Calibration method of air pressure sensor, elevator positioning method, device, and storage medium

Abstract

This invention discloses a calibration method for barometric pressure sensors, an elevator positioning method, equipment, and a storage medium. The method includes: when the vent of a sealed container is opened and a temperature change event occurs inside the sealed container, constructing multiple detection points for each barometric pressure sensor; determining a first inflection point among multiple first candidate points; sampling the multiple first candidate points at a first frequency from the detection points; sampling multiple detection points in the neighborhood of the first inflection point at a second frequency as second candidate points; the second frequency being higher than the first frequency; confirming a second inflection point based on the multiple second candidate points; sampling multiple detection points in the neighborhood of the second inflection point based on the gradient changes of the multiple second candidate points as target points; and constructing a barometric pressure compensation table for calibrating each barometric pressure sensor based on the first candidate points, second candidate points, and target points. This improves the accuracy of barometric pressure compensation, effectively enhancing the quality of subsequent operations relying on barometric pressure sensors and ensuring safety.

Description

Technical Field

[0001] This invention relates to the field of air pressure measurement technology, and in particular to a calibration method for air pressure sensors, an elevator positioning method, equipment, and storage medium. Background Technology

[0002] In scenarios such as elevators, smart wearable devices, and smart homes, barometric pressure sensors are used to detect barometric pressure values ​​in real time, enabling services such as location tracking, weather warnings, health monitoring, and control of home appliances, providing users with various services in their daily lives and production.

[0003] Under normal circumstances, the physical characteristics of the sensitive element in the barometric pressure sensor change with temperature, and the internal structure and circuit of the barometric pressure sensor will also deviate from the ideal working state due to temperature fluctuations. This results in a large deviation between the detected barometric pressure value and the true value at different temperatures. In this case, a compensation value for the barometric pressure is configured for the barometric pressure sensor at different temperatures.

[0004] Currently, the compensation value of air pressure is obtained by linear interpolation for the statistical compensation value of a single air pressure sensor within a narrow temperature range (such as 25℃±5℃), and then applied to other air pressure sensors of the same type.

[0005] However, linear interpolation fitting of air pressure compensation values ​​within a narrow temperature range is a simplistic modeling approach that deviates from the actual air pressure variation with temperature. This results in a discrepancy between the detected air pressure value and the true value even after the air pressure sensor is calibrated, leading to lower quality of subsequent operations and even safety risks.

[0006] For example, in an elevator scenario, if the air pressure detected by the air pressure sensor is inaccurate, it may cause the car's positioning to be off, potentially leading to incorrect leveling of the car and resulting in injury to users when entering or exiting the car. Summary of the Invention

[0007] This invention provides a calibration method for a barometric pressure sensor, an elevator positioning method, equipment, and a storage medium to improve the manufacturing accuracy of a barometric pressure compensation gauge.

[0008] In a first aspect, embodiments of the present invention provide a method for calibrating a barometric pressure sensor, comprising arranging multiple barometric pressure sensors inside a sealed container and arranging a barometric pressure calibrator outside the container, the method comprising:

[0009] When the air vent of the sealed container is opened and a temperature change event occurs inside the sealed container, multiple detection points are constructed for each of the pressure sensors; the detection points include the temperature value inside the sealed container and the pressure compensation value of the pressure sensor, and the pressure compensation value is the difference between the pressure value of the pressure calibrator and the pressure value of the pressure sensor.

[0010] A first inflection point is determined from the first candidate points; the first candidate points are sampled from the detection points at a first frequency;

[0011] From the neighborhood of the first inflection point, the detection points are sampled at a second frequency to serve as second candidate points; the second frequency is higher than the first frequency.

[0012] The second inflection point is confirmed based on the second candidate point;

[0013] Within the neighborhood of the second inflection point, multiple detection points are sampled based on the gradient changes of multiple second candidate points, and used as target points;

[0014] A pressure compensation table for calibrating the pressure sensor is constructed based on the first candidate point and the second candidate point outside the neighborhood of the target point and the second inflection point.

[0015] Secondly, embodiments of the present invention also provide an elevator positioning method, wherein air pressure sensors are arranged at the ends of the elevator car and the hoistway, and the air pressure sensors are configured with an air pressure compensation table constructed according to the air pressure sensor calibration method described in the first aspect, the method comprising:

[0016] For each of the aforementioned barometric pressure sensors, the barometric pressure value of the barometric pressure sensor and the temperature value of the environment in which the barometric pressure sensor is located are collected;

[0017] For each of the aforementioned pressure sensors, the pressure value is calibrated according to the pressure compensation value corresponding to the temperature value in the pressure compensation table configured for the pressure sensors;

[0018] If calibration is completed, the car is positioned based on the difference between the air pressure value corresponding to the car and the air pressure value corresponding to the end of the hoistway.

[0019] Thirdly, embodiments of the present invention also provide a calibration device for a barometric pressure sensor, characterized in that multiple barometric pressure sensors are arranged inside a sealed container and a barometric pressure calibrator is arranged outside the container, the device comprising:

[0020] The detection point construction module is used to construct multiple detection points for each of the air pressure sensors when the air vent of the sealed container is opened and a temperature change event occurs inside the sealed container; the detection points include the temperature value inside the sealed container and the air pressure compensation value of the air pressure sensor, and the air pressure compensation value is the difference between the air pressure value of the air pressure calibrator and the air pressure value of the air pressure sensor.

[0021] The first inflection point confirmation module is used to determine a first inflection point from the first candidate points; the first candidate points are sampled from the detection points at a first frequency.

[0022] The second candidate point sampling module is used to sample the detection point from the neighborhood of the first inflection point at a second frequency as a second candidate point; the second frequency is higher than the first frequency.

[0023] The second inflection point confirmation module is used to confirm the second inflection point based on the second candidate point;

[0024] The target point sampling module is used to sample multiple detection points in the neighborhood of the second inflection point based on the gradient changes of multiple second candidate points, and use them as target points.

[0025] The barometric pressure compensation table construction module is used to construct a barometric pressure compensation table for calibrating the barometric pressure sensor based on the first candidate point and the second candidate point outside the neighborhood of the target point and the second inflection point.

[0026] Fourthly, embodiments of the present invention also provide an elevator positioning device, wherein air pressure sensors are arranged at the ends of the elevator car and the hoistway, and the air pressure sensors are configured with an air pressure compensation table constructed according to the air pressure sensor calibration method described in the first aspect, the method comprising:

[0027] An environmental data acquisition module is used to acquire the air pressure value and temperature value of the environment in which each air pressure sensor is located for each air pressure sensor.

[0028] A pressure calibration module is used to calibrate the pressure value for each of the pressure sensors according to the pressure compensation value corresponding to the temperature value in the pressure compensation table configured for the pressure sensors.

[0029] The car positioning module is used to position the car based on the difference between the air pressure value corresponding to the car and the air pressure value corresponding to the end of the hoistway, once calibration is completed.

[0030] Fifthly, embodiments of the present invention also provide a computer device, the computer device comprising:

[0031] One or more processors;

[0032] Storage device for storing one or more programs;

[0033] When the one or more programs are executed by the one or more processors, the one or more processors implement a calibration method for a barometric pressure sensor as provided in the first aspect of the present invention, or an elevator positioning method as provided in the second aspect of the present invention.

[0034] In a sixth aspect, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a calibration method for a barometric pressure sensor as provided in the first aspect of the present invention, or an elevator positioning method as provided in the second aspect of the present invention.

[0035] In a seventh aspect, embodiments of the present invention also provide a computer program product, the computer program product including a computer program, which, when executed by a processor, implements a calibration method for a barometric pressure sensor as provided in the first aspect of the present invention, or an elevator positioning method as provided in the second aspect of the present invention.

[0036] In this embodiment of the invention, when the vent of a sealed container is opened and a temperature change event occurs inside the sealed container, multiple detection points are constructed for each pressure sensor. The detection points include the temperature value inside the sealed container and the pressure compensation value of the pressure sensor. The pressure compensation value is the difference between the pressure value of the pressure calibrator and the pressure value of the pressure sensor. A first inflection point is determined from multiple first candidate points. The multiple first candidate points are sampled from the detection points at a first frequency. From the neighborhood of the first inflection point, multiple detection points are sampled at a second frequency as second candidate points. The second frequency is higher than the first frequency. A second inflection point is confirmed based on the multiple second candidate points. In the neighborhood of the second inflection point, multiple detection points are sampled based on the gradient change of the multiple second candidate points as target points. A pressure compensation table for calibrating each pressure sensor is constructed based on the first candidate points, second candidate points, and target points. This embodiment uses vents to balance the air pressure inside and outside the sealed container, allowing the pressure sensor to focus on the effects of temperature. A first-frequency sparse sampling method roughly captures the pressure sensor's response pattern, quickly obtaining a general measurement range. A second-frequency dense sampling method precisely locates nonlinear regions. These two sampling steps, from coarse to fine, reduce the amount of sampling and computation, while also differentiating between linear and nonlinear regions for personalized sampling, closely reflecting the actual changes in air pressure with temperature, thus improving the accuracy of the pressure compensation meter. Furthermore, multiple pressure sensors are used in parallel to create dedicated pressure compensation meters, further improving the accuracy of pressure compensation and effectively enhancing the quality of subsequent operations relying on pressure sensors, ensuring safety. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0038] Figure 1 A flowchart illustrating a calibration method for a barometric pressure sensor provided in Embodiment 1 of the present invention;

[0039] Figure 2 This is a calibration device for a barometric pressure sensor provided in Embodiment 1 of the present invention;

[0040] Figure 3 This is a structural diagram of the sensor PCBA provided in Embodiment 1 of the present invention;

[0041] Figure 4 This is a perspective view of the sealed container provided in Embodiment 1 of the present invention;

[0042] Figure 5 This is a flowchart of an elevator positioning method provided in Embodiment 2 of the present invention;

[0043] Figure 6 This is a structural block diagram of a calibration device for a barometric pressure sensor provided in Embodiment 3 of the present invention;

[0044] Figure 7 This is a structural block diagram of an elevator positioning device provided in Embodiment 4 of the present invention;

[0045] Figure 8 This is a schematic diagram of the structure of a computer device provided in Embodiment 5 of the present invention. Detailed Implementation

[0046] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0047] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be used interchangeably where appropriate so that the embodiments of the invention described herein can cover implementations in sequences other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0048] Example 1

[0049] See Figure 1The diagram illustrates a flowchart of a barometric pressure sensor calibration method according to Embodiment 1 of the present invention. This embodiment is applicable to identifying nonlinear regions in the temperature-pressure relationship within a preset temperature range, adaptively sampling the nonlinear regions, and performing linear interpolation on the linear regions to construct a barometric pressure compensation table. This method can be executed by a barometric pressure sensor calibration device, which can be implemented in hardware and / or software and can be configured in a computer device. Figure 1 As shown, the method includes:

[0050] Step 101: When the air vent of the sealed container is opened or a temperature change event occurs inside the sealed container, multiple detection points are constructed for each pressure sensor.

[0051] In this embodiment, multiple pressure sensors are arranged inside a sealed container, and a pressure calibrator is arranged outside. When the vent of the sealed container is opened, the pressure inside and outside the sealed container becomes the same, allowing the pressure sensors inside the sealed container to focus on the effects of temperature. The pressure calibrator provides a standard answer; by comparing the pressure value measured by the pressure calibrator with the pressure value measured by the pressure sensors inside the sealed container at a certain temperature, it can be determined how much the pressure sensor has deviated from its measurement. By controlling temperature changes inside the sealed container, multiple detection points are established for each pressure sensor, providing a data foundation for subsequent sampling.

[0052] For example, when a temperature change event occurs inside a sealed container, the process of constructing multiple detection points for the pressure sensor is divided into three stages: preprocessing, low-temperature calibration, and high-temperature calibration.

[0053] Pre-processing stage: Construct the environment outside the sealed container by turning on the air conditioner to keep the outside of the sealed container at a constant temperature of 25°C. The barometric pressure calibrator is initialized and broadcasts the barometric pressure value outside the sealed container in real time (e.g., 101325 Pa). After completing the construction of the environment outside the sealed container, multiple barometric pressure sensors to be calibrated are arranged in the sealed container and connected to a power source.

[0054] Low-temperature calibration: In this embodiment, the low-temperature range is set to (-10℃~25℃). After the pretreatment stage is completed, a low-temperature environment is constructed inside the sealed container. The cooling element arranged in the sealed container is opened by closing the vent, and the temperature is reduced to -10℃ at a rate of 2℃ / min. Since the elevator operating environment is usually in the range of (-10℃~45℃), the ambient temperature value of the experiment in this embodiment is set in combination with the elevator operating environment. The temperature change range during the temperature change event in the sealed container is (-10℃~45℃). The temperature range setting is different for different operating scenarios, and it is not limited here. The sealed container was cooled to the lowest temperature required for this experiment (-10℃), and the temperature inside the sealed container was monitored by a temperature sensor. The temperature was maintained stable for 10 minutes to complete the construction of the low-temperature environment. After the low-temperature environment was established, the solenoid valve in the sealed container was energized to open the vent, allowing the air pressure inside and outside the sealed container to equalize. This pressure equalization took approximately 30 seconds. The sealed container was then heated to 25℃ at a rate of 0.5℃ / min. The temperature sensor was set to collect a temperature value every 0.1℃, and the pressure sensor collected the corresponding air pressure values ​​for each temperature value. These values ​​were received via Bluetooth from a pressure calibrator. The collected air pressure values ​​are used to establish detection points for each air pressure sensor in the low-temperature range. The detection points include the temperature value inside the sealed container and the air pressure compensation value of the air pressure sensor. The air pressure compensation value is the difference between the air pressure value of the air pressure calibrator and the air pressure value of the air pressure sensor. Since there are many detection points for each air pressure sensor, this embodiment divides the temperature range in the temperature change event into two smaller temperature ranges. The calibration operation of the air pressure sensor is completed for one small temperature range first, and then the calibration operation of the air pressure sensor is completed for the remaining small temperature range, so as to reduce the amount of data calculation and reduce the computational cost.

[0055] High-temperature calibration: The high-temperature range is set to (25℃~45℃). After completing the low-temperature calibration, a high-temperature environment is constructed. By closing the vent, the heater placed inside the sealed container is turned on, and the temperature is increased to 45℃ at a rate of 3℃ / min. The temperature inside the sealed container is monitored by a temperature sensor, and the temperature is maintained stable for 10 minutes to complete the construction of the high-temperature environment. After completing the construction of the high-temperature environment, the low-temperature calibration steps are repeated, i.e., the solenoid valve is energized to open the vent, balancing the air pressure inside and outside the sealed container, and the temperature is decreased to 25℃ at a rate of 0.5℃ / min. A temperature value is collected every 0.1℃, and the air pressure sensor collects the corresponding air pressure value. The air pressure value collected by the air pressure calibrator is received via Bluetooth. Detection points are constructed for each air pressure sensor in the high-temperature range, and the detection points constructed in the high-temperature range are analyzed to complete the calibration operation of the air pressure sensors. In this embodiment, the high-temperature calibration can be completed first, followed by the low-temperature calibration; this is not a limitation.

[0056] Because the pressure and temperature sensors have low computing power, they read data from every frame. Therefore, the initial detection points constitute a huge amount of data. If the initial detection points are directly used to build a pressure compensation table, the table will be massive, noisy, and inefficient when querying. The massive amount of data (detection points) will also consume a lot of storage space, increase costs, and increase the computational burden. In most of the massive detection points, the temperature value and the pressure compensation value are linearly related. For example, 100 or 1000 consecutive detection points may be approximately a horizontal straight line on the x and y axes. Therefore, there is a lot of redundant data in the initial detection points. This embodiment is based on the constructed detection points, which are the foundation for all subsequent accurate calibration operations. Without these original data (detection points), it is difficult to analyze the temperature characteristics of the pressure sensor and to build a pressure compensation table that can operate in an elevator environment.

[0057] For example, in this embodiment of the invention, the barometric pressure compensation gauge is manufactured by means of... Figure 2 The image shows the fabrication of a calibration device for a barometric pressure sensor. Figure 2 A constant temperature room of 25°C was constructed, housing the barometric calibrator and the sealed container. Placing the calibrator at 25°C ensures the stability and accuracy of its measured pressure values, preventing temperature fluctuations from interfering with its hardware performance and measurement results, thus guaranteeing the calibration accuracy of the pressure sensor being calibrated. 25°C is the standard operating temperature for most electronic components and precision sensors; at this temperature, the temperature drift coefficient of components is minimal, and hardware performance is at its most stable state, minimizing hardware characteristic drift caused by temperature changes and ensuring the calibrator's measurement accuracy. The barometric calibrator transmits the collected pressure values ​​to the MCU (Microcontroller Unit), which then transmits them via Bluetooth. From there, the pressure values ​​are transmitted to the individual sensor PCBAs (Printed Circuit Board Assemblies) within the sealed container, where various detection points are established.

[0058] The sealed container contains a cooling chip, a heater, a temperature control module, a temperature sensor, a power supply assembly, an air vent, a fan, and multiple sensor PCBAs. The multiple sensor PCBAs are arranged on a sensor bracket, with each sensor PCBA spaced more than 50 mm apart to reduce thermal coupling. The sensor bracket can be used for quick installation and removal. After installation, the sensor PCBAs receive data through a data interface.

[0059] The sealed container is double-layered vacuum insulated, with the inner wall covered with insulation material. The insulation material is used to ensure that the constant temperature of 25°C outside the sealed container does not affect the temperature inside the sealed container, thus isolating the temperature exchange between the inside and outside of the sealed container.

[0060] The cooling element is a semiconductor cooling element with a cooling rate of 2℃ / min; the heater is a resistance heater with a heating rate of 3℃ / min; the temperature sensor is a PT100, and the temperature value collected by the temperature sensor has a maximum deviation of 0.1℃.

[0061] The temperature sensor collects the temperature value in the sealed container and transmits it to the AD (analog-to-digital converter) module in the temperature control module, which converts the analog signal output by the temperature sensor into a digital signal for recognition and processing by the MCU and PID algorithm module.

[0062] The PID algorithm module dynamically adjusts the temperature deviation using the PID (proportional-integral-derivative) algorithm. The MCU outputs control commands to the cooling output section or the heating output section to control the cooling element to cool down or the heater to heat up, thus realizing the temperature change event.

[0063] The power supply unit provides electrical energy, the fan is used to equalize the temperature of the sealed container, and the solenoid valve vent is used to balance the air pressure inside and outside the sealed container.

[0064] For example, such as Figure 3 The diagram shows the structure of the sensor PCBA. Component 3 in the diagram includes a data acquisition and control unit, a pressure sensor, a temperature sensor, and Bluetooth. The pressure sensor is used to collect the pressure value in the sealed container, the temperature sensor is used to collect the temperature value in the sealed container, Bluetooth is used to receive the pressure value collected by the pressure calibrator, and the data acquisition and control unit is used to establish detection points.

[0065] For example, Figure 4 The image shown is a 3D view of the exterior of a sealed container. Figure 4 The system includes an vent 401 and a cooling element 402. The vent 401 is located at the center of a surface perpendicular to the surface of the cooling element 402. When the vent 401 is opened, pressure balancing occurs, and gas flows from the center outwards or in the opposite direction, more evenly promoting the overall gas flow within the sealed container. Compared to vents at the edges, this reduces localized gas accumulation and flow obstruction within the container, making the pressure balancing process smoother and less affected by the gas distribution within the sealed container, thus improving the stability and efficiency of pressure balancing. The cooling element 402 is located at the top of the sealed container to cool it, enabling low-temperature calibration of the pressure sensor. The vent 401 has a diameter of approximately 5 mm and its opening and closing are controlled by a solenoid valve with a response time of less than or equal to 10 ms.

[0066] Step 102: Determine the first inflection point from the first candidate points.

[0067] In this embodiment, the initially constructed detection points are continuously collected during temperature change events, resulting in a large amount of data containing a significant amount of redundant information (such as regions where the pressure compensation value changes gradually with temperature). Directly performing detailed analysis on all detection points would significantly increase the computational burden and reduce efficiency. The first candidate points are sampled from the detection points at a first frequency (a relatively low frequency), which preserves the overall trend of pressure compensation value changes with temperature while greatly reducing the data volume. This makes subsequent gradient calculations and inflection point identification easier to perform, and samples a general measurement range, allowing for a rough capture of the pressure sensor's response pattern. The first inflection point is then searched among the selected first candidate points to initially locate the nonlinear region between temperature and pressure compensation values. Determining the first inflection point helps clarify the relationship between pressure and temperature changes, ensuring that subsequent sampling resources are concentrated in the critical region that has the greatest impact on calibration accuracy (i.e., near the first inflection point).

[0068] For example, the difference between the air pressure compensation values ​​of two adjacent first candidate points is calculated as the air pressure change; the difference between the temperature values ​​of two adjacent first candidate points is calculated as the temperature change; the ratio between the air pressure change and the temperature change is calculated as the primary air pressure gradient value between two adjacent first candidate points; the absolute value of the difference between the two primary air pressure gradient values ​​corresponding to three consecutive first candidate points is taken as the absolute gradient difference; if the absolute gradient difference is greater than the gradient deviation threshold, the first candidate point located in the middle position among the three consecutive first candidate points is determined as the first inflection point.

[0069] The primary pressure gradient between two adjacent detection points can be expressed by the following formula:

[0070]

[0071] Among them, g i ΔP represents the primary pressure gradient between two adjacent detection points. i+1 ΔP represents the air pressure compensation value corresponding to the larger temperature value among two adjacent detection points. i T represents the air pressure compensation value corresponding to the smaller temperature value among two adjacent detection points. i+1 T represents the temperature value with the larger temperature value among two adjacent detection points. i This indicates the temperature value with the smaller temperature value among two adjacent detection points.

[0072] Step 103: Sample and detect points in the neighborhood of the first inflection point at the second frequency, and use them as the second candidate points.

[0073] In this embodiment, after confirming the first inflection point, a neighborhood is constructed based on the first inflection point. This neighborhood is the region where the rate of change of the pressure compensation value abruptly changes, and the data within this neighborhood is currently relatively sparse. Therefore, the sampling detection point at the second frequency is used as the second candidate point, with the second frequency being higher than the first frequency. This compensates for the insufficient density in the region where the rate of change of the pressure compensation value abruptly changes, providing a high-density data foundation for subsequent accurate analysis. The first frequency sampling is a coarse sampling, filtering first candidate data from a large amount of data. It can both preserve the overall trend of pressure compensation value changes with temperature and significantly reduce the amount of data. The second frequency sampling is a fine sampling, focusing computational resources on the neighborhood of the first inflection point. The two samplings significantly reduce the amount of data while ensuring the data analysis accuracy of the neighborhood of the first inflection point, forming an efficient data processing logic of global coarse mapping plus local fine mapping.

[0074] The advantage of this stratified sampling strategy is that it avoids excessive computational load and low analysis efficiency caused by the massive amount of data from the original detection points, and also avoids the waste of resources caused by indiscriminate sampling of all regions. The coarse sampling at the first frequency is sufficient to reflect its variation pattern, without the need for additional computational resources. For nonlinear regions such as the neighborhood of the first inflection point where the rate of change of air pressure compensation value changes abruptly, the fine sampling at the second frequency can accurately capture the change of compensation value corresponding to every tiny temperature fluctuation, providing high-density, high-resolution data support for subsequent steps.

[0075] For example, the difference between the temperature values ​​of two first candidate points adjacent to the first inflection point is calculated as the first reference temperature difference; the product between the first reference temperature difference and the first neighborhood coefficient is calculated as the first temperature step; the first temperature step is extended forward and backward based on the temperature value in the first inflection point to obtain the neighborhood of the first inflection point; within the neighborhood of the first inflection point, multiple detection points are sampled at a second frequency as second candidate points.

[0076] The first neighborhood coefficient is related to the sharpness of the first inflection point. If the sharpness of the first inflection point is high (meaning that the pressure compensation value undergoes a drastic change within a very small temperature range, such as a jump from 0.1 kPa to 0.8 kPa in pressure when the temperature changes by only 0.5℃), then the neighborhood of the first inflection point does not need to be too wide. In this case, setting a smaller first neighborhood coefficient can result in a smaller first temperature step (e.g., if the first neighborhood coefficient is 0.3 and the first reference temperature difference is 2℃, then the first temperature step is 0.6℃, and the neighborhood range is the temperature value of the first inflection point ± 0.6℃). This can accurately delineate the nonlinear region of the pressure compensation value change and avoid non-critical data caused by an overly wide neighborhood of the first inflection point (e.g., the pressure compensation value has returned to normal). The neighborhood of the first inflection point is included to reduce redundant calculations in subsequent high-frequency sampling. If the sharpness of the first inflection point is low (meaning that the sudden change in the pressure compensation value is dispersed over a wide temperature range, such as when the temperature changes by 2°C, the pressure compensation value gradually increases from 0.1 kPa to 0.8 kPa), then the neighborhood of the first inflection point needs to be wider. In this case, setting a larger first neighborhood coefficient can result in a larger first temperature step size (e.g., if the first neighborhood coefficient is 0.8 and the first reference temperature difference is 2°C, then the first temperature step size is 1.6°C, and the neighborhood range is the temperature value of the first inflection point ± 1.6°C). This avoids the nonlinear region of the temperature-pressure compensation value change being missed due to an overly narrow neighborhood, which would lead to data loss in the second frequency sampling.

[0077] Step 104: Confirm the second inflection point based on the second candidate point.

[0078] In this embodiment, the first inflection point is a potential inflection point of abrupt change in temperature-pressure compensation value, which is a rough inflection point location. From a large number of first candidate points, the possible region of drastic change in pressure compensation value (the neighborhood of the first inflection point) is quickly located. More refined sampling is performed in the neighborhood of the first inflection point to supplement the data in the neighborhood of the first inflection point. The sampling points in the neighborhood of the first inflection point are the second candidate points. At this time, the first inflection point has been marked as the second candidate point. The second inflection point is confirmed based on the second candidate point. This is used to correct the nonlinear region between temperature-pressure compensation value initially located by the first inflection point, providing an accurate benchmark for subsequent fine sampling and ensuring the core accuracy of the final calibration table.

[0079] The first inflection point is a potential inflection point because it is determined by sampling the first candidate point at a first frequency (relatively low frequency). Its positioning logic depends on the absolute value of the primary pressure gradient difference between three consecutive first candidate points exceeding a threshold. Although this method can quickly pinpoint the approximate area of ​​abrupt changes in the rate of change of the pressure compensation value, it suffers from significant positioning accuracy defects due to the low-frequency characteristics of the first candidate points. For example, if the first frequency is to sample one first candidate point every 1°C, when the temperature difference between two adjacent first candidate points is 1°C, the primary pressure gradient value can only reflect the average rate of change within this 1°C interval, failing to capture more subtle gradient fluctuations within the interval. If the abrupt change in the rate of change of the pressure compensation value does not occur exactly at a single first candidate point, but rather between two first candidate points (e.g., 25.3°C is the true gradient abrupt change point, but the first candidate points only include 25°C and 26°C), then the first inflection point can only be roughly located at 25°C or 26°C, resulting in a positioning error of more than 0.3°C. The second candidate point is a detection point sampled from the neighborhood of the first inflection point at a higher frequency (e.g., one point every 0.1℃). The data density of the second candidate point is much higher than that of the first candidate point. It can cover every minute temperature change range with a smaller temperature interval within the approximate area where the first inflection point is located. At this time, by re-analyzing the inflection point through the second candidate point, the regional deviation caused by the low frequency of the first inflection point can be effectively corrected, and the inflection point location can be focused from a coarse temperature range to a precise temperature value. The precise temperature value and the corresponding air pressure compensation value are used as the second inflection point.

[0080] For example, the average temperature value of the second candidate point corresponding to the primary pressure gradient value is calculated as the average temperature value; the difference between the two primary pressure gradient values ​​corresponding to three consecutive second candidate points is divided by the difference between the average temperature values ​​corresponding to the two primary pressure gradient values, and this is used as the secondary pressure gradient value of the second candidate point located in the middle position among the three consecutive second candidate points; if the current secondary pressure gradient value is 0, and the signs of the secondary pressure gradient values ​​on the left and right sides of the current secondary pressure gradient value are opposite, then the second candidate point is confirmed as the second inflection point; if the signs of the secondary pressure gradient values ​​corresponding to two consecutive second candidate points are opposite, then a detection point with a secondary pressure gradient value of 0 is extracted between the two consecutive second candidate points as a potential point; if the potential point satisfies the condition that the signs of the secondary pressure gradient values ​​on the left and right sides are opposite, then the potential point is determined as the second inflection point.

[0081] The secondary pressure gradient at a given detection point can be calculated using the following formula:

[0082]

[0083] in, Let (dTdΔP) be the secondary pressure gradient value of the detection point located in the middle of three consecutive detection points.T+ΔT Let (dTdΔP) be the pressure gradient value of the last two detection points out of three consecutive detection points. T ΔT represents the first two temperature gradient values ​​among three consecutive detection points, and ΔT represents the difference between the average temperature of the last two detection points and the average temperature of the first two detection points among three consecutive detection points.

[0084] Step 105: In the neighborhood of the second inflection point, sample multiple detection points based on the gradient changes of multiple second candidate points, and use them as target points.

[0085] In this embodiment, after confirming the second inflection point, a neighborhood of the second inflection point is constructed based on it. The second inflection point is approximately the center point in this neighborhood. The second inflection point is a critical point that can truly reflect the drastic changes in the air pressure compensation value. The neighborhood of the second inflection point represents the nonlinear region of the temperature-air pressure compensation value. The sampling of the nonlinear region affects the upper limit of the calibration accuracy of the air pressure sensor. By analyzing the gradient change of the second candidate band in the neighborhood of the second inflection point, the sampling frequency of the neighborhood of the second inflection point is confirmed. This avoids the waste of computing resources caused by blindly adopting high-frequency sampling. The limited computing power is concentrated on the nonlinear region that has the greatest impact on the calibration accuracy. Multiple detection points are sampled as target points according to the sampling frequency. At this time, the second inflection point has been marked as the target point, realizing dense sampling in the neighborhood where the air pressure compensation value changes drastically, and providing dense data for the nonlinear region in the final air pressure compensation table.

[0086] For example, the difference between the temperature values ​​of two second candidate points adjacent to the second inflection point is calculated as the second reference temperature difference; the product of the second reference temperature difference and the second neighborhood coefficient is calculated as the second temperature step size; the second neighborhood coefficient is related to the sharpness of the second inflection point; the second temperature step size is extended forward and backward based on the temperature value at the second inflection point to obtain the neighborhood of the second inflection point; within the neighborhood of the second inflection point, the primary pressure gradient value between the pressure values ​​of two consecutive second candidate points is queried; within the neighborhood of the second inflection point, the absolute values ​​of each primary pressure gradient value are added together to obtain the total absolute gradient value; the total absolute gradient value is divided by the number of primary pressure gradient values ​​to obtain the gradient change value; a third frequency is determined based on the gradient change value; the third frequency is positively correlated with the gradient change value; multiple detection points are collected within the neighborhood of the second inflection point based on the third frequency as target points.

[0087] The gradient change value can be calculated using the following formula:

[0088]

[0089] in, Let |g be the gradient value. i| represents the absolute value of the primary pressure gradient between two consecutive detection points, and n represents the number of primary pressure gradient values.

[0090] For example, if the gradient change value is greater than the first gradient threshold, then the third frequency is determined to be the first value; if the gradient change value is greater than or equal to the second gradient threshold and less than or equal to the first gradient threshold, then the third frequency is determined to be the second value; if the gradient change value is less than the second gradient threshold, then the third frequency is determined to be the third value; the first value is greater than the second value; the second value is greater than the third value.

[0091] The gradient change value being greater than the first gradient threshold indicates that The first value is any value between 0.1℃ and 0.5℃; a gradient change value greater than or equal to the second gradient threshold and less than or equal to the first gradient threshold indicates... The second value is any value between 0.5℃ and 1℃; a gradient change value less than the second gradient threshold indicates... The third value is any value between 1℃ and 5℃. The above data is only for illustrative purposes and does not impose any restrictions on its value.

[0092] Step 106: Construct a pressure compensation table for calibrating the barometric pressure sensor based on the first candidate point and the second candidate point outside the neighborhood of the target point and the second inflection point.

[0093] In this embodiment, after sampling the nonlinear region (neighborhood of the second inflection point), a pressure compensation table for calibrating the barometric pressure sensor is constructed using the target point, the first candidate point outside the neighborhood of the second inflection point, and the second candidate point. Multiple barometric pressure sensors are used to create dedicated pressure compensation tables in parallel, which further improves the accuracy of pressure compensation and effectively improves the quality of subsequent business operations that rely on barometric pressure sensors, ensuring safety.

[0094] For example, a linear interpolation operation can be performed on the temperature range outside the domain of the second inflection point to construct a pressure compensation table, as follows:

[0095] In the neighborhood of the second inflection point, linear interpolation is performed between two adjacent sampling points to obtain new sampling points; the sampling points include the first candidate point, the second candidate point, and the endpoints of the neighborhood of the second inflection point; the sampling points and the target point are written into the pressure compensation table used to calibrate the barometric pressure sensor.

[0096] The linear interpolation can be expressed by the following formula:

[0097]

[0098] Tb = Ta + ΔTi;

[0099] Wherein, P(T) is the air pressure compensation value of the new sampling point, P(Ta) is the air pressure compensation value of the two adjacent sampling points with smaller temperature values, P(Tb) is the air pressure compensation value of the two adjacent sampling points with larger temperature values, T is the temperature value of the new sampling point, ΔTi is the difference between the temperature values ​​of the two adjacent sampling points, Tb is the temperature value of the two adjacent sampling points with larger temperature values, and Ta is the temperature value of the two adjacent sampling points with smaller temperature values.

[0100] Current technologies for creating barometric pressure compensation gauges typically involve sampling from a massive number of measurement points at a preset frequency, performing linear interpolation on the sampled data, and finally constructing the pressure compensation gauge using the sampled data and the linear difference. These technologies assume a linear relationship between temperature and the pressure compensation value; however, they overlook the non-linear nature of pressure compensation values ​​with temperature changes. The pressure compensation value (i.e., measurement error) of a barometric pressure sensor is affected by multiple factors, including the material properties of the sensitive element, the circuit signal amplification mechanism, and the physical expansion characteristics of the gas. It does not exhibit a single linear relationship across the entire temperature range, especially in specific temperature intervals (such as the temperature coefficient abrupt change region of the barometric pressure sensor's sensitive element or the circuit temperature drift threshold region). In these intervals, the pressure compensation value can fluctuate dramatically non-linearly with temperature: a temperature change of only 0.5°C can cause the compensation value to jump from 0.1 kPa to 0.6 kPa. Current technologies, sampling at a fixed frequency and relying on linear interpolation, can only fit the average trend between adjacent sampling points, completely failing to capture the details of these non-linear fluctuations. This directly leads to a significant decrease in the measurement accuracy of barometric pressure sensors in non-linear temperature ranges. This invention identifies the nonlinear region of the temperature-pressure compensation value by locating the secondary inflection point, performs intensive sampling on this nonlinear region, concentrates limited computing resources on the nonlinear region, and performs linear interpolation on the linear region. By distinguishing between the linear and nonlinear regions and formulating two different sampling methods, the production efficiency of the pressure compensation meter is greatly improved, as is the calibration accuracy of the pressure compensation meter. This effectively improves the quality of subsequent business operations that rely on pressure sensors and ensures safety.

[0101] In this embodiment of the invention, when the vent of a sealed container is opened and a temperature change event occurs inside the sealed container, multiple detection points are constructed for each pressure sensor. The detection points include the temperature value inside the sealed container and the pressure compensation value of the pressure sensor. The pressure compensation value is the difference between the pressure value of the pressure calibrator and the pressure value of the pressure sensor. A first inflection point is determined from multiple first candidate points. The multiple first candidate points are sampled from the detection points at a first frequency. From the neighborhood of the first inflection point, multiple detection points are sampled at a second frequency as second candidate points. The second frequency is higher than the first frequency. A second inflection point is confirmed based on the multiple second candidate points. In the neighborhood of the second inflection point, multiple detection points are sampled based on the gradient change of the multiple second candidate points as target points. A pressure compensation table for calibrating each pressure sensor is constructed based on the first candidate points, second candidate points, and target points. This embodiment uses vents to balance the air pressure inside and outside the sealed container, allowing the pressure sensor to focus on the effects of temperature. A first-frequency sparse sampling method roughly captures the pressure sensor's response pattern, quickly obtaining a general measurement range. A second-frequency dense sampling method precisely locates nonlinear regions. These two sampling steps, from coarse to fine, reduce the amount of sampling and computation, while also differentiating between linear and nonlinear regions for personalized sampling, closely reflecting the actual changes in air pressure with temperature, thus improving the accuracy of the pressure compensation meter. Furthermore, multiple pressure sensors are used in parallel to create dedicated pressure compensation meters, further improving the accuracy of pressure compensation and effectively enhancing the quality of subsequent operations relying on pressure sensors, ensuring safety.

[0102] Example 2

[0103] See Figure 5 The diagram illustrates a flowchart of an elevator positioning method according to Embodiment 1 of the present invention. This embodiment is applicable to situations where the air pressure in the elevator lobby and shaft is compensated at both ends based on an air pressure compensation table to position the elevator. This method can be executed by an elevator positioning device, which can be implemented in hardware and / or software and can be configured in a computer device. Figure 5 As shown, the method includes:

[0104] Step 501: For each barometric pressure sensor, collect the air pressure value and temperature value of the environment where the barometric pressure sensor is located.

[0105] In this embodiment, pressure sensors and temperature sensors are installed at the ends of the elevator car and shaft. The pressure sensors are equipped with a pressure compensation table constructed according to the method in Embodiment 1. The pressure sensors read the pressure values ​​collected by the pressure sensors and the temperature sensors read the temperature values ​​collected by the temperature sensors, thus collecting the pressure and temperature values ​​of the environment in which each pressure sensor is located. The working principle of a pressure sensor is typically based on measuring changes in ambient air pressure to determine the relative position or height of a target object. However, the output pressure value of the pressure sensor itself is affected by temperature changes under different ambient temperatures. When the ambient temperature changes, the pressure values ​​measured by the pressure sensor may deviate, thus affecting the final measurement results and positioning accuracy. To ensure that the pressure sensor can accurately reflect pressure changes under different temperature conditions, it is necessary to collect ambient temperature data. This helps to determine the source of the pressure value deviation and also provides data support for subsequent pressure compensation.

[0106] Step 502: For each pressure sensor, calibrate the pressure value according to the pressure compensation value corresponding to the temperature value in the pressure compensation table configured for the pressure sensor.

[0107] In this embodiment, the output value of the barometric pressure sensor is affected by the ambient temperature, and temperature fluctuations can cause errors in the barometric pressure measurement. Consequently, the measurement accuracy and stability of the barometric pressure sensor may vary with temperature changes, leading to deviations in the output pressure value. Therefore, a barometric pressure compensation meter provides a corresponding pressure compensation value based on the ambient temperature of the barometric pressure sensor, correcting the pressure value and thus eliminating or reducing the impact of temperature changes.

[0108] Based on the collected temperature value, look up the corresponding air pressure compensation value in the air pressure compensation table, and add the air pressure value measured by the air pressure sensor to complete the calibration of the collected air pressure value.

[0109] For example, the calibrated air pressure value at a certain temperature can be expressed by the following formula:

[0110] Pref = Praw + ΔP@Tself;

[0111] Where Pref represents the calibrated air pressure value at a certain temperature, Praw represents the collected air pressure value at a certain temperature, and ΔP@Tself represents the air pressure compensation value at a certain temperature.

[0112] Step 503: If calibration is completed, the car is positioned based on the difference between the air pressure value corresponding to the car and the air pressure value corresponding to the end of the hoistway.

[0113] In this embodiment, the height or position of the elevator car is indirectly calculated by utilizing the difference in air pressure values ​​between the elevator car and the hoistway end using air pressure sensors. Air pressure sensors detect the air pressure at the elevator's location, a value affected by environmental factors such as altitude, temperature, and wind speed. Since the elevator car and the hoistway end are typically at different heights, their air pressure values ​​will differ. By acquiring air pressure values ​​using sensors installed at these two locations and using an air pressure compensation table, the data from these sensors can be accurately calibrated. After calibration, the difference between the air pressure value in the car and the air pressure value at the hoistway end reflects the relative height between the car and the hoistway. Based on this difference, the relative position of the car can be accurately determined, thus achieving precise elevator positioning.

[0114] For example, the difference between the air pressure value corresponding to the car and the air pressure value corresponding to the end of the hoistway is divided by the air pressure ratio coefficient to obtain the height difference between the car and the end of the hoistway.

[0115] The height difference between the car and the end of the hoistway can be calculated using the following formula:

[0116]

[0117] Where H is the height difference between the car and the end of the hoistway, P1 is the air pressure value corresponding to the car, P2 is the air pressure value corresponding to the end of the hoistway, and α is the air pressure proportional coefficient, which is usually 0.12 Pa / m.

[0118] If the air pressure sensor is installed at the bottom of the shaft, the sum of the absolute height of the bottom of the shaft and the height difference is divided by the absolute height of a single floor to determine the floor where the car is located, thus completing the elevator positioning.

[0119] If the air pressure sensor is installed at the top of the end of the shaft, the difference between the absolute height of the top of the shaft and the height difference is divided by the absolute height of a single floor to determine the floor where the car is located, thus completing the elevator positioning.

[0120] The pressure sensor can also be installed in other locations in the wellbore. The above is just an example and does not limit the location where the pressure sensor can be installed in the wellbore.

[0121] In this embodiment of the invention, for each pressure sensor, the air pressure and temperature values ​​of the environment in which the pressure sensor is located are collected. For each pressure sensor, the air pressure value is calibrated according to the air pressure compensation value corresponding to the temperature value in the air pressure compensation table configured for the pressure sensor. If calibration is completed, the car is positioned based on the difference between the air pressure value corresponding to the car and the air pressure value corresponding to the end of the hoistway. This embodiment quickly completes the air pressure value calibration based on the ambient air pressure and temperature values ​​collected by each pressure sensor and the air pressure compensation value corresponding to the temperature value in the air pressure compensation table. This effectively eliminates the influence of temperature changes on the detection accuracy of the pressure sensors, ensuring that the calibrated air pressure value is closer to the actual ambient air pressure conditions. This not only significantly improves the accuracy and reliability of elevator positioning and avoids positioning deviation problems caused by air pressure detection errors, but also improves the safety of elevator operation and the riding experience.

[0122] Example 3

[0123] Figure 6 This is a schematic diagram of a calibration device for a barometric pressure sensor provided in Embodiment 2 of the present invention. Multiple barometric pressure sensors are arranged inside a sealed container, and a barometric pressure calibrator is arranged outside. Figure 5 As shown, the device includes:

[0124] The detection point construction module 601 is used to construct multiple detection points for each of the air pressure sensors when the air vent of the sealed container is opened and a temperature change event occurs inside the sealed container; the detection points include the temperature value inside the sealed container and the air pressure compensation value of the air pressure sensor, and the air pressure compensation value is the difference between the air pressure value of the air pressure calibrator and the air pressure value of the air pressure sensor.

[0125] The first inflection point confirmation module 602 is used to determine a first inflection point among the first candidate points; the first candidate points are sampled from the detection point at a first frequency.

[0126] The second candidate point sampling module 603 is used to sample the detection point from the neighborhood of the first inflection point at a second frequency as a second candidate point; the second frequency is higher than the first frequency.

[0127] The second inflection point confirmation module 604 is used to confirm the second inflection point based on the second candidate point;

[0128] The target point sampling module 605 is used to sample multiple detection points in the neighborhood of the second inflection point based on the gradient changes of multiple second candidate points, and use them as target points.

[0129] The bar pressure compensation table construction module 606 is used to construct a bar pressure compensation table for calibrating the bar pressure sensor based on the first candidate point and the second candidate point outside the neighborhood of the target point and the second inflection point.

[0130] In one embodiment of the present invention, the first inflection point confirmation module 602 includes:

[0131] The air pressure change calculation module is used to calculate the difference between the air pressure compensation values ​​in two adjacent first candidate points as the air pressure change.

[0132] The temperature change calculation module is used to calculate the difference between the temperature values ​​of two adjacent first candidate points as the temperature change.

[0133] A primary pressure gradient value calculation module is used to calculate the ratio between the pressure change and the temperature change, which is used as the primary pressure gradient value between two adjacent first candidate points.

[0134] The absolute gradient difference calculation module is used to take the absolute value of the difference between two primary pressure gradient values ​​corresponding to three consecutive first candidate points as the absolute gradient difference.

[0135] The first inflection point acquisition module is used to determine the first candidate point located in the middle position among three consecutive first candidate points as the first inflection point if the absolute gradient difference is greater than the gradient deviation threshold.

[0136] In one embodiment of the present invention, the second candidate point sampling module 603 includes:

[0137] The first reference temperature difference calculation module is used to calculate the difference between the temperature values ​​of two first candidate points adjacent to the first inflection point, as the first reference temperature difference;

[0138] The first temperature step calculation module is used to calculate the product between the first reference temperature difference and the first neighborhood coefficient, which is used as the first temperature step.

[0139] The neighborhood calculation module of the first inflection point is used to expand the first temperature step forward and backward based on the temperature value at the first inflection point to obtain the neighborhood of the first inflection point.

[0140] The second candidate point acquisition module is used to sample multiple detection points in the neighborhood of the first inflection point at a second frequency as second candidate points.

[0141] In one embodiment of the present invention, the second inflection point confirmation module 604 includes:

[0142] The temperature average calculation module is used to calculate the average value of the temperature values ​​in the second candidate points corresponding to the primary pressure gradient value, and use it as the temperature average.

[0143] The secondary pressure gradient value calculation module is used to divide the difference between the two primary pressure gradient values ​​corresponding to three consecutive second candidate points by the difference between the average temperature values ​​corresponding to the two primary pressure gradient values, and use it as the secondary pressure gradient value of the second candidate point located in the middle position among the three consecutive second candidate points;

[0144] The second inflection point determination module is used to confirm the second candidate point as the second inflection point if the current secondary pressure gradient value is 0 and the signs of the secondary pressure gradient values ​​on the left and right sides of the current secondary pressure gradient value are opposite.

[0145] The potential point determination module is used to extract the detection point with a secondary pressure gradient value of 0 between two consecutive second candidate points if the numerical signs of the secondary pressure gradient values ​​corresponding to two consecutive second candidate points are opposite, and use it as a potential point.

[0146] The second inflection point acquisition module is used to determine the potential point as the second inflection point if the signs of the secondary pressure gradient values ​​on the left and right sides are opposite.

[0147] In one embodiment of the present invention, the target point sampling module 605 includes:

[0148] The second reference temperature difference calculation module is used to calculate the difference between the temperature values ​​of two second candidate points adjacent to the second inflection point, as the second reference temperature difference;

[0149] The second temperature step calculation module is used to calculate the product between the second reference temperature difference and the second neighborhood coefficient, which is used as the second temperature step.

[0150] The neighborhood calculation module for the second inflection point is used to expand the second temperature step forward and backward based on the temperature value at the second inflection point to obtain the neighborhood of the second inflection point.

[0151] The primary pressure gradient value query module is used to query the primary pressure gradient value between the pressure values ​​of two consecutive second candidate points in the neighborhood of the second inflection point.

[0152] The total gradient absolute value calculation module is used to add the absolute values ​​of each of the primary pressure gradient values ​​in the neighborhood of the second inflection point to obtain the total gradient absolute value.

[0153] The gradient change value calculation module is used to divide the absolute value of the total gradient by the number of primary pressure gradient values ​​to obtain the gradient change value.

[0154] The third frequency determination module is used to determine a third frequency based on the gradient change value; the third frequency is positively correlated with the gradient change value.

[0155] The target point acquisition module is used to collect multiple detection points in the neighborhood of the second inflection point based on the third frequency, and use them as target points.

[0156] In one embodiment of the present invention, the third frequency determination module includes:

[0157] The first value determination module is used to determine the third frequency as the first value if the gradient change value is greater than the first gradient threshold.

[0158] The second value determination module is used to determine the third frequency as the second value if the gradient change value is greater than or equal to the second gradient threshold and less than or equal to the first gradient threshold.

[0159] The third value determination module is used to determine the third frequency as the third value if the gradient change value is less than the second gradient threshold; the first value is greater than the second value; and the second value is greater than the third value.

[0160] In one embodiment of the present invention, the barometric pressure compensation meter construction module 606 includes:

[0161] The new sampling point acquisition module is used to perform linear interpolation between two adjacent sampling points outside the neighborhood of the second inflection point to obtain a new sampling point; the sampling point includes the first candidate point, the second candidate point, and the endpoints of the neighborhood of the second inflection point;

[0162] The pressure compensation table acquisition module is used to write the sampling point and the target point into the pressure compensation table used for calibrating the pressure sensor.

[0163] The pressure sensor calibration device provided in this embodiment of the invention can execute the pressure sensor calibration method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the pressure sensor calibration method.

[0164] Example 4

[0165] Figure 7 This is a schematic diagram of an elevator positioning device according to Embodiment 2 of the present invention. Pressure sensors are arranged at both the ends of the elevator car and the hoistway. The pressure sensors are configured with a pressure compensation table constructed according to the method described in Embodiment 1. Figure 7 As shown, the device includes:

[0166] The environmental data acquisition module 701 is used to acquire the air pressure value and the temperature value of the environment where the air pressure sensor is located for each of the air pressure sensors.

[0167] The air pressure calibration module 702 is used to calibrate the air pressure value for each of the air pressure sensors according to the air pressure compensation value corresponding to the temperature value in the air pressure compensation table configured for the air pressure sensors.

[0168] The car positioning module 703 is used to position the car based on the difference between the air pressure value corresponding to the car and the air pressure value corresponding to the end of the hoistway if calibration is completed.

[0169] In one embodiment of the present invention, the car positioning module 703 includes:

[0170] The height difference calculation module is used to divide the difference between the air pressure value corresponding to the car and the air pressure value corresponding to the end of the hoistway by the air pressure ratio coefficient to obtain the height difference between the car and the end of the hoistway.

[0171] The first elevator positioning module is used to, if the air pressure sensor is arranged at the bottom of the end of the shaft, divide the sum of the absolute height of the bottom of the shaft and the height difference by the absolute height of a single floor to obtain the floor where the car is located, so as to complete the positioning of the elevator.

[0172] The second elevator positioning module is used to, if the air pressure sensor is arranged at the top of the end of the shaft, divide the difference between the absolute height of the top of the shaft and the height difference by the absolute height of a single floor to obtain the floor where the car is located, so as to complete the positioning of the elevator.

[0173] The elevator positioning device provided in the embodiments of the present invention can execute the elevator positioning method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the elevator positioning method.

[0174] Example 5

[0175] See Figure 8This diagram illustrates a structural schematic of a computer device according to an embodiment of the present invention. The term "computer device" is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, blade servers, mainframe computers, and other suitable computers. The computer device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0176] like Figure 8 As shown, the computer device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer programs stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the computer device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0177] Multiple components in computer device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of monitors, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows computer device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0178] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a barometric pressure sensor calibration method, or an elevator positioning method.

[0179] In some embodiments, the barometric pressure sensor calibration method, or the elevator positioning method, may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on computer device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the barometric pressure sensor calibration method, or the elevator positioning method, described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the barometric pressure sensor calibration method, or the elevator positioning method, by any other suitable means (e.g., by means of firmware).

[0180] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0181] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0182] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0183] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0184] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0185] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0186] Example 6

[0187] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements a barometric pressure sensor calibration method or an elevator positioning method as provided in any embodiment of this invention.

[0188] In implementing the computer program product, computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0189] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0190] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method of calibrating a barometric pressure sensor, characterized by, The method involves arranging multiple pressure sensors inside a sealed container and a pressure calibrator outside the container, and includes: When the air vent of the sealed container is opened and a temperature change event occurs inside the sealed container, multiple detection points are constructed for each of the pressure sensors; the detection points include the temperature value inside the sealed container and the pressure compensation value of the pressure sensor, and the pressure compensation value is the difference between the pressure value of the pressure calibrator and the pressure value of the pressure sensor. A first inflection point is determined from the first candidate points; the first candidate points are sampled from the detection points at a first frequency; From the neighborhood of the first inflection point, the detection points are sampled at a second frequency to serve as second candidate points; the second frequency is higher than the first frequency. The second inflection point is confirmed based on the second candidate point; Within the neighborhood of the second inflection point, multiple detection points are sampled based on the gradient changes of multiple second candidate points, and used as target points; A pressure compensation table for calibrating the pressure sensor is constructed based on the first candidate point and the second candidate point outside the neighborhood of the target point and the second inflection point.

2. The method of claim 1, wherein, Determining the first inflection point among the first candidate points includes: Calculate the difference between the air pressure compensation values ​​of two adjacent first candidate points as the air pressure change; Calculate the difference between the temperature values ​​of two adjacent first candidate points as the temperature change; Calculate the ratio between the pressure change and the temperature change, and use it as the first pressure gradient value between two adjacent first candidate points; The absolute value of the difference between the two primary pressure gradient values ​​corresponding to three consecutive first candidate points is taken as the absolute gradient difference. If the absolute gradient difference is greater than the gradient deviation threshold, then the first candidate point located in the middle position among the three consecutive first candidate points is determined as the first inflection point.

3. The method according to claim 1, characterized in that, The step of sampling the detection points from the neighborhood of the first inflection point at a second frequency as second candidate points includes: Calculate the temperature difference between the two first candidate points adjacent to the first inflection point, and use it as the first reference temperature difference; Calculate the product of the first reference temperature difference and the first neighborhood coefficient, and use it as the first temperature step size; Based on the temperature value at the first inflection point, the first temperature step size is extended forward and backward to obtain the neighborhood of the first inflection point; Within the neighborhood of the first inflection point, multiple detection points are sampled at a second frequency to serve as second candidate points.

4. The method according to claim 2, characterized in that, The step of confirming the second inflection point based on the second candidate point includes: The average temperature value is calculated for the temperature values ​​at the second candidate points corresponding to the primary pressure gradient value and is used as the average temperature value. The difference between the two primary pressure gradient values ​​corresponding to three consecutive second candidate points is divided by the difference between the average temperature values ​​corresponding to the two primary pressure gradient values, and this is taken as the secondary pressure gradient value of the second candidate point located in the middle position among the three consecutive second candidate points. If the current secondary pressure gradient value is 0, and the signs of the secondary pressure gradient values ​​on the left and right sides of the current secondary pressure gradient value are opposite, then the second candidate point is confirmed as the second inflection point. If the signs of the secondary pressure gradient values ​​corresponding to two consecutive second candidate points are opposite, then the detection point with a secondary pressure gradient value of 0 is extracted between the two consecutive second candidate points as a potential point. If the potential point satisfies the opposite signs of the secondary pressure gradient values ​​on the left and right sides, then the potential point is determined to be the second inflection point.

5. The method according to claim 1, characterized in that, The step of sampling multiple detection points as target points within the neighborhood of the second inflection point based on the gradient changes of multiple second candidate points includes: Calculate the temperature difference between the two second candidate points adjacent to the second inflection point, and use it as the second reference temperature difference; Calculate the product between the second reference temperature difference and the second neighborhood coefficient, and use it as the second temperature step; Based on the temperature value at the second inflection point, the second temperature step size is extended forward and backward to obtain the neighborhood of the second inflection point; Within the neighborhood of the second inflection point, query the first pressure gradient value between the pressure values ​​of two consecutive second candidate points; Within the neighborhood of the second inflection point, the absolute values ​​of each of the primary pressure gradient values ​​are added together to obtain the total absolute value of the gradient. Divide the absolute value of the total gradient by the number of primary pressure gradient values ​​to obtain the gradient change value; A third frequency is determined based on the gradient change value; the third frequency is positively correlated with the gradient change value. Based on the third frequency, multiple detection points are collected in the neighborhood of the second inflection point as target points.

6. The method according to claim 5, characterized in that, Determining the third frequency based on the gradient change value includes: If the gradient change value is greater than the first gradient threshold, then the third frequency is determined to be the first value; If the gradient change value is greater than or equal to the second gradient threshold and less than or equal to the first gradient threshold, then the third frequency is determined to be the second value. If the gradient change value is less than the second gradient threshold, then the third frequency is determined to be the third value; the first value is greater than the second value; the second value is greater than the third value.

7. The method according to any one of claims 1-6, characterized in that, The step of constructing a pressure compensation table for calibrating the pressure sensor based on the first candidate points and the second candidate points outside the neighborhood of the target point and the second inflection point includes: In the neighborhood of the second inflection point, linear interpolation is performed between two adjacent sampling points to obtain new sampling points; the sampling points include the first candidate point, the second candidate point, and the endpoints of the neighborhood of the second inflection point; The sampling point and the target point are written into the pressure compensation table used to calibrate the pressure sensor.

8. An elevator positioning method, characterized in that, Pressure sensors are installed at both the ends of the elevator car and the hoistway. These pressure sensors are configured with a pressure compensation table constructed according to any one of claims 1-7. The method includes: For each of the aforementioned barometric pressure sensors, the barometric pressure value and the temperature value of the environment in which the barometric pressure sensor is located are collected; For each of the aforementioned pressure sensors, the pressure value is calibrated according to the pressure compensation value corresponding to the temperature value in the pressure compensation table configured for the pressure sensors; If calibration is completed, the car is positioned based on the difference between the air pressure value corresponding to the car and the air pressure value corresponding to the end of the hoistway.

9. A computer device, characterized in that, include: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the calibration of the barometric pressure sensor as described in any one of claims 1-7, or the elevator positioning method as described in claim 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program performs the calibration of the barometric pressure sensor as described in any one of claims 1-7, or the elevator positioning method as described in claim 8.

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