Non-electric variable adjustment method for temperature and humidity of an environment in which a golden potted plant grows

Abstract

The present application relates to the technical field of facility agriculture environment control, and discloses a non-electric variable adjustment method for temperature and humidity of an anaphalis contorta growing environment, which comprises the following steps: collecting dry-bulb temperature and relative humidity and calculating real-time dew point temperature to generate a dew point approximation index; when the dry-bulb temperature is higher than a set value and triggers cooling, monitoring the relationship between the index and a safety defense threshold; when the index is lower than the threshold, locking the permission of humidifying and driving ventilation; when the index is higher than the threshold, unlocking the permission and limiting the humidifying output according to the dry-bulb temperature drop rate, so that the dew point rise rate is lower than the dry-bulb temperature drop rate. Through the establishment of the dew point defense boundary and the asynchronous decoupling control logic, the present application solves the transient condensation problem caused by the response time constant mismatch in the multivariable coupling system, eliminates the leaf surface micro-condensation risk, and realizes the high-precision non-destructive regulation and control of the anaphalis contorta growing environment.

Description

TECHNICAL FIELD

[0001] The present application relates to a non-electric variable adjustment method for the temperature and humidity of the growth environment of Anoectochilus roxburghii, belonging to the technical field of facility agriculture environment control. BACKGROUND

[0002] In the current facility agriculture environment control, Anoectochilus roxburghii crops need to maintain a high-humidity and weak-light growth environment to ensure quality. The existing technology mostly uses a closed-loop adjustment system based on a negative feedback mechanism. The system uses distributed point temperature and humidity sensors in the greenhouse space to collect parameters, calculates the deviation through an algorithm, drives the ventilation and humidification actuators to act, and corrects the environmental dry-bulb temperature and relative humidity. This type of system assumes that the data collected by the sensors at the point represents the overall state of the controlled object, and the output response characteristics of the actuators remain linear over a long period of time. In the high-humidity and static wind steady-state control scenario of Anoectochilus roxburghii, the general control method based on point sampling and linear model has limitations. Anoectochilus roxburghii plants are short and limit air flow velocity. In the long-term quasi-steady environment, a layer of relatively static water vapor-rich boundary layer is easily formed on the leaf surface due to transpiration and limited air diffusion capacity.

[0003] A relatively static water vapor-rich boundary layer is formed between the leaf surface and the ambient air, and the data read by the sensors suspended in the environment deviates from the real state of the micro interface of the leaf surface. The monitoring data is decoupled from the micro physical situation in space, which leads to the fact that the control system cannot perceive the actual condensation risk in the leaf boundary layer when the sensor readings show safety, and induces stem rot disease. The core micro-mist nozzle and ventilation filter screen of the control loop are scaled in a long-term high-humidity and high-dust environment, which causes fouling and clogging or flux attenuation physical drift, leading to the failure of the control algorithm based on the fixed parameter model, causing system shock or degradation of the adjustment accuracy. Simply relying on the optimization of the spatial distribution of hardware sensors does not solve the problems of control strategy hysteresis and passivity. For example, the utility model patent with the publication number CN204390089U discloses a greenhouse temperature and humidity control device. The device obtains environmental signals through a collection circuit, compares the signals with the preset upper and lower limits of temperature and humidity through a single-chip microcomputer, and independently drives a relay to control the start and stop of heating or cooling equipment. Although this scheme constructs an automatic hardware loop, the core logic remains a linear threshold response to a single physical quantity, ignoring the strong coupling effect of thermodynamic parameters. In the high-humidity and static wind steady-state scenario of Anoectochilus roxburghii, the control based on the independent loop of macroscopic space parameters cannot penetrate the leaf retention boundary layer to perceive the real micro condensation risk, and it is difficult to adaptively compensate when the performance of the actuator decays over time, which makes the system prone to critical point shock or adjustment failure.

[0004] Therefore, it is a technical problem to be solved by the present application to construct an active detection method for the hidden state of the micro interface and to have an online adaptive calibration of the non-electric variable adjustment method for the physical drift of the actuator, so as to solve the problems of perception distortion and parameter mismatch. SUMMARY

[0005] To solve the problems raised in the background art, the technical scheme of the present application is as follows: a non-electric variable adjustment method for the temperature and humidity of the growth environment of Chrysopidium fortunei, which is executed based on an adjustment system comprising a ventilation unit, a humidification unit and a heating unit, and comprises the following steps:

[0006] Collecting dry-bulb temperature data and relative humidity data in the growth environment at a preset frequency, calculating real-time dew point temperature based on the dry-bulb temperature data and the relative humidity data, and generating a dew point approximation degree index representing the numerical difference between the dry-bulb temperature and the real-time dew point temperature;

[0007] When the dry-bulb temperature is higher than the target set value and triggers the cooling adjustment logic, the dew point approximation degree index is compared with a preset safety defense threshold in real time;

[0008] When the dew point approximation degree index is lower than the preset safety defense threshold, a first logic control instruction is generated, the first logic control instruction sets the lockout state flag of the humidification unit, and the ventilation unit is driven to perform a dry air exchange action until the dew point approximation degree index rises above the preset safety defense threshold;

[0009] When the dew point approximation degree index is higher than the preset safety defense threshold, a second logic control instruction is generated, the second logic control instruction resets the lockout state flag of the humidification unit, and calculates an output power upper limit value of the humidification unit based on the real-time falling rate of the dry-bulb temperature, and uses the output power upper limit value to clamp the amplitude of the driving signal of the humidification unit, so that the dew point temperature rising rate caused by the humidification action is always lower than the real-time falling rate of the dry-bulb temperature.

[0010] Preferably, the method further comprises an active diagnosis step for the microclimate boundary layer: monitoring the operating state of the adjustment system, generating a fluid disturbance instruction when the time length of the dry-bulb temperature and the relative humidity maintained in the target control dead zone reaches a preset threshold; driving the ventilation unit to perform a short-time pulsed air supply action according to the fluid disturbance instruction, the intensity of the air supply action being configured to be sufficient to cause convective mixing of the air in the environment and the crop surface boundary layer; collecting transient response data of the relative humidity in a high-frequency sampling mode during the execution of the air supply action, and calculating the positive jump amplitude of the transient response data relative to the reference value before the air supply action; comparing the positive jump amplitude with a preset boundary layer saturation threshold, and generating a dew point correction factor when the positive jump amplitude exceeds the boundary layer saturation threshold; using the dew point correction factor to increase the calculated value of the real-time dew point temperature, and using the increased real-time dew point temperature to trigger the first logic control instruction or the second logic control instruction.

[0011] Preferably, the method further comprises an adaptive calibration step of the latent heat coupling factor: recording an actual response trajectory of the dry-bulb temperature during a simple humidification action performed by the regulation system, calculating an actual state variation amount caused by the humidification action; calculating a theoretically expected variation amount of the dry-bulb temperature based on the current latent heat coupling factor and the humidification action control parameter; constructing a performance residual between the actual state variation amount and the theoretically expected variation amount, and performing statistical filtering processing on the performance residuals of a plurality of consecutive regulation cycles; when the processed performance residual exceeds a preset tolerance band, performing a reverse correction operation based on the polarity and amplitude of the performance residual to update the latent heat coupling factor; and generating a subsequent feed-forward compensation instruction for the humidification unit or the heating unit using the updated latent heat coupling factor to offset the influence caused by the physical performance drift of the humidification unit.

[0012] Preferably, the setting step of the preset safety defense threshold comprises: obtaining the flow rate data of the ambient air and the dry-bulb temperature value at the current time; calculating the minimum saturation difference required to maintain the interface moisture evaporation at the current flow rate based on a preset fluid heat quality exchange model; mapping the minimum saturation difference to a corresponding critical temperature difference value, and setting the critical temperature difference value as the preset safety defense threshold.

[0013] Preferably, the step of calculating the upper limit value of the output power of the humidification unit according to the real-time descending rate of the dry-bulb temperature follows the following constraint logic: in each control cycle, obtaining the real-time descending rate of the dry-bulb temperature ; calculating the partial derivative sensitivity of the dew point temperature to the humidification amount according to the current environmental state ; determining the maximum allowed output amount of the humidification unit according to the following relationship : , wherein, is a preset safety factor less than 1, used to ensure that the rising rate of the dew point temperature strictly lags behind the descending rate of the dry-bulb temperature.

[0014] Preferably, the first logic control instruction further comprises a dead zone asymmetric regulation logic: a hysteresis comparison link is introduced when judging whether to release the lockout state flag of the humidification unit; the threshold for releasing the lockout state flag is set as the preset safety defense threshold plus a preset hysteresis bandwidth, so that the condition for entering the lockout state is more stringent than the condition for exiting the lockout state, preventing high-frequency oscillation of the regulation system near the critical point.

[0015] Preferably, the short-time pulsed air supply action driven by the fluid disturbance instruction comprises: controlling the fan speed of the ventilation unit to superimpose a sinusoidal fluctuation signal of a specific frequency on the basis of the reference speed; the specific frequency is set to be non-overlapping with the natural frequency of the crop canopy airflow, so as to enhance the boundary layer separation effect while avoiding inducing structural resonance.

[0016] Preferably, the specific steps of the reverse correction operation include: judging the polarity of the performance residual, when the actual state variation is less than the theoretical expected variation, it is determined that the humidifying unit exists blocking type attenuation; the latent heat coupling factor is decreased by a preset step size until the performance residual calculated in the subsequent period converges within the preset tolerance band.

[0017] Preferably, the method further includes a multivariate decoupling step based on enthalpy: calculating the specific enthalpy of the environment in real time, decomposing the adjustment demand into sensible heat adjustment demand and latent heat adjustment demand; when the sensible heat adjustment demand and the latent heat adjustment demand conflict in direction, the latent heat adjustment demand determined by the dew point approximation degree index is given priority to respond, and the sensible heat adjustment action contrary to the latent heat adjustment demand is inhibited.

[0018] Preferably, the ventilation unit and the humidifying unit in the adjustment system are connected to the central controller through the bus, and the state machine is run inside the central controller, the state machine includes the safety monitoring state, the locking drying state and the limited humidifying state, and the migration between each state is only driven by the real-time drop rate of the dew point approximation degree index and the dry-bulb temperature.

[0019] Compared with the prior art, the beneficial effects of the present application are:

[0020] 1. In the temperature and humidity environment of the Anaphalis contorta, an active diagnosis mechanism based on fluid dynamics disturbance is constructed, the decoupling problem of sensor data and micro-interface state space of the controlled object in a static monitoring environment is solved, a short-time controlled pulse airflow is output by the ventilation execution unit in the steady state interval, the microclimate boundary layer retained on the surface of the controlled object is stripped and mixed with the environment free flow air convection, the transient response waveform characteristics during the non-electric variable disturbance of relative humidity are collected and analyzed, the saturation risk of the micro-interface that cannot be perceived by the conventional fixed-point sensor is inversely calculated and deduced, passive environmental parameter following adjustment is changed into active state identification based on physical excitation, the sensing blind area in the control system under the steady state high humidity working condition is eliminated by using the principle of fluid mechanics, and prior defense capability against the hidden condensation risk is established.

[0021] 2. An asynchronous decoupling control architecture based on dew point defense logic is established, the system oscillation and excessive adjustment defects caused by the mismatch of energy transfer and mass transfer response time constants in the multivariate coupled environment are avoided, when the environment dew point approximation degree is lower than the preset safety defense boundary, the high response sensitivity humidification adjustment permission is suspended through the logic interlocking mechanism, the dry air exchange action is preferentially driven, the dry-bulb temperature change rate and the dew point temperature change rate are differentially dynamically constrained, the surface temperature of the controlled object is maintained above the environment dew point, and the formation path of the micro-condensation water film in the nonlinear coupling field is blocked from the thermodynamic root based on the timing decoupling and permission management strategy of physical response characteristics, and high stability smooth adjustment of the complex temperature and humidity environment is realized under the low algorithmic power working condition.

[0022] 3. Introducing a self-healing mechanism based on closed-loop residual analysis control model parameters, solving the problem of non-linear decay of physical performance of the actuator in the whole life cycle of the non-electric variable regulation system, leading to the mismatch of the control model, and synchronously extracting the actual response trajectory of the dry-bulb temperature when performing the regular environmental regulation action, comparing the time domain with the expected trajectory generated based on the current model parameters to build the efficiency residual, using the statistical filtering of the residual polarity and amplitude to inversely correct the latent heat coupling gain coefficient of the feedforward control channel, converting the control deviation into system identification calibration data source, realizing online adaptive compensation of the physical aging phenomenon of the nozzle atomization efficiency or fan air volume decay, and ensuring that the control system maintains long-term regulation precision and stability without manual calibration or additional flow detection hardware. BRIEF DESCRIPTION OF DRAWINGS

[0023] Fig. 1 The regulation control flowchart of the present application integrates fluid disturbance diagnosis and parameter self-healing calibration;

[0024] Fig. 2 The correlation characteristic curve of the safety defense threshold, condensation risk and relative energy consumption index of the present application;

[0025] Fig. 3 The hierarchical regulation system architecture of the present application contains a microclimate active diagnosis mechanism. DETAILED DESCRIPTION

[0026] The following specific embodiments of the present application are described, which are intended to provide a detailed understanding of the technical solutions of the present application, but should not be regarded as limiting the protection scope of the present application.

[0027] The non-electric variable regulation method for the temperature and humidity of the growth environment of the gold pteridophyte provided by the present application contains a closed-loop regulation system of a central processing unit, an environment perception sensor and an actuator, the actuator includes a variable frequency ventilation unit, a high-pressure micro-mist humidification unit and a heat exchange heating unit, the central processing unit collects the dry-bulb temperature and the relative humidity data in the environment in real time, and performs the following control procedures; for the problem of distorted sensing data caused by the retention of the crop leaf boundary layer in the static wind and high humidity environment, the system periodically performs fluid dynamics disturbance diagnosis, when the dry-bulb temperature and the relative humidity are maintained in the target control dead zone for a preset time length and no regulation instruction is output, the processor generates a fluid disturbance instruction, the time length is set to 300 seconds to 600 seconds, the fluid disturbance instruction drives the variable frequency ventilation unit to superimpose a frequency of The sinusoidal wave signal executes a short-duration pulsed airflow action lasting 15 to 45 seconds, with the intensity set sufficient to induce convective mixing between ambient air and the crop surface boundary layer, without causing the ambient dry-bulb temperature to exceed the target control dead zone, and the frequency... Set to 0.5Hz to 2Hz, during the air supply operation, the system acquires transient response data from the relative humidity sensor at a rate 5 to 10 times higher than the conventional sampling frequency, and calculates the positive jump amplitude of this data relative to the reference value before the air supply operation. ,like If the boundary layer saturation threshold exceeds 3% to 5%, the system determines that there is a hidden risk of condensation and generates a dew point correction factor. and using the formula Increase the calculated value of the real-time dew point temperature.

[0028] The system is based on the original or corrected real-time dew point temperature. Constructing a dynamic condensation defense boundary ,in The processor monitors the dew point approach in real time, based on a preset security defense threshold. At dry bulb temperature Higher than the target setting value When this triggers a cooling adjustment requirement, the processor... Hierarchical control is implemented in the state when Below At this time, the system generates the first control command, sets the lockout status flag of the humidification unit, prohibits the output of humidification action, and drives the variable frequency ventilation unit to perform dry air exchange until... rebounded to In addition to the preset hysteresis bandwidth, when Higher than At this time, the system generates a second control command to reset the lockout status flag of the humidification unit, allowing the humidification and cooling actions to be performed. In this state, the processor calculates the rate of decrease in dry bulb temperature in real time. And the partial derivative sensitivity of dew point temperature to humidification under current environmental conditions And according to the formula Determine the maximum permissible drive signal amplitude of the humidification unit. ,in To ensure a safety factor between 0.6 and 0.8, the control logic limits the humidification rate so that the rate of increase of the dew point temperature is lower than the rate of decrease of the dry bulb temperature.

[0029] To eliminate thermodynamic coupling oscillations caused by the endothermic effect of water mist phase change, the system performs latent heat feedforward compensation. Before generating the signal to drive the humidification unit, the processor calculates the expected instantaneous cooling load increment based on the water mist mass flow rate setpoint, converts this increment into an equivalent heat compensation signal, and applies it according to a preset latent heat coupling factor. By adjusting the signal gain, the system superimposes the adjusted heat compensation signal onto the control loop of the heat exchange heating unit or as a negative bias onto the control loop of the variable frequency ventilation unit, simultaneously generating a reverse heat flux at the moment of humidification. To address actuator physical performance drift, the system performs adaptive calibration based on performance residuals. The processor identifies simple humidification events during the adjustment process, records the actual response trajectory of the dry-bulb temperature during these events, and calculates the actual state variation. Meanwhile, the processor is based on the current latent heat coupling factor. Theoretical expected variation in dry-bulb temperature calculated with control parameters System construction performance residual The system performs a moving average filtering process on the performance residuals over multiple consecutive adjustment cycles. When the mean value of the processed residuals exceeds the preset tolerance band, the system performs a reverse correction operation to update the latent heat coupling factor. The updated parameters are used to compensate for changes in physical performance caused by nozzle blockage or airflow reduction. The system adopts asymmetric control dead zone logic. When judging the start and stop conditions of each execution unit, the dead zone width setting value in the cooling direction is less than the dead zone width setting value in the heating direction, and the dead zone width setting value in the humidification direction is less than the dead zone width setting value in the dehumidification direction.

[0030] Example 1: In a modern greenhouse for high-density, vertical cultivation of *Anoectochilus roxburghii*, the system faces extreme conditions of high temperature and humidity with stagnant airflow in the summer afternoon. Under these conditions, the external dry-bulb temperature rises rapidly, and the greenhouse restricts conventional ventilation to maintain a high-humidity environment. This results in the formation of a stable, high-humidity stagnant boundary layer within the crop canopy, causing a discrepancy between environmental sensor readings and the leaf microclimate. When the dry-bulb temperature is monitored... With relative humidity If the system remains within the target control dead zone for 500 seconds without any adjustment command output, the processor determines that the system has entered a quasi-steady state and generates a fluid disturbance command. The variable frequency ventilation unit superimposes a sinusoidal wave signal with a frequency of 1.0 Hz onto the base speed and executes a pulsed air supply for 30 seconds. This action induces convective mixing between ambient air and the crop surface boundary layer. During this period, the system collects relative humidity data at a frequency of 10 Hz and calculates the positive jump amplitude. The dew point concentration was 4.2%, exceeding the preset boundary layer saturation threshold of 3.5%. The system determined there was a risk of latent condensation and generated a dew point correction factor. And increase the real-time dew point temperature The calculated value, this corrected dew point approximation degree below the safety defense threshold , triggers the first control instruction, which sets the lockout state flag of the humidification unit, prohibits the humidification action output, and drives the variable frequency ventilation unit to perform dry air exchange. With the introduction of dry air, the ambient dew point temperature decreases, gradually rises to the safe region.

[0031] When the outside air temperature drops, the greenhouse enters the night cooling stage, at this time higher than , the system generates a second control instruction to reset the lockout state flag of the humidification unit to allow humidification action to assist in cooling. The processor calculates the dry-bulb temperature drop rate 0.8℃ / min, and calculates the maximum allowed driving signal amplitude of the humidification unit according to the formula , the humidification unit operates under limited power, so that the rising rate of the dew point temperature is always lower than the falling rate of the dry-bulb temperature, ensuring that the two temperature trajectories do not cross. The processor calculates the expected instantaneous cooling load increment based on the water mist mass flow rate set value, and generates a heat compensation signal based on the latent heat coupling factor to superimpose on the heat exchange heating unit. The heating unit generates a reverse heat flux at the same time as the humidification action occurs, offsetting the temperature drop caused by water mist evaporation heat absorption, maintaining the smooth decline of the environment dry-bulb temperature. After continuous operation, the system identifies the performance residual during pure humidification action The average exceeds the tolerance band, indicating that the nozzle is slightly blocked. The processor performs a reverse correction operation to reduce the value of the latent heat coupling factor . In the adjustment period, the system automatically increases the driving signal amplitude of the humidification unit based on the updated parameters to compensate for physical performance drift, ensuring control accuracy.

[0032] Example 2: To verify the rationality of the non-electric variable adjustment method of the present application in real engineering environment, an intelligent greenhouse test platform simulating the growth environment of Anubias nana is constructed, which integrates a variable frequency ventilation unit, a high-pressure micro-mist humidification unit and a heat exchange heating unit, and is equipped with a distributed dry-bulb temperature and relative humidity sensor array. To reproduce the electromagnetic environment and physical disturbance in real industrial field, Gaussian white noise with a signal-to-noise ratio of 20dB is actively superimposed on the input end of the sensor signal, and random wind speed fluctuation disturbance is introduced into the environmental airflow field. Three parallel control groups are set up for differential verification. Control group A uses the traditional temperature and humidity independent PID control logic, i.e. the temperature loop controls ventilation and heating independently, and the humidity loop controls humidification independently, with no logical interlocking between the two. Test group B uses the asynchronous decoupling control logic based on the dew point defense boundary of the present application, wherein the safety defense threshold The temperature was set to 1.5℃; control group C, as the out-of-range control group, also adopted the logic of this invention, but with a different safety defense threshold. The temperature was set to 0℃ to verify the necessity of setting a safety margin. The test simulated typical high-temperature and high-humidity cooling conditions: the initial environmental conditions were a dry-bulb temperature of 32℃ and a relative humidity of 85%. The calculated real-time dew point temperature was 29.2℃, and the target set temperature was 25℃. The cooling command is triggered at any time, and the three test groups start adjustment simultaneously.

[0033] In control group A, the cooling action caused a rapid drop in dry-bulb temperature, while the humidification unit remained on to maintain the humidity setpoint. Monitoring data showed that, within 180 to 240 seconds after the start of adjustment, due to the lack of a decoupling mechanism, the rate of decrease in dew point temperature lagged behind the rate of decrease in dry-bulb temperature. This caused the dry-bulb temperature trajectory to cross the dew point temperature trajectory downwards, resulting in a low dew point approach. The presence of negative values, reaching a minimum of -0.5℃, indicates microscopic condensation on the leaf surface. Furthermore, due to the lack of compensation for the latent heat of phase change during humidification, the dry-bulb temperature exhibited low-frequency oscillations of ±1.8℃ when approaching the target value, extending the system stabilization time to 600 seconds. In test group B, the system monitored in real time... When detected When the temperature approaches the 1.5℃ defense threshold, the first control command is triggered, locking the humidification unit and prioritizing the dry air exchange. (See Table 1). This group operates throughout the entire cooling process. The temperature remained consistently above 1.2℃, with no risk of condensation. Simultaneously, due to the latent heat feedforward compensation mechanism, the heating unit synchronously outputs reverse heat flux upon resumption of humidification, offsetting the temperature drop caused by evaporative heat absorption. The dry-bulb temperature decrease exhibited a linear trend, with oscillations controlled within ±0.3℃, and the stabilization time shortened to 350 seconds. In control group C, although asynchronous decoupling logic was used, the lack of physical safety margin and limitations imposed by sensor response delay and actuator thermal inertia resulted in issues during the rapid cooling phase. A momentary negative value (-0.2℃) still occurred, resulting in the detection of a slight condensation film. This result confirms the necessity of setting a positive and sufficient safety threshold to counteract system hysteresis and environmental disturbances.

[0034] Table 1: Comparison of Key Performance Indicators under Different Control Strategies

[0035]

[0036] The above test data show that under the same initial conditions and environmental disturbances, the application avoids transient condensation in the cooling process and improves the stability of temperature and humidity regulation through asynchronous decoupling control and latent heat feedforward compensation mechanism, especially the setting of the safety defense threshold, which establishes the physical buffer boundary to cope with system hysteresis, which is the key parameter to realize lossless regulation.

[0037] Embodiment 3: This embodiment combines Figs. 1 to 3 the non-electric variable adjustment method of the growth environment temperature and humidity of Anoectochilus roxburghii, as shown in Fig. 1 , the system performs high-frequency acquisition of dry-bulb temperature and relative humidity data, enters the core index calculation and correction module to calculate the real-time dew point temperature and generate the dew point approximation index, and this process is parallelly associated with the left fluid dynamics disturbance active diagnosis module and the right latent heat coupling factor adaptive calibration module. The active diagnosis module generates a dew point correction factor feedback to the core calculation link after detecting the micro condensation risk through short-time pulse air supply, and the calibration module reversely corrects the control parameters based on the efficiency residual error analysis to offset the physical drift and provide parameter correction feedback. The logic enters the judgment link of the cooling trigger and the comparison of the safety defense threshold, and is divided into two streams according to the relationship between the dew point approximation index and the threshold value: when the index is lower than the threshold value, it enters the first logic control, i.e. the condensation defense mode, and the humidification is locked and the dry air exchange action is preferentially driven; when the index is higher than the threshold value, it enters the second logic control, i.e. the asynchronous decoupling mode, and the humidification output is released based on the dry-bulb temperature drop rate. The two paths finally converge in the actuator control instruction generation module, which generates the final signal by combining the comprehensive logic judgment, power clamping and feedforward compensation, respectively drives the ventilation unit to perform dry air exchange or pulse air supply, drives the humidification unit to run under the output power upper limit clamping, and drives the heating unit to perform feedforward compensation reverse heat flux. At the same time, the actual response trajectory is fed back for residual error analysis, forming a complete closed-loop control loop.

[0038] As Fig. 2 shown, the horizontal axis represents the safety defense threshold , with units of ℃, and the scale range covers 0.5 to 3, and the vertical axis represents the index value. The legend includes the condensation risk index shown by the dashed line and the relative energy consumption index shown by the solid line. As the threshold value increases from 0.5℃ to 1.5℃, the condensation risk index shows a downward trend and returns to zero at 1.5℃, while the relative energy consumption index shows an approximately linear upward trend with the increase of the threshold value, and the two curves intersect near the threshold value of 1.1℃; as Fig. 3As shown, the system constructs a multi-level data interaction architecture. The top layer uses environmental sensing sensors to provide temperature, humidity, and flow rate data input to generate the dew point approximation index module. At the same time, the microclimate boundary layer active diagnosis module intervenes under steady-state timeout conditions, driving fluid disturbance commands, i.e., pulsed air supply, and feeding back the diagnosis results to the index generation stage. The core layer performs anti-condensation stratified control. Based on the comparison results between the index and the threshold, the left path triggers dry air exchange and lock-in humidification logic and generates control commands when the index is less than the threshold. The right path triggers asynchronous decoupled humidification and power clamping logic and generates control commands when the index is greater than the threshold. The middle path performs model parameter self-healing calibration in parallel to correct the output parameters. All control commands finally converge at the bottom layer to regulate the ventilation, humidification, and heating actuators, achieving precise intervention in the growth environment.

[0039] Example 4: Addressing the lack of specific quantitative basis for setting the preset security defense threshold in the original document, this example constructs a standardized engineering calibration procedure for this threshold based on the principle of thermodynamic mass transfer. In a non-electrical variable control system, the security defense threshold... The setting directly determines the effectiveness of the condensation defense boundary and the system's adjustment margin. Setting the value too low will fail to offset the risk of transient condensation caused by system response lag; setting it too high will lead to excessive dehumidification or heating, increasing energy consumption and affecting crop growth. Therefore, it is necessary to determine the optimal balance between defense reliability and operational economy. The values ​​are crucial, and the calibration procedure is carried out in a controlled environmental test chamber. This test chamber is equipped with a variable frequency ventilation unit, a high-pressure micro-mist humidification unit, and high-precision temperature and humidity sensors consistent with the actual application scenario. The basic operating conditions of the environment are set as a dry bulb temperature of 30°C and a relative humidity of 90%, simulating the high humidity environment for the growth of *Anoectochilus roxburghii*. A series of gradient cooling experiments are performed, and different values ​​are set in each set of experiments. Trial values, ranging from 0.5℃ to 3.0℃, in steps of 0.5℃, for each The system executes the same rapid cooling command, setting the target temperature to 25℃ and the cooling rate to 1.0℃ / min.

[0040] During the cooling process, the system records the dew point approach in real time. The trajectory of the change was observed, and a high-sensitivity capacitive condensation sensor installed on the simulated blade surface was used to monitor the occurrence of micro-condensation. The cumulative energy consumption of the heating and dehumidification units during the cooling process was recorded. When set to 0.5℃ and 1.0℃, although the system energy consumption is low, in the initial rapid response phase of cooling, due to the lag in the actuator's action, the actual energy consumption is high. After repeatedly dropping below 0°C, the condensation sensor detected a condensation signal lasting for more than 30 seconds, indicating a failure of the protection mechanism. When the temperature is raised to 1.5℃, The minimum value remained above 0.2℃, no condensation signal was detected throughout the process, and the system energy consumption was within a reasonable range. When the temperature is further increased to 2.0℃ and above, although the risk of condensation is completely eliminated, the system frequently activates dehumidification and heating to maintain a larger dew point interval, leading to increased energy consumption and greater fluctuations in ambient humidity, deviating from the optimal growth range of *Anoectochilus roxburghii*. Based on the above experimental results, it is established that... The optimal value principle is to select the threshold with the lowest energy consumption and the smallest humidity fluctuation, while ensuring no condensation occurs. Based on the calibration results under the experimental conditions, [the value is determined]. The preferred value is locked between 1.5℃ and 1.8℃. This calibration procedure provides a clear operational basis for determining personalized safety defense thresholds based on different environmental loads and equipment characteristics in practical engineering applications.

[0041] Example 5: Latent heat coupling factor in the cultivation of Anoectochilus roxburghii in high-latitude or low-light winter environments. To mitigate the risks of baseline drift and control model failure, this embodiment constructs an adaptive parameter initialization and dynamic calibration engineering procedure. During initial system deployment or drastic seasonal environmental changes, an offline calibration mode is initiated. The greenhouse is placed in an adiabatic, sealed state with no light and no crop transpiration, maintaining a constant wind speed. The micro-mist humidification unit executes a series of step-pulse jet actions, while simultaneously acquiring the transient response curve of the dry-bulb temperature at a frequency of 10Hz. By analyzing the sensible heat temperature drop caused by the evaporation of a unit mass of water mist and combining it with the energy conservation equation, the initial value characterizing the current gas-liquid phase change efficiency of the space is calculated in reverse. This value eliminates model errors caused by changes in the basic environmental heat capacity.

[0042] After completing the baseline parameter calibration, the system enters the online adaptive operation phase. To address the potential model miscorrection issues caused by inherent sensor noise and random environmental perturbations, the system executes a boundary convergence procedure based on statistical characteristics. During continuous operation cycles, it records in real-time the deviation sequence between the actual and theoretically expected changes during simple humidification and simple ventilation actions. A Gaussian distribution model is applied to extract statistical features from the deviation sequence, and the standard deviation of the deviation data is calculated. The system will have performance residuals The effective tolerance band is dynamically set to The confidence interval is defined, and the inverse correction operation is activated only when the monitored performance residual amplitude continuously exceeds the confidence interval, thereby shielding unstructured interference and ensuring that the control model only compensates for the actual drift of the actuator's physical performance.

[0043] Example 6: This embodiment details a set of standardized engineering deployment and parameter benchmarking procedures for a non-electric variable adjustment system for the growth environment of golden pteridophyte, aiming to address the influence of different regions, different thermal performance of enclosure structures, and different aging degrees of equipment on the control model accuracy, to ensure that the system can quickly converge to the optimal working state before the first operation and after periodic maintenance, to perform offline identification of environmental thermodynamic characteristic parameters, and to drive the variable frequency ventilation unit to run at 50% of the rated power for 30 minutes under static conditions without crops, without light, and with closed doors and windows, and to record the decay curves of indoor dry-bulb temperature and relative humidity simultaneously, and to use the heat balance equation to inversely solve the current comprehensive heat transfer coefficient of the greenhouse enclosure structure and air permeability , drive the high-pressure micro-mist humidification unit to perform a 5-minute rated injection, and record the rising rate of environmental relative humidity , to calibrate the current water vapor capacity coefficient of the space , the above parameters constitute the boundary conditions of the system's basic thermodynamic model, providing a physical benchmark for subsequent dew point defense calculations; then perform dynamic optimization and boundary locking of control parameters, the system automatically generates a set of simulated disturbance signals covering the target control domain based on the calibrated thermodynamic model, and in closed-loop operation mode, gradually increases the safety defense threshold from 0.5°C with a step size of 0.1°C , until the monitored dew point approximation degree is always positive under the simulated most adverse working conditions, and the system adjustment frequency caused by this is not more than the preset mechanical loss limit, record the value under this critical state, and set it as the optimal defense threshold under the current working condition, for the latent heat coupling factor , the system performs online gradient calibration, gradually adjusts the preset value of while maintaining a constant dry-bulb temperature, and observes the dry-bulb temperature fluctuation amplitude caused by simple humidification action, when the fluctuation amplitude converges to the sensor measurement error range, the current value is locked as the running benchmark.

[0044] Finally, execute the fault tolerance logic verification of abnormal working conditions, the system simulates sensor failure and actuator sticking, etc. extreme scenarios, verify whether the system can automatically switch to the safety degradation mode according to the preset fault tree logic, and output clear alarm codes, when all verification items are passed, the system can enter the formal hosting operation state, the preset safety defense threshold , perform a condensation critical point approximation gradient pressure test based on the condensation critical point approximation gradient, lock the environmental relative humidity in the to interval under high-humidity constant-temperature environment, with step in the to range monotonically increasing Set value, each set value keeps stage with attached leaf surface micro-capacitive humidity probe to collect 300 seconds surface impedance data; record analysis impedance data variance rate, impedance variance converges to environment base noise level corresponding minimum Value marked as critical defense point, superimposed To Physical redundancy solidifies as final threshold value, locking in consideration of inhibiting liquid film formation and avoiding excessive dehumidification energy consumption engineering work point, fluid disturbance instruction specific frequency determines execution frequency scanning and response gain analysis, driving ventilation unit to output variable frequency pulse air flow in To Range, synchronously monitor relative humidity sensor time domain response waveform peak value, calculate humidity change rate and wind speed change rate ratio at each frequency point to obtain system frequency domain sensitivity function; identify sensitivity function main peak center frequency, set fluid disturbance instruction execution frequency as this center frequency Times to Times, according to the principle of maximum boundary layer separation efficiency, destroy the turbulence intensity of the static stagnation layer of the crop canopy at the minimum average air volume input, avoid the inherent mechanical resonance frequency of the crop canopy to prevent physical damage, latent heat coupling factor Initialize and online correction to execute standard unit step response closed loop identification, initial start or environmental thermal load step change steady state period, drive humidification unit to output constant mass flow pulse with duration Actual dry bulb temperature drop trajectory is fitted as a first-order inertial lag link transfer function using least squares method; calculate the ratio of the steady-state gain of the transfer function and the calculated value of the theoretical evaporation heat absorption model as the initial reference value, and subsequently calculate the residual integral of the humidification action temperature prediction in real time, and when the absolute value of the residual integral exceeds the preset sensor accuracy tolerance, use gradient descent algorithm to monotonically correct the , until the predicted residual converges to a zero mean Gaussian white noise sequence.

[0045] It is apparent for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

[0046] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the present application.

Claims

1. A non-electric variable method for regulating the temperature and humidity of the growing environment of *Anoectochilus roxburghii*, the method being implemented based on a regulation system comprising a ventilation unit, a humidification unit, and a heating unit, characterized in that... Includes the following steps: Dry bulb temperature and relative humidity data in the growth environment are collected at a preset frequency. Real-time dew point temperature is calculated based on dry bulb temperature and relative humidity data, and a dew point approximation index is generated to characterize the numerical difference between dry bulb temperature and real-time dew point temperature. When the dry bulb temperature exceeds the target set value and triggers the cooling adjustment logic, the dew point approach index is compared with the preset safety defense threshold in real time. When the dew point approach index is lower than the preset safety defense threshold, a first logic control command is generated. The first logic control command sets the lockout status flag of the humidification unit and drives the ventilation unit to perform dry air exchange until the dew point approach index rises back to above the preset safety defense threshold. When the dew point approach index is higher than the preset safety defense threshold, a second logic control command is generated. The second logic control command resets the lockout status flag of the humidification unit and calculates the upper limit of the output power of the humidification unit based on the real-time rate of decrease of the dry bulb temperature. The upper limit of the output power is used to clamp the amplitude of the drive signal of the humidification unit so that the rate of increase of the dew point temperature caused by the humidification action is always lower than the real-time rate of decrease of the dry bulb temperature. Furthermore, the method also includes an active diagnostic step for the microclimate boundary layer: monitoring the operating status of the regulation system, generating a fluid disturbance command when the dry-bulb temperature and relative humidity remain within the target control dead zone for a preset threshold duration; driving the ventilation unit to perform short-term pulsed air supply action according to the fluid disturbance command; collecting transient response data of relative humidity in a high-frequency sampling mode during the air supply action, and calculating the positive jump amplitude of the transient response data relative to the reference value before the air supply action; comparing the positive jump amplitude with a preset boundary layer saturation threshold, and generating a dew point correction factor when the positive jump amplitude exceeds the boundary layer saturation threshold; increasing the calculated value of the real-time dew point temperature using the dew point correction factor, and triggering a first logic control command or a second logic control command using the increased real-time dew point temperature; The method also includes an adaptive calibration step for the latent heat coupling factor: recording the actual response trajectory of the dry-bulb temperature during the simple humidification action of the regulating system, and calculating the actual state variation caused by the humidification action; calculating the theoretical expected variation of the dry-bulb temperature based on the current latent heat coupling factor and the humidification action control parameters; constructing the performance residual between the actual state variation and the theoretical expected variation, and performing statistical filtering on the performance residual for multiple consecutive regulating cycles; when the processed performance residual exceeds the preset tolerance band, performing an inverse correction operation based on the polarity and amplitude of the performance residual to update the latent heat coupling factor; and using the updated latent heat coupling factor to generate subsequent feedforward compensation commands for the humidification unit or heating unit to counteract the effects of the physical performance drift of the humidification unit.

2. The method for non-electrical variable regulation of temperature and humidity in the growth environment of *Anoectochilus roxburghii* according to claim 1, characterized in that, The steps for setting the preset safety defense threshold include: acquiring ambient air velocity data and the current dry-bulb temperature value; calculating the minimum saturation difference required to maintain interfacial moisture evaporation at the current flow rate based on the preset fluid heat and mass exchange model; mapping the minimum saturation difference to the corresponding critical temperature difference value, and setting the critical temperature difference value as the preset safety defense threshold.

3. The method for non-electrical variable regulation of temperature and humidity in the growth environment of *Anoectochilus roxburghii* according to claim 1, characterized in that, The first logic control command also includes dead-zone asymmetric adjustment logic: when determining whether to release the lockout status flag of the humidification unit, a hysteresis comparison circuit is introduced; The threshold for unlocking the state is set to a preset security defense threshold plus a preset hysteresis bandwidth, making the conditions for entering the locked state more stringent than the conditions for exiting the locked state.

4. The method for non-electrical variable regulation of temperature and humidity in the growth environment of *Anoectochilus roxburghii* according to claim 1, characterized in that, The specific steps of the reverse correction operation include: determining the polarity of the performance residual; when the actual change is less than the theoretical expected change, determining that the humidification unit has a blockage-type attenuation; decreasing the latent heat coupling factor by a preset step size until the performance residual calculated in subsequent cycles converges to the preset tolerance band.

5. The method for non-electrical variable regulation of temperature and humidity in the growth environment of *Anoectochilus roxburghii* according to claim 1, characterized in that, The ventilation unit and humidification unit in the regulation system are connected to the central controller via a bus. The central controller is configured to execute the method described in claim 1. The central controller has a state machine running inside, which includes a safety monitoring state, a locked drying state, and a restricted humidification state. The transition between each state is driven only by the dew point approach index and the real-time rate of decrease of the dry bulb temperature.

6. The method for non-electrical variable regulation of temperature and humidity in the growth environment of *Anoectochilus roxburghii* according to claim 1, characterized in that, The steps for calculating the upper limit of the humidifier unit's output power based on the real-time rate of decrease of the dry-bulb temperature follow the following constraint logic: Within each control cycle, the real-time rate of decrease of the dry-bulb temperature is obtained. Calculate the partial derivative sensitivity of dew point temperature with humidification rate based on the current environmental conditions. The maximum allowable output of the humidification unit is determined based on the following formula. : ,in, A safety factor of less than 1 is preset to ensure that the rate of increase of dew point temperature strictly lags behind the rate of decrease of dry bulb temperature; the short-term pulsed air supply action driven by the fluid disturbance command includes: controlling the fan speed of the ventilation unit to superimpose a sinusoidal wave signal of a specific frequency on the basis of the reference speed; the specific frequency is set to not overlap with the natural frequency of the crop canopy airflow, so as to enhance the boundary layer stripping effect while avoiding structural resonance. The method also includes a multivariate decoupling step based on enthalpy: the specific enthalpy of the environment is calculated in real time, and the regulation demand is decomposed into sensible heat regulation demand and latent heat regulation demand; when the sensible heat regulation demand and latent heat regulation demand conflict in direction, the latent heat regulation demand determined by the dew point approximation index is given priority.

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