Watch movement accurate operation system based on intelligent sensing and self-adaptive regulation and control

Abstract

The invention relates to the technical field of intelligent sensing, and provides a watch movement accurate operation system based on intelligent sensing and self-adaptive control, which comprises a multi-mode sensor module used for collecting environmental parameters, movement states and geographic position data; the data processing module is connected with the sensor module and generates a regulation and control instruction through multi-source data fusion; the self-adaptive regulation and control module is connected with the data processing module and is used for dynamically adjusting movement operation parameters and time zone offset; the power management unit is used for switching power supply modes according to load requirements; and the wireless communication module supports data interaction with a time service server and external equipment. Through fusion of temperature, vibration and magnetic field data, nonlinear errors caused by superposition of high temperature and vibration are solved, mechanical wear is reduced in combination with a progressive adjustment algorithm, daily errors caused by magnetic field interference are compressed from + / -8 seconds to + / -0.3 seconds, and the time precision can still be maintained to be smaller than or equal to + / -0.1 seconds per day in a ground-network-free area (such as an ocean vessel).

Description

Technical Field

[0001] This invention relates to the field of intelligent sensing technology, specifically to a precise watch movement operating system based on intelligent sensing and adaptive control. Background Technology

[0002] As precision timekeeping devices, watches are subject to long-term influences from environmental temperature, mechanical vibration, and magnetic field interference. With the development of smart wearable devices, users have placed higher demands on watches' stability in extreme environments, their ability to automatically calibrate across time zones, and their battery life. Traditional mechanical and quartz watch movements rely on fixed compensation mechanisms, making it difficult for them to dynamically adapt to complex and changing physical environments, leading to decreased accuracy and increased mechanical wear.

[0003] Existing solutions only compensate for single factors such as temperature or magnetic field, ignoring the coupling effect of multiple physical fields. Traditional time zone switching requires manual adjustment of the crown, and frequent operation increases the wear rate of the gear set by more than 30%. Fixed threshold strategy cannot adapt to rapid environmental changes, resulting in a compensation lag of more than 10 seconds. High-precision mode consumes too much power, while low-power mode shuts down key sensors, sacrificing environmental perception capabilities. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a precise watch movement operation system based on intelligent sensing and adaptive control. This system solves the problems of existing technologies that only compensate for single factors such as temperature or magnetic field, ignore multi-physical field coupling effects, require manual adjustment of the crown for traditional time zone switching, increase gear wear rate by more than 30% due to frequent operation, cannot adapt to rapid environmental changes due to fixed threshold strategy resulting in compensation lag of more than 10 seconds, have excessive power consumption in high-precision mode, and shut down key sensors in low-power mode, sacrificing environmental perception capabilities.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a precise watch movement operating system based on intelligent sensing and adaptive control, comprising:

[0006] A multimodal sensor module is used to collect environmental parameters, watch core status, and geographical location data.

[0007] The data processing module connects to the sensor module and generates control commands through multi-source data fusion.

[0008] The adaptive control module connects to the data processing module to dynamically adjust the watch movement parameters and time zone offset.

[0009] The power management unit switches the power supply mode according to load demand;

[0010] The wireless communication module supports data interaction with the time synchronization server and external devices.

[0011] Preferably, the multimodal sensor module includes:

[0012] Environmental sensor group: temperature sensor, magnetic field sensor, and barometric pressure sensor;

[0013] Motion sensor group: accelerometer and gyroscope sensor;

[0014] Geolocation Unit: Integrates GPS / BeiDou dual-mode chip to acquire latitude, longitude and altitude data in real time.

[0015] Preferably, the data processing module performs the following operations:

[0016] The weighted fusion of sensor data is calculated using the following formula:

[0017]

[0018] Among them, S i The signal-to-noise ratio of the sensor is given, and γ = 1 is the time zone offset attenuation factor.

[0019] The local standard time is calculated by matching the time zone database. The compensation formula is as follows:

[0020]

[0021] Where λ is longitude, C DST This is the marker for daylight saving time.

[0022] Preferably, the adaptive control module includes:

[0023] Crystal oscillator frequency compensation unit: Based on temperature change dual closed-loop control of the crystal oscillator frequency, the compensation formula is as follows:

[0024]

[0025] Where λ is longitude, C DST This is the location for daylight saving time.

[0026] Time Zone Transition Unit: When crossing a time zone boundary is detected and the speed v ≥ 200 km / h, the progressive time adjustment algorithm is activated, with the following rate formula:

[0027]

[0028] Preferably, the geolocation unit is linked to the magnetic field sensor:

[0029] When a change in geographical location Δφ ≥ 15° is detected, geomagnetic declination calibration is triggered: B cal =B raw +μ·Δφ.

[0030] Preferably, the power management unit includes:

[0031] Low power mode: Turns off unnecessary sensors, but keeps the geolocation unit awake every 30 minutes;

[0032] High-performance mode: Full sensor sampling, wireless communication module synchronizes time signal every 6 hours.

[0033] Preferably, it also includes a self-learning unit:

[0034] Train a time error prediction model using historical data:

[0035] Δt=k1·ΔT+k2·a rms +k3·B ext +k4·|Δt zone |;

[0036] The model parameters are updated every 24 hours, and the training data includes time zone switching labels.

[0037] Preferably, the progressive time transition algorithm is linked to the protection of the watch movement's mechanical structure:

[0038] When the time adjustment rate exceeds 0.5 seconds / minute, the drive gear torque is limited to the following;

[0039] The vibration amplitude is monitored by a gyroscope. If it exceeds the threshold A... th =0.1mm, pause time adjustment.

[0040] Preferably, the wireless communication module supports:

[0041] Emergency Synchronization Mode: When entering an unrecorded time zone, UTC reference signals are acquired via NB-IoT + satellite dual links;

[0042] User behavior learning: Dynamically adjust the time synchronization period based on cross-time zone frequency, using the following formula:

[0043] T sync =T base ·(1+η·min(N zome N max )).

[0044] Preferably, under environmental conditions ranging from -40℃ to 85℃ and 10G vibration, the following indicators are verified:

[0045] Daily cumulative error ≤ ±0.5 seconds;

[0046] Gear wear across time zones ≤ 0.01 mg / 10,000 switches;

[0047] Geomagnetic interference suppression rate ≥95%.

[0048] Working principle:

[0049] Multimodal sensing layer

[0050] An environmental sensor array (temperature, magnetic field, air pressure), a motion sensor array (accelerometer, gyroscope), and a geolocation unit collect physical environment and user behavior data in real time, forming a multi-dimensional sensing matrix. The air pressure sensor uses the formula: Inversely calculate the altitude and correct the temperature compensation parameters;

[0051] Intelligent decision-making layer

[0052] The data processing module employs a weighted fusion algorithm to remove low signal-to-noise ratio data, and combines a time zone database with a self-learning model to predict time errors. Sensor weights are dynamically adjusted to ensure robust decision-making.

[0053] Adaptive Execution Layer

[0054] Crystal frequency compensation: Dual closed-loop control iteratively corrects the α and β coefficients based on real-time temperature and historical error to suppress nonlinear drift;

[0055] Time zone transition control: Based on the speed v graded adjustment rate (formula radj), combined with the gyroscope monitoring vibration amplitude, a balance between mechanical protection and accuracy is achieved;

[0056] Power management: According to T sync =T base ·(1+0.2·min(N zome 5) Dynamically optimize energy consumption and extend battery life;

[0057] The self-learning unit of the closed-loop optimization layer updates the model parameters every 24 hours and trains the error prediction model through historical data, forming a closed loop of "perception-decision-execution-feedback" to continuously improve the system's adaptability.

[0058] This invention provides a precise watch movement operating system based on intelligent sensing and adaptive control. It offers the following advantages:

[0059] 1. This invention solves the nonlinear error caused by the superposition of high temperature and vibration by integrating temperature, vibration and magnetic field data. Combined with a progressive adjustment algorithm to reduce mechanical wear, it reduces the daily error caused by magnetic field interference from ±8 seconds to ±0.3 seconds. Even in areas without ground network (such as ocean-going ships), it can still maintain a time accuracy of ≤±0.1 seconds / day.

[0060] 2. The present invention features dual closed-loop crystal oscillator compensation and intelligent power management, which ensures stable operation in extreme environments. Combined with continuous iteration of the error prediction model, it improves the accuracy and adaptability in complex scenarios, extends the life of the watch movement, and reduces the false trigger rate to less than 5%, thereby extending the battery life by 40%. Attached Figure Description

[0061] Figure 1 This is a system diagram of the present invention. Detailed Implementation

[0062] 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.

[0063] Example:

[0064] Please see the appendix Figure 1 This invention provides a precise watch movement operation system based on intelligent sensing and adaptive control, comprising:

[0065] A multimodal sensor module is used to collect environmental parameters, watch core status, and geographic location data, including:

[0066] The environmental sensor group consists of a temperature sensor, a magnetic field sensor, and a barometric pressure sensor. The barometric pressure sensor is used to deduce altitude using a formula based on changes in air pressure.

[0067] Motion sensor group: accelerometer and gyroscope sensor;

[0068] Geographic positioning unit: integrates GPS / BeiDou dual-mode chip to acquire latitude, longitude and altitude data in real time;

[0069] The data processing module, connected to the sensor module, generates control commands through multi-source data fusion and performs weighted fusion of sensor data. The weighting formula is as follows:

[0070]

[0071] Among them, S i The signal-to-noise ratio of the sensor is given, and γ = 1 is the time zone offset attenuation factor.

[0072] The local standard time is calculated by matching the time zone database. The compensation formula is as follows:

[0073]

[0074] Where λ is longitude, C DST This is the location for daylight saving time.

[0075] The geolocation unit is linked with the magnetic field sensor:

[0076] When a change in geographical location Δφ ≥ 15° is detected, geomagnetic declination calibration is triggered: B cal =B raw+μ·Δφ;

[0077] The adaptive control module, connected to the data processing module, dynamically adjusts the watch movement's operating parameters and time zone offset, including:

[0078] Crystal oscillator frequency compensation unit: Based on temperature change dual closed-loop control of the crystal oscillator frequency, the compensation formula is as follows:

[0079]

[0080] Where λ is longitude, C DST This is the location for daylight saving time.

[0081] Time Zone Transition Unit: When crossing a time zone boundary is detected and the speed v ≥ 200 km / h, the progressive time adjustment algorithm is activated, with the following rate formula:

[0082]

[0083] The advanced time transition algorithm is linked with the watch movement's mechanical structure protection:

[0084] When the time adjustment rate exceeds 0.5 seconds / minute, the drive gear torque is limited to the following;

[0085] The vibration amplitude is monitored by a gyroscope. If it exceeds the threshold A... th =0.1mm, pause time adjustment;

[0086] The power management unit switches the power supply mode according to load demand, including:

[0087] Low power mode: Turns off unnecessary sensors, but keeps the geolocation unit awake every 30 minutes;

[0088] High-performance mode: Full sensor sampling, wireless communication module synchronizes time signal every 6 hours;

[0089] The wireless communication module supports data interaction with the time synchronization server and external devices. The wireless communication module supports:

[0090] Emergency Synchronization Mode: When entering an unrecorded time zone, UTC reference signals are acquired via NB-IoT + satellite dual links;

[0091] User behavior learning: Dynamically adjust the time synchronization period based on cross-time zone frequency, using the following formula:

[0092] T sync =T base ·(1+η·min(N zome N max ));

[0093] Self-learning unit:

[0094] Train a time error prediction model using historical data:

[0095] Δt=k1·ΔT+k2·a rms +k3·B ext +k4·|Δt zone |;

[0096] Model parameters are updated every 24 hours. The training data includes time zone switching labels. The model is validated under environmental conditions ranging from -40℃ to 85℃ and with 10G vibration, using the following metrics:

[0097] Daily cumulative error ≤ ±0.5 seconds;

[0098] Gear wear across time zones ≤ 0.01 mg / 10,000 switches;

[0099] Geomagnetic interference suppression rate ≥95%.

[0100] The following description, in conjunction with specific embodiments, will be provided.

[0101] Example:

[0102] Data collection phase

[0103] Geographic positioning unit: The real-time position of the aircraft (40°N, 116°E → 48°N, 3°W) is obtained through a GPS / BeiDou dual-mode chip, and the speed v = 900 km / h is detected.

[0104] Environmental sensor group: The temperature sensor detected the core temperature rising from 25℃ to 32℃, and the magnetic field sensor measured the change in geomagnetic declination Δφ = 28°;

[0105] Motion sensor group: The gyroscope monitors the vibration amplitude A = 0.08 mm, and the accelerometer determines it to be in "flight state".

[0106] Data Processing and Decision Making

[0107] Data fusion: The weights of each sensor are calculated according to the weight formula, with the magnetic field sensor receiving the highest weight due to its signal-to-noise ratio Si = 8.2;

[0108] Time zone compensation: According to the formula Calculate time zone offset + 1 hour + 1 hour (Paris Daylight Saving Time applies);

[0109] Geomagnetic calibration: Trigger B cal =B raw +0.2×28=5.6μT, eliminating geomagnetic declination interference.

[0110] Adaptive control execution

[0111] Time zone transition algorithm: Since v≥800km / h, the time is gradually adjusted at a rate of 1 second / minute, while limiting gear torque;

[0112] Crystal oscillator frequency compensation: based on Frequency drift was suppressed to within 0.07 ppm;

[0113] Power Management: Switch to high-performance mode and synchronize UTC signals via NB-IoT every 6 hours to ensure timing error <0.3 seconds.

[0114] Self-learning optimization

[0115] Update the error prediction model: Δt = 0.12X7 + 0.05X0.8 + 0.03X5.6 + 0.1X1 = 1.3 seconds, with correction coefficients k1-k4;

[0116] The training data was labeled with "cross-time zone flight" scenarios to optimize subsequent control strategies.

[0117] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A precise watch movement operating system based on intelligent sensing and adaptive control, characterized in that, include: A multimodal sensor module is used to collect environmental parameters, watch core status, and geographical location data. The data processing module connects to the sensor module and generates control commands through multi-source data fusion. The adaptive control module connects to the data processing module to dynamically adjust the watch movement parameters and time zone offset. The power management unit switches the power supply mode according to load demand; The wireless communication module supports data interaction with the time synchronization server and external devices.

2. The watch movement precision operation system based on intelligent sensing and adaptive control according to claim 1, characterized in that, The multimodal sensor module includes: Environmental sensor group: temperature sensor, magnetic field sensor, and barometric pressure sensor; Motion sensor group: accelerometer and gyroscope sensor; Geolocation Unit: Integrates GPS / BeiDou dual-mode chip to acquire latitude, longitude and altitude data in real time.

3. The precise operation system of a watch movement based on intelligent sensing and adaptive control according to claim 2, characterized in that, The data processing module performs the following operations: The weighted fusion of sensor data is calculated using the following formula: Among them, S i The signal-to-noise ratio of the sensor is given, and γ = 1 is the time zone offset attenuation factor. The local standard time is calculated by matching the time zone database. The compensation formula is as follows: Where λ is longitude, C DST This is the marker for daylight saving time.

4. The precise operation system of a watch movement based on intelligent sensing and adaptive control according to claim 1, characterized in that, The adaptive control module includes: Crystal oscillator frequency compensation unit: Based on temperature change dual closed-loop control of the crystal oscillator frequency, the compensation formula is as follows: Where λ is longitude, C DST This is the location for daylight saving time; Time Zone Transition Unit: When crossing a time zone boundary is detected and the speed v ≥ 200 km / h, the progressive time adjustment algorithm is activated, with the following rate formula:

5. The precise operation system of a watch movement based on intelligent sensing and adaptive control according to claim 2, characterized in that, The geolocation unit is linked to the magnetic field sensor: When a change in geographical location Δφ ≥ 15° is detected, geomagnetic declination calibration is triggered: B cal =B raw +μ·Δφ.

6. The precise operation system of a watch movement based on intelligent sensing and adaptive control according to claim 1, characterized in that, The power management unit includes: Low power mode: Turns off unnecessary sensors, and keeps the geolocation unit awake every 30 minutes; High-performance mode: Full sensor sampling, wireless communication module synchronizes time signal every 6 hours.

7. The precise operation system of a watch movement based on intelligent sensing and adaptive control according to claim 1, characterized in that, It also includes self-learning units: Train a time error prediction model using historical data: Δt=k1·ΔT+k2·a rms +k3·B ext +k4·|Δt zone |; The model parameters are updated every 24 hours, and the training data includes time zone switching labels.

8. The precise operation system of a watch movement based on intelligent sensing and adaptive control according to claim 4, characterized in that, The progressive time transition algorithm is linked to the protection of the watch movement's mechanical structure: When the time adjustment rate exceeds 0.5 seconds / minute, the drive gear torque is limited to the following; The vibration amplitude is monitored by a gyroscope. If it exceeds the threshold A... th =0.1mm, pause time adjustment.

9. The precise operation system of a watch movement based on intelligent sensing and adaptive control according to claim 1, characterized in that, The wireless communication module supports: Emergency Synchronization Mode: When entering an unrecorded time zone, UTC reference signals are acquired via NB-IoT + satellite dual links; User behavior learning: Dynamically adjust the time synchronization period based on cross-time zone frequency, using the following formula: T sync =T base ·(1+η·min(N zome ,N max ))。 10. The precise operation system of a watch movement based on intelligent sensing and adaptive control according to claim 1, characterized in that, The following indicators were verified under environmental conditions ranging from -40℃ to 85℃ and under 10G vibration: Daily cumulative error ≤ ±0.5 seconds; Gear wear across time zones ≤ 0.01 mg / 10,000 switches; Geomagnetic interference suppression rate ≥95%.

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