An elevator health degree evaluation system

Abstract

The application provides an elevator health degree evaluation system, relates to the technical field of elevator health degree evaluation, and can reflect the complex interaction between elevators in the actual running environment by constructing the vibration data of key nodes and the mapping relationship between the vibration data and the working condition data of each elevator in the elevator group; the health conditions of each key component of the elevator are accurately reflected by combining the corrected data with multi-index weighted scoring, and the comprehensive health evaluation of the whole elevator group is further realized by designing the redundancy principle. By combining the vibration data collected by the load test and the machine learning technology, the application quantifies and eliminates the interference of the adjacent elevator on the vibration of the elevator to be evaluated, corrects the vibration signal, effectively avoids the misjudgment caused by the interference of the adjacent elevator, improves the accuracy and stability of the elevator health degree evaluation, supports the dynamic monitoring and early warning of the elevator group under different running states, and improves the running safety guarantee capability and maintenance management efficiency of the elevator group.

Description

An elevator health assessment system Technical Field

[0001] This invention relates to the field of elevator health assessment technology, specifically to an elevator health assessment system. Background Technology

[0002] With the widespread construction of modern high-rise buildings and large commercial complexes, elevator groups, as core facilities for vertical transportation, are receiving increasing attention for their safety and operational reliability. Elevator health assessment, as a crucial means of ensuring passenger safety and efficient equipment operation, relies on the accurate monitoring and analysis of the vibration status of key elevator components. In existing technologies, most health monitoring systems primarily rely on vibration data from individual elevators for diagnosis, often neglecting the complex vibration interference generated by the mutual influence of multiple elevators operating simultaneously within an elevator group. Furthermore, load changes and operating states of adjacent elevators significantly affect the vibration signals of the elevator being evaluated; without differentiation and correction, misjudgments and omissions can easily occur, affecting the accuracy and reliability of the health assessment. In actual operating environments, the vibration signals of elevator groups are complex and influenced by multiple factors; the lack of systematic interference identification and elimination techniques makes it difficult to achieve a scientific assessment of the overall health status of the elevator group.

[0003] In the prior art, CN118701900A discloses an elevator health evaluation system and method. This system includes a parameter acquisition module and a health evaluation module. The parameter acquisition module collects real-time data of elevator health indicators for the target elevator. These indicators include vibration acceleration, elevator car noise, elevator car temperature, car door opening and closing time, and door closing gap. The health evaluation module evaluates the health of the target elevator based on the real-time data of these indicators, obtaining a real-time health index. While this method can evaluate elevator health, it primarily relies on data from a single elevator and does not consider the vibration interference and operating condition coupling effects of multiple elevators within a group, leading to reduced accuracy in the final health evaluation.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide an elevator health evaluation system to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] An elevator health assessment system, specifically including:

[0008] The data acquisition module is used to collect data on the elevators to be evaluated in the elevator group. The data includes the first vibration data of the elevator to be evaluated during the load test and the second vibration data after each round of maintenance. The module also collects the operating condition data of each other elevator in the elevator group simultaneously.

[0009] The data analysis module is used to analyze the mapping relationship between the working condition data and the first vibration data in the load test, and to quantify the impact of the other elevators in the elevator group on the elevator to be evaluated based on the mapping relationship.

[0010] A data correction module is used to generate a vibration offset based on a mapping relationship, and to correct the second vibration data based on the vibration offset to generate corrected data.

[0011] The health evaluation module is used to combine correction data and first vibration data to generate a health score for the elevator to be evaluated, and to treat the remaining elevators in the elevator group as elevators to be evaluated in turn, so as to achieve a health evaluation of the entire elevator group.

[0012] Preferably, the operating condition data includes operating status, load weight, and elevator distance between the elevator to be evaluated, and the first vibration data collected by the elevator to be evaluated in the load test includes independent vibration data and coordinated vibration data.

[0013] Preferably, the specific steps of the load test are as follows:

[0014] S101: The process of all elevators in the elevator group moving from the bottom floor to the top floor and then back to the initial position is defined as an operating cycle;

[0015] S102: The elevator to be evaluated shall be run unloaded for at least two operating cycles, while the other elevators in the elevator group shall not be running, and the vibration data collected by the elevator to be evaluated during this process shall be calibrated as independent vibration data.

[0016] S103: The elevator to be evaluated shall be run unloaded for at least two operating cycles, and the other elevators in the elevator group shall also be run unloaded for at least two operating cycles. The vibration data collected by the elevator to be evaluated during this process shall be labeled as coordinated vibration data.

[0017] S104: Change the operating status and load weight of the remaining elevators in the elevator group and repeat step S103 to obtain several sets of coordinated vibration data.

[0018] Preferably, both the first vibration data and the second vibration data include the average vibration amplitude and the main vibration frequency, and both types of vibration data are collected at key nodes of the elevator to be evaluated, including the car, guide rail, traction sheave, and brake.

[0019] Preferably, the logic for analyzing the mapping relationship between the operating condition data and the first vibration data is as follows:

[0020] For each key node, calculate the difference between the average vibration amplitude and the main vibration frequency between each group of coordinated vibration data and independent vibration data, and use the two differences together as the vibration offset.

[0021] For each key node, a mapping relationship between its vibration offset and the combination of operating condition data is constructed based on machine learning algorithms.

[0022] Preferably, during later maintenance, several sets of second vibration data are collected after each later maintenance, and the second vibration data are corrected according to the mapping relationship and the working condition data during the later maintenance.

[0023] Preferably, the logic for generating correction data is as follows:

[0024] For each critical node, calculate the average vibration amplitude and principal vibration frequency of each set of second vibration data;

[0025] For each critical node, based on the operating condition data during later maintenance and in conjunction with the corresponding mapping relationship, the vibration offset corresponding to that operating condition data is calculated.

[0026] For each critical node, the average vibration amplitude and main vibration frequency calculated from the second vibration data are subtracted from the vibration offset to generate correction data, thus completing the correction of each set of second vibration data.

[0027] Preferably, the logic for generating a health score for the elevator to be evaluated by combining the correction data and the first vibration data is as follows:

[0028] Using the first vibration data and the physical performance of the elevator as a reference, the reference vibration amplitude and reference vibration frequency are obtained. The reference vibration amplitude is the sum of the average vibration amplitude of the independent vibration data and the preset maximum amplitude increment, and the reference vibration frequency is the natural vibration frequency of the elevator to be evaluated.

[0029] For each key node, calculate the difference between each set of correction data and the reference vibration amplitude and reference vibration frequency. The difference between the average vibration amplitude corresponding to the correction data and the reference vibration amplitude is calibrated as the first difference, and the absolute difference between the main vibration frequency corresponding to the correction data and the reference vibration frequency is calibrated as the second difference.

[0030] The first difference is standardized using the largest amplitude increment, and the second difference is standardized using the reference vibration frequency. After standardization, the values ​​are weighted and the average of all weighted values ​​is taken to generate a health score for each key node. The health score is negatively correlated with the first difference and positively correlated with the second difference.

[0031] The importance of each key node is determined based on the physical performance of the elevator. After normalization, it is used as the weight corresponding to the key node. This weight is then used to weight the health score of the key node to generate the health score of the elevator to be evaluated.

[0032] The preferred logic for evaluating the overall health of the elevator group is as follows:

[0033] All elevators in the elevator group are treated as elevators to be evaluated in turn, and their health scores are calculated.

[0034] The health scores of all elevators to be evaluated are compared with the preset scoring thresholds in turn, and the elevators to be evaluated are divided into two states, healthy and unhealthy, based on the comparison results, in order to reflect the operational risks of the elevators to be evaluated.

[0035] The percentage of elevators in an unhealthy state within the elevator group is statistically analyzed and compared with the preset design redundancy. Based on the comparison results, the elevator group as a whole is divided into two states: healthy and unhealthy, which are used to reflect the overall load capacity of the elevator group.

[0036] Compared with the prior art, the beneficial effects of the present invention are:

[0037] This invention constructs vibration data of key nodes and their mapping relationship with the operating condition data of each elevator in the elevator group, reflecting the complex interactions between elevators in the actual operating environment. By combining the corrected data with multi-index weighted scoring, it accurately reflects the health status of each key component of the elevator and further achieves a comprehensive health evaluation of the entire elevator group through the design redundancy principle. Overall, this invention combines multi-condition vibration data collected from load tests with machine learning technology to quantify and eliminate interference from neighboring elevators, achieving precise correction of vibration signals. This not only effectively avoids misjudgments caused by interference from neighboring elevators, improving the accuracy and stability of elevator health evaluation, but also supports dynamic monitoring and early warning of the elevator group under different operating conditions, enhancing the elevator group's operational safety assurance capabilities and maintenance management efficiency. Attached Figure Description

[0038] Figure 1 is a schematic diagram of the module structure of the present invention;

[0039] Figure 2 is a schematic diagram of the overall process of the present invention;

[0040] Figure 3 is a schematic diagram of the load test process in this invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0042] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0043] Example:

[0044] Please refer to Figures 1-3. This invention provides a technical solution:

[0045] An elevator health assessment system specifically includes: a data acquisition module, a data analysis module, a data correction module, and a health assessment module.

[0046] The data acquisition module is used to collect data on the elevators under evaluation that are undergoing load testing and subsequent maintenance within the elevator group. It collects the first vibration data of the elevator under evaluation during the load test and the second vibration data during the subsequent maintenance. Simultaneously, it collects the operating condition data of each other elevator in the elevator group. The operating condition data includes the operating status, load weight, and elevator distance from the elevator under evaluation. Both the first and second vibration data include vibration amplitude and main vibration frequency. Both types of vibration data are collected at the key nodes of the elevator under evaluation, including the car, guide rails, traction sheave, and brake. These parts are designated as critical points because the elevator car is the main load-bearing component for passengers and goods. Its vibration reflects the overall operational stability, and its vibration directly affects ride comfort and safety. Abnormal vibration often indicates malfunctions in the traction system, guide rails, or suspension components. The guide rails guide the vertical movement of the car and counterweight. The fit between the guide rails and the car directly affects the smoothness of movement. Wear, deformation, or poor lubrication can easily cause localized abnormal vibrations with noticeable characteristics. The traction sheave transmits driving force through steel cables, driving the car up and down. Bearing wear, imbalance, or surface damage can generate significant vibrations and affect the safe operation of the entire elevator system. The brake ensures the elevator remains stationary at the stop position and is a critical safety component. Wear on its friction plates or uneven braking force can cause abnormal vibrations or noise. These parts are common areas of elevator malfunction, are crucial to elevator safety, and are easy to monitor for vibration signals. Therefore, inspecting these parts can effectively warn of potential risks and assess the elevator's health.

[0047] The first vibration data collected in the load test includes independent vibration data and coordinated vibration data. The specific steps of the load test are as follows:

[0048] S101: The process of all elevators in the elevator group moving from the bottom floor to the top floor and then back to the initial position is defined as an operating cycle;

[0049] S102: The elevator to be evaluated shall be run unloaded for at least two operating cycles, while the other elevators in the elevator group shall not be running, and the vibration data collected during this process shall be calibrated as independent vibration data.

[0050] S103: The elevator to be evaluated shall run unloaded for at least two operating cycles, while the other elevators in the elevator group shall also run normally for at least two operating cycles, and the vibration data collected during this process shall be calibrated as coordinated vibration data.

[0051] S104: Change the operating status (i.e., running or not running) and load weight of the remaining elevators in the elevator group and repeat step S103 to obtain several sets of coordinated vibration data.

[0052] It is understandable that when collecting the first vibration data during load testing, the manufacturer can conduct the test on the elevators themselves, or it can be done immediately after the elevator group is installed and accepted. When collecting the second vibration data during later maintenance, it can be done periodically (e.g., weekly, monthly, depending on expert experience). Specifically, assume there are six identical standard passenger elevators in the elevator group, numbered 1 to 6, with a weight limit of 1000 kg and a design redundancy of two (meaning four elevators at full load are sufficient for normal transport needs). The maintenance frequency is once a month. Taking elevator number 1 as an example, if the manufacturer conducts the load test, the risk of accelerated aging due to multiple tests does not need to be considered. Therefore, a full-factor testing method can be used, that is, when repeating step S103, all operating conditions are traversed, and based on each combination of operating conditions, the load weight of the remaining elevators is further changed. When changing the load weight, an increase in passenger capacity can be simulated in increments of 75 kg, with 1000 kg used when the elevator's weight limit is exceeded, i.e., 75 kg, 150 kg, ..., 975 kg, 1000 kg. The advantage of this method is the ability to collect a large number of data samples, but the disadvantage is the high testing cost. If the load test is conducted immediately after the elevator group is installed and accepted, an orthogonal test method can be used, with operating status and load weight as test factors, and a reasonable number of levels set for testing. During later maintenance, at the beginning of each month, several sets of vibration data from daily operation are collected for the elevators to be evaluated in the elevator group as secondary vibration data, and the operating condition data of the other elevators are collected simultaneously. Ultimately, for elevator number 1, one set of independent vibration data and several sets of coordinated vibration data will be collected, which reflect the intrinsic performance of the elevator group; at the same time, several sets of secondary vibration data will be collected each month, which reflect the real-time status of the elevator group. Both the coordinated vibration data and the secondary vibration data correspond to a combination of operating condition data of the other elevators in the elevator group.

[0053] In the load test, independent vibration data represents the pure vibration characteristics without interference from neighboring elevators, providing a stable and reliable vibration benchmark for subsequent anomaly diagnosis. Cooperative vibration data, on the other hand, represents vibration information under different operating states and load combinations of neighboring elevators, used to simulate the complex situation of mutual interference between elevators in the actual working environment of the elevator group. The fact that at least two operating cycles are run each time data is collected is to take the average value and avoid the influence of accidental factors on the accuracy of the data.

[0054] The first and second vibration data cover the elevator's vibration performance under ideal controlled conditions and actual operating conditions. For the elevator being evaluated, its vibration data mainly includes three components: 1. The vibration inherent in the elevator itself when unloaded; 2. The vibration caused by the load when a load is applied, which is related to the load and the material properties of that part, and is usually positively correlated with the load; 3. The influence of other elevators in the elevator group. During the elevator health evaluation process, since other elevators will affect the elevator being evaluated, if this influence is not eliminated, it may lead to misjudgments during later maintenance. Taking the guide rail as an example, under normal circumstances and without damage, its material properties are not affected, and the vibration caused by the load when a load is applied is not large. Considering this component alone, it does not exceed the allowable range. However, if the influence of other elevators in the elevator group is added, it may lead to an overestimation of the actual collected second vibration data, resulting in the erroneous conclusion that "the guide rail has material damage."

[0055] The vibration data of the elevator to be evaluated are calibrated into a set. The three types of components are respectively labeled as ~ So, in the first vibration data:

[0056] Independent vibration data This can be expressed as:

[0057]

[0058] Coordinated vibration data Represented as:

[0059]

[0060] Second vibration data Represented as:

[0061]

[0062] By combining the second vibration data with the operating condition data and then comparing it with the first vibration data, interference from adjacent elevators can be eliminated, thereby improving the authenticity and reliability of the health assessment.

[0063] The data analysis module is used to analyze the correlation between the working condition data and the first vibration data in the load test, and to quantify the impact of the other elevators in the elevator group on the elevator to be evaluated based on the analysis results.

[0064] The logic for analyzing the correlation between the operating condition data and the first vibration data is as follows:

[0065] For each key node, the average vibration amplitude and principal vibration frequency of the independent vibration data and each group of coordinated vibration data are calculated separately, and can be displayed as follows:

[0066]

[0067]

[0068] In the formula Indicates the first Independent vibration data of key nodes, These represent the corresponding average vibration amplitude and principal vibration frequency, respectively. No. The first key node Group coordinated vibration data, These represent the corresponding average vibration amplitude and principal vibration frequency, respectively; subscripts , These represent the indexes of key nodes and the indexes of coordinated vibration data during the load test, respectively. Since a combination of data under a specific load condition corresponds to a set of coordinated vibration data, therefore... It can also be used as an index for combinations of load test data; in other words, The actual meaning is that "the combination of operating data of the remaining elevators in the elevator group is the first..." When planting, the elevator to be evaluated is the first The coordinated vibration data corresponding to each key node.

[0069] For each key node, calculate the difference between the average vibration amplitude and the principal vibration frequency between each set of coordinated vibration data and independent vibration data. These two differences are then combined to form the vibration offset, which can be expressed as follows:

[0070]

[0071] In the formula Indicates the first The first key node The vibration offset corresponding to the group's coordinated vibration data. It's easy to see from the expression for the vibration offset that its essence is the third of the three types of components mentioned above: the influence of other elevators within the elevator group. .

[0072] For each key node, a mapping relationship between its vibration offset and the combination of operating condition data is constructed based on machine learning algorithms. Correlation analysis of the operating condition data and the first vibration data is completed to quantify the impact of the other elevators in the elevator group on the elevator to be evaluated.

[0073] The operating data of each of the remaining elevators in the elevator group are represented as a set. The set contains:

[0074]

[0075] In the formula This indicates the elevator's number. These represent the elevator's operating status, load weight, and distance from the elevator under evaluation, respectively. The operating status is represented by a binary label, with 0 indicating no operation and 1 indicating operation. The operating data is then combined and represented as follows: The set then has:

[0076]

[0077] In the formula Indicates the first Combination of various working condition data, This represents the set of elevator numbers excluding the elevator to be evaluated. In this embodiment, since elevator number 1 is the elevator to be evaluated, then... .

[0078] When constructing the mapping relationship, the machine learning algorithms used include decision tree regression, random forest regression, or neural network models, which can be selected based on expert experience. The final mapping relationship can be expressed as:

[0079]

[0080] In the formula This represents the mapping function obtained by fitting the data using a machine learning algorithm.

[0081] By constructing this mapping relationship, the impact of different operating states, load weights, and elevator spacing of other elevators on the elevator under evaluation can be reflected. In subsequent daily operation, the mapping relationship can be used to accurately predict vibration offset, thereby ensuring the effectiveness of correction, making the corrected vibration data more accurately reflect the elevator's own state, reducing misjudgments due to interference from neighboring elevators, and enhancing the reliability of anomaly identification.

[0082] The data correction module is used to correct the second vibration data based on the analysis results and the operating condition data in the later maintenance, and to generate corrected data.

[0083] The logic for correcting the second vibration data based on the analysis results and the operating condition data during subsequent maintenance, and generating the corrected data, is as follows:

[0084] For each key node, the average vibration amplitude and principal vibration frequency of the second vibration data are calculated and can be displayed as follows:

[0085]

[0086] In the formula Indicates the first The first key node Group 2 vibration data, These represent the corresponding average vibration amplitude and principal vibration frequency, respectively, with subscripts indicating the frequency. This serves as an index for the second set of vibration data. It's understandable that each set of second vibration data corresponds to a set of operating condition data from later maintenance procedures. Therefore, similar to the data processing method in load tests, the subscript here... It can also be used as an index for the combination of operating condition data obtained on the same day during later maintenance.

[0087] For each critical node, based on the operating condition data from subsequent maintenance and the corresponding mapping relationship, the vibration offset corresponding to that operating condition data is calculated. ;

[0088] For each critical node, the average vibration amplitude and principal vibration frequency calculated from each set of second vibration data are subtracted from the vibration offset to generate correction data. The correction of the second vibration data is completed, and the formula for calculating the correction data is:

[0089]

[0090] Represented in set form as:

[0091]

[0092] These represent the average vibration amplitude and principal vibration frequency corresponding to this set of corrected data, respectively. As can be seen from the expression for the corrected data, after correction, the corrected data is equivalent to eliminating the influence of other elevators in the elevator group. Therefore, only the vibration that exists under no-load conditions remains. The amount of vibration caused by the load when a load is applied. Two types of components are used to avoid affecting the evaluation results of the elevators to be evaluated in the elevator group.

[0093] The health assessment module is used to combine correction data and first vibration data to generate a health score for the elevator to be evaluated, and to treat the remaining elevators in the elevator group as elevators to be evaluated in turn, so as to achieve a health assessment of the entire elevator group.

[0094] The logic for generating a health score for the elevator to be evaluated by combining the correction data and the first vibration data is as follows:

[0095] Using the first vibration data and the physical performance of the elevator as a reference, the reference vibration amplitude and reference vibration frequency are obtained. The reference vibration amplitude is the sum of the average vibration amplitude of the independent vibration data and the preset maximum amplitude increment, and the reference vibration frequency is the natural vibration frequency of the elevator to be evaluated.

[0096] For each key node, calculate the difference between each set of correction data and the reference vibration amplitude and reference vibration frequency. The difference between the average vibration amplitude corresponding to the correction data and the reference vibration amplitude is calibrated as the first difference, and the absolute difference between the main vibration frequency corresponding to the correction data and the reference vibration frequency is calibrated as the second difference.

[0097] The first difference is standardized using the largest amplitude increment, and the second difference is standardized using the reference vibration frequency. After standardization, a weighted average is applied, and the average of all weighted values ​​is taken to generate a health score for each key node. The health score is negatively correlated with the first difference and positively correlated with the second difference. The formula for calculating the health score is as follows:

[0098]

[0099] In the formula Indicates the first Health score at key points, Indicates the increment factor. Indicates the reference vibration frequency. , The weights represent the normalization values, which are usually set to equal weights, but can also be adjusted according to actual needs. This represents the sensitivity factor, which is generally set to a positive odd number to avoid affecting the sign of the base.

[0100] in This represents the maximum amplitude increment, indicating the change in vibration amplitude caused by the load when the elevator is fully loaded; it is also known as the component. The theoretically permissible maximum value. The reasonable range of this variation is generally defined by elevator safety standards or manufacturer technical specifications, and typically cannot exceed a certain percentage of the elevator's vibration amplitude when unloaded. In this embodiment, the elevator's permissible vibration amplitude increment when fully loaded is no higher than 20% of the vibration amplitude when unloaded; therefore, the increment factor can be set to 0.2.

[0101] As can be seen from the calculation formula of the critical node health score, the first difference reflects the difference between the average vibration amplitude during daily operation and the maximum theoretical value. It can be understood that, after eliminating the influence of other elevators, the average vibration amplitude corresponding to the corrected data is essentially equivalent to a component. With weight The sum of the two differences should, under normal circumstances, not exceed the baseline vibration amplitude. Therefore, during normal use, the first difference is negative, and after normalization, the base is also negative. Since the sensitivity factor is a positive odd number and does not change the sign of the base, the exponential function has a negative value, resulting in a larger overall health score. Conversely, when the first difference increases, the base increases, leading to a decrease in the health score. Furthermore, when a critical point of the elevator malfunctions, the average vibration amplitude during daily operation increases abnormally, exceeding the baseline vibration amplitude. In this case, the first difference is positive, and the base is also positive. The sensitivity factor exponentially amplifies this, causing a sharp decrease in the health score, thus better evaluating and warning about the elevator's health. The second difference reflects the change in the main vibration frequency caused by the load. It is understandable that when the elevator's main vibration frequency is close to the baseline vibration frequency (i.e., the elevator's natural vibration frequency), there may be a risk of resonance. Therefore, the larger the absolute difference between the two, the lower the risk of elevator operation and the higher the health score.

[0102] The importance of each key node is determined based on the physical performance of the elevator. After normalization, it is used as the weight corresponding to the key node. This weight is then used to weight the health score of the key node to generate the health score of the elevator to be evaluated.

[0103] The importance of each key node can be scored based on expert experience, and the scores are then normalized before analysis. By weighted summation, the health score of the elevator to be evaluated can be obtained, which reflects the material risks at key points of the elevator and the resonance risks during operation, and comprehensively evaluates its health.

[0104] The logic for evaluating the overall health of the elevator group is as follows:

[0105] All elevators in the elevator group are treated as elevators to be evaluated in turn, and their health scores are calculated.

[0106] The health scores of all elevators to be evaluated are compared with the preset scoring thresholds in turn, and the elevators to be evaluated are divided into two states: healthy and unhealthy, based on the comparison results.

[0107] The percentage of elevators in an unhealthy state within the elevator group is statistically analyzed, and this percentage is compared with the preset design redundancy. Based on the comparison results, the elevator group as a whole is divided into two states: healthy and unhealthy.

[0108] In simple terms, the health status of an elevator reflects the risks associated with its operation, while the health status of an elevator group reflects its ability to meet normal transportation needs. Even within a healthy elevator group, there may be unhealthy elevators, but the group as a whole still meets normal transportation requirements; the unhealthy elevators can be repaired individually. Conversely, if the elevator group is unhealthy, it is considered that the entire group cannot meet normal transportation needs. In practical applications, evaluating the health status of elevator groups can serve as a reference for event planning in scenarios such as hotels and shopping malls. For example, when the elevator group is healthy, events can proceed normally and can meet the transportation needs of large passenger flows. When the elevator group is unhealthy, if events are to continue, measures such as limiting passenger flow or encouraging people to use the stairs need to be taken to avoid exceeding the elevator group's capacity and reducing safety risks.

[0109] In this embodiment, a health assessment is performed on the entire elevator group. Elevators 1 through 6 are treated as elevators to be evaluated, and their health scores are calculated (the specific calculation process is not detailed here). If the health score of any elevator is lower than a preset threshold, that elevator is considered to have operational risks and is classified as unhealthy. A redundancy of 2 elevators (33%) is designed. When the proportion of unhealthy elevators in the elevator group does not exceed this value, the elevator group is considered to still meet normal transportation needs and is in a healthy state. Conversely, when the proportion of unhealthy elevators exceeds this value, the elevator group is considered to be unable to meet normal transportation needs and is therefore in an unhealthy state.

[0110] By sequentially evaluating each elevator in the elevator group, a health check of each elevator in the entire group is achieved, avoiding missed detections of single-point faults. This method ensures comprehensive monitoring of the elevator group's operational safety, meeting the high requirements for overall system safety in actual operation. Furthermore, by statistically analyzing the percentage of unhealthy elevators and comparing it with the design redundancy (33% in this example), and comprehensively considering the number of backup elevators and the system's fault tolerance, the method fully embodies the principle of system-level safety redundancy for the elevator group, avoiding excessive alarms due to isolated individual elevator anomalies.

[0111] The overall process in this embodiment is as follows:

[0112] S1: Conduct load tests and subsequent maintenance on the elevators to be evaluated in the elevator group, collect the first vibration data of the elevator to be evaluated in the load test and the second vibration data in the subsequent maintenance, and simultaneously collect the operating condition data of each other elevator in the elevator group.

[0113] S2: Analyze the correlation between the working condition data and the first vibration data in the load test, and quantify the impact of the other elevators in the elevator group on the elevator to be evaluated based on the analysis results;

[0114] S3: Correct the second vibration data based on the analysis results and the operating condition data during later maintenance, and generate corrected data;

[0115] S4: Combine the correction data and the first vibration data to generate a health score for the elevator to be evaluated, and treat the remaining elevators in the elevator group as elevators to be evaluated in turn, so as to achieve a health evaluation of the entire elevator group.

[0116] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0117] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0118] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0119] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. An elevator health assessment system, characterized in that, Specifically, it includes: The data acquisition module is used to collect data on the elevator to be evaluated within the elevator group. This data includes the first vibration data of the elevator to be evaluated during the load test and the second vibration data after each round of maintenance. Simultaneously, it collects the operating condition data of each of the other elevators in the elevator group. The operating condition data includes the operating status, load weight, and elevator spacing with the elevator to be evaluated. The first vibration data collected by the elevator to be evaluated during the load test includes independent vibration data and coordinated vibration data. The specific steps of the load test are as follows: S101: Define the process of all elevators in the elevator group moving from the bottom floor to the top floor and then back to the initial position as one operating cycle; S102: Run the elevator to be evaluated unloaded for at least two operating cycles, while the other elevators in the elevator group do not operate, and label the vibration data collected by the elevator to be evaluated during this process as independent vibration data; S103: Run the elevator to be evaluated unloaded for at least two operating cycles, and simultaneously, the other elevators in the elevator group also run unloaded for at least two operating cycles, and label the vibration data collected by the elevator to be evaluated during this process as coordinated vibration data; S104: Change the elevator... The operating status and load weight of the remaining elevators in the group are recorded, and step S103 is repeated to obtain several sets of coordinated vibration data. A data analysis module is used to analyze the mapping relationship between the operating condition data and the first vibration data in the load test, and to quantify the impact of the remaining elevators in the elevator group on the elevator to be evaluated based on the mapping relationship. The logic for analyzing the mapping relationship between the operating condition data and the first vibration data is as follows: for each key node, the difference between the average vibration amplitude and the main vibration frequency between each set of coordinated vibration data and independent vibration data is calculated, and the two differences are used together as the vibration offset. For each key node, a mapping relationship between its vibration offset and the combination of operating condition data is constructed based on a machine learning algorithm. A data correction module is used to generate the vibration offset based on the mapping relationship, and to correct the second vibration data based on the vibration offset to generate corrected data. A health evaluation module is used to combine the corrected data and the first vibration data to generate a health score for the elevator to be evaluated, and to treat the remaining elevators in the elevator group sequentially as elevators to be evaluated, so as to achieve a health evaluation of the entire elevator group.

2. The elevator health assessment system according to claim 1, characterized in that: Both the first vibration data and the second vibration data include the average vibration amplitude and the main vibration frequency. Both types of vibration data are collected at the key nodes of the elevator to be evaluated, including the car, guide rail, traction sheave, and brake.

3. The elevator health assessment system according to claim 2, characterized in that: During later maintenance, several sets of second vibration data were collected after each maintenance, and the second vibration data were corrected based on the mapping relationship and the operating condition data during the later maintenance.

4. The elevator health assessment system according to claim 3, characterized in that: The logic for generating correction data is as follows: For each key node, calculate the average vibration amplitude and main vibration frequency of each set of second vibration data; for each key node, calculate the vibration offset corresponding to the working condition data based on the working condition data in the later maintenance and the corresponding mapping relationship; for each key node, subtract the vibration offset from the average vibration amplitude and main vibration frequency calculated from the second vibration data to generate correction data, thus completing the correction of each set of second vibration data.

5. The elevator health assessment system according to claim 4, characterized in that: The logic for generating a health score for the elevator under evaluation by combining calibration data and first vibration data is as follows: Using the first vibration data and the elevator's physical performance as references, a reference vibration amplitude and a reference vibration frequency are obtained. The reference vibration amplitude is the sum of the average vibration amplitude of independent vibration data and the preset maximum amplitude increment. The reference vibration frequency is the inherent vibration frequency of the elevator under evaluation. For each key node, the difference between each set of calibration data and the reference vibration amplitude and reference vibration frequency is calculated sequentially. The difference between the average vibration amplitude corresponding to the calibration data and the reference vibration amplitude is designated as the first difference, and the absolute difference between the main vibration frequency corresponding to the calibration data and the reference vibration frequency is designated as the second difference. The first difference is standardized using the maximum amplitude increment, and the second difference is standardized using the reference vibration frequency. After standardization, weighting is performed, and the average of all weighted values ​​is taken to generate a health score for each key node. The health score is negatively correlated with the first difference and positively correlated with the second difference. The importance of each key node is determined based on the physical performance of the elevator. After normalization, it is used as the weight corresponding to the key node. This weight is then used to weight the health score of the key node to generate the health score of the elevator to be evaluated.

6. The elevator health assessment system according to claim 4, characterized in that: The logic for evaluating the health of the entire elevator group is as follows: All elevators in the group are treated sequentially as elevators to be evaluated, and their health scores are calculated. The health scores of all elevators to be evaluated are compared sequentially with preset scoring thresholds. Based on the comparison results, the elevators to be evaluated are divided into two states: healthy and unhealthy, reflecting the operational risks of the elevators to be evaluated. The percentage of elevators in the group that are in an unhealthy state is calculated and compared with the preset design redundancy. Based on the comparison results, the entire elevator group is divided into two states: healthy and unhealthy, reflecting the overall load capacity of the elevator group.

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