining" or the like. In other examples, wear rate table 320 may contain values other than percentages. By way of example, and not limitation, the degree of wear can be expressed as the thickness (e.g., in millimeters, centimeters, inches, etc.) of the material removed (e.g., the length due to the deviation from the individual measured points 310 to the corresponding one of the new points 314) or remaining material (for example, the length due to the deviation from the individual measured points 310 to the corresponding one of the points 312 with maximum allowable wear). In some instances, metrics other than percent wear may be of particular interest and/or more intuitive to some machine drivers and/or technicians. For example, the wear rate table 320 shows a relatively wide range of wear percentages, such as 45% to 85%, while the thickness of the material at each of the measured points 310 (eg, measured on the maximum allowable wear model 306) is relatively uniform. In other words, using a specific point in Fig. 3, the deviation from the third measured point 310c to the third maximum allowable wear point 312c is very close to the deviation between the fourth measured point 312d and the fourth maximum allowable wear point 312d, despite the wear percentage being 85% and 45%, respectively. In this example, the wear along the third line 318c is faster than the wear along the fourth line 318d, causing a discrepancy in percentage wear. However, the technician may be more interested in knowing the thickness of the remaining material rather than the percentages. In other additional examples, the wear rate table 320, in accordance with another embodiment, may also contain the estimated life of the part. For example, a wear part may have an estimated part life, which is measured in hours. In some embodiments, the wear percentage may correspond to the remaining life of the part. For example, suppose that the life of the part in question is 100 hours. In this example, the 85 percent wear due to the third measured point 310c may indicate that there are 15 hours left before the part needs to be replaced. In other examples, the remaining life may be otherwise determined on a point basis. For example, empirical studies of wear parts can be used to develop a lookup table or other database that relates the life of a part, such as the remaining life of the part, to one or more parameters: deviation, remaining thickness of the part, and/or wear percentage, for example, as determined by the methods shown in Fig. 3. Such calculations may also take into account conditions, including, but not limited to, the task being performed, material composition or other conditions that cause wear, metrics associated with the user 106 (for example, when the user is the driver of the machine 104), or other information that affects the wear of the part. .

The methods described herein may include providing information about wear, in accordance with the embodiments described in accordance with Fig. 2 and/or fig. 3 to a user, such as user 106. As an example, but not limited to, data processing system(s) 120 may send signals, such as including information on wear rate(s), to user device 108 to provide information to user 106. about wear parts of the machine 104. For example, in fig. 4 shows a wear part status data display system 400 . The data display system 400 is shown as a user device 108, for example, to be viewed by the user 106. The data display system 400 may have one or more user interface elements that allow the user 106 to provide or control information about the status of wear parts, such as a worn part 116, such as a tooth. earthwork tools. The data display system 400 may include a part identification window 402 displaying the part in question, such as being analyzed. In the example, the part identification window 402 contains both a visual representation of the part, such as a digital image of a new part (which may be a new part 114) corresponding to the measured part (a worn part 116), and a textual description of the part, such as the text "bucket tooth". ". In other examples, the part identification window 402 may contain alternative or additional information. For example, without limitation, the part identification window 402 may also contain the part identification number and the identification number of the machine 104 to which the part belongs, the location of the part in the machine 104, and/or additional information.

The data display system 400 may further include a wear image 404, which may be a visual image of the measured part, such as corresponding to sensor data, generated by the sensor 110, together with wear information determined by the system(s) 120 to process the data as described. ways here. In an example, the wear image 404 is a color-coded heat map or similar image, typically showing the amount of wear. More specifically, the wear image contains a series of dots 406 that are color coded to show wear. In particular, dots 406 due to more worn parts are represented as relatively darker dots in the wear image 404, while dots 406 due to less worn parts are represented as relatively lighter dots. Although the image is shown in black and white, other color coding schemes may be used in other embodiments. By way of example and not limitation, the wear image 404 may use shades of red to indicate points 406 due to wear greater than 65%, shades of green to indicate points 406 having less than 35% wear, and shades of yellow to indicate points 406 due to wear. ranging from 35% to 65%. Of course, these colors and values are provided by way of example only, other colors and/or values may also be used. Moreover, the dots 406 may be of a relatively smaller size, such as a pixel size, and/or may be in some other graphical representation. In some examples, each of the points 406 may correspond to one point or measured points 208, 310, although this is not required. Typically, the wear image 404 may be an intuitive graphic that allows the user 106 to easily determine the condition of the part being measured.

The data display system 400 may also contain additional information to help the user 106 determine the status of the part being measured. As shown in fig. 4, the data display system 400 may also contain a status bar 408 that displays information about the part. In the figure, status line 408 shows the remaining part life (36 hours in the example), total part wear (62%), and maximum part wear (85%). In embodiments, the data display system 400 may contain additional or different information than that shown in the status line 408. By way of example, and not limitation, the data display system 400 may include information about other wear indicators described herein. In addition, and although not shown in Fig. 4, the data display system 400 may have interactive features that allow the user 106 to collect additional information about the part being measured. By way of example, and not limitation, the user 106 can select points on the wear image 404 and obtain information about those particular points. For example, the data display system 400 may display a pop-up window that includes wear information for a selected one of the dots 406 or area of dots.

In addition, the data display system 400 may further have interactive controls for performing or instructing an action to be performed on the part being measured. For example, the "replacement order" user interface element 410 may be a selectable area in the display system 400 that, when selected by the user 106, orders a replacement part. For example, user device 108 may generate and transmit a signal to dealer computing device(s) 122 to order a replacement part from the dealer. In some examples, selecting a user interface element for ordering a part may open a new user interface (not shown) through which the user 106 can place an order, check inventory, and/or perform some additional action. The data display system 400 may also include a new part analysis user interface element 412 . This element may be a selectable area displayed in the data display system 400, which, when selected by the user 106, may display a similar interface to the data display system 400, but related to a different measured part. For example, when a machine, such as machine 104, contains multiple teeth, the user 106 can obtain information about the different teeth upon selecting item 412. As an example, but not limited to, selecting item 412 results in a pop-up menu or similar visual list of wear parts, which can be analyzed by the user 106. Although not shown, the data display system 400 is capable of stimulating or allowing the user 106 to perform various actions on the wear parts. For example, in cases where the sensor 110 is integrated into or associated with the user device 108, the display system 400 may facilitate the collection of data from the sensor using the sensor 110. In addition, as noted above, in some embodiments, the functions provided by the component 124 for wear determinations may be performed by the user device 108. In these examples, the display system 400 may include one or more user interface elements that cause the user device 108 to follow instructions to determine the amount of wear caused by a wear part.

On fig. 5 is a block diagram of an exemplary system 500 for quantifying part wear, in accordance with the embodiments described herein. In at least one example, system 500 may include one or more remote computing devices 502 that communicate over one or more networks 504 with a user device 508 that can communicate with a user 506. In some examples, the remote computing device(s) The device(s) 502 may be the system(s) 120 for data processing. User device 508 may be, for example, user device 108, and user 506 may be user 106. By way of example and not limitation, user device 508 may be tablet computing devices, desktop computing devices, portable computing devices, mobile computing device or any other device capable of accessing and displaying graphical user interfaces and communicating with remote computing device(s) 502. Network(s) 504 may be a local area network (LAN), a wide area network (WAN), including, without limitation, the Internet, or any combination thereof, and may use both wired and wireless communication technologies using any suitable communication protocols and methods.

The remote computing device(s) 502 may include a processor(s) 510 and a storage device 512 coupled to the processor(s) 510. In the example shown, the storage device 512 of the remote computing device(s) ) 502 stores a wear detection system 514, a graphical user interface (GUI) generation system 516, and a constraint model generation system 518. Although these systems are shown and will be described below as separate components, however, the functionality of various systems may be different than discussed. In addition, fewer or more systems and components may be used to perform the various functions described herein. The storage device 512 may also contain data arrays 520 with models 522. Although in Fig. 5, they are shown as being in memory 512 for illustrative purposes, however, it is contemplated that wear detection system 514, GUI generation system 516, constraint model generation system 518, and/or any or all datasets 520 may additionally or alternatively be available. for the remote computing device(s) 502 (eg, stored or otherwise available to a remote storage device on the remote computing device(s) 502).

In at least one example, the wear detection system 514 may include a function to determine the amount of wear caused by a wear part, such as a worn part 116. For example, the wear detection system 514 may be substantially the same as the wear detection component 124 described above. wear. In examples, the wear detection system 514 may receive data from a sensor of the measured part, compare the data from the sensor with one or more models 522 stored in the data array 520. For example, models 522 may represent a new part model and a worn part model. In embodiments, the model of the worn part may correspond to the part with the maximum allowable wear.

In some examples, the GUI generation system 516 may include functionality for creating one or more interactive interfaces, such as a GUI 400 for presentation on a user's device 508. In some examples, GUI generation system 516 may receive information from wear detection system 514 and/or GUI generation models 522. As an example, but not limited to, as shown in Fig. 4, GUI generation system 516 may receive wear amount information from wear determination system 514 and details of the new part model from models 522 to generate representation 404 and image 402, respectively.

The constraint model generation system 518 may have the functionality to define a constraint model, structure, or contour that can be used as a reference for determining wear, as described herein. In the examples, the system for generating the bounding model may be the same as the component 128 for determining the bounding surface. For example, the constraining model generation system 518 is able to determine the constraining structure based on the part in question and/or other factors. As detailed herein, a bounding model can be used as a reference contour that guides the measurements used to determine wear. In some examples, constraint model generation system 518 may retrieve a constraint model from memory, such as one of the models 522. In other examples, constraint model generation system 518 may determine a constraint model using a model, such as a model of a maximum wearable part.

The remote computing device(s) 502 may also comprise a communication connection(s) 524 that provides communication between the remote computing device(s) 502 and another local or remote ) device(s), including, but not limited to, dealer computing device(s) 122. ) 504. Communication connections 524 may provide Wi-Fi based communications, such as frequencies defined by the IEEE 802.11 standards, short range wireless communications frequencies such as BLUETOOTH ^® , other radio frequencies, or frequencies of any suitable wired or wireless communication protocol that allows corresponding computing device to interact with another computing device(s).

In some embodiments, remote computing device(s) 502 may send information, such as instructions for creating a GUI, to user device 508 via network(s) 504. User device(s) 508 is capable of receiving such information from remote computing(s) device(s) 502 and display the GUI on the display 528 of the device 508 of the user. In some embodiments, the user device 508 may perform some of the functions attributed to the remote computing device(s) 502, including, for example, creating a GUI. To facilitate GUI creation, user device 508 may receive information from remote computing device(s) 502. In one example, at least user device 508 may include one or more processors 530 and a storage device 532 connected to processor(s) 530. In the example shown, memory 532 of user device 508 may store a component 534 for determining wear and/or contain arrays 536 of data. In the examples, wear component 534 may be substantially the same as wear determination system 514, and data arrays 536 may include some or all of the same information stored in data array 520.

The user device 508 may also include a communication connection(s) 538 that provides communication between the user device 508 and other local or remote device(s). For example, communication connection(s) 538 can enhance communications with remote computing device(s) 502, such as over network(s) 504. Communication connection(s) 538 can provide Wi-Fi based communication, such as frequencies defined by the IEEE 802.11 standards, short range wireless communications frequencies such as BLUETOOTH ^® , other radio frequencies, or frequencies of any suitable wired or wireless communication protocol that allows the respective computing device to communicate with other computing device(s).

As also shown in fig. 5, user device 508 may include a sensor 526. For example, sensor 526 may be similar to sensor 110, and may be integrated with user device 508 or otherwise coupled to user device 508. In examples, sensor 526 may be an imaging device configured to receive data from a 3D sensor indicative of a worn part, as described herein. The sensor 526 may be a distance sensor, such as a radar sensor, a LiDAR sensor, a transit time sensor, and the like. In other examples, sensor 526 may be a 3D camera.

The processor(s) 510 of the remote computing device(s) 502 and the processor(s) 530 of the user device 508 may be any suitable processor capable of executing data processing instructions and performing operations as described herein. By way of example and without limitation, processor(s) 510, 530 may include one or more central processing units (CPUs), graphics processing units (GPUs), or any other device or part of a device that processes electronic data to convert that electronic data into other electronic data. data that may be stored in registers and/or memory. In some examples, integrated circuits (eg, ASICs, etc.), gate arrays (eg, FPGAs, etc.), and other hardware devices may also be considered processors because they execute coded instructions.

Memory 512 and memory 532 are examples of non-volatile computer-readable media. The storage device 512, 532 may store an operating system and one or more software applications, commands, programs, and/or data for performing the methods and functions described herein belonging to various systems. In various embodiments, the memory may be implemented in any suitable technology, such as static random access memory (SRAM), synchronous dynamic random access memory (SDRAM), nonvolatile electrically reprogrammable read only memory, or any other type of memory. capable of storing information. The architectures, systems, and individual elements described in this document may contain many other logical, software, and physical components, and some that are shown in the accompanying figures are merely examples relevant to the discussion in this document.

Although various systems and components are shown as discrete systems, the drawings are examples only and more or less discrete systems may only perform the various functions described in this document. In addition, functionality assigned to remote computing device(s) 502 may be executed on user device 508 and/or functionality assigned to user device 508 may be executed by remote computing device(s) 502.

On fig. 6 and 7 are flow charts depicting exemplary processes 600, 700 of the present disclosure that may be associated with part wear detection as described herein. The exemplary processes 600, 700 (as well as the process 200 shown in Figure 2 and discussed above) are a set of steps in a logical flow diagram, where the steps are actions or operations that can be implemented in hardware, software, or their combinations. In the context of software, steps are computer-executable instructions stored in a memory device. During the execution of such instructions, for example, by the processor(s) 510, 530, their implementation may cause the processor(s) 510, 530 and/or various components of the computing device(s) 502 and/or user device 508 to perform the listed actions or operations. . Typically, computer-executable instructions include routines, subroutines, objects, components, data structures, and the like that perform certain functions or implement certain abstract data types. The order in which the operations are described should not be construed as a limitation, and any number of described blocks may be combined in any order and/or in parallel to implement the processes. In some embodiments, one or more process blocks may be omitted entirely. Moreover, processes 600, 700 may be combined in whole or in part with other methods.

On fig. 6 shows in greater detail an example process 600 for determining wear on a wear part, such as wear part 116, which may belong to a machine, such as machine 104. Process 600 may be performed by data processing system(s) 120, remote computing device(s) 502, and/or user devices 108, 508, although other components may perform some or all of the steps in process 600. In addition, the steps in process 600 need not be performed in the order shown in FIG. 6, but may be performed in a different order in accordance with the disclosed embodiments.

At 602, method 600 includes receiving data from a sensor for a wear part. For example, data processing system(s) 120 may receive sensor data generated by wear part sensor 110, such as wear part 116 used in machine 104. For example, user 106 is prompted to capture certain types of wear part 116 using sensor 110. In As an example, without limitation, the sensor 110 may be mounted on a stand or other frame that is designed to accommodate the sensor 110 relative to the worn part 116. In some examples, at least the data from the sensor may be point cloud data containing a plurality of points and a thickness layer, due to points (for example, the thickness of the layer relative to the sensor 110). In examples, sensor 110 may be a distance sensor, such as a transit time sensor, a LiDAR sensor, a radar sensor, a 3D scanner, and the like.

At 604, method 600 includes deriving models of a non-worn part and/or a part with maximum allowable wear. For example, the data processing system(s) 120 may retrieve, access, or otherwise obtain information, such as one or more part models, that describe or otherwise be conditional on the worn part 116. In some examples, the part models may be a new part model, eg, new part models 214, 304, which may be a new part 114. Such a new part model may have the coordinates or surface dimensions of a new, eg, largely unused part. In the examples, a new model of a part is described with nominal dimensions or "as per specification" dimensions. The part models may also, or alternatively, contain a maximum wear part model, such as maximum wear part models 216, 306. Such models of the maximum wear part may have the coordinates or dimensions of the surface of the part worn to the maximum allowable wear, which may be a predetermined maximum allowable wear. In the examples, the maximum allowable wear may correspond to the amount of wear that causes the inevitable failure of the part, or some other maximum allowable wear. In at least some examples, the maximum allowable wear can be determined empirically.

At 606, process 600 may comprise defining a bounding box or a bounding model that encloses models. For example, data processing system(s) 120 may retrieve, access, generate, or otherwise determine a constraint model, such as constraint models 222, 308. As described herein, a constraint model may define an orientation or direction along which the wear components 124, 514, 534 to determine wear. In the examples, the constraint model may be any model, typically with a convex shape, structure, or surface that at least partially encloses the measured points and surfaces defined by the model(s) obtained in step 604. In some cases, the constraint model may practically coincide with the profile of the part model with the maximum allowable wear, but be slightly larger.

At 608, process 600 may suppress the determination of wear for individual points in the sensor data. For example, step 608 may comprise aligning the measured points (or a model representing the measured points or other data from a sensor), the model(s), and a bounding box in a coordinate system, such as a 3D coordinate system, and measuring the deviation between the models along lines oriented according to the limiting model. For example, for each of the measured points 208, 310 determine the deviation from this point to one or both points on the new model, for example, one of the new points 228, 314 and/or points on the model with the maximum allowable wear, for example, one of the points 230 , 312 with maximum allowable wear. Such deviations are measured along lines 234, 318 that are oriented in accordance with the constraint model 222, 308. In at least some examples, the lines 234, 318 may be lines perpendicular to the constraint model and passing through the measured points 208, 310, as described in this document. The degree of wear can be further determined, at least in part, based on these deviations. So in the example in Fig. 3, the wear rate may be a percentage of wear, which may be the ratio of the first deviation (from the measured point to the new point) and the second deviation (from the new point to the corresponding point with the maximum allowable wear, where the new point, the measured point and the point with the maximum allowable wear lie on the same straight line).

At step 610, the process 600 may determine whether the degree of wear due to individual measured points meets or exceeds the maximum allowable wear. For example, at 610, outliers may be removed. By way of example, and not limitation, points in sensor data may be due to surrounding components or objects in the environment of the wear part under test, and such actions may result in wear rates exceeding a predetermined threshold, such as greater than 100%. However, there may be a need to save all points that show wear percentage up to and including a value greater than 100%. In some cases, a part of the worn part may be worn beyond the maximum allowable wear, for example, when the maximum allowable wear corresponds to the surface coordinates of the wear part, which suggest replacement of the part, but may not be due to part failure. Similarly, data due to positions of mounting holes, mounting members, features not expected to wear, or other holes that may be calculated as having excessive wear may be filtered at 610.

For example, if at block 610 it is determined that an individual point meets or exceeds a wear threshold, then block 612 may include ignoring the point. As noted above, points having exceptionally high wear rates, such as greater than or equal to 125% in some examples, may be considered anomalous and thus may be excluded from further consideration.

In addition, if at step 610 it is determined that the degree of wear does not meet or exceed the threshold value, then step 600 may include step 614 of creating an image of the part with wear indicators at each point. That is, the measured points that are not filtered out at step 610 can be used to identify wear caused by the part by the user 106 . On fig. 4, an exemplary wear part image 404 is shown that visualizes point-by-point wear on the wear part, such as in a heat map.

At block 616 of block 600, a graphical user interface containing an image can be connected. For example, the data processing system(s) 120 may generate a graphical user interface similar to the graphical user interface 400 and send information that allows the user device 108 to render the graphical user interface 400 on its display. In examples, interface 400 may display additional information about the wear part, including one or more additional wear indicators, information about the wear part, such as type or model, instructions and/or controls for ordering spare parts, or other information.

On fig. 7 shows an exemplary step 700 of replacing a wear part, for example, when the wear part or part of the wear part indicates that the part is worn and/or may fail. In some examples, step 700 may be performed by one or more components of peripheral equipment 100, while other components may perform some or all of the steps of step 700. The steps of step 700 may optionally be performed in the order shown in FIG. 7, however, they may be performed in a different order in accordance with the disclosed embodiments.

At block 702, block 700 comprises determining the degree of wear for the wear part. For example, step 702 may include all or parts of steps 200, 600 described herein. In embodiments, the wear rate may represent the wear rate for each point, for example, for a single one of several measured points, or may be a single indicator due to the entire part. By way of example, and not limitation, a wear index describing a part as a whole may be an average or weighted average of all or a subset of all wear indexes at each point. In at least one example, a wear index for a part may be an average of some given number (eg, top 30) or a percentage (eg, top 10% of all points) of certain wear indexes. In other examples, the wear rate of the part may be the maximum calculated wear rate over the measured points. Other indicators are also the subject of discussion in this document and will be evaluated by experts in the art, taking into account the advantages of this disclosure.

At block 704, block 700 may comprise determining whether the amount of wear meets or exceeds a wear threshold. For example, an operator, foreman, administrator, manufacturer, technician, or other person associated with a wear part or a machine using the wear part is able to determine that parts having wear above a given threshold, such as above 85%, 90%, 95% etc. wear, must be replaced. Thus, at step 704, it can be determined whether the wear rate determined at step 702 is at or above this threshold.

If at step 704 it is determined that the degree of wear does not meet or exceed the threshold value, then step 700 returns to step 702 to continue determining the degree of wear of the part. In particular, in this case, the part can still be used.

In contrast, if it is determined at step 704 that the wear rate meets or exceeds a wear threshold, then step 706 of step 700 may include ordering a replacement part. For example, data processing system(s) 120 and/or user device 108 may send a signal or other information to dealer computing device(s) 122 and instruct dealer computing device(s) 122 to ship a replacement part. and/or schedule maintenance to install a new spare part. In other cases, the dealer computing device(s) 122 may obtain wear information and determine that the wear part should be replaced. In some examples, the wear threshold may be determined, at least in part, based on the period of time required to obtain a replacement wear part. For example, when a spare wear part is stored in a location near the manufacturing site where the machine is operating, the wear rate of that part may reach a relatively higher level, for example, because it can be immediately replaced if it breaks down. In addition, if spare parts are not available at the manufacturing site, then the wear threshold may be relatively lower, for example, to allow additional time to obtain a spare part.

At block 708, block 700 may comprise replacing a wear part. For example, a technician or other person may be scheduled to visit to replace a wear part with a replacement part ordered at 706. As described herein, maintaining machines with wear parts that are not excessively worn can improve machine efficiency and productivity.

Although not explicitly shown in Fig. 7, however, the methods described herein may perform one or more additional or alternative actions based on whether the wear rate meets or exceeds the threshold (eg, at 704), including any combination, for example:

Signaling to change the indicator light at the operator's station of the machine 104 from green (continue operation) to red (stop operation), so that the operator knows that the wear part is about to fail. The operator can then manually control the machine 104 to stop ongoing earthworks using the part and/or take action to investigate the cause of the wear and/or replace the worn part.

Sending signals to the user device 108 indicating that a wear part needs to be replaced. The user device 108, in turn, can display visual information on the display (eg, the message "Stop using"), for example, through the interface 400, informing the operator that the wear part may fail in the near future. The operator can then manually control the machine 104 to stop ongoing earthworks using the part and/or take some other action.

Signaling to a module in the machine 104 indicating that a wear part is at risk of imminent failure and/or needs to be replaced. The machine module, in turn, can signal vehicle components to stop machine 104 or otherwise limit additional wear on a wear part.

Signaling to the speed control module that a wear part needs to be replaced. In response to the signal(s), the speed control module may limit the use of machine 104 by: reducing the speed of machine 104; stopping the machine 104; decrease in throttle opening; or the engine speed of the machine or the like.

Signaling to an autonomous control module associated with the machine 104 indicating that a wear part needs to be replaced. In response to the signals, the autonomous control module may, for example, change the current mode of operation of the machine 104 or perform other functions to reduce or prevent additional wear.

Industrial Applicability

The disclosed systems and methods find application to any peripheral equipment with which the user wishes to determine the degree of wear of a wear part. By using a sensor to collect data from a wear part sensor, such as the thickness of a layer of dots on the surface of the wear part and determine the wear rate from the data from the sensor, the disclosed systems and methods allow a user to easily evaluate a part even without detailed knowledge of the part, part wear rate, characteristics. or cars.

For example, as shown in fig. 1, user 106 may operate machine 104 in work area 102. After the end of a shift, or after some other period of time, user 106 may stop machine 104 and use sensor 110 to collect sensor data about a worn part 116, such as a tooth on a bucket. machine 104. User 106 can then, using mobile device 108 connected to sensor 110, transmit data from the sensor to a remote computing system, such as data processing system(s) 120. The data system(s) 120 may then determine the wear rate of the measured points from one or more part models 126 using the bounding surface 222. In more detail, the data system(s) 120 may use the component 124 to determine wear by determining deviations between measured points on the measured part and the corresponding positions on the model 214 of the new part and/or the model 216 of the worn part or the part with the maximum allowable wear. These measured deviations are located along a line oriented in accordance with the bounding surface 222. In at least some embodiments, the line runs perpendicular to the bounding surface. In embodiments, if it is determined that the amount of wear due to the measured part indicates that the part is due for replacement, then the data processing system(s) 120 is able to signal the need to the dealer computing device(s) 122 such that may be carried out in several stages, for example, ordering a new part 114, for example, using the device 130 for processing orders.

The methods described herein can improve the efficiency of work sites, such as in work area 102, and/or increase the productivity of machines, such as machine 104. By way of example, and not limitation, the methods described herein can provide proper maintenance and/or replacement of wear parts resulting in more efficient use of the machine 104, including, but not limited to, reduced fuel consumption and/or wear of other ancillary parts. For example, if teeth like those shown in enlarged view 112 in Fig. 1 are not replaced, but instead allow them to fail, the bucket to which the teeth are attached will be subject to wear or otherwise break. In this embodiment, replacing or repairing the bucket is much more costly, both financially and in terms of machine downtime, than routinely replacing a worn part 116 with a new part 114. In addition, using parts that are not too worn or used will help keep the job going. faster than with worn, broken and/or missing parts.

It will be apparent to those skilled in the art to which this invention relates that computer programs for carrying out the disclosed methods may be stored in and/or read from computer-readable storage media. The computer-readable storage medium may store computer-executable instructions that, when executed by a processor, cause the computer to perform, among other things, the methods disclosed herein. Typical computer-readable storage media can be: magnetic storage devices such as a hard disk, floppy disk, magnetic tape, or other magnetic storage device known in the art; optical storage devices such as CD-ROM, DVD-ROM or other optical storage devices known in the art; and/or electronic storage devices such as E PROM, flash drive, or other integrated circuit storage device known in the art. The computer-readable storage medium may be implemented as one or more components of peripheral equipment 100.

Those skilled in the art will appreciate that various modifications and changes can be made to the disclosed wear parts management system without departing from the spirit and scope of the present invention. Other embodiments of the invention will be apparent to those skilled in the art upon consideration of the description and practice of using the disclosed embodiments. It is intended that the description and examples be regarded as illustrative only, and that the true scope of the invention is indicated in the following claims and their equivalents.

Claims (50)

1. A computerized method for determining the degree of wear of a part, including: receiving data from the sensor corresponding to the surface (206) of the part (116) in the working area of the part; the data from the sensor contains information about the plurality of image points (208, 310) on the surface (206) obtained by the imaging sensor; obtaining a first model (214) conditioned by a non-worn part corresponding to the part (116); the first model (214) defines the first contour of the unworn part; obtaining a second model (216), due to the part with the maximum allowable wear corresponding to the part (116); the second model (216), defines the second contour of the part with the maximum allowable wear; creation of a bounding contour (222) spaced from the surface (206), the first contour and the second contour, while the bounding contour (222) is the surfaces that, at least partially, cover the first model (214) and the second model (216) , as well as the measured surface (206) of the part (116); determination for a point (208c) located on the measured surface 206 of the part 116 in the working area of the part, from a plurality of points (208, 310), at least: the first deviation (d1) between the point (208c) and the first position (228) in the working area of the part on the first contour of the first model (214); or a second deviation (d2) between the point (208c) and the second position (230) in the working area of the part on the second contour of the second model (216); And determination based on at least one first deviation (d1) or second deviation (d2) of the degree of wear caused by the part (116), while the first deviation (d1) and the second deviation (d2) are located along the line passing from the bounding contour (222) and through the point (208c). 2. Computerized method according to claim. 1, characterized in that the point (208c) is the first point, and the degree of wear is the first degree of wear due to the first point (208c); computerized method, further comprising: determination for the second point (310b) from the set of points (208, 310), at least: the third deviation between the second point (310b) and the third position (314b) on the first circuit, or a fourth deviation between the second point (310b) and the fourth position (312b) on the second contour, wherein the third deviation and the fourth deviation are along the second line extending from the bounding contour (308) through the second point (310b); And determination of the second degree of wear due to the second point (310b). 3. The computerized method of claim 2, further comprising determining an overall wear rate for the part (116) based at least in part on the first wear rate and the second wear rate. 4. Computerized method according to claim 3, characterized in that the overall wear rate is one of the average values determined using the first wear rate and the second wear rate, or the maximum value of the first wear rate or the second wear rate. 5. The computerized method of claim 2, further comprising: determining the overall wear rate of the part without using the second wear rate based at least in part on a second wear rate that meets or exceeds a threshold wear rate. 6. Computerized method according to claim 1, characterized in that the line (234) is perpendicular to the bounding contour (222). 7. Computerized method according to claim 1, characterized in that the boundary contour (222) has a first profile and the first contour has a second profile different from the first profile. 8. The computerized method of claim 1, further comprising: alignment of the surface representation (206) of the part (116), the first contour and the second contour in the coordinate system; And creating a bounding contour (222) to at least partially cover the surface, the first contour and the second contour in the coordinate system, in which the first deviation (d1) and the second deviation (d2) are deviations in the coordinate system. 9. The computerized method of claim 1, further comprising: generating visual data due to a graphical representation (404) of the part (116) and a visual representation (408) of the degree of wear; And creating a graphical representation (404) of the part and a visual representation (408) on the display (108) for display. 10. Computerized method according to claim 1, characterized in that: the first contour, at least in part, is based on the first three-dimensional model of the unworn part; the second contour is based at least in part on a second 3D model of the maximum wear part, and bounding contour (222) is a three-dimensional contour. 11. Computerized method according to claim 1, characterized in that the degree of wear is expressed as a percentage of wear, including the ratio of at least one first deviation (d1) or second deviation (d2) to a third deviation between the first position on the first circuit and the second position on the second circuit. 12. A system for determining the degree of wear of a part, comprising: one or more processors (510); And a computer-readable medium (512) that stores instructions whose execution causes one or more processors (510) to perform actions, including: obtaining information about the state of the surface of the part (116), while the information is a set of image points describing the surface of the part (116) in the working area, received by the imaging sensor; generating, at least in part, based on the information, a first model (206) of the part (116); comparison of the first model (206) with: a second model (214) containing information about the surface of a non-worn part corresponding to the part (116), the third model (216), containing information about the surface of the part with the maximum allowable wear corresponding to the part (116), and a fourth pattern (222) defined by a bounding surface at least partially enclosing the first pattern (206), the second pattern (214), and the third pattern (216); And determination based on a comparison of the degree of wear caused by a given part. 13. The system according to claim 12, characterized in that the comparison includes: determining for the set of points (208) on the surface of the part (116), at least one first deviation (d1) between the corresponding point from the set of points (208) and the surface of the unworn part along the direction from the limiting surface and through the corresponding point or the second deviation ( d2) between the corresponding point and the surface of the worn part along the direction, wherein the degree of wear is at least partially based on the first deviation (d1) or the second deviation (d2). 14. The system according to claim. 13, characterized in that the degree of wear is a percentage of wear based at least in part on the ratio of at least the first deviation (d1) or the second deviation (d2) to the third deviation, which represents is the sum of the first deviation (d1) and the second deviation (d2). 15. The system according to claim 12, the actions of which additionally include: generating visual data due to a graphical representation (404) of the part (116) and a visual representation (408) of the degree of wear; And creating a graphical representation (404) of the part and a visual representation (408) on the display (108) for display.