Electronic scale with dynamic compensation function

Abstract

The invention discloses an electronic scale with a dynamic compensation function, and aims to improve the weighing precision and stability, the electronic scale comprises a pressure sensor module, a dynamic compensation controller and a communication module, the pressure sensor employs an MEMS technology, and supports a 0-1000g measuring range; the dynamic compensation controller is internally provided with a temperature and vibration compensation algorithm, the weighing stability is ensured by collecting temperature and vibration data in real time and dynamically adjusting output signals of the sensor, the controller supports an automatic calibration mode, calibration is automatically conducted according to different weights, calibration data are stored, and the sensor module and the controller are connected through a four-core shielding wire. The controller and the communication module are integrated on the main control board, in addition, the controller supports multi-device ID management and Bluetooth wireless calibration, the long-term stability and high precision of the system are guaranteed, the relation between sensor output signals and the weight is optimized through linear regression and the least square method, it is guaranteed that the weighing result is accurate, and the weighing accuracy is improved. The electronic scale is widely applicable to industrial and precise weighing requirements.

Description

Technical Field

[0001] The present invention relates to an electronic scale with a dynamic compensation function. Background Art

[0002] With the wide application of electronic scales in various industries, especially in scenarios with high-precision requirements such as laboratories and the pharmaceutical industry, accurate weighing and stable performance have become particularly important. Currently, most electronic scales on the market adopt traditional static calibration methods. The static calibration method usually relies on fixed weights to manually calibrate the zero point and linear parameters of the electronic scale. This process requires manually placing multiple weights and relying on manual data recording to ensure the accuracy of the weighing result.

[0003] For electronic scales represented by the resistance strain gauge technology, although widely used in commercial, industrial and other fields, its calibration process still has significant drawbacks. Specifically, the traditional static calibration method faces the following problems:

[0004] Low calibration efficiency: The static calibration process usually requires multiple weight replacements, and manual data recording and processing are also required after each weight replacement. Since the weight of each weight needs to be measured and corrected multiple times, the operation is cumbersome and consumes a large amount of time, seriously affecting the calibration efficiency.

[0005] Poor anti-interference ability: Factors such as environmental temperature, humidity changes, and external mechanical vibrations will affect the measurement accuracy of the electronic scale. Since the traditional static calibration method fails to fully consider the impact of these dynamic changes on the weighing result, in actual applications, the anti-interference ability of the electronic scale is poor and it is easily affected by the external environment, resulting in weighing errors.

[0006] Lack of dynamic compensation: The current calibration method cannot real-time correct the weighing errors caused by temperature fluctuations, mechanical vibrations or pressure changes. Especially in laboratories or the pharmaceutical industry with high-precision requirements, it cannot meet the demand for dynamic compensation. This means that the electronic scale cannot automatically calibrate according to real-time pressure fluctuations or environmental changes, affecting the stability and accuracy of the weighing result. Summary of the Invention

[0007] The purpose of the present invention is to provide an electronic scale with a dynamic compensation function, which can solve problems such as low efficiency, poor anti-interference ability and lack of dynamic compensation, so as to meet the needs of high-precision application scenarios such as modern industry and laboratories.

[0008] The technical solution adopted by the present invention to solve its technical problems is:

[0009] An electronic scale with a dynamic compensation function, comprising:

[0010] A pressure sensor module, using a MEMS pressure sensor, supporting a range of 0 - 1000g;

[0011] Dynamic compensation controller, with built-in temperature and vibration compensation algorithms, collects temperature and vibration data in real time, adjusts sensor output signals, and ensures weighing stability;

[0012] Communication module, supporting RS-485 protocol, for real-time interaction with the gateway;

[0013] The pressure sensor module is connected to the dynamic compensation controller via a 4-core shielded cable, and the controller and communication module are integrated into the main control board;

[0014] The controller automatically calibrates according to the weight of different weights in an automatic calibration mode and stores the calibration data;

[0015] The dynamic compensation controller dynamically adjusts the output signal of the pressure sensor according to the temperature and vibration data collected in real time.

[0016] Preferably, the dynamic compensation algorithm formula of the dynamic compensation controller is:

[0017] W out =W raw +K t ΔT+K v ΔV

[0018] Where Wout is the output weight, Wraw is the raw sensor reading, Kt is the temperature compensation coefficient, Kv is the vibration compensation coefficient, ΔT is the temperature change, and ΔV is the vibration change.

[0019] Preferably, the calibration mode includes:

[0020] Empty the weighing pan and start calibration mode;

[0021] A 500g weight is placed, and the controller automatically recognizes it and starts a 10-second countdown for calibration;

[0022] Replace the 1000g weight and repeat the calibration steps;

[0023] Calibration data is encrypted and stored in non-volatile memory.

[0024] Preferably, the controller supports management of 255 device IDs and is adapted to Internet of Things scenarios.

[0025] Preferably, the wireless calibration replaces RS-485 communication with a Bluetooth module and adds a power consumption management unit.

[0026] Preferably, the controller adopts a multi-sensor redundancy design and is additionally provided with a spare pressure sensor.

[0027] Preferably, the automated calibration process includes a multi-weight adaptive recognition technology that automatically identifies different weights and performs automatic calibration according to the weight of the weights, as follows:

[0028] Read the output signals of multiple weights with known weights through the sensor;

[0029] Use the linear regression algorithm to calculate the relationship between the sensor output signal and the actual weight of the weight, and obtain the calibration coefficient of the sensor;

[0030] Correct the sensor output signal according to the calibration coefficient to obtain the final weighing result;

[0031] Automatically identify different weights, and ensure accurate weight readings corresponding to different weights through multiple readings and calibrations;

[0032] During the calibration process, optimize the calibration coefficient by the least squares method to minimize the error between the sensor reading and the actual weight.

[0033] Preferably, the calibration coefficient includes a proportional coefficient a and an offset b, which are obtained by solving the following equations by the least squares method:

[0034]

[0035] Where Ri is the sensor reading during the i-th weight calibration, and Mi is the actual weight of the weight used in the i-th time.

[0036] Preferably, the calibration coefficients a and b are used to correct the sensor output signal R to obtain the accurate weight Mcal of the weight, and this correction process is realized by the following formula:

[0037]

[0038] The beneficial effects of the present invention are:

[0039] The automated calibration process reduces manual intervention and optimizes the entire calibration process. Through automated data collection and processing, the calibration time is significantly shortened, the work efficiency can be improved, and the calibration time is shortened to 50% of the traditional method. For application scenarios with high-frequency use of electronic scales, such as industrial production and laboratory environments, it can greatly save time and labor costs, and at the same time improve the overall efficiency of production and testing.

[0040] The introduced dynamic compensation algorithm can monitor and correct the weighing errors caused by environmental factors (such as temperature fluctuations, mechanical vibrations, etc.) in real time, thus effectively reducing the impact of environmental interference. Through real-time dynamic adjustment, the weighing error of the electronic scale can be controlled within ±0.5g. Compared with the ±1g of the traditional solution, the accuracy is nearly doubled. This makes the application of the electronic scale more reliable in industries with high-precision requirements (such as laboratory research, pharmaceutical industry, etc.), meeting the needs of high-precision weighing.

[0041] This solution supports multi-device ID management (1 to 255), can flexibly manage multiple electronic scale devices, and can be widely applied in the Internet of Things (IoT) environment. The networking and centralized management of devices provide enterprises with a more efficient way of data collection and monitoring, facilitating the unified management and remote control across regions and multiple devices, greatly enhancing the scalability and adaptability of the system, and being suitable for large-scale deployment and digital transformation requirements. Brief Description of the Drawings

[0042] Figure 1 It is a schematic internal structure diagram of an electronic scale with a dynamic compensation function according to the present invention;

[0043] Figure 2 It is a schematic external structure diagram of an electronic scale with a dynamic compensation function according to the present invention. Specific Implementation Method

[0045] The principles and features of the present invention will be described below in conjunction with the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention. In the following paragraphs, the present invention will be described more specifically by way of example with reference to the accompanying drawings. The advantages and features of the present invention will be clearer according to the following description and the claims. It should be noted that the accompanying drawings are all in a very simplified form and use non-precise scales, only for the purpose of facilitating and clearly assisting in explaining the purpose of the embodiments of the present invention.

[0046] In the description of the present invention, it should be understood that the orientation or positional relationships indicated by the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", etc. are based on the orientation or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation on the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first", "second", etc. may explicitly or implicitly include one or more of such features. In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, the terms "mounted", "connected", "coupled" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be directly connected, or indirectly connected through an intermediate medium, and it may be the communication inside two elements.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this invention belongs. The terms used in the description of the present invention herein are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. Embodiment

[0048] Refer to Figure 1-2 As shown, an electronic scale with a dynamic compensation function includes:

[0049] A pressure sensor module 1, using a MEMS pressure sensor, supporting a range of 0 - 1000 g;

[0050] A dynamic compensation controller 2, built - in with temperature and vibration compensation algorithms, collecting temperature and vibration data in real - time, adjusting the output signal of the sensor to ensure weighing stability;

[0051] A communication module 3, supporting the RS - 485 protocol, for real - time interaction with the gateway;

[0052] The pressure sensor module 1 and the dynamic compensation controller 2 are connected by a 4 - core shielded wire 4, and the controller and the communication module 3 are integrated on the main control board;

[0053] The controller automatically calibrates according to the weights of different weights through an automatic calibration mode and stores the calibration data;

[0054] The dynamic compensation controller 2 dynamically adjusts the output signal of the pressure sensor according to the temperature and vibration data collected in real - time.

[0055] The built-in temperature and vibration compensation algorithms monitor environmental changes in real time and automatically adjust the output signal of the sensor. In this way, even in different working environments (such as temperature changes and vibration interference), the influence of environmental factors on the weighing result can be effectively reduced, ensuring higher weighing accuracy and stability, especially outstanding in applications with high-precision requirements.

[0056] The controller automatically calibrates according to the weights of different weights through the automatic calibration mode and stores the calibration data. This function reduces manual operation and errors, avoids the instability and errors brought by manual calibration, and ensures the accuracy and reliability during the long-term use of the device, especially suitable for occasions that require frequent calibration.

[0057] The built-in module supporting the RS-485 communication protocol enables the electronic scale to interact and transmit data with other devices in real time through the gateway. This provides convenience for the remote monitoring and management of the system. Especially in industrial environments, it can realize the centralized control of multiple devices and real-time data analysis, improving the networking ability of the device and the scalability of the system.

[0058] The dynamic compensation algorithm formula of the dynamic compensation controller 2 is as follows:

[0059] W out = W raw + K t ·ΔT + K v ·ΔV

[0060] Where, Wout is the output weight, Wraw is the original sensor reading, Kt is the temperature compensation coefficient, Kv is the vibration compensation coefficient, ΔT is the temperature change, and ΔV is the vibration change.

[0061] Through the dynamic compensation algorithm, the temperature change (ΔT) and vibration change (ΔV) are collected in real time, and the original sensor reading (Wraw) is adjusted according to the temperature compensation coefficient (Kt) and vibration compensation coefficient (Kv). This enables the electronic scale to automatically correct the output weight (Wout) according to environmental changes, greatly reducing the influence of environmental factors (such as temperature fluctuations and vibration interference) on the weighing result and ensuring a more stable and accurate weighing.

[0062] This algorithm can automatically adapt to different working environments. Whether it is rapid temperature changes or fluctuations in vibration interference, it dynamically adjusts the output signal of the sensor. This means that the scale can maintain high accuracy and stability in various complex environments, with stronger adaptability, especially suitable for applications in dynamic or harsh environments, such as factory workshops, during transportation, or laboratory environments.

[0063] Through compensation for temperature and vibration, the system can reduce errors caused by environmental fluctuations, and maintain stable weighing accuracy during long-term use. This reduces the accumulation of weighing errors caused by environmental factors, enables the device to maintain high accuracy for a longer time, reduces the maintenance frequency, improves the user experience and the long-term reliability of the device.

[0064] The calibration mode includes:

[0065] Empty the weighing pan and start the calibration mode;

[0066] Place a 500g weight, and the controller automatically identifies and starts a 10-second countdown for calibration;

[0067] Replace the 1000g weight and repeat the calibration steps;

[0068] The calibration data is encrypted and stored in the non-volatile memory.

[0069] This solution reduces manual intervention by automatically identifying the weight and starting the countdown for calibration. The user only needs to empty the weighing pan and place the standard weight, avoiding possible errors or improper operations during manual calibration, and ensuring the accuracy and efficiency of the calibration process.

[0070] By using weights of different weights (such as 500g and 1000g), the system performs multi-point calibration. This method can effectively improve the overall accuracy of the weighing system, because it not only calibrates at one weight point, but also covers errors under different load conditions, ensuring that the electronic scale can maintain high accuracy within different weight ranges.

[0071] The calibration data is encrypted and stored in the non-volatile memory, which ensures the security and long-term reliability of the data. Even after a power outage or system restart, the calibration data will not be lost, ensuring the continuous accuracy of the device and preventing the risk of malicious tampering or data loss, which is suitable for application environments that require high security.

[0072] The controller supports the management of 255 device IDs and is adapted to the Internet of Things scenario. The wireless calibration replaces the RS-485 communication through a Bluetooth module and adds a power consumption management unit. The controller adopts a multi-sensor redundancy design and adds a spare pressure sensor.

[0073] Supporting the management of up to 255 device IDs and being adapted to the Internet of Things scenario enables the system to achieve centralized management and remote monitoring in the case of large-scale deployment. Through Internet of Things technology, the status, calibration information, fault diagnosis, etc. of the device can be uploaded to the cloud in real time, facilitating data analysis, fault warning and remote maintenance, and greatly improving the operation efficiency and management convenience.

[0074] Replacing the traditional RS-485 communication with a Bluetooth module simplifies the device connection and calibration process, making calibration more flexible and convenient, and avoiding the limitations of traditional wired connections. In addition, the added power consumption management unit can effectively control the energy consumption of the system, extend the service life of the device, especially suitable for the Internet of Things environment that requires long-term operation and is sensitive to power consumption, reducing maintenance costs and energy consumption.

[0075] By adopting a multi-sensor redundancy design and adding a spare pressure sensor, the system has higher fault tolerance and reliability. When one sensor fails or shows deviation, the spare sensor can immediately take over the work to ensure the continuous operation of the system without affecting the weighing accuracy and the normal operation of the device. This design improves the stability of the system, especially suitable for critical fields or application scenarios with long-term operation, such as industrial production, warehousing and logistics, etc.

[0076] The automated calibration process includes multi-weight adaptive recognition technology, which automatically identifies different weights and performs automatic calibration according to the weight of the weights, specifically as follows:

[0077] Read the output signals of multiple weights with known weights through the sensor;

[0078] Use the linear regression algorithm to calculate the relationship between the sensor output signal and the actual weight of the weight to obtain the calibration coefficient of the sensor;

[0079] Correct the sensor output signal according to the calibration coefficient to obtain the final weighing result;

[0080] Automatically identify different weights. Through multiple readings and calibrations, ensure that the weight readings corresponding to different weights are accurate;

[0081] During the calibration process, optimize the calibration coefficient through the least squares method to minimize the error between the sensor reading and the actual weight.

[0082] Through the multi-weight adaptive recognition technology, the system can automatically identify different weights and perform automatic calibration according to their weights, avoiding manual intervention and human errors. Using the linear regression algorithm to calculate the relationship between the sensor output signal and the actual weight of the weight can accurately obtain the calibration coefficient. Such an automated calibration process not only improves the calibration efficiency but also ensures the accuracy of the weighing result, reducing errors in manual operations.

[0083] During the calibration process, use the least squares method to optimize the calibration coefficient to minimize the error between the sensor reading and the actual weight. The least squares method can dynamically adjust and optimize the calibration coefficient through multiple readings and calibrations to ensure that the system's response to different weights is always accurate. This optimization method can greatly improve the stability and accuracy of the system and is applicable to various changing environments and application scenarios.

[0084] By reading the output signals of multiple weights with known weights and performing linear regression, the system can adapt to the characteristics of different weights and adjust the calibration coefficient of the sensor in real time. This makes the system more adaptable and able to maintain high-precision weighing results under different conditions (such as temperature and humidity changes). The automated calibration process also improves the long-term reliability of the system, ensuring the continuous accuracy of the equipment after long-term use.

[0085] The calibration coefficient includes a proportional coefficient a and an offset b, which are obtained by solving the following equations using the least squares method:

[0086]

[0087] where Ri is the sensor reading during the i-th weight calibration, and Mi is the actual weight of the weight used in the i-th time.

[0088] The least squares method minimizes the error between the sensor reading and the actual weight of the weight by optimizing the calibration coefficient. This method can comprehensively consider the deviations of all data points at multiple calibration points to obtain the most suitable proportional coefficient and offset, thereby improving the accuracy of the calibration result. It is particularly suitable for application scenarios that require high-precision weighing, such as laboratories, industrial production, and quality control.

[0089] The scheme of solving the calibration coefficient by the least squares method has strong adaptability. Whether it is the long-term drift of the sensor or different weight ranges of the weights, the calibration coefficient can be updated through multiple calibrations to adapt to environmental changes or equipment aging. This enables the system to maintain high stability and reliability during long-term use.

[0090] Using the least squares method can automatically solve the proportional coefficient a and the offset b, reduce manual intervention, and optimize the calibration process through algorithms. This makes the calibration process more efficient and automated, reduces the complexity and error of manual operations, and improves the operation convenience and maintenance efficiency of the equipment.

[0091] The calibration coefficients a and b are used to correct the sensor output signal R to obtain the accurate weight Mcal of the weight. This correction process is achieved through the following formula:

[0092]

[0093] By using the calibration coefficients a and b, the output signal of the sensor can be effectively corrected, eliminating the errors that the sensor may generate. This makes the sensor reading more accurate, ensuring that the weighing result reflects the actual weight and avoiding errors caused by the deviation of the sensor itself, which is crucial especially for high-precision weighing requirements.

[0094] The calibration coefficients a and b are dynamically calculated by the least squares method based on the actual weight of the weights and can automatically adapt to changes during the use of the device (such as sensor drift, environmental factor changes, etc.). This correction process can maintain long-term stability, reduce the impact of device aging or environmental factors on the weighing accuracy, and ensure reliability over a long period of time.

[0095] This correction process is automatically completed based on the formula, reducing manual intervention and achieving fully automated calibration. Users only need to perform preliminary calibration and do not need to repeatedly calibrate, thus improving the efficiency and operational simplicity of the system. Especially in fields such as industry and scientific research, this automated correction greatly saves time and labor costs.

[0096] The above embodiments of the present invention do not limit the protection scope of the present invention. The implementation manners of the present invention are not limited thereto. All kinds of modifications, substitutions or changes made to the above structure of the present invention according to the above content of the present invention, in accordance with the common general knowledge and customary means in the art, without departing from the above basic technical idea of the present invention, shall fall within the protection scope of the present invention.

Claims

1. An electronic scale with dynamic compensation function, characterized in that, It includes: A pressure sensor module that uses a MEMS pressure sensor and supports a measurement range of 0 - 1000g; A dynamic compensation controller that incorporates temperature and vibration compensation algorithms, real - time collects temperature and vibration data, and adjusts the sensor output signal to ensure weighing stability; A communication module that supports the RS - 485 protocol and is used for real - time interaction with the gateway; The pressure sensor module is connected to the dynamic compensation controller through a 4 - core shielded wire, and the controller and the communication module are integrated on the main control board; The controller automatically calibrates according to the weights of different weights through the automatic calibration mode and stores the calibration data; The dynamic compensation controller dynamically adjusts the output signal of the pressure sensor according to the real - time collected temperature and vibration data.

2. The electronic scale with dynamic compensation function according to claim 1, wherein, The dynamic compensation algorithm formula of the dynamic compensation controller is: W out = W raw + K t ·ΔT + K v ·ΔV Where, Wout is the output weight, Wraw is the original sensor reading, Kt is the temperature compensation coefficient, Kv is the vibration compensation coefficient, ΔT is the temperature change, and ΔV is the vibration change.

3. The electronic scale with dynamic compensation function according to claim 2, characterized in that, The calibration mode includes: Empty the weighing pan and start the calibration mode; Place a 500g weight, and the controller automatically identifies and starts a 10 - second countdown for calibration; Replace the 1000g weight and repeat the calibration step; The calibration data is encrypted and stored in the non - volatile memory.

4. The electronic scale with dynamic compensation function according to claim 3, characterized in that, The controller supports the management of 255 device IDs and is adapted to the Internet of Things scenario.

5. The electronic scale with dynamic compensation function according to claim 4, characterized in that, The wireless calibration replaces the RS - 485 communication through a Bluetooth module and adds a power consumption management unit.

6. The electronic scale with dynamic compensation function according to claim 5, wherein, The controller adopts a multi - sensor redundancy design and is equipped with a spare pressure sensor.

7. The electronic scale with dynamic compensation function according to claim 3, characterized in that, The automated calibration process includes a multi - weight adaptive identification technology that automatically identifies different weights and performs automatic calibration according to the weight of the weights. Specifically: Read the output signals of multiple weights with known weights through the sensor; Use the linear regression algorithm to calculate the relationship between the sensor output signal and the actual weight of the weight to obtain the calibration coefficient of the sensor; Correct the sensor output signal according to the calibration coefficient to obtain the final weighing result; Automatically identify different weights, and ensure accurate weight readings corresponding to different weights through multiple readings and calibrations; During the calibration process, optimize the calibration coefficient through the least - squares method to minimize the error between the sensor reading and the actual weight.

8. The electronic scale with dynamic compensation function according to claim 7, characterized in that, The calibration coefficient includes a proportional coefficient a and an offset b, which are obtained by solving the following equations through the least - squares method: Where, Ri is the sensor reading during the i - th weight calibration, and Mi is the actual weight of the weight used in the i - th time.

9. The electronic scale with dynamic compensation function according to claim 8, characterized in that, The calibration coefficients a and b are used to correct the sensor output signal R to obtain the accurate weight Mcal of the weight. This correction process is achieved through the following formula:

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