Air pressure data acquisition method, elevator floor estimation and anomaly detection method and system
By acquiring air pressure data and fusing acceleration data, and leveraging the advantages of air pressure sensors and acceleration sensors, the problems of high difficulty and low accuracy in elevator operation status detection and integration into the control system have been solved, achieving efficient and low-cost elevator operation status monitoring.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHENGDU PENGYE SOFTWARE
- Filing Date
- 2022-01-17
- Publication Date
- 2026-06-16
AI Technical Summary
Existing technologies require integration with the elevator control system for elevator operation status detection, which leads to high maintenance difficulty and cost. Furthermore, the accelerometer is susceptible to vibration, resulting in cumulative errors, low accuracy, and long processing time.
By using air pressure data acquisition methods, air pressure sensors are used to collect data and process it according to the timeliness of air pressure. Combined with acceleration data, floor estimation and anomaly detection are performed to establish a height model. Kalman filtering and other filtering algorithms are used for correction to avoid direct connection to the elevator control system.
It improves detection accuracy, reduces maintenance difficulty and cost, avoids damage to the elevator system, and achieves high-precision monitoring of operating status.
Smart Images
Figure CN116481492B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of operational status detection technology, and more specifically, to a method for acquiring air pressure data, an elevator floor estimation method, and an anomaly detection method and system. Background Technology
[0002] Regarding technical solutions for detecting and monitoring operational status (such as elevator operational status), current existing technologies have at least the following technical problems:
[0003] ① It requires connection to the elevator control system, which is difficult and costly in terms of design, implementation and operation management. It requires professional personnel for maintenance, and the maintenance process may also damage the elevator system.
[0004] ② Elevator motion detection and abnormal position stopping judgment mainly rely on accelerometers. However, due to vibrations during elevator movement, especially in older elevators, the sensitivity of the accelerometer will cause these influencing factors to be output, significantly affecting the accelerometer's integral result. Multiple motion errors, when superimposed, will produce a large offset, resulting in cumulative error, low accuracy, and affecting precision. Furthermore, using accelerometers for detection also has the problem of being time-consuming. Summary of the Invention
[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for acquiring air pressure data, an elevator floor estimation method and an anomaly detection method and system, thereby improving the detection accuracy. It can more accurately correct the height calculated by the accelerometer, effectively utilize the motion timeliness of the accelerometer and the short-term stability of the barometer, and combine their advantages to make the system more reliable. Furthermore, it does not require connection to the elevator control system, which significantly reduces the difficulty and cost in design, implementation and operation management, and avoids safety hazards that may be caused by damage to the elevator system during elevator maintenance.
[0006] The objective of this invention is achieved through the following solution:
[0007] A method for acquiring air pressure data involves collecting air pressure data from an air pressure sensor, but instead of using the data directly, performing the following steps: processing the collected air pressure data according to the air pressure validity period to obtain valid operating air pressure data; and using the valid operating air pressure data as air pressure data that can be directly used.
[0008] Furthermore, the air pressure sensing device collects air pressure data including air pressure data of the elevator shaft.
[0009] An elevator floor estimation and anomaly detection method based on the air pressure data acquisition method described above utilizes the effective operating air pressure data and acceleration data to perform floor estimation and detect anomalies in operating status.
[0010] Further, it includes sub-steps:
[0011] Record the time required for the air pressure to stabilize to the true value after the elevator moves as T_stable, and record the air pressure aging period as T_Vaild;
[0012] For the starting stage of the elevator, assume that the elevator stopping time before operation is t1_stop. If t1_stop is greater than T_stable, it is considered that the starting air pressure value of this operation is valid, and at the same time record the estimated height value of the elevator air pressure h1_press;
[0013] For the stopping stage of the elevator, assume that the stopping duration after the elevator stops is t2_stop. If t2_stop is greater than T_stable, record the height value at the moment of T_stable when the elevator stops as h2_press; at the same time record the start time and stop time of the elevator as t_start and t_end respectively; if both the start and end heights are valid, and the elevator running time t_end - t_start < T_vaild, it is considered that the start and end match, and the air pressure data traveled between the start and end is valid operating air pressure data and can be directly utilized.
[0014] Further, estimate the speed and height integration according to the acceleration data, perform filtering after obtaining the effective air pressure data, and perform filtering and correction on the floor height.
[0015] Further, after performing multiple filtering corrections on the floor height, it includes the steps: dynamically establish and update the floor height model according to the height of the historical filtering correction.
[0016] Further, according to the historical statistical information of the elevator running speed and acceleration and the floor height model, and compare with the current data to calculate the acceleration anomaly, speed anomaly and uneven floor anomaly information.
[0017] Further, the filtering includes Kalman filtering, extended Kalman filtering and complementary filtering.
[0018] Further, it includes the step of setting a threshold, and the normal value can be learned through historical data statistics. When the result of comparing the normal value with the current data exceeds the set threshold, the current anomaly information can be obtained.
[0019] An elevator floor estimation and its anomaly detection system executes the method steps described in any one of the above.
[0020] The beneficial effects of the present invention are:
[0021] The embodiments of the present invention take into account the timeliness and motion effects of barometers, and propose a method for acquiring barometer data based on this, which can be applied to any scenario with barometer instability to obtain effective operating barometer pressure, thereby helping to improve detection accuracy.
[0022] This invention integrates barometer and accelerometer results. Based on operational data, the accelerometer deviation can be determined. Using this monitoring data from the barometer, the calculated altitude can be more accurately corrected. This approach effectively combines the timeliness of accelerometer movement with the short-term stability of barometer, resulting in a more reliable system.
[0023] This invention automatically constructs a floor model based on historical operating data, performs unordered calibration, and can quickly establish a floor height model based on multiple height measurements from the barometer, thereby improving detection accuracy.
[0024] When applied to elevator maintenance, this invention can be implemented simply by placing a barometer on the elevator; no other operations are required, making it easy to install.
[0025] Based on historical data, this invention can calculate abnormal information such as acceleration, speed, and floor leveling, thereby enabling the design of a detection and monitoring scheme for elevator operation status. It does not require connection to the elevator control system, significantly reducing the difficulty and cost in design, implementation, and operation management, and avoiding safety hazards that may be caused to the elevator system during maintenance. Attached Figure Description
[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0027] Figure 1 This is a diagram of the first elevator's operation process; sub-graph (a) shows the acceleration curve, and sub-graph (b) shows the height calculated based on air pressure, with the horizontal axis in minutes.
[0028] Figure 2 The diagram shows the operation process of the second elevator; sub-graph (a) is the acceleration curve, and sub-graph (b) is the height calculated based on air pressure. The horizontal axis is in minutes. Detailed Implementation
[0029] All features disclosed in all embodiments of this specification, or steps in all methods or processes implied in the disclosure, may be combined and / or extended or replaced in any way, except for mutually exclusive features and / or steps.
[0030] The following is based on the appendix Figures 1-2 The present invention will provide a further detailed description of the technical problem solved by the present invention, the technical concept, the working principle, the working process, and the beneficial effects.
[0031] In addressing the technical problems mentioned above, this invention utilizes a barometer combined with an accelerometer to detect the elevator's operating status. Compared to solutions relying solely on accelerometers, this approach mitigates the issues of long processing times and low accuracy to some extent. However, it also reveals the following technical problems:
[0032] ③In an ideal situation, air pressure is related to velocity, which can be qualitatively analyzed based on Bernoulli's theorem:
[0033]
[0034] In the formula, g is the acceleration due to gravity; z is the vertical height; p is the atmospheric pressure; ρ is the atmospheric density; and C is a constant.
[0035] Air density is essentially constant and can be considered a constant. In reality, air pressure is related to speed and temperature, especially in enclosed spaces like elevator shafts. Furthermore, the cross-sectional area of the elevator car typically occupies at least 50% of the entire shaft (for example, a Hitachi elevator weighing 1350 kg has a car size of 2000mm*1500mm and a shaft size of 2550mm*2200mm, meaning the car area occupies 53.4% of the shaft area). When the elevator moves, it accelerates the surrounding air and creates "positive pressure zones" and "negative pressure zones" around the elevator, generating vortices that further accelerate the air around the car. At this time, barometers are not stable and can only serve as qualitative references. Experiments have shown that it takes at least 30 seconds for the air pressure to stabilize after the elevator has started operating. Figure 1 As shown, the horizontal axis represents time, the vertical axis of subplot (a) is acceleration, and the vertical axis of subplot (b) is height. In subplot (a), the red horizontal line represents zero acceleration, and the peaks and troughs represent the elevator's acceleration and deceleration stages, respectively. From Figure 1 As can be seen, after the elevator stops moving up or down, the air pressure needs a recovery period. Furthermore, the barometer has a certain lag; the air pressure recovery time is longer than the elevator's stopping time, which is typically around 10 seconds. Therefore, during peak hours, due to the continuous operation of the elevator, a stable air pressure cannot be obtained. In addition, due to changes in temperature and pressure, the height calculated from the pressure at the same point will also vary. Figure 2It is the change curve when the elevator remains stationary on the first floor for 2 consecutive hours. It can be found that the height changes rapidly and is close to 10 meters. Therefore, the following conclusions can be drawn: 1. Due to the influence of movement, the barometer must stabilize for a period of time after movement before the pressure is effective. 2. The barometer measurement has a certain timeliness, that is, the measurement within a certain period of time is effective (through experiments, it is found that 5 minutes can be a suitable time, that is, two readings within 5 minutes are required to calculate the true relative height difference). Considering the above two factors, it can be seen that during the peak period of the elevator, based only on the barometer reading method, the accuracy of the discrimination system will be relatively low.
[0036] It should be noted that not only in the elevator passage scenario, but also in other scenarios involving the detection of the operating state, as long as there is air pressure instability in the scenario, the solution that only uses a barometric sensor device to obtain air pressure values, such as a barometer directly obtaining air pressure data to judge the operating state, has similar problems.
[0037] To solve the newly discovered technical problems above, the design idea of the present invention is as follows: Consider the timeliness of the barometer and the influence of movement. In specific implementation, record the time required for the air pressure to stabilize as the true value after movement as T_stable, and record the air pressure validity period (how long the air pressure remains stable under the stationary state) as T_Vaild.
[0038] For the start of the elevator operation, assume that the elevator stop time before operation is t1_stop. If t1_stop is greater than T_stable, it is considered that the air pressure value at the start of this operation is effective, and at the same time record the elevator air pressure estimated height value h1_press.
[0039] Similarly, for the elevator docking stage, assume that the docking duration after the elevator docks is t2_stop. If t2_stop is greater than T_stable, record the height value at the moment of T_stable when the elevator docks as h2_press. At the same time, record the times when the elevator starts and docks as t_start and t_end respectively. If both the start and end heights are effective, and the elevator operation time t_end - t_start < T_vaild, it is considered that the start and end match, and the air pressure data traveled between the start and end is valid operating air pressure data and can be used to calibrate the system.
[0040] Building upon the solution to technical problem ③ mentioned above, an unexpected technical effect was achieved in addressing technical problem ② raised in the background. In specific implementation, based on the above scheme, the heights statistically recorded by the accelerometer and estimated by the barometer are recorded. Based on the operational data, the deviation of the accelerometer can be obtained. Using the supervisory data from the barometer, the height calculated by the accelerometer can be more accurately corrected. Simultaneously, a floor height model can be quickly established based on multiple height measurements from the barometer, improving detection accuracy. This method effectively combines the timeliness of the accelerometer's motion with the short-term stability of the barometer, making the system more reliable.
[0041] In other embodiments of the present invention, based on the above scheme, abnormal information such as acceleration, speed and leveling can be calculated from historical data, thereby enabling the design of a detection and monitoring scheme for the elevator's operating status. This eliminates the need to connect to the elevator control system, significantly reducing the difficulty and cost in design, implementation and operation management, and avoiding safety hazards that may be caused to the elevator system during maintenance.
[0042] Example 1: A method for acquiring air pressure data, which involves collecting air pressure data from an air pressure sensor but not using it directly. Instead, the method performs the following steps: processing the collected air pressure data according to the air pressure validity period to obtain valid operating air pressure data; and using the valid operating air pressure data as air pressure data that can be directly used.
[0043] Example 2: Based on Example 1, the air pressure sensing device collects air pressure data including air pressure data of the elevator passage.
[0044] Example 3: Based on Example 2, an elevator floor estimation and anomaly detection method based on the air pressure data acquisition method described above is provided, which uses the effective operating air pressure data to perform floor estimation and operation status anomaly detection.
[0045] Embodiment 4: On the basis of Embodiment 3, it includes sub-steps: Denote the duration required for the air pressure to stabilize to the true value after the elevator moves as T_stable, and denote the air pressure aging period as T_Vaild (how long the air pressure remains stable under the stationary state); for the starting stage of the elevator operation, assume the elevator stop time before operation is t1_stop. If t1_stop is greater than T_stable, it is considered that the starting air pressure value of this operation is valid, and at the same time record the estimated height value h1_press of the elevator air pressure; for the elevator stop stage, assume the stop duration after the elevator stops is t2_stop. If t2_stop is greater than T_stable, record the height value at the moment of T_stable when the elevator stops as h2_press; at the same time record the times when the elevator starts and stops as t_start and t_end respectively; if both the starting and ending heights are valid, and the elevator operation time t_end - t_start < T_vaild, it is considered that the air pressure data during the travel between the start and the end is valid operating air pressure data and can be directly utilized. For example, the number of operations included between the start and the end is greater than or equal to 1 because the elevator may have continuous operations. For instance, it stops at the 1st floor for a long time, then goes from the 1st floor to the 5th floor, stops for only about 10 seconds, and then goes from the 5th floor to the 10th floor and stops at the 10th floor for a long time. The air pressure data of a single operation process is unavailable because the stop time is too short, but when looking at the two operations combined, the air pressure from the 1st floor to the 10th floor is valid.
[0046] Embodiment 5: On the basis of Embodiment 4, estimate the speed and height by integrating the acceleration data, perform filtering after obtaining the valid air pressure data, and perform filtering correction on the floor height.
[0047] Embodiment 6: On the basis of Embodiment 5, after performing multiple filtering corrections on the floor height, it includes the step: Dynamically establish and update the height model of the floor according to the height of the historical filtering correction.
[0048] Embodiment 7: On the basis of Embodiment 5, according to the historical statistical information of the elevator running speed and acceleration and the floor height model, and compare with the current data to calculate the acceleration anomaly, speed anomaly and uneven floor anomaly information. The acceleration anomaly means a large difference from the normal value, the speed anomaly means a large difference from the normal speed, and the uneven floor information means a large distance between the elevator stop height and the corresponding floor surface height.
[0049] Embodiment 8: On the basis of Embodiment 5, the filtering can be other filtering algorithms such as Kalman filtering, extended Kalman filtering and complementary filtering.
[0050] Example 9: Based on Example 7, information on acceleration anomalies, velocity anomalies, and unevenness layer anomalies can be obtained by setting thresholds. Normal values can be learned through historical data statistics (e.g., through data-driven algorithms such as clustering or Gaussian estimation) and compared with the current values to obtain the current anomaly information.
[0051] Example 10: Based on any of Examples 1 to 9, an elevator floor estimation and anomaly detection system performs the steps of the method described in any of the above examples.
[0052] If the functions of this invention are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium, and all or part of the steps of the methods described in the various embodiments of this invention are executed in a computer device (which may be a personal computer, server, or network device, etc.) and the corresponding software. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, or optical discs. Test data or actual data resides in read-only memory (RAM), random access memory (RAM), etc., during program implementation.
Claims
1. A method for acquiring air pressure data, characterized in that, After collecting the air pressure data by the air pressure sensing device, instead of directly using it, the following steps are performed: Process the collected air pressure data according to the air pressure aging period to obtain the effective operating air pressure data; Use the effective operating air pressure data as the directly usable air pressure data; Denote the time required for the air pressure to stabilize to the true value after the elevator moves as T_stable, and denote the air pressure aging period as T_vaild; For the starting stage of the elevator, assume that the elevator stop time before operation is t1_stop. If t1_stop is greater than T_stable, it is considered that the starting air pressure value of this operation is valid, and at the same time, record the estimated height value of the elevator air pressure h1_press; For the elevator stop stage, assume that the stop duration after the elevator stops is t2_stop. If t2_stop is greater than T_stable, record the height value at the T_stable moment of the elevator stop as h2_press; At the same time, record the start and stop times of the elevator as t_start and t_end respectively; If both the start and end heights are valid, and the elevator running time t_end - t_start < T_vaild, it is considered that the start and end match, and the air pressure data traveled between the start and end is the effective operating air pressure data and can be directly used.
2. The method for acquiring air pressure data according to claim 1, characterized in that, The air pressure data collected by the air pressure sensing device includes the air pressure data of the elevator shaft.
3. An elevator floor estimation and anomaly detection method based on the air pressure data acquisition method of claim 2, characterized in that, Use the effective operating air pressure data and acceleration data for floor estimation and abnormal operation state detection.
4. The elevator floor estimation and anomaly detection method according to claim 1, characterized in that, Perform speed and height integral estimation according to the acceleration data, filter after obtaining effective air pressure data, and perform filter correction on the floor height.
5. The elevator floor estimation and anomaly detection method according to claim 4, characterized in that, After performing multiple filter corrections on the floor height, it includes the steps of: Dynamically establishing and updating the floor height model according to the historically filtered and corrected height.
6. The elevator floor estimation and anomaly detection method according to claim 4, characterized in that, According to the historically statistical elevator running speed and acceleration information and the floor height model, and compare with the current data to calculate the acceleration abnormality, speed abnormality and uneven floor abnormality information.
7. The elevator floor estimation and anomaly detection method according to claim 4, characterized in that, The filtering includes Kalman filtering, extended Kalman filtering and complementary filtering.
8. The elevator floor estimation and anomaly detection method according to claim 6, characterized in that, It includes the step of setting a threshold, and the normal value can be learned through historical data statistics. When the result of comparing the normal value with the current data exceeds the set threshold, the current abnormal information can be obtained.
9. An elevator floor estimation and anomaly detection system, characterized in that, Execute the method steps described in any one of claims 1 to 8.