Elevator operation failure early warning method and system thereof

Abstract

The application discloses an elevator operation fault early warning method and system, and relates to the technical field of intelligent elevator control, which aims to improve the operation safety and fault response capability of the elevator under potential abnormal state; by constructing load critical drift test working condition, sudden non-vertical stress test working condition and weak power fluctuation interference test working condition, abnormal behaviors that are difficult to appear in the normal operation process of the elevator but exist safety hazards are induced; operation data under various working conditions are collected, drift overload response coefficients, guide rail non-vertical interference coefficients and power induced instability coefficients are respectively calculated, and are compared with preset thresholds respectively to determine whether operation faults such as braking response mismatch, safety clamp action asynchronization and door lock control disturbance exist, and if the judgment is abnormal, targeted strategies are automatically generated and early warning is issued. The application can realize active identification and classified response of elevator faults, and effectively improve maintenance efficiency and operation reliability.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent elevator control, and in particular to an elevator operation failure early warning method and system thereof. Background Art

[0002] As a high-frequency vertical transportation tool, the operational safety of elevators is directly related to the safety of passengers' lives and property. Current elevator safety protection systems generally rely on the coordinated control and fault alarm mechanisms of key safety components such as safety clamps, speed limiters, door locks, and brakes. However, existing fault monitoring systems are mostly based on routine operating data or passive alarm triggering mechanisms, making it difficult to identify potential hidden faults that may only be exposed under specific extreme operating conditions. This results in the following technical flaws:

[0003] Braking response hysteresis or failure: When the elevator car is close to the rated load limit, if the passengers or items are unevenly distributed, causing the center of gravity of the car to shift, it will induce response hysteresis when the brake is activated, and even cause substantial failure of the brake at a higher degree of drift.

[0004] Asynchronous safety clamp action: When structural deviations occur during elevator operation, such as car tilt or guide rail bias, the friction and tension between the left and right guide rails deviate, causing the triggering time of the two sides of the safety clamp to be asynchronous. During emergency braking, a "slanted brake" state may be formed, inducing safety risks.

[0005] Control logic instability and door lock false triggering: When the elevator control system is interfered with by unstable power supply, such as short-term voltage fluctuations or transient power supply disturbances, the door lock logic judgment and response signals may be delayed, falsely triggered, or even disordered, resulting in abnormal door lock alarms or actual failure, affecting the security of the control link. Summary of the Invention

[0006] In view of the deficiencies in the prior art, the present invention provides an elevator operation fault early warning method and system thereof to solve the problems mentioned in the background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: an elevator operation failure early warning method and system, comprising:

[0008] The extreme operating condition testing module is used to proactively induce operational anomalies that are difficult to detect during normal operation but pose potential safety risks, based on the elevator's structural configuration and safety device parameters. This module constructs multiple extreme test conditions, including critical load excursion, sudden non-vertical force, and weak power supply fluctuation interference.

[0009] A data acquisition module is configured to acquire data of the elevator in a load critical drift test condition, in a sudden non-vertical force test condition, and in a weak power fluctuation interference test condition;

[0010] The load critical drift effect recognition module is configured to establish a transient overload disturbance sequence based on a car rated load curve, generate a drift overload response coefficient GZX, and compare and analyze the GZX with a first threshold Q1 to determine whether the real-time load of the elevator car and the brake response are matched, and if not, a strategy is given.

[0011] The sudden non-vertical force effect recognition module is configured to simulate the lateral stress response of the guide rail in a car tilting state, obtain a non-vertical interference coefficient DFG, and compare and analyze the DFG with a second threshold Q2 to determine whether the safety gear action of the elevator car is synchronized, and if not, a strategy is given.

[0012] The weak power fluctuation interference effect recognition module is configured to introduce a non-ideal power supply fluctuation simulation, monitor the stability of the door lock logic and control system response, construct a power-induced instability coefficient DYS, and compare and analyze the DYS with a third threshold Q3 to determine whether the control system input voltage fluctuation interferes with the door lock control, and if so, a strategy is given.

[0013] Preferably, the extreme condition test module includes a device recognition unit, a load critical drift test condition unit, a sudden non-vertical force test condition unit, and a weak power fluctuation interference test condition unit.

[0014] The device recognition unit is configured to recognize and label the constituent devices of the elevator whole machine structure and its key safety devices, and acquire information including device unique number, installation floor and relative position, debugging configuration number, safety interface type and response characteristic parameter through two-dimensional code and radio frequency tag scanning, control system device code analysis and historical operation data retrieval.

[0015] The load critical drift test condition unit is configured to simulate the occurrence of gravity center offset of the car load in the boundary state close to the rated limit, to induce abnormal brake response lag and uneven tension.

[0016] The sudden non-vertical force test condition unit is configured to induce uneven guide rail friction and asymmetric safety gear response by introducing car tilting, guide rail installation deviation or rope tension asymmetry.

[0017] The weak power fluctuation interference test condition unit is configured to induce the logic response of the door lock controller and safety devices under abnormal power supply conditions by controlling the voltage of the control system to drop for a short time.

[0018] Preferably, the data acquisition module includes a load critical drift test condition acquisition unit, a sudden non-vertical force test condition acquisition unit, and a weak power supply fluctuation interference test condition acquisition unit;

[0019] The load critical drift test condition acquisition unit is used to collect data during the load critical drift test condition of the elevator. A high-precision load sensor is installed on the weighing support structure at the bottom of the car to collect the car load value sequence; a tension load sensor is installed at the brake drive shaft connection structure to record the load feedback value during the startup response phase.

[0020] The sudden non-vertical force test condition acquisition unit is used to collect data when the elevator is subjected to sudden non-vertical force test conditions. Thin-film friction sensors are installed on the left and right guide shoe bases and side sliding surfaces to collect the friction value sequences of the left and right guide rails. Tension sensors are installed on the guide wheel at the rope pulley outlet above the elevator shaft to collect the tension values ​​of the left and right traction ropes.

[0021] The weak power supply fluctuation interference test condition acquisition unit is used to collect data during the weak power supply fluctuation interference test condition. By installing a high-speed voltage monitoring sensor at the PLC power input port and the inverter main control input end, the control voltage value sequence is collected; by setting a logic state recording program on the door lock control logic board, the number of abnormal intermittent or switching abnormalities is recorded.

[0022] Preferably, the load critical drift effect identification module includes a first calculation unit and a first analysis unit;

[0023] The first calculation unit is used to extract load critical drift test condition data, establish a transient overload disturbance sequence based on the car rated load curve, and calculate and obtain the drift overload response coefficient GZX after dimensionless processing.

[0024] Preferably, the first analysis unit is configured to preset a first threshold Q1 and compare and analyze the drift overload response coefficient GZX with the first threshold Q1 to obtain a first evaluation result, including:

[0025] When the drift overload response coefficient GZX is less than the first threshold Q1, it indicates that the real-time load of the elevator car matches the braking response, and the elevator operation is stable and continuously monitored;

[0026] When the first threshold Q1≤drift overload response coefficient<GZXfirst threshold , indicating a level 1 mismatch between the elevator's real-time load and brake response, with a risk of brake hysteresis. This triggers the first warning instruction and generates the first strategy: extending the pre-brake trigger signal timing by 20% to increase brake response time. The elevator is also labeled as a load response offset risk, and maintenance personnel are advised to correct the weighing displacement feedback device.

[0027] When the drift overload response coefficient GZX is greater than a first threshold value When the drift overload response coefficient GZX is greater than a first threshold value

[0028] Preferably, the sudden non-vertical force effect identification module comprises a second calculation unit and a second analysis unit.

[0029] The second calculation unit is used to simulate the response of the guide rail lateral stress under the inclined state of the car, extract sudden non-vertical force test working condition data, and calculate the guide rail non-vertical interference coefficient DFG after dimensionless processing.

[0030] Preferably, the second analysis unit is used to compare and analyze the guide rail non-vertical interference coefficient DFG with a preset second threshold value Q2, and obtain a second evaluation result including:

[0031] When the guide rail non-vertical interference coefficient DFG is less than the second threshold value Q2, it indicates that the safety gear action of the elevator car is synchronous, and there is no risk of oblique braking, and continuous monitoring is performed.

[0032] When the guide rail non-vertical interference coefficient DFG is greater than or equal to the second threshold value Q2, it indicates that the safety gear action of the elevator car is asynchronous, and there is a risk of oblique braking, a third warning instruction is triggered, and a third strategy is generated: performing safety gear recalibration process on the elevator, stopping the elevator at the maintenance layer, cutting off the main drive circuit, and only retaining the calibration power supply and control channel; issuing a safety gear calibration mode instruction through the maintenance panel, loading the current left and right guide rail friction and tension data, checking whether the release is synchronous by respectively releasing the left and right safety gear braking states, if synchronous, suggesting manual periodic retesting, and prompting to check the coaxiality of the rope wheel and fine-tune the guide shoe; if the release of either side fails, the system operation is locked, and a "brake mechanism jam" prompt is given, the process is terminated and manual maintenance is prompted.

[0033] Preferably, the weak power fluctuation disturbance effect identification module comprises a third calculation unit and a third analysis unit.

[0034] The third calculation unit is used to introduce a non-ideal power fluctuation simulation, monitor the stability of the door lock logic and control system response, extract weak power fluctuation disturbance test working condition data, and calculate the power-induced instability coefficient DYS after dimensionless processing.

[0035] Preferably, the third analysis unit is used to preset a third threshold value Q3, and compare and analyze the power-induced instability coefficient DYS with the third threshold value Q3 to obtain a third evaluation result including:

[0036] When the power-induced instability coefficient DYS < the third threshold Q3, it indicates that the control system input voltage fluctuation does not interfere with the door lock control, the door lock execution state is stable, and continuous monitoring is performed.

[0037] When the third threshold Q3 ≤ the power-induced instability coefficient DYS < the third threshold , it indicates that there is a first-level fluctuation anomaly in the control system input voltage, which has the risk of causing door lock control failure and delayed response, triggers the fourth early warning instruction, generates the fourth strategy: lengthens the door lock controller output logic delay threshold by 20%, pushes the control system input voltage fluctuation and door lock signal synchronization check maintenance suggestion to the maintenance personnel, and labels it with the "voltage fluctuation interference" risk label.

[0038] When the power-induced instability coefficient DYS ≥ the third threshold , it indicates that there is a second-level fluctuation anomaly in the control system input voltage, which has the risk of causing door lock false triggering and logic disorder, triggers the fifth early warning instruction, generates the fifth strategy: immediately prohibits the elevator from continuing to run, pushes the replacement of the power filter assembly and the door lock electromagnetic contact element maintenance suggestion to the maintenance personnel, and labels it with the "control link power instability risk" label.

[0039] Preferably, an elevator operation failure early warning method comprises the following steps:

[0040] Step one, based on the elevator structure configuration and its safety device parameters, actively induce operation anomalies that are difficult to appear but have potential safety risks during normal operation, and construct multiple types of extreme test working conditions; the extreme test working conditions include load critical drift test working condition, sudden non-vertical force test working condition and weak power fluctuation interference test working condition;

[0041] Step two, collect data when the elevator is in the load critical drift test working condition, the elevator is in the sudden non-vertical force test working condition and the weak power fluctuation interference test working condition;

[0042] Step three, establish a transient overload disturbance sequence based on the car rated load curve, generate a drift overload response coefficient GZX, and compare and analyze it with the first threshold Q1 to determine whether the elevator car real-time load and brake response match, if not, give a strategy;

[0043] Step four, through the guide rail lateral stress response in the quasi-car tilting state, obtain the guide rail non-vertical interference coefficient DFG, and compare and analyze it with the second threshold Q2 to determine whether the safety gear action of the elevator car is synchronized, if not, give a strategy;

[0044] Step five, through the introduction of non-ideal power supply fluctuation simulation, the stability monitoring of the door lock logic and control system response, the power induced instability coefficient DYS is constructed, and compared with the third threshold Q3, whether the control system input voltage fluctuation disturbs the door lock control is judged, if the disturbance is given strategy.

[0045] The application provides an elevator operation fault early warning method and system.

[0046] (1) The elevator operation fault early warning method and system, by constructing three types of extreme conditions of drift overload response test, guide rail non-vertical interference test and weak power fluctuation interference test, respectively for structural overload anomaly in the elevator operation process, vertical deviation response caused by guide rail installation error and control fault caused by unstable power supply, the problem of insufficient extreme fault response simulation in existing elevator test is filled, and the foundation for comprehensive evaluation of system operation safety is laid.

[0047] (2) The elevator operation fault early warning method and system, by arranging multiple sensor arrays in the test platform, collecting key operation data such as car speed, acceleration, vibration, running offset, door control feedback state and controller response signal, covering power response, track response and control response in the whole process of elevator operation, the integrity and timeliness of data acquisition are effectively improved, and high-quality support is provided for subsequent coefficient calculation and risk discrimination.

[0048] (3) The elevator operation fault early warning method and system, by calculating and obtaining three types of risk identification coefficients of drift overload response coefficient DPO, guide rail non-vertical interference coefficient DGD and power induced instability coefficient DYS, respectively based on multi-dimensional signal difference characteristics, track deflection angle disturbance characteristics and door control response time difference characteristics, it has the technical advantages of quantitative accuracy, threshold discrimination and strategy generation, and realizes accurate identification and grade classification of different types of operation faults.

[0049] (4) The elevator operation fault early warning method and system, by organically integrating extreme condition construction, data acquisition, coefficient evaluation and strategy generation, a set of elevator operation fault prediction and early warning system for complex operation environment is established, which has the ability of automatic identification, grade judgment and response strategy pushing, significantly improves the perception accuracy and disposal efficiency of the system to operation abnormality, and promotes the upgrade of elevator operation maintenance from experience type to data driven type and prediction type. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 The application provides an elevator operation fault early warning system block diagram flow chart;

[0051] Figure 2A schematic diagram of steps of an elevator operation fault early warning method. DETAILED DESCRIPTION

[0052] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0053] Embodiment 1

[0054] Please refer to Figure 1 The present application provides an elevator operation fault early warning method and system, comprising:

[0055] An extreme working condition test module is configured to induce operation abnormalities that are difficult to appear but have potential safety risks in normal operation based on elevator structure configuration and safety device parameters, and to construct multiple types of extreme test working conditions. The extreme test working conditions include a load critical drift test working condition, a sudden non-vertical force test working condition and a weak power fluctuation interference test working condition.

[0056] A data acquisition module is configured to acquire data of the elevator in the load critical drift test working condition, the elevator in the sudden non-vertical force test working condition and the elevator in the weak power fluctuation interference test working condition.

[0057] A load critical drift effect identification module is configured to establish a transient overload disturbance sequence based on a car rated load curve, to generate a drift overload response coefficient GZX, and to compare and analyze the GZX with a first threshold Q1 to determine whether the real-time load of the elevator car and the brake response are matched. If not, a strategy is given.

[0058] A sudden non-vertical force effect identification module is configured to simulate the lateral stress response of the guide rail in the inclined state of the car, to obtain a non-vertical interference coefficient DFG of the guide rail, and to compare and analyze the DFG with a second threshold Q2 to determine whether the safety gear action of the elevator car is synchronous. If not, a strategy is given.

[0059] A weak power fluctuation interference effect identification module is configured to introduce a non-ideal power supply fluctuation simulation, to monitor the stability of the door lock logic and the control system response, to construct a power-induced instability coefficient DYS, and to compare and analyze the DYS with a third threshold Q3 to determine whether the control system input voltage fluctuation interferes with the door lock control. If so, a strategy is given.

[0060] In this embodiment, by constructing multiple types of extreme test working conditions covering load critical drift, sudden non-vertical force and weak power fluctuation, the structural and control risks that are difficult to expose but potentially exist in normal operation are actively induced, combined with three types of risk criteria of drift overload response coefficient GZX, guide rail non-vertical interference coefficient DFG and power induced instability coefficient DYS, a set of operation abnormality recognition mechanism that can be quantified, compared and strategically linked is formed, which effectively improves the pre-identification and response capability of potential faults in elevator operation, and realizes the transformation from passive alarm to active sensing and strategic intervention.

[0061] Embodiment 2

[0062] This embodiment is an explanation and description in embodiment 1. Specifically, the extreme working condition test module includes a device identification unit, a load critical drift test working condition unit, a sudden non-vertical force test working condition unit and a weak power fluctuation disturbance test working condition unit.

[0063] The device identification unit is used to identify and label the constituent devices of the elevator whole machine structure and its key safety devices, and to collect information including device unique number, installation floor and relative position, debugging configuration number, safety interface type and response characteristic parameter information through two-dimensional code and radio frequency tag scanning, control system device code analysis and historical operation data retrieval.

[0064] The load critical drift test working condition unit is used to simulate the occurrence of gravity center offset of the car load in the boundary state close to the rated limit, to induce abnormal brake response lag and tension unevenness; the critical load boundary state refers to the running state when the load in the elevator car reaches or approaches the rated limit, such as 90%~100% rated load, at this time the system is at the maximum stress edge and the response mechanism is most sensitive, once disturbance occurs, abnormality is easy to appear; the gravity center offset induction method is to place a large amount of heavy objects close to one side in the car to make the load gravity center deviate from the geometric center of the car, form a overturning moment and change the tension distribution of the steel wire rope group; the brake response lag is that due to the load eccentricity, part of the brake device is stressed first and part of it is stressed later, resulting in uneven brake force and short-term response delay; the tension unevenness is that the tension distribution of the traction steel wire rope is unbalanced, which aggravates the relaxation on one side and the tightening on the other side, increasing the nonlinear response risk of the system; the structure is slightly inclined and the guide is unbalanced: the gravity center offset causes the contact pressure of the car and the guide to be biased, which further causes the guide friction force to be abnormal and the guide to be offset, affecting the pre-tightening force matching of the safety gear;

[0065] The sudden non-vertical force test working condition unit is used to induce uneven guide rail friction and asymmetric response of the safety gear by introducing car micro-tilt, guide rail installation deviation or rope wheel tension asymmetry; approach the operating state of the upper limit of the rated load of the elevator, such as 90-100% rated load, which is usually stable, but in this critical zone, any center of gravity disturbance or inertia deviation is more likely to cause response delay or dynamic out-of-control; simulate the non-uniform load conditions in real scenarios, such as “passengers concentrated on one side in the car” or “large volume of objects, layout biased to one side”, so that the car forms a non-linear pull-down or upward torque in vertical operation; brake response lag: due to the difference in tension between the traction side and the counterweight side, the brake action has the risk of asynchronous response between the left and right sides; uneven wire rope tension: increases the risk of local fatigue and slip of the wire rope; car yaw or tilt trend is enhanced: causes uneven guide rail contact pressure, increases the difficulty of safety gear response;

[0066] The weak power fluctuation interference test working condition unit is used to induce the logic response of the door lock controller and safety device under abnormal power supply conditions by controlling the short-time voltage drop of the system; when the door is normally opened, the 24V control power supply voltage is temporarily reduced to 18V due to load fluctuation, causing the door lock logic chip to reset temporarily, the door lock state cannot be confirmed, and the “door not closed” alarm occurs; or when the elevator is ready to start, the bus voltage is temporarily dropped due to the simultaneous start of air conditioners or high-power equipment, causing the frequency converter or control PLC to restart, and the elevator “stops”.

[0067] In this embodiment, by setting the extreme working condition test module and refining it into the equipment identification unit, the load critical drift test working condition unit, the sudden non-vertical force test working condition unit and the weak power fluctuation interference test working condition unit, a multi-type test environment close to actual hidden danger scenarios can be comprehensively constructed, wherein by simulating conditions such as center of gravity deviation, guide rail stress asymmetry, voltage short-time fluctuation, potential abnormal response is induced and observed, and the multi-dimensional risk perception ability of the elevator system under critical boundary conditions is significantly enhanced, providing high-value boundary data support for subsequent fault identification and early warning strategy generation.

[0068] Embodiment 3

[0069] This embodiment is an explanation and description in embodiment 2, specifically, the data acquisition module includes a load critical drift test working condition acquisition unit, a sudden non-vertical force test working condition acquisition unit and a weak power fluctuation interference test working condition acquisition unit;

[0070] The load critical drift test working condition acquisition unit is used to acquire data of the elevator in the load critical drift test working condition, high-precision load sensors are installed on the car bottom weighing support structure to acquire the car load value sequence; a tension load sensor is installed on the brake transmission shaft connection structure to record the load feedback value in the starting response stage;

[0071] The sudden non-vertical force test working condition collection unit is used to collect data of the elevator in a sudden non-vertical force test working condition, a thin film friction force sensor is installed on the left and right guide shoe bases and the side sliding surface to collect a left and right side guide rail friction force value sequence; a tension sensor is installed at the rope wheel outlet guide wheel above the elevator shaft to collect the tension value of the left and right side traction rope;

[0072] The weak power fluctuation interference test working condition collection unit is used to collect data in a weak power fluctuation interference test working condition, a high-speed voltage monitoring sensor is installed at the input port of the PLC power supply and the input end of the frequency converter main control to collect a control voltage value sequence; a logic state recording program is set on the door lock control logic board to record the number of times of abnormal intermittent or switch abnormality.

[0073] In this embodiment, by setting the data collection module and dividing it into three types of test working condition collection units of load critical drift, sudden non-vertical force and weak power fluctuation interference, fine monitoring can be implemented for different potential risk sources. Among them, through the distributed arrangement of the load sensor, the friction force sensor, the tension sensor and the high-speed voltage monitor, the system can synchronously collect key data such as car load change, guide rail uneven force, traction tension imbalance and control voltage fluctuation, realize high-frequency and precise recording of the response state of multiple types of working conditions, and provide comprehensive and accurate original data support for elevator operation abnormality identification and strategy response.

[0074] Embodiment 4

[0075] This embodiment is an explanation and description in embodiment 1. Specifically, the load critical drift effect identification module includes a first calculation unit and a first analysis unit.

[0076] The first calculation unit is used to extract load critical drift test working condition data, and based on the rated load curve of the car, a transient overload disturbance sequence is established, and after dimensionless processing, a drift overload response coefficient GZX is calculated and obtained, and the formula is as follows:

[0077] ;

[0078] In the formula, represents the car load change value in the disturbance loading process, represents the corresponding load response change value when the brake is started, represents the rated load value of the elevator, which is obtained from the elevator parameters.

[0079] In this embodiment, the first calculation unit in the load critical drift effect identification module is used to construct a transient overload disturbance sequence based on the car rated load curve, and the dimensionless processing is used to accurately calculate the drift overload response coefficient GZX, so as to realize the quantitative analysis of the elevator brake response under the load critical state. This method can accurately reflect the matching of the brake response and the car load change, effectively identify the brake response lag and load drift anomaly, and improve the sensitivity and reliability of the elevator safety monitoring.

[0080] Embodiment 5

[0081] This embodiment is an explanation and description in embodiment 4. Specifically, the first analysis unit is used to compare and analyze the drift overload response coefficient GZX with the first threshold Q1 through the preset first threshold Q1, and obtain the first evaluation result, including:

[0082] When the drift overload response coefficient GZX is less than the first threshold Q1, it indicates that the real-time load of the elevator car matches the brake response, the elevator runs stably, and continuous monitoring is required.

[0083] When the first threshold Q1 is less than the drift overload response coefficient GZX and the first threshold , it indicates that the real-time load of the elevator matches the brake response with a first level anomaly, there is a risk of brake lag, a first warning instruction is triggered, and a first strategy is generated: the 20% pre-brake trigger signal timing is extended, the brake reaction time is increased; the load response offset risk label is added to the elevator, and the maintenance personnel is pushed to push the maintenance suggestion of correcting the weighing displacement feedback device;

[0084] When the drift overload response coefficient GZX is greater than the first threshold , it indicates that the real-time load of the elevator matches the brake response with a second level anomaly, there is a risk of brake failure, a second warning instruction is triggered, and a second strategy is generated: immediately prohibit the elevator from running, and push the maintenance personnel to push the maintenance suggestion of replacing the brake spring.

[0085] The first threshold Q1 is obtained as follows: in the experimental stage, a plurality of groups of different types of elevators (such as commercial elevators, bed elevators, and cargo elevators) are selected for critical load disturbance test, the extreme states that may occur in actual operation, such as load transient or uneven tension, are simulated, and the drift overload response coefficient GZX corresponding to each test is calculated. A set of historical data set for statistical analysis is formed by accumulating multiple tests. The drift overload response coefficients GZX of these historical data sets are statistically analyzed to determine their regular fluctuation ranges under different elevator types and load states, and the drift overload response coefficient GZX mean value and standard deviation are mainly obtained.

[0086] On the basis of the average of the drift overload response coefficient GZX, the time effectiveness requirement of the brake response performance in the GB7588-2003 Safety Code for the Manufacture and Installation of Elevators and the tolerance requirement of the load identification accuracy ±5% in the GB / T24476-2009 General Technical Conditions for Elevator Car Load Identification System are referred to, the average of GZX plus 2 times of the standard deviation is set as the first threshold Q1, and under the condition that the load distribution is stable and the system is normally operated, the value of GZX should be normally distributed around the average.

[0087] In the embodiment, the hierarchical early warning mechanism is set by the first analysis unit, the preset first threshold Q1 is used for real-time comparative analysis of the drift overload response coefficient GZX, and the matching degree of the elevator car load and the brake response can be accurately judged. When GZX is lower than Q1, the system determines that the elevator is stably operated and continues to monitor; when GZX is between Q1 and 150% of Q1, the system identifies a first abnormal risk, automatically prolongs the pre-brake trigger timing and pushes the maintenance suggestion, and effectively prevents the brake delay risk; when GZX is more than 150% of Q1, the system determines a second abnormal risk, timely prohibits the elevator from operating and pushes the maintenance suggestion of replacing the brake spring, and significantly improves the elevator operation safety guarantee level and the maintenance response efficiency.

[0088] Embodiment 6

[0089] The embodiment is an explanation and description in embodiment 1, specifically, the sudden non-vertical stress effect identification module includes a second calculation unit and a second analysis unit;

[0090] The second calculation unit is used for the lateral stress response of the guide rail in the inclined state of the car, extracts the sudden non-vertical stress test working condition data, and after the non-dimensional processing, the guide rail non-vertical interference coefficient DFG is calculated and obtained, and the formula is as follows:

[0091] ;

[0092] In the formula, DFG represents the left guide rail friction peak value, DFG represents the right guide rail friction peak value, DFG represents the left traction rope tension, DFG represents the right traction rope tension.

[0093] In this embodiment, through the second calculation unit of the burst non-vertical force effect recognition module, based on the guide rail lateral stress response under the car tilt state, the guide rail friction force and the traction rope tension data are accurately extracted, and the guide rail non-vertical interference coefficient DFG is calculated through dimensionless processing. This coefficient can quantify the uneven stress of the guide rail caused by non-vertical force during elevator operation and potential safety hazards, assist in accurately judging the synchronization of the guide rail safety gear action, and improve the sensitivity of fault identification and the safety of elevator operation.

[0094] Embodiment 7

[0095] This embodiment is an explanation and description in embodiment 6. Specifically, the second analysis unit is used to compare and analyze the guide rail non-vertical interference coefficient DFG with the second threshold Q2 by presetting the second threshold Q2, and obtain the second evaluation result, including:

[0096] When the guide rail non-vertical interference coefficient DFG is less than the second threshold Q2, it indicates that the safety gear action of the elevator car is synchronous, there is no risk of oblique brake, and continuous monitoring is required.

[0097] When the guide rail non-vertical interference coefficient DFG is greater than or equal to the second threshold Q2, it indicates that the safety gear action of the elevator car is asynchronous, there is a risk of oblique brake, a third warning instruction is triggered, and a third strategy is generated: the elevator is subjected to safety gear recalibration process, the elevator stops at the maintenance layer, the main drive circuit is cut off, and only calibration power supply and control channel are reserved; Through the maintenance panel, the safety gear calibration mode instruction is issued, the current left and right guide rail friction and tension data are loaded, the left and right safety gear brake states are released respectively, the release synchronization is checked, if it is synchronized, manual periodic retesting is recommended, and the coaxiality of the rope wheel and the fine adjustment of the guide shoe are prompted to check; If the release fails on either side, the system operation is locked, the "brake mechanism jam" is prompted, the process is stopped and manual maintenance is prompted.

[0098] The second threshold Q2 is obtained by selecting several typical elevator systems during the experimental phase. Guide rail friction and rope tension data were collected for various installation accuracy, guide rail spacing errors, and eccentric loading conditions, simulating extreme conditions such as car tilt or uneven load. This data set was used to construct a historical sample dataset for calculating the guide rail non-vertical interference factor (DFG). Statistical analysis of this dataset revealed the mean and standard deviation of DFG under the assumption of synchronized safety clamp operation, thereby extracting the reasonable range of guide rail force fluctuations under normal elevator operation. In accordance with the technical requirements for safety clamp response consistency and jaw synchronization in the "GB 7588-2003 Safety Code for Elevator Manufacturing and Installation," the second threshold Q2 was set as the mean of DFG plus twice the standard deviation. This threshold, Q2, covers approximately 95% of normal deviation samples and effectively identifies guide rail stress anomalies caused by non-vertical forces without causing false alarms. This serves as the trigger limit for determining the risk of asynchronous safety clamp operation. The second threshold Q2 is adaptable and can be fine-tuned according to the purpose of the elevator (such as high-speed passenger elevators, hospital bed elevators, etc.) or the guide rail structure type (such as T-shaped guide rails, L-shaped guide rails) to meet the differentiated requirements of different systems for synchronization accuracy and operation smoothness.

[0099] In this embodiment, a second analysis unit uses a preset second threshold value Q2 to compare and analyze the guide rail non-vertical interference coefficient DFG, accurately determining the synchronization of the elevator car's safety clamp operation. When asynchrony of the safety clamp operation and the risk of skew braking are detected, the system automatically triggers an early warning and generates a targeted safety clamp recalibration strategy, directing the elevator to a maintenance floor and executing a detailed calibration process. This effectively prevents brake jamming and skew braking accidents, significantly improving elevator safety assurance and maintenance efficiency.

[0100] Example 8

[0101] This embodiment is explained in Example 1. Specifically, the weak power supply fluctuation interference effect identification module includes a third calculation unit and a third analysis unit;

[0102] The third calculation unit is used to introduce non-ideal power supply fluctuation simulation, monitor the stability of the door lock logic and control system response, extract weak power supply fluctuation interference test condition data, and calculate the power supply induced instability coefficient DYS after dimensionless processing. The formula is as follows:

[0103] ;

[0104] Where, Indicates the standard deviation of the inverter control voltage sampling, Indicates the rated control voltage, which is obtained from the elevator parameters. Indicates the ratio of door lock logic abnormal trigger times, Door lock abnormal weight coefficient;

[0105]

[0106] wherein n represents the number of sampling times, Vi represents the control voltage value of the i-th sampling, Vi represents the average value of the control voltage of all samplings.

[0107] Door lock abnormal weight coefficient The acquisition method of the door lock abnormal weight coefficient is as follows: through the attribution analysis of the door lock response data of the multi-type elevator under the weak power supply fluctuation working condition, the occurrence frequency and influence degree of the door lock control delay, the false triggering and the failure event are counted, the door lock instability characteristic factor caused by the power supply fluctuation is extracted, and the fault influence evaluation index system of the door lock is constructed in combination with the fault tolerance redundancy ability of the door lock control loop and the response margin of the main control panel. Referring to the elevator electrical safety standard, the door lock structure technical specification and the field fault sample, the relative weight of the door lock abnormality in the system stability judgment is determined by combining the expert experience and the maintenance feedback, and the value is set to reflect the influence level of the door lock abnormality on the whole machine running stability under the power supply fluctuation background, so as to provide quantitative basis for the subsequent door lock control strategy optimization and safety redundancy judgment.

[0108] In this embodiment, through the third computing unit of the weak power supply fluctuation interference effect identification module, the fluctuation amplitude of the frequency converter control voltage and the door lock logic abnormal triggering frequency are monitored in real time by using non-ideal power supply fluctuation simulation, and the power supply induced instability coefficient DYS is calculated. This coefficient can accurately reflect the stability of the elevator control system under the power supply fluctuation interference, realize the early warning and risk identification of the door lock control failure caused by the power supply abnormality, guarantee the safe and reliable operation of the door lock logic, effectively prevent the elevator from stopping and safety accidents caused by the power supply fluctuation, and improve the stability and safety of the whole elevator operation.

[0109] Embodiment 9

[0110] This embodiment is an interpretation and explanation in embodiment 8. Specifically, the third analysis unit is used to preset a third threshold Q3, and the power supply induced instability coefficient DYS is compared with the third threshold Q3 for comparative analysis, and a third evaluation result is obtained, including:

[0111] When the power supply induced instability coefficient DYS is less than the third threshold Q3, it indicates that the control system input voltage fluctuation does not interfere with the door lock control, the door lock execution state is stable, and continuous monitoring is carried out.

[0112] When the third threshold Q3 is less than or equal to the power supply induced instability coefficient DYS and the power supply induced instability coefficient DYS is less than the fourth threshold Q4, it indicates that the control system input voltage fluctuation has interfered with the door lock control, and the door lock execution state is unstable. The door lock control strategy is adjusted, and the door lock control state is monitored. ​​When the power-induced instability coefficient DYS is greater than the third threshold value Q3, it indicates that there is a second-level fluctuation anomaly in the input voltage of the control system, which has the risk of causing door lock mis-triggering and logic disorder, triggers the fifth early warning instruction, generates the fifth strategy: immediately prohibit the elevator from continuing to run, push the maintenance personnel to replace the power filter component and door lock electromagnetic contact element maintenance suggestion, and mark the "control link power instability risk" label.

[0113] When the power-induced instability coefficient DYS is greater than the third threshold value Q3, it indicates that there is a second-level fluctuation anomaly in the input voltage of the control system, which has the risk of causing door lock mis-triggering and logic disorder, triggers the fifth early warning instruction, generates the fifth strategy: immediately prohibit the elevator from continuing to run, push the maintenance personnel to replace the power filter component and door lock electromagnetic contact element maintenance suggestion, and mark the "control link power instability risk" label.

[0114] The third threshold value Q3 is obtained in the following manner: In the experimental stage, multiple types of elevator control systems are selected to simulate different levels of power fluctuation conditions, focusing on covering non-ideal power supply situations such as transient voltage drop, voltage fluctuation frequency anomaly, and power phase shift. Corresponding variable frequency converter control voltage sampling data and door lock logic abnormal response data are collected to construct a historical sample data set. Through statistical analysis of multiple experimental samples of the power-induced instability coefficient DYS, the mean and standard deviation of DYS under stable operating conditions are obtained, reflecting the basic robustness of the system to power disturbances. On this basis, referring to the standard requirements for control system immunity and door lock response delay in "GB / T10060-2001 Elevator Electrical Control Equipment General Technical Conditions", the mean value of DYS plus 2 times the standard deviation is set as the third threshold value Q3. This setting range covers about 95% of normal fluctuation samples, which can identify door lock control hazards caused by power instability while ensuring continuous operation.

[0115] In this embodiment, the third analysis unit performs hierarchical evaluation of the power-induced instability coefficient DYS based on the preset third threshold value Q3, achieving accurate identification of door lock control anomalies caused by elevator control system input voltage fluctuations. When a first-level fluctuation anomaly is detected, the system automatically extends the response tolerance time of the door lock controller output logic, reduces false positives, and pushes maintenance recommendations; when a second-level fluctuation anomaly is detected, the elevator is immediately prohibited from running and a maintenance instruction is issued to replace the power filter component and door lock electromagnetic contact, significantly improving the safety protection capability of the elevator under abnormal power supply conditions and ensuring the stability and safety of the elevator door lock system.

[0116] Embodiment 10

[0117] ​An elevator operation failure early warning method, please refer to Figure 2 , comprising the following steps:

[0118] Step one, by configuring the elevator structure and its safety device parameters, to actively induce operation abnormalities that are difficult to appear but latent safety risks in normal operation, to build a plurality of extreme test conditions; the extreme test conditions include load critical drift test condition, sudden non-vertical force test condition and weak power fluctuation disturbance test condition;

[0119] Step two, collect data when the elevator is in the load critical drift test condition, the elevator is in the sudden non-vertical force test condition and the weak power fluctuation disturbance test condition;

[0120] Step three, based on the rated load curve of the car, establish a transient overload disturbance sequence, generate a drift overload response coefficient GZX, and compare and analyze it with the first threshold Q1, to determine whether the real-time load of the elevator car and the braking response are matched, if not matched, give the strategy;

[0121] Step four, by simulating the lateral stress response of the guide rail in the inclined state of the car, obtain the non-vertical disturbance coefficient DFG of the guide rail, and compare and analyze it with the second threshold Q2, to determine whether the safety gear action of the elevator car is synchronized, if not synchronized, give the strategy;

[0122] Step five, by introducing a non-ideal power supply fluctuation simulation, to monitor the stability of the door lock logic and control system response, to build a power-induced instability coefficient DYS, and to compare and analyze it with the third threshold Q3, to determine whether the control system input voltage fluctuation disturbs the door lock control, if it does, give the strategy.

[0123] In this embodiment, by constructing extreme condition test, data acquisition and multiple safety coefficient calculation and comparative analysis in steps, the safety risks of the elevator under complex abnormal conditions such as load drift, non-vertical force and power fluctuation can be systematically identified and evaluated, precise response strategies can be automatically generated for different abnormal degrees, the elevator operation safety and maintenance efficiency can be effectively improved, the risk of sudden failure can be reduced, and the stable operation of the elevator under extreme environment can be ensured.

[0124] The size of the threshold is set for easy comparison, and the size of the threshold depends on the amount of sample data and the base number set by the person skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameters and the quantized values.

[0125] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value, and the coefficients in the formulas are set by the person skilled in the art according to the actual situation. The above is only a preferred specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can make equivalent replacement or change according to the technical scheme and the inventive concept of the present application within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. An elevator operation failure early warning system, characterized by, Comprise: extreme working condition test module, for inducing operation abnormalities that are difficult to appear but potential safety risks in normal operation based on elevator structure configuration and its safety device parameters, to build multiple extreme test working conditions; The extreme test working condition includes load critical drift test working condition, sudden non-vertical force test working condition and weak power fluctuation disturbance test working condition; Data acquisition module for collecting data of elevator in load critical drift test working condition, elevator in sudden non-vertical force test working condition and weak power fluctuation disturbance test working condition; Load critical drift effect identification module is used to establish transient overload disturbance sequence based on car rated load curve, generate drift overload response coefficient GZX, and compare and analyze with first threshold Q1, to judge whether elevator car real-time load and brake response match, if not match, give strategy; Sudden non-vertical force effect identification module is used to simulate car tilt state under guide rail lateral stress response, obtain guide rail non-vertical disturbance coefficient DFG, and compare and analyze with second threshold Q2, to judge whether elevator car safety gear action is synchronous, if not synchronous, give strategy; Weak power fluctuation disturbance effect identification module is used to introduce non-ideal power supply fluctuation simulation, to monitor stability of door lock logic and control system response, to build power induced instability coefficient DYS, and compare and analyze with third threshold Q3, to judge whether control system input voltage fluctuation disturbs door lock control, if disturbance, give strategy.

2. The elevator operation failure early warning system according to claim 1, characterized by, The extreme working condition test module includes equipment identification unit, load critical drift test working condition unit, sudden non-vertical force test working condition unit and weak power fluctuation disturbance test working condition unit; The equipment identification unit is used to identify and label the constituent equipment of elevator whole machine structure and its key safety devices, to collect information including equipment unique number, installation floor and relative position, debugging configuration number, safety interface type and response characteristic parameter through two-dimensional code and radio frequency tag scanning, control system equipment code analysis and historical operation data retrieval mode; The load critical drift test working condition unit is used to induce brake response lag and tension unevenness by simulating car load center of gravity shift in boundary state close to rated limit; The sudden non-vertical force test working condition unit is used to induce guide rail friction force unevenness and safety gear asymmetric response by introducing car micro-tilt, guide rail installation deviation or rope wheel tension asymmetry; The weak power fluctuation disturbance test working condition unit is used to induce door lock controller and safety device logic response under power abnormality by control system voltage short-time drop.

3. An elevator operation failure early warning system according to claim 2, characterized in that, The data acquisition module includes load critical drift test working condition acquisition unit, sudden non-vertical force test working condition acquisition unit and weak power fluctuation disturbance test working condition acquisition unit; The load critical drift test working condition acquisition unit is used to collect data of elevator in load critical drift test working condition, to collect car load value sequence by installing high-precision load cell on car bottom weighing support structure, to record load feedback value in starting response stage by installing tension load cell on brake transmission shaft connection structure; The sudden non-vertical force test working condition collection unit is used for collecting data of the elevator in a sudden non-vertical force test working condition, collecting a left and right side guide rail friction value sequence by installing a film friction sensor on a left and right guide shoe base and a side slide surface; and collecting a left and right side traction rope tension value by installing a tension sensor at an elevator shaft upper rope wheel outlet guide wheel. The weak power fluctuation interference test working condition collection unit is used for collecting data in a weak power fluctuation interference test working condition, collecting a control voltage value sequence by installing a high-speed voltage monitoring sensor on a PLC power input port and a frequency converter main control input end; and recording an abnormal intermittent or switch abnormal number of times by setting a logic state recording program on a door lock control logic board.

4. The elevator operation failure early warning system according to claim 1, characterized by, The load critical drift effect recognition module includes a first calculation unit and a first analysis unit. The first calculation unit is used for extracting load critical drift test working condition data, establishing a transient overload disturbance sequence based on a car rated load curve, and calculating a drift overload response coefficient GZX after dimensionless processing.

5. An elevator operation failure early warning system according to claim 4, characterized in that, The first analysis unit is used for comparing and analyzing the drift overload response coefficient GZX with a first threshold Q1 by presetting the first threshold Q1, and obtaining a first evaluation result, including: When the drift overload response coefficient GZX is less than the first threshold Q1, it indicates that the real-time load of the elevator car matches the brake response, the elevator runs stably, and continuous monitoring is performed. When the first threshold Q1≤drift overload response coefficient <GZX first threshold , indicating that the elevator real-time load and brake response match the first level of abnormality, there is a risk of brake delay, triggering the first early warning instruction, generating the first strategy: extending the 20% pre-brake trigger signal timing, increasing the brake reaction time; Labeling the load response offset risk for this elevator, pushing the maintenance personnel to repair the maintenance suggestion of the weighing displacement feedback device; When the drift overload response coefficient GZX > the first threshold value When the drift overload response coefficient GZX > the first threshold value, it indicates that the elevator real-time load and the brake response match the secondary abnormality, there is a risk of brake failure, triggers the second early warning instruction, and generates the second strategy: immediately prohibit the elevator operation, and push the maintenance suggestion of replacing the brake tension spring to the maintenance personnel.

6. The elevator operational failure early warning system of claim 1, wherein, The sudden non-vertical force effect recognition module includes a second calculation unit and a second analysis unit. The second calculation unit is used for simulating a car tilting state guide rail lateral stress response, extracting sudden non-vertical force test working condition data, and calculating a guide rail non-vertical interference coefficient DFG after dimensionless processing.

7. An elevator operational failure early warning system according to claim 6, wherein, The second analysis unit is used for comparing and analyzing the guide rail non-vertical interference coefficient DFG with a second threshold Q2 by presetting the second threshold Q2, and obtaining a second evaluation result, including: When the guide rail non-vertical interference coefficient DFG is less than the second threshold Q2, it indicates that the safety gear action of the elevator car is synchronous, there is no risk of oblique braking, and continuous monitoring is performed. When the guide rail non-vertical interference coefficient DFG is greater than or equal to the second threshold Q2, it indicates that the safety gear action of the elevator car is asynchronous, there is a risk of oblique braking, a third warning instruction is triggered, and a third strategy is generated: performing a safety gear recalibration process on the elevator, stopping the elevator at a maintenance layer, cutting off the main drive circuit, and only retaining a calibration power supply and control channel; issuing a safety gear calibration mode instruction through a maintenance panel, loading the current left and right guide rail friction and tension data, releasing the left and right safety gear braking states respectively, checking whether the release is synchronous, if synchronous, suggesting manual periodic retesting, prompting to check the coaxiality of the rope wheel and fine-tune the guide shoe, if either side fails to release, locking the system operation, prompting "brake mechanism jamming", and aborting the process and prompting manual maintenance.

8. The elevator operational failure early warning system of claim 1, wherein, The weak power fluctuation interference effect recognition module includes a third calculation unit and a third analysis unit. The third calculation unit is used for introducing a non-ideal power supply fluctuation simulation, monitoring the stability of the door lock logic and control system response, extracting weak power fluctuation interference test working condition data, and calculating a power induced instability coefficient DYS after dimensionless processing.

9. An elevator operational failure early warning system according to claim 8, wherein, The third analysis unit is used to preset a third threshold Q3, and the power supply induced instability coefficient DYS is compared and analyzed with the third threshold Q3 to obtain a third evaluation result, including: When the power supply induced instability coefficient DYS is less than the third threshold Q3, it indicates that the control system input voltage fluctuation does not interfere with the door lock control, the door lock execution state is stable, and continuous monitoring is performed. When the third threshold Q3≤power-induced instability coefficient DYS<the third threshold When the third threshold Q3≤power-induced instability coefficient DYS<the third threshold When the third threshold Q3≤power-induced instability coefficient DYS<the third threshold When the third threshold Q3≤power-induced instability coefficient DYS<the third threshold When the third threshold Q3≤power-induced instability coefficient DYS<the third threshold When the third threshold Q3≤power-induced instability coefficient DYS<the third threshold When the third threshold Q3≤power-induced instability coefficient DYS<the third threshold When the third threshold Q3≤power-induced instability coefficient DYS<the third threshold When the third threshold Q3≤power-induced instability coefficient DYS<the third threshold When the third threshold Q3≤power-induced instability coefficient DYS<the third threshold When the third threshold Q3≤power-induced instability coefficient DYS<the third threshold When the third threshold Q3≤power-induced instability coefficient DYS When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS ≥ third threshold value When the power supply induces a DYS 10. A method for elevator operation failure early warning, applied to the elevator operation failure early warning system of any one of claims 1-9, characterized in that, The method comprises the following steps: Step one, based on the elevator structure configuration and its safety device parameters, actively induce operation abnormalities that are difficult to appear but latent safety risks in normal operation process, and construct multiple extreme test conditions; the extreme test conditions include load critical drift test condition, sudden non-vertical force test condition and weak power fluctuation interference test condition; Step two, collect data of the elevator in the load critical drift test condition, the elevator in the sudden non-vertical force test condition and the weak power fluctuation interference test condition; Step three, establish a transient overload disturbance sequence based on the car rated load curve, generate a drift overload response coefficient GZX, and compare and analyze it with the first threshold Q1 to determine whether the elevator car real-time load and brake response are matched, and if not, give a strategy; Step four, by simulating the lateral stress response of the guide rail in the inclined state of the car, obtain a guide rail non-vertical interference coefficient DFG, and compare and analyze it with the second threshold Q2 to determine whether the safety gear action of the elevator car is synchronized, and if not, give a strategy; Step five, by introducing a non-ideal power supply fluctuation simulation, the stability of the door lock logic and control system response is monitored, a power supply induced instability coefficient DYS is constructed, and compared and analyzed with the third threshold Q3 to determine whether the control system input voltage fluctuation interferes with the door lock control, and if so, give a strategy.

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