High-precision weighing system and calibration method

Abstract

The present application relates to the field of precision measurement technology, especially to a high-precision weighing system and calibration method, comprising: a main weighing channel comprising a resistance strain sensor and a first analog-to-digital converter; an inertial perception feedback unit rigidly attached to the fixed end of the sensor, used to establish an environmental reference frame; an active stress intervention unit attached to the non-strain region of the sensor elastomer; and a central fusion controller connected to the main weighing channel, the inertial perception feedback unit and the active stress intervention unit, respectively. The present application provides a high-precision weighing system and calibration method, which captures environmental vibrations and structural responses in real time through the inertial perception feedback unit, generates micro-vibrations or test pulses in cooperation with the active stress intervention unit, actively eliminates mechanical hysteresis, eliminates environmental interference with zero delay, and performs closed-loop self-checking of structural health, solving the problems of large physical zeroing dead zone, slow seismic response and inability to self-diagnose of traditional weighing systems.

Description

Technical Field

[0001] This invention belongs to the field of precision metrology technology, and in particular relates to a high-precision weighing system and calibration method. Background Technology

[0002] In the increasingly demanding fields of chemistry and medicine, such as modern precision manufacturing, high-end drug development, and advanced materials characterization, high-precision weighing systems are no longer just basic metrology tools, but have become a key factor affecting experimental repeatability, process consistency, and even product safety. Especially for the measurement of microgram or even submicrogram mass changes during analytical experiments such as trace compound synthesis, quantitative detection of biomacromolecules, and nanomaterial characterization, which directly reflect reaction yield, drug activity, and material properties, unprecedented challenges are posed to the high precision, rapid response, and long-term stability of weighing systems. Therefore, passive weighing sensors based on resistance strain gauges, due to their simple structure and controllable cost, have dominated the weighing sensor market for a long time. Their essence lies in the minute deformation of a metallic elastomer under force, relying on the strain resistance adhering to its surface to convert mechanical signals into electrical signals. This method was effective in meeting the measurement needs of conventional laboratories in static, clean, and undisturbed environments, derived under the assumption of linear material mechanical response and idealized environments.

[0003] However, when the precision requirements for manipulating substances in the chemical and pharmaceutical fields increase to the milligram or even microgram level, the aforementioned architecture suffers from inherent physical defects that are difficult to overcome. The lattice slip and dislocation superposition of the metallic elastomer during loading and unloading lead to residual stress and creep, resulting in significant hysteresis: the same load produces different output signals along the loading and unloading paths, and a "zero-load dead zone" appears near zero load. Furthermore, the mechanical interfaces within the sensor, such as bolt fasteners and fulcrum contact surfaces, exhibit static friction (stick-slip effect). With mass changes on the order of milligrams, static friction is sufficient to overcome the micro-displacement of the elastomer, causing the signal to be zero or jump, completely disrupting continuity and fidelity. Existing technologies attempt to alleviate the above problems through software compensation: for example, the patent with publication number CN113393525B uses visual recognition to correct the eccentricity error of an object, which only involves external geometric and physical properties and is powerless against physical nonlinearities originating from the metal elastomer itself and the internal mechanical structure; another example is the patent with publication number CN114397003B, which uses a three-stage zero-point correction. Although it can solve the drift problem in static conditions, it is also based on the complete stillness of the system. It uses low-pass filtering to suppress vibration, sacrificing response speed, and cannot detect the integrity of the sensor structure: when overload impact causes the initiation of microcracks, loosening of screws, or fatigue of the elastomer, the system may continue to output seemingly normal readings, but in fact the measurement benchmark has deviated, posing a highly concealed safety hazard.

[0004] Fundamentally, the aforementioned shortcomings stem from the fact that the weighing system design artificially treats the sensor as a single passive signal conversion device, rather than a complex mechanical-material coupling entity, neglecting its physical evolution during dynamic service. The high-precision scenarios in chemical and pharmaceutical applications demand zero tolerance for true signal accuracy, and black-box processing methods cannot meet this requirement. For example, in high-throughput drug screening, static friction causes initial mass lag or signal distortion in the weighing instrument after the addition of micro-liter liquids, thus misleading screening results; in nanocatalyst configuration, zero-point drift caused by material creep, without timely zeroing, cannot guarantee consistent load capacity across batches of products. More critically, the aforementioned methods cannot proactively perceive and intervene in the sensor's own "health condition," cannot provide early warnings of performance degradation, and cannot actively release residual stress or break static friction through physical means, thus failing to restore the system's inherent sensitivity. Therefore, how to break through the physical constraints of traditional passive weighing architecture and build an intelligent weighing system that can actively manage mechanical state, diagnose structural health in real time, and maintain high-fidelity output under dynamic disturbances has become a core technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art, solve or at least alleviate a series of technical problems in the prior art, such as inaccurate zeroing caused by sensor physical hysteresis, reading delay caused by filtering algorithm, and lack of self-checking capability of mechanical structure health, and provide a high-precision weighing system and calibration method.

[0006] To achieve the above objectives, the present invention provides the following technical solution: In a first aspect, this application provides a calibration method and a high-precision weighing system, the system comprising: The main weighing channel includes a resistance strain gauge sensor, a signal conditioning circuit, and a first analog-to-digital converter, used to acquire raw weighing data containing gravity signals and environmental interference; the inertial sensing feedback unit includes a high-sensitivity MEMS accelerometer, rigidly mounted on the fixed base or under the elastic body of the resistance strain gauge sensor, used to construct an environmental reference frame and capture the tilt angle of gravity direction and environmental vibration waveforms in real time. The active stress intervention unit includes a piezoelectric actuator, which is attached to the non-strained region of the elastic body of the resistive strain sensor and configured to generate micron-level high-frequency mechanical waves or single impact pulses in a controlled manner. The central fusion controller is configured to run multi-task parallel logic, synchronously collect data from the main weighing channel and the inertial sensing feedback unit, and dynamically generate drive signals based on the current system state to control the vibration frequency and waveform of the active stress intervention unit, forming a sensing-motion mutual feedback closed-loop control.

[0007] By setting up an inertial sensing feedback unit and an active stress intervention unit, a "dual-dimensional sensing-active control" hardware architecture was constructed, solving the problem of physical hysteresis that passive measurement cannot overcome in existing technologies. Through a central fusion controller running multi-task parallel logic, closed-loop control from environmental fingerprint extraction and absolute zero-point reconstruction to dynamic seismic resistance was achieved.

[0008] The central fusion controller incorporates an environmental fingerprint extraction and system self-test module. When the system is powered on or idle, it drives the active stress intervention unit to emit test pulses. Simultaneously, the inertial sensing feedback unit captures the waveform of this pulse propagating on the sensor's mechanical beam. The amplitude of the captured waveform is compared with a preset structural health fingerprint. If the waveform amplitude attenuation exceeds a preset threshold, it is determined that the mechanical structure is loose or has abnormal damping. This "tapping-listening" mechanism enables real-time diagnosis of the sensor's structural health.

[0009] The central fusion controller contains an absolute zero-point reconstruction module. Upon receiving a zeroing command, it drives the active stress intervention unit to generate high-frequency damped oscillation waves with decreasing amplitude. This vibration energy overcomes the residual stress in the sensor's elastomer lattice and the static friction at mechanical connections. After the inertial sensing feedback unit confirms the dissipation of aftershock energy, it captures data from the main weighing channel as the physical true zero point. Compared to traditional zeroing algorithms, this method eliminates mechanical hysteresis at the physical level, significantly improving the accuracy of micro-weighing.

[0010] Preferably, the central fusion controller includes a dynamic weighting and environmental interference removal module. This module establishes a ground vibration transfer function, converts the vertical axis acceleration data collected by the inertial sensing feedback unit into an equivalent spurious weight value, and performs differential subtraction in real-time on the raw data of the main weighing channel. This method eliminates the need for high-order low-pass filtering and directly removes environmental vibration interference without delay, resolving the conflict between stability and response speed.

[0011] Preferably, the system further includes dead zone wake-up logic. When the reading of the main weighing channel remains unchanged for a long time, but the inertial sensing feedback unit detects a slight tilt or airflow disturbance, it determines that the system has entered the mechanical dead zone. Then, it drives the active stress intervention unit to generate a subthreshold micro-vibration that is inaudible to the human ear, converting static friction into dynamic friction to update the high-precision reading, effectively preventing small weight changes from being masked by static friction.

[0012] Secondly, this application provides a calibration method using the aforementioned high-precision weighing system, comprising the following steps: Step S1: Environmental fingerprint extraction and system self-test. An environmental vibration baseline is established through the inertial sensing feedback unit, and a piezoelectric-inertial loop is used to perform a structural integrity self-test. Step S2: Based on the reconstruction of the absolute zero point by active stress release, the mechanical hysteresis is cleaned up by micro-vibration sequence to obtain the physical true zero point; Step S3: Dynamic weighting and environmental interference elimination, distinguishing between impact and normal loading based on the nature of the loading event, and performing real-time differential seismic resistance; Step S4: Abnormal state circuit breaking and protection. When continuous and severe non-gravity direction vibration is detected, the reading is locked and the intervention is stopped.

[0013] Preferably, step S1 includes: The inertial sensing feedback unit collects high-frequency environmental triaxial acceleration and statistically analyzes the vibration background noise; The central fusion controller drives the active stress intervention unit to emit extremely short test pulses; The inertial sensing feedback unit synchronously captures the conducted waveform. If the waveform amplitude is lower than the preset value, it is judged as a mechanical fault and an alarm is triggered.

[0014] Preferably, step S2 includes: During the zeroing operation, the active stress intervention unit is triggered to generate a decaying oscillation wave with a frequency that decreases from high to low. The inertial sensing feedback unit monitors the amplitude in real time, and the closed-loop control of the driving voltage ensures that the vibration intensity overcomes the static friction force without causing displacement. At the moment the vibration stops and the aftershock dissipates, the latched main weighing channel data is written to the zero-point register.

[0015] Preferably, step S3 includes: When the reading of the main weighing channel changes abruptly, the inertial sensing feedback unit analyzes the Z-axis acceleration; If an external vibration that is out of sync with the reading change is detected, the interference component is calculated based on the vibration transfer function and subtracted in real time. If a reading deadlock is detected but there is a slight disturbance in the environment, a covert micro-jitter update of the reading is triggered.

[0016] Preferably, in step S4, when the inertial sensing feedback unit detects that the environmental vibration exceeds the safety threshold, it forcibly prohibits the active stress release action in step S2 to prevent incorrect zero-point calibration on unstable foundations and maintains the display of the last stable reading until the environment recovers.

[0017] The steps are nested within each other. An environmental baseline is established through the inertial sensing feedback unit to guide the actions of the active stress intervention unit and verify the intervention effect in real time, forming a tight logical closed loop. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall hardware architecture of the system of the present invention; Figure 2 This is a schematic diagram illustrating the principle of active stress relief to eliminate mechanical hysteresis in this invention. Figure 3 This is a flow diagram of the real-time anti-seismic logic signal based on inertial differential in this invention. Figure 4 This is a waveform comparison diagram of the structural health self-check of the present invention; Figure 5 This is a logical relationship diagram of each step in the calibration method of the present invention. Detailed Implementation

[0019] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention. Example

[0021] This embodiment discloses a high-precision weighing system and calibration method, such as Figure 1 As shown, the high-precision weighing system mainly consists of four core parts: the main weighing channel, the inertial sensing feedback unit, the active stress intervention unit, and the central fusion controller. The parts are connected by electrical connections to achieve signal interaction and coordinated control.

[0022] Specifically, the main weighing channel forms the foundation for precision metrology. This channel includes a resistance strain gauge sensor, a signal conditioning circuit, and a first analog-to-digital converter. The resistance strain gauge sensor employs a full-bridge Wheatstone bridge structure, with its elastomer preferably made of age-treated aerospace-grade aluminum alloy or precipitation-hardened stainless steel to ensure excellent elastic aftereffect characteristics. The bridge consists of four precision metal foil strain gauges (R1, R2, R3, R4), which are respectively attached to the stress-sensitive areas of the elastomer to sense minute deformations caused by external loads. When a heavy object is placed on the weighing pan, the elastomer deforms, causing the bridge to lose balance and output a differential voltage signal at the millivolt (mV) level. The signal conditioning circuit is connected to the sensor's output. Its core is a low-noise, zero-drift instrumentation amplifier (Amplifier). This amplifier employs chopper stabilization technology to effectively suppress low-frequency 1 / f noise and temperature drift, amplifying the weak differential signal to the linear input range of the first analog-to-digital converter (ADC) (e.g., 0-2.5V or 0-5V). A first-order passive RC anti-aliasing filter is placed between the amplifier and the ADC to filter out high-frequency noise above the Nyquist frequency, preventing aliasing from contaminating the digital signal. The first ADC uses a high-resolution Sigma-Delta architecture with at least 24 bits and a sampling rate set between 1kHz and 4kHz to ensure high-precision quantization of the weight signal. To minimize power supply noise interference with the weak signal, the main weighing channel is powered by an independent ultra-low noise linear regulator (LDO), and the single-point grounding principle for analog ground (AGND) and digital ground (DGND) is strictly implemented on the PCB layout.

[0023] Specifically, the inertial feedback unit is a key sensing component that distinguishes this system from traditional weighing systems. Its function is to establish an environmental reference frame independent of the gravity signal. The core device of this unit is a high-bandwidth, high-sensitivity MEMS inertial measurement unit (IMU), or more specifically, a triaxial MEMS accelerometer. The accelerometer's range is set to ±2g to ±8g, its bandwidth is not less than 1kHz, and its noise floor density is preferably less than 25µg / √Hz. Rigid coupling in the mounting method is a prerequisite for the unit to function. In this embodiment, the inertial feedback unit is not simply attached to the PCB board, but is directly fixed to the metal mounting base of the resistance strain gauge sensor by screws, or directly attached to the non-strain surface of the sensor's elastic body using high-modulus epoxy resin. This rigid connection ensures that the MEMS accelerometer can capture mechanical vibration waveforms that are completely synchronized with the sensor, including low-frequency shaking transmitted from the foundation and the high-frequency modal response of the sensor beam itself, thereby ensuring the consistency of their phases and providing a precise physical basis for the subsequent differential cancellation algorithm. The inertial sensing feedback unit is connected to the central fusion controller via a high-speed SPI or I2C bus. Its real-time sampling rate is set to be higher than that of the main weighing channel (e.g., 8kHz or higher) in order to capture fleeting transient impact signals.

[0024] Specifically, the active stress intervention unit, acting as the system's actuator, endows the system with the ability to actively adjust its physical state. This unit includes a piezoelectric actuator and a high-voltage drive circuit. The piezoelectric actuator employs a PZT (lead zirconate titanate) piezoelectric ceramic sheet with a significant inverse piezoelectric effect, such as the PZT-5 or PZT-8 series materials. The installation position of the piezoelectric actuator is precisely calculated, attaching it to the neutral layer region on the side or the non-primary strain region at the end of the elastic body of the resistance strain gauge sensor. This layout design aims to ensure that the mechanical energy generated by the piezoelectric sheet can be effectively coupled into the elastic body structure, forming a propagating stress wave, while the stiffness intervention of the piezoelectric sheet does not alter the sensor's original sensitivity coefficient for weight measurement. The high-voltage drive circuit includes a digital-to-analog converter (DAC) and a high-voltage linear amplifier. Because piezoelectric ceramic sheets exhibit capacitive load characteristics, and generating effective mechanical deformation at the micrometer level typically requires a drive voltage of tens of volts, high-voltage amplifiers are designed to output voltage swings from ±30V to ±100V and have a sufficiently high slew rate to accurately track the high-frequency complex waveforms (such as damped sine waves, pulse waves, etc.) emitted by the central fusion controller.

[0025] Specifically, the central fusion controller is the core of the entire system's computation and control hub. This embodiment uses a high-performance microcontroller based on an ARM Cortex-M7 or DSP core, or a dual-core heterogeneous architecture of "MCU + FPGA". The MCU is responsible for top-level logic control, state machine management, human-machine interaction, and communication protocol stack; the FPGA or DSP coprocessor is responsible for low-level high-speed parallel data acquisition, FFT spectrum analysis, and real-time generation of piezoelectric drive waveforms. The controller integrates a direct memory access (DMA) controller to ensure that the transfer of main channel ADC data and inertial unit data does not consume CPU core resources, thus guaranteeing the real-time performance of the control loop. The central fusion controller runs multi-task parallel logic, including environmental fingerprint extraction logic, absolute zero-point reconstruction logic, dynamic anti-vibration logic, and dead-zone wake-up logic. The logic modules exchange status flags and data through shared memory.

[0026] Figure 1 This is a schematic diagram of the overall hardware architecture of the calibration method and high-precision weighing system in the embodiments of this application. Figure 1 The system's signal flow and control closed loop are demonstrated. External loads act on the sensor, generating the main channel signal; simultaneously, environmental vibrations act on the sensor base and are captured by the inertial unit. The central fusion controller receives both signals simultaneously. On one hand, it uses a differential algorithm to eliminate interference in the digital domain; on the other hand, it generates control commands based on the current state (such as a zeroing request). These commands drive the piezoelectric actuator via the drive circuit to physically intervene in the sensor (such as vibration cleaning). The effects of this intervention (such as aftershock attenuation) are again captured by the inertial unit and fed back to the controller, forming a complete "perception-decision-execution-feedback" closed loop.

[0027] In one specific embodiment, the environmental fingerprint extraction and system self-test module is configured to operate during the system power-on initialization phase or during prolonged idle periods. The module's workflow is as follows: First, the inertial sensing feedback unit initiates high-frequency continuous sampling (e.g., for 1 second) to collect triaxial acceleration data of the environment. The central fusion controller calculates the RMS value (root mean square value) of each axis and performs a Fast Fourier Transform (FFT) to obtain the spectral distribution, statistically determining the current "vibration background noise." If the detected vibration amplitude exceeds a preset safety threshold (e.g., exceeding 0.05g, which typically means the device is placed on an unstable table or is near heavy machinery), the system will set an "environmental instability flag" and automatically disable the high-precision measurement mode to prevent incorrect calibration parameters from being written. Next, a piezoelectric-inertial loop self-test ("knock-feedback" mechanism) is performed. The central fusion controller drives the active stress intervention unit to generate an extremely short (e.g., pulse width of 50μs to 200μs), large-amplitude single pulse signal. Due to the inverse piezoelectric effect, this electrical pulse is converted into a mechanical shock wave that propagates inside the metal beam of the sensor. Simultaneously, the inertial sensing feedback unit captures the stress wave response signal at the highest sampling rate (e.g., 20kHz). The controller extracts features from the captured time-domain waveform, including the initial peak amplitude, the damping ratio, and the main resonant frequency. These measured parameters are then compared with the "structural health fingerprint" stored in the non-volatile memory at the factory using normalized cross-correlation. If the initial peak amplitude decreases significantly relative to the reference value (e.g., below 80%), it usually indicates an abnormal increase in damping of the mechanical connection structure, potentially due to foreign object jamming or aging and softening of the protective adhesive. If the resonant frequency shifts significantly (e.g., more than 5%) or unexpected clutter peaks appear in the spectrum, it usually indicates a change in structural stiffness, potentially due to loose fixing screws or early fatigue microcracks in the elastomer. Once an abnormal structural health is determined, the system immediately issues an alarm signal via the display or communication interface and marks the data stream as "untrusted," thus achieving proactive health diagnosis at the sensor's mechanical level.

[0028] In one specific embodiment, the absolute zero-point reconstruction module is used to address the sensor's physical hysteresis problem. This module is triggered upon receiving a user's "zeroing" or "tare" command, or when the system determines that the zero-point drift exceeds the limit. Its core lies in the Hysteresis Cleaning Sequence. The central fusion controller uses Direct Digital Frequency Synthesis (DDS) technology to generate a specific set of digital waveform data, which drives the piezoelectric actuator via a DAC. This waveform is designed as a "variable frequency damped oscillation wave," specifically characterized by a frequency that starts near the sensor's first-order natural frequency (e.g., 300Hz), linearly or logarithmically scans to a low frequency (e.g., 10Hz), while the amplitude decays exponentially to zero over time. This physical process utilizes the principle of energy injection at the microscopic level: the high-frequency micro-vibrations generated by the piezoelectric actuator propagate within the elastic body, providing additional kinetic energy for dislocation slip in the metal lattice, helping them overcome the potential barrier and release residual internal stress caused by loading history. Simultaneously, at the macroscopic level, the vibration changes the contact state between the various mechanical connection surfaces of the sensor (such as threaded connections and the connection between the sensor and the weighing pan) from high-resistance static friction to low-resistance kinetic friction. Under kinetic friction, the elastic body can overcome frictional resistance, slip slightly, and rebound to the natural equilibrium position with the lowest energy (i.e., the true physical zero point). During this process, the inertial sensing feedback unit monitors the vibration amplitude at the sensor end in real time, and the controller dynamically adjusts the gain of the piezoelectric drive voltage through a PID algorithm to ensure that the vibration amplitude is just sufficient to overcome static friction (typically a micrometer-level displacement), but strictly controlled within a safe range, insufficient to cause macroscopic jumping of the entire weighing body or damage to the sensor. When the drive signal stops, the inertial unit continues to monitor the "aftershock" signal. Once it is confirmed that the aftershock energy has been completely dissipated (i.e., the acceleration reading returns to the background level), the controller immediately triggers the data latch of the main weighing channel ADC, writing the current reading into the zero-point register. The zero point obtained in this way is a "true zero point" after physical cleaning, rather than a "defective zero point" simply deducted by the traditional algorithm, thus completely eliminating the zero-point tracking error caused by mechanical hysteresis.

[0029] Figure 2 This is a schematic diagram illustrating the principle of active stress release to eliminate mechanical hysteresis in the embodiments of this application. Figure 2 This vividly illustrates the convergence process of the hysteresis loop after active micro-vibration intervention. The originally open hysteresis loop, after being subjected to an oscillating wave with decreasing amplitude, can quickly converge to the center of the origin along a spiral trajectory, intuitively demonstrating the effectiveness of physical cleaning.

[0030] In one specific embodiment, the dynamic weighting and environmental interference elimination module runs throughout the normal weighing cycle of the system, aiming to resolve the contradiction between filtering delay and reading stability. This module includes loading nature identification logic and real-time differential anti-vibration logic. First, when the reading of the main weighing channel changes abruptly (i.e., the first derivative exceeds a preset threshold), the system needs to determine whether this is a valid loading action by the user (such as placing an item) or an invalid impact from the external environment (such as tapping a table). The controller synchronously reads and analyzes the Z-axis acceleration signal of the inertial sensing feedback unit. If the main channel reading changes, but the Z-axis acceleration of the inertial unit remains stable or has only slight high-frequency noise, the system determines it as normal loading, and outputs the weight data normally. If the main channel reading changes at the same time, and the inertial unit detects a sharp acceleration spike (e.g., the peak value exceeds 1g), the system determines it as impact interference. At this time, the system immediately activates the overload protection logic, temporarily freezing the displayed value to prevent invalid data from causing control malfunctions. Second, under normal weighing or slight vibration environments, real-time differential anti-vibration is performed. The system pre-calibrated experimentally or through online adaptive learning to obtain the transfer function of "foundation vibration-sensor reading". or coupling coefficient Within each frame sampling period, the inertial unit collects the vertical vibration acceleration of the environment in real time. The controller calculates the equivalent spurious weight force generated on the sensor by the vibration based on the transfer function. Then, the controller performs a subtraction operation in the underlying data stream: .in, This is the sensor's raw, noisy reading. This is the corrected true weight. Since this compensation is based on direct cancellation of physical causes and involves algebraic operations on instantaneous values, it does not rely on long-term integration or low-pass filtering, thus exhibiting almost no phase delay. This allows the system to instantly output a stable true weight, even on a workbench with significant vibrations, much like on a precision marble table, greatly reducing settling time. This makes it particularly suitable for scenarios with extremely high speed requirements, such as dynamic checkweighing in assembly lines.

[0031] Figure 3 This is a flow diagram of the real-time anti-seismic logic signal based on inertial differential in the embodiments of this application. Figure 3 The diagram illustrates the parallel pipeline structure for signal processing. The upper part shows the signal path for the main weighing channel, while the lower part shows the signal path for the inertial unit; both converge at the "differential fusion node." The diagram clearly marks the conversion stage (transfer function module) from the acceleration signal to the equivalent signal, as well as the final subtraction node, demonstrating the technical approach for zero-delay interference immunity.

[0032] In one specific embodiment, the dead-zone wake-up module is specifically designed to address the "numerical deadlock" problem commonly encountered in high-precision weighing. In micro-weighing (such as chemical reagent titration), extremely small changes in weight occur (e.g., a drop of liquid is added), but due to the presence of static friction, the elastic body becomes "stuck," causing the sensor reading to remain unchanged, forming a dead zone. The module's determination logic is as follows: when the change in the main weighing channel reading is less than one division value over a period of time (e.g., 2 seconds), it is in a "static" state; however, simultaneously, the inertial sensing feedback unit detects minute tilt changes, airflow disturbances, or micro-vibrations of the base in the environment, and according to the physical model, the integral of these disturbances should theoretically cause a change in the reading. At this point, the system determines that the sensor is trapped in a "mechanical dead zone." The central fusion controller then activates a concealed micro-jitter mode. The controller drives the active stress intervention unit to generate a random vibration signal that is inaudible to the human ear, has an extremely high frequency, and whose amplitude is near the ADC quantization noise threshold. This micro-jitter utilizes the principle of stochastic resonance, not only breaking static friction and converting it into kinetic friction, enabling the elastic body to respond sensitively to minute changes in external force, but also injecting a suitable amount of noise energy into the system, allowing weak signals that were originally below the ADC detection threshold to "emerge" and be acquired. The micro-jitter lasts for an extremely short time (e.g., a few hundred milliseconds), and stops immediately once the main channel reading is updated (exiting the dead zone), thus significantly improving the system's resolution and ability to capture minute changes.

[0033] Furthermore, the parameter configuration module is responsible for dynamically adjusting the system's operating parameters. This module maintains a lookup table for optimized filter parameters. Although this system primarily relies on physical differential vibration damping, digital filters are still required in the extremely high frequency noise range. This lookup table records the optimal digital filter parameters (such as cutoff frequency and order) corresponding to different environmental vibration levels (determined by the vibration energy measured by the inertial unit). When the inertial unit detects a change in the environmental vibration frequency (e.g., from low-frequency shaking to high-frequency motor vibration), the parameter configuration module queries the lookup table based on the vibration characteristic code and dynamically adjusts the coefficients of the main channel digital filter to achieve the best balance between signal-to-noise ratio and response speed. For example, when the environment is relatively still, the filter bandwidth is widened to improve the response speed; when the environment is harsh, the bandwidth is narrowed to ensure that the readings do not jump.

[0034] In one specific embodiment, the system also includes an abnormal state fuse and protection mechanism. This mechanism operates independently of the main control loop as a highest-priority safety protection task. It continuously monitors the output of the inertial sensing feedback unit, focusing on the vibration components in non-gravity directions (such as the horizontal X and Y axes) and the drive current of the piezoelectric actuator. If continuous and severe non-gravity vibration is detected (e.g., earthquakes, drops during transportation, or violent shaking of the equipment by human intervention), or if an abnormal increase in the piezoelectric actuator circuit current is detected (indicating a possible short circuit or breakage of the piezoelectric element), the system will immediately trigger the fuse protection: First, the drive output of the piezoelectric actuator is cut off in hardware to prevent the system from entering a self-excited oscillation state and damaging the sensor or drive circuit; second, the current displayed reading is locked in software, and a red alarm icon flashes on the human-machine interface to prompt the user to check the equipment environment. After confirming that the environment has returned to calm (i.e., the inertial data has returned to the normal range) and remains so for several seconds, the system automatically restarts step S1 for self-testing, and only resumes normal measurement function after the self-test passes.

[0035] Furthermore, this embodiment can also be extended to distributed networking application scenarios. Large-scale industrial automated batching systems typically include multiple weighing nodes. The system of this application can form a distributed network via CAN bus, RS485, or industrial Ethernet. In this embodiment, the inertial sensing feedback unit of each node is not only used for its own seismic resistance but is also reused as a distributed "seismic wave sensor." When a node (e.g., a node near the entrance) detects strong ground vibrations (such as a forklift passing by), it can send a "vibration warning" signal to subsequent nodes via the network. Upon receiving the warning, subsequent nodes can initiate active seismic resistance logic in advance or pause high-precision measurements and maintain the current value within milliseconds before the arrival of the seismic wave, thereby forming a regionally collaborative anti-interference network and significantly improving the metering stability of the entire production line.

[0036] Furthermore, this embodiment can also incorporate temperature compensation technology. A high-precision digital temperature sensor (accuracy better than 0.05℃) is integrated near the resistance strain gauge sensor. The central fusion controller not only performs mechanical compensation based on inertial data, but also corrects the piezoelectric coefficient of the piezoelectric actuator by looking up a table based on the real-time acquired temperature data. The constants (variable with temperature) and the sensor's sensitivity coefficient (Young's modulus varies with temperature). Since both the piezoelectric effect and the elastic modulus are temperature-sensitive, introducing temperature-dimensional compensation ensures that the active stress intervention unit can produce a constant and accurate physical intervention effect over a wide temperature range (e.g., -10℃ to +40℃), achieving high-precision measurement in all weather conditions.

[0037] Figure 4 This is a waveform comparison diagram of the structural health self-check in the embodiments of this application. Figure 4The left side shows the standard response waveform received by the inertial unit when the system is in a healthy state, with a clear impact leading edge and an exponentially decaying tail. The right side shows the waveform under fault conditions; for example, when the sensor fixing screws are loose, obvious second harmonic oscillations appear in the waveform, and the decay rate slows down (damping decreases); when the elastic body has microcracks, the resonant frequency shifts. Through a visual comparison of waveform characteristics, the physical basis of the self-test logic is clearly illustrated.

[0038] Figure 5 This is a logical relationship diagram of each step of the calibration method in the embodiments of this application. Figure 5 The nested logic from S1 to S4 is described in detail using a flowchart. S1 environmental self-check is a prerequisite for S2 and S3; the S2 zeroing operation incorporates nested sub-loops of piezoelectric drive and inertial feedback; and S3 normal weighing involves the parallel execution of three sub-tasks: impact identification, differential vibration damping, and dead-zone wake-up. Each step is tightly coupled through status flags, forming a rigorous logical closed loop that ensures the system can make optimal control decisions under any operating condition.

[0039] Specifically, to achieve the above functions, the software architecture of the central fusion controller adopts a layered design. The bottom layer is the Hardware Abstraction Layer (HAL), responsible for driving peripherals such as ADC, DAC, IMU, and GPIO; the middle layer is the algorithm library, containing mathematical tools such as FFT transformation, PID control, FIR / IIR filtering, and matrix operations; the application layer implements the specific business logic state machines of S1-S4 mentioned above. To ensure real-time performance, core algorithms (such as multiply-accumulate operations for differential anti-vibration) are executed in interrupt service routines (ISRs), with their execution frequency synchronized with the ADC sampling rate (e.g., 1kHz); while slow tasks (such as temperature compensation and HMI refresh) run in the background main loop. The generation of piezoelectric drive waveforms adopts DMA (Direct Memory Access) mode, pre-calculating the waveform point matrix in memory, and triggering the DMA by a timer to automatically transfer the data to the DAC, thereby freeing up CPU resources for complex fusion algorithm calculations.

[0040] In summary, this specific implementation method, through innovative hardware architecture design—introducing an inertial sensing feedback unit as the "vestibule" and an active stress intervention unit as the "muscles," combined with the central fusion controller as the "brain"—constructs an intelligent weighing system with self-sensing, self-physical adjustment, and self-diagnosis capabilities. It does not rely on an ideal external environment but actively adapts to and overcomes environmental interference and material defects, fundamentally solving the pain points of traditional weighing technology such as lag, slow response, and sub-optimal operation, thus providing a completely new technological path for the field of precision metrology. The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0041] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A high-precision weighing system, characterized in that, It includes a main weighing channel, an inertial sensing feedback unit, an active stress intervention unit, and a central fusion controller; The main weighing channel includes a resistance strain gauge sensor, a signal conditioning circuit, and a first analog-to-digital converter, used to collect raw weighing data containing gravity signals and environmental interference. The inertial sensing feedback unit includes a high-sensitivity MEMS accelerometer, which is rigidly mounted on the fixed base or elastic body of the resistive strain sensor to construct an environmental reference frame and capture the tilt angle of gravity direction and environmental vibration waveforms in real time. The active stress intervention unit includes a piezoelectric actuator, which is attached to the non-strained region of the elastic body of the resistive strain sensor and configured to generate micron-level high-frequency mechanical waves or single impact pulses in a controlled manner. The central fusion controller is configured to run multi-task parallel logic, synchronously collect data from the main weighing channel and the inertial sensing feedback unit, and dynamically generate drive signals based on the current system state to control the vibration frequency and waveform of the active stress intervention unit, forming a sensing-motion mutual feedback closed-loop control.

2. The high-precision weighing system according to claim 1, characterized in that, The central fusion controller operates an environmental fingerprint extraction and system self-test module. The module is configured to drive the active stress intervention unit to emit a test pulse when the system is powered on or idle, and the inertial sensing feedback unit synchronously captures the transmitted waveform of the pulse on the sensor mechanical beam. The amplitude of the captured waveform is compared with the preset structural health fingerprint. If the waveform amplitude decay exceeds the preset threshold, it is determined that the mechanical structure is loose or the damping is abnormal.

3. The high-precision weighing system according to claim 1, characterized in that, The central fusion controller operates an absolute zero-point reconstruction module. When a zeroing command is received, the module drives the active stress intervention unit to generate a high-frequency damped oscillation wave with decreasing amplitude. The vibration energy is used to overcome the residual stress of the sensor's elastomer metal lattice and the static friction at the mechanical connection. After the inertial sensing feedback unit confirms the dissipation of aftershock energy, the data from the main weighing channel is captured as the physical true zero point.

4. The high-precision weighing system according to claim 1, characterized in that, The central fusion controller operates a dynamic weighting and environmental interference removal module. The module is configured to establish a foundation vibration transfer function, convert the vertical axis acceleration data collected by the inertial sensing feedback unit into an equivalent spurious weight value, and perform differential subtraction operation in real time on the original data of the main weighing channel to directly remove environmental vibration interference without the need for low-pass filtering delay.

5. The high-precision weighing system according to claim 4, characterized in that, The dynamic weighting and environmental interference elimination module also includes dead zone wake-up logic. When the reading of the main weighing channel remains unchanged for a long time, but the inertial sensing feedback unit detects a slight tilt or airflow disturbance, it determines that the system has entered the mechanical dead zone. Then, it drives the active stress intervention unit to generate a subthreshold micro-vibration that is inaudible to the human ear, converting static friction into dynamic friction to update the high-precision reading.

6. A calibration method using the high-precision weighing system as described in any one of claims 1-5, characterized in that, Includes the following steps: Step S1: Environmental fingerprint extraction and system self-test. An environmental vibration baseline is established through the inertial sensing feedback unit, and a piezoelectric-inertial loop is used to perform a structural integrity self-test. Step S2: Based on the reconstruction of the absolute zero point by active stress release, the mechanical hysteresis is cleaned up by micro-vibration sequence to obtain the physical true zero point; Step S3: Dynamic weighting and environmental interference elimination, distinguishing between impact and normal loading based on the nature of the loading event, and performing real-time differential seismic resistance; Step S4: Abnormal state circuit breaking and protection. When continuous and severe non-gravity direction vibration is detected, the reading is locked and the intervention is stopped.

7. The calibration method according to claim 6, characterized in that, Step S1 includes: The inertial sensing feedback unit collects environmental triaxial acceleration at high frequency and statistically analyzes the vibration background noise. The central fusion controller drives the active stress intervention unit to emit extremely short test pulses; The inertial sensing feedback unit synchronously captures the conducted waveform. If the waveform amplitude is lower than the preset value, it is judged as a mechanical fault and an alarm is triggered.

8. The calibration method according to claim 6, characterized in that, Step S2 includes: During the zeroing operation, the active stress intervention unit is triggered to generate a decaying oscillation wave with a frequency that decreases from high to low. The inertial sensing feedback unit monitors the amplitude in real time, and the closed-loop control of the driving voltage ensures that the vibration intensity overcomes the static friction force without causing displacement. At the moment the vibration stops and the aftershock dissipates, the latched main weighing channel data is written to the zero-point register.

9. The calibration method according to claim 6, characterized in that, Step S3 includes: When the reading of the main weighing channel changes abruptly, the inertial sensing feedback unit analyzes the Z-axis acceleration; If an external vibration that is out of sync with the reading change is detected, the interference component is calculated based on the vibration transfer function and subtracted in real time. If a reading deadlock is detected but there is a slight disturbance in the environment, a covert micro-jitter update of the reading is triggered.

10. The calibration method according to claim 6, characterized in that, In step S4, when the inertial sensing feedback unit detects that the environmental vibration exceeds the safety threshold, it forcibly prohibits the active stress release action in step S2 to prevent incorrect zero-point calibration on unstable foundations and maintains the display of the last stable reading until the environment recovers.

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