An abnormal intelligent diagnosis method for a visible light communication-based lift

Abstract

The application provides an abnormal intelligent diagnosis method for a lifting elevator based on visible light communication, and relates to the technical field of elevator intelligent monitoring, comprising the following steps: obtaining running data and visible light communication link data in the running process of the lifting elevator; determining a running stage according to the running data and mapping the visible light communication link data to the corresponding running stage; extracting light link state features to generate running light link fingerprints; determining a reference light link template according to the running data and the running stage, and comparing the reference light link template with the running light link fingerprints to obtain abnormal residuals; determining an abnormal type according to the association between the abnormal residuals and the running data, generating an abnormal auxiliary diagnosis result, and updating the reference light link template according to the confirmation result. The method can improve the elevator abnormal source distinguishing ability and diagnosis interpretability.

Description

Technical Field

[0001] This application belongs to the field of elevator intelligent monitoring technology, specifically involving an intelligent diagnostic method for elevator anomalies based on visible light communication. Background Technology

[0002] Elevators are widely used in educational buildings, office buildings, laboratories, dormitories, hospitals, industrial parks, and commercial buildings. Their operational status directly affects the safety of personnel passage and the reliability of building equipment operation. With the development of intelligent building equipment and safety monitoring technology, how to identify abnormal states during elevator operation in a timely and accurate manner has become an important technical issue in elevator safety monitoring and auxiliary operation and maintenance.

[0003] Current elevator anomaly monitoring typically relies on floor signals, leveling signals, door zone signals, and alarm codes output by the elevator control system, or on external sensors such as accelerometers, vibration sensors, current sensors, and door magnetic sensors to collect operational data. The elevator's operating status is then analyzed using threshold judgments, statistical analysis, or intelligent diagnostic models. Some solutions also upload the collected data to a remote monitoring platform for operational trend analysis and anomaly alerts.

[0004] However, in existing buildings or university buildings, the underlying data interface of elevator controllers is often limited by equipment manufacturer protocols, maintenance permissions, and safety management requirements. Furthermore, the deployment of external sensors may be affected by installation space, wiring conditions, and renovation costs. Simultaneously, there are issues such as inconsistent sampling times between different data sources, unclear correspondence between operational phases, and difficulty in distinguishing the source of anomalies. For example, floor positioning deviations, door zone obstruction, car vibration, sensor offset, and communication link anomalies may exhibit similar fluctuation characteristics in externally acquired data, leading to a single diagnostic basis and insufficient accuracy in distinguishing anomaly types. Summary of the Invention

[0005] This application provides a method for intelligent diagnosis of elevator anomalies based on visible light communication to solve the problems mentioned above.

[0006] The technical solution adopted in this application is as follows: This application provides an intelligent diagnostic method for elevator anomalies based on visible light communication, characterized by including: The system acquires operational data and visible light communication link data during the operation of the elevator. The visible light communication link data is generated by visible light communication nodes located in the elevator car, landings, shaft sections, and / or door areas. The operating stage of the elevator is determined based on the operating data, and the visible light communication link data is mapped to the corresponding operating stage. Based on the mapped visible light communication link data, optical link status features are extracted, and the operating optical link fingerprint of the elevator is generated according to the optical link status features under each operating stage. Based on the running data and the running stage, a corresponding reference optical link template is determined from the preset reference optical link template library, and the running optical link fingerprint is compared with the reference optical link template to obtain abnormal residuals; Based on the correlation between the abnormal residuals and the operating data, the abnormal type of the elevator is determined, an abnormal auxiliary diagnosis result is generated, and the reference optical link template is updated based on the confirmation result of the abnormal auxiliary diagnosis result.

[0007] According to one embodiment of this application, determining the operating stage of the elevator based on the operating data and mapping the visible light communication link data to the corresponding operating stage includes: Configure a unified time base for the operational data and the visible light communication link data; Based on the speed changes, acceleration changes, leveling status, door zone status, and / or door opening / closing status in the operating data, the switching time of the operating phase of the elevator is determined. Based on the switching time of the operation phase, a phase time window corresponding to each operation phase is generated; According to the unified time reference, the visible light communication link data is allocated to the corresponding stage time window to obtain the stage link data set corresponding to each operation stage.

[0008] According to one embodiment of this application, determining the corresponding reference optical link template from a preset reference optical link template library based on the operating data and the operating stage includes: The template matching parameters are determined based on the operation data. The template matching parameters include at least one of the following: operation direction, starting floor, target floor, current floor segment, speed range, load range, door status, and operation stage. From the preset reference optical link template library, determine a reference optical link template that matches the template matching parameters; The reference optical link template is an optical link status feature template established according to the template matching parameters under normal operating conditions.

[0009] According to one embodiment of this application, after allocating the visible light communication link data to the corresponding stage time window, the method further includes: Based on at least one of the following: changes in received light intensity, changes in bit error rate, changes in packet loss rate, and the number of consecutive missing optical identifiers, abnormal link sampling data in the stage link data set is identified; When the abnormal link sampling data meets the temporary occlusion condition, the abnormal link sampling data is marked as occlusion sampling data, and the occlusion sampling data is compensated based on adjacent sampling data within the same operation phase. When the abnormal link sampling data does not meet the temporary occlusion condition, the abnormal link sampling data is retained as abnormal candidate data for generating the running optical link fingerprint.

[0010] According to one embodiment of this application, comparing the running optical link fingerprint with the reference optical link template to obtain the abnormal residual includes: Based on the difference between the running optical link fingerprint and the reference optical link template, at least two of the following are calculated: position residual, motion residual, occlusion residual, communication residual, light source residual, and gate residual. Based on the aforementioned operational phase, configure corresponding residual weights for different types of abnormal residuals; A comprehensive anomaly score is generated based on different types of abnormal residuals and their corresponding residual weights. The position residual is used to characterize the deviation between the optical identification information and the floor status or level status; the motion residual is used to characterize the deviation between the optical link change and the speed or acceleration; the occlusion residual is used to characterize the sudden drop in light intensity or abnormal signal recovery; the communication residual is used to characterize the abnormal bit error rate, packet loss rate or signal-to-noise ratio; the light source residual is used to characterize the missing optical identification; and the door area residual is used to characterize the deviation between the door area optical link change and the door opening / closing status.

[0011] According to one embodiment of this application, the visible light communication link data is generated by a visible light communication transmitting node and a visible light communication receiving node; The visible light communication transmitting node includes LED transmitting modules installed at corresponding positions in the elevator car, landing, shaft section, door area and / or lifting test platform; The visible light communication receiving node includes a photodiode, an ambient light sensor, an image sensor, and / or a multi-channel optical receiving array; The data frames transmitted by the visible light communication transmitting node include at least one of the following: frame header, node number, floor identifier, door zone identifier, status code, diagnostic detection sequence, and check code; The visible light communication receiving node generates the optical identification information based on the data frame, and generates at least one of the received light intensity, communication quality information, and optical path change information based on the received signal.

[0012] According to one embodiment of this application, updating the reference optical link template based on the confirmation result of the abnormal auxiliary diagnosis includes: Based on the confirmation results, the currently running sample is determined to be a normal sample or an abnormal sample; When the current running sample is a normal sample, at least one of the feature mean, feature variance and normal threshold range of the reference optical link template under the corresponding running stage is updated based on the current running sample. When the current running sample is an abnormal sample, the running optical link fingerprint, abnormal residual and abnormal type corresponding to the current running sample are written into the abnormal sample database; Adjust the residual weights and / or anomaly determination thresholds for different operating stages based on the normal samples and / or the abnormal samples.

[0013] According to one embodiment of this application, generating abnormal auxiliary diagnostic results includes: Based on the anomaly type, the anomaly residual, the operational phase, and the operational data, generate the anomaly location, anomaly stage, anomaly evidence information, and auxiliary inspection suggestions; The location of the anomaly, the stage of the anomaly, the evidence information of the anomaly, and the auxiliary inspection suggestions are output to the auxiliary inspection object. The system receives a confirmation result from the auxiliary inspection object based on the abnormal auxiliary diagnostic result, and uses the confirmation result as the basis for updating the reference optical link template.

[0014] According to one embodiment of this application, the elevator includes an elevator in a campus building, an elevator experimental platform, or a simulated elevator platform; The operational data comes from external acceleration sensors, external vibration sensors, external door magnetic sensors, external photoelectric switches, lifting test platform control signals and / or authorized elevator operation status interface data. The visible light communication link data includes at least one of the following: optical identification information, received light intensity, signal-to-noise ratio, bit error rate, packet loss rate, optical identification arrival time, multi-channel light intensity difference, light intensity fluctuation frequency, and optical path obstruction duration.

[0015] This application also provides an intelligent diagnosis of elevator anomalies based on visible light communication, including: The data acquisition module is used to acquire the operating data and the visible light communication link data; The operation phase determination module is used to determine the operation phase of the elevator based on the operation data, and to map the visible light communication link data to the corresponding operation phase; The optical link fingerprint generation module is used to extract optical link status features based on the mapped visible light communication link data, and generate the operating optical link fingerprint according to the optical link status features under each operating stage. The template comparison module is used to determine the corresponding reference optical link template from the preset reference optical link template library based on the running data and the running stage, and compare the running optical link fingerprint with the reference optical link template to obtain the abnormal residual; An anomaly diagnosis module is used to determine the anomaly type of the elevator based on the correlation between the anomaly residual and the operating data, and to generate the anomaly auxiliary diagnosis result. The template update module is used to update the reference optical link template based on the confirmation result of the abnormal auxiliary diagnosis result.

[0016] Due to the adoption of the above technical solution, the beneficial effects achieved by this application are as follows: This application obtains operational data and visible light communication link data during the operation of an elevator, and determines the operational stage of the elevator based on the operational data. This allows the visible light communication link data to be mapped to the corresponding operational stage for analysis, thereby avoiding mixed judgments of link changes under different operational stages and improving the stage consistency of the data on which anomaly diagnosis is based.

[0017] This application extracts optical link status features based on mapped visible light communication link data and generates operational optical link fingerprints based on the optical link status features at each operational stage. This enables the optical identification information, received light intensity, communication quality information, and optical path change information in the visible light communication link to be organized into a feature sequence reflecting the operating status of the elevator, thereby improving the ability to characterize floor passage, door zone changes, car movement status, and link health status.

[0018] This application determines the corresponding reference optical link template from a preset reference optical link template library based on the operating data and operating stage, so that the fingerprint of the currently operating optical link can be compared with the normal template under the same or similar operating conditions, thereby reducing the interference caused by different operating directions, different floor sections, different speed ranges or different door states to the anomaly judgment.

[0019] This application obtains abnormal residuals by comparing the operating optical link fingerprint with the reference optical link template, and determines the abnormal type of the elevator based on the correlation between the abnormal residuals and the operating data. This makes the abnormal diagnosis no longer rely solely on a single sensor data or a single threshold, but can combine different residual sources such as position residuals, motion residuals, obstruction residuals, communication residuals, light source residuals, and door area residuals for judgment, thereby improving the ability to distinguish abnormal sources.

[0020] This application configures a unified time base for operational data and visible light communication link data, and generates a phase time window based on the switching time of the operational phase. This enables data from different sampling frequencies and different acquisition sources to be correlated within the same operational phase, thereby improving the accuracy of multi-source data synchronization and phase mapping.

[0021] This application identifies abnormal link sampling data in the stage link data set, compensates for occlusion sampling data when the temporary occlusion condition is met, and retains it as abnormal candidate data when the temporary occlusion condition is not met. This can reduce the misleading effect of short-term occlusion by personnel, ambient light disturbance or short-term node loss on the diagnostic results, while retaining the basis for judging real anomalies.

[0022] This application sets up visible light communication transmitting nodes and visible light communication receiving nodes, and enables the transmitting nodes to send data frames containing frame headers, node numbers, floor identifiers, door zone identifiers, status codes, diagnostic detection sequences, and check codes. This allows for the acquisition of link data related to floors, door zones, node status, and communication quality on a low-cost hardware basis, thereby enhancing the engineering feasibility of the solution.

[0023] This application updates the baseline optical link template based on the confirmation results of the auxiliary diagnosis of anomalies. The results formed by manual confirmation, experimental annotation or maintenance feedback can be fed back to the template library, so that the baseline optical link template, residual weight and anomaly judgment threshold can be corrected with the accumulation of samples, thereby forming a closed loop of data acquisition, anomaly diagnosis, result confirmation and template update. Attached Figure Description

[0024] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a diagram illustrating the architecture of an intelligent diagnostic system for elevator malfunctions provided in an embodiment of this application. Figure 2 Flowchart of an intelligent diagnostic method for elevator anomalies based on visible light communication provided in this application embodiment; Figure 3 This is a schematic diagram of the visible light communication node arrangement provided in an embodiment of this application. Detailed Implementation

[0025] The technical solution of this application will be further described below with reference to the accompanying drawings and embodiments. It should be understood that the following embodiments are only used to illustrate this application and are not intended to limit the scope of protection of this application.

[0026] In the description of the embodiments of this application, the terms "first," "second," etc., are only used to distinguish different objects and do not indicate that there is a difference in order or importance between the objects; the term "multiple" can mean two or more; the term "and / or" is used to describe the association relationship between related objects, indicating that there can be three relationships, for example, A and / or B can mean that A exists alone, A and B exist simultaneously, or B exists alone. Unless otherwise explicitly stated, "visible light communication" in the embodiments of this application can be understood as a communication method that uses visible light signals for identification transmission, link status acquisition, or short-range information exchange.

[0027] The elevator described in this application embodiment can be a real elevator in a building, or an elevator experimental platform or a simulated elevator platform. For elevators in real buildings, this application embodiment preferably adopts a non-intrusive data acquisition method, which does not change the original safety control logic of the elevator, does not directly control the start and stop of the elevator, and does not replace the legal elevator inspection and testing results. For elevator experimental platforms or simulated elevator platforms, operating data and link data can be collected through experimental platform control signals, external sensors, and visible light communication nodes to verify the anomaly auxiliary diagnostic logic.

[0028] Figure 1 The architecture of an intelligent diagnostic system for elevator anomalies provided in an embodiment of this application is illustrated. For example... Figure 1 As shown, the system may include a visible light communication transmitting node, a visible light communication receiving node, a data acquisition module, an operation phase determination module, an optical link fingerprint generation module, a template comparison module, an anomaly diagnosis module, and a template update module.

[0029] Visible light communication transmitting nodes can be installed at corresponding locations in elevator cars, landings, shaft sections, door zones, and / or elevator test platforms. A visible light communication transmitting node may include an LED transmitting module, a microcontroller control module, a drive circuit, and a power supply module. The LED transmitting module can transmit visible light data frames, which may include at least one of the following: frame header, node number, floor identifier, door zone identifier, status code, diagnostic detection sequence, and checksum. Specifically, the node number distinguishes different transmitting nodes, the floor identifier identifies the floor or simulated floor corresponding to the transmitting node, the door zone identifier identifies the door zone or door opening / closing area corresponding to the transmitting node, the status code indicates the transmitting node's own status, the diagnostic detection sequence is used to calculate the bit error rate, packet loss rate, and signal-to-noise ratio, and the checksum is used to determine whether the received data is valid.

[0030] Visible light communication receiving nodes can be installed on moving parts of elevator cars, car doors, shaft sections, landings, or elevator test platforms. Visible light communication receiving nodes may include photodiodes, ambient light sensors, image sensors, and / or multi-channel optical receiving arrays. In one possible implementation, the multi-channel optical receiving array includes a left receiving channel, a right receiving channel, an upper receiving channel, and a lower receiving channel. The light intensity difference between different receiving channels can be used to characterize changes in receiving posture, car sway, partial occlusion, or receiving node offset.

[0031] The data acquisition module is used to acquire operational data and visible light communication link data during the operation of the elevator. Operational data can originate from external accelerometers, external vibration sensors, external door magnetic sensors, external photoelectric switches, elevator test platform control signals, and / or authorized elevator operation status interface data. Operational data may include at least one of the following: running direction, starting floor, target floor, current floor, running speed, running acceleration, leveling status, door zone status, door opening / closing status, load status, external vibration data, and test platform control signals.

[0032] Visible light communication link data is generated by visible light communication nodes and collected by visible light communication receiving nodes. This visible light communication link data may include at least one of the following: optical identification information, received light intensity, signal-to-noise ratio, bit error rate, packet loss rate, optical identification arrival time, multi-channel light intensity difference, light intensity fluctuation frequency, and duration of optical path obstruction. Visible light communication link data can be configured with a unified timestamp with the operational data, or a correspondence can be established through sampling sequence numbers or synchronization trigger signals.

[0033] Figure 2 The flowchart of the intelligent diagnosis method for elevator anomalies based on visible light communication provided in the embodiments of this application is illustrated. Figure 2 As shown, the method may include the following steps.

[0034] S100, acquire the operation data and visible light communication link data during the operation of the elevator. The visible light communication link data is generated by visible light communication nodes set in the elevator car, landing, shaft section and / or door area.

[0035] Specifically, during the operation of an elevator or lifting test platform, the data acquisition module can simultaneously receive operational data and visible light communication link data. For elevators in real buildings, operational data can be preferentially acquired through external accelerometers, external door magnetic sensors, external photoelectric switches, or authorized data interfaces; for lifting test platforms, operational data can directly originate from the speed, position, door status, or control commands output by the test platform controller. Visible light communication link data can be obtained by the visible light communication receiving node after receiving, demodulating, and verifying the data frames sent by the visible light communication transmitting node.

[0036] For example, LED transmitting modules can be installed near the door frames of elevators in campus buildings, while photoelectric receiving modules can be installed on the side of the elevator car. When the elevator car passes a corresponding floor or enters a door area, the photoelectric receiving module receives the floor and door area markers transmitted by the LED transmitting module and records the arrival time, received light intensity, bit error rate, and packet loss rate of the markers. As another example, in a three-story elevator experimental platform, an LED transmitting module is installed for each simulated floor, and a multi-channel light receiving array is installed on the simulated elevator car. During platform operation, the system collects the light markers corresponding to each floor and the multi-channel light intensity differences.

[0037] S200, determine the operating stage of the elevator based on the operating data, and map the visible light communication link data to the corresponding operating stage.

[0038] Specifically, the operation phase determination module can determine the operation phase of the elevator based on speed changes, acceleration changes, leveling status, door zone status, and / or door opening / closing status in the operation data. The operation phase may include at least one of the following: start-up phase, acceleration phase, constant speed phase, deceleration phase, leveling phase, door opening phase, door closing phase, and stopping phase.

[0039] In one possible implementation, when the operating speed gradually increases from zero and the acceleration is greater than a preset acceleration threshold, the elevator is determined to be in the start-up or acceleration phase; when the operating speed is within a stable range and the acceleration is less than a preset fluctuation threshold, the elevator is determined to be in the constant speed phase; when the operating speed gradually decreases and approaches the target floor, the elevator is determined to be in the deceleration phase; when the leveling state is valid and the operating speed is close to zero, the elevator is determined to be in the leveling phase; when the door state changes from closed to open, it is determined to be in the door opening phase; when the door state changes from open to closed, it is determined to be in the door closing phase.

[0040] After determining the operational phase, the system configures a unified time base for the operational data and visible light communication link data, and generates a phase time window corresponding to each operational phase based on the phase switching time. Subsequently, the system allocates the visible light communication link data to the corresponding phase time windows according to the unified time base to obtain the phase link data set corresponding to each operational phase. For example, the gate area light identifier, received light intensity, and bit error rate received within the leveling phase time window are classified as the leveling phase link data set, and the light intensity drop data and packet loss data within the gate closing phase time window are classified as the gate closing phase link data set.

[0041] Through the above processing, visible light communication link data is no longer treated as isolated data for judgment, but is instead linked to the different operating stages of the elevator. Therefore, changes in the light path caused by people or door obstruction during the door opening / closing stage, periodic light intensity fluctuations caused by car vibration during the constant speed stage, and time shifts in light marker arrival caused by floor position deviations during the leveling stage can be analyzed separately in different operating stages.

[0042] S300: Extract optical link status features based on the mapped visible light communication link data, and generate the operating optical link fingerprint of the elevator according to the optical link status features under each operating stage.

[0043] Specifically, the optical link fingerprint generation module can extract features from the link data sets at each stage to obtain the optical link status features under the corresponding operational stage. The optical link status features may include at least one of the following: optical identification features, optical intensity features, communication quality features, time features, multi-channel difference features, frequency domain features, and occlusion features.

[0044] The optical identification features can include floor identification, door zone identification, hoistway section identification, and node number, used to characterize the floor, door zone, or hoistway section passed by the car; optical intensity features can include average optical intensity, peak optical intensity, optical intensity drop amplitude, and optical intensity recovery time, used to characterize optical path stability, obstruction status, or light source attenuation; communication quality features can include bit error rate, packet loss rate, and signal-to-noise ratio, used to characterize the health status of the visible light communication link; time features can include optical identification arrival time, optical identification duration, and the time interval between adjacent optical identification arrivals, used to characterize floor passage time and operating rhythm; multi-channel difference features can include left-right optical intensity difference, up-down optical intensity difference, and optical intensity dispersion between multiple receiving channels, used to characterize car swaying, receiver offset, or local obstruction; frequency domain features can include the dominant frequency of optical intensity fluctuation and the amplitude of periodic fluctuation, used to characterize car vibration or operating jitter; obstruction features can include the duration of optical intensity drop, obstruction recovery time, and continuous packet loss time, used to characterize door zone obstruction, personnel obstruction, or foreign object obstruction.

[0045] In one possible implementation, the system can extract optical link state features through methods such as sliding window statistics, filtering, peak detection, threshold judgment, spectrum analysis, or bit error rate statistics. For example, within each stage time window, the system calculates the average received light intensity, the variance of received light intensity, the average bit error rate, the peak packet loss rate, and the number of consecutive optical identifier missing; in the constant speed stage, the system performs frequency domain analysis on the light intensity change sequence to obtain the dominant frequency of light intensity fluctuations; and in the gate stage, the system calculates the duration of light intensity drops and the recovery time.

[0046] After obtaining the optical link status characteristics at each operational stage, the system combines the optical link status characteristics of each stage according to the time sequence of the elevator's operation to generate an operational optical link fingerprint. The operational optical link fingerprint may include at least one of the following: the arrival order of floor optical markers, the arrival time interval of floor optical markers, the appearance time of door zone optical markers, the light intensity change curve during the leveling stage, the duration of optical path obstruction during the door opening and closing stage, the light intensity fluctuation frequency during the constant speed stage, the multi-channel light intensity difference change curve, the bit error rate change curve, the packet loss rate change curve, and the location of missing light source codes.

[0047] For example, when an elevator travels from the first floor to the fifth floor, under normal circumstances, the optical link fingerprint should contain a sequence of floor light identifiers that match the order in which the floors are passed, and the arrival time interval between adjacent floor light identifiers should match the changes in the operating speed. If a floor light identifier is missing for a long period of time, the arrival time of the floor light identifier deviates significantly from the normal template, or the bit error rate and packet loss rate increase abnormally in a certain stage, the corresponding information can be used as an anomaly representation in the optical link fingerprint.

[0048] S400, based on the running data and the running stage, determine the corresponding reference optical link template from the preset reference optical link template library, and compare the running optical link fingerprint with the reference optical link template to obtain the abnormal residual.

[0049] Specifically, the template comparison module can determine template matching parameters based on operational data. Template matching parameters may include at least one of the following: operating direction, starting floor, target floor, current floor segment, speed range, load range, door status, and operational stage. The preset reference optical link template library can be optical link status feature templates established under normal operating conditions according to the aforementioned template matching parameters.

[0050] When establishing a reference optical link template library, multiple sets of operational data and visible light communication link data of elevators or lifting test platforms under normal operating conditions can be collected first, and then classified according to operating direction, floor segment, speed range, door status, and operating stage. Subsequently, the mean, variance, normal threshold range, and normal trend of the corresponding optical link status characteristics are calculated for each type of sample, thereby forming the corresponding reference optical link template. For example, reference optical link templates for "upward, second to third floor, constant speed stage" and "downward, third floor leveling, door opening stage" can be established respectively.

[0051] During the current operation, the template matching module determines the corresponding template matching parameters based on the current operating data and the operating stage, and selects a reference optical link template from the reference optical link template library that matches the template matching parameters. Then, the fingerprint of the currently running optical link is compared with the reference optical link template to obtain abnormal residuals.

[0052] Anomaly residuals can include at least one of the following: position residuals, motion residuals, occlusion residuals, communication residuals, light source residuals, door zone residuals, and attitude residuals. Position residuals characterize the deviation between optical identifier information and floor status or leveling status; motion residuals characterize the deviation between optical link changes and speed or acceleration; occlusion residuals characterize sudden drops in light intensity or abnormal signal recovery; communication residuals characterize abnormal bit error rate, packet loss rate, or signal-to-noise ratio; light source residuals characterize the absence of a certain optical identifier; door zone residuals characterize the deviation between changes in the door zone optical link and the door opening / closing status; and attitude residuals characterize the continuous deviation of multi-channel light intensity differences from the normal template.

[0053] In one possible implementation, the system assigns corresponding residual weights to different types of abnormal residuals based on the operational phase. For example, during the leveling phase, the weights of position residuals and door zone residuals can be higher than those of motion residuals; during the constant speed phase, the weights of motion residuals and attitude residuals can be higher than those of door zone residuals; and during the door opening or closing phase, the weights of occlusion residuals and door zone residuals can be higher than those of light source residuals. By configuring residual weights for different operational phases, the calculation of abnormal residuals can be made more consistent with the phase characteristics of the elevator's operation.

[0054] S500, based on the correlation between the abnormal residual and the operating data, determine the abnormal type of the elevator, generate an abnormal auxiliary diagnosis result, and update the reference optical link template based on the confirmation result of the abnormal auxiliary diagnosis result.

[0055] Specifically, the anomaly diagnosis module determines the anomaly type based on the correlation between abnormal residuals, operating stages, and operating data. For example, when the arrival order or arrival time of the floor light markers is inconsistent with the floor status, a floor positioning anomaly can be identified; when there is a duration deviation between the door zone light markers and the leveling status during the leveling stage, a leveling anomaly can be identified; when the light intensity fluctuates periodically during the constant speed or deceleration stage and is correlated with acceleration or vibration data, a car vibration anomaly can be identified; when the duration of the sudden drop in light intensity during the door opening or closing stage is abnormal and is correlated with changes in the door zone status, a door zone obstruction anomaly can be identified; when the light marker corresponding to a certain transmitting node is missing multiple times, while other operating data are basically normal, a visible light transmitting node anomaly can be identified; when the signals of multiple transmitting nodes are abnormally attenuated or the bit error rate continues to increase, a visible light receiving node anomaly or a communication link degradation anomaly can be identified.

[0056] The anomaly auxiliary diagnostic results can include at least one of the following: anomaly type, floor where the anomaly occurred or simulated floor, operational stage at which the anomaly occurred, anomaly residual type, anomaly level, anomaly confidence level, anomaly evidence information, and auxiliary inspection suggestions. The anomaly evidence information can include the number of missing optical markers that triggered the anomaly judgment, the duration of sudden drops in light intensity, changes in bit error rate, changes in packet loss rate, leveling status deviation, changes in multi-channel light intensity difference, and corresponding operational stage information. Auxiliary inspection suggestions can be output to experimental personnel, campus building management personnel, or maintenance personnel for reference in experimental analysis, equipment inspection, or maintenance.

[0057] In one possible implementation, when the diagnostic result indicates an anomaly in the visible light emission node of a certain floor, the auxiliary diagnostic results may include the floor number, the number of consecutive missing nodes, whether nodes on other floors are normal, and suggestions for checking the power supply or installation angle of the LED nodes on that floor. When the diagnostic result indicates an anomaly in the door area obstruction, the auxiliary diagnostic results may include the duration of the sudden drop in light intensity during the door closing phase, the door state switching time, and suggestions for checking obstructions in the door area or the door operator's actions. When the diagnostic result indicates an anomaly in the car vibration, the auxiliary diagnostic results may include the correspondence between the light intensity fluctuation frequency during the constant speed phase, the changes in multi-channel light intensity difference, and external acceleration data.

[0058] The template update module updates the baseline optical link template based on the confirmation results of the anomaly auxiliary diagnosis. Confirmation results can come from manual confirmation, experimental annotation, or maintenance feedback. When the current running sample is confirmed as a normal sample, the system can update at least one of the characteristic mean, characteristic variance, and normal threshold range of the baseline optical link template for the corresponding operating stage based on the current running sample. When the current running sample is confirmed as an anomalous sample, the system can write the running optical link fingerprint, anomalous residual, and anomalous type corresponding to the current running sample into the anomalous sample database. Subsequently, based on normal samples and / or anomalous samples, the residual weights and / or anomalous judgment thresholds for different operating stages are adjusted. Through the above processing, a closed loop of data acquisition, fingerprint generation, template comparison, anomaly diagnosis, confirmation feedback, and template update can be formed.

[0059] Figure 3 A schematic diagram of the visible light communication node arrangement provided in an embodiment of this application is shown. Figure 3 As shown, in one embodiment of a lifting test platform, LED transmitting modules can be installed on each simulated floor, a multi-channel optical receiving array can be installed on the simulated car side, and door area LED nodes can be installed in the simulated door area. The test platform controller provides operational data such as running direction, floor position, speed, and door status. An edge computing device receives control signals from the test platform and visible light communication link data, performing operational phase division, optical link status feature extraction, operational optical link fingerprint generation, and anomaly diagnosis.

[0060] In one embodiment for campus building elevators, the visible light communication transmitting node can be installed near the permitted landing door frame, in the car auxiliary lighting location, or in the door auxiliary location, while the visible light communication receiving node can be installed inside the car or on the door side. Operational data can originate from external accelerometers, external door magnetic sensors, external photoelectric switches, or authorized elevator operation status interface data. This embodiment does not require direct access to the elevator controller's underlying protocol, nor does it alter the elevator safety circuit; it is only used to output auxiliary diagnostic results for anomalies.

[0061] In one embodiment of link anomaly branch processing, after allocating visible light communication link data to the corresponding stage time window, the system identifies link anomaly sampling data in the stage link data set based on at least one of the following: changes in received light intensity, changes in bit error rate, changes in packet loss rate, and the number of consecutive missing optical identifiers. When the link anomaly sampling data meets the temporary occlusion condition, the system marks the link anomaly sampling data as occluded sampling data and compensates the occluded sampling data based on adjacent sampling data within the same operating stage; when the link anomaly sampling data does not meet the temporary occlusion condition, the system retains the link anomaly sampling data as anomaly candidate data for generating the operating optical link fingerprint.

[0062] The temporary occlusion conditions can include at least one of the following: the duration of a sudden drop in light intensity is less than a preset occlusion time threshold, the bit error rate or packet loss rate recovers to the normal range within a short period of time, or the number of times the optical identifier of the same node is missing does not exceed a preset consecutive missing number threshold. This branch of processing can reduce the impact of factors such as short-term personnel passing by and instantaneous ambient light disturbances on anomaly diagnosis, while retaining persistent link anomalies as a basis for subsequent diagnosis.

[0063] In one embodiment of anomaly residual calculation, the system compares the running optical link fingerprint with a reference optical link template, calculates at least two of the following: position residual, motion residual, occlusion residual, communication residual, light source residual, and gate residual, and assigns residual weights to different types of anomaly residuals according to the operational stage. The system can generate a comprehensive anomaly score based on the different types of anomaly residuals and their corresponding residual weights. The comprehensive anomaly score is used to assist in determining the anomaly level or anomaly confidence.

[0064] In one closed-loop feedback embodiment, after outputting the anomaly auxiliary diagnostic result, the system receives confirmation results from experimental personnel, management personnel, or maintenance personnel. If the confirmation result indicates that the anomaly auxiliary diagnostic result is consistent with the actual inspection result, the system adds the corresponding sample to the anomaly sample library and updates the judgment threshold or residual weight of the corresponding anomaly type; if the confirmation result indicates that the current sample belongs to normal fluctuations, the system adds the corresponding sample to the normal template library and corrects the normal threshold range under the corresponding operating stage. Thus, the system can continuously correct the reference optical link template based on actual application or experimental results.

[0065] In one exemplary embodiment, taking a three-story lifting experimental platform as an example, LED emitting modules are respectively installed at the landing positions of the first, second, and third floors. These three LED emitting modules transmit visible light data frames with node numbers L1, L2, and L3, respectively. A photoelectric receiving node and an external accelerometer are installed on the simulated elevator car. When the simulated elevator car moves from the first floor to the third floor, the data acquisition module acquires the acceleration data output by the external accelerometer, the running direction and speed data output by the experimental platform controller, and the visible light communication link data received by the photoelectric receiving node. Under normal operating conditions, the photoelectric receiving node sequentially receives node number L2 from the second floor and node number L3 from the third floor, and the arrival time interval between adjacent light markers matches the speed change of the experimental platform. The system combines the arrival order of light markers, the arrival time interval of light markers, the change in received light intensity, and the change in bit error rate during this operation into a running optical link fingerprint, and uses this as a normal sample to establish the corresponding reference optical link template.

[0066] In one example of an abnormal floor positioning, when an elevator or lifting test platform ascends from the first floor to the third floor, the operational data indicates that it has entered the third-floor leveling stage. However, the visible light communication receiving node does not receive the corresponding optical identifier for the third floor within the corresponding stage time window, or the arrival time of the received third-floor optical identifier is continuously delayed compared to the reference optical link template. The system determines the current operational stage as the leveling stage based on the operational data and compares the visible light communication link data within this stage with the reference optical link template corresponding to the third-floor leveling stage to obtain the position residual. When the position residual exceeds a preset position residual threshold, the system determines that there is an abnormal floor positioning or leveling deviation and generates an auxiliary diagnostic result including the abnormal floor, abnormal stage, optical identifier arrival time deviation, and auxiliary inspection suggestions.

[0067] In an example of door zone occlusion anomaly, when the elevator is in the closing phase, the LED transmitting module corresponding to the door zone continuously transmits a door zone identifier. The visible light communication receiving node on the car side receives the door zone identifier and records the received light intensity and packet loss rate. Under normal circumstances, the light intensity change curve during the closing phase should return to the normal range corresponding to the reference optical link template after the door occlusion ends. If, during a door closing process, the received light intensity suddenly drops and the duration exceeds a preset occlusion time threshold, while the packet loss rate continues to increase, the system compares the link data set of this phase with the reference optical link template corresponding to the closing phase to obtain the occlusion residual and the door zone residual. When both the occlusion residual and the door zone residual meet the anomaly judgment conditions, the system determines that there is a door zone occlusion anomaly and outputs the door zone occlusion duration, the stage of the anomaly, and auxiliary inspection suggestions for checking for foreign objects in the door zone or the door operator's operating status.

[0068] In a temporary obstruction compensation example, when the elevator is in the door-opening phase, a passenger briefly passes through the optical path between the visible light communication receiving node and the door area LED transmitting module, causing a short-term drop in received light intensity and a small amount of packet loss. If the duration of this light intensity drop is less than a preset obstruction time threshold, and the bit error rate or packet loss rate recovers to the normal range within an adjacent sampling window, the system marks the abnormal sampling data of this link as obstruction sampling data and compensates for the obstruction sampling data based on adjacent sampling data within the same operating phase. The compensated phase link data set continues to be used to generate the operating optical link fingerprint. This processing avoids misjudging short-term personnel passage or momentary obstruction as door area anomalies or communication link degradation anomalies.

[0069] In one example of a visible light emitting node anomaly, when the elevator repeatedly passed through the fifth floor area, the operational data indicated that the car had entered the corresponding fifth floor section. However, the visible light communication receiving node repeatedly failed to receive the floor marker sent by the fifth-floor LED emitting module, while the floor markers of other floors were received normally, and there were no obvious abnormalities in the operating speed, acceleration, or leveling status. The system generates a light source residual based on the long-term absence of the fifth-floor light marker, and based on the correlation between the light source residual and the operational data, determines that the visible light emitting node corresponding to the fifth floor is abnormal or that there is partial obstruction at that node. It then generates an auxiliary diagnostic result including the node number, the number of times the marker is missing, the abnormal floor, and checks on the power supply, installation angle, or coding status of the LED emitting module.

[0070] In one example of visible light receiver node anomaly, during the operation of an elevator across multiple floor sections, the light markers corresponding to multiple floors exhibited overall low received light intensity, continuously increasing bit error rate, or continuously increasing packet loss rate. However, the operational data did not show any significant anomalies in speed, acceleration, door status, or leveling status. Based on the communication residuals corresponding to multiple nodes and the changes in multi-channel light intensity differences, the system determined that the anomaly was most likely related to visible light communication receiver node offset, receiver contamination, or changes in receiver installation posture, and generated auxiliary diagnostic results for the receiver node anomaly.

[0071] In one example of abnormal car vibration, when the elevator is in a constant-speed operation phase, both the left and right receiving channels in the multi-channel optical receiving array can receive visible light signals. However, the light intensity difference between the left and right channels varies periodically, and the acceleration data collected by the external accelerometer exhibits periodic fluctuations at a corresponding frequency. The system extracts the multi-channel light intensity difference variation curve and light intensity fluctuation frequency from the link data set during the constant-speed phase and compares it with the corresponding reference optical link template to obtain motion residuals and attitude residuals. When the motion residuals and attitude residuals meet the anomaly detection criteria, the system determines that there is an abnormal car vibration, abnormal receiving attitude, or an abnormal trend in the guide components, and outputs the anomaly occurrence stage, light intensity fluctuation frequency, acceleration fluctuation characteristics, and auxiliary inspection suggestions.

[0072] In one example of updating a reference optical link template, the system outputs an auxiliary diagnostic result for an anomaly during a certain gate-closing phase as a gate occlusion anomaly. Subsequently, experimental or maintenance personnel confirm that the anomaly was caused by temporary foreign object occlusion in the gate area. After receiving this confirmation result, the system writes the running optical link fingerprint, occlusion residual, gate residual, anomaly type, and confirmation result for that operation into the anomaly sample library. If subsequent samples show that similar gate occlusion anomalies have similar durations of light intensity drops and packet loss rate variations, the system adjusts the anomaly judgment threshold and residual weight corresponding to the gate residual based on the newly added anomaly samples. If the confirmation result indicates that a sample initially judged as an anomaly actually belongs to normal fluctuations, the system adds the sample to the normal template library and updates the feature mean, feature variance, and normal threshold range of the reference optical link template under the corresponding operating phase.

[0073] In one example of campus building auxiliary monitoring, without altering the original safety control logic of the elevator, a low-power LED emitting module is installed near the elevator door frame at each floor of the campus teaching building. A visible light communication receiving node and an external accelerometer are installed inside the elevator car. The edge computing device determines the elevator's start-up, constant speed, deceleration, and leveling stages based on data output from the external accelerometer. It also generates an operational optical link fingerprint based on the floor markers, received light intensity, and bit error rate received by the visible light communication receiving node. When the system detects a long-term missing floor marker or a persistent positional residual during a leveling stage, it only generates anomaly auxiliary diagnostic results and auxiliary inspection suggestions, without directly controlling the elevator's start / stop or altering the elevator's safety loop.

[0074] In one data frame parsing example, the data frame sent by the visible light communication transmitting node includes a frame header, node number, floor identifier, door zone identifier, status code, diagnostic probe sequence, and checksum. After receiving the visible light signal, the visible light communication receiving node first determines the start position of the data frame based on the frame header, then parses the node number, floor identifier, and door zone identifier, and determines the validity of the data frame based on the checksum. When the data frame is valid, the system records the arrival time of the corresponding optical identifier, the received light intensity, and the signal-to-noise ratio; when the data frame is invalid, the system calculates the bit error rate or packet loss rate based on the diagnostic probe sequence, and writes the statistical results as communication quality characteristics into the corresponding stage link data set. This application also provides an intelligent diagnostic system for elevator anomalies based on visible light communication. The system includes a data acquisition module, an operation stage determination module, an optical link fingerprint generation module, a template comparison module, an anomaly diagnosis module, and a template update module. The data acquisition module acquires operation data and visible light communication link data. The operation stage determination module determines the operation stage of the elevator based on the operation data and maps the visible light communication link data to the corresponding operation stage. The optical link fingerprint generation module extracts optical link status features based on the mapped visible light communication link data and generates an operation optical link fingerprint based on the optical link status features under each operation stage. The template comparison module determines the corresponding reference optical link template from a preset reference optical link template library based on the operation data and operation stage, and compares the operation optical link fingerprint with the reference optical link template to obtain an anomaly residual. The anomaly diagnosis module determines the anomaly type of the elevator based on the correlation between the anomaly residual and the operation data and generates an anomaly auxiliary diagnosis result. The template update module updates the reference optical link template based on the confirmation result of the anomaly auxiliary diagnosis.

[0075] This application also provides an electronic device, which may include a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it can implement the intelligent diagnostic method for elevator anomalies based on visible light communication described in any of the above embodiments.

[0076] This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program can implement the intelligent diagnostic method for elevator anomalies based on visible light communication described in any of the above embodiments. The computer-readable storage medium may include a read-only memory, a random access memory, a magnetic disk, an optical disk, flash memory, or other media capable of storing program code.

[0077] The above embodiments are only some implementation methods of this application. Those skilled in the art can combine, replace or modify the above embodiments without departing from the technical concept of this application. Such combinations, replacements or modifications should all fall within the protection scope of this application.

Claims

1. A method for intelligent diagnosis of elevator anomalies based on visible light communication, characterized in that, include: The system acquires operational data and visible light communication link data during the operation of the elevator. The visible light communication link data is generated by visible light communication nodes located in the elevator car, landings, shaft sections, and / or door areas. The operating stage of the elevator is determined based on the operating data, and the visible light communication link data is mapped to the corresponding operating stage. Based on the mapped visible light communication link data, optical link status features are extracted, and the operating optical link fingerprint of the elevator is generated according to the optical link status features under each operating stage. Based on the running data and the running stage, a corresponding reference optical link template is determined from the preset reference optical link template library, and the running optical link fingerprint is compared with the reference optical link template to obtain abnormal residuals; Based on the correlation between the abnormal residuals and the operating data, the abnormal type of the elevator is determined, an abnormal auxiliary diagnosis result is generated, and the reference optical link template is updated based on the confirmation result of the abnormal auxiliary diagnosis result.

2. The method according to claim 1, characterized in that, The step of determining the operating stage of the elevator based on the operating data and mapping the visible light communication link data to the corresponding operating stage includes: Configure a unified time base for the operational data and the visible light communication link data; Based on the speed changes, acceleration changes, leveling status, door zone status, and / or door opening / closing status in the operating data, the switching time of the operating phase of the elevator is determined. Based on the switching time of the operation phase, a phase time window corresponding to each operation phase is generated; According to the unified time reference, the visible light communication link data is allocated to the corresponding stage time window to obtain the stage link data set corresponding to each operation stage.

3. The method according to claim 1, characterized in that, The step of determining the corresponding reference optical link template from a preset reference optical link template library based on the operating data and the operating stage includes: The template matching parameters are determined based on the operation data. The template matching parameters include at least one of the following: operation direction, starting floor, target floor, current floor segment, speed range, load range, door status, and operation stage. From the preset reference optical link template library, determine a reference optical link template that matches the template matching parameters; The reference optical link template is an optical link status feature template established according to the template matching parameters under normal operating conditions.

4. The method according to claim 2, characterized in that, After allocating the visible light communication link data to the corresponding time windows, the process further includes: Based on at least one of the following: changes in received light intensity, changes in bit error rate, changes in packet loss rate, and the number of consecutive missing optical identifiers, abnormal link sampling data in the stage link data set is identified; When the abnormal link sampling data meets the temporary occlusion condition, the abnormal link sampling data is marked as occlusion sampling data, and the occlusion sampling data is compensated based on adjacent sampling data within the same operation phase. When the abnormal link sampling data does not meet the temporary occlusion condition, the abnormal link sampling data is retained as abnormal candidate data for generating the running optical link fingerprint.

5. The method according to claim 1, characterized in that, The step of comparing the running optical link fingerprint with the reference optical link template to obtain abnormal residuals includes: Based on the difference between the running optical link fingerprint and the reference optical link template, at least two of the following are calculated: position residual, motion residual, occlusion residual, communication residual, light source residual, and gate residual. Based on the aforementioned operational phase, configure corresponding residual weights for different types of abnormal residuals; A comprehensive anomaly score is generated based on different types of abnormal residuals and their corresponding residual weights. The position residual is used to characterize the deviation between the optical identification information and the floor status or level status; the motion residual is used to characterize the deviation between the optical link change and the speed or acceleration; the occlusion residual is used to characterize the sudden drop in light intensity or abnormal signal recovery; the communication residual is used to characterize the abnormal bit error rate, packet loss rate or signal-to-noise ratio; the light source residual is used to characterize the missing optical identification; and the door area residual is used to characterize the deviation between the door area optical link change and the door opening / closing status.

6. The method according to claim 1, characterized in that, The visible light communication link data is generated by the visible light communication transmitting node and the visible light communication receiving node; The visible light communication transmitting node includes LED transmitting modules installed at corresponding positions in the elevator car, landing, shaft section, door area and / or lifting test platform; The visible light communication receiving node includes a photodiode, an ambient light sensor, an image sensor, and / or a multi-channel optical receiving array; The data frames transmitted by the visible light communication transmitting node include at least one of the following: frame header, node number, floor identifier, door zone identifier, status code, diagnostic detection sequence, and check code; The visible light communication receiving node generates the optical identification information based on the data frame, and generates at least one of the received light intensity, communication quality information, and optical path change information based on the received signal.

7. The method according to claim 1, characterized in that, The step of updating the reference optical link template based on the confirmation result of the abnormal auxiliary diagnosis includes: Based on the confirmation results, the currently running sample is determined to be a normal sample or an abnormal sample; When the current running sample is a normal sample, at least one of the feature mean, feature variance and normal threshold range of the reference optical link template under the corresponding running stage is updated based on the current running sample. When the current running sample is an abnormal sample, the running optical link fingerprint, abnormal residual and abnormal type corresponding to the current running sample are written into the abnormal sample database; Adjust the residual weights and / or anomaly determination thresholds for different operating stages based on the normal samples and / or the abnormal samples.

8. The method according to claim 1, characterized in that, The generation of abnormal auxiliary diagnostic results includes: Based on the anomaly type, the anomaly residual, the operational phase, and the operational data, generate the anomaly location, anomaly stage, anomaly evidence information, and auxiliary inspection suggestions; The location of the anomaly, the stage of the anomaly, the evidence information of the anomaly, and the auxiliary inspection suggestions are output to the auxiliary inspection object. The system receives a confirmation result from the auxiliary inspection object based on the abnormal auxiliary diagnostic result, and uses the confirmation result as the basis for updating the reference optical link template.

9. The method according to claim 1, characterized in that, The elevators include elevators in campus buildings, elevator test platforms, or simulated elevator platforms; The operational data comes from external acceleration sensors, external vibration sensors, external door magnetic sensors, external photoelectric switches, lifting test platform control signals and / or authorized elevator operation status interface data. The visible light communication link data includes at least one of the following: optical identification information, received light intensity, signal-to-noise ratio, bit error rate, packet loss rate, optical identification arrival time, multi-channel light intensity difference, light intensity fluctuation frequency, and optical path obstruction duration.

10. The method according to any one of claims 1 to 9, characterized in that, The method is executed by an intelligent diagnostic system for elevator anomalies, which includes: The data acquisition module is used to acquire the operating data and the visible light communication link data; The operation phase determination module is used to determine the operation phase of the elevator based on the operation data, and to map the visible light communication link data to the corresponding operation phase; The optical link fingerprint generation module is used to extract optical link status features based on the mapped visible light communication link data, and generate the operating optical link fingerprint according to the optical link status features under each operating stage. The template comparison module is used to determine the corresponding reference optical link template from the preset reference optical link template library based on the running data and the running stage, and compare the running optical link fingerprint with the reference optical link template to obtain the abnormal residual; An anomaly diagnosis module is used to determine the anomaly type of the elevator based on the correlation between the anomaly residual and the operating data, and to generate the anomaly auxiliary diagnosis result. The template update module is used to update the reference optical link template based on the confirmation result of the abnormal auxiliary diagnosis result.

Images