Elevator health state assessment method and device, medium and equipment

Abstract

The embodiment of the invention discloses an elevator health state assessment method and device, a medium and equipment, and relates to the technical field of elevator monitoring, according to the elevator health state assessment method and device, monitoring of a lift car and a guide rail during elevator running is achieved by arranging a plurality of vibration sensors along the guide rail, monitoring can be achieved more comprehensively, and the elevator health state assessment efficiency is improved. In addition, fine changes can be monitored, effectiveness of evaluation results is improved, after fluctuation data are obtained through comparison, linear changes of data of abnormal fluctuation parts are only used for reflecting the size of the relative distance, so that the section where the guide rail is abnormal is determined, and the situation of the detected vibration data of the lift car is used for judging whether the guide rail is abnormal or not. The abnormal part generated by vibration of the lift car is utilized to more accurately position the abnormal point location in the suspected interval, and finally the health state of the lift is effectively and timely evaluated by combining the historical abnormal point location and the current abnormal point location.

Description

Technical Field

[0001] The present application relates to the technical field of elevator monitoring, and in particular to an elevator health status assessment method, device, medium and equipment. Background Art

[0002] An elevator is a permanent transportation device that serves several specific floors in a building and whose car runs on at least two rows of rigid rails that are perpendicular to the horizontal plane or inclined at an angle of less than 15° to the plumb line. In order to ensure the safe operation of the elevator, it is necessary to conduct a health status assessment of the elevator. However, the current assessment method still mainly relies on manual operation. Maintenance personnel are sent to inspect and check the status of some key components periodically. Then, the health assessment of the elevator is conducted based on the status of each component to determine whether there are any safety hazards. If there are any, the corresponding components are repaired and replaced. For example, one of the important indicators is the straightness of the guide rail. If the straightness is abnormal, the safety of the elevator operation will be affected. During operation, jitter and abnormal noise may occur. The timeliness of the existing assessment method is poor. It is very likely that the guide rail has already had an abnormality during the period between the maintenance cycles. Even if a lot of time is spent on the inspection of the entire guide rail, there may be problems of incompleteness. In addition, under manual processing, some minor abnormalities may be missed, resulting in low effectiveness of the assessment results. Summary of the invention

[0003] The main purpose of this application is to provide an elevator health status assessment method, device, medium and equipment, aiming to solve the problems of poor timeliness of elevator health status assessment and poor effectiveness of assessment results in the prior art.

[0004] To achieve the above objectives, the technical solutions adopted in the embodiments of the present application are as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for evaluating the health status of an elevator, comprising the following steps:

[0006] Acquire car vibration data and guide rail vibration data during elevator operation; wherein the guide rail vibration data is obtained based on a plurality of vibration sensors evenly distributed along the guide rail;

[0007] Compare the car vibration data and the guide rail vibration data with the car standard vibration data and the guide rail standard vibration data respectively to obtain the car vibration fluctuation data and the guide rail vibration fluctuation data;

[0008] When the number of frames of the guide rail vibration fluctuation data is greater than a preset number of frames, determining a suspected abnormal interval of the guide rail according to a linear change of the guide rail vibration fluctuation data;

[0009] According to the car vibration fluctuation data, the target abnormal point is determined within the suspected abnormal range of the guide rail;

[0010] Evaluate the health status of the elevator based on historical abnormal points and target abnormal points.

[0011] In a possible implementation of the first aspect, determining a suspected abnormal interval of the guide rail according to a linear change of the guide rail vibration fluctuation data includes:

[0012] According to the vibration fluctuation data of the guide rail, a plurality of fluctuation deviation values ​​are obtained; wherein one fluctuation deviation value corresponds to one vibration sensor;

[0013] According to the magnitude of multiple fluctuation deviation values, the linear change is obtained to determine the suspected abnormal interval of the guide rail.

[0014] In a possible implementation of the first aspect, determining a target abnormal point within a suspected abnormal interval of a guide rail according to the car vibration fluctuation data includes:

[0015] According to the car vibration fluctuation data, determine the interval position of abnormal data relative to complete data;

[0016] The interval position is mapped to the guide rail to determine the target abnormal point within the suspected abnormal interval of the guide rail.

[0017] In a possible implementation of the first aspect, before comparing the car vibration data and the guide rail vibration data with the car standard vibration data and the guide rail standard vibration data respectively to obtain the car vibration fluctuation data and the guide rail vibration fluctuation data, the method further includes:

[0018] According to the vibration sensor corresponding to the guide rail vibration data and the distance between the car and the vibration sensor when collecting each frame of data, the guide rail vibration data is adjusted to obtain the guide rail target vibration data.

[0019] In a possible implementation of the first aspect, according to a vibration sensor corresponding to the guide rail vibration data and a distance between the car and the vibration sensor when collecting each frame of data, the guide rail vibration data is adjusted to obtain the guide rail target vibration data, including:

[0020] An adjustment curve is obtained according to the vibration sensor corresponding to the guide rail vibration data and the distance between the car and the vibration sensor when collecting each frame of data;

[0021] According to the adjustment curve, the guide rail vibration data corresponding to each frame number is adjusted so that the guide rail vibration data presents a horizontal straight line distribution, and the guide rail target vibration data is obtained.

[0022] In a possible implementation of the first aspect, before comparing the car vibration data and the guide rail vibration data with the car standard vibration data and the guide rail standard vibration data respectively to obtain the car vibration fluctuation data and the guide rail vibration fluctuation data, the method further includes:

[0023] Unify the standard vibration data of the car and the standard vibration data of the guide rail to obtain the target standard data;

[0024] The car vibration data and the guide rail vibration data are respectively compared with the car standard vibration data and the guide rail standard vibration data to obtain the car vibration fluctuation data and the guide rail vibration fluctuation data, including:

[0025] The car vibration data and guide rail vibration data are respectively compared with the target standard data to obtain the car vibration fluctuation data and guide rail vibration fluctuation data.

[0026] In a possible implementation of the first aspect, obtaining car vibration data and guide rail vibration data during elevator operation includes:

[0027] Obtaining original car vibration data and original guide rail vibration data during elevator operation;

[0028] The original car vibration data and the original guide rail vibration data are cleaned, and the cleaned data are cropped based on the effective time series to obtain the car vibration data and the guide rail vibration data with the same number of frames.

[0029] In a second aspect, an embodiment of the present application provides an elevator health status assessment device, comprising:

[0030] An acquisition module, the acquisition module is used to acquire car vibration data and guide rail vibration data when the elevator is running; wherein the guide rail vibration data is obtained based on a plurality of vibration sensors evenly distributed along the guide rail;

[0031] A comparison module, which is used to compare the car vibration data and the guide rail vibration data with the car standard vibration data and the guide rail standard vibration data respectively, to obtain the car vibration fluctuation data and the guide rail vibration fluctuation data;

[0032] A determination module, the determination module is used to determine the suspected abnormal interval of the guide rail according to the linear change of the guide rail vibration fluctuation data when the frame number of the guide rail vibration fluctuation data is greater than the preset frame number;

[0033] The abnormal module is used to determine the target abnormal point within the suspected abnormal range of the guide rail according to the vibration fluctuation data of the car;

[0034] Evaluation module,The evaluation module is used to evaluate the health status of the elevator based on historical abnormal points and target abnormal points.

[0035] In a third aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program. When the computer program is loaded and executed by a processor, the elevator health status assessment method provided in any one of the first aspects above is implemented.

[0036] In a fourth aspect, an embodiment of the present application provides an electronic device, including a processor and a memory, wherein:

[0037] The memory is used to store computer programs;

[0038] The processor is used to load and execute a computer program so that the electronic device executes the elevator health status assessment method provided in any one of the first aspects above.

[0039] Compared with the prior art, the beneficial effects of this application are:

[0040] The embodiments of the present application propose an elevator health status assessment method, device, medium and equipment, the method comprising: obtaining car vibration data and guide rail vibration data during elevator operation; wherein the guide rail vibration data is obtained based on multiple vibration sensors evenly distributed along the guide rail; comparing the car vibration data and guide rail vibration data with the car standard vibration data and the guide rail standard vibration data, respectively, to obtain car vibration fluctuation data and guide rail vibration fluctuation data; when the number of frames of the guide rail vibration fluctuation data is greater than a preset number of frames, determining a suspected abnormal interval of the guide rail according to the linear change of the guide rail vibration fluctuation data; determining a target abnormal point within the suspected abnormal interval of the guide rail according to the car vibration fluctuation data; and assessing the health status of the elevator according to the historical abnormal points and the target abnormal points. The present application realizes the monitoring of the elevator car and the guide rail when the elevator is running by deploying vibration sensors. Multiple vibration sensors are deployed along the guide rail, which can realize more comprehensive monitoring and can monitor relatively subtle changes, thereby improving the effectiveness of the evaluation results. By comparing the vibration data collected by each with the standard vibration data, it can be found that the vibration data has fluctuating parts. When the number of frames of the guide rail vibration fluctuation data is greater than the preset number of frames, it means that the abnormal fluctuation of the data is not caused by accidental factors. At the same time, considering that the change in the distance between the vibration sensor and the moving car will affect the overall level of the vibration data, after the fluctuation data are obtained by comparison, only the linear change of the data of the abnormal fluctuation part is used to reflect the size of the relative distance, so as to determine the interval where the guide rail has an abnormality. Since the vibration sensors cannot be deployed too densely, this interval is relatively large and can only be determined as a suspected interval. At this time, the detected vibration data of the car can be used to use the abnormal part of the car vibration to more accurately locate the abnormal point in the suspected interval, and finally combine the historical abnormal points with the current abnormal points to achieve an effective and timely evaluation of the health status of the elevator. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A schematic diagram of the structure of an electronic device of a hardware operating environment involved in an embodiment of the present application;

[0042] Figure 2 A flow chart of an elevator health status assessment method provided in an embodiment of the present application;

[0043] Figure 3 A schematic diagram of a module of an elevator health status assessment device provided in an embodiment of the present application;

[0044] Markings in the figure: 101 - processor, 102 - communication bus, 103 - network interface, 104 - user interface, 105 - memory. DETAILED DESCRIPTION

[0045] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0046] See attached Figure 1 , attached Figure 1 This is a schematic diagram of the structure of an electronic device of the hardware operating environment involved in the embodiment of the present application. The electronic device may include: a processor 101, such as a central processing unit (CPU), a communication bus 102, a user interface 104, a network interface 103, and a memory 105. Among them, the communication bus 102 is used to realize the connection and communication between these components. The user interface 104 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the user interface 104 may also include a standard wired interface and a wireless interface. The network interface 103 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (WI re l ess-FI de l ity, WI-FI) interface). The memory 105 may optionally be a storage device independent of the aforementioned processor 101. The memory 105 may be a high-speed random access memory (RAM) memory, or it may be a stable non-volatile memory (NVM), such as at least one disk storage; the processor 101 may be a general-purpose processor, including a central processing unit, a network processor, etc., or it may be a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component.

[0047] Those skilled in the art will appreciate that Figure 1 The structure shown in the figure does not constitute a limitation on the electronic device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0048] As attached Figure 1 As shown, the memory 105 as a storage medium may include an operating system, a network communication module, a user interface module, and an elevator health status assessment device.

[0049] In the attached Figure 1 In the electronic device shown, the network interface 103 is mainly used for data communication with the network server; the user interface 104 is mainly used for data interaction with the user; the processor 101 and the memory 105 in the present application can be set in the electronic device, and the electronic device calls the elevator health status assessment device stored in the memory 105 through the processor 101, and executes the elevator health status assessment method provided in the embodiment of the present application.

[0050] See attached Figure 2 Based on the hardware device of the aforementioned embodiment, the embodiment of the present application provides an elevator health status assessment method, comprising the following steps:

[0051] S10: Acquire elevator car vibration data and guide rail vibration data during elevator operation; wherein the guide rail vibration data is obtained based on a plurality of vibration sensors evenly distributed along the guide rail.

[0052] In the specific implementation process, the elevator guide rail is the safety rail for the elevator to travel up and down in the hoistway. The guide rail is installed on the hoistway wall and is fixed to the hoistway wall by the guide rail frame and the guide rail bracket. The straightness of the guide rail is a key factor in ensuring the smooth operation of the elevator. By detecting the vibration data of the guide rail when the elevator is running, it can be determined whether its straightness is affected. If a single vibration sensor is deployed, then if the abnormal position is far away from the sensor, the data fed back by the sensor may not reflect the abnormal vibration changes. Therefore, multiple vibration sensors evenly distributed along the guide rail are set to achieve comprehensive monitoring. The vibration data of the car can be obtained by setting a vibration sensor on the car. The vibration sensor moves with the car, so there is no need to set up multiple ones.

[0053] In one embodiment, obtaining car vibration data and guide rail vibration data during elevator operation includes:

[0054] Obtaining original car vibration data and original guide rail vibration data during elevator operation;

[0055] The original car vibration data and the original guide rail vibration data are cleaned, and the cleaned data are cropped based on the effective time series to obtain the car vibration data and the guide rail vibration data with the same number of frames.

[0056] In the specific implementation process, due to the start, stop, and stay of the elevator, as well as the influence of the use environment and personnel, the collected original data may be missing, discontinuous, and sudden. Data cleaning can be considered. Data cleaning can remove duplicate values, eliminate obviously discrete data, and interpolate missing data to improve the integrity and quality of the data. The cleaned data is trimmed according to the time series to keep the car vibration data and the guide rail vibration data with the same number of frames for subsequent processing and analysis.

[0057] S20: Compare the car vibration data and the guide rail vibration data with the car standard vibration data and the guide rail standard vibration data respectively to obtain the car vibration fluctuation data and the guide rail vibration fluctuation data.

[0058] In the specific implementation process, abnormal data can be obtained by comparing the monitored data with the corresponding standard data, and such abnormal data is manifested as fluctuating data in the vibration data. The standard data used for comparison can be the vibration data collected by each vibration sensor while ensuring that the elevator is running without abnormalities. Since multiple sensors are arranged on the guide rail for detection, the data collected by each vibration sensor is different, and the standard data used for comparison is also different. The separate comparison will be slightly complicated. Therefore, it is considered whether the data can be adjusted so that each sensor can be compared with the same standard. The embodiment of the present application provides a method: the car vibration data and the guide rail vibration data are respectively compared with the car standard vibration data and the guide rail standard vibration data. Before obtaining the car vibration fluctuation data and the guide rail vibration fluctuation data, the method also includes:

[0059] According to the vibration sensor corresponding to the guide rail vibration data and the distance between the car and the vibration sensor when collecting each frame of data, the guide rail vibration data is adjusted to obtain the guide rail target vibration data.

[0060] In the specific implementation process, since multiple vibration sensors are set, the relative distance between the elevator car and different vibration sensors does not change when the elevator is running. According to the vibration situation, regardless of whether the guide rail is abnormal, the closer the vibration sensor is to the car, the higher the overall level of feedback data will be. Therefore, the vibration data is adjusted by the distance between the car and the vibration sensor, so that the data with smaller values ​​fed back by the sensor far away becomes larger. The adjusted data is the target vibration data of the guide rail. Specifically: according to the vibration sensor corresponding to the guide rail vibration data and the distance between the car and the vibration sensor when collecting each frame of data, the guide rail vibration data is adjusted to obtain the guide rail target vibration data, including:

[0061] An adjustment curve is obtained according to the vibration sensor corresponding to the guide rail vibration data and the distance between the car and the vibration sensor when collecting each frame of data;

[0062] According to the adjustment curve, the guide rail vibration data corresponding to each frame number is adjusted so that the guide rail vibration data presents a horizontal straight line distribution, and the guide rail target vibration data is obtained.

[0063] In the specific implementation process, since the elevator car will cause vibration and collect vibration data only when it moves, and the distance between the constantly moving car and the sensor is changing at any time, the size of the adjustment required for each frame of data is different, so the change in distance is quantified into a curve, and the curve is used as an adjustment curve to adjust each frame of data. After the curve is drawn in the coordinate system, time is used as the horizontal axis, and the vertical axis corresponds to the size of the adjustment coefficient of the frame number data at that moment. Without adjustment, the curve of the vibration data fed back by the vibration sensor is diverse. Even if there is no abnormality and smooth operation, the curve may be a straight line with a positive slope (the vibration sensor and the car are gradually approaching), or a curve with a negative slope (the vibration sensor and the car are gradually moving away), or an inverted V-shaped curve (the vibration sensor and the car are gradually approaching and then gradually moving away). The adjustment curve is obtained according to the change in relative distance to adjust the guide rail vibration data, so that the linear performance of the guide rail vibration data presents a horizontal straight line distribution. From the curve performance of the vibration data, the previous example continues to explain:

[0064] For example, the curve of vibration data is a straight line with a positive slope. The smaller the ordinate, the farther away from the car. The corresponding ordinate value on the adjustment curve is larger. The larger the vibration data under the frame number needs to be adjusted, the closer the slope of the straight line with a positive slope is to zero, presenting a horizontal straight line state.

[0065] The vibration sensor for the car moves with the car, so the above problem will not occur. The linear expression of the feedback data is originally a horizontal straight line distribution, and the vibration data of the guide rail is adjusted to a similar state, so the standard data for comparison can be unified, and the standard data for comparison can be a horizontal straight line. When comparing, the horizontality is used as the standard, and the discrete part of the vibration data relative to the horizontal straight line can be regarded as data with vibration fluctuations; that is: before comparing the car vibration data and the guide rail vibration data with the car standard vibration data and the guide rail standard vibration data respectively, and obtaining the car vibration fluctuation data and the guide rail vibration fluctuation data, the method also includes:

[0066] Unify the standard vibration data of the car and the standard vibration data of the guide rail to obtain the target standard data.

[0067] Based on the above steps, the car vibration data and the guide rail vibration data are compared with the car standard vibration data and the guide rail standard vibration data respectively to obtain the car vibration fluctuation data and the guide rail vibration fluctuation data, including:

[0068] The car vibration data and guide rail vibration data are respectively compared with the target standard data to obtain the car vibration fluctuation data and guide rail vibration fluctuation data.

[0069] S30: When the number of frames of the guide rail vibration fluctuation data is greater than a preset number of frames, a suspected abnormal interval of the guide rail is determined according to a linear change of the guide rail vibration fluctuation data.

[0070] In the specific implementation process, under ideal conditions, the elevator runs smoothly without any faults, and the vibration data will not show abnormal fluctuations. However, in actual situations, the start and stop of the elevator and the influence of the sensor transmission signal may cause abnormal fluctuations in the feedback vibration data. However, considering that the impact will not last for a long time, such as the start and stop of the elevator is only a few seconds, the abnormality of the sensor transmission signal may be smaller, which may be between minutes and seconds or even milliseconds. The above situations are different from the continuous existence of abnormal situations. Therefore, a frame number is set as a threshold to identify data anomalies caused by these sudden factors. These abnormal fluctuations in data are directly affected by the abnormal parts of the guide rail and are related to the relative distance. The farther the distance, the more obvious the abnormal fluctuations. Therefore, through the linear changes in the vibration fluctuation data of the guide rail, the suspected abnormal interval of the guide rail can be determined.

[0071] Specifically: According to the linear change of the guide rail vibration fluctuation data, determine the suspected abnormal range of the guide rail, including:

[0072] According to the vibration fluctuation data of the guide rail, a plurality of fluctuation deviation values ​​are obtained; wherein one fluctuation deviation value corresponds to one vibration sensor;

[0073] According to the magnitude of multiple fluctuation deviation values, the linear change is obtained to determine the suspected abnormal interval of the guide rail.

[0074] In the specific implementation process, since different vibration sensors are at different distances from the abnormal position, the distance will be directly reflected in the fluctuation deviation value of the guide rail vibration fluctuation data. The larger the fluctuation deviation value, the closer the corresponding vibration sensor is to the abnormal position. Then the linearity formed by the change in the size of the fluctuation deviation value points to the position closest to the abnormality. However, due to the long length of the guide rail, the sensors will not be densely arranged along the guide rail, so the determination is only a preliminary determination of the suspected abnormal interval, and the car vibration data needs to be used for further determination.

[0075] S40: According to the car vibration fluctuation data, a target abnormal point is determined within the guide rail suspected abnormality interval.

[0076] In the specific implementation process, after the suspected abnormal interval is determined using the guide rail vibration data, the car vibration data is used to determine a more accurate abnormal location. Specifically: According to the car vibration fluctuation data, the target abnormal point is determined within the suspected abnormal interval of the guide rail, including:

[0077] According to the car vibration fluctuation data, determine the interval position of abnormal data relative to complete data;

[0078] The interval position is mapped to the guide rail to determine the target abnormal point within the suspected abnormal interval of the guide rail.

[0079] In the specific implementation process, since the vibration of the car is directly affected by the distance from the abnormal part, the car vibration fluctuation data can directly reflect the abnormal part. The car vibration fluctuation data is used as abnormal data, and its interval position in the complete data corresponds to the position of the abnormal point on the guide rail. A mapping relationship is formed, and the interval position is mapped to the guide rail, and then combined with the suspected interval determined by the linear change of the guide rail vibration fluctuation data. If the deviation between the target abnormal point and the abnormal position pointed to by the linear change is within a reasonable range, then the target abnormal point can be determined to be reliable.

[0080] S50: Evaluate the health status of the elevator based on the historical abnormal points and the target abnormal points.

[0081] In the specific implementation process, after the target abnormal point is obtained, it indicates that the health status of the elevator is poor. In order to achieve a more comprehensive evaluation, historical data is combined for evaluation. The historical abnormal points also characterize the occurrence of abnormal points. Based on this information, the current target abnormal point or the location and frequency of historical abnormalities in its vicinity can be determined, and the health status of the elevator is comprehensively considered. For example, if a certain section has experienced abnormalities many times, then the health status of the elevator is poor, and this section needs to be inspected in detail.

[0082] In this embodiment, vibration sensors are arranged to monitor the elevator car and guide rails during operation. Multiple vibration sensors are arranged along the guide rails, which can realize more comprehensive monitoring and monitor relatively subtle changes, thereby improving the effectiveness of the evaluation results. By comparing the vibration data collected by each sensor with the standard vibration data, it can be found that the vibration data has fluctuating parts. When the number of frames of the guide rail vibration fluctuation data is greater than the preset number of frames, it means that the abnormal fluctuation of the data is not caused by accidental factors. At the same time, considering that the change in the distance between the vibration sensor and the moving car will affect the overall level of the vibration data, after the fluctuation data are obtained by comparison, only the linear change of the data of the abnormal fluctuation part is used to reflect the size of the relative distance, so as to determine the interval where the guide rail has an abnormality. Since the vibration sensors cannot be arranged too densely, this interval is relatively large and can only be determined as a suspected interval. At this time, the detected vibration data of the car can be used to use the abnormal part of the car vibration to more accurately locate the abnormal point in the suspected interval, and finally combine the historical abnormal points with the current abnormal points to achieve an effective and timely evaluation of the health status of the elevator.

[0083] Refer to the attached Figure 3 Based on the same inventive concept as in the above-mentioned embodiment, the embodiment of the present application further provides an elevator health status assessment device, comprising:

[0084] An acquisition module, the acquisition module is used to acquire car vibration data and guide rail vibration data when the elevator is running; wherein the guide rail vibration data is obtained based on a plurality of vibration sensors evenly distributed along the guide rail;

[0085] A comparison module, which is used to compare the car vibration data and the guide rail vibration data with the car standard vibration data and the guide rail standard vibration data respectively, to obtain the car vibration fluctuation data and the guide rail vibration fluctuation data;

[0086] A determination module, the determination module is used to determine the suspected abnormal interval of the guide rail according to the linear change of the guide rail vibration fluctuation data when the frame number of the guide rail vibration fluctuation data is greater than the preset frame number;

[0087] The abnormal module is used to determine the target abnormal point within the suspected abnormal range of the guide rail according to the vibration fluctuation data of the car;

[0088] Evaluation module,The evaluation module is used to evaluate the health status of the elevator based on historical abnormal points and target abnormal points.

[0089] Those skilled in the art should understand that the division of the various modules in the embodiment is only a division of logical functions, and can be fully or partially integrated into one or more actual carriers in actual application, and these modules can be all implemented in the form of software called by the processing unit, or all implemented in the form of hardware, or implemented in the form of a combination of software and hardware. It should be noted that the modules in the elevator health status assessment device in this embodiment correspond one-to-one to the steps in the elevator health status assessment method in the aforementioned embodiment. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned elevator health status assessment method, which will not be repeated here.

[0090] Based on the same inventive concept as in the aforementioned embodiment, the embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when loaded and executed by a processor, implements the elevator health status assessment method provided in the embodiment of the present application.

[0091] Based on the same inventive concept as in the above-mentioned embodiment, an embodiment of the present application further provides an electronic device, including a processor and a memory, wherein:

[0092] The memory is used to store computer programs;

[0093] The processor is used to load and execute a computer program so that the electronic device executes the elevator health status assessment method provided in the embodiment of the present application.

[0094] In some embodiments, the computer readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or various devices including one or any combination of the above memories. The computer may be various computing devices including intelligent terminals and servers.

[0095] In some embodiments, executable instructions may be in the form of a program, software, software module, script or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine or other unit suitable for use in a computing environment.

[0096] As an example, executable instructions may, but need not, correspond to a file in a file system, may be stored as part of a file that stores other programs or data, such as in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing one or more modules, subroutines, or code portions).

[0097] By way of example, executable instructions may be deployed to be executed on one computing device, or on multiple computing devices located at one site, or on multiple computing devices distributed across multiple sites and interconnected by a communication network.

[0098] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0099] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0100] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory / random access memory, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a multimedia terminal device (which can be a mobile phone, a computer, a television receiver, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0101] In summary, the present application provides an elevator health status assessment method, device, medium and equipment, the method comprising: obtaining car vibration data and guide rail vibration data during elevator operation; wherein the guide rail vibration data is obtained based on multiple vibration sensors evenly distributed along the guide rail; comparing the car vibration data and guide rail vibration data with the car standard vibration data and the guide rail standard vibration data, respectively, to obtain car vibration fluctuation data and guide rail vibration fluctuation data; when the number of frames of the guide rail vibration fluctuation data is greater than a preset number of frames, determining the suspected abnormal interval of the guide rail according to the linear change of the guide rail vibration fluctuation data; determining the target abnormal point within the suspected abnormal interval of the guide rail according to the car vibration fluctuation data; and evaluating the health status of the elevator according to the historical abnormal points and the target abnormal points. The present application realizes the monitoring of the elevator car and the guide rail when the elevator is running by deploying vibration sensors. Multiple vibration sensors are deployed along the guide rail, which can realize more comprehensive monitoring and can monitor relatively subtle changes, thereby improving the effectiveness of the evaluation results. By comparing the vibration data collected by each with the standard vibration data, it can be found that the vibration data has fluctuating parts. When the number of frames of the guide rail vibration fluctuation data is greater than the preset number of frames, it means that the abnormal fluctuation of the data is not caused by accidental factors. At the same time, considering that the change in the distance between the vibration sensor and the moving car will affect the overall level of the vibration data, after the fluctuation data are obtained by comparison, only the linear change of the data of the abnormal fluctuation part is used to reflect the size of the relative distance, so as to determine the interval where the guide rail has an abnormality. Since the vibration sensors cannot be deployed too densely, this interval is relatively large and can only be determined as a suspected interval. At this time, the detected vibration data of the car can be used to use the abnormal part of the car vibration to more accurately locate the abnormal point in the suspected interval, and finally combine the historical abnormal points with the current abnormal points to achieve an effective and timely evaluation of the health status of the elevator.

[0102] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for evaluating the health status of an elevator, characterized in that: The following steps are involved: Acquire car vibration data and guide rail vibration data when the elevator is running; wherein the guide rail vibration data is obtained based on a plurality of vibration sensors evenly distributed along the guide rail; Comparing the car vibration data and the guide rail vibration data with the car standard vibration data and the guide rail standard vibration data respectively to obtain car vibration fluctuation data and guide rail vibration fluctuation data; When the number of frames of the guide rail vibration fluctuation data is greater than a preset number of frames, determining a suspected abnormal interval of the guide rail according to a linear change of the guide rail vibration fluctuation data; According to the car vibration fluctuation data, determining a target abnormal point within the guide rail suspected abnormal interval; Evaluate the health status of the elevator based on the historical abnormal points and the target abnormal points.

2. The elevator health status assessment method according to claim 1, characterized in that: Determining the suspected abnormal interval of the guide rail according to the linear change of the guide rail vibration fluctuation data includes: According to the guide rail vibration fluctuation data, a plurality of fluctuation deviation values ​​are obtained; wherein one fluctuation deviation value corresponds to one vibration sensor; According to the magnitudes of the plurality of fluctuation deviation values, a linear change condition is obtained to determine a suspected abnormal interval of the guide rail.

3. The elevator health status assessment method according to claim 1, characterized in that: The step of determining a target abnormal point within the guide rail suspected abnormality interval according to the car vibration fluctuation data comprises: Determine the interval position of abnormal data relative to complete data based on the car vibration fluctuation data; The interval position is mapped to the guide rail to determine the target abnormal point position within the suspected abnormal interval of the guide rail.

4. The elevator health status assessment method according to claim 1, characterized in that: Before comparing the car vibration data and the guide rail vibration data with the car standard vibration data and the guide rail standard vibration data respectively to obtain the car vibration fluctuation data and the guide rail vibration fluctuation data, the method further includes: According to the vibration sensor corresponding to the guide rail vibration data and the distance between the car and the vibration sensor when collecting each frame of data, the guide rail vibration data is adjusted to obtain the guide rail target vibration data.

5. The elevator health status assessment method according to claim 4, characterized in that: The method of adjusting the guide rail vibration data according to the vibration sensor corresponding to the guide rail vibration data and the distance between the car and the vibration sensor when collecting each frame of data, and obtaining the guide rail target vibration data includes: Obtaining an adjustment curve according to the vibration sensor corresponding to the guide rail vibration data and the distance between the car and the vibration sensor when collecting each frame of data; According to the adjustment curve, the guide rail vibration data corresponding to each frame number is adjusted so that the guide rail vibration data presents a horizontal straight line distribution, thereby obtaining the guide rail target vibration data.

6. The elevator health status assessment method according to claim 5, characterized in that: Before comparing the car vibration data and the guide rail vibration data with the car standard vibration data and the guide rail standard vibration data respectively to obtain the car vibration fluctuation data and the guide rail vibration fluctuation data, the method further includes: Unifying the car standard vibration data and the guide rail standard vibration data to obtain target standard data; The step of comparing the car vibration data and the guide rail vibration data with the car standard vibration data and the guide rail standard vibration data to obtain the car vibration fluctuation data and the guide rail vibration fluctuation data comprises: The car vibration data and the guide rail vibration data are respectively compared with the target standard data to obtain car vibration fluctuation data and guide rail vibration fluctuation data.

7. The elevator health status assessment method according to claim 1, characterized in that: The step of obtaining the car vibration data and guide rail vibration data during elevator operation includes: Obtaining original car vibration data and original guide rail vibration data during elevator operation; The original car vibration data and the original guide rail vibration data are cleaned, and the cleaned data are cropped based on a valid time series to obtain car vibration data and guide rail vibration data with the same number of frames.

8. An elevator health status assessment device, characterized in that: include: An acquisition module, the acquisition module is used to acquire car vibration data and guide rail vibration data when the elevator is running; wherein the guide rail vibration data is obtained based on a plurality of vibration sensors evenly distributed along the guide rail; A comparison module, the comparison module is used to compare the car vibration data and the guide rail vibration data with the car standard vibration data and the guide rail standard vibration data respectively, to obtain the car vibration fluctuation data and the guide rail vibration fluctuation data; A determination module, the determination module is used to determine a suspected abnormal interval of the guide rail according to a linear change of the guide rail vibration fluctuation data when the number of frames of the guide rail vibration fluctuation data is greater than a preset number of frames; An abnormality module, the abnormality module is used to determine a target abnormal point within the suspected abnormality interval of the guide rail according to the vibration fluctuation data of the car; An evaluation module is used to evaluate the health status of the elevator based on historical abnormal points and the target abnormal points.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is loaded and executed by the processor, the elevator health status assessment method according to any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: comprising a processor and a memory, wherein: The memory is used to store computer programs; The processor is used to load and execute the computer program so that the electronic device executes the elevator health status assessment method according to any one of claims 1 to 7.

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