Elevator brake failure edge detection method and system

Abstract

The application discloses an elevator brake failure edge detection method and system, and belongs to the technical field of elevator brake performance detection. First, define the car empty load to go up to the upper end forced deceleration position at the maximum allowable speed, and the loaded 110% rated load to go down to the lower end forced deceleration position at the maximum allowable speed as the brake failure edge condition; calculate the theoretical minimum braking deceleration according to the maximum running speed and the buffer parameters; adopt the same load twice braking method to measure the actual braking deceleration under four working conditions of the empty load uplink middle and upper parts and the 110% load downlink middle and lower parts, introduce the multi-physical field compensation model such as the steel wire rope elasticity correction, the non-uniform correction of the compensating chain, the temperature and humidity compensation and the rotational inertia decoupling, and calculate the actual braking deceleration of the failure edge by using the difference formula; calculate the safety margin coefficient to carry out three-level grading early warning. The method has the advantages of high detection precision, good safety, high automation degree, the ability of detecting the elevator brake failure edge and predicting the remaining life.

Description

Technical Field

[0001] This invention relates to the field of elevator braking performance testing technology, and in particular to a method and system for detecting the failure edge of an elevator brake. Background Technology

[0002] Elevator brakes are core components ensuring the safe operation of elevators, and their braking performance directly affects the safety of personnel and equipment. Current elevator brake performance testing methods primarily employ a 125% rated load downward braking test and a 100% rated load group braking test, assuming the failure of one group of braking components in the drive unit's electromechanical brake. The existing technology has the following problems: 1. The specific operating environment of the elevator and the specific technical parameters of its components were ignored, making it difficult for the test results to reflect the true performance of the brake under actual working conditions.

[0003] 2. 125% of the rated load exceeds the upper limit of the normal operating load, which poses a risk of damaging the elevator car structure, traction system and wire rope. In addition, moving the weights is time-consuming, labor-intensive and has a high safety risk.

[0004] 3. While some no-load alternative testing methods avoid the need to handle weights, they have some shortcomings: they require prior knowledge of the balance coefficient K; they do not consider the influence of physical field factors such as the elastic deformation of the wire rope, the non-uniformity of the compensation chain, changes in ambient temperature and humidity, and the rotational inertia of the system on the braking deceleration; they can only output a qualitative judgment of pass or fail, and cannot provide quantitative safety margin and life prediction; the testing process still requires a lot of manual operation and has a low degree of automation. Summary of the Invention

[0005] This invention aims to at least solve one of the technical problems existing in the prior art. To this end, this invention proposes a method and system for detecting the failure edge of an elevator brake. By performing braking tests at two different positions under the same load, the method utilizes the position difference and deceleration difference to eliminate braking force and system mass parameters that are difficult to measure directly, thereby automatically and accurately detecting the failure edge of the elevator brake and predicting its remaining life.

[0006] On one hand, embodiments of the present invention provide a method for detecting the failure edge of an elevator brake, including: The elevator car is unloaded and moves upward at the maximum permissible speed, then brakes at the forced deceleration position at the upper end of the shaft; the elevator car is loaded with a load of 110% of its rated load and moves downward at the maximum permissible speed, then brakes at the forced deceleration position at the lower end of the shaft, thus determining the conditions for the failure edge of the elevator brake. Based on the maximum permissible operating speed of the elevator car V1 and the maximum impact speed of the buffer V 2，And the minimum braking deceleration a in the upward direction is calculated based on the minimum braking deceleration calculation formula, using the distance H1 between the end face of the counterweight buffer and the impact plate or the distance H2 between the end face of the car buffer and the impact plate. u1 and the minimum braking deceleration a in the downward direction d1 Determine the theoretical value of the minimum braking deceleration at the edge of elevator brake failure; The actual braking deceleration at the failure edge was measured using the same-load double braking method: the average braking deceleration a1 from unloaded upward travel to the middle of the travel, the average braking deceleration a2 from unloaded upward travel to the upper part of the travel, the average braking deceleration a3 from 110% rated load downward travel to the middle of the travel, and the average braking deceleration a4 from 110% rated load downward travel to the lower part of the travel, and the corresponding car positions L1, L2, L3 and L4 were recorded. The actual braking deceleration a at the failure edge position in the upward direction is calculated based on the braking deceleration difference formula. u2 And the actual braking deceleration a in the downward direction at the failure edge position. d2 ; If (a u2 >a u1 And (a) d2 >a d1 If the elevator brake is on the verge of failure or has already failed, then the elevator brake is considered safe; otherwise, the elevator brake is considered to be on the verge of failure or has already failed. Calculate and output the safety margin coefficients for the uplink and downlink directions.

[0007] According to some embodiments of the present invention, the formula for calculating the minimum braking deceleration is as follows: a u1 = (V1 2 -V2 2 ) / (2H1), a d1 = (V1 2 -V2 2 ) / (2H2); In the formula, a u1 For the minimum braking deceleration in the upward direction, a d1 V1 is the minimum braking deceleration in the downward direction, V2 is the maximum permissible running speed of the car, V2 is the maximum impact speed of the buffer, H1 is the distance between the end face of the counterweight buffer and the impact plate, and H2 is the distance between the end face of the car buffer and the impact plate. The braking deceleration difference formula is as follows: a u2 = a1- (L2(a1-a2) / L1) · (1+J / (mR 2 )) -1 + f(T,H r ), ad2 = a3- (L4(a3-a4) / L3) · (1+J / (mR 2 )) -1 + g(T,H r ); In the formula, a u2 a is the actual braking deceleration in the upward direction at the failure edge position. d2 Let J be the actual braking deceleration in the downward direction at the failure edge position, m be the system moment of inertia, R be the car system mass, L be the traction sheave radius, L1, L2, L3, and L4 be the car positions, and f(T,H) be the actual braking deceleration in the downward direction at the failure edge position. r ) is the temperature and humidity compensation function in the upward direction, g(T,H) r ) represents the temperature and humidity compensation function in the downward direction, where T is the ambient temperature of the brake operating environment, and H is the temperature and humidity compensation function in the downward direction. r Relative humidity; The formula for calculating the safety margin coefficient is as follows: η u = a u2 / a u1 , η d = a d2 / a d1 ; In the formula, η u η is the safety margin factor in the upward direction. d This represents the safety margin coefficient in the downward direction.

[0008] According to some embodiments of the present invention, the method for obtaining the system's moment of inertia includes: After the motor travels to the top of its travel without load, keep the brake closed and briefly energize to reverse the motor. Measure the static holding torque of the brake, and calculate the equivalent value of the system's moment of inertia by using the relationship between torque and angular acceleration; Substituting the system's rotational inertia into the braking deceleration differential formula achieves complete decoupling between rotation and translation.

[0009] According to some embodiments of the present invention, in the step of measuring the actual braking deceleration at the failure edge using the co-load secondary braking method, multi-sensor fusion and redundancy verification are employed: The linear acceleration is measured using an accelerometer installed inside the car, the angular acceleration is measured using a rotary encoder installed on the side of the traction sheave, and the slippage is measured using a magnetic scale installed on the surface of the wire rope. The measured values ​​of three independent physical quantities are fused using Kalman filtering to obtain the optimal estimated deceleration value; If the deviation of the three values ​​exceeds the preset threshold, it is determined to be a measurement abnormality and an alarm is triggered.

[0010] According to some embodiments of the present invention, the step of measuring the actual braking deceleration at the failure edge using the same-load secondary braking method further includes: Temperature and humidity sensors are installed on the brake shoes to collect the ambient temperature and relative humidity of the brake's working environment in real time. Establish the formula for the braking torque decay model: F b (T,H r ) = F b0 · (1-k T ·(T-T0))·(1-k H ·(H r -H r0 )) ; In the formula, F b0 The standard power is the brake's operating temperature under standard conditions, where T is the brake's ambient temperature and H is the rated power. r For relative humidity, k T The temperature decay coefficient is determined experimentally; k H The humidity attenuation coefficient is T0; T0 is the temperature under standard operating conditions, and H is the humidity attenuation coefficient. r0 Humidity under standard operating conditions; Normalize a1, a2, a3, and a4 by dividing the measured values ​​by (1-k). T ·(T-T0))·(1-k H ·(H r -H r0 This yields the deceleration under equivalent standard operating conditions, thus eliminating the influence of environmental differences on the test results.

[0011] According to some embodiments of the present invention, the step of measuring the actual braking deceleration at the failure edge using the same-load secondary braking method further includes: Establish a dynamic length correction model for the traction wire rope and calculate the elastic elongation of the wire rope: ΔL = F r · L / (E·A), In the formula, F r Let E be the tension of the wire rope, E be the modulus of elasticity, and A be the total cross-sectional area of ​​the wire rope. Introduce a non-uniform linear density correction factor λ(h): λ(h) = 1 + α·(h / H) 2 , In the formula, α is an empirical constant, ranging from 0.02 to 0.05, obtained through experimental fitting; h is the actual height of the car from the ground floor; and H is the total lifting height. Add the correction term β·(ΔL / L1)·(a1-a2) to the calculation formula of the braking deceleration difference formula; In the formula, β is the elastic compensation coefficient, with a value range of 0.1 to 0.3, which is calibrated through a single no-load self-learning run.

[0012] According to some embodiments of the present invention, after the step of calculating and outputting the uplink safety margin coefficient and the downlink safety margin coefficient, the method further includes: Based on the safety margin factor, a graded early warning system for failure edge is implemented: If η ≥ 1.2, then it is level one safety; If 1.0 ≤ η < 1.2, then it is a level two attention; If η < 1.0, then it is a level three hazard; Collect at least 3 historical test data, use the grey prediction model GM(1,1) to predict the changing trend of the safety margin coefficient in the next 6 months, predict the safe life, and output the remaining safe operating days or suggest the next test date.

[0013] According to some embodiments of the present invention, the method further includes self-learning calibration: After the elevator is first installed or inspected, it automatically performs a full-condition calibration procedure to measure the standard deceleration under each condition, and calculate and store the system parameters. Subsequent testing will automatically call upon the stored system parameters for correction, eliminating the need to repeatedly measure system parameters.

[0014] On the other hand, embodiments of the present invention provide an elevator brake failure edge detection system for implementing the above-mentioned elevator brake failure edge detection method, comprising: The brake detection module includes an acceleration detection unit, a position detection unit, a temperature and humidity detection unit, a rotary encoder, and a magnetic scale module. The acceleration detection unit is installed inside the car or on the traction steel cable and is used to measure the average braking deceleration during braking. The position detection unit is equipped with a laser rangefinder, installed inside the hoistway, and is used to measure the real-time position of the car within the hoistway. The temperature and humidity detection unit includes a patch thermocouple and a humidity sensor, installed at the brake shoe, and is used to collect brake operating environment parameters. The rotary encoder is installed on the traction sheave side and is used to measure angular acceleration. The magnetic scale is installed on the surface of the steel cable and is used to measure slippage. An edge computing terminal, installed in the elevator machine room or control cabinet, is connected to the brake detection module and is used to execute the above-mentioned elevator brake failure edge detection method. The cloud service platform, connected to the edge computing terminal, is used to store historical detection data, execute gray prediction models, and push early warning information.

[0015] According to some embodiments of the present invention, the edge computing terminal includes: The data acquisition module is used to receive measurement data from the brake detection module; The self-learning calibration module is used to automatically execute the full-condition calibration procedure after initial installation or maintenance and to store system parameters. The differential calculation module is used to calculate the actual braking deceleration at the failure edge based on the same-load secondary braking method; the temperature and humidity compensation module is used to correct the deceleration calculation results based on the data from the temperature and humidity detection unit. The rotational inertia decoupling module is used to eliminate the influence of the system's rotational inertia on the calculation results; The graded early warning module is used to calculate the safety margin coefficient and classify the safety levels; The lifespan prediction module is used to output the remaining safe operating days based on a grey prediction model.

[0016] The embodiments of the present invention have at least the following beneficial effects: By conducting braking tests at two different locations (middle and upper / lower) under the same load, the braking force and system mass parameters that are difficult to measure directly are eliminated by utilizing the position difference and deceleration difference. Multi-physics compensation models, such as wire rope elasticity correction, compensation chain non-uniformity correction, temperature and humidity compensation, and rotational inertia decoupling, are introduced to improve calculation accuracy. Graded early warning is implemented through safety margin coefficients, and a grey prediction model is used to predict remaining life. A multi-sensor fusion and redundancy verification mechanism is employed to ensure the reliability and robustness of the detection. By introducing multi-physics coupling compensation, differential inference, graded early warning, grey prediction models, and edge computing, the problems of high risk, low accuracy, and lack of intelligence in existing elevator brake detection methods are effectively solved. This allows for automatic and accurate detection of elevator brake failure edges and prediction of remaining life.

[0017] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0018] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart of the elevator brake failure edge detection method according to an embodiment of the present invention; Figure 2 This is a functional block diagram of the elevator brake failure edge detection system according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the elevator car's running position and measurement conditions in the elevator brake failure edge detection method according to an embodiment of the present invention. Figure 4This is a schematic diagram of the elevator car position and running direction during measurement a1 of the elevator brake failure edge detection method according to an embodiment of the present invention. Figure 5 This is a schematic diagram of the elevator car position and running direction during measurement a2 in the elevator brake failure edge detection method of this embodiment of the invention; Figure 6 This is a schematic diagram of the elevator car position and running direction when measuring a3 in the elevator brake failure edge detection method of this embodiment of the invention; Figure 7 This is a schematic diagram of the hierarchical early warning and gray prediction model output of the elevator brake failure edge detection method according to an embodiment of the present invention. Detailed Implementation

[0019] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0020] In the description of this invention, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., are based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention.

[0021] In the description of this invention, "several" means one or more, "multiple" means two or more, "greater than," "less than," "exceeding," etc. are understood to exclude the stated number, and "above," "below," "within," etc. are understood to include the stated number. If "first," "second," etc. are used in the description, they are only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance or implicitly indicating the number of indicated technical features or the order of the indicated technical features.

[0022] In the description of this invention, unless otherwise explicitly defined, the terms "setting", "installing", "connecting" and "linking" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this invention in conjunction with the specific content of the technical solution.

[0023] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] Please see Figures 1 to 3 This embodiment provides a method for detecting the failure edge of an elevator brake, mainly including steps S101~S106: S101. When the elevator car is unloaded and moves upward at the maximum permissible operating speed, it is braked at the forced deceleration position at the upper end of the shaft; when the elevator car is loaded with a load of 110% of its rated load capacity and moves downward at the maximum permissible operating speed, it is braked at the forced deceleration position at the lower end of the shaft. This determines the conditions for determining the edge of elevator brake failure.

[0025] S102, Based on the maximum permissible operating speed of the elevator car V1 and the maximum impact speed of the buffer V... 2， And the minimum braking deceleration a in the upward direction is calculated based on the minimum braking deceleration calculation formula, using the distance H1 between the end face of the counterweight buffer and the impact plate or the distance H2 between the end face of the car buffer and the impact plate. u1 and the minimum braking deceleration a in the downward direction d1 To determine the theoretical value of the minimum braking deceleration at the edge of elevator brake failure.

[0026] S103. Measure the actual braking deceleration at the edge of failure using the same-load secondary braking method: Measure the average braking deceleration a1 from unloaded upward travel to the middle of the travel, the average braking deceleration a2 from unloaded upward travel to the upper part of the travel, the average braking deceleration a3 from 110% rated load downward travel to the middle of the travel, and the average braking deceleration a4 from 110% rated load downward travel to the lower part of the travel, and record the corresponding car positions L1, L2, L3, and L4.

[0027] S104. Calculate the actual braking deceleration a in the upward direction at the failure edge position based on the braking deceleration difference formula. u2 And the actual braking deceleration a in the downward direction at the failure edge position. d2 .

[0028] S105, if (a u2 >a u1 And (a) d2 >a d1 If the elevator brake is within a certain range, it is determined that the elevator brake is safe; otherwise, it is determined that the elevator brake is on the verge of failure or has already failed.

[0029] S106. Calculate and output the safety margin coefficients for the uplink and downlink directions.

[0030] The formula for calculating the minimum braking deceleration is as follows: a u1 = (V1 2 -V2 2 ) / (2H1), a d1 = (V1 2 -V2 2 ) / (2H2); In the formula, a u1For the minimum braking deceleration in the upward direction, a d1 V1 is the minimum braking deceleration in the downward direction, V2 is the maximum permissible running speed of the car, V2 is the maximum impact speed of the buffer, H1 is the distance between the end face of the counterweight buffer and the impact plate, and H2 is the distance between the end face of the car buffer and the impact plate.

[0031] The differential formula for braking deceleration is: a u2 = a1- (L2(a1-a2) / L1) · (1+J / (mR 2 )) -1 + f(T,H r ), a d2 = a3- (L4(a3-a4) / L3) · (1+J / (mR 2 )) -1 + g(T,H r ); In the formula, a u2 a is the actual braking deceleration in the upward direction at the failure edge position. d2 Let J be the actual braking deceleration in the downward direction at the failure edge position, m be the system moment of inertia, R be the car system mass, L be the traction sheave radius, L1, L2, L3, and L4 be the car positions, and f(T,H) be the actual braking deceleration in the downward direction at the failure edge position. r ) is the temperature and humidity compensation function in the upward direction, g(T,H) r ) represents the temperature and humidity compensation function in the downward direction, where T is the ambient temperature of the brake operating environment, and H is the temperature and humidity compensation function in the downward direction. r This refers to relative humidity. For outdoor sightseeing elevators, temperature and humidity compensation needs to be increased during the hot and humid summer months to reduce errors.

[0032] The formula for calculating the safety margin factor is: η u = a u2 / a u1 , η d = a d2 / a d1 ; In the formula, η u η is the safety margin factor in the upward direction. d This represents the safety margin coefficient in the downward direction.

[0033] The above-mentioned method for obtaining the system's moment of inertia includes: After the motor travels to the top of its travel without load, keep the brake closed and briefly energize to reverse the motor. Measure the static holding torque of the brake, and calculate the equivalent value of the system's moment of inertia by using the relationship between torque and angular acceleration; Substituting the system's moment of inertia into the braking deceleration differential formula achieves complete decoupling between rotation and translation.

[0034] In step S103 above, the actual braking deceleration at the failure edge is measured using the same-load secondary braking method, and multi-sensor fusion and redundancy verification are employed. The linear acceleration is measured using an accelerometer installed inside the car, the angular acceleration is measured using a rotary encoder installed on the side of the traction sheave, and the slippage is measured using a magnetic scale installed on the surface of the wire rope. The measured values ​​of three independent physical quantities are fused using Kalman filtering to obtain the optimal estimated deceleration value; If the deviation of the three values ​​exceeds the preset threshold, it is determined to be a measurement abnormality and an alarm is triggered.

[0035] The step S103 above, which uses the same-load secondary braking method to measure the actual braking deceleration at the failure edge, also includes: Temperature and humidity sensors are installed on the brake shoes to collect the ambient temperature and relative humidity of the brake's working environment in real time. Establish the formula for the braking torque decay model: F b (T,H r ) = F b0 · (1-k T ·(T-T0))·(1-k H ·(H r -H r0 )) ; In the formula, F b0 The standard power is the brake's operating temperature under standard conditions, where T is the brake's ambient temperature and H is the rated power. r For relative humidity, k T The temperature decay coefficient is determined experimentally; k H The humidity attenuation coefficient is T0; T0 is the temperature under standard operating conditions, and H is the humidity attenuation coefficient. r0 Humidity under standard operating conditions; Normalize a1, a2, a3, and a4 by dividing the measured values ​​by (1-k). T ·(T-T0))·(1-k H ·(H r -H r0 This yields the deceleration under equivalent standard operating conditions, thus eliminating the influence of environmental differences on the test results.

[0036] The step S103 above, which uses the same-load secondary braking method to measure the actual braking deceleration at the failure edge, also includes: Establish a dynamic length correction model for the traction wire rope and calculate the elastic elongation of the wire rope: ΔL = F r· L / (E·A), In the formula, F r Let E be the tension of the wire rope, E be the modulus of elasticity, and A be the total cross-sectional area of ​​the wire rope. Introduce a non-uniform linear density correction factor λ(h): λ(h) = 1 + α·(h / H) 2 , In the formula, α is an empirical constant, ranging from 0.02 to 0.05, obtained through experimental fitting; h is the actual height of the car from the ground floor; and H is the total lifting height. Add the correction term β·(ΔL / L1)·(a1-a2) to the calculation formula of the braking deceleration difference formula; In the formula, β is the elastic compensation coefficient, with a value range of 0.1 to 0.3, which is calibrated through a single no-load self-learning run.

[0037] In step S106 above, after calculating and outputting the uplink safety margin coefficient and the downlink safety margin coefficient, the following is also included: Based on the safety margin factor, a graded early warning system for failure edge is implemented: If η ≥ 1.2, then it is level one safety; If 1.0 ≤ η < 1.2, then it is a level two attention; If η < 1.0, then it is a level three hazard; Collect at least 3 historical test data, use the grey prediction model GM(1,1) to predict the changing trend of the safety margin coefficient in the next 6 months, predict the safe life, and output the remaining safe operating days or suggest the next test date.

[0038] In some embodiments of the present invention, the method further includes self-learning calibration: After the elevator is first installed or inspected, it automatically performs a full-condition calibration procedure to measure the standard deceleration under each condition, and calculate and store the system parameters. Subsequent testing will automatically call upon the stored system parameters for correction, eliminating the need to repeatedly measure system parameters.

[0039] For example, after the elevator is first installed, a full-condition calibration procedure is automatically executed. Based on the measured standard deceleration under each condition, the system parameters (such as the standard driving force F under standard conditions) are deduced. b0 The following parameters are calculated and stored: car system mass m, system moment of inertia J, empirical constant α, and elastic compensation coefficient β.

[0040] Please see Figure 2 This embodiment discloses an elevator brake failure edge detection system for implementing the aforementioned elevator brake failure edge detection method, comprising: The brake detection module 100 includes an acceleration detection unit, a position detection unit, a temperature and humidity detection unit, a rotary encoder, and a magnetic scale. The acceleration detection unit is installed inside the car or on the traction steel wire rope to measure the average braking deceleration during braking. The position detection unit is equipped with a laser rangefinder, installed inside the hoistway, to measure the real-time position of the car in the hoistway. The temperature and humidity detection unit includes a patch thermocouple and a humidity sensor, installed at the brake shoe, to collect the brake's operating environment parameters. The rotary encoder is installed on the side of the traction sheave to measure angular acceleration. The magnetic scale is installed on the surface of the steel wire rope to measure slippage. Edge computing terminal 200 is installed in the elevator machine room or control cabinet and connected to brake detection module 100 to perform the above-mentioned elevator brake failure edge detection method. The cloud service platform 300 is connected to the edge computing terminal 200 to store historical detection data, execute gray prediction models, and push early warning information.

[0041] In some embodiments of the present invention, the edge computing terminal 200 includes: The data acquisition module is used to receive measurement data from the brake detection module 100; The self-learning calibration module is used to automatically execute the full-condition calibration procedure after initial installation or maintenance and to store system parameters. The differential calculation module is used to calculate the actual braking deceleration at the failure edge based on the same-load secondary braking method; the temperature and humidity compensation module is used to correct the deceleration calculation results based on the data from the temperature and humidity detection unit. The rotational inertia decoupling module is used to eliminate the influence of the system's rotational inertia on the calculation results; The graded early warning module is used to calculate the safety margin coefficient and classify the safety levels; The lifespan prediction module is used to output the remaining safe operating days based on a grey prediction model.

[0042] The elevator brake failure edge detection method and system provided in this embodiment will be described in detail below: 1. Determine the conditions for the failure edge of the elevator brake.

[0043] (1) Failure boundary condition of car upward movement When the elevator car is empty and traveling upwards at its maximum permissible speed, emergency braking is most critical at the forced deceleration position at the top of the shaft (usually a certain distance between the car and the top terminal, preset by the elevator control system based on rated speed and deceleration). This is because, when empty, the counterweight side has a greater weight than the car side, resulting in the maximum eccentric torque; the car's kinetic and potential energy are both high during upward travel; and the forced deceleration position is close to the limit, meaning that brake failure could lead to overshooting the top. Therefore, this invention defines the brake failure edge condition in the upward direction as the car traveling upwards at its maximum permissible speed with an empty car, and then braking at the forced deceleration position at the top of the shaft. The maximum permissible speed can be obtained by consulting the elevator's technical parameter table or the speed governor nameplate.

[0044] (2) Failure boundary conditions of car descent According to national standards, overload detection devices should trigger an alarm and stop the elevator when the load exceeds 110% of the rated load capacity. Therefore, 110% of the rated load capacity is the upper limit allowed for normal elevator operation. Under this load, braking tests will not exceed the overload protection threshold, ensuring both safety and close approximation of actual operating limits. When the car is loaded with 110% of the rated load and descends at the maximum permissible operating speed to the forced deceleration position at the bottom of the hoistway, the inertial force and eccentric torque that the brake needs to overcome are at their maximum. Therefore, this invention defines "a load of 110% of the rated load in the car, descending at the maximum permissible operating speed, and braking at the forced deceleration position at the bottom of the hoistway" as the brake failure edge condition in the downward direction.

[0045] 2. Determine the theoretical value of the minimum braking deceleration at the edge of elevator brake failure.

[0046] (1) Obtain elevator technical parameters The elevator technical parameter table shows: The maximum permissible operating speed of the car is V1 (unit: m / s). This value is usually equal to 1.0 to 1.2 times the rated speed, depending on the speed limiter setting.

[0047] The maximum impact velocity of the buffer is V2 (unit: m / s). This value can be obtained from the buffer type test certificate or nameplate. Different buffer types correspond to different V2 values, which are generally 0.5~2.5 m / s.

[0048] (2) Measurement position and spacing The following two key distances were measured using a laser rangefinder: When the car is in the forced deceleration position at the upper end of the hoistway, record the car's position L2 in the hoistway (with the ground floor level as the reference zero point, upward as positive), and simultaneously measure the distance H1 (unit: m) between the counterweight buffer end face and the counterweight impact plate. This distance can be directly measured using a laser rangefinder in the hoistway pit.

[0049] When the car is in the forced deceleration position at the lower end of the hoistway, record the car position L4 and measure the distance H2 between the end face of the car buffer and the car impact plate.

[0050] (3) Calculate the theoretical minimum braking deceleration According to Newton's second law of motion, a force analysis is performed on the elevator braking process. Under ideal conditions (ignoring the elasticity of the steel rope, air resistance, etc.), when the car impacts the buffer at velocity V1, its velocity must be reduced to no more than the maximum allowable impact velocity V2 of the buffer within the remaining buffer travel H1 or H2. This is derived from the formula for uniformly decelerated motion: V2 2 =V1 2 2aH; The required minimum average deceleration can be obtained: a = (V1 2 -V2 2 ) / (2H); Therefore, the theoretical value of the minimum braking deceleration in the upward direction is: a u1 = (V1 2 -V2 2 ) / (2H1); The theoretical minimum braking deceleration in the downward direction is: a d1 = (V1 2 -V2 2 ) / (2H2); This value represents the following: if the actual braking deceleration that the brake can provide is greater than this value, the elevator can still be safely stopped without damaging the buffer under the condition of failure edge; otherwise, there is a risk of overshooting or bottoming out.

[0051] 3. The actual braking deceleration at the failure edge is measured using the same-load secondary braking method, and multi-physics field compensation is introduced.

[0052] The same load double braking method is adopted, that is, under the same load (no load or 110% load), two braking tests are carried out at the middle position and the upper / lower position respectively. The unknown system parameters are eliminated by the difference between the two measurement results.

[0053] Please see Figure 3 Braking deceleration was measured under four operating conditions, as detailed below: (1) Operating Condition 1: Please refer to Figure 4, with the car at no load, traveling upward at the rated speed to the middle of the travel (i.e., the car and the counterweight are at the same horizontal position, at which time the masses of the steel wire ropes and the compensation chains on both sides of the traction sheave are substantially equal, and the unbalanced torque is only generated by the weight difference between the car and the counterweight), the power supply to the motor and the brake is cut off to make the brake perform emergency braking. An acceleration sensor installed in the car (or a rotary encoder installed on the traction steel wire ropes) is used to record the speed-time curve throughout the braking process, and the average braking deceleration from the start of braking to the complete stop of the car is calculated by integration or differentiation, denoted as a1. At the same time, the position of the car at the moment when braking starts is recorded, denoted as L1. For the convenience of calculation, the middle position of the travel is defined as the coordinate origin (L=0), the position at the top floor leveling is +L (L is half of the full travel), and the position at the bottom floor leveling is L.

[0054] (2) Working condition 2: Please refer to Figure 5 , with the car at no load, traveling upward at the rated speed to a certain position L1 in the upper part of the travel (satisfying L<L1<L, usually L1=L / 4 or L / 3), the power supply is cut off for braking in the same way, and the average braking deceleration a2 and the car position L1 are measured.

[0055] (3) Working condition 3: Please refer to Figure 6 , with the car loaded with 110% of the rated load (confirmed by an overload detection device or pre-weighing), traveling downward at the rated speed to the middle of the travel (the car and the counterweight are at the same horizontal position), the power supply is cut off for braking, and the average braking deceleration a3 and the car position L3=0 are measured.

[0056] (4) Working condition 4: With the car loaded with 110% of the rated load, traveling downward at the rated speed to a certain position L3 in the lower part of the travel (satisfying L<L3<L, usually L3= L / 4 or L / 3), the power supply is cut off for braking, and the average braking deceleration a4 and the car position L3 are measured.

[0057] (5) Dynamic length correction model for traction steel wire ropes - compensation chains In traditional dynamic models, it is usually assumed that the linear density of the steel wire ropes and the compensation chains is uniform, and their elastic deformation is ignored. However, for high-rise elevators with a lifting height exceeding 50m, the errors caused by these factors cannot be ignored.

[0058] Elongation correction of steel wire ropes: When the car is braking, the tensile force borne by the steel wire ropes increases instantaneously, resulting in elastic elongation of the steel wire ropes. According to Hooke's law, the relationship between the elastic elongation ΔL, the tensile force F of the steel wire rope, the original length L of the steel wire rope, the elastic modulus E and the total cross-sectional area A is as follows: ΔL = F r · L / (E·A), where Fr Let E be the tension of the wire rope, E be the modulus of elasticity, and A be the total cross-sectional area of ​​the wire rope. The elastic modulus E for a typical elevator wire rope is approximately 1.0 × 10⁻⁶. 5 1.2×10 5 A = n·πd 2 / 4, where n is the number of wire ropes and d is the diameter of a single wire rope.

[0059] Wire rope tension F r Estimation of deceleration during braking: F r ≈ (m+m1)(g+a).

[0060] Elastic elongation causes the actual braking distance of the car to be slightly larger than the theoretical value, thus affecting the average deceleration. Therefore, an elastic correction term is introduced: Δa e =β·(ΔL / L1)·(a1-a2); Where β is the elastic compensation coefficient, with a value range of 0.1 to 0.3, and is calibrated through a single no-load self-learning run.

[0061] Correction for Non-uniform Linear Density of Compensating Chain: The function of the compensating chain is to compensate for the weight change of the traction wire rope due to length variations during lifting. Ideally, the linear density of the compensating chain should equal the linear density of the wire rope and be uniform along its entire length. However, in actual manufacturing and use, the linear density of the compensating chain may deviate, and with prolonged use, chain pitch wear can lead to uneven linear density distribution. Therefore, a non-uniform linear density correction factor is introduced: λ(h) = 1 + α·(h / H) 2 ; In the formula, α is an empirical constant, ranging from 0.02 to 0.05, which is fitted by experiments; h is the actual height of the car from the bottom floor (0≤h≤H); H is the total lifting height; When the car is in the middle (h=H / 2), λ=1+α / 4, and the correction is relatively small; when the car is at the top (h=H) or bottom (h=0), the correction is the largest. This correction factor is multiplied into the weight difference term of the compensation chain.

[0062] (6) Temperature, humidity and wear integrated compensation model Braking torque is significantly affected by ambient temperature, humidity, and brake shoe wear. High temperatures reduce the coefficient of friction; for organic-based friction materials, the coefficient of friction decreases by approximately 2% for every 10°C increase in temperature. High humidity environments can cause rust or water film to adhere to the brake wheel surface, reducing friction. Brake shoe wear leads to changes in contact area and contact pressure.

[0063] To this end, a patch thermocouple and a humidity sensor are installed on the brake shoe to collect temperature T (unit: °C) and relative humidity Hr (unit: %RH) in real time.

[0064] Establish the formula for the braking torque decay model: F b (T,H) = F b0 · (1-k T ·(T-T0))·(1-k H ·(H r -H r0 )) ; In the formula, T0 is the temperature under standard operating conditions, and H... r0 For wet conditions under standard operating conditions, F b0 Under standard operating conditions (T0=20℃, H r0 The standard power rating is 50%RH, where T is the brake operating ambient temperature, and H is the RH value. r For relative humidity, k T The temperature attenuation coefficient, determined experimentally, typically has a value of 0.002 / ℃, meaning that for every 10℃ increase in temperature, the braking force decreases by 2%; k H This is the humidity attenuation coefficient, with a typical value of 0.001 / %RH, meaning that for every 10% increase in humidity, the braking force decreases by 1%.

[0065] Normalize a1, a2, a3, and a4 by dividing the measured values ​​by (1-k). T ·(T-T0))·(1-k H ·(H-H0)) is used to obtain the deceleration under equivalent standard operating conditions, so as to eliminate the influence of environmental differences on the test results.

[0066] (7) Obtaining and decoupling the system's moment of inertia The total moment of inertia J of an elevator braking system includes the moments of inertia of rotating components such as the traction sheave, brake sheave, motor rotor, guide sheave, and deflector sheave. The moment of inertia affects the angular deceleration during braking, and consequently, the linear deceleration of the car. Traditional methods often neglect the moment of inertia or incorporate it into the translational mass, leading to errors.

[0067] On-site measurement of rotational inertia: After the motor travels to the upper part of its stroke under no-load conditions, the brake is kept closed (i.e., the brake shoes are gripping the brake wheel). Then, power is applied briefly (approximately 0.5 seconds) to cause the motor to output a reverse torque. However, the motor rotor cannot rotate with the brake closed. At this time, the static holding torque M output by the motor is measured. hold According to torque balance, this torque is equal to the braking torque provided by the brake. Simultaneously, a rotary encoder is used to measure minute angular displacement changes in the motor shaft, and the equivalent value of the moment of inertia J is estimated using angular acceleration.

[0068] After obtaining the moment of inertia J, a decoupling factor of (1+J / (mR)) is introduced into the deceleration calculation formula. 2 )) -1 Where m is the mass of the car system (which can be estimated by the torque difference between unloaded and 110% load conditions), and R is the radius of the traction sheave. This factor reflects the weakening effect of rotational inertia on linear deceleration; the larger the rotational inertia, the lower the efficiency of converting the same braking torque into linear deceleration.

[0069] (8) Calculate the actual braking deceleration at the failure edge in the upward direction. Taking into account the above corrections, the formula for calculating the actual braking deceleration at the failure edge in the upward direction is derived as follows: a u2 = a1- (L2(a1-a2) / L1) · (1+J / (mR 2 )) -1 +β·(ΔL / L1)·(a1-a2) + f(T,H); in: The first term, a1, represents the measured deceleration at the midpoint. The second term (L2(a1-a2) / L1) · (1+J / (mR) 2 )) -1 It is a linear extrapolation term, assuming that the deceleration changes linearly with position and is corrected for by the moment of inertia; The third term, β·(ΔL / L1)·(a1-a2), is the elasticity compensation term for the wire rope. The fourth term f(T,H) r ) is the temperature and humidity compensation term, which corrects the deceleration to the equivalent value under standard conditions.

[0070] (9) Calculate the actual braking deceleration at the failure edge in the downward direction. The formula for calculating the downward direction is: a d2 = a3- (L4(a3-a4) / L3) · (1+J / (mR 2 )) -1 +β·(ΔL / L1)·(a1-a2) + g(T,H); The meanings of the terms in the formula are similar to those above, where L4 is the downlink failure edge position (i.e., the lower forced deceleration position), L3 is the downlink lower measurement position, and g(T,H) r ) is the temperature and humidity compensation function in the downward direction.

[0071] It should be noted that, in order to improve the robustness of detection and avoid misjudgments caused by the failure of a single sensor, multi-sensor fusion and redundancy verification are adopted: An accelerometer sensor, installed on the top of the car or inside the car, directly measures the linear acceleration of the car.

[0072] A rotary encoder, installed on the end of the traction sheave shaft, measures the angular velocity of the traction sheave and converts the angular acceleration into the linear acceleration of the car by multiplying the angular acceleration by the radius of the traction sheave.

[0073] A magnetic scale is installed on the surface of the wire rope to measure the amount of slippage of the wire rope relative to the traction sheave. The deceleration is obtained by the derivative of the slippage.

[0074] Three signals (linear acceleration, angular acceleration, and slip) are simultaneously input to a Kalman filter, with the three independent physical quantities mutually verifying each other. The Kalman filter is an optimal estimation filter that can fuse multi-source data and suppress noise, improving accuracy. The optimal estimate of deceleration is obtained through the Kalman filter recursive formula. Simultaneously, the residuals between the three measurements and the optimal estimate are calculated. If the residual of any sensor continuously exceeds a preset threshold (e.g., 10%), the sensor is considered faulty, its weight is reset to zero, it is automatically isolated, and an alarm message is output.

[0075] It should be noted that an anomaly detection and retry mechanism is also employed: after each braking test, the calculated deceleration is compared with the average deceleration under the same working condition in the historical database. If the deviation exceeds three times the standard deviation, an automatic retry is initiated (repeating the braking test under the same working condition). If the deviation persists after the retry, the nature of the deviation is assessed: if the deviation is positive (i.e., greater deceleration), it may be due to favorable factors such as good guide rail lubrication, and no alarm is triggered; if the deviation is negative (smaller deceleration), it may be due to a sudden decrease in brake performance or a measurement malfunction, and the system outputs an abnormal warning, recommending manual verification.

[0076] 4. Determine if the brake is on the verge of failure and issue tiered warnings.

[0077] (1) Basic judgment If (a u2 >a u1 And (a) d2 >a d1 If the brake is deemed safe and capable of meeting braking requirements under conditions of impending failure, then the brake is deemed safe. Otherwise, if the brake is determined to be on the verge of failure or has already failed, it should be taken out of service immediately for inspection and repair.

[0078] (2) Calculation of safety margin coefficient Simply judging as pass / fail is too crude and cannot reflect the degradation trend of braking performance. Therefore, a safety margin factor is introduced: η u = a u2 / a u1 , η d= a d2 / a d1 ; In the formula, η u η is the safety margin factor in the upward direction. d This represents the safety margin factor in the downward direction. A larger η value indicates that the actual performance of the brake is more adequate relative to the minimum safety requirements.

[0079] (3) Tiered early warning Based on the safety margin factor, a graded early warning system for failure edge is implemented: If η ≥ 1.2, it is considered Level 1 safety, indicating that the braking performance is sufficient and far exceeds the safety threshold; it is recommended to conduct regular periodic testing.

[0080] If 1.0 ≤ η < 1.2, it is classified as Level 2 attention, indicating that the braking performance is on the verge of failure and close to the failure threshold; it is recommended to arrange maintenance and inspection within 1 month.

[0081] If η < 1.0, it is a level three hazard, indicating insufficient braking performance and that the elevator is in a state of failure; the elevator should be stopped immediately and the brake replaced or repaired.

[0082] 5. Predict remaining lifetime based on grey prediction model.

[0083] To scientifically plan maintenance schedules, the grey prediction model GM(1,1) is used to predict the future trend of the safety margin coefficient. The grey prediction model is suitable for time series forecasting with limited data and an exponential growth trend, and is well-suited for the degradation process of elevator brakes (typically exhibiting exponential decay). The specific steps are as follows: (1) Collect historical detection data: Record the η values ​​obtained from at least 3 (e.g. 6) past detections, and arrange them in chronological order as sequence η. (0) =[η (0) (1),η (0) (2),...,η (0) [n]; where η (0) is the original data sequence, and n is the number of detections.

[0084] (2) Accumulate and generate sequence: η(1)(k)=∑i=1k η(0)(i), generate a sequence with an exponential growth trend; where η(1) is the accumulated and generated sequence; k is the time index (k=1,2,...,n), k=1 represents the earliest historical data point, and k=n represents the most recent historical data point (current time point).

[0085] (3) Establish the grey differential equation: η (0) (k)+az (1) (k)=b; where z (1) (k) is the background value sequence, z (1)(k)=0.5η (1) (k)+0.5η (1) (k 1) is the background value; a is the development coefficient; b is the gray effect quantity.

[0086] (4) Solve for a and b using the least squares method: [a, b] T =(B T B) 1 B T Y; where B is the data matrix, i.e., the independent variable matrix of the least squares method; Y is the data vector, i.e., the dependent variable vector of the least squares method; (B T B) 1 B T Y is the least squares estimation formula.

[0087] (5) Obtain the time response formula: ; In the formula, This is the cumulative predicted value at the (k+1)th point in the cumulative domain; is the initial historical value; e is the base of the natural logarithm, approximately 2.71828.

[0088] (6) Cumulative subtraction and restoration: ; In the formula, This is the final predicted value for the (k+1)th point in the original domain; This is the cumulative predicted value at the (k+1)th point in the cumulative domain; This is the cumulative predicted value of the k-th point in the cumulative domain.

[0089] (7) Predict the value of η at future moments, find the time point corresponding to when η drops to 1.0 (Level 3 danger threshold), and calculate the number of days from the current date to that time point, which is the remaining safe operating days. At the same time, output a suggested date for the next inspection, usually set to half of the remaining days.

[0090] Please see Figure 7 For example, take 6 data points from January 2025 to November 2025 as the training set: η (0) =[1.35,1.30,1.28,1.22,1.18,1.12]; Accumulated generation: η (1) =[1.35,2.65,3.93,5.15,6.33].

[0091] The remaining lifetime is predicted using the steps of the grey prediction model described above. Solve for η.(0) The value of k corresponding to (k)=1.0η is calculated iteratively. When k=9.5 (i.e., mid-June 2026), η≈0.95. The predicted remaining safe operating days are approximately 45 days. Therefore, a warning will be issued on May 30, 2026: The current elevator braking performance is at level three danger, with an estimated remaining safe operating days of 45 days. It is recommended that brake maintenance be carried out before June 15, 2026.

[0092] The following section uses the brake failure edge detection of a high-rise high-speed elevator as an example to provide a detailed description of the elevator brake failure edge detection method and system provided in this embodiment.

[0093] I. Elevator Technical Parameters Rated load capacity: 1050kg; Rated speed: 1.75m / s; Lifting height: 60m; Traction ratio: 2:1; Balance coefficient: 0.48; Wire ropes: 5 strands, diameter 10mm, elastic modulus E=1.1×10 5 MPa; Compensation chain: all-plastic composite, unit mass 2.5kg / m.

[0094] The car's mass P = 600 kg, the balance coefficient K = 0.48, and the rated load Q = 1050 kg. The total mass of the wire rope is m. s =250kg, total mass of the compensation chain m b =200kg, traction ratio i=2, traction wheel radius R=0.4m.

[0095] II. Testing Steps 1. Determine the failure edge conditions By consulting the elevator technical parameter table, we find that the maximum permissible operating speed of the elevator car is V1 = 1.2 × 1.75 = 2.1 m / s.

[0096] 2. Calculate the theoretical minimum braking deceleration. Consulting the elevator's technical parameters table, we find that the maximum impact speed of the buffer is V2 = 2.0 m / s.

[0097] On-site measurement: The distance between the end face of the counterweight buffer and the impact plate is H1 = 1.30m; The distance between the end face of the car buffer and the impact plate is H2 = 1.20m.

[0098] calculate: a u1 = (V1 2 -V2 2 ) / (2H1) =(2.1 2 -2.0 2 ) / (2×1.30) =0.158m / s 2 ; ad1 = (V1 2 -V2 2 ) / (2H2) =(2.1 2 -2.0 2 ) / (2×1.20) =0.171m / s 2 .

[0099] 3. Measure the actual deceleration The test was conducted under four operating conditions, with each condition repeated three times and the average value taken. The measurement data is shown in Table 1.

[0100] Table 1 Measurement data for four operating conditions Simultaneously record: Upward failure edge position L2 = 24.72m (distance from the bottom floor level); Downward failure edge position L4 24.68m; ambient temperature T=22℃, relative humidity Hr=5%RH.

[0101] 4. Multiphysics compensation Temperature decay coefficient k T =0.002 / ℃ and humidity attenuation coefficient k H =0.001 / %RH, obtained through bench testing of the friction material of the same type of brake under controlled temperature and humidity conditions. The elastic compensation coefficient β ranges from 0.1 to 0.3, and the specific value is automatically calibrated through the calibration procedure during initial installation; the actual calibration result is 0.2. The standard gravitational acceleration g is taken as 9.8 m / s². 2 .

[0102] Calculate the counterweight mass W = P + KQ = 600 + 0.48 × 1050 = 1104 kg; Calculate the total mass m of the system: m = P + W + i 2 m s +m b = 600 + 1104 + 2 2 ×250+200=2904kg.

[0103] (1) Wire rope elasticity correction The total cross-sectional area of ​​the wire rope, A = 5π(0.012) / 4 = 3.93 × 10⁻⁶ 4 m 2 ; Estimate the tension F of the wire rope r ≈m(g+a2)≈(2000)(9.8+3.28)=37984N; Elastic elongation ΔL = (37984 × 60) / (1.1 × 10) 11 ×3.93×10 4 ) = 0.0528m; The elastic compensation term β·(ΔL / L1)·(a1-a2)=0.2×(0.0528 / 7.5)×(3.52-3.28)=0.00034 (the impact is minor and can be ignored).

[0104] (2) Temperature and humidity compensation Temperature and humidity compensation in the upward direction f(T,H) r ) = a1·(1-k T ·(T-T0))·(1-k H ·(H r -H r0 )) =3.52×(1-(1-0.002×(22-20))×(1-0.001×(55-50))=3.52×0.0091≈0.032m / s 2 .

[0105] Downward temperature and humidity compensation g(T,H) r ) = a4·(1-k T ·(T-T0))·(1-k H ·(H r -H r0 )) =2.48×(1-(1-0.002×(22 20))×(1-0.001×(55-50))=2.48×0.0091≈0.0225m / s 2 .

[0106] Considering sensor measurement error and engineering safety margin, we take g(T,H) r The compensation value is 0.028 m / s 2 .

[0107] (3) Decoupling of rotational inertia Measured static holding torque M hold =450 N·m, estimated moment of inertia J = 12.5 kg·m 2 Decoupling factor: (1+J / (mR)) 2 )) -1 =(1+12.5 / 2904×0.4 2 ) -1 =0.974.

[0108] Calculate the actual upward deceleration: a u2 = a1-(L2(a1-a2) / L1) · (1+J / (mR 2)) -1 + f(T,H r ) =3.52-24.72×(3.52-3.28) / 7.5×0.974+0.032=2.782m / s 2 .

[0109] Calculate the actual downward deceleration: a d2 = a3- (L4(a3-a4) / L3) · (1+J / (mR 2 )) -1 + g(T,H r ) =2.70-(-24.68×(2.70-2.48) / (-7.4)×0.974+0.028=2.013m / s 2 .

[0110] 5. Safety assessment and classification After comparison, because (a u2 >a u1 And (a) d2 >a d1 Therefore, the elevator brake is deemed safe. Calculate the safety margin coefficients for the uplink and downlink directions: η u = a u2 / a u1 = 2.782 / 0.158 = 17.6, η d = a d2 / a d1 = 2.013 / 0.171 = 11.8; The safety margin coefficients for both the upward and downward directions are greater than 1.2, indicating Level 1 safety.

[0111] Then, the grey prediction model outputs that the remaining safe lifespan is greater than 5 years.

[0112] The elevator brake failure edge detection method and system provided in this invention have the following beneficial effects: 1. High Safety: The test load is controlled within 110% of the rated load, lower than the national standard's test limit of 125%, avoiding damage to the elevator structure from overload testing. No weights need to be moved, completely eliminating the risk of weights slipping into the elevator car and the risk of injury from falling objects. The testing process is automatically controlled by an edge computing terminal 200, eliminating the need for personnel to enter the high-risk areas of the shaft or machine room.

[0113] 2. High Precision: Employing a dual-load braking method, it eliminates parameters such as braking force and system mass, which are difficult to measure directly, through position difference, essentially a self-calibration method. By introducing multi-physics compensation models such as wire rope elasticity correction, compensation chain non-uniformity correction, temperature and humidity compensation, and rotational inertia decoupling, the detection error is reduced from ±8% in existing technologies to within ±2%. Multi-sensor fusion and Kalman filtering significantly improve the reliability of the measured values.

[0114] 3. Fully Automated and Intelligent: The system automatically controls the elevator to perform the testing process without manual intervention. Its self-learning calibration function allows it to adapt to different elevator models and lifting heights, eliminating the need for on-site input of complex structural parameters. Test results are automatically uploaded to the cloud service platform, generating reports and sending alerts automatically.

[0115] 4. Quantitative Assessment and Lifespan Prediction: Not only does it output pass / fail status, but it also outputs safety margin coefficients to quantify the degree of braking performance degradation. It introduces graded early warning standards (such as Level 1 Safety, Level 2 Caution, and Level 3 Danger) to provide intuitive basis for maintenance decisions. A grey prediction model is used to predict the remaining safe operating days, realizing the shift from reactive maintenance to predictive maintenance.

[0116] 5. High robustness: The multi-sensor redundancy design ensures the system can still operate normally or automatically alarm when a single sensor fails. The anomaly detection and retry mechanism effectively avoids misjudgments caused by random errors.

[0117] 6. High Detection Efficiency: Through automatic detection and data analysis, remote management of large-scale elevator groups can be achieved, significantly improving detection efficiency, reducing labor costs, and enhancing safety. It is especially suitable for continuous monitoring of the brakes of old elevators, high-frequency elevators, and elevators in public gathering places.

[0118] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

Claims

1. A method for detecting the failure edge of an elevator brake, characterized in that, include: When the elevator car is unloaded, it travels upwards at the maximum permissible speed and is braked at the forced deceleration position at the top of the shaft. The elevator car is loaded with a load of 110% of its rated load capacity and descends at the maximum permissible operating speed. It is then braked at the forced deceleration position at the lower end of the shaft to determine the conditions for the failure edge of the elevator brake. Based on the maximum permissible operating speed of the elevator car V1 and the maximum impact speed of the buffer V 2， And the minimum braking deceleration a in the upward direction is calculated based on the minimum braking deceleration calculation formula, using the distance H1 between the end face of the counterweight buffer and the impact plate or the distance H2 between the end face of the car buffer and the impact plate. u1 and the minimum braking deceleration a in the downward direction d1 Determine the theoretical value of the minimum braking deceleration at the edge of elevator brake failure; The actual braking deceleration at the failure edge was measured using the same-load double braking method: the average braking deceleration a1 from unloaded upward travel to the middle of the travel, the average braking deceleration a2 from unloaded upward travel to the upper part of the travel, the average braking deceleration a3 from 110% rated load downward travel to the middle of the travel, and the average braking deceleration a4 from 110% rated load downward travel to the lower part of the travel, and the corresponding car positions L1, L2, L3 and L4 were recorded. The actual braking deceleration a at the failure edge position in the upward direction is calculated based on the braking deceleration difference formula. u2 And the actual braking deceleration a in the downward direction at the failure edge position. d2 ; If (a u2 >a u1 And (a) d2 >a d1 If the elevator brake is on the verge of failure or has already failed, then the elevator brake is considered safe; otherwise, the elevator brake is considered to be on the verge of failure or has already failed. Calculate and output the safety margin coefficients for the uplink and downlink directions.

2. The elevator brake failure edge detection method according to claim 1, characterized in that, The formula for calculating the minimum braking deceleration is: in u1 = (V1 2 -V2 2 ) / (2H1) , a d1 = (V1 2 -V2 2 ) / (2H2) ; In the formula, a u1 For the minimum braking deceleration in the upward direction, a d1 V1 is the minimum braking deceleration in the downward direction, V2 is the maximum permissible running speed of the car, V2 is the maximum impact speed of the buffer, H1 is the distance between the end face of the counterweight buffer and the impact plate, and H2 is the distance between the end face of the car buffer and the impact plate. The braking deceleration difference formula is as follows: a u2 = a1 - (L2(a1-a2) / L1) · (1+J / (mR 2 )) -1 + f(T,H r ) , a d2 = a3 - (L4(a3-a4) / L3) · (1+J / (mR 2 )) -1 + g(T,H r ); In the formula, a u2 a is the actual braking deceleration in the upward direction at the failure edge position. d2 Let J be the actual braking deceleration in the downward direction at the failure edge position, m be the system moment of inertia, R be the car system mass, L be the traction sheave radius, L1, L2, L3, and L4 be the car positions, and f(T,H) be the actual braking deceleration in the downward direction at the failure edge position. r ) is the temperature and humidity compensation function in the upward direction, g(T,H) r ) represents the temperature and humidity compensation function in the downward direction, where T is the ambient temperature of the brake operating environment, and H is the temperature and humidity compensation function in the downward direction. r Relative humidity; The formula for calculating the safety margin coefficient is as follows: or u = a u2 / a u1 , or d = a d2 / a d1 ; In the formula, η u η is the safety margin factor in the upward direction. d This represents the safety margin coefficient in the downward direction.

3. The elevator brake failure edge detection method according to claim 2, characterized in that, The method for obtaining the system's moment of inertia includes: After the motor travels to the top of its travel without load, keep the brake closed and briefly energize to reverse the motor. Measure the static holding torque of the brake, and calculate the equivalent value of the system's moment of inertia by using the relationship between torque and angular acceleration; Substituting the system's rotational inertia into the braking deceleration differential formula achieves complete decoupling between rotation and translation.

4. The elevator brake failure edge detection method according to claim 1, characterized in that, In the step of measuring the actual braking deceleration at the failure edge using the co-load secondary braking method, multi-sensor fusion and redundancy verification are employed. The linear acceleration is measured using an accelerometer installed inside the car, the angular acceleration is measured using a rotary encoder installed on the side of the traction sheave, and the slippage is measured using a magnetic scale installed on the surface of the wire rope. The measured values ​​of three independent physical quantities are fused using Kalman filtering to obtain the optimal estimated deceleration value; If the deviation of the three values ​​exceeds the preset threshold, it is determined to be a measurement abnormality and an alarm is triggered.

5. The elevator brake failure edge detection method according to claim 2, characterized in that, The step of measuring the actual braking deceleration at the failure edge using the same-load secondary braking method also includes: Temperature and humidity sensors are installed on the brake shoes to collect the ambient temperature and relative humidity of the brake's working environment in real time. Establish the formula for the braking torque decay model: F b (T,H r ) = F b0 · (1-k T ·(T-T0))·(1-k H ·(H r -H r0 )) ; In the formula, F b0 The standard power is the brake's operating temperature under standard conditions, where T is the brake's ambient temperature and H is the rated power. r For relative humidity, k T The temperature decay coefficient is determined experimentally; k H The humidity attenuation coefficient is T0; T0 is the temperature under standard operating conditions, and H is the humidity attenuation coefficient. r0 Humidity under standard operating conditions; Normalize a1, a2, a3, and a4 by dividing the measured values ​​by (1-k). T ·(T-T0))·(1-k H ·(H r -H r0 This allows us to obtain the deceleration under equivalent standard operating conditions, thus eliminating the influence of environmental differences on the test results.

6. The elevator brake failure edge detection method according to claim 2, characterized in that, The step of measuring the actual braking deceleration at the failure edge using the same-load secondary braking method also includes: Establish a dynamic length correction model for the traction wire rope and calculate the elastic elongation of the wire rope: ΔL = F r · L / (E·A), In the formula, F r Let E be the tension of the wire rope, E be the modulus of elasticity, and A be the total cross-sectional area of ​​the wire rope. Introduce a non-uniform linear density correction factor λ(h): λ(h) = 1 + α·(h / H) 2 , In the formula, α is an empirical constant, ranging from 0.02 to 0.05, obtained through experimental fitting; h is the actual height of the car from the ground floor; and H is the total lifting height. Add the correction term β·(ΔL / L1)·(a1-a2) to the calculation formula of the braking deceleration difference formula; In the formula, β is the elastic compensation coefficient, with a value range of 0.1 to 0.3, which is calibrated through a single no-load self-learning run.

7. The elevator brake failure edge detection method according to claim 1, characterized in that, After the steps of calculating and outputting the uplink safety margin coefficient and the downlink safety margin coefficient, the method further includes: Based on the safety margin coefficient η, a graded early warning system for failure edge is implemented: If η ≥ 1.2, then it is level one safety; If 1.0 ≤ η < 1.2, then it is a level two attention; If η < 1.0, then it is a level three hazard; Collect at least 3 historical test data, use the grey prediction model GM(1,1) to predict the changing trend of the safety margin coefficient in the next 6 months, predict the safe life, and output the remaining safe operating days or suggest the next test date.

8. The elevator brake failure edge detection method according to claim 1, characterized in that, The method also includes self-learning calibration: After the elevator is first installed or inspected, it automatically performs a full-condition calibration procedure to measure the standard deceleration under each condition, and calculate and store the system parameters. Subsequent testing will automatically call upon the stored system parameters for correction, eliminating the need to repeatedly measure system parameters.

9. An elevator brake failure edge detection system, used to implement the elevator brake failure edge detection method as described in any one of claims 1 to 8, characterized in that, include: The brake detection module includes an acceleration detection unit, a position detection unit, a temperature and humidity detection unit, a rotary encoder, and a magnetic scale module. The acceleration detection unit is installed inside the car or on the traction steel cable to measure the average braking deceleration during braking. The position detection unit is equipped with a laser rangefinder, installed inside the hoistway, to measure the real-time position of the car within the hoistway. The temperature and humidity detection unit includes a patch thermocouple and a humidity sensor, installed at the brake shoe to collect brake operating environment parameters. The rotary encoder is installed on the traction sheave side to measure angular acceleration. The magnetic scale is mounted on the surface of the wire rope and is used to measure the amount of slippage. An edge computing terminal, installed in the elevator machine room or control cabinet, is connected to the brake detection module and is used to execute the elevator brake failure edge detection method according to any one of claims 1 to 8. The cloud service platform, connected to the edge computing terminal, is used to store historical detection data, execute gray prediction models, and push early warning information.

10. The elevator brake failure edge detection system according to claim 9, characterized in that, The edge computing terminal includes: The data acquisition module is used to receive measurement data from the brake detection module; The self-learning calibration module is used to automatically execute the full-condition calibration procedure after initial installation or maintenance and to store system parameters. The differential calculation module is used to calculate the actual braking deceleration at the failure edge based on the same-load secondary braking method; the temperature and humidity compensation module is used to correct the deceleration calculation results based on the data from the temperature and humidity detection unit. The rotational inertia decoupling module is used to eliminate the influence of the system's rotational inertia on the calculation results; The graded early warning module is used to calculate the safety margin coefficient and classify the safety levels; The lifespan prediction module is used to output the remaining safe operating days based on a grey prediction model.

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