A glass intelligent defrosting control system for a driller's cabin based on temperature and humidity data driving

Abstract

This invention relates to the field of industrial control technology, specifically disclosing an intelligent defrosting control system for driller's cabin glass driven by temperature and humidity data. This system comprises an effective dew point determination module, a frosting risk determination module, an air source output limit module, and a defrosting control adjustment module. The intelligent defrosting monitoring component first obtains the effective dew point of the glass microenvironment through the effective dew point determination module. Subsequently, the frosting risk determination module compares the frost risk and margin of each zone, enabling more sensitive identification of areas prone to residual frost, such as corners and edges. Next, the air source output limit module applies maximum / minimum constraints to the branch air source. Finally, the defrosting control adjustment module identifies residual frost at the edges and corners and adaptively adjusts the valve opening, hot-end duty cycle / duration, and defrosting duration to achieve a closed-loop scheduling of strong defrosting, maintenance, and further enhancement. This ensures continuous clear visibility of the glass while balancing energy consumption and stability under complex operating conditions and limited air supply.

Description

Technical Field

[0001] This invention relates to the field of industrial control technology, specifically to an intelligent defrosting control system for the driller's cabin glass driven by temperature and humidity data. Background Technology

[0002] The driller's cabin is the core control center of the oil drilling rig, usually located near the drilling platform. It is used to centrally install key control and monitoring terminals such as brake levers, top drives / winches. The driller observes the wellhead, drilling platform hoisting, and personnel activities in real time through its windows and monitoring interface and executes operating instructions. Because the cabin is relatively enclosed and personnel spend a long time on duty, breathing and moisture can easily increase the indoor humidity, while the low temperature and wind chill outside can lower the surface temperature of the glass, making it more prone to fogging and frost. Therefore, the special function of defrosting the driller's cabin glass is to continuously restore and maintain the clarity of key views, ensuring the driller's real-time visual monitoring and safety intervention capabilities of the work area.

[0003] The existing intelligent defrosting process for driller's cabin glass typically involves the following steps: The system collects real-time data on the temperature, relative humidity, and inner surface temperature of the glass inside the driller's cabin using sensors. The controller performs timestamp alignment and filtering to remove noise from the multi-source data. Subsequently, the controller calculates the air dew point temperature based on the temperature and humidity, and compares the dew point temperature with the glass surface temperature to obtain the condensation / frost margin and corresponding risk level. When the margin falls below the threshold or the risk increases, the controller automatically generates a defrosting control strategy, linking dehumidification equipment (such as fan units or damper actuators) to output dry hot air to raise the glass surface temperature and reduce the moisture content near the glass. During execution, the controller continuously monitors the margin recovery rate and risk changes, dynamically adjusting the airflow, power, and duration. Once the margin recovers to a safe range and remains stable, it exits strong defrosting and switches to low-power maintenance, thus achieving adaptive defrosting with visibility as the priority and energy consumption as the controllable goal under conditions of changing external temperature and fluctuating indoor humidity.

[0004] The aforementioned defrosting process for the driller's cabin glass is usually based on environmental parameters such as cabin temperature and humidity. The controller then switches the airflow between the hot and cold ends according to winter / summer conditions. Condition identification is achieved by setting temperature and humidity ranges. The inner surface of the glass is purged and heated through the defrosting air duct to improve visibility. However, in actual drilling sites, the formation of fogging and frost on the glass often exhibits obvious "localized first-onset" characteristics. For example, the edges and corners of the window frame are more significantly affected by cold bridges, air leaks, or external wind cooling. The rate of change of their surface temperature is not synchronized with the rate of change of the average temperature and humidity inside the cabin. Localized airflow and moisture accumulation can also cause frost and fogging to appear earlier.

[0005] Therefore, when the control strategy mainly switches modes around the environmental threshold, it is easy for a time lag to occur when the environmental parameters have not yet reached the critical value, but the glass has already reached the conditions for frost formation. This makes the defrosting action more of a post-event compensation than a pre-emptive suppression. At the same time, under the condition of uniform airflow purging, the low-temperature areas at the edges and corners may require stronger or more precise heat and airflow distribution to restore clarity synchronously. Therefore, there may be a phenomenon that the overall field of view is improved, but local areas still have intermittent residual frost and fog, which brings adverse effects such as fluctuations in the clarity of key observation areas, repeated triggering, and increased energy consumption. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides an intelligent defrosting control system for driller's cabin glass based on temperature and humidity data, which can effectively solve the problems mentioned in the background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an intelligent defrosting control system for driller's cabin glass driven by temperature and humidity data, comprising: an effective dew point determination module, used to receive initial data from multi-source monitoring of the driller's cabin in real time through an intelligent defrosting monitoring component, perform data preprocessing, and calculate the dew point based on the preprocessed temperature and humidity data to obtain the effective dew point of the driller's cabin glass; a frost risk determination module, used to define the driller's cabin glass area into zones through the intelligent defrosting monitoring component, estimate the equivalent temperature of each glass zone, and determine the frost risk based on the effective dew point of the driller's cabin glass; an air source output limit module, used to limit the output of branch air sources in conjunction with the air source processing component according to the frost risk determination result, and the intelligent defrosting monitoring component to perform defrosting control based on the limit result; and a defrosting control adjustment module, used to intelligently execute defrosting control through a controller, and simultaneously identify residual frost at the edges and corners, adaptively adjusting the defrosting control process according to the identification result to complete the intelligent defrosting control process for the driller's cabin glass.

[0008] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) This invention provides an intelligent defrosting control system for the driller's cabin glass based on temperature and humidity data. The intelligent defrosting monitoring component first accesses initial data from multiple sources, such as the temperature and humidity inside and outside the driller's cabin and the temperature and humidity at the air duct outlet, in real time through the effective dew point determination module. It then performs preprocessing such as validity checks, filtering, and time alignment. Based on this, it calculates and integrates the effective dew point of the glass microenvironment, thereby providing a benchmark parameter closer to the glass boundary layer for subsequent risk assessment. Subsequently, the frosting risk assessment module defines the glass area into zones and recursively estimates the equivalent temperature of each zone. It compares this temperature with the effective dew point to obtain the frost risk and margin of each zone, enabling areas prone to residual frost, such as corner and edge areas, to defrost. The system is more sensitive to identification; then, the gas source output limit module, based on the risk assessment result, links with the gas source processing component to apply maximum / minimum constraints to the branch air source and generate executable defrosting control quantities, ensuring that the defrosting output meets the minimum requirements while avoiding the occupation of the public gas source on site; finally, the defrosting control adjustment module, during the execution process, connects to the image feedback of the driller's room monitoring camera to identify residual frost at the edge corners, and adaptively adjusts the valve opening, hot end duty cycle / duty time, and defrosting duration without exceeding the limit, realizing a closed-loop scheduling of strong defrosting, maintenance, and further enhancement, thereby continuously maintaining a clear glass view under complex operating conditions and limited gas source conditions while taking into account energy consumption and stability.

[0009] (2) This invention introduces existing industrial monitoring camera equipment in the driller's room to continuously statistically analyze the contrast, edge clarity and whitening ratio of the glass corner area. This solution can identify local problems such as residual frost in the glass corner and edge areas that are difficult to accurately reflect by temperature, humidity and dew point margin alone. The residual frost identification results are directly linked to the adaptive adjustment of valve opening, hot end duty cycle / duty time and defrosting time. This enables the control system to strengthen control and suppress repeated frost in a timely manner when the corner coverage is reduced, the cold bridge effect is significant or the jet is difficult to reach, thereby improving the recovery speed and long-term stability of the glass corner field of view.

[0010] (3) This solution reuses the same set of basic monitoring parameters (indoor temperature and humidity, duct outlet temperature and humidity, valve opening, branch pressure, channel status and image indicators) in multiple stages: temperature and humidity are used for both dew point calculation and operating condition determination; valve opening and branch pressure are used for both airflow dominance coefficient and effective dew point correction and air source quota and execution quantity constraint; image residual frost index is used not only to determine whether it is necessary to strengthen (defrost / temperature control) but also to determine whether it is allowed to downgrade to maintain operation; this multi-parameter reuse reduces the need for additional sensors and new wiring, while forming a consistent data closed loop between risk assessment, resource allocation and strategy adjustment, improving control interpretability and engineering deployability, and reducing system transformation costs and maintenance complexity.

[0011] (4) Compared with the common existing process that is only based on indoor temperature and humidity / dew point threshold triggering and then simply linked to heating or air curtain, this solution adopts a combined control mechanism of effective dew point (boundary layer fusion), zoned equivalent temperature (zone recursion), air source output limit (maximum / minimum constraint), and image residual frost closed loop (corner correction) at the control level: on the one hand, it avoids directly equating the overall indoor dew point with the glass boundary layer state, which would cause misjudgment and response lag; on the other hand, it can perform executable scheduling of output capacity within constraints in the scenario where the public air source is limited, and suppress corner repetition and strategy jitter through residual frost feedback, thereby achieving higher control accuracy, stronger adaptability and more reliable vision guarantee effect under complex environmental changes, while taking into account energy consumption and resource occupation. Attached Figure Description

[0012] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0013] Figure 1 This is a schematic diagram of the system module connections of the present invention.

[0014] Figure 2 This is a schematic diagram of the glass monitoring structure in the driller's cabin.

[0015] Figure 3 This is a schematic diagram illustrating the principle of glass monitoring in the driller's booth.

[0016] Figure 4 This is a schematic diagram of the glass partitions in the driller's cabin.

[0017] Reference numerals in the attached diagram: 1. Compressed air source; 2. Air source treatment assembly; 3. Flow regulating valve; 4. Vortex tube; 5. Cold end outlet; 6. Hot end outlet; 7. Two-position five-way solenoid valve; 8. Indoor defrosting duct; 9. Exhaust duct; 10. Driller's cabin glass; 11. Temperature sensor; 12. Humidity sensor; 13. Controller. Detailed Implementation

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0019] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0020] In this embodiment of the invention, the specific implementation of the intelligent monitoring process for the driller's cabin glass is as follows: Figure 2 , Figure 3 As shown, Figure 2 A schematic diagram of the glass monitoring structure in the driller's cabin. Figure 3This is a schematic diagram of the drilling crew cabin glass monitoring principle. The control system uses compressed air source 1 in the drilling crew cabin as power. After purification and pressure stabilization by air source treatment component 2, the air supply intensity is adjusted by flow regulating valve 3 and sent into vortex tube 4. Vortex tube 4 forms cold end outlet 5 and hot end outlet 6 respectively. Controller 13 receives environmental signals from temperature sensor 11 and humidity sensor 12, drives two-position five-way solenoid valve 7 to switch between cold end outlet 5 and hot end outlet 6, and introduces the selected airflow into indoor defrosting duct 8 to form a directional air curtain along the inner side of glass 10. At the same time, it is discharged through exhaust duct 9, realizing anti-fogging blowing of glass 10 in summer and defrosting and heating of glass 10 in winter, thereby ensuring clear visibility and operational safety of the drilling crew cabin front window.

[0021] Example 1: See Figure 1 As shown, this embodiment of the invention provides a technical solution: an intelligent defrosting control system for driller's cabin glass driven by temperature and humidity data, including an effective dew point determination module, a frost risk determination module, a gas source output limit module, and a defrosting control adjustment module.

[0022] The effective dew point determination module is connected to the frost risk determination module, the frost risk determination module is connected to the gas source output limit module, and the gas source output limit module is connected to the defrost control adjustment module.

[0023] The known intelligent defrosting monitoring component uses a controller as its core. After receiving environmental signals from temperature and humidity sensors, it determines the operating condition and activates an airflow switching device to switch between the cold and hot ends of the vortex tube. In this embodiment, the airflow switching device uses a two-position five-way solenoid valve to allow the selected airflow to blow through the indoor defrosting duct onto the driller's cabin glass surface, thereby maintaining the visibility of the glass. Specifically, when the operating condition is determined to be high temperature and high humidity in summer, it enters anti-fog mode and activates the cold end output to form a low-temperature, dry airflow for blowing. When the operating condition is determined to be low temperature in winter, it enters defrosting mode and activates the hot end output to form a high-temperature airflow for blowing. Thus, anti-fog and defrosting are two different operating modes of the same monitoring component under different conditions.

[0024] In terms of control logic and execution mechanism, the main process of the execution method of this invention in defogging and defrosting is universal, and both follow a closed-loop link of sensor acquisition - controller determination - drive solenoid valve switching - blowing the glass through the air duct. The core execution objective of this invention is to defrost the glass of the driller's cabin: In winter, the controller determines to enter the defrosting mode based on the temperature sensor signal and drives the two-position five-way solenoid valve to switch, so that the hot end outlet of the vortex tube is connected to the indoor defrosting air duct leading to the glass; the high-temperature airflow continuously blows the glass surface to melt the frost and evaporate the moisture, thereby restoring clear visibility.

[0025] The effective dew point determination module is used to receive initial data from the multi-source monitoring system of the driller's cabin in real time through the intelligent defrosting monitoring component, perform data preprocessing, and calculate the dew point based on the preprocessed temperature and humidity data to obtain the effective dew point of the driller's cabin glass.

[0026] The initial data from the multi-source monitoring system for the aforementioned driller's cabin includes real-time temperature and humidity data for the driller's cabin, real-time image data of the driller's cabin glass, and the current execution status data of the defrosting-related equipment in the driller's cabin.

[0027] Real-time temperature and humidity datasets are obtained through monitoring by temperature and humidity sensors. Temperature sensors detect the external ambient temperature of the driller's cabin, while humidity sensors detect the internal humidity. Real-time image data is collected by monitoring cameras in the driller's cabin and transmitted to the image data processing unit of the intelligent defrosting monitoring component to identify residual frost in the glass corner areas. The current execution status dataset of the defrosting-related equipment in the driller's cabin can be extracted from the execution records of each device.

[0028] The data preprocessing specifically involves the controller performing validity checks, median filtering, abrupt change marking, and light smoothing on the real-time temperature and humidity data stream {T(t), RH(t)} (T(t) represents the real-time temperature data stream; RH(t) represents the real-time humidity data stream) of the driller's cabin according to the sampling time t. First, the validity of the current sampled value is checked. If it meets the preset physical range (e.g., T...), the data is processed accordingly. min ≤T(t)≤T max 0≤RH(t)≤100%, where T min T max (These represent preset physical maximum and minimum temperatures) and the variation range does not exceed a reasonable transition threshold (e.g., |T(t)-T(t-∆t)|≤∆T). max RH(t)-RH(t-∆t)|≤∆RH max Where ∆t represents the sampling interval, ∆T max ∆RH max If the maximum allowable temperature jump and the maximum allowable humidity jump are respectively represented, the data is considered valid and enters the median filter. The median filter uses a sliding window of length 2k+1 to remove spikes from the valid data, where k represents the window radius (used to control the range of the number of data points selected before and after). The window length is 2k+1. For example, if k=1, three points are considered (the previous point, the current point, and the next point / or historical points are used to obtain the result. , . , These represent the results of temperature and humidity after median filtering, respectively. `median{·}` represents the median, which means sorting the data in the window from smallest to largest and taking the middle number.

[0029] Then, mutation labeling is performed on the filtering results. or , where Θ T Θ RH Let temperature and humidity be the threshold values ​​for abrupt changes, respectively. A mutation marker m(t) is generated, where m(t) = 1 if the temperature and humidity at that moment are considered abrupt / abnormal / unstable, and m(t) = 0 otherwise. Finally, a light smoothing process is performed on the non-mutated data to form the control input, such as exponential smoothing. , T f (t), RH f (t) represent the smoothed temperature and smoothed humidity, respectively, and λ represents the set smoothing coefficient. When m(t)=1, to avoid abrupt changes contaminating the smoothing results, a freeze or fast follow strategy can be adopted (e.g., let T...). f (t)=T f (t-∆t) or let λ=λ fast , λ fast This indicates a larger smoothing factor (such as 0.7 or 0.8) used for fast following, to facilitate rapid adjustment during abrupt changes.

[0030] For real-time temperature and humidity data that fail the validity check, the controller does not enter the median filtering stage but directly sets the mutation flag m(t)=1 and records the sampled value as an abnormal sample for robust determination of subsequent control strategies.

[0031] The effective dew point of the driller's cabin glass was analyzed in the following way: The real-time temperature and humidity dataset of the driller's cabin is extracted, including the real-time temperature and humidity inside the driller's cabin. These are then used together in the dew point calculation expression to obtain the dew point temperature inside the driller's cabin.

[0032] In this embodiment, the controller obtains the real-time temperature T inside the driller's cabin from the temperature and humidity sensor. in，f (t) and relative humidity RH in，f (t), and substituting the above temperature and humidity into the dew point calculation expression, we obtain the dew point temperature T in the driller's cabin. dew，in (t); for example, a Magnus-type approximation can be used: let , γ(t) is an intermediate quantity in the dew point calculation, and a and b are preset constants (consistent with the temperature unit). This enables real-time estimation of the critical temperature for water vapor condensation in the driller's cabin, providing a reference input for subsequent effective dew point fusion.

[0033] The real-time temperature and humidity at the defrost duct outlet are extracted and substituted into the dew point calculation expression to obtain the dew point temperature at the defrost duct outlet.

[0034] In this embodiment, the controller obtains the real-time temperature T at the outlet of the indoor defrosting duct from temperature and humidity measuring points located at the outlet of the duct. out (t) and relative humidity RH out (t), and substitute both temperature and humidity into the same dew point calculation expression to obtain the dew point temperature T at the defrost duct outlet. dew，out (t); for example, a Magnus-type approximation can be used: let The dew point at the duct outlet reflects the humidity of the purge airflow itself and serves as a dew point reference when the boundary layer near the glass is dominated by the purge airflow.

[0035] An airflow dominance coefficient is introduced, and the effective dew point of the driller's cabin glass is obtained by combining the dew point temperature inside the driller's cabin with the dew point temperature at the defrost duct outlet.

[0036] In this embodiment, to characterize the degree to which the boundary layer air near the glass is dominated by the airflow from the defrosting duct outlet, an airflow dominance coefficient α(t)∈[0,1] is introduced, and the dew point temperature T inside the driller's cabin is used as the reference value. dew，in (t) and the dew point temperature T at the duct outlet dew，out (t) is correlated and merged according to α(t) to obtain the effective dew point of the driller's cabin glass. For example, using a linear mixed form: When α(t) approaches 1, it means that the area near the glass is mainly affected by the dry purging airflow, and the effective dew point is closer to the dew point at the air duct outlet. When α(t) is smaller, it means that the proportion of indoor humid air mixed in is higher, and the effective dew point is closer to the dew point in the driller's room, so that the frost risk assessment is more consistent with actual working conditions such as edge corner coverage attenuation.

[0037] The analysis process for the airflow dominance coefficient is as follows: The current execution status dataset of the defrosting-related equipment includes the current valve opening of the flow control valve and the current outlet pressure of the air source processing component. The valve opening is used to characterize the airflow intensity level entering the vortex tube and exiting through the air duct, and the outlet pressure is used to characterize the sufficiency of branch air supply and the air supply capacity boundary, providing input for subsequent mapping calculations of constraint factors.

[0038] Based on the pre-defined mapping relationship in the database, the current valve opening of the flow control valve and the current outlet pressure of the air source processing component are mapped to the first limiting factor and the second limiting factor of airflow dominance, respectively.

[0039] Based on the airflow dominance limiting factor, the minimum value is denoted as the airflow dominance coefficient. When the valve opening is too small, resulting in insufficient coverage, the first limiting factor becomes the limiting term; when the gas source pressure is too low, resulting in insufficient gas supply, the second limiting factor becomes the limiting term. This makes the airflow dominance coefficient more sensitive to changes in the actual purging dominance capability, thereby enabling the effective dew point to adaptively adjust according to the execution state and gas supply conditions.

[0040] Through the above steps, this solution can convert the temperature and humidity inside the driller's cabin and the temperature and humidity at the defrosting duct outlet into dew point temperatures that directly reflect the critical conditions for frost formation, without adding additional complex sensor deployments. This achieves simultaneous quantification of the indoor humid air risk benchmark and the drying capacity of the purging airflow. Furthermore, an airflow dominance coefficient is introduced, and two limiting factors are mapped based on the flow control valve opening and the outlet pressure of the air source processing component. The minimum value is used to form a bottleneck constraint, allowing the effective dew point to adaptively correct in real time according to changes in valve opening and air supply sufficiency. This avoids overly optimistic estimations of the glass boundary layer's moisture content when air supply is insufficient or airflow coverage is inadequate. Therefore, frost risk assessment and defrosting strategy generation can be based on an effective dew point that more closely reflects the actual microenvironment of the glass. This improves the risk sensitivity and response reliability to areas prone to residual frost, such as edges and corners, while maintaining the stability and interpretability of the control strategy under limited air supply conditions, reducing adverse effects such as repeated defrosting, energy waste, and delayed field of view recovery.

[0041] The frost risk assessment module defines the driller's cabin glass area into zones using the intelligent defrosting monitoring component, estimates the equivalent temperature of each glass zone, and assesses the frost risk by comparing it with the effective dew point of the driller's cabin glass.

[0042] The aforementioned drilling crew cabin glass area zoning can be divided into three functional zones from the outside in, based on the likelihood of frost formation, as detailed below. Figure 4 As shown. Figure 4 In the diagram, four rectangular areas labeled a1, a2, a3, and a4 correspond to the edge areas at the four corners of the glass window and are defined as Glass Area 1 (corner edge area); four strip-shaped areas labeled b1, b2, b3, and b4 are located at the top, left, right, and bottom edges of the glass, respectively, avoiding the corner areas, and are defined as Glass Area 2 (edge ​​non-corner area); the area c located in the center and indicated by a dashed boundary is the main body of the central part of the glass and is defined as Glass Area 3 (center area). Through this corner, edge, and center zoning method, different equivalent temperature estimates, control intensities, and maintenance strategies can be set for the risk differences between areas a, b, and c in subsequent frost risk assessment and defrosting strategy control, achieving differentiated defrosting control that better suits the frost characteristics of different parts of the glass.

[0043] The equivalent temperature of each glass partition is estimated, and the specific analysis process is as follows: The current execution status dataset of the defrosting-related equipment also includes the current channel status of the airflow switching device. The current purging mode Mode(t) is determined based on the current channel status s7(t) of the airflow switching device. For example, when s7(t) connects the cold end outlet of the vortex tube to the indoor defrosting duct, it is determined to be the cold end purging mode; when s7(t) connects the hot end outlet of the vortex tube to the indoor defrosting duct, it is determined to be the hot end purging mode; and when they are not connected, it is determined to be the stop-blowing / maintain mode.

[0044] The channel status includes cold end outlet and hot end outlet. The purging modes include cold end purging mode, hot end purging mode, and stop / maintain purging mode.

[0045] The controller further determines the flow control valve's current valve opening degree u. v (t), according to the mapping relationship set in the controller database, classify or map the current purging intensity Level(t) to an intensity level (such as low / medium / high).

[0046] The controller selects from a preset set of purging parameters based on the current purging mode and purging intensity. (in , , All represent the hot-end heating rate, and L / M / H represent different purging intensities. This represents the equivalent rate of change under cold-end purging. The corresponding zone temperature change rate is selected from the (representing the stop-blowing / maintenance rate) and the equivalent temperature estimate of each zone is recursively updated to obtain the equivalent temperature estimate of each glass zone. , .

[0047] in Δt represents the estimated equivalent temperature of the i-th glass section at time t. The equivalent temperature is not the actual temperature measured at a point on the glass, but rather the temperature that the controller calculates based on the current purging status and that represents the overall thermal state of the section. g is the identifier of glass / glass-related variables, i is the section number, and Δt is the time step / period for one update by the controller. It is the estimated equivalent temperature of this partition in the next control cycle (the next update time); Let be the rate of temperature change of glass partition i at time t; Select( The mode-intensity rate selection rule or lookup table function allows the corner edge area, non-corner edge area, and center area to correspond to different heating / cooling rates. This enables the acquisition of equivalent temperature estimates for each glass zone as a function of the purging mode and purging intensity without the need to install temperature measuring elements at each point on the glass. These estimates are then used for subsequent margin calculations with the effective dew point and for determining the risk of frost formation.

[0048] The estimated equivalent temperature of each glass zone is compared with the effective dew point of the driller's cabin glass to determine the risk of frost formation.

[0049] In this embodiment, the controller directly maps the solenoid valve channel state and valve opening and other execution states to the zone temperature change rate, so that the update of the glass temperature state corresponds one-to-one with the actual purging conditions, avoiding the lag in response to the glass thermal state caused by relying solely on ambient temperature and humidity. By configuring different rate parameters for the glass corner edge area, non-corner edge area and center area and selecting them by mode-intensity-zone lookup table, the differences in the impact of cold bridge and coverage attenuation on the edge corners can be naturally reflected, thereby improving the risk sensitivity and control targeting of areas prone to residual frost. The zone equivalent temperature estimate is obtained by recursive update, which can obtain a temperature characterization that can be used for margin calculation without the need to deploy additional temperature measuring elements at each point of the glass, reducing hardware modification costs and improving system deployability. The zone equivalent temperature and effective dew point are combined to determine the frost risk, which can provide a more stable and interpretable state input for the minimum constraint setting and adaptive adjustment of the subsequent defrosting strategy, thereby reducing repeated defrosting, shortening the field of view recovery time, and taking into account energy consumption and control stability under limited air supply conditions.

[0050] The specific analysis process for determining the risk of frost formation is as follows: The estimated equivalent temperature of each glass zone is compared with the effective dew point of the driller's cabin glass to obtain the frost margin of each glass zone. The frost margin is then compared with a predefined frost margin reference value, which represents the baseline value corresponding to the pre-set frost margin. If the frost margin of a glass zone is less than or equal to the frost margin reference value, the glass zone is determined to have a risk of frost formation.

[0051] The glass zone with the smallest frost margin among the zones with a risk of frost is designated as the frost-marking zone.

[0052] The air source output limit module is used by the intelligent defrosting monitoring component to limit the output of branch air sources based on the defrosting risk assessment result and in conjunction with the air source processing component. The intelligent defrosting monitoring component then performs defrosting control based on the limit result.

[0053] The output of the branch air source is limited, and the specific analysis process is as follows: The difference between the frost margin of the frost mark zone and the frost margin reference value is extracted and recorded as the frost margin deviation of the frost mark zone. The outlet limiting pressure of the gas source treatment component is then matched to obtain the result.

[0054] The ratio of the frost margin deviation of the frost mark zone at the current time point to the frost margin deviation of the frost mark zone at the previous time point is used to determine whether to correct the outlet limiting pressure of the gas source processing component based on the ratio result.

[0055] The above ratio processing yields the deviation change rate of the frosting indicator zone, which is compared with the predefined deviation threshold change rate. If the deviation change rate of the frosting indicator zone is less than the deviation threshold change rate, it is determined that the outlet limit pressure needs to be corrected. The limit pressure adjustment factor is matched according to the deviation change rate of the frosting indicator zone, and multiplied by the outlet limit pressure to obtain the corrected outlet limit pressure, which is recorded as the minimum output value of the branch air source. Otherwise, it is determined that no correction of the outlet limit pressure is required.

[0056] The outlet limiting pressure of the air source processing component is recorded as the maximum output value of the branch air source, which, together with the rated minimum output value of the branch air source, forms the branch air source output constraint.

[0057] The branch air source refers to the compressed air supplied from the driller's room, which forms the air supply branch in this control system. The compressed air first enters the air source processing component for filtration, pressure stabilization, and removal of impurities and condensate. The processed air is then sent from the outlet of the air source processing component to the inlet of the flow regulating valve. The controller controls the air supply of the branch by adjusting the opening of the flow regulating valve, so that the outlet airflow of the flow regulating valve is supplied to the vortex tube as a power source according to the set intensity, thereby providing a stable and controllable air source input for subsequent cold / hot end airflow output and glass purging.

[0058] The intelligent defrost monitoring component performs defrost control, and the specific analysis process is as follows: The required air volume parameter of the frost-marked zone is obtained by matching the frost margin of the frost-marked zone and compared with the output capacity parameter of the branch air source. If the required air volume parameter is less than or equal to the output capacity parameter, the controller performs defrosting based on the required air volume parameter.

[0059] The required gas volume parameters include at least one of the following: the minimum valve opening of the flow control valve, the minimum duration of the hot-end output of the airflow switching device, or the minimum duty cycle. The duty cycle is expressed as the proportion of the actual on time of the hot-end (or cold-end) airflow output to the total time of the cycle within a fixed control cycle.

[0060] The output capacity parameter is the upper limit of the maximum output intensity that the branch air source is allowed to provide under the output constraint of the branch air source. The upper limit of the maximum output intensity includes at least one of the following: the maximum valve opening of the flow regulating valve, the maximum duration of the hot end output of the airflow switching device, or the maximum duty cycle.

[0061] In one specific embodiment: Scene setting: Frost indicator zone: Glass area 1 (corner edge area); The current frost margin for this zone is: ΔT1(t) = −0.8℃ (meaning the glass equivalent temperature is 0.8℃ lower than the effective dew point, indicating a high risk). Preset safety margin: θ safe =2℃; Objective: In T resp = Bring the margin back to a safe range within 60 seconds.

[0062] The controller has a pre-defined "margin recovery capacity table" (example): Flow control valve opening 30% + airflow switching device hot end duty cycle 30% → slow margin recovery; Flow control valve opening 50% + airflow switching device hot end duty cycle 50% → medium; Flow regulating valve opening 70% + airflow switching device hot end duty cycle 70% → fast.

[0063] 1) Obtain the required gas volume parameters (minimum constraint) by matching the frost allowance. First, calculate "how much margin is needed": ΔT need =θ safe −ΔT1(t)=2−(−0.8)=2.8℃; Table lookup / rule matching (example matching rule): If ΔT need ≤1℃: Low demand (valve opening ≥30%, hot end duty cycle ≥30%) 1<ΔT need ≤2.5℃: Required (valve opening ≥50%, hot end duty cycle ≥50%); If ΔT need >2.5℃: High demand (valve opening ≥70%, hot end duty cycle ≥70%).

[0064] Because ΔT need =2.8℃>2.5℃, therefore the required gas volume parameter is obtained (it must include at least one of the two parameters; here we cite both as examples): minimum valve opening of the flow control valve u. min，req =70%; Minimum duty cycle of hot-end output D min，req =70%.

[0065] 2) Output capability parameters (maximum upper limit) are derived from branch output constraints. Assuming that compressed air is shared on-site, to avoid competing for air supply, the control system presets the branch output limit: the maximum valve opening u of the flow regulating valve. max =80%; Maximum duty cycle of hot end D max =80%.

[0066] 3) Comparison: Demand ≤ Output Capacity? Item-by-item comparison: u min，req =70%≤u max =80%; D min，req =70%≤Dmax =80%.

[0067] 4) The controller performs defrosting according to the required gas volume parameters (and is still subject to the maximum upper limit). When the controller generates and executes the strategy, it ensures that the output is at least as high as the minimum requirement constraint and does not exceed the maximum limit. For example, set the valve 3 opening to u(t)=70%, switch valve 7 to the hot end, output pulses according to the period Tp, and the duty cycle D(t)=70%. Execute continuously for 60 seconds, and then downshift or exit strong defrosting based on the subsequent margin recovery.

[0068] When the required gas volume parameter is determined to be greater than the output capacity parameter, the controller executes remedial control logic.

[0069] The above-mentioned remedial control logic is a timing-based remedial measure that switches the continuous maximum intensity output to a pulse duty cycle output and extends the total running time. After completing the above comparison and remedial logic, the controller generates a defrosting strategy and outputs executable control quantities in real time. The executable control quantities include at least the hot / cold end channel selection of the airflow switching device and its pulse period and duty cycle parameters, the position or opening of the flow regulating valve, and the corresponding strategy duration and holding time. The executable control quantities also satisfy the branch air source output constraints.

[0070] Based on the above specific embodiment scenario settings and the premise that 1) the required gas volume parameter obtained by matching the frost margin remains unchanged: 1) Setting the supply capacity parameter to a lower level → demand > supply occurs. Assuming that the compressed air supply is simultaneously occupied by other equipment, to ensure a common air source, the control system's preset branch output limit becomes stricter: maximum valve opening limit u max =50%; Maximum hot-end duty cycle upper limit D max =50%.

[0071] Comparison: u min，req =70%>u max =50%; D min，req =70%>D max =50%.

[0072] 2) Example of remedial logic Remedial objective: Without exceeding the upper limit (50% / 50%), restore the margin in the corner edge area to a safe level, or at least quickly stop the damage and prevent further frost formation. Because the upper limit is only 50%, the controller will lock the execution at the upper limit and extend the total defrosting time. Actual valve opening u(t) = u max =50%; Actual hot-end duty cycle D(t) = D max =50%; at the same time, the response time is increased from 60s (for example) to T.resp =120s.

[0073] This means using more time to compensate for insufficient strength. In engineering terms, it's equivalent to: same total heat / drying amount = strength × time. If the strength decreases, the time is increased.

[0074] The defrost control adjustment module is used to intelligently execute defrost control through the controller, and at the same time identify residual frost at the edges and corners. Based on the identification results, it adaptively adjusts the defrost control process to complete the intelligent defrost control process of the driller's cabin glass.

[0075] Edge corner residual frost recognition, the specific recognition process is as follows: The real-time image data of the driller's cabin glass includes the real-time grayscale values ​​of each pixel in the current frame of the glass grayscale image. The contrast index, edge sharpness index, and whitening ratio of the glass grayscale image in the current frame are obtained by performing basic image frame calculations.

[0076] In the current grayscale frame, the image data processing unit extracts the grayscale matrix I of the glass target region. t (x, y), where (x, y) are the pixel coordinates within the glass target area. The contrast ratio can be represented by the grayscale standard deviation, i.e., first calculate the grayscale mean of the glass target area, then calculate the grayscale variance and take the square root to obtain the contrast ratio. When residual frost on the glass causes the image to appear white, gray, and with weakened details, the grayscale distribution of the glass target area converges, and the contrast ratio usually continues to decrease, thus it can be used for residual frost identification and judgment.

[0077] In the current grayscale frame, the image data processing unit performs edge response calculations on the grayscale matrix of the glass target area to obtain the pixel gradient or second-order derivative response, and uses its energy / variance as a sharpness indicator. When glass frosting smooths out the edges and textures, the high-frequency components decrease, and the sharpness indicator will significantly decrease, thus it can be used to characterize whether the edges are blurred.

[0078] In the current grayscale frame, the whitening ratio is used to quantify the proportion of pixels that are persistently white and lack texture within the glass target area. The image data processing unit first sets a brightness threshold τI and a texture threshold τT, where τI is used to determine whether a pixel is too bright or white, and τT is used to determine whether a pixel lacks texture (using the grayscale gradient magnitude ||I| of the pixel at coordinate (x,y) at time t). t (x, y) | represents texture intensity); when a pixel simultaneously satisfies I t A pixel is considered a whitened pixel when (x, y) ≥ τI and ||It(x, y)| ≤ τT. Let N be the total number of whitened pixels within the glass target area. white If the total number of pixels in the glass target area is N, then the whitening ratio is: W t =N white / N,N white=#{(x, y)∣I t (x, y)≥τI∧∣∇It(x, y)∣≤τT}, where W t The whitening ratio for the current frame, #{ } represents the pixel count that meets the conditions; this definition can simultaneously constrain image brightness and low image texture, thereby reducing misjudgments caused by normal reflective bright areas and making the whitening ratio closer to the local whitening characteristics caused by residual frost / fog.

[0079] The presence of residual frost at the edges and corners is determined by using contrast index, edge sharpness index, and whitening ratio.

[0080] When the identification result indicates the presence of residual frost, the controller performs adaptive adjustments to the current defrosting control process. The adaptive adjustments include at least: adjusting the output valve opening of the flow regulating valve and / or adjusting the duty cycle or duration of the hot end output of the airflow switching device, provided that the output of the branch air source does not exceed the constraint. The controller also adjusts the defrosting duration or switches to pulse duty cycle control.

[0081] The controller first calculates the frosting margin gap ΔT for the frosting indicator zone. need (t)=max(0,θ) safe −ΔT min (t)), and combined with the change in the whitening ratio ΔW(t)=W t -W t−Δt The change in edge sharpness ΔE(t) = E t -E t−Δt Generate the residual frost severity level S(t), where W t−Δt E represents the whitening percentage of the frosting marker zone at time (t-Δt); t E represents the edge sharpness of the frosting marker at time t. t−Δt The edge sharpness of the frost marker zone at time (t-Δt) is represented. Using a pre-defined mapping relationship in the database, the severity level of residual frost is obtained by mapping the change in whitening ratio to the change in edge sharpness. Subsequently, based on S(t) and ΔT... need (t) Select the corresponding increment from the preset step size set and limit the increment of the execution quantity: increase the current valve opening u(t) of the flow control valve in increments of Δu(t)∈{5%,10%,15%} and limit it to u(t+)=min(u(t)+Δu(t), u max ), where u max The maximum valve opening is limited by the output constraint; and the hot-end output duty cycle D(t) of the airflow switching device is increased in increments of ΔD(t)∈{5%, 10%, 15%} and limited to D(t+)=min(D(t)+ΔD(t), D max ), or the hot-end output duration thot (t) with Δt hot The step size of (t)∈{5s, 10s, 20s} is extended and limited to t. hot (t+)=min(t hot (t)+Δt hot (t), t hot，max Meanwhile, to compensate for insufficient defrosting caused by limited gas supply or reduced corner coverage, the controller progressively extends the total defrosting duration T in increments of ΔText(t)∈{10s, 30s, 60s}. total (t+)=T total (t)+ΔT ext (t), or switch the continuous hot-end output to a periodic output T. p The pulse duty cycle is controlled; after each adjustment, the controller continues to acquire image indicators and update the residual frost recognition results until the residual frost is eliminated and the stable holding conditions are met (the stable holding conditions are specifically: no residual frost is detected, the indicator does not continue to increase, the margin is met, and the stability is maintained for a period of time T). hold After a few seconds, it enters the downshift maintenance phase, thereby achieving adaptive enhanced defrosting control of residual frost without exceeding the maximum limit of the branch air source. Example 2:

[0082] Under the condition that other conditions remain unchanged in Example 1, the above-mentioned airflow dominance coefficient α(t) can be obtained not only by using the minimum short-board constraint method from the first airflow dominance limiting factor α1(t) and the second airflow dominance limiting factor α2(t), but also by using a product fusion method. That is, the controller performs a product-type synthesis on the two limiting factors to characterize the degree to which the two limiting factors are simultaneously satisfied, for example, according to α(t)=α1(t). w1 *α2(t) w2 (Where w1 and w2 are preset weights in the database and satisfy w1+w2=1) Determine the airflow dominance coefficient, or in a simplified embodiment, directly take α(t)=α1(t)*α2(t); Through this product fusion method, when either the coverage capacity corresponding to the valve opening or the air supply sufficiency corresponding to the branch pressure decreases, α(t) will decrease synchronously, thereby achieving a continuous and smooth characterization of the dominance without introducing a limiting factor to take the minimum value hard switch, and is used for the subsequent dynamic correction of the effective dew point.

[0083] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A smart defrosting control system for driller's cabin glass based on temperature and humidity data, characterized in that, include: The effective dew point determination module is used to receive initial data from the multi-source monitoring of the driller's cabin in real time through the intelligent defrosting monitoring component, perform data preprocessing, and calculate the dew point based on the preprocessed temperature and humidity data to obtain the effective dew point of the driller's cabin glass. The frost risk assessment module is used to define the glass area of ​​the driller's cabin by partitioning it through the intelligent defrosting monitoring component, estimate the equivalent temperature of each glass partition, and assess the frost risk by comparing it with the effective dew point of the driller's cabin glass. The air source output limit module is used to limit the output of branch air sources in conjunction with the air source processing component based on the frost risk assessment result. The intelligent defrost monitoring component performs defrost control based on the limit result. The defrost control adjustment module is used to intelligently execute defrost control through the controller, and at the same time identify residual frost at the edges and corners. Based on the identification results, it adaptively adjusts the defrost control process to complete the intelligent defrost control process of the driller's cabin glass. The effective dew point of the driller's cabin glass was analyzed in the following manner: The real-time temperature and humidity dataset of the driller's cabin is extracted, including the real-time temperature and humidity inside the driller's cabin. These are then substituted into the dew point calculation expression to obtain the dew point temperature inside the driller's cabin. The real-time temperature and humidity at the defrost duct outlet are extracted and substituted into the dew point calculation expression to obtain the dew point temperature at the defrost duct outlet. An airflow dominance coefficient is introduced, and the effective dew point of the driller's cabin glass is obtained by combining the dew point temperature inside the driller's cabin with the dew point temperature at the defrost duct outlet. The specific analysis process for the airflow dominance coefficient is as follows: The current execution status dataset of the defrosting associated equipment includes the current valve opening of the flow control valve and the current outlet pressure of the air source processing component; The current valve opening of the flow control valve and the current outlet pressure of the air source processing component are mapped to the first limiting factor and the second limiting factor of airflow dominance, respectively, and the minimum value of the two is recorded as the airflow dominance coefficient.

2. The intelligent defrosting control system for driller's cabin glass based on temperature and humidity data as described in claim 1, characterized in that, Includes the following steps: The initial data from the multi-source monitoring system of the driller's cabin includes the real-time temperature and humidity dataset of the driller's cabin, the real-time image data of the driller's cabin glass, and the current execution status dataset of the defrosting-related equipment of the driller's cabin. The data preprocessing is specifically performed as follows: The real-time temperature and humidity dataset in the driller's cabin is sequentially subjected to validity checks, median filtering, mutation labeling, and light smoothing. Real-time temperature and humidity data that fail the validity check are directly subjected to mutation labeling.

3. The intelligent defrosting control system for driller's cabin glass based on temperature and humidity data as described in claim 1, characterized in that, Includes the following steps: The specific analysis process for estimating the equivalent temperature of each glass partition is as follows: The current execution status dataset of the defrosting associated equipment also includes the current channel status of the airflow switching device, and the current purging mode is determined based on the current channel status of the airflow switching device. The current purging intensity is determined based on the current valve opening of the flow regulating valve. The controller selects the corresponding zone temperature change rate from the preset rate parameter set according to the current purging mode and the current purging intensity, and recursively updates the equivalent temperature estimate of each zone to obtain the equivalent temperature estimate of each glass zone. The risk of frost formation is determined based on the estimated equivalent temperature of each glass zone and the effective dew point of the driller's cabin glass.

4. The intelligent defrosting control system for driller's cabin glass based on temperature and humidity data as described in claim 3, characterized in that: The specific analysis process for determining the risk of frost formation is as follows: The equivalent temperature estimate of each glass zone is compared with the effective dew point of the driller's cabin glass to obtain the frost margin of each glass zone. The frost margin of a glass zone is compared with the predefined frost margin reference value. If the frost margin of a glass zone is less than or equal to the frost margin reference value, the glass zone is determined to have a risk of frost. The glass partition with the smallest frost margin among those with a risk of frost is designated as the frost-marking partition.

5. The intelligent defrosting control system for driller's cabin glass based on temperature and humidity data as described in claim 4, characterized in that, Includes the following steps: The specific analysis process for limiting the output of the branch air source is as follows: Extract the difference between the frost margin of the frost mark zone and the frost margin reference value, and record it as the frost margin deviation of the frost mark zone. Match it to obtain the outlet limiting pressure of the gas source treatment component. The ratio of the frost margin deviation of the frost mark zone at the current time point to the frost margin deviation of the frost mark zone at the previous time point is processed, and the result of the ratio processing is used to determine whether to perform correction on the outlet limiting pressure of the gas source processing component. The outlet limiting pressure of the air source processing component is recorded as the maximum output value of the branch air source, which, together with the predefined rated minimum output value of the branch air source, forms the branch air source output constraint.

6. The intelligent defrosting control system for driller's cabin glass based on temperature and humidity data as described in claim 1, characterized in that, Includes the following steps: The intelligent defrosting monitoring component performs defrosting control, and the specific analysis process is as follows: The required air volume parameter of the frost mark zone is obtained by matching the frost margin of the frost mark zone, and compared with the output capacity parameter of the branch air source. If the required air volume parameter is less than or equal to the output capacity parameter, the controller performs defrosting based on the required air volume parameter. When the required gas volume parameter is determined to be greater than the output capacity parameter, the controller executes remedial control logic.

7. The intelligent defrosting control system for driller's cabin glass based on temperature and humidity data as described in claim 6, characterized in that: The required gas volume parameters include at least one of the following: the minimum valve opening of the flow regulating valve, the minimum duration of the hot end output of the airflow switching device, or the minimum duty cycle. The output capacity parameter is the upper limit of the maximum output intensity that the branch air source is allowed to provide under the output constraint of the branch air source. The upper limit of the maximum output intensity includes at least one of the following: the maximum valve opening of the flow regulating valve, the maximum duration of the hot end output of the airflow switching device, or the maximum duty cycle.

8. The intelligent defrosting control system for driller's cabin glass based on temperature and humidity data as described in claim 1, characterized in that, Includes the following steps: The specific process for identifying residual frost at the edge corners is as follows: The real-time image data of the driller's cabin glass includes the real-time grayscale value of each pixel in the current frame of the glass grayscale image. The contrast index, edge sharpness index and whitening ratio of the glass grayscale image in the current frame are obtained by performing basic image frame calculations. The contrast index, edge sharpness index, and whitening ratio are used to determine whether there is residual frost at the edge corners. When the identification result indicates the presence of residual frost, the controller performs adaptive adjustments to the current defrosting control process. The adaptive adjustments include at least: increasing the output valve opening of the flow regulating valve and / or increasing the duty cycle or duration of the hot end output of the airflow switching device, provided that the output of the branch air source is not constrained, and extending the defrosting duration or switching to pulse duty cycle control.

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