Intelligent granary door lock control system and method based on Internet of Things

Abstract

The invention discloses a granary intelligent door lock control system and method based on the Internet of Things, and relates to the technical field of door lock control, and the system comprises a risk factor calculation module which is used for calculating an expansion risk factor of a target door lock according to the relative humidity of a target granary, the environmental CO2 concentration and the static resistance of a lock cylinder fit clearance in the target door lock; the difference calculation module is used for calculating the resistance relative difference of the lock cylinder fit clearance based on the expansion plug risk factor; and the first updating module is used for stripping the FeCO3 foaming layer of the lock cylinder fit clearance based on the resistance relative difference and the relative humidity, and calculating the first updating resistance of the lock cylinder fit clearance. According to the method, effective identification and active intervention can be carried out on hidden and sudden expansion characteristics of layered foaming corrosion in a high-humidity granary environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of door lock control, and particularly relates to a granary intelligent door lock control system based on Internet of Things. BACKGROUND

[0002] The temperature difference between day and night in the granary is significant, the grains continuously release heat by breathing, and the phenomenon of warehouse sweat is formed with the metal wall, and the three superimposed lead to the formation of a small climate environment with high humidity and high carbon dioxide in the warehouse. Specifically, after sunset, the metal warehouse wall cools down rapidly, and the water vapor in the air condenses on the gap between the door lock and the wall panel to form a film; the local carbon dioxide concentration can be increased to 0.5% to 2% by volume due to the breathing of grains, molds and pests; under the joint action of condensed water and carbon dioxide, a complex porous corrosion product layer of ferrous carbonate and ferrous hydroxide with a layered foaming structure is easily generated in the ultra-small fitting gap between the lock tongue and the shell; the volume expansion rate of the corrosion layer is much higher than that of ordinary red rust, and after absorbing water, it shows a rapid expansion plugging characteristic, which will produce instantaneous top pressure resistance when the door lock performs opening and closing action, causing the intelligent door lock to fail without warning. Since the foaming corrosion is mostly located in the closed gap, it is difficult to be discovered early through visual inspection, and in addition, the granary door lock usually bears the first control function of warehouse security, and once it fails, it will directly threaten the quality of grains and the safety of warehouse.

[0003] The self-checking means of the existing intelligent door lock mostly adopts single-point resistance threshold or regular manual maintenance method, which cannot effectively identify and actively intervene in the hidden and sudden expansion plugging characteristics of the layered foaming corrosion in the high-humidity granary environment. SUMMARY

[0004] The purpose of the present application is to solve the problem in the prior art that the layered foaming corrosion in the high-humidity granary environment cannot be effectively identified and actively intervened, and a granary intelligent door lock control system and method based on Internet of Things are proposed.

[0005] In order to solve the problems in the prior art, the present application adopts the following technical scheme:

[0006] A granary intelligent door lock control system based on Internet of Things, comprising:

[0007] A risk factor calculation module for calculating the expansion plugging risk factor of the target door lock according to the relative humidity of the target granary, the environmental CO2 concentration and the static resistance of the lock core fitting gap in the target door lock;

[0008] A difference calculation module for calculating the relative difference of the resistance of the lock core fitting gap based on the expansion plugging risk factor;

[0009] A first updating module for stripping the FeCO3 foaming layer of the lock core fitting gap based on the relative difference of the resistance and the relative humidity, and calculating the first updated resistance of the lock core fitting gap.

[0010] a passivation injection module configured to perform an alkali passivation injection into the lock cylinder fitting gap based on the first updated resistance and measure a pH value and a local CO2 concentration of the lock cylinder fitting gap;

[0011] an improvement rate calculation module configured to calculate a second updated resistance of the lock cylinder fitting gap according to the pH value and the local CO2 concentration, and calculate an electrical resistance improvement rate of the lock cylinder fitting gap according to the second updated resistance;

[0012] a door lock control module configured to perform an advanced reverse micro-drive on a bolt driving mechanism of the target door lock according to the electrical resistance improvement rate before a next unlocking action is performed.

[0013] Preferably, the swelling risk factor of the target door lock is calculated according to a relative humidity of a target granary, an ambient CO2 concentration, and a static resistance of the lock cylinder fitting gap in the target door lock, comprising:

[0014] obtaining the relative humidity of the target granary and the ambient CO2 concentration;

[0015] obtaining the static resistance of the lock cylinder fitting gap;

[0016] substituting the relative humidity, the ambient CO2 concentration, and the static resistance into a swelling risk factor calculation formula to calculate the swelling risk factor of the target door lock.

[0017] Preferably, a resistance relative difference of the lock cylinder fitting gap is calculated based on the swelling risk factor, comprising:

[0018] if the swelling risk factor exceeds a preset factor threshold, performing a single square wave pulse processing on a bolt-shell loop of the target door lock;

[0019] measuring a transient resistance of the lock cylinder fitting gap during the single square wave pulse processing;

[0020] calculating an absolute difference between the transient resistance and the static resistance, and taking the absolute difference as the resistance relative difference of the lock cylinder fitting gap.

[0021] Preferably, a FeCO3 blister layer of the lock cylinder fitting gap is peeled based on the resistance relative difference and the relative humidity, comprising:

[0022] if the resistance relative difference exceeds a preset difference threshold, setting a bolt of the lock cylinder fitting gap as a cathode of an electrolysis loop and setting a shell of the lock cylinder fitting gap as an anode of the electrolysis loop;

[0023] applying a peeling constant current to the lock cylinder fitting gap and starting a micro-electrolysis reaction of the lock cylinder fitting gap;

[0024] calculating an electrolysis duration of the electrolysis loop according to the relative humidity;

[0025] During the electrolysis time, the bubbles generated by the electrolysis reaction in the electrolysis circuit are used to peel off the FeCO3 foaming layer.

[0026] Preferably, calculating the update resistance of the lock core fitting clearance includes:

[0027] After the stripping process is completed, the instantaneous voltage and instantaneous current of the lock core fitting clearance are obtained;

[0028] Divide the instantaneous voltage by the instantaneous current to calculate the first updated resistance of the lock cylinder fit clearance.

[0029] Preferably, injecting an alkaline agent into the lock core fitting gap for passivation based on the first update resistor and measuring the pH value and local CO2 concentration of the lock core fitting gap include:

[0030] If the first update resistance exceeds the preset resistance threshold, Ca(OH)2 is released into the lock core fitting gap;

[0031] Allow Ca(OH)2 to react with the condensate and CO2 in the lock cylinder fit gap, and measure the pH value and local CO2 concentration of the lock cylinder fit gap in real time.

[0032] Preferably, measuring the second updated resistance of the lock core fit clearance according to the pH value and the local CO2 concentration, and calculating the resistance improvement rate of the lock core fit clearance according to the second updated resistance, comprises:

[0033] If the pH value exceeds a preset pH threshold and the local CO2 concentration is lower than a preset volume fraction, a second updated resistance of the lock cylinder fit clearance is measured;

[0034] The difference between the second updated resistance and the static resistance is divided by the static resistance to obtain the resistance improvement rate of the lock core fitting clearance.

[0035] In order to solve the above problems, the present invention also provides a granary intelligent door lock control method based on the Internet of Things, the method comprising:

[0036] S1. Calculate the target door lock's bulging risk factor based on the target granary's relative humidity, ambient CO2 concentration, and the static resistance of the lock core's clearance in the target door lock;

[0037] S2. Calculate the relative resistance difference of the lock core fit gap based on the plugging risk factor;

[0038] S3, stripping the FeCO3 foaming layer in the lock core fitting gap based on the relative resistance difference and relative humidity, and calculating a first updated resistance of the lock core fitting gap;

[0039] S4. Injecting an alkaline agent into the lock core fitting gap for passivation based on the first update resistor, and measuring the pH value and local CO2 concentration of the lock core fitting gap;

[0040] S5. Measure a second updated resistance of the lock core fit clearance based on the pH value and the local CO2 concentration, and calculate a resistance improvement rate of the lock core fit clearance based on the second updated resistance;

[0041] S6. Before the next unlocking action is executed, the bolt drive mechanism of the target door lock is micro-driven in the reverse direction in advance according to the resistance improvement rate.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] 1. This invention accurately identifies the hidden characteristics of layered blister corrosion in high-humidity, high-CO2 environments by constructing a calculation model for bulging risk factors that integrates the relative humidity of the target granary, the ambient CO2 concentration, and the static resistance of the lock core fit gap. When the risk factor exceeds the threshold, a single square wave pulse is processed to obtain the transient resistance and calculate the relative difference, enabling early detection of corrosion trends within closed gaps. This relative resistance difference then triggers an electrolytic stripping mechanism. With the lock tongue as the cathode and the lock body as the anode, a constant current is applied. The bubbles generated by the micro-electrolytic reaction efficiently strip the FeCO3 blister layer. This solves the problems of traditional visual inspections that prevent closed crevice corrosion from being detected and single-point resistance threshold misjudgments, enabling the proactive identification and targeted removal of hidden corrosion.

[0044] 2. The present invention combines alkaline agent passivation injection with dynamic intervention to form a full-process active protection system for sudden expansion and plugging characteristics. After the stripping process, Ca(OH)2 is released based on the first updated resistor, reacting with the condensate and CO2 to adjust the pH value and reduce the local CO2 concentration, forming a passivation film to inhibit corrosion regeneration; by calculating the resistance improvement rate, the lock tongue drive mechanism is reversely micro-driven in advance before the next unlocking, effectively alleviating the instantaneous top pressure blockage caused by the expansion of corrosion products, and avoiding the door lock from malfunctioning without warning. Compared with regular manual maintenance, this method realizes real-time response and dynamic adjustment to sudden expansion and plugging, significantly improving the operational reliability of smart door locks in high-humidity granary environments, and ensuring the continuity of storage security. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0046] Figure 1 This is a functional module diagram of a granary intelligent door lock control system based on the Internet of Things provided by one embodiment of the present invention;

[0047] Figure 2 The present invention provides a flowchart of a method for controlling a smart door lock for a granary based on the Internet of Things according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0049] Example: This example provides a granary intelligent door lock control system based on the Internet of Things, see Figure 1 , specifically, including:

[0050] A risk factor calculation module is used to calculate the target door lock's bulging risk factor based on the target granary's relative humidity, the ambient CO2 concentration, and the static resistance of the lock core fit gap in the target door lock;

[0051] Specifically, because lamellar blister corrosion typically occurs in closed or semi-closed metal micro-gap structures and is highly concealed, sudden, and invisible, it is difficult to effectively identify early through traditional visual inspections or single threshold sensing. Under the combined effects of high humidity and high carbon dioxide concentrations, this corrosion process forms a porous iron carbonate corrosion layer within the lock core gap. This, accompanied by water film adsorption and micro-gas precipitation, further leads to reversible or irreversible blockage and stagnation in the structural gap, causing abnormal resistance fluctuations in this area. Therefore, to achieve quantitative perception and forward warning of this type of corrosion risk, the system needs to combine three key parameters: the relative humidity of the target granary's current environment, the ambient carbon dioxide concentration, and the static resistance of the lock core gap in the target door lock. This factor is a highly sensitive and fast-response fusion indicator to comprehensively determine whether the conditions for lamellar blister corrosion formation exist and its development trend, thereby providing accurate data triggering for subsequent electrolytic stripping, self-repair control, and dynamic maintenance strategies.

[0052] Specifically, layered blistering corrosion refers to the accumulation of corrosion products with a layered structure and porous morphology formed on the metal surface, especially iron-based materials, under micro-liquid film coverage conditions, after periodic redox reactions in a corrosive environment with high humidity and rich carbon dioxide. This phenomenon is often manifested as iron carbonate corrosion products with internal water attachment and external cracks stacked on the metal interface to form an expansive layered structure. The volume stress induced by gas generation or moisture migration can easily form peeling force or top pressure in narrow gaps, thereby causing local expansion or jamming of the micro-fit gaps between metal components. This form of corrosion is highly specific compared to conventional uniform surface rust or intergranular corrosion. Specifically, the corrosion morphology is highly concealed and often occurs at bonding interfaces or occluded areas that cannot be directly observed. The corrosion generation rate is discontinuous and is severely affected by microclimate and fluctuations in carbon dioxide concentration. The corrosion products have strong water absorption and can repeatedly expand and contract in a humid environment, with significant secondary expansion and plugging behavior. The corrosion products have enhanced conductivity, which can easily lead to an abnormal decrease in gap resistance and cause early misjudgment. The morphology of the corrosion products shows an obvious stacked structure and included cavities, and their peeling behavior can be induced by the superposition of factors such as microbubbles, electrochemical gas evolution, and thermal stress, thereby forming a periodic blocking risk.

[0053] In an embodiment of the present invention, the target door lock's bulging risk factor is calculated based on the relative humidity of the target granary, the ambient CO2 concentration, and the static resistance of the lock core fit gap in the target door lock, including:

[0054] Obtain the relative humidity and ambient CO2 concentration of the target granary;

[0055] Get the static resistance of the lock core fit clearance;

[0056] Substitute the relative humidity, ambient CO2 concentration, and static resistance into the blockage risk factor calculation formula to calculate the blockage risk factor of the target door lock. The blockage risk factor calculation formula is as follows:

[0057] SRF=RH+120·C env +80·(R-R0)

[0058] Where SRF is the risk factor for expansion, RH is the relative humidity, and C env is the ambient CO2 concentration, R is the static resistance, and R0 is the reference resistance.

[0059] Specifically, in an embodiment of the present invention, when calculating the blockage risk factor of the target door lock based on the relative humidity of the target granary, the ambient carbon dioxide concentration and the static resistance of the lock core fitting gap in the target door lock, the relative humidity data and carbon dioxide concentration data in the current environment of the target granary are first collected through the sensor module, where the relative humidity is a humidity value in percentage form, and the carbon dioxide concentration is in volume fraction form; then, the current static resistance value of the lock core fitting gap is obtained through an electrode circuit arranged inside the door lock, and the resistance is the steady-state ohmic resistance between the electrodes in the unexcited state; then, the obtained relative humidity, ambient carbon dioxide concentration and static resistance values ​​are substituted into the risk factor calculation formula in turn to obtain the blockage risk factor value of the target door lock in the current cycle. The risk factor serves as the first trigger indicator for judging the corrosion risk of the door lock, and is used to determine whether to enter the subsequent pulse detection and corrosion stripping process.

[0060] Specifically, the lock core fitting clearance refers to the micron-level mechanical activity gap formed between the lock tongue or lock core and the shell or guide groove during its movement in the smart door lock structure. This gap not only ensures the smooth sliding of the lock tongue during normal unlocking or locking actions, but also becomes a high-risk area where corrosion, water vapor and impurities are easily retained due to its closed position and poor ventilation; the expansion risk factor is a comprehensive judgment indicator used to characterize the local mechanical expansion trend caused by the accumulation of corrosion products, water vapor adsorption or gas precipitation in the fitting gap. It is used to quantify the potential risk of abnormal movements such as jamming and blocking of the door lock due to layered blistering corrosion, and serves as the pre-trigger basis for the self-diagnosis and self-repair process of the smart door lock.

[0061] A difference calculation module is used to calculate the relative difference in resistance of the lock core fit gap based on the expansion risk factor;

[0062] In an embodiment of the present invention, calculating the relative resistance difference of the lock core fitting clearance based on the plugging risk factor includes:

[0063] If the blockage risk factor exceeds the preset factor threshold, a single square wave pulse is processed on the bolt-housing circuit of the target door lock;

[0064] During a single square wave pulse process, the transient resistance of the lock cylinder fit clearance is measured;

[0065] The absolute difference between the transient resistance and the static resistance is calculated, and the absolute difference is used as the relative resistance difference of the lock core fitting clearance.

[0066] Specifically, the control system first determines whether the expansion risk factor calculated in the previous cycle exceeds a preset factor threshold. If it exceeds the threshold, it is considered that there is a local expansion trend in the lock core fitting gap, and further electrical structure confirmation is required; at this time, the controller applies a single pulse excitation signal with a set of preset parameters to the electrode structure between the lock tongue and the shell of the door lock. The pulse signal current amplitude is fifty milliamperes and the pulse duration is twenty milliseconds to stimulate the resistance change response in the fitting gap structure; within the processing cycle of the pulse excitation, the transient voltage of the lock core fitting gap is obtained in real time through the voltage acquisition module, and the transient resistance value at the current moment is calculated in combination with the known pulse current; then the measured transient resistance is differenced with the static resistance recorded in step one to obtain the absolute difference between the two, and the difference is divided by the static resistance value to finally obtain the relative difference in resistance of the lock core fitting gap. This relative difference serves as an important indicator for judging the degree of structural micro-blocking or local accumulation of corrosion products, and is used as the basis for determining whether to perform electrolytic stripping treatment in the future.

[0067] Specifically, the lock tongue housing circuit of the target door lock refers to a controllable current path constructed between the lock tongue assembly and its mating metal housing inside the smart door lock. The circuit is configured by respectively setting conductive electrodes on the surface of the lock tongue and the housing, and using a controller to realize on-off and current parameter modulation, thereby performing functional operations such as resistance measurement, electrolytic stripping or corrosion identification; single square wave pulse processing refers to the control system applying a square waveform excitation signal with a constant current amplitude and a limited time width to the above-mentioned lock tongue housing circuit under specific judgment conditions. The duration of this signal is generally several milliseconds, which is used to briefly activate the current response inside the gap, so as to extract the transient resistance change behavior of the lock core mating gap without destroying the original structural state, thereby realizing early electrical diagnosis of local corrosion or foreign body bulging trends.

[0068] A first updating module is configured to perform a stripping process on the FeCO3 foaming layer of the lock core fitting gap based on the relative resistance difference and the relative humidity, and calculate a first updated resistance of the lock core fitting gap;

[0069] In an embodiment of the present invention, the FeCO3 foaming layer in the lock core fitting gap is stripped based on the relative resistance difference and relative humidity, including:

[0070] If the relative resistance difference exceeds a preset difference threshold, the lock tongue in the lock core fitting gap is set as the cathode of the electrolytic circuit, and the housing in the lock core fitting gap is set as the anode of the electrolytic circuit;

[0071] Applying a constant current to the lock core fitting gap and starting a micro-electrolysis reaction in the lock core fitting gap;

[0072] Calculate the electrolysis time of the electrolysis circuit according to the relative humidity;

[0073] During the electrolysis time, the bubbles generated by the electrolysis reaction in the electrolysis circuit are used to peel off the FeCO3 foaming layer.

[0074] Specifically, the control system first determines whether the calculated relative resistance difference exceeds the set difference threshold. If it exceeds the threshold, it is considered that there is a risk of accumulation of layered blistering corrosion products in the lock core fitting gap. At this time, the control module sets the electrode connected to the lock tongue in the door lock as the cathode of the electrolytic circuit, and the electrode at the shell end as the anode of the electrolytic circuit. The controller applies a constant stripping current to the electrolytic circuit, so that the lock core fitting gap is in a micro-electrolytic reaction state; then, the system determines the relative humidity value currently collected, combined with the ambient temperature and structural gap characteristics. The electrolysis time required for the electrolysis reaction controls the current on-off cycle to avoid over-stripping or thermal stress accumulation. During the entire electrolysis time, the electrolyte film in the gap continues to undergo micro-electrolysis reaction under the action of constant current, generating a large number of microbubbles mainly composed of hydrogen or oxygen. These bubbles exert a stripping impact force on the iron carbonate foaming layer during the precipitation process, while destroying the layered bonding interface structure of the corrosive products, prompting them to peel and desorb from the metal interface, thereby achieving non-destructive removal of the foaming corrosion products in the lock core fitting gap, providing a clean reaction surface for subsequent passivation injection and performance recovery.

[0075] Specifically, the FeCO3 blister layer in the lock core fitting gap refers to the ferrous carbonate corrosion product generated by the electrochemical corrosion reaction in the tiny fitting gap between the lock core and the shell in the door lock structure under high humidity and high carbon dioxide concentration environment. It has a porous layered structure and adheres to the metal surface. The corrosion layer is often accompanied by gas precipitation under the action of water vapor or micro-electrolysis, forming a blister corrosion morphology containing an air cavity, which can easily cause fitting blockage and sticking; the stripping treatment refers to constructing an electrolysis circuit between the lock core and the shell, applying a constant current under controlled conditions to stimulate the micro-electrolysis reaction, prompting the generation of directional bubbles and local stress in the gap liquid film, thereby causing the blister corrosion layer to desorb from the metal substrate surface, achieving the purpose of removing corrosion products; the first update resistance refers to the static resistance value calculated by re-applying a constant current to the lock core fitting gap and measuring its voltage response after completing the above-mentioned stripping treatment. It is used to reflect the stripping effect and the degree of corrosion removal, and is a key electrical parameter for subsequent passivation treatment and effect verification.

[0076] In an embodiment of the present invention, calculating the update resistance of the lock core fitting clearance includes:

[0077] After the stripping process is completed, the instantaneous voltage and instantaneous current of the lock core fitting clearance are obtained;

[0078] Divide the instantaneous voltage by the instantaneous current to calculate the first updated resistance of the lock cylinder fit clearance.

[0079] Specifically, first, after the stripping process is completed, the controller synchronously obtains the instantaneous voltage value and the corresponding instantaneous current value at both ends of the lock core fitting gap through a high-sampling rate data acquisition unit, wherein the instantaneous voltage is the stable potential difference measured during the application of a constant excitation signal, and the instantaneous current is the steady-state current value actually passing through the corresponding circuit; then, the control module divides the instantaneous voltage by the corresponding instantaneous current, and calculates the static resistance value of the lock core fitting gap after the stripping is completed according to Ohm's law, and this resistance value is defined as the first updated resistance; compared with the original static resistance before stripping, the first updated resistance can more truly reflect the actual conduction state after the desorption of the corrosion layer, and has the technical advantages of strong dynamic responsiveness and clear structural state indication, and can provide an accurate basis for the adjustment of subsequent passivation treatment strategies.

[0080] A passivation injection module is used to inject an alkaline agent into the lock core fitting gap based on the first update resistor and measure the pH value and local CO2 concentration of the lock core fitting gap;

[0081] In an embodiment of the present invention, alkaline agent passivation injection is performed into the lock core fitting gap based on the first update resistor, and the pH value and local CO2 concentration of the lock core fitting gap are measured, including:

[0082] If the first update resistance exceeds the preset resistance threshold, Ca(OH)2 is released into the lock core fitting gap;

[0083] Allow Ca(OH)2 to react with the condensate and CO2 in the lock cylinder gap, and measure the pH value and local CO2 concentration of the lock cylinder gap in real time.

[0084] Specifically, the system first determines whether the first updated resistance obtained exceeds the set resistance threshold. If the value exceeds the threshold range, it indicates that there is still a high risk of residual corrosion in the lock core fitting gap after stripping. At this time, the controller starts the passivation injection unit and accurately releases a predetermined dose of calcium hydroxide particles into the lock core fitting gap through the micro-injection valve. After the release, the particles quickly react with the residual micro-liquid condensate and locally enriched carbon dioxide gas in the gap to generate calcium carbonate precipitate and release water molecules. This reaction can reduce the acidity of the gap and form a dense passivation film, effectively blocking the subsequent intrusion of water vapor or corrosive gas. At the same time, during the reaction process, the pH value of the gap area and the local carbon dioxide volume fraction are collected respectively through the embedded micro-sensor, and the measurement results are uploaded to the control module in real time, providing basic data support for the subsequent improvement rate calculation and passivation effect evaluation.

[0085] an improvement rate calculation module, configured to measure a second updated resistance of the lock core fit clearance according to a pH value and a local CO2 concentration, and calculate a resistance improvement rate of the lock core fit clearance according to the second updated resistance;

[0086] In an embodiment of the present invention, measuring a second updated resistance of the lock core fit clearance according to a pH value and a local CO2 concentration, and calculating a resistance improvement rate of the lock core fit clearance according to the second updated resistance include:

[0087] If the pH value exceeds a preset pH threshold and the local CO2 concentration is lower than a preset volume fraction, a second updated resistance of the lock cylinder fit clearance is measured;

[0088] The difference between the second updated resistance and the static resistance is divided by the static resistance to obtain the resistance improvement rate of the lock core fitting clearance.

[0089] Specifically, based on the collected pH value and the local carbon dioxide volume fraction concentration in the lock core fitting gap, the second updated resistance of the lock core fitting gap is further measured and its resistance improvement rate is calculated. First, the controller determines whether the current pH value exceeds the set pH threshold, and at the same time confirms that the local carbon dioxide concentration is lower than the preset safety volume fraction index. If both of these judgment conditions are met, the system triggers the resistance measurement module and obtains the voltage response by applying a constant excitation current, thereby calculating the second updated resistance of the lock core fitting gap. This resistance value reflects the degree of improvement in the overall conduction capacity after the alkaline agent passivation injection; then, the difference between the second updated resistance and the initially collected static resistance is calculated, and the difference is divided by the initial static resistance value. The normalized ratio obtained is the resistance improvement rate of the lock core fitting gap. The higher the improvement rate value, the better the passivation treatment effect, which can provide an accurate quantitative basis for the early pre-drive condition judgment in the subsequent door lock control strategy.

[0090] The door lock control module is used to perform a micro-drive in the reverse direction on the bolt drive mechanism of the target door lock in advance according to the resistance improvement rate before the next unlocking action is executed.

[0091] Specifically, in an intelligent door lock control method based on the Internet of Things architecture of the present invention, the system constructs a closed-loop mechanism with data perception, cloud judgment and edge response linkage as the core, and uses the resistance improvement rate of the lock core fitting gap as a remote state evaluation indicator to dynamically determine whether a reverse micro-drive operation is required before the next unlocking action to avoid structural jamming failure.

[0092] First, a sensing unit deployed in the smart door lock terminal periodically collects the updated static resistance value and historical resistance value of the lock cylinder fit gap, calculates the resistance improvement rate, and uploads this indicator to the cloud server in real time via the wireless communication module. Second, the cloud platform constructs a dynamic decision-making algorithm based on environmental models, historical behavior data, and lock type information to determine whether the resistance improvement rate is lower than the set drive stability threshold. If the resistance improvement rate is determined to be lower than the drive stability threshold, the cloud platform identifies the door lock as potentially having a fault risk, such as insufficient repair of the lock cylinder fit gap, residual structural blockage, or unstable contact resistance. It then issues a reverse pre-drive execution command to the target door lock via the IoT control channel. Upon receiving the command, the door lock control module locally enters the response phase. Within a preset lead time window before the user unlock action is triggered, it controls the drive motor to perform a reverse micro-displacement operation, causing the lock tongue to briefly retreat in the opposite direction at a very small angle. This relaxes the structural gap, eliminates initial stuck stress, and alleviates poor electrical contact between the mating surfaces. After the pre-drive is completed, the lock tongue returns to the ready position and completes the unlocking operation in the normal direction when the main unlock action signal is triggered.

[0093] Specifically, the lock tongue drive mechanism refers to a mechanical and electronically controlled composite component installed inside the smart door lock for controlling the extension and retraction of the lock tongue. It usually includes a micro motor, a gear reduction group, a linkage push rod and a position sensor. Its function is to accurately drive the lock tongue to complete the locking and unlocking operations of the door lock after receiving the control signal; early reverse micro-drive means that before the door lock has officially executed the unlocking command, the control system actively sends a short-term, low-amplitude reverse action command to the lock tongue drive mechanism based on the judgment of the structural expansion trend or insufficient resistance improvement rate, so that the lock tongue slightly retracts to release the residual sticking force or static friction between it and the mating parts, thereby improving the reliability and responsiveness of the subsequent formal unlocking action.

[0094] Specifically, the entire process builds an IoT intelligent control closed loop of perception, cloud decision-making and local execution. It can not only significantly improve the stability and responsiveness of smart door locks in extreme environments such as high humidity and high corrosion, but also has modular deployment capabilities and remote configurability. It is especially suitable for key scenarios such as granaries, warehouses, and experimental stations that have high requirements for door lock operation reliability. The solution quantifies the corrosion recovery status through the resistance improvement rate and introduces a feedforward pre-drive mechanism to effectively prevent unlocking failure or action delay caused by incomplete removal of blockages, thereby enhancing the system's early intervention capabilities for structural degradation.

[0095] In order to solve the above problems, the present invention also provides a granary intelligent door lock control method based on the Internet of Things, the method comprising:

[0096] S1. Calculate the target door lock's bulging risk factor based on the target granary's relative humidity, ambient CO2 concentration, and the static resistance of the lock core's clearance in the target door lock;

[0097] S2. Calculate the relative resistance difference of the lock core fit gap based on the plugging risk factor;

[0098] S3. Stripping the FeCO3 foaming layer in the lock core fitting gap based on the relative resistance difference and relative humidity, and calculating a first updated resistance of the lock core fitting gap;

[0099] S4. Injecting an alkaline agent into the lock core fitting gap for passivation based on the first update resistor, and measuring the pH value and local CO2 concentration of the lock core fitting gap;

[0100] S5. Measure a second updated resistance of the lock core fit clearance based on the pH value and the local CO2 concentration, and calculate a resistance improvement rate of the lock core fit clearance based on the second updated resistance;

[0101] S6. Before the next unlocking action is executed, the bolt drive mechanism of the target door lock is micro-driven in the reverse direction in advance according to the resistance improvement rate.

[0102] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A granary intelligent door lock control system based on the Internet of Things, characterized in that: include: A risk factor calculation module is used to calculate the target door lock's bulging risk factor based on the target granary's relative humidity, the ambient CO2 concentration, and the static resistance of the lock core fit gap in the target door lock; A difference calculation module is used to calculate the relative difference in resistance of the lock core fit gap based on the expansion risk factor; A first updating module is configured to perform a stripping process on the FeCO3 foaming layer of the lock core fitting gap based on the relative resistance difference and the relative humidity, and calculate a first updated resistance of the lock core fitting gap; A passivation injection module is used to inject an alkaline agent into the lock core fitting gap based on the first update resistor and measure the pH value and local CO2 concentration of the lock core fitting gap; an improvement rate calculation module, configured to measure a second updated resistance of the lock core fit clearance according to a pH value and a local CO2 concentration, and calculate a resistance improvement rate of the lock core fit clearance according to the second updated resistance; The door lock control module is used to perform a micro-drive in the reverse direction on the bolt drive mechanism of the target door lock in advance according to the resistance improvement rate before the next unlocking action is executed.

2. The granary intelligent door lock control system based on the Internet of Things according to claim 1 is characterized in that: The target door lock's bulging risk factor is calculated based on the target granary's relative humidity, ambient CO2 concentration, and the static resistance of the lock core clearance in the target door lock, including: Obtain the relative humidity and ambient CO2 concentration of the target granary; Get the static resistance of the lock core fit clearance; Substitute the relative humidity, ambient CO2 concentration, and static resistance into the blockage risk factor calculation formula to calculate the blockage risk factor of the target door lock.

3. The granary intelligent door lock control system based on the Internet of Things according to claim 1 is characterized in that: Calculate the relative resistance difference of the lock core fit clearance based on the risk factor for expansion, including: If the blockage risk factor exceeds the preset factor threshold, a single square wave pulse is processed on the bolt-housing circuit of the target door lock; During a single square wave pulse process, the transient resistance of the lock cylinder fit clearance is measured; The absolute difference between the transient resistance and the static resistance is calculated, and the absolute difference is used as the relative resistance difference of the lock core fitting clearance.

4. The granary intelligent door lock control system based on the Internet of Things according to claim 1 is characterized in that: The FeCO3 foaming layer in the lock core fitting gap is stripped based on the relative resistance difference and relative humidity, including: If the relative resistance difference exceeds a preset difference threshold, the lock tongue in the lock core fitting gap is set as the cathode of the electrolytic circuit, and the housing in the lock core fitting gap is set as the anode of the electrolytic circuit; Applying a constant current to the lock core fitting gap and starting a micro-electrolysis reaction in the lock core fitting gap; Calculate the electrolysis time of the electrolysis circuit according to the relative humidity; During the electrolysis time, the bubbles generated by the electrolysis reaction in the electrolysis circuit are used to peel off the FeCO3 foaming layer.

5. The granary intelligent door lock control system based on the Internet of Things according to claim 4 is characterized in that: Calculate the updated resistance of the lock cylinder fit clearance, including: After the stripping process is completed, the instantaneous voltage and instantaneous current of the lock core fitting clearance are obtained; Divide the instantaneous voltage by the instantaneous current to calculate the first updated resistance of the lock cylinder fit clearance.

6. The granary intelligent door lock control system based on the Internet of Things according to claim 1 is characterized in that: Based on the first updated resistor, an alkaline agent is injected into the lock core fitting gap for passivation, and the pH value and local CO2 concentration of the lock core fitting gap are measured, including: If the first update resistance exceeds the preset resistance threshold, Ca(OH)2 is released into the lock core fitting gap; Allow Ca(OH)2 to react with the condensate and CO2 in the lock cylinder fit gap, and measure the pH value and local CO2 concentration of the lock cylinder fit gap in real time.

7. The granary intelligent door lock control system based on the Internet of Things according to claim 1 is characterized in that: Measuring a second updated resistance of the lock core fit clearance according to the pH value and the local CO2 concentration, and calculating a resistance improvement rate of the lock core fit clearance according to the second updated resistance, including: If the pH value exceeds a preset pH threshold and the local CO2 concentration is lower than a preset volume fraction, a second updated resistance of the lock cylinder fit clearance is measured; The difference between the second updated resistance and the static resistance is divided by the static resistance to obtain the resistance improvement rate of the lock core fitting clearance.

8. A method for controlling a granary intelligent door lock based on the Internet of Things, characterized in that: The method comprises: S1. Calculate the target door lock's bulging risk factor based on the target granary's relative humidity, ambient CO2 concentration, and the static resistance of the lock core's clearance in the target door lock; S2. Calculate the relative resistance difference of the lock core fit gap based on the plugging risk factor; S3, stripping the FeCO3 foaming layer in the lock core fitting gap based on the relative resistance difference and relative humidity, and calculating a first updated resistance of the lock core fitting gap; S4. Injecting an alkaline agent into the lock core fitting gap for passivation based on the first update resistor, and measuring the pH value and local CO2 concentration of the lock core fitting gap; S5. Measure a second updated resistance of the lock core fit clearance based on the pH value and the local CO2 concentration, and calculate a resistance improvement rate of the lock core fit clearance based on the second updated resistance; S6. Before the next unlocking action is executed, the bolt drive mechanism of the target door lock is micro-driven in the reverse direction in advance according to the resistance improvement rate.

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