Life evaluation method of roller rails for intelligent sliding doors

Abstract

The present application discloses a roller rail life assessment method for smart sliding door, which relates to the field of data processing technology. The roller rail life assessment method for smart sliding door includes: obtaining usage data of smart sliding door; based on the usage data, obtaining multiple segmented data; based on each segmented data, obtaining the wear characteristic value of the smart sliding door; based on the wear characteristic value, obtaining the friction power increase trend value of the smart sliding door; based on the friction power increase trend value, obtaining the service life of the smart sliding door. The present application introduces the characteristic value of environmental factors, and based on the usage data of smart sliding door, performs segmentation and feature extraction on the usage data. Then, the wear characteristic value of the smart sliding door in the usage data is analyzed. According to the relationship between the wear characteristic value and the cause of friction, the friction power increase trend value of the smart sliding door is further evaluated, so that the evaluation result is more accurate.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and specifically to a method for evaluating the life of a roller slide rail for an intelligent slide rail door. Background Art

[0002] In modern society, smart home products are becoming increasingly popular. As an important part of smart home products, smart sliding doors are widely welcomed for their convenience, quietness, and space saving. Due to the long-term repeated loads and complex environment, the rollers and rails of smart sliding doors are prone to wear and fatigue damage, which in turn affects the performance and life of the entire door. Therefore, accurate evaluation of the life of rollers and rails is of great significance to ensure the safe operation of smart sliding doors and reduce maintenance costs.

[0003] Since the lifespan of smart sliding doors varies greatly in different usage environments, usage habits and usage frequencies, the traditional unified evaluation standards conducted under laboratory conditions are difficult to accurately reflect the lifespan performance of smart sliding doors in actual use. Summary of the invention

[0004] The purpose of the present application is to provide a roller rail life assessment method for smart sliding door, so as to solve the technical problem that it is difficult to accurately assess the service life of smart sliding door in actual environment.

[0005] To achieve the above objectives, this application provides the following technical solutions: A roller slide rail life assessment method for an intelligent slide rail door, comprising: Acquire usage data of the smart sliding door; the usage data at least includes the motor power of the smart sliding door; Based on the usage data, a plurality of segmented data are obtained; each segmented data includes a pushing process of the intelligent sliding door, and each pushing process includes a starting acceleration phase, a uniform speed phase, and a deceleration phase of the intelligent sliding door; Based on each segmented data, acquiring a wear characteristic value of the intelligent sliding door; Based on the wear characteristic value, a friction power increase trend value of the smart sliding door is obtained; the friction power increase trend value is at least used to characterize the magnitude of the change in friction force of the smart sliding door caused by the wear of the roller and the sliding rail; Based on the friction power increase trend value, the service life of the intelligent sliding door is obtained.

[0006] As a specific solution in the technical solution of the present application, the wear characteristic value of the intelligent sliding door is obtained based on each segmented data, including: Based on the first segmented data, a slide rail wear characteristic value is obtained; the first segmented data is any one of the segmented data; the slide rail wear characteristic value is at least used to characterize the influence of the slide rail wear on the friction power characteristics of the intelligent slide rail door; Based on the first segmented data, an environmental factor characteristic value is obtained; the environmental factor characteristic value is at least used to characterize the influence of dust on the friction power characteristics of the intelligent sliding door; Based on the first segmented data, a roller wear characteristic value is obtained; the roller wear characteristic value is at least used to characterize the influence of roller wear on the friction power characteristics of the intelligent sliding door; Based on the slide rail wear characteristic value, the environmental factor characteristic value and the roller wear characteristic value, the wear characteristic value of the intelligent slide rail door is obtained.

[0007] As a specific solution in the technical solution of the present application, the step of obtaining the rail wear characteristic value based on the first segmented data includes: Based on the first segmented data, a first mean, a second mean and a third mean are obtained; the first mean is the mean of the motor power in the startup acceleration stage in the first segmented data; the second mean is the mean of the motor power in the uniform speed stage in the first segmented data; the third mean is the mean of the motor power in the deceleration stage in the first segmented data; Based on the first mean, the second mean and the third mean, a first integral area, a second integral area and a third integral area are obtained; the first integral area is the area of ​​the area formed by the motor power curve in the startup acceleration stage and the straight line with the motor power equal to the first mean; the second integral area is the area of ​​the area formed by the motor power curve in the uniform speed stage and the straight line with the motor power equal to the second mean; the third integral area is the area of ​​the area formed by the motor power curve in the deceleration stage and the straight line with the motor power equal to the third mean; The slide rail wear characteristic value is acquired based on the first integrated area, the second integrated area, and the third integrated area.

[0008] As a specific solution in the technical solution of the present application, obtaining the rail wear characteristic value based on the first integral area, the second integral area and the third integral area includes: A first sequence and a second sequence are constructed based on each segmented data in time sequence; the first sequence is the sum of the first integral area, the second integral area and the third integral area corresponding to each segmented data; the second sequence is the motor power corresponding to the startup acceleration stage, the uniform speed stage and the deceleration stage of each segmented data; Based on the Pearson correlation coefficient, obtaining a correlation value between the first sequence and the second sequence; The correlation degree value is used as the slide rail wear characteristic value.

[0009] As a specific solution in the technical solution of the present application, the step of obtaining the characteristic value of the environmental factor based on the first segmented data includes: Based on the first segmented data, a first difference is obtained; the first difference is the difference between the motor power consumed in the entire process of the first segmented data and the motor power consumed in the previous adjacent segmented data; Based on the first segmented data, a fourth mean is obtained; the fourth mean is an average value of motor power differences in a startup acceleration phase of each adjacent segmented data whose timing is before the first segmented data; Based on the first difference and the fourth mean, the environmental factor characteristic value is obtained; the environmental factor characteristic value is equal to the ratio of the fourth mean to the first difference.

[0010] As a specific solution in the technical solution of the present application, the method of obtaining the friction power increase trend value of the intelligent sliding door based on the wear characteristic value includes: Based on the current segmented data, a second difference; the second difference is the difference between the motor power corresponding to the current segmented data and the motor power corresponding to the second segmented data of the smart sliding door under dust-free conditions; the number of push-pull times corresponding to the second segmented data is the same as the number of push-pull times corresponding to the current segmented data; Obtain a first power growth value and a second power growth value through the second difference by using the least square method; the first power growth value is the growth value of the motor power caused by the environmental factors caused by unit dust deposition; the second power growth value is the growth value of the motor power caused by the roller and slide rail factors caused by unit dust deposition; Based on the first power increase value and the second power increase value, the friction power increase trend value of the intelligent sliding door is obtained.

[0011] As a specific solution in the technical solution of the present application, the calculation formula for obtaining the first power increase value and the second power increase value by using the least squares method through the second difference is as follows: in, represents the second difference value corresponding to the lth segmentation data; Indicates the friction power value of the roller and the slide rail corresponding to the l-1th segmentation data; represents the ratio of the rail wear characteristic value to the roller wear characteristic value in the lth segmented data; F represents the second power growth value; represents the environmental factor characteristic value corresponding to the l-1th segmentation data; Indicates the first power increase value.

[0012] As a specific solution in the technical solution of the present application, the calculation formula for obtaining the friction power increase trend value of the intelligent sliding door based on the first power increase value and the second power increase value is as follows: in, Indicates the friction power increase trend value corresponding to the i-th segmentation data; represents the second difference corresponding to the i-1th segmentation data; Represents the characteristic value of the environmental factor corresponding to the i-th segmentation data; It represents the sum of the rail wear characteristic value and roller wear characteristic value corresponding to the i-th segmentation data.

[0013] As a specific solution in the technical solution of the present application, the service life of the intelligent sliding door is obtained based on the friction power increase trend value, including: Based on the usage data, obtaining the current usage count and current usage duration of the smart sliding door; Based on the friction power increase trend value and the power threshold, obtaining a usage times threshold; the power threshold is obtained in advance; Based on the usage count threshold, the current usage count and the current usage duration, the service life of the smart sliding door is obtained.

[0014] As a specific solution in the technical solution of the present application, based on the usage count threshold, the current usage count and the current usage duration, the calculation formula for obtaining the service life of the smart sliding door is as follows: in, Indicates the remaining usage time of the smart sliding door; Indicates the usage count threshold; Indicates the current number of times used; Indicates the current usage time.

[0015] Compared with the prior art, the beneficial effects of this application are: This application introduces the characteristic values ​​of environmental factors and segments and extracts features from the usage data based on the usage data of the smart sliding door. Then the wear characteristic values ​​of the smart sliding door in the usage data are analyzed. According to the relationship between the wear characteristic values ​​and the causes of friction, the friction power increase trend value of the smart sliding door is further evaluated, and the subsequent friction power of the smart sliding door is adjusted accordingly. When the predicted friction power reaches the power threshold, it is considered that the smart sliding door has reached its service life. This method can evaluate the service life of the smart sliding door based on its usage in the actual environment, making the evaluation result more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic flow chart of a roller rail life assessment method for a smart sliding door proposed in an embodiment of the present application; Figure 2 A schematic diagram of the motor power and time during a certain pushing process of an intelligent sliding door proposed in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0018] The terms "first", "second", etc. in the specification of the embodiment of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence, such as the first sequence and the second sequence proposed below, which belong to different sequences. It should be understood that the sequences used in this way can be interchanged where appropriate, so that the embodiments described here can be implemented in an order other than the content illustrated or described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device including a series of steps or modules need not be limited to those steps or modules clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. The division of the modules that appear in the embodiment of the present application is only a logical division. There may be other division methods when implemented in practical applications, such as multiple modules can be combined or integrated into another system, or some features can be ignored, or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, and the indirect coupling or communication connection between modules can be electrical or other similar forms, which are not limited in the embodiment of the present application. Furthermore, the modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed in multiple circuit modules, and some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiment of the present application.

[0019] In order to solve the technical problem that it is difficult to accurately evaluate the service life of the smart sliding door in the actual environment proposed in the background technology, the present application proposes a roller rail life evaluation method for the smart sliding door, including steps S100 to S500, as shown in FIG. Figure 1As shown, this figure is a flow chart of the roller slide rail life assessment method for intelligent sliding door.

[0020] Step S100: Obtain usage data of the smart sliding door.

[0021] In this embodiment, the usage data includes at least the motor power of the smart sliding door. It should be noted that the smart sliding door generally adopts a magnetic levitation track control system, and its structure is mainly composed of a built-in motor, a slide rail and a roller. The motor system and the transmission system are integrated inside the track. During its operation, the built-in motor drives the roller to move on the slide rail, thereby realizing the intelligent opening and closing of the smart sliding door. The motor power, the operating position of the smart sliding door and the operating speed of the smart sliding door during the motor driving process are collected by the motor system itself, which is a mature technology and will not be described here.

[0022] Step S200: Based on the usage data, a plurality of segmented data are obtained.

[0023] In this embodiment, each segmented data includes a pushing process of the intelligent sliding door. Figure 2 The figure is a schematic diagram of the motor power and time during a certain push process of the smart sliding door. The smart sliding door includes three stages in each push process, which are the start-up acceleration stage (i.e. Figure 2 Stage 1 as shown), uniform speed stage (i.e. Figure 2 Phase 2 as shown) and the deceleration phase (i.e. Figure 2 Stage three shown). In each stage of the sliding of the intelligent sliding door, the working power of its motor (i.e., motor power) needs to resist the friction force under various circumstances in addition to providing acceleration. During the entire working time, if there is no friction resistance, the working power of the motor can be considered to act directly on the intelligent sliding door. Therefore, the remaining monitoring data under the force on the intelligent sliding door is removed according to the monitored intelligent sliding door speed data, which is the current friction resistance consumption power. In this embodiment, the power consumption in the uniform speed stage is defined as the current rated resistance, and the power in the startup acceleration stage is removed from the current rated resistance, and its power can be recorded as the corresponding power size of the corresponding speed change. The ratio of the remaining power after removing the rated resistance power in the startup acceleration stage to the acceleration is recorded as the rated power size under the unit acceleration of the current intelligent sliding door. For each speed and time correspondence obtained during the monitoring process, the speed change power at that place can be obtained according to the acceleration size per unit time and the rated power under the unit acceleration of the current intelligent sliding door. According to the monitored power-time correspondence, the speed change power is removed to obtain the power value consumed by the friction resistance in a single test process.

[0024] Step S300: Based on each segmented data, the wear characteristic value of the intelligent sliding door is obtained.

[0025] It should be noted that when analyzing the power consumed by the friction resistance of the smart sliding door, the friction loss of the smart sliding door mainly exists in: friction loss caused by the wear of the roller itself, friction loss caused by the wear of the slide rail itself, and friction loss caused by environmental factors (dust). These factors will have different degrees of loss growth in different usage environments. At the same time, the above-mentioned friction loss will be in different power fluctuations in the monitored data, which makes it more difficult to evaluate the life of the current smart sliding door based on the power consumed by the friction resistance. In order to clearly identify the friction loss caused by the wear of the roller itself and the friction loss caused by the wear of the slide rail itself in each segmented data, in an embodiment of the present application, step S300, based on each segmented data, obtains the wear characteristic value of the smart sliding door, including steps S310 to S340.

[0026] Step S310: based on the first segmented data, obtaining the rail wear characteristic value.

[0027] In this embodiment, the first segmented data is any segmented data among the segmented data. That is to say, the rail wear characteristic value, environmental factor characteristic value and roller wear characteristic value in each segmented data in this embodiment can be obtained by referring to the acquisition method of the first segmented data. In this embodiment, the rail wear characteristic value is at least used to characterize the influence of the rail wear on the friction power characteristics of the intelligent rail door.

[0028] It should be noted that the wear of the contact surface of the slide rail is mainly affected by the number of times the smart slide rail door is used and the operating speed of the smart slide rail door. As the number of uses increases, the contact surface between the overall slide rail of the smart slide rail door and the roller gradually wears. At the same time, during a single wear process, changes in speed will cause different areas of the slide rail to be subjected to different pressure concentrations, which in turn causes local wear on the contact surface. For the first segmented data, the power data in each stage (i.e., the startup acceleration stage, the uniform speed stage, and the deceleration stage, etc.) can be subtracted from the mean to obtain power data with a power greater than 0. The continuous protruding part in the data is the wear area of ​​the corresponding slide rail. Based on this, step S310, based on the first segmented data, obtains the slide rail wear characteristic value, including steps S311 to S313.

[0029] Step S311: based on the first segmented data, obtain a first mean, a second mean and a third mean.

[0030] In this embodiment, the first mean value is the mean value of the motor power in the startup acceleration phase in the first segmented data. The second mean value is the mean value of the motor power in the uniform speed phase in the first segmented data. The third mean value is the mean value of the motor power in the deceleration phase in the first segmented data. Based on a certain curve segment, obtaining the average value corresponding to the curve segment is a mature technology and will not be described in detail here.

[0031] Step S312: Based on the first mean value, the second mean value and the third mean value, obtain a first integrated area, a second integrated area and a third integrated area.

[0032] In this embodiment, the first integral area is the area of ​​the area formed by the motor power curve in the startup acceleration stage and the straight line with the motor power equal to the first mean. The second integral area is the area of ​​the area formed by the motor power curve in the uniform speed stage and the straight line with the motor power equal to the second mean. The third integral area is the area of ​​the area formed by the motor power curve in the deceleration stage and the straight line with the motor power equal to the third mean. Based on a certain curve and a certain straight line, using integration to obtain the area between the curve and the straight line is a mature technology and will not be described in detail here.

[0033] Step S313: acquiring the rail wear characteristic value based on the first integrated area, the second integrated area and the third integrated area.

[0034] It should be noted that if the wear of the slide rail is more serious, the area corresponding to the first integral area, the second integral area or the third integral area will be larger. Based on this, in this embodiment, the sum of the first integral area, the second integral area and the third integral area can be used as the characteristic value of the slide rail wear.

[0035] In order to obtain a rail wear characteristic value that can accurately characterize the degree of rail wear, in one embodiment of the present application, step S313, based on the first integral area, the second integral area and the third integral area, obtains the rail wear characteristic value, including steps S314 to S316.

[0036] Step S314: constructing a first sequence and a second sequence based on each segmented data in time sequence.

[0037] In this embodiment, the first sequence is the sum of the first integral area, the second integral area and the third integral area corresponding to each segmented data. The second sequence is the motor power corresponding to the startup acceleration stage, the uniform speed stage and the deceleration stage of each segmented data. It should be noted that when the wear degree of the slide rail increases faster during the wear process of the slide rail, the more serious the wear of the rail is, that is, the greater the ratio of the corresponding values ​​in the first sequence and the second sequence.

[0038] Step S315: Based on the Pearson correlation coefficient, obtain the correlation value between the first sequence and the second sequence.

[0039] It is easy to understand that with the long-term use of the smart sliding door, the wear of the sliding rail increases. If the wear of the sliding rail increases, the ratio of the corresponding values ​​in the first sequence and the second sequence gradually increases, and the corresponding correlation value can be obtained based on the Pearson correlation coefficient.

[0040] Step S316: using the correlation value as the rail wear characteristic value.

[0041] In this embodiment, the slide rail wear characteristic value can characterize the wear degree of the slide rail, that is, it can characterize the influence of the slide rail wear on the friction power characteristic of the intelligent slide rail door.

[0042] Step S320: Acquire characteristic values ​​of environmental factors based on the first segmented data.

[0043] In this embodiment, the environmental factor characteristic value is at least used to characterize the effect of dust on the friction power characteristics of the smart sliding door. During long-term use, the friction between the roller and the rail of the smart sliding door increases due to the adsorption and deposition of dust or oil on the rail. It is easy to understand that if the dust or oil is adsorbed and deposited for a short time during the continuous use of the rail, the effect on the friction of the rail is small. Therefore, the environmental factor characteristic value can be obtained in a fixed-length time interval. Specifically, step S320, based on the first segmented data, obtains the environmental factor characteristic value, including steps S321 to S323.

[0044] Step S321: obtaining a first difference based on the first segmented data.

[0045] In this embodiment, the first difference is the difference between the motor power consumed in the entire process of the first segmented data and the motor power consumed in the adjacent previous segmented data. It should be noted that the increased power consumption each time the smart sliding door is pushed can be considered to be caused by the wear factor of the sliding rail, the environmental factor and the roller wear factor. In other words, the increased first difference is caused by these three factors together.

[0046] Step S322: Based on the first segmented data, obtain a fourth mean.

[0047] In this embodiment, the fourth mean is the average of the motor power differences in the startup acceleration phase of each adjacent segmented data whose timing is before the first segmented data. It should be noted that if there is interference from environmental factors, such as the deposition of dust or oil, a greater startup power is required when the roller is started. In other words, the fourth mean can be considered as an increase in power consumption caused by environmental factors.

[0048] Step S323: Based on the first difference and the fourth mean, obtain the characteristic value of the environmental factor.

[0049] In this embodiment, the environmental factor characteristic value is equal to the ratio of the fourth mean value to the first difference value. In this embodiment, in order to avoid the first difference value being zero, which in turn causes the ratio of the fourth mean value to the first difference value to be abnormal (that is, the denominator is zero), the calculation formula of the environmental factor characteristic value may also be as follows: D=C / (|B|+A) Wherein, D represents the characteristic value of the environmental factor; C represents the fourth mean; B represents the first difference; A represents a constant, which is any positive number greater than 0; | | represents finding the absolute value.

[0050] Step S330: obtaining roller wear characteristic values ​​based on the first segmented data.

[0051] In this embodiment, the roller wear characteristic value is at least used to characterize the effect of roller wear on the friction power characteristic of the smart sliding door. As can be seen from the foregoing, each time the smart sliding door is pushed, the increased power consumption is caused by the rail wear factor, environmental factors and roller wear factors. Therefore, in this embodiment, the roller wear characteristic value = 1 - rail wear characteristic value - environmental factor characteristic value.

[0052] Step S340: Based on the slide rail wear characteristic value, the environmental factor characteristic value and the roller wear characteristic value, the wear characteristic value of the intelligent slide rail door is obtained.

[0053] In this embodiment, the rail wear characteristic value, the environmental factor characteristic value and the roller wear characteristic value are the wear characteristic values ​​of the smart rail door. It is easy to understand that when considering the service life of the smart rail door, the influence of the rail wear factor and the roller wear factor should be considered, while the influence of the environmental factor should be ignored.

[0054] Step S400: Based on the wear characteristic value, the friction power increase trend value of the intelligent sliding door is obtained.

[0055] In this embodiment, the friction power increase trend value is at least used to characterize the magnitude of the change in friction force of the smart sliding door caused by the wear of the rollers and rails. In an embodiment of the present application, the sum of the rail wear characteristic value and the roller wear characteristic value can be used as the friction power increase trend value of the smart sliding door. In order to obtain the friction power increase trend value that accurately characterizes the magnitude of the change in friction force of the smart sliding door caused by the wear of the rollers and rails, in one embodiment of the present application, step S400, based on the wear characteristic value, obtains the friction power increase trend value of the smart sliding door, including steps S410 to S430.

[0056] Step S410: based on the current segmented data, a second difference.

[0057] In this embodiment, the second difference is the difference between the motor power corresponding to the current segmentation data and the motor power corresponding to the second segmentation data of the smart sliding door under dust-free conditions. The push and pull times corresponding to the second segmentation data are the same as the push and pull times corresponding to the current segmentation data.

[0058] It should be noted that in the life cycle of the smart sliding door, compared with the experimental simulation environment (that is, dust-free conditions), the actual operating habits of users and changes in the environment are mainly introduced, and this change will directly lead to a large difference in the wear growth rate of the smart sliding door in the current use environment and in the experimental environment. It can be foreseen that: the slide rails and rollers have a direct effect during use, and the degree of wear between them will directly affect each other. The dust deposition brought by the environment will directly affect the slide rails and rollers, thereby increasing the friction between the rollers and the slide rails. That is, compared with the smart sliding door used in dust-free conditions, the motor power increases more rapidly due to roller wear and slide rail wear.

[0059] In this embodiment, the second difference is the part that increases the surface friction between the slide rail and the roller due to the influence of environmental dust deposition, thereby increasing the motor power. Dust deposition increases the friction between the roller and the slide rail surface during relative motion, thereby increasing the degree of wear, and the difference in surface friction between the roller and the slide rail is also caused by uneven dust deposition during the motion process.

[0060] Step S420: Obtain a first power increase value and a second power increase value by using the second difference value through the least square method.

[0061] In this embodiment, the first power increase value is the increase value of the motor power caused by the environmental factors caused by unit dust deposition; the second power increase value is the increase value of the motor power caused by the roller and rail factors caused by unit dust deposition. In this embodiment, step S420, the calculation formula for obtaining the first power increase value and the second power increase value by the least square method through the second difference is as follows: in, represents the second difference value corresponding to the lth segmentation data; Indicates the friction power value of the roller and the slide rail corresponding to the l-1th segmentation data; represents the ratio of the rail wear characteristic value to the roller wear characteristic value in the lth segmented data; F represents the second power growth value; represents the environmental factor characteristic value corresponding to the l-1th segmentation data; Indicates the first power increase value.

[0062] In this embodiment, the first power increase value T and the second power increase value F can be calculated based on the least square method through the above formula.

[0063] Step S430: Based on the first power growth value and the second power growth value, the friction power increase trend value of the intelligent sliding door is obtained.

[0064] It should be clear that the ratio of the rail wear characteristic value to the roller wear characteristic value in the segmented data will gradually approach 1 as the friction increases. Based on this, step S430 obtains the friction power increase trend value of the smart rail door based on the first power increase value and the second power increase value. The specific calculation formula is as follows: in, Indicates the friction power increase trend value corresponding to the i-th segmentation data; represents the second difference corresponding to the i-1th segmentation data; Represents the characteristic value of the environmental factor corresponding to the i-th segmentation data; It represents the sum of the rail wear characteristic value and roller wear characteristic value corresponding to the i-th segmentation data.

[0065] Step S500: Based on the friction power increase trend value, the service life of the intelligent sliding door is obtained.

[0066] It should be clear that as the use time increases, the remaining service life of the smart sliding door decreases. In this embodiment, step S500, based on the friction power increase trend value, obtains the service life of the smart sliding door, including steps S510 to S530.

[0067] Step S510: Based on the usage data, obtain the current usage count and current usage duration of the smart sliding door.

[0068] It should be clear that reading the current usage count and current usage duration of the smart sliding door from the usage receipt is a mature technology and will not be elaborated here.

[0069] Step S520: Based on the friction power increase trend value and the power threshold, a usage times threshold is obtained.

[0070] In this embodiment, the power threshold is obtained in advance. It should be clear that after the intelligent sliding door reaches its service life (that is, the roller and / or active sliding rail are completely damaged), the motor power exceeds a certain threshold and the movement of the intelligent sliding door cannot be achieved. In this embodiment, we define the motor power of the intelligent sliding door after reaching its service life as the power threshold. In this embodiment, when analyzing the service life of the intelligent sliding door, it is first necessary to determine in what state the current intelligent sliding door can be considered to have reached the use limit, that is, reached its service life. The degree of wear of the mechanical parts of the intelligent sliding door (especially the roller and the sliding rail) is the core factor in evaluating its life. When such parts reach the wear threshold, the intelligent sliding door will have problems such as stuck and unable to slide, that is, the motor power reaches the power threshold. Based on this, in order to obtain an accurate power threshold, the intelligent sliding door can be continuously used in a standard laboratory environment (dust-free), and the drive motor can be replaced in time during the test according to the cumulative number of uses and the motor temperature to ensure that the motor use during the test meets the actual use environment. When stuck or sliding cannot be achieved during the sliding process, it means that the upper limit of use has been reached. The motor operating power and operating speed at each operating position are monitored during each sliding process. During the experiment of the intelligent sliding door, the rollers and the slide rails in its structure are constantly rubbing against each other, which increases the friction resistance between the rollers and the slide rails and destroys the structure of the contact surfaces. When the friction resistance between the rollers and the slide rails continues to increase, in the corresponding monitoring data, the motor at the same position needs to use more power to make it move. The average power in a single monitoring process is used as the vertical coordinate, and the number of experiments is used as the horizontal coordinate to construct the two-dimensional experimental monitoring data, and the maximum operating power in the monitoring process is used as the power threshold.

[0071] As can be seen from the foregoing, when the smart sliding door reaches the power threshold during long-term use, its service life is reached. In this embodiment, since the friction power increase trend value and the current motor power are obtained, it can be calculated based on how many times the motor power of the smart sliding door can reach the power threshold after pushing and pulling. In other words, if the power threshold and the friction power increase trend value can be obtained, the use times threshold of the smart sliding door can be calculated, which will not be elaborated here.

[0072] Step S530: Based on the usage count threshold, the current usage count and the current usage duration, the service life of the smart sliding door is obtained.

[0073] In the embodiment of the present application, any reasonable method can be used to obtain the service life of the smart sliding door based on the usage count threshold, the current usage count and the current usage duration. For example: In step S530, based on the usage count threshold, the current usage count and the current usage duration, the calculation formula for obtaining the service life of the smart sliding door is as follows: in, Indicates the remaining usage time of the smart sliding door; Indicates the usage count threshold; Indicates the current number of times used; Indicates the current usage time.

[0074] In this embodiment, the smart sliding door can be monitored in real time through the user's usage behavior and habits, and the current usage level can be pushed to the user in real time. The user can regularly repair the smart sliding door according to the wear level of the smart sliding door, thereby increasing its usage time and improving the user experience.

[0075] The embodiment of the roller rail life assessment method for smart sliding doors proposed in the present application introduces the characteristic values ​​of environmental factors, and segments and extracts features from the usage data based on the usage data of the smart sliding doors. Then, the wear characteristic values ​​of the smart sliding doors in the usage data are analyzed. Based on the relationship between the wear characteristic values ​​and the causes of friction, the friction power increase trend value of the smart sliding door is further evaluated, and the subsequent friction power of the smart sliding door is adjusted accordingly. When the predicted friction power reaches the power threshold, it is considered that the smart sliding door has reached its service life. This method can evaluate the service life of the smart sliding door based on its usage in the actual environment, so that the evaluation result is more accurate.

[0076] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0077] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the methods, devices and equipment described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0078] In the several embodiments provided in the embodiments of the present application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0079] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0080] In addition, each functional module in each embodiment of the present application can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0081] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0082] The computer program product includes one or more computer instructions. When the computer program is loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a digital video disk), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0083] Although the embodiments of the present application have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles of the present application.

Claims

1. A roller rail life assessment method for an intelligent sliding door, characterized in that: include: Acquire usage data of the smart sliding door; the usage data at least includes the motor power of the smart sliding door; Based on the usage data, a plurality of segmented data are obtained; each segmented data includes a pushing process of the intelligent sliding door, and each pushing process includes a starting acceleration phase, a uniform speed phase, and a deceleration phase of the intelligent sliding door; Based on each segmented data, acquiring a wear characteristic value of the intelligent sliding door; Based on the wear characteristic value, a friction power increase trend value of the smart sliding door is obtained; the friction power increase trend value is at least used to characterize the magnitude of the change in friction force of the smart sliding door caused by the wear of the roller and the sliding rail; Based on the friction power increase trend value, the service life of the intelligent sliding door is obtained.

2. The roller rail life assessment method for intelligent sliding door according to claim 1 is characterized in that: The step of obtaining the wear characteristic value of the intelligent sliding door based on each segmented data includes: Based on the first segmented data, a slide rail wear characteristic value is obtained; the first segmented data is any one of the segmented data; the slide rail wear characteristic value is at least used to characterize the influence of the slide rail wear on the friction power characteristics of the intelligent slide rail door; Based on the first segmented data, an environmental factor characteristic value is obtained; the environmental factor characteristic value is at least used to characterize the influence of dust on the friction power characteristics of the intelligent sliding door; Based on the first segmented data, a roller wear characteristic value is obtained; the roller wear characteristic value is at least used to characterize the influence of roller wear on the friction power characteristics of the intelligent sliding door; Based on the slide rail wear characteristic value, the environmental factor characteristic value and the roller wear characteristic value, the wear characteristic value of the intelligent slide rail door is obtained.

3. The roller rail life assessment method for intelligent sliding door according to claim 2 is characterized in that: The step of obtaining the rail wear characteristic value based on the first segmented data includes: Based on the first segmented data, a first mean, a second mean and a third mean are obtained; the first mean is the mean of the motor power in the startup acceleration stage in the first segmented data; the second mean is the mean of the motor power in the uniform speed stage in the first segmented data; the third mean is the mean of the motor power in the deceleration stage in the first segmented data; Based on the first mean, the second mean and the third mean, a first integral area, a second integral area and a third integral area are obtained; the first integral area is the area of ​​the area formed by the motor power curve in the startup acceleration stage and the straight line with the motor power equal to the first mean; the second integral area is the area of ​​the area formed by the motor power curve in the uniform speed stage and the straight line with the motor power equal to the second mean; the third integral area is the area of ​​the area formed by the motor power curve in the deceleration stage and the straight line with the motor power equal to the third mean; The slide rail wear characteristic value is acquired based on the first integrated area, the second integrated area, and the third integrated area.

4. The roller rail life assessment method for intelligent sliding door according to claim 3 is characterized in that: The acquiring the rail wear characteristic value based on the first integrated area, the second integrated area, and the third integrated area includes: A first sequence and a second sequence are constructed based on each segmented data in time sequence; the first sequence is the sum of the first integral area, the second integral area and the third integral area corresponding to each segmented data; the second sequence is the motor power corresponding to the startup acceleration stage, the uniform speed stage and the deceleration stage of each segmented data; Based on the Pearson correlation coefficient, obtaining a correlation value between the first sequence and the second sequence; The correlation degree value is used as the slide rail wear characteristic value.

5. The roller rail life assessment method for an intelligent sliding door according to any one of claims 2 to 4, characterized in that: The obtaining of the environmental factor characteristic value based on the first segmented data includes: Based on the first segmented data, a first difference is obtained; the first difference is the difference between the motor power consumed in the entire process of the first segmented data and the motor power consumed in the previous adjacent segmented data; Based on the first segmented data, a fourth mean is obtained; the fourth mean is an average value of motor power differences in a startup acceleration phase of each adjacent segmented data whose timing is before the first segmented data; Based on the first difference and the fourth mean, the environmental factor characteristic value is obtained; the environmental factor characteristic value is equal to the ratio of the fourth mean to the first difference.

6. The roller rail life assessment method for intelligent sliding door according to claim 5, characterized in that: The obtaining, based on the wear characteristic value, a friction power increase trend value of the intelligent sliding door includes: Based on the current segmented data, a second difference; the second difference is the difference between the motor power corresponding to the current segmented data and the motor power corresponding to the second segmented data of the smart sliding door under dust-free conditions; the number of push-pull times corresponding to the second segmented data is the same as the number of push-pull times corresponding to the current segmented data; Obtain a first power growth value and a second power growth value through the second difference by using the least square method; the first power growth value is the growth value of the motor power caused by the environmental factors caused by unit dust deposition; the second power growth value is the growth value of the motor power caused by the roller and slide rail factors caused by unit dust deposition; Based on the first power increase value and the second power increase value, the friction power increase trend value of the intelligent sliding door is obtained.

7. The roller rail life assessment method for intelligent sliding door according to claim 6, characterized in that: The calculation formula for obtaining the first power increase value and the second power increase value by using the least square method through the second difference is as follows: in, represents the second difference value corresponding to the lth segmentation data; Indicates the friction power value of the roller and the slide rail corresponding to the l-1th segmentation data; represents the ratio of the rail wear characteristic value to the roller wear characteristic value in the lth segmented data; F represents the second power growth value; represents the environmental factor characteristic value corresponding to the l-1th segmentation data; Indicates the first power increase value.

8. The roller rail life assessment method for intelligent sliding door according to claim 7, characterized in that: The calculation formula for obtaining the friction power increase trend value of the intelligent sliding door based on the first power increase value and the second power increase value is as follows: in, Indicates the friction power increase trend value corresponding to the i-th segmentation data; represents the second difference corresponding to the i-1th segmentation data; Represents the characteristic value of the environmental factor corresponding to the i-th segmentation data; It represents the sum of the rail wear characteristic value and roller wear characteristic value corresponding to the i-th segmentation data.

9. The roller rail life assessment method for intelligent sliding door according to claim 8, characterized in that: The obtaining the service life of the intelligent sliding door based on the friction power increase trend value includes: Based on the usage data, obtaining the current usage count and current usage duration of the smart sliding door; Based on the friction power increase trend value and the power threshold, obtaining a usage times threshold; the power threshold is obtained in advance; Based on the usage count threshold, the current usage count and the current usage duration, the service life of the smart sliding door is obtained.

10. The roller rail life assessment method for intelligent sliding door according to claim 9, characterized in that: Based on the usage count threshold, the current usage count and the current usage duration, the calculation formula for obtaining the service life of the smart sliding door is as follows: in, Indicates the remaining usage time of the smart sliding door; Indicates the usage count threshold; Indicates the current number of times used; Indicates the current usage time.

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