780results about "Weighing apparatus testing/calibration" patented technology

The invention relates to a body weight measuring method and device with automatic calibration and temperature compensation functions, and the method comprises the steps: synchronously obtaining the surface temperature and environment temperature data of a bearing structure through a temperature sensor array; calculating a current temperature difference value between the surface temperature and the environment temperature, generating a control signal when the current temperature difference value exceeds a material thermal deformation threshold value, and calculating a surface temperature change rate; selecting a compensation mode according to the compensation control signal and the surface temperature change rate, starting a compensation process based on a closed loop verification mechanism, and correcting the original weighing value according to a temperature-drift relational database to generate preliminary compensation data; when the calculated accumulated temperature impact value reaches a set threshold value, triggering a parameter self-updating operation to obtain final weighing data; and outputting final weighing data with temperature credibility rating to an interactive interface so as to solve the problems of error accumulation and manual intervention dependence caused by temperature fluctuation in a traditional scheme.

The invention relates to the technical field of data processing, and discloses a truck scale anomaly detection method, device and equipment and a storage medium, and the method comprises the steps: obtaining the operation state data and peripheral image data of a truck scale when a to-be-weighed vehicle drives onto the truck scale; processing the operation state data and the peripheral image data by using a preset target detection model, and performing cross validation and correlation analysis on a processing result to obtain a preliminary abnormality diagnosis result and a potential fault prediction result; and generating a target anomaly detection report according to the preliminary anomaly diagnosis result and the potential fault prediction result. And when the to-be-weighed vehicle is driven into the truck scale, the running state data and the peripheral image data are processed by using a preset target detection model, then cross validation and correlation analysis are performed, and a target anomaly detection report is generated. Abnormal conditions in the running process of the truck scale can be found more timely and accurately, a detailed basis is provided for subsequent maintenance and repair, and stable running of the truck scale is effectively guaranteed.

The invention relates to the technical field of weighing equipment detection, and discloses a detection output method, device and equipment for weighing equipment and a storage medium, and the method comprises the steps: carrying out the preprocessing and analog-to-digital conversion of original output signals of a plurality of weighing sensors in the weighing equipment, and obtaining synchronous digital signal data; bayesian multi-channel signal fusion and anomaly detection are carried out based on the synchronous digital signal data, and multi-channel fusion signal data and an anomaly detection identifier are obtained; performing inter-channel correlation analysis and adaptive weight distribution according to the abnormal detection identifier and the multi-channel fusion signal data to obtain a multi-channel weighted fusion result and a calibration compensation parameter; and carrying out real-time fault isolation and multi-channel working state identification on the multi-channel weighted fusion result based on the calibration compensation parameter, and generating a weighing detection result, the weight distribution can be automatically optimized according to the real-time working state and the signal quality of each weighing sensor channel, and the accuracy and the stability of the measurement of the weighing equipment are improved.

The invention relates to the technical field of industrial visual inspection and intelligent assembly, solves the technical problem that the assembly task cannot be completed while the defect and quality of a blade are detected in the prior art, and particularly relates to an aircraft engine blade detection method, system and equipment. Carrying out multi-dimensional data acquisition to obtain leaf data; analyzing the key size, the surface damage and the coating integrity of the blade according to the collected blade data, and identifying the size error and the surface defect of the blade; and after the weighing equipment is calibrated, the static weight is read, and compensation calculation is carried out in combination with environmental factors, so that whether the quality of the blade is within a qualified range or not is judged. According to the method, multiple processes and multiple numerical parameters are comprehensively considered, full-process and multi-numerical-parameter engine blade detection is achieved, and assembly accuracy is guaranteed. And meanwhile, an efficient and reliable solution is provided for the aeronautical manufacturing industry, and the overall assembly quality and efficiency are remarkably improved.

The invention relates to the technical field of error calibration, and discloses a sensor error calibration method, device and equipment and a storage medium, and the method comprises the steps: collecting the environment state information of a sensor, and calculating the partition calibration parameter of each sensor based on the environment state information; each sensor is divided into a plurality of dynamic calibration intervals based on the partition calibration parameters, each dynamic calibration interval comprises a plurality of error parameters, and the interval range of the adjacent dynamic calibration intervals can be dynamically adjusted through the difference value between the error parameters; calculating an error compensation value of each dynamic calibration interval according to the error parameters; generating calibration information based on the error compensation value, and inputting the calibration information into each dynamic calibration interval to obtain a target calibration interval; and compensating the real-time weighing data of the sensor according to the target calibration interval. The system can respond to the change of errors of a plurality of sensors in real time, ensures that each sensor can be effectively calibrated under different working conditions, and further improves the measurement precision.

The invention provides a remote maintenance and intelligent inspection early warning management method and system for a weight meter, and relates to the technical field of intelligent measurement and monitoring, and the method comprises the steps: arranging a multi-source sensor array on a weighing mechanism to collect detection data, carrying out the three-domain conjoint analysis through an edge calculation unit, and extracting multi-dimensional coupling features; the remote monitoring platform establishes a multi-scale damage evolution prediction model based on deep learning to realize the prediction of microscopic crack propagation and macroscopic fatigue damage; an intelligent material is adopted to realize self-adaptive active compensation, and prediction-compensation-evaluation-optimization closed-loop control is formed. The operation reliability and the metering precision of the weight meter can be improved, and the service life of equipment is prolonged.

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.

The invention provides a bulk material weighing method, system and device based on double sensors, and relates to the technical field of electronic scale verification, and the method comprises the steps: weighing a bulk material through double sensors, and obtaining an original weight signal corresponding to each sensor in the double sensors; performing preprocessing and scene filtering on each original weight signal to obtain effective weight data of each sensor on the bulk material; mutual correction analysis is carried out based on each effective weight data, and the data deviation state of the double sensors is judged; and according to the data deviation state, the final weight value of the bulk material is determined. According to the method, the problems of time difference, noise, sensor drifting and the like are effectively eliminated through the technical means of preprocessing, scene filtering, mutual correction analysis and the like, meanwhile, the consistency and the accuracy of data of the double sensors are ensured through mutual correction analysis, and finally, the precision and the stability of bulk material weighing are remarkably improved through comprehensive analysis and optimization processing.

The invention discloses a weight measuring system in a vehicle motion state and a control method thereof, and relates to the field of vehicle-mounted weighing, weight data are collected from a strain gauge sensor and a tilt angle sensor, and an algorithm processor is used for processing the weight data and compensating a dynamic effect; and fitting a neural network model by using a multi-section function, predicting a vehicle load measurement value by training the neural network model, and outputting the vehicle load measurement value in real time. The high precision of the neural network is reserved, the efficiency of the system is remarkably improved, delay is reduced, and the problem that a traditional system is inaccurate in measurement in a motion state is solved. According to the method, the neural network model is fitted through the multi-segment function, through approximation fitting, the calculation efficiency and the real-time performance are improved, meanwhile, the measurement accuracy is kept, powerful technical support is provided for application of the vehicle-mounted weighing system, delay is reduced, and the method is more suitable for the vehicle-mounted weighing system with the high real-time performance requirement.

The invention discloses a fault identification processing method and device based on an internet of things digital weighing system, and the method comprises the steps: a fault detection step: tracking and recording the weighing data and state of each sensor of the internet of things digital weighing system, and judging whether the sensors have faults or not; and an output replacement step: if a sensor fails, generating predicted weighing data according to the historical weighing data of the sensor and the weighing barycentric coordinates of the weighing platform, taking the predicted weighing data as the output of the failed sensor, and outputting the weighing value of the whole scale in combination with the weighing data of other normal sensors. According to the invention, rapid identification and early warning can be realized, and the influence of abnormal data of the sensor can be effectively eliminated or reduced by learning and utilizing historical weighing data and a weighing gravity center change rule of the weighing platform, so that the reliability of the internet-of-things digital weighing system can be effectively improved; and production losses such as shutdown and production halt caused by the abnormal problem of the sensor of the weighing system of the field user are reduced.

The invention relates to the technical field of weighing sensor data processing, and discloses a weighing sensor data compensation method, device and equipment and a storage medium, and the method comprises the steps: obtaining the multi-dimensional environment characteristics of a weighing sensor in a current measurement environment when the weighing sensor is detected to start metering; extracting a dynamic characteristic component corresponding to each time dimension of the weighing sensor according to historical measurement data of the weighing sensor; respectively inputting each dynamic characteristic component and the multi-dimensional environment characteristics into different compensation modules to generate a plurality of compensation parameter components; and fusing all the compensation parameter components to generate a comprehensive compensation parameter, inputting the comprehensive compensation parameter into the trained compensation operation network, and compensating metering data of the weighing sensor in the current measurement environment to obtain compensated data. Through a modular compensation mode, interference factors such as temperature, humidity and attitude are captured, data of the weighing sensor can be adjusted more finely, and the accuracy and effectiveness of compensation are improved.

The invention relates to the technical field of whole-process intelligent supervision, in particular to a whole-process intelligent supervision system and method for epidemic woods based on a block chain and the Internet of Things, and the system comprises an epidemic wood dynamic identification module, an integrated pressure sensor NFC chip is installed on the trunk of each epidemic wood, a pressure sensor is used for periodically collecting pressure values, monitoring the change of a packaging state, and carrying out the monitoring of the whole-process intelligent supervision of the epidemic woods. A new encryption sequence is generated through the NFC chip according to a preset time interval and stored, a mobile terminal APP reads the current encryption sequence of the NFC chip, the current encryption sequence and a background encryption key are matched and verified, and after verification is passed, a pressure value and the encryption sequence are combined. According to the method, the pressure sensor and the NFC chip are integrated for the trunk of each epidemic wood, real-time monitoring of packaging integrity and generation and verification of a dynamic encryption sequence are achieved, uniqueness and anti-counterfeiting capability of the identity of the source epidemic wood are improved, and it is ensured that each unit of epidemic wood can be accurately and safely tracked from the initial stage.

The invention provides an anti-cheating intelligent weighing system and method based on a multi-source signal, and relates to the technical field of weighing, and the method comprises the steps: carrying out the dynamic calculation based on pressure distribution time sequence data, an object three-dimensional contour, a gravity center position track and deformation displacement field data which are synchronously collected in real time, and combining a preset conduction reference library to generate multi-source features; dynamically calculating and generating a first weight, a second weight and a third weight based on a force conduction deviation value, a contour confidence value and a pressure distribution entropy value in the multi-source features; dynamically calculating and generating a dynamic credible threshold based on the first weight, the second weight and the third weight in combination with the geometric cross-border proportion value and the force conduction deviation degree value; calculating a global consistency index in the current weighing period based on the conduction reference library; based on the global consistency index and the dynamic credible threshold, an anti-cheating result is generated according to a preset judgment condition, and high-precision and high-reliability weighing anti-cheating is achieved through multi-source signal fusion and dynamic analysis.

The invention provides a construction site intelligent weighing management method and system based on dynamic compensation and a medium. The method comprises the steps that zero calibration is carried out by obtaining the weighing state of weighing equipment, or a corresponding original weight data set, a vibration amplitude, a tank rotating speed and a vehicle parking inclination angle are obtained according to a preset sampling frequency, processing is carried out according to the tank rotating speed and the vibration amplitude, and the rotating state of a tank is obtained; self-adaptive filtering compensation processing is carried out on the original weight data set according to the rotation state to obtain final measurement weight data, then abnormal value detection is carried out on the final measurement weight data, and intelligent weighing management is carried out according to the detection result; according to the invention, through real-time determination of the weighing state, evaluation of the rotation state of the tank body, dynamic real-time adaptive filtering compensation processing, obtaining of the final measured weight data, and anomaly detection, intelligent weighing management based on dynamic compensation is realized, and the adaptability and accuracy of weighing are improved.

The invention relates to the field of charging bucket scale calibration, in particular to a calibration method for a large charging bucket scale, which comprises the following steps of: firstly, acquiring calibration data of a small number of point locations by using a standard weight, establishing an accurate and reliable mathematical model through the data, and deducing theoretical analog voltage of the point locations required by subsequent calibration; then, the extremely stable portable calibrator is used for outputting actual analog voltages (consistent with the deduced theoretical analog voltages in size) of the point positions to complete all calibration work, so that random errors and system deviations in the measurement process are effectively eliminated, the accuracy of calibration results is ensured, the use amount of standard weights is also remarkably reduced, and the cost is reduced. The weight carrying difficulty and the storage pressure are reduced, the situation that the space of the furnace top of a blast furnace in an iron making plant is limited is greatly relieved, the operation process is greatly simplified, and the calibration speed of a large charging bucket scale on site is greatly increased.

The invention discloses an electronic scale real-time tamper-proofing method and system based on cloud monitoring and data networking, and relates to the technical field of electronic scale tamper-proofing, and the method comprises the steps: carrying out the real-time collection and networking synchronization of multi-source data, collecting commodity and operation data through a multispectral camera, and achieving the dynamic networking of more than or equal to three electronic scales within 10 meters through a LoRa module; multi-scale cooperative verification and abnormity determination are carried out; generating a holographic evidence packet, encrypting fragments, and separately storing a weight curve, an action video and a spectrum report in a private chain, an alliance chain and a judicial chain; real-time tamper-proof response is carried out, an abnormal scale is locked, and hardware self-destruction is triggered; the system comprises a terminal layer multispectral sensing unit, a cooperative verification unit, a tamper-proof unit, an edge layer dynamic weight engine, a cloud layer holographic block chain and an anti-coercion interface, solves the problems that distributed cheating is difficult to identify, and an evidence collection chain is incomplete, improves the safety of distributed cheating identification, and improves the safety of distributed cheating identification. Real-time tampering prevention and credible evidence storage of the electronic scale are realized.

The invention discloses a truck information acquisition method and system integrating vehicle-mounted weighing and multi-positioning, and relates to the technical field of data processing, multi-source sensing cooperative acquisition is performed through a vehicle-mounted weighing sensor, a GPS positioning unit, a middle intersection positioning unit and a vehicle-mounted IMU, timestamps are added to data streams based on a unified system clock, and the data streams are acquired through a multi-source sensor. Synchronously acquiring static calibration parameters and driving attitude parameters; constructing a load transfer compensation model, and deducting false load components caused by pitching, rolling, acceleration and deceleration and vibration of the vehicle to obtain an actual load sequence; a confidence model is constructed based on sequence data features and attitude association verification to represent the confidence of the two types of sequences, and a fusion position sequence in a unified time domain is generated by adopting a weighted fusion and interpolation compensation strategy; and finally, through time synchronization alignment and sampling frequency compensation, a load-position corresponding relation is established, a joint representation data set is generated, and high-precision and full-scene integrated acquisition of the truck operation core data is realized.

The invention belongs to the technical field of agricultural information, and particularly discloses and provides a smart field intelligent scale system based on statistical analysis, which comprises a horizontal calibration module, a gravity center calibration module, a weight analysis module, a weight correction module, a yield analysis module and a yield confirmation module. According to the method, multi-dimensional environmental parameters such as crop stacking images, wind speeds and wind direction angles are fused, the influence of wind interference and stacking forms on weighing is dynamically analyzed, accurate quantification of wind interference in the field environment is achieved, and meanwhile, the crop weight is accurately measured based on the corrected weight of crops during weighing and the position coordinates of a harvesting area. According to the method, the actual yield of each harvested farmland area is accurately calculated in combination with the area of each farmland area, then the predicted yield of the target farmland is reversely deduced, the balance and scientificity of field yield prediction are improved, and through cooperative work of horizontal calibration and gravity center calibration, the problem of measurement deviation caused by uneven ground and uneven gravity center in a field environment is solved.

The invention discloses a torpedo tank car molten iron weight on-line correction system which comprises a torpedo tank weighing device used for obtaining the weight of a torpedo tank and remaining substances in the torpedo tank; the torpedo ladle lining infrared imaging device is used for acquiring contour data of the lining when the torpedo ladle is empty and contour data of residual substances in the torpedo ladle during iron returning; and the molten iron weight calculation module is used for obtaining data of the torpedo ladle weighing device and the torpedo ladle lining infrared imaging device, calculating the weight of residual substances in the torpedo ladle and obtaining the corrected weight of the residual substances in the torpedo ladle. The invention further discloses an online correction method for the molten iron weight of the torpedo tank car. The invention aims to solve the problem of on-line measurement precision of the weight of the molten iron in the iron ladle on the iron-steel interface under the iron return condition.

The invention provides an electronic belt scale calibration method, and belongs to the technical field of belt scale calibration. The electronic belt scale calibration method comprises the following steps: S1, a storage member conveys one of N weights stored in the storage member to a flexible release member; s2, the flexible release part places the weight on a calibration weighing platform, and the calibration weighing platform obtains the actual weight of the weight; s3, the flexible release part places the weight on a conveying belt, in a running state, of the electronic belt scale in a zero-impact mode; s4, the flexible recovery part recovers the weight in a zero-impact mode; s5, the flexible recovery part conveys the weights into the storage part; and S6, returning to the step S1 when the accumulated weight is less than the first preset weight, and stopping until the accumulated weight corresponding to the M weights is equal to the first preset weight. According to the invention, intelligentization, automation and standardization of the calibration process of the electronic belt scale are realized, and high precision and high stability of calibration work are realized.

An anti-cheating price computing scale comprises a scale body, the scale body comprises a shell and a seat body which are connected with each other, and a space between the shell and the seat body forms an accommodating cavity; the weighing device is arranged in the accommodating cavity and is used for measuring the weight of an object on the scale body; the anti-disassembly device is arranged in the containing cavity and electrically connected to the weighing device, the anti-disassembly device comprises an elastic switch, one of the shell and the base abuts against the end, not provided with the elastic switch, of the anti-disassembly device, and the other one of the shell and the base abuts against the elastic switch, so that the elastic switch is in a compressed state, and the anti-disassembly device and the weighing device are in a communicated state; the weighing device works normally; when the anti-disassembly device is separated from the seat body or the shell, the elastic switch automatically bounces off under the action of elastic force, the anti-disassembly device and the weighing device are in a disconnected state, and the weighing device stops working.

The invention discloses a small automatic weighing and feeding device and an operation method thereof. The small automatic weighing and feeding device comprises a handle, a control operation display screen, a power box, a compressed air pump, an oil pump, a hydraulic supporting rod, a weighing assembly, a hopper and the like. Weighing and peeling, sensor calibration, rated quantity setting, real-time weight monitoring and starting and stopping of hydraulic / pneumatic equipment are integrally controlled through the control operation display screen, and full-process automation of material weighing, lifting and discharging is achieved; the height of the hopper is adjusted through the hydraulic supporting rod, residual materials are cleaned in cooperation with the vibrator, and it is guaranteed that the hopper is clean through compressed air blowing. The system is simple in structure, reasonable in layout, multi-end in function, convenient to overhaul and maintain and safe and reliable in performance.

The invention belongs to the technical field of intelligent traffic, and particularly relates to a dynamic weighing analysis method, system and equipment for a high-speed driving vehicle, and the method comprises the following steps: constructing a multi-mode sensing layer: integrating a fiber grating sensor, a quartz piezoelectric sensor, a millimeter wave radar and a laser radar to form a ternary fusion sensing matrix, wherein the laser radar accurately captures the tire grounding form through three-dimensional reconstruction of the tire grounding form, extraction of a three-dimensional contour multi-modal sensing matrix of a tire contact area and combination of laser radar three-dimensional contour extraction; a space-time dynamic correction algorithm and scene exclusive correction are adopted, and the error control effect under all working conditions is greatly improved.

The invention relates to the field of industrial metering, and discloses a data-driven belt weigher intelligent calibration method and system, and the method comprises the steps: when a calibration command is triggered, collecting real-time data to form a feature vector input model, calculating and predicting a calibration coefficient and zero offset, writing the calibration coefficient and zero offset into a metering instrument to complete calibration, carrying out the importance analysis and screening of feature variables, and obtaining a calibration result. Optimizing model parameters; and performing rationality verification and adaptive adjustment on the prediction parameters, generating a calibration report, and adding data to a historical library. According to the method, a data-driven artificial intelligence model which is fully trained and can deeply reproduce the internal rule of the physical calibration process is used for replacing the traditional physical chain code calibration operation which is time-consuming and labor-consuming and possibly causes danger. Through historical data learning, the mapping relation between the operation states of the belt weigher under various working conditions and environments and the calibration parameters of the belt weigher is established, so that non-contact, high-efficiency and intelligent automatic calibration is realized.

A patient handling apparatus (10) comprising a base (30) with a frame (31) and a patient support device (20). The patient handling apparatus (10) further comprises a weighing arrangement (90) for weighing a patient supported by the patient support device (20), said weighing arrangement (90) comprising a sub frame (91) and a plurality of load sensors (95, 96, 97). The sub frame (91) is arranged on the load sensors (95, 96, 97), said load sensors (95, 96, 97) defining a weighing area (S), whereby the patient support device (20) is mounted to the frame (31) such that a central point (C) of a seat support portion (21) of the patient support device (20) is positioned outside the weighting area (S) in at least one position of the patient support device (20).

The invention discloses an electronic scale calibration method based on a laser scanner. The method comprises the following steps: (1) obtaining the weighing platform height of an electronic scale to be calibrated through a laser matrix array; (2) a servo motor is adopted to drive a workbench bearing the electronic scale, so that the workbench can ascend or descend; (3) transferring a mechanical arm and controlling the mechanical arm to clamp a weight, recording a clamping point of the weight, placing the weight on a weighing platform of the electronic scale, and recording a placing point of the weight; and (4) obtaining the real-time weight of the electronic scale, the real-time weight being the display weight of the electronic scale, and comparing the real-time weight with the actual weight of the weight to obtain an error value. According to the electronic scale calibration method based on the laser scanner, through cooperative work of various automatic devices such as the laser matrix array, the mechanical arm and the servo motor, full-automatic execution of the electronic scale calibration process is achieved, manual intervention is greatly reduced, and calibration efficiency and consistency are improved.

The invention discloses a circuit board collaborative assembly station which comprises an assembly initial detection station used for automatic assembly and initial detection of a circuit board. The temperature test station is used for testing the long-term stability of the circuit board and is arranged on the conveying and discharging side of the assembly initial test station; and the final testing station is used for performing final performance testing and packaging on the circuit board and is arranged on the conveying and discharging side of the temperature testing station. According to the assembly initial station, intelligent dispatching of materials among nine stations is achieved through a speed chain transmission device (RFID binding material boxes / trays) and a truss robot (magnetic railing ruler positioning + / -0.1 mm), and the time consumed by manual transfer is shortened by 30%; a composite robot (AGV + mechanical arm) of a temperature test station automatically grabs a storage, transportation and measurement integrated clamp, incubator butt joint (the three-level positioning precision is + / -0.25 mm) is completed, and 72-hour continuous temperature cycle unattended operation is achieved; the speed chain and the transfer robot of the final station are linked, and automatic butt joint of the vibration clamp and the test equipment is supported.

The invention relates to the technical field of electronic scale calibration, in particular to a weighing calibration method which comprises a modeling module, a traceability electronic scale, a traceability weight, an industrial-grade router and a weighing system remote online calibration app. The method comprises the following steps: carrying out digital modeling on a weighing range of a calibrated material tank scale through weight or material superposition, establishing a standard model through tracing of a high-precision single magnetic cylinder electronic scale, carrying out integration subdivision on a sampling voltage, and finally comparing a standard indicating value of an actual slope model of the subdivided calibrated material tank scale with an original indicating value of the calibrated material tank scale to obtain a real error value. Comprising a single sensor, the processing relates to a series of latest technologies such as materials, hyperfine processing, superspeed cutting, precise online measurement, real-time abrasion and temperature compensation, and the manufactured analytical balance is quicker in response, more stable in indicating value reading, firmer and more durable, and is slightly influenced by environment temperature.

The invention provides a quartz crystal microbalance resonant frequency detection system, a control method and a terminal, a direct digital frequency synthesis excitation unit is adopted to generate a frequency sweep excitation signal with a preset frequency range and stepping, and the frequency sweep excitation signal is conditioned by a signal injection and conditioning unit and then injected into a QCM sensor. And then the pure amplitude response detection unit measures and quantifies voltage response amplitudes of the QCM sensor under different excitation frequencies, and the resonant frequency intelligent determination unit determines the resonant frequency of the QCM sensor according to the voltage response amplitudes. According to the invention, a QCM self-oscillation circuit does not need to be designed and debugged, a precise phase detection assembly does not need to be configured, the circuit board layout is simpler, and components are greatly reduced. The QCM resonant frequency can be accurately measured only through efficient amplitude detection, a complex algorithm is avoided, the operational capability requirement and the software development difficulty are reduced, the QCM resonant frequency measuring device has the advantages of being simple in structure, low in cost, easy to integrate and the like, miniaturization and low-power-consumption design can be easily achieved, and the QCM resonant frequency measuring device is suitable for portable and wearable application.

Microprocessor for a scale system for a mobile storage carrier operates in three states: motion, stable, and fault where stability is determined based on load cell signal variations or external sources and a fault state follows a stable state in response to signal drift in one or more load cells.