Testing, monitoring and servicing the performance / condition of a passenger conveying system

Abstract

The invention relates to testing, monitoring and servicing of performance / condition of a passenger transport system. The method comprises performing, in a semi-automatic or full-automatic manner, the following computer-implemented steps: determining (40), by a remote computing unit (26), an operational sequence of operations of the system (18) to perform at least one function of the system; starting an operating action according to the determined operating sequence by means of the remote computing unit (26); causing an acquisition unit (30) to acquire measurement data specific to an operation action; transferring the acquired data from the acquisition unit (30) to a diagnostic unit (32); forwarding the processed data from the diagnostic unit (32) to the cloud network (22); retrieving the processed data from the cloud network (22); analyzing the condition data by processing data retrieved from the cloud network (22); an analysis report indicative of the diagnostic results is issued (48) and made available for retrieval in the cloud network (22).

Description

(19) State Intellectual Property Office (12) Invention Patent Application (10) Application Publication Number (43) Application Publication Date (21) Application Number 202610009977.2 (22) Application Date 2026.01.06 (30) Priority Data 25150891.7 2025.01.09 EP (71) Applicant KONE AG Address Helsinki, Finland (72) Inventors M. Mistonan T. Lindström T. Nieberg (74) Patent Agency King & Wood Mallesons, Beijing 11256 Patent Attorney Yi Yongmei (51) Int.Cl. B66B 5 / 00 (2006.01) B66B 1 / 06 (2006.01) B66B 1 / 34 (2006.01) (54) Title of Invention: Testing, Monitoring and Service of Performance / Condition of Passenger Transport System (57) Abstract: This invention relates to testing, monitoring and service of performance / condition of passenger transport system. The method comprises performing the following computer-implemented steps semi-automatically or fully automatically: determining (40) a sequence of operations of system (18) by a remote computing unit (26) to perform at least one function of the system; initiating an operation action according to the determined sequence of operations by means of the remote computing unit (26); causing an acquisition unit (30) to acquire measurement data specific to the operation action; causing the acquired data to be transmitted from the acquisition unit (30) to a diagnostic unit (32); causing the processed data to be forwarded from the diagnostic unit (32) to a cloud network (22); retrieving the processed data from the cloud network (22); analyzing condition data by processing the data retrieved from the cloud network (22); issuing (48) an analysis report indicating the diagnostic results and making the report available for retrieval in the cloud network (22). Claims 3 pages, Description 9 pages, Drawings 1 page CN 122355129 A 2026.07.10 CN 1 22 35 51 29 A 1. A method for testing the performance and / or condition of a passenger transport system (18), the system comprising: a controller configured to operate a transport; a data acquisition unit (30) continuously collecting data on the condition and / or performance of at least one system component; a diagnostic unit (32) communicatively coupled to the acquisition unit (30) and configured to process the data collected by the acquisition unit (30); and a forwarding unit for data communication with a cloud computing network (22), the method comprising semi-automatically or fully automatically performing the following computer-implemented steps by a remote computing unit (26) as part of the cloud network (22) to test the operation of the transport system (18): determining (40) a sequence of operations of the transport system (18) by the remote computing unit (26) to perform at least one function of the system;The remote computing unit (26) initiates an operation according to a determined operating sequence; the acquisition unit (30) acquires measurement data specific to the operation; the acquired data is transmitted from the acquisition unit (30) to the diagnostic unit (32); the processed data is forwarded from the diagnostic unit (32) to the cloud network (22); the processed data is retrieved from the cloud network (22); the retrieved data is analyzed by processing the data retrieved from the cloud network (22); and an analysis report indicating the diagnostic results is issued (48), and the report is made available for retrieval in the cloud network (22). 2. The method according to claim 1, wherein the method includes the diagnostic unit (32) processing the processed data (46) by setting one or more parameter values ​​and setting corresponding limit values ​​for each parameter value, thereby defining a desired performance range for the operation at the start; the diagnostic unit (32) determines the extent to which the acquired measurement data extends the defined performance range beyond the one or more limit values. 3. The method according to claim 1 or 2, wherein the remote computing unit (26) is a remote maintenance center communicatively coupled to the cloud network (22). 4. The method according to any one of claims 1 to 3, wherein at least one step of the automation method is outsourced to be processed by another cloud computing unit communicating with the elevator controller (18). 5. The method according to any one of claims 1 to 4, wherein, when claim 2 is invoked, the analysis of the acquired measurement data is supported by an artificial intelligence (AI) algorithm that uses a trained machine learning unit to assist in calculating the determined results and / or assist in setting the one or more limit values. 6. The method according to any one of claims 1 to 5, wherein the analysis report indicating the determined results is analyzed by considering whether the transmission system can be adapted to extend the desired performance range by updating software or software components, or by setting different operating values, so that the considered parameters can accordingly enter the desired performance range. 7. The method according to claim 6, wherein a service step of remotely installing new parameter values ​​or new software or software components is included to adapt the parameters to extend the desired performance range. 8. The method according to any one of claims 1 to 7, wherein the method is automatically triggered by computer-aided scheduling rules, for example, daily, weekly, or monthly. 9. A method for monitoring the performance of a passenger transport system (18), the system comprising: a controller (18) configured to operate the transport; and a data acquisition unit (30) continuously acquiring data on the status and / or performance of at least one system component. (Claims 1 / 3 page 2 CN 122355129 A)According to; a diagnostic unit (32), communicatively coupled to the acquisition unit (30) and configured to process data collected by the acquisition unit (30); and a forwarding unit for data communication with a cloud computing network (22), wherein the controller is configured to periodically send telemetry data from the acquisition unit (30) and / or from the diagnostic unit (32) to the cloud (22), the data being retrievable by a remote computing unit (26) of a remote maintenance center, wherein the retrieved telemetry data is analyzed by the remote computing unit (26) with reference to condition-based triggers to apply the method according to any one of claims 1 to 7, the condition-based triggers being, for example, fault codes or service requirements. 10. The method according to claim 9, wherein the retrieved telemetry data is analyzed by comparing the system's performance metrics with standard metric data, such as waiting time, ride duration, and number of passengers transported, the standard metric data being generated by a reference group of other conveyors with similar configurations, wherein if the system's performance is significantly lower than that of similar conveyors, the system issues a recommendation for maintenance performance testing according to any one of claims 1 to 7. 11. The method of any one of claims 9 or 10, wherein the analysis is supported by AI-driven insights, analyzing accompanying complex patterns and / or fault relationships. 12. A computer program residing on a computer-readable medium and comprising a set of instructions configured to cause a computer or group of computers to perform the computer-implemented method steps of any one of claims 1 to 11. 13. A non-transitory computer-readable medium storing a computer program of claim 12 for performing computer-implemented steps to audit the operation of at least one installed component by means of a computing unit. 14. A system comprising: a passenger transport system (18) including: at least one conveyor and a plurality of other components; an acquisition unit (30) configured to acquire measurement data of at least one component of the system, the data relating to the condition and / or operation of the at least one component; a diagnostic unit (32) communicatively coupled to the acquisition unit for processing the measurement data; a forwarding unit for communicating the measurement data of the acquisition unit and / or the processed data of the diagnostic unit (32) to a cloud network (22) for retrieving the data of the forwarding unit in the cloud; and a conveyor controller (18) configured to operate the conveyor, wherein the system further comprises: a remote computing unit (26) as part of the cloud network (22), wherein the remote computing unit (26) is configured to: determine (40) a sequence of operations of the passenger transport system (18) to perform at least one function of the system;Starting with the determined operating sequence, an operation is performed on the at least one component; the acquisition unit (30) acquires measurement data specific to the operation on the at least one component; specific acquisition data from the acquisition unit (30) is transmitted to the diagnostic unit (32); processed data is forwarded from the diagnostic unit (32) to the cloud network (22); the processed data is retrieved from the cloud network (22); condition data of the at least one component is analyzed based on the retrieval of the processed data; and an analysis report is published (48) based on the operation as a result of the analysis, the analysis report indicating the diagnostic condition result and enabling the report to be retrieved in the cloud network (22). 15. The system according to claim 14, wherein the diagnostic unit (32) is configured to process the data (46) by setting one or more parameter values ​​and setting corresponding limit values ​​for the parameter values ​​respectively, thereby defining a desired performance range; determining the extent to which the acquired measurement data extends the defined performance range beyond the one or more limit values; and issuing (48) an analysis report indicating the determined results and making the report available for retrieval in the cloud network (22). [Claims 2 / 3 page 3 CN 122355129 A] Test, monitoring and service technology of passenger transport system performance / condition

[0001] This invention relates to the field of passenger transport technology. In particular, this invention relates to testing and / or monitoring such transport systems by inspecting the functional capabilities and operational quality of the components or subsystems of the transport system. Finally, this invention optionally relates to computer-aided maintenance of passenger transport systems. Background Art

[0002] Any of these passenger transport systems can generally be considered as a distributed mechatronics system. Taking an elevator as an example, it includes an elevator car and possibly a counterweight, which are suspended within the elevator shaft by a suspension device or supported by a hydraulic mechanism. Numerous mechanical and electrical components belong to this system, particularly along the elevator shaft. These elevator components contribute to various elevator functions, such as guiding any movement of the elevator car within the shaft, measuring the elevator car's position, illuminating the elevator system, suspending the elevator car, driving the elevator car, controlling the elevator system, transmitting data within and / or to entities outside the elevator system, interfacing with the elevator user, ensuring the safety of the elevator system, and braking and / or stopping the elevator car's movement. Among these elevator components are elevator doors, door drive units, guide rails, fixed supports, lifting ropes, traction sheaves, motors, encoders, bearings, lights, control nodes, user interfaces, data cables, and cameras for measuring the elevator car's position.The system includes position measurement targets, safety switches and safety contacts, safety brakes, control cabinets, power units, and various other types of sensors, actuators, and structural components.

[0003] Now consider other passenger transport systems, such as escalators or moving walkways, which, even when dedicated to a single system, include multiple mechanical and electrical components, for example, arranged along the length of the escalator or moving walkway. All these components contribute to various operational functions, such as guiding the movement of steps or trays. Other components are handrails, step chains, drive chains, guide rails, guardrails, comb plates, traction systems, motors, encoders, lights, control nodes, user interfaces, data cables, cameras, position measurement devices, safety switches and safety contacts, safety brakes, control cabinets, power units, and various other types of sensors, actuators, and structural elements. When commissioning such a system after installation, functional behaviors are performed to ensure the system operates as expected. Typically, this test operation includes verifying that the system can operate at the desired speed and ride comfort and that the steps or trays move seamlessly.

[0004] For example, when comb plates or railings are assembled and attached to a structure, the drilling, positioning, and alignment of components are often done manually, leading to variations in the quality of component operation. Even with installation checks to confirm that newly installed components are functional, the system may still exhibit operational variability due to different installation conditions.

[0005] After basic functionality has been approved during commissioning by technicians, the conveyor system is put into operation, and maintenance monitoring begins to assess when components require maintenance or replacement. Any installation must be maintained regularly to prevent failure and reduce downtime of the conveyor system. Such failure can be caused by, for example, wear of any system component, installation errors, or defective components. Maintaining a conveyor system can be laborious, requiring maintenance personnel to make multiple site visits over a large geographic area. Much of the time spent includes traveling to the conveyor system site and performing routine checks. Furthermore, identifying and locating component failures and accessing the faulty component in the field can be problematic and / or time-consuming.

[0006] However, this is not just about shutting down the system to correct a failure. For example, elevators are critical for the movement of people within a building. It is not enough for elevators to move up and down according to user requests; they also need to meet necessary performance and passenger flow requirements. If elevator performance fails to meet design levels due to, for example, suboptimal settings or conditions less than 100%, it can significantly impact passenger flow.

[0007] Currently, effectively testing the performance of a transport system requires specialized equipment and the presence of field experts to perform and interpret the results. This process is labor-intensive and expensive, limiting its application to rare and exceptional cases. As a result, comprehensive performance evaluations are rarely conducted, leaving many potential problems undetected until they manifest as significant operational malfunctions.

[0008] Although the performance or condition of a transport system can also be assessed through rapid field testing (e.g., running a conveyor or an elevator to different floors), this method only identifies major malfunctions, such as a conveyor failing to move. It cannot detect more subtle problems that can adversely affect the performance of the system or the ability of a system group like an elevator assembly to effectively transport people. Such problems may include conveyor speed, or elevator door speed, or incorrect parameter settings in the optimization algorithm, which, although not obvious, can impair the overall efficiency and service quality of the transport system.

[0009] Taking elevators as an example, elevators are equipped with many adjustable parameters, each affecting performance. These parameters are usually configured with predetermined factory settings, which can be fine-tuned on-site if necessary. However, adjusting these settings is a complex task and is usually avoided unless there is an obvious and urgent problem. Therefore, many small but influential deviations in the settings remain unresolved, potentially reducing the elevator's optimal function and operational capability. Summary of the Invention

[0010] Objective of the Invention. The objective of embodiments of the present invention is to address the above-mentioned deficiencies. Specifically, the objective of embodiments of the present invention is to improve the condition and performance quality of components of a transport system. Furthermore, it simplifies maintenance work and improves maintenance effectiveness.

[0011] The above-mentioned objective is achieved by the subject matter of independent claims 1, 9, 12, 13, and 14, which respectively disclose a method for testing the performance of a passenger transport system, a method for monitoring such a system, a computer program for implementing the steps of the method, a data carrier for the computer program, and a transport system. The dependent claims relate to advantageous embodiments.

[0012] The present invention demonstrates a novel method applied to:

[0013] i) continuously and remotely monitoring a passenger transport system via a remote service unit;

[0014] ii) operating the transport system from the remote service unit for routine performance testing; and

[0015] iii) analyzing the behavior of the transport system from the remote unit; and

[0016] iv) remotely servicing the transport system, if applicable or necessary, by adjusting parameters, updating software, or changing data values ​​of the system.

[0017] The method of the present invention for testing the performance of a passenger transport system involves monitoring performance by remotely implementing test operations using a remote computing unit within a cloud network. The minimum-level passenger transport system includes a control system with a controller configured to operate the conveyor, a data acquisition unit that continuously collects status and performance data of system components, a forwarding unit for data communication with a cloud computing network, and a diagnostic unit designed to process or at least preprocess the acquired data. The method follows semi-automatic or fully automatic execution of the following computer-implemented steps, which can be categorized into the following four example tools:

[0018] - Remote test sequence generator

[0019] -

[0020] Remote Test Sequence Analyzer - Remote Test Sequence Reporter, and

[0021] - Optionally, Remote Test Sequence Scheduler.

[0022] With advancements in passenger transport system diagnostics, modern systems generate vast amounts of data that can be used to test the condition of subsystems and components, and it is precisely this data that, according to the present invention, is used to analyze the condition of any installed components of the passenger transport system specification, page 2 / 9, 6 CN 122355129 A.

[0023] Remote Test Sequence Generator: The performance testing process itself originates from the tools of the remote test sequence generator. The remote test sequence generator verifies remote operation by checking availability, authorization, and security, and then controls the transport for test runs. Referring, for example, to elevator systems, these systems can generate elevator car calls to move the car to a specific floor, or initiate actions such as opening or closing doors. The system can run a series of car calls to access all available floors while monitoring local activity or pausing the sequence if necessary. It may record progress and send status updates to ensure safe and effective remote testing.

[0024] The detailed testing process of the remote test sequence generator can begin with the remote computing unit checking any authorization from the requester. Such authorization includes obtaining permission to control the passenger transport system, at least within a specific range, to perform the method of the invention.

[0025] The checks are then performed in accordance with the specific requirements for the transport system under consideration. Some checks can be performed directly in the cloud, such as verifying the type of contract related to the customer or understanding customer preferences, such as the appropriate time for testing. Other checks rely on real-time information from the transport system itself, including its current mode or readings from equipment such as the load weighing system of an elevator.

[0026] Following a positive outcome of the authorization process, the method then involves a sequence of the following automated steps performed by the computing unit.

[0027] The method includes determining a running sequence for the operation of the transport system, identifying at least one function of the system to be performed. Once determined, the remote computing unit initiates operational actions based on the identified running sequence. Simultaneously, the remote computing unit can access and retrieve actual measurement data collected by the data acquisition unit during the running sequence, ensuring the utilization of real-time information about the system performance and condition. Earlier acquired measurement data can also be used, which has been stored in memory and can be used to better classify the current measurement data, for example, to examine historical processes that have led to the current measurement data. For this purpose, the data acquisition unit may include a memory storing past measurement data.

[0028] Regarding the components described above as examples, similar to those used in elevator systems, elevator doors, door drive units, guide rails, fixed supports, lifting ropes, traction sheaves, motors, encoders, bearings, lights, control nodes, user interfaces, data cables,Cameras, position measurement targets for measuring the position of the elevator car, safety switches and safety contacts, safety brakes, control cabinets, power units, and various other types of sensors, actuators, and structural components, some of which already provide data recording because the sensors are mounted together with the corresponding components. This also applies to other conveying systems such as handrails, step chains, drive chains, guide rails, guardrails, comb plates, traction systems, motors, encoders, and control nodes.

[0029] Where other components do not have means for providing data for the method according to this testing invention, it is advantageous to use sensors and couple them to the corresponding components, which enables data to be read out functionally from the respective components.

[0030] The remote computing unit can also enable the acquisition unit to transmit the acquired measurement data specific to the operational action to the diagnostic unit of the conveying system. This data is then preprocessed in the diagnostic unit and then retrieved first by the remote computing unit via the cloud. Alternatively, this solution can also be used in combination with the acquisition, i.e., preprocessed data acquired from the diagnostic unit of the conveying system and measurement data acquired by the acquisition unit. This also enables the evaluation of actual measurement results using earlier acquired measurement data, which has been stored in memory and can be used to better classify current measurement data, for example, by examining historical processes that have led to the current measurement data. For this purpose, the data acquisition unit may include a memory storing past measurement data.

[0031] Controlled operating actions can deviate from the operating mode of a component under normal use, having the advantage of being able to run specific test sequences. Compared to tests conducted only under normal operation, these can provide better and more detailed information about the component's functionality through the specific measurements obtained. The operating procedure for operating the component under consideration in a specific manner, according to an embodiment, may also include embedding the operating sequence by coupling it with other entities. For example, the function of opening and closing elevator doors can be embedded in the process of the elevator car reaching a specific floor. Measurement data for door movement (which is subsequently used to evaluate the door's functionality to debug the door or a portion thereof) is then embedded in the elevator car movement process, which ends when the car reaches a specific floor.

[0032] Importantly, the fundamental principle is that the delivery system does not perform actions involving security risks, even when requested from the cloud. Safety-critical checks, such as ensuring safety chains are broken and preventing conveyor movement in such situations, are always performed on-site. Security is ensured through two types of checks. First, static or semi-static characteristics are verified, including whether the requester is authorized, whether the contract allows remote operation, whether local regulations permit such operation, and whether the requested operation is...Supported by the hardware and software of the conveyor system. Secondly, assess the dynamic condition of the equipment to ensure that the conveyor system's mode allows for remote operation (e.g., not allowed in fire mode or when the test switch is activated) and whether the tenant uses the conveyor system, in which case the latter takes precedence over the test sequence if someone attempts to use the conveyor system during testing. These checks are performed in the cloud and on the equipment itself to ensure that security is not compromised, even in the rarest edge cases. No additional communication is required between the equipment and the cloud network; all checks can be based on the conveyor system's master data, contract information, and telemetry data provided by the equipment for a normal 24 hours a day.

[0033] The system can record the progress of the test sequence and send status messages accordingly. These status messages serve multiple purposes. First, they track and record the test progress in real time, providing detailed updates. Again using the example of an elevator system, this might involve things like "Moved to 2nd floor, good," "Door open, good," "Door closed, good," or "Moved to 3rd floor, good." This ensures that any problems preventing the elevator from completing the full test sequence can be located by identifying the last successful step. Furthermore, status messages are crucial for reporting the real-time status of the test sequence, especially during manual test execution, while also serving as a record of test execution and its results. These records can then be used for analysis, troubleshooting, or further reporting purposes.

[0034] Remote Test Sequence Analyzer: The retrieved measurement data and / or preprocessed data of the conveyor system are then read out and analyzed by a tool implemented on a remote computing unit, the remote test sequence analyzer.

[0035] According to a preferred embodiment, the diagnostic unit present at the conveyor system site preprocesses / processes the data by setting parameter values ​​from the measured values ​​and also setting corresponding limit values, thereby establishing a desired performance range for the specific operational action initiated, representing a benchmark of acceptable operating conditions for the components. By setting these values, the system can detect deviations that may indicate potential problems in alignment, installation quality, or component wear. The diagnostic unit then assesses the extent to which the acquired data meets or exceeds these predetermined performance limits, thereby providing insights into any deviations from the expected operating standards.

[0036] Alternatively, the diagnostic unit of the conveyor system represents only a part of a larger diagnostic unit, which is further partially present in the cloud computing and also partially present at the remote site. The diagnostic unit of the delivery system preprocesses the acquired data and transmits this preprocessed data to the cloud for forwarding to the final processing of the diagnostic unit, which is remote and directly connected to the computing unit, which includes other computing tools such as a remote test sequence generator, a remote test sequence analyzer, a remote test sequence reporter, and a remote test sequence scheduler.

[0037] In summary, the aforementioned tools of the remote test sequence analyzer monitor the operation and / or function of conveyor components and such components by evaluating processed data that may be preprocessed in the diagnostic unit at the system site, and collect long-term statistical data to identify aging effects.

[0038] Remote Test Sequence Reporter: Based on this analysis, the diagnostic unit generates an analysis report according to the next tool of the remote test sequence reporter, which indicates the evaluation results. The report can be retrieved in the cloud network, allowing maintenance service centers to access detailed performance data and insights about the operation of the conveyor system. This solution allows different reports to be generated from the same test, suitable for a variety of purposes. For customers, the report can show the condition of their equipment and provide transparency about the actions performed. For authorities or inspectors, it can serve as evidence of equipment condition and demonstrate compliance, especially when patrols are replaced by such reports. Technicians benefit from detailed information about the current and past condition of the conveyor system to assist in maintenance work or troubleshooting. In addition, the report may include specific guidance or instructions for resolving potential problems. The test sequence itself may trigger individual service requests, including detailed information about the problem and instructions for necessary repairs.

[0039] Internally, the cloud view report can provide a comprehensive overview of the test sequence, including results, floors successfully accessed (elevators, escalators), even floors considered locked, any faults encountered, travel time to the floor (elevator, escalator), number of door operations (elevator), and energy consumption. Externally, customer-facing reports can be derived from this internal data to present information in a simplified manner, such as the time of test execution and its overall good / bad condition, or if more detailed information is required. When a fault or anomaly is detected, a service request can be automatically generated, providing all necessary information and maintenance instructions to ensure rapid resolution.

[0040] This method ensures continuous, effective, and accurate monitoring of the transport system, supporting proactive maintenance and optimal system performance. The remote test sequence reporter visualizes the overall test sequence results and related movement data, focusing on faults or deviations, and a printable report (e.g., PDF) summarizing the test sequence can be generated.

[0041] This invention has a significant competitive advantage by identifying transport system condition problems before they become visible to customers and users. This proactive approach not only ensures uninterrupted service but also improves customer satisfaction by preventing interruptions. Furthermore, the invention differs from existing technologies in its ability to measure, influence, and demonstrate the impact of actions on the performance of the transport system. By demonstrating measurable improvements and tangible results, the invention strengthens maintenance efforts as a reliable solution for optimizing elevator operation.

[0042] This proactive and performance-driven approach results in higher-value maintenance. Moreover, this solution enhances…This invention is presented as a leading innovation in providing superior human flow solutions.

[0043] There are different scenarios that trigger the above-mentioned performance testing methods. The condition and performance of the transport system must be thoroughly evaluated to ensure that the system operates effectively and reliably. Performance testing can be triggered by various events, including periodic checks, such as annual checks, continuous monitoring, customer inquiries about performance, or parameter changes applied to the transport system. In the case of continuous monitoring according to the invention, the transport system periodically transmits telemetry data to the cloud.

[0044] Remote test sequence scheduler: According to an embodiment of the invention, there exists a remote test sequence scheduler as a tool for automating and optimizing test execution. It is based on:

[0045] - scheduling rules (e.g., daily, weekly, monthly)

[0046] - and / or condition-based triggers (e.g., fault codes, service requests),

[0047] - and / or AI-driven insights (e.g., complex patterns and fault relationships).

[0048] The remote test sequence scheduler is a highly advanced tool designed to remotely initiate and manage diagnostic tests with precision and adaptability. It operates through a multi-functional mechanism, utilizing pre-defined routines, dynamic condition-based triggers, and advanced AI-driven insights. These functions can work independently or collaboratively to ensure optimal responsiveness and efficiency under various operating conditions.

[0049] At its core, the scheduler can initiate tests based on pre-defined schedules, thereby achieving routine maintenance and monitoring with high consistency. For example, daily testing ensures that critical systems are continuously validated, while weekly scheduling strikes a balance between operational and diagnostic needs. Monthly testing is suitable for systems with a low probability of failure, providing regular assessments without unnecessary interruptions. This scheduling-based approach provides predictability and ensures compliance with maintenance protocols or regulatory standards, thereby promoting reliable performance over time.

[0050] Failed or interrupted tests can be automatically rescheduled, and batch execution ensures any load balancing. Manual initiation or intervention is also possible and supports maintenance tasks, providing a general and effective solution for managing test operations.

[0051] In addition to or instead of conventional scheduling, the scheduler can be equipped to react dynamically to real-time operational data, initiating tests whenever specific conditions are met. This includes scenarios such as fault code detection, where diagnostic tests are automatically triggered to quickly resolve potential problems. Similarly, when service thresholds, such as mileage limits or component wear levels, are reached, the scheduler initiates targeted tests to preemptively troubleshoot faults. Furthermore, it can respond to anomalous events, such as performance anomalies or environmental stressors, ensuring the system remains responsive and resilient under changing conditions.

[0052] Moreover, a test sequence can be automatically executed after a repair request has been reported for a device component. Whenever a specific...When a device component is reported for repair (indicating a problem or malfunction), this allows the system to automatically execute a predetermined test sequence. Repair requests can be triggered by an automated fault detection system, user reports, or remote monitoring identifying irregularities. Following a repair request, the system initiates a test sequence to diagnose the problem, verify the malfunction, and identify the root cause. This sequence is tailored to the reported fault and involves operational checks and simulations to assess the component's functionality. By adapting to the real-time environment as described above, this condition-based functionality optimizes resource allocation and ensures timely intervention.

[0053] According to this alternative, the invention also includes a separate prior continuous monitoring process prior to applying the above testing steps: the above testing method then follows conventional methods for monitoring transport systems, which involve configuring the transport system controller to periodically transmit telemetry data from acquisition and / or diagnostic units to the cloud for access by a computing unit of a remote service system. The computing unit analyzes the retrieved telemetry data by comparing performance metrics of the transport system (e.g., waiting time, ride duration, and passenger throughput) with a reference group of transports sharing similar configurations. If the analysis shows that the performance of the conveyor is significantly lower than that of similar conveyors, the system automatically suggests performing the above tests to identify and address potential problems.

[0054] These continuously retrieved data are processed by the algorithm, resulting in a distinction between problems caused by suboptimal parameter settings and problems caused by functional or condition-related defects. It also verifies customer value preferences and any special requirements. These inputs allow the algorithm to determine whether the performance of the conveyor system is consistent with customer expectations and whether the parameters are optimally configured to meet these needs. The algorithm then evaluates the results by comparing the conveyor system's metrics with a reference group.

[0055] Based on these results, the algorithm provides one of several outcomes.

[0056] i) If the conveyor system is operating under optimal conditions, no further action is required.

[0057] ii) If the performance of the conveyor system is not optimal due to the parameters it uses or the version of software it is running, the algorithm analyzes parameter optimization or software updates. The diagnostic unit then analyzes whether parameters can be automatically adjusted for performance optimization and / or software updates. If so, this is done by a remote computing unit, causing the transport system controller to automatically modify the corresponding values / parameters, or to send these values / parameters or software updates from the cloud computing unit to the transport system controller for implementation. After uploading the new parameters, values, or software, the elevator controller then verifies these changes through simulation or further performance testing according to the maintenance method of the present invention described above.

[0058] Alternatively, if the parameters are correct but performance problems persist, the system will issue a warning of deteriorating transport system condition, identify potential causes, and provide actionable recommendations to improve the system's performance in the field.

[0059] To further enhance its capabilities, the scheduler can incorporate artificial intelligence to analyze complex datasets and reveal drive pre-The diagnostic insights it provides identify recurring patterns and connects seemingly unrelated failures, revealing root causes that traditional methods might overlook. This predictive capability enables proactive testing, where potential failures are predicted and addressed before they impact the system. Therefore, AI-driven analytics enhances the scheduler's ability to predict and mitigate risks, reducing downtime and improving overall system reliability.

[0060] The real advantage of the remote test sequence scheduler lies in its ability to seamlessly combine these capabilities. Scheduler routines can be enhanced with real-time, condition-based triggers, ensuring comprehensive monitoring adapts to predictable cycles and unexpected events. Dynamic triggers can further leverage AI insights to precisely address deeper, more complex problems. As scheduling becomes richer with AI-driven data, routine checks become more targeted and effective, focusing attention on critical areas requiring intervention. This integrated approach makes the scheduler a robust and adaptive framework for diagnostics, ensuring delivery systems remain in optimal condition and minimizing disruptions caused by unplanned downtime.

[0061] The performance analysis of the conveying system relies on a robust set of interconnected databases, one of which is the storage database of the diagnostic unit. The conveying system parameter database stores all current and historical parameters for each conveyor or conveyor group. The conveying system performance database retains records of all performance tests, linking them to the corresponding parameter settings. The recommended parameter database contains optimized configurations for various conveying system settings, a curated set dynamically updated based on actual tests. Finally, the conveying system uses a pattern database to aggregate raw and processed data on usage patterns of individual conveyors or conveyor groups. This database enables the definition of relevant performance tests suitable for each situation and the calculation of the actual impact of a specific performance level. Considering elevators, this could mean achieving a wait time of less than 30 seconds in 95% of cases under a specific setting.

[0062] All algorithms used for analysis can rely on expert-defined rules, artificial intelligence (AI) or generative AI techniques, utilizing advanced data processing techniques to provide accurate and actionable insights.

[0063] Hereinafter, the method of the present invention is described with reference to an elevator system as a passenger conveying system and is supported by the accompanying drawings. Brief Description of the Drawings

[0064] Figure 1 shows a flowchart of the processing steps according to the present invention.

[0065] Reference numerals

[0066] Elevator system 18

[0067] Computer network cloud 22

[0068] Remote service center 24

[0069] Remote computing unit 26

[0070] Acquisition unit 30

[0071] Diagnostic unit 32

[0072] Remote test sequence scheduler 42

[0073] Remote test sequence generator 44

[0074] Remote Test Sequence Analyzer 46

[0075] Remote Test Sequence Reporter 48 Detailed Implementation

[0076] Assume the system performs permanent monitoring implemented by the remote test sequence scheduler 42 tool. The scheduler can initiate tests based on a predetermined schedule, enabling routine maintenance and monitoring to be performed with high consistency. In addition to its regular scheduling, the scheduler is also equipped with dynamic responses to real-time operational data, initiating tests whenever specific conditions are met. This includes scenarios such as the detection of fault codes, where diagnostic tests are automatically triggered to quickly resolve potential problems. Similarly, when service thresholds, such as mileage limits or component wear levels, are reached, the scheduler initiates target tests to preemptively troubleshoot faults. Furthermore, it can respond to abnormal events, such as performance anomalies or environmental stress, ensuring the system remains responsive and resilient under changing conditions. By adapting to the real-time environment, this condition-based functionality optimizes resource allocation and ensures timely intervention. Regardless of whether the monitoring results have indicated a failure via “condition-based rules,” or whether the time period has simply expired via “scheduling-based rules,” or whether “AI-based rules” have provided insight into the operation of the elevator on-site in the building, the remote test sequence scheduler 42 tool outputs results that are used by the remote test sequence generator 44 tool to trigger performance tests to perform various checks to verify remote operation (availability, authorization, security).

[0077] The remote computing unit first checks any authorization from the requester. This authorization includes obtaining permission to control the elevator system, at least within a specific scope, to perform the method.

[0078] The elevator under consideration is then checked against specific requirements. Some checks can be performed directly in the cloud, such as verifying the type of contract related to the customer or understanding customer preferences, such as appropriate test times. Other checks rely on real-time information from the elevator itself, including its current mode or readings from devices such as the load system.

[0079] Following the positive outcome of the authorization process, the method begins with a remote computing unit 26, such as one of the remote service centers 24, which determines the operating sequence of the elevator system 18 at the elevator building site to test any condition or specific performance or to test general performance. This sequence specifies the necessary steps to perform at least one specific function of the system. Once determined, the remote computing unit 26 initiates the operating actions according to a predetermined sequence. The initiation triggers the acquisition unit 30 to capture measurement data tailored to the specific operation being performed.

[0080] The performance testing phase begins when the elevator is driven to the second lowest floor, ensuring the test starts from a mid-level position within the system scope. The elevator then travels downwards to the lowest floor, performing automatic door operations (including an opening and closing sequence).During the phase, precise data on door motion dynamics, such as speed, alignment, and force, are collected. The elevator then moves upward, stopping at each floor where it performs door operations, collecting consistent performance data across all floors. This sequence is repeated multiple times (typically 5 cycles) to ensure statistical reliability and minimize data inconsistencies caused by anomalies.

[0081] Simultaneously, the elevator makes multiple trips between terminal floors to collect additional operational data, such as power balance and energy consumption.

[0082] Throughout these trips, the acquisition unit 30 continuously collects the data required for the operational actions, which is then transmitted to the diagnostic unit 32 of the elevator system 18 for processing. The diagnostic unit 32 refines the data and forwards it to the cloud for centralized storage and access.

[0083] Telemetry messages containing car status updates, door and fault events, and responses to remote commands are thus sent from the diagnostic unit 32 of the elevator system 18 to the cloud 22 and the cloud-based remote computing unit 26.

[0084] After the test sequence is completed, the system transitions to post-test data analysis performed by the remote test sequence analyzer 46 tool. This phase involves aggregating telemetry data and daily statistics with historical performance metrics stored in a central diagnostic database. Advanced algorithms and AI-driven insights are used to analyze the combined dataset in near real-time. This analysis assesses operational trends, detects anomalies, and generates diagnostic outputs, including fault occurrence analysis and specific component performance assessments. Furthermore, the system is designed to assess the severity and urgency of identified problems, enabling it to generate and send notifications such as “Service Required.” These notifications are tailored based on the analysis results and can specify whether the problem requires immediate technical attention (“now”) or can be resolved during the next scheduled maintenance visit. This feature enhances system operational efficiency by ensuring timely response to critical faults, optimizing maintenance scheduling for non-urgent issues, thereby reducing downtime and improving overall system reliability.

[0085] Based on this analysis, an analysis report is generated via the Remote Test Sequence Reporter 48 tool. According to a convenient embodiment, page 8 / 9 of the specification, 12 CN 122355129 A, the report includes comprehensive findings (e.g., average operational metrics), performance trends, and diagnostic insights. The report is available on the cloud for authorized retrieval and review. Remote technicians access the commissioning report via a secure cloud interface to assess elevator performance and determine if adjustments such as parameter tweaking or software updates are needed. If necessary, the system communicates specific optimizations to the technicians, such as modifying speed parameters or reconfiguring door timing.

[0086] If the elevator's performance is not optimal due to the parameters it uses or the version of software it runs, the algorithm analyzes parameter optimization or software updates. The diagnostic unit then analyzes whether parameters for performance optimization can be automatically adjusted and / or...Update the software. If so, this is done by the remote computing unit, causing the elevator controller to automatically modify the corresponding values / parameters, or to send these values / parameters or software updates from the cloud computing unit to the elevator controller for implementation. After uploading the new parameters, values, or software, the elevator controller can then verify these changes through simulation or further performance testing. Alternatively, if the parameters are correct but performance problems persist, the system will issue a warning of deteriorating elevator condition, identify potential causes, and provide actionable recommendations to improve the system's performance in the field.

[0087] Once the adjustments are implemented, an additional test sequence verifies their effectiveness in resolving the identified problems, ensuring optimal system performance.

[0088] This iterative process ensures the functionality, safety, and efficiency of the elevator system, while cloud integration provides a seamless platform for data analysis, reporting, and performance optimization.

[0089] This process is designed to be flexible and adaptable to various elevator configurations and operational requirements. Depending on the analyzed condition data, certain steps in the sequence can be adjusted, skipped, or added. For example, if initial telemetry data shows recurring door alignment problems at specific floors, the system can incorporate additional door operation tests at these locations to pinpoint the problem. Advanced algorithms, driven by AI or generative AI technologies, ensure that the analysis is both accurate and effective, identifying root causes and providing actionable insights.

[0090] By automating routine condition checks and enhancing predictive maintenance, this solution reduces the need for on-site technician visits, simplifies the maintenance process, and lowers operating costs. Furthermore, it allows technicians to focus on critical tasks requiring their expertise, increasing productivity and minimizing elevator downtime. The system ensures faster, more systematic, and comprehensive resolution of potential problems, thereby optimizing operational efficiency and improving customer satisfaction. Specification 9 / 9 pages 13 CN 122355129 A Figure 1 Specification Drawing 1 / 1 page 14 CN 122355129 A Abstract The invention is about testing, monitoring, and serving the performance / condition of a passenger conveying system. Method comprises semi-automatic or full-automatic execution of the following computer-implemented steps of determining (40) by a remote computing unit (26) a running sequence ofoperation of the system (18) to execute at least one function of the system; starting an operation action from the determined running sequence by means of the remote computing unit (26); causing the acquiring unit (30) to acquire measurement data specified to the operation action; causing a transfer of the acquired data from the acquiring unit (30) to the diagnostic unit (32); causing a forwarding of processed data from the diagnostic unit (32) to the cloud-net (22); retrieving the processed data from the cloud-net (22); analysing condition data by processing the retrieved data from the cloud-net (22); issuing (48) an analytical report that indicates the diagnosis result and making the report available for retrieval in the cloud-net (22).

Claims

1. A method for testing the performance and / or condition of a passenger transport system (18), said system comprising: A controller configured to operate the conveyor; a data acquisition unit (30) continuously collecting data on the status and / or performance of at least one system component; A diagnostic unit (32), communicatively coupled to the acquisition unit (30) and configured to process data collected by the acquisition unit (30); and a forwarding unit for data communication with the cloud computing network (22), the method comprising semi-automatically or fully automatically performing the following computer-implemented steps by a remote computing unit (26) as part of the cloud network (22) to test the operation of the delivery system (18): The remote computing unit (26) determines (40) the operating sequence of the conveying system (18) in order to perform at least one function of the system; The remote computing unit (26) initiates the operation according to the determined running sequence; The acquisition unit (30) acquires measurement data specific to the operation action; The acquired data is transmitted from the acquisition unit (30) to the diagnostic unit (32). The processed data is forwarded from the diagnostic unit (32) to the cloud network (22); Retrieve the processed data from the cloud network (22); The data is analyzed by processing the data retrieved from the cloud network (22); as well as Publish (48) an analysis report indicating the diagnostic results and enable the report to be retrieved in the cloud network (22).

2. The method according to claim 1, wherein, The method includes The diagnostic unit (32) processes the processed data (46) by setting one or more parameter values ​​and setting corresponding limit values ​​for each parameter value, thereby defining the expected performance range for the initial operation. The diagnostic unit (32) determines the extent to which the acquired measurement data extends the defined performance range beyond one or more of the limit values.

3. The method according to claim 1 or 2, wherein, The remote computing unit (26) is a remote maintenance center that is communicatively coupled to the cloud network (22).

4. The method according to any one of claims 1 to 3, wherein, At least one step in the automation method is outsourced to be handled by another cloud computing unit that communicates with the elevator controller (18).

5. The method according to any one of claims 1 to 4, wherein, When claim 2 is invoked, the analysis of the acquired measurement data is supported by an artificial intelligence (AI) algorithm, which uses trained machine learning units to assist in calculating the determined results and / or to assist in setting the one or more limit values.

6. The method according to any one of claims 1 to 5, wherein, The analysis report, which indicates the determined results, considers whether the transmission system can be adapted to the parameters indicating an extended expected performance range by updating software or software components, or by setting different operating values, so that the considered parameters can be brought into the expected performance range accordingly.

7. The method according to claim 6, wherein, This includes service steps for remotely installing new parameter values ​​or new software or software components to adapt to parameters that extend the desired performance range.

8. The method according to any one of claims 1 to 7, wherein, The method is automatically triggered by computer-aided scheduling rules, such as daily, weekly, or monthly.

9. A method for monitoring the performance of a passenger transport system (18), the system comprising: Controller (18), which is configured to operate the conveyor; The data acquisition unit (30) continuously acquires data on the status and / or performance of at least one system component; A diagnostic unit (32), communicatively coupled to the acquisition unit (30) and configured to process data collected by the acquisition unit (30); and a forwarding unit for data communication with a cloud computing network (22), wherein the controller is configured to periodically send telemetry data from the acquisition unit (30) and / or from the diagnostic unit (32) to the cloud (22), the data being retrievable by a remote computing unit (26) of a remote maintenance center, wherein the retrieved telemetry data is analyzed by the remote computing unit (26) with reference to a condition-based trigger to apply the method according to any one of claims 1 to 7, the condition-based trigger being, for example, a fault code or service requirement.

10. The method according to claim 9, wherein, The retrieved telemetry data is analyzed by comparing the system’s performance metrics with standard metrics such as waiting time, ride duration, and number of passengers transported. The standard metrics are generated by a reference group of other conveyors with similar configurations. If the system’s performance is significantly lower than that of similar conveyors, the system issues a recommendation for maintenance performance testing according to any one of claims 1 to 7.

11. The method according to any one of claims 9 or 10, wherein, The analysis is supported by AI-driven insights, analyzing the complex patterns and / or fault relationships that accompany it.

12. A computer program residing on a computer-readable medium and comprising a set of instructions configured to cause a computer or group of computers to perform computer-implemented method steps according to any one of claims 1 to 11.

13. A non-transitory computer-readable medium storing a computer program according to claim 12, for performing computer-implemented steps to audit the operation of at least one installed component by means of a computing unit.

14. A system comprising: A passenger transport system (18) includes: at least one conveyor and a plurality of other components; an acquisition unit (30) configured to acquire measurement data of at least one component of the system, the data relating to the condition and / or operation of the at least one component; a diagnostic unit (32) communicatively coupled to the acquisition unit for processing the measurement data; a forwarding unit for communicating the measurement data of the acquisition unit and / or the processed data of the diagnostic unit (32) to a cloud network (22) for retrieving the data of the forwarding unit in the cloud; and a conveyor controller (18) configured to operate the conveyor, wherein the system further includes: A remote computing unit (26) as part of the cloud network (22), wherein the remote computing unit (26) is configured to: Determine (40) the operating sequence of the passenger transport system (18) to perform at least one function of the system; The operation action for the at least one component begins from the determined operating sequence; The acquisition unit (30) acquires measurement data specific to the operation action of the at least one component; The specific acquisition data from the acquisition unit (30) is transmitted to the diagnostic unit (32); The processed data is forwarded from the diagnostic unit (32) to the cloud network (22); Retrieve the processed data from the cloud network (22); The condition data of the at least one component is analyzed based on the retrieval of the processed data; and Based on the operation action, an analysis report (48) is issued as a result of the analysis, the analysis report indicating the diagnostic status result and enabling the report to be retrieved in the cloud network (22).

15. The system according to claim 14, wherein, The diagnostic unit (32) is configured to The data is processed by setting one or more parameter values ​​and setting corresponding limit values ​​for the parameter values, thereby defining the desired performance range (46). Determine the extent to which the acquired measurement data extends the defined performance range beyond one or more of the stated limits; as well as Issue (48) an analysis report of the determined results and enable the report to be retrieved in the cloud network (22).

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