Safety control method and system for hydraulic lifting platform

Abstract

The invention discloses a safety control method and system for a hydraulic lifting platform, and relates to the technical field of hydraulic lifting platforms. According to the method, five levels of control thresholds are set in freezing erosion level division, and when the freezing erosion level reaches the L3 level or above, a sealing perturbation dynamic response mechanism is further triggered. And calculating and outputting a sealing perturbation response index SPI based on the freezing erosion characteristic index FRI. And whether the sealed area enters a micro-crack sensitive state under cold start impact is quantified. And jointly calculating a start control composite response index CCI through a sealing perturbation response index SPI and a freezing erosion characteristic index FRI, and expressing the overall risk intensity. And the platform can execute final strategies such as delay starting, power limiting, linear boosting or alarming and the like according to the segmentation relation between the control interval threshold values, the field state can be accurately matched, and the intelligent closed-loop process of the control response through freezing evaluation, sealing disturbance recognition and response level switching is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of hydraulic lifting platform, in particular to a safety control method and system of hydraulic lifting platform. BACKGROUND

[0002] As the core means of modern engineering machinery power transmission, hydraulic technology is widely used in high-load rotation and lifting control in fields such as metallurgy, petrochemical industry, construction and offshore platform. In these industries, hydraulic lifting platforms, due to their compact structure, strong carrying capacity and high adjustment precision, have become an important equipment for indoor and outdoor maintenance, assembly and maintenance operations; especially in extremely cold environments, unattended hydraulic lifting platforms bear the automatic lifting of key facilities such as upper sensor arrays and aerial work tools. For a complete "safety control method of hydraulic lifting platform", its research not only covers the system integration from energy conversion, hydraulic circuit design to signal acquisition, but also needs to go deep into the microscopic icing mechanism of sealing elements at extremely low temperatures and the optimization of operation safety strategies.

[0003] At present, under extremely cold environmental conditions, the sealing lip around the hydraulic lifting platform in the static state often produces tiny ice crystals due to high humidity and low temperature; the existing control system usually ignores this hidden risk and directly restores the oil pressure at the conventional hydraulic opening rate when starting, which causes the ice crystals to break or fall off under high pressure impact and damage the sealing structure. Although some solutions use heating preheating or flow limiting deceleration to alleviate the icing problem, they cannot dynamically adjust the starting strategy according to the specific environmental changes and static periods of the platform on site, and have defects such as insufficient prevention, delayed response and high energy consumption, making it difficult to balance safety and reliability with work efficiency.

[0004] The root of these deficiencies lies in the lack of systematic monitoring and periodic evaluation of the ice crystal micro-erosion process: the growth and shedding cycle of ice crystals on the sealing surface often occurs repeatedly on a millimeter scale and a time window of hours, and simple temperature or heating control cannot grasp its timing rules. Once the cold start fails to accurately limit the speed or segmentally unlock, the local sealing rupture caused by ice crystal shedding will cause micro-leakage, triggering overall pressure imbalance, eventually causing platform lifting instability, pressure drop, system emergency stop or sealing component fatigue damage, and in severe cases, even causing overall operation interruption and equipment maintenance cost surge. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a safety control method and system of hydraulic lifting platform, which solves the problems mentioned in the background art.

[0006] To achieve the above purpose, the present application is realized by the following technical scheme: S1, set key points on the large hydraulic lifting platform, and set perception devices in the key points, real-time collect perception data of the large hydraulic lifting platform, and transmit the perception data to a safety control server; S2, pre-process the perception data in the safety control server, obtain a standardized perception data set, and calculate an output frozen erosion feature index FRI; S3, based on the output result of the frozen erosion feature index FRI, perform frozen erosion grading, and based on the frozen erosion grading result, start a corresponding preliminary control strategy, and when the frozen erosion grading exceeds L3 level, trigger a sealed micro-perturbation dynamic response mechanism; S4, after triggering the sealed micro-perturbation dynamic response mechanism, calculate the frozen erosion feature index FRI, output a sealed micro-perturbation response index SPI, and calculate and output a start control composite response index CCI; S5, compare and evaluate the control interval threshold value with the start control composite response index CCI, and trigger a final execution strategy.

[0007] Preferably, the S1 includes S11 and S12; S11, set four key points on the large hydraulic lifting platform, and set perception devices in each key point, real-time collect perception data of the large hydraulic lifting platform in a cold environment; The key points include an A1 key point, an A2 key point, an A3 key point, and an A4 key point; The perception devices include a thin film capacitance type humidity sensor, a thin film type heat flow sensor, a thermocouple array, an acoustic emission sensor, and a response type piezoelectric pressure sensor; The perception data includes a humidity condensation aggregation rate Rhumid, a heat dissipation flux density Qdissip, a micro-vibration frequency response Fvib, an instantaneous pressure rise ratio ΔP, and a temperature Tenv; S12, based on the communication module built in all perception devices, set LoRa physical layer and LoRaWAN network protocol stack to work cooperatively, connect the communication module of the perception device with the safety control server in an end-to-end manner, and simultaneously after the end-to-end connection, transmit the real-time collected perception data to the safety control server.

[0008] Preferably, the S2 includes S21; S21, pre-process the perception data in the safety control server, and obtain a standardized perception data set; The pre-processing includes standardization processing and ice crystal derivation; The standardization processing standardizes the perception data by using Z-score standardization, and eliminates the dimension influence of all parameters in the perception data; The ice crystal is derived by deriving the ice crystal aggregation density Pice based on the humidity condensation aggregation rate Rhumid, the heat dissipation flux density Qdissip and the temperature Tenv, and the standardization perception data set is obtained by integrating the ice crystal aggregation density Pice and the perception data; The ice crystal aggregation density Pice is derived by the following algorithm formula: Pice=f(Rhumiud, tidle, Tenv, Qdissip), wherein: f represents a function estimator for mapping multiple environmental variables to an aggregation density, and tidle represents a standing time, which is dimensionless; The standardization perception data set includes the humidity condensation aggregation rate Rhumid, the heat dissipation flux density Qdissip, the micro-vibration frequency response Fvib, the instantaneous pressure rise ratio ΔP and the ice crystal aggregation density Pice.

[0009] Preferably, the S2 further includes S22; S22, extracting the humidity condensation aggregation rate Rhumid, the heat dissipation flux density Qdissip and the ice crystal aggregation density Pice in the standardization perception data set, and calculating and outputting the freeze erosion characteristic index FRI to measure the surface icing phenomenon of the sealing structure of the large hydraulic lifting platform after a long time of static state in a cold environment due to the effects of temperature and humidity. The freeze erosion characteristic index FRI is calculated and outputted by the following algorithm formula: ; In the formula, log represents a logarithmic function.

[0010] Preferably, the S3 includes S31; S31, performing a preliminary comparative evaluation based on the output result of the freeze erosion characteristic index FRI, and performing freeze erosion grading based on the preliminary comparative evaluation result, and the specific evaluation content is as follows: When the freeze erosion characteristic index FRI is less than 0.8, the current freeze erosion level is divided into L1 level, i.e. safe; When the freeze erosion characteristic index FRI is in the range of [0.8, 1.6), the current freeze erosion level is divided into L2 level, i.e. slight freeze; When the freeze erosion characteristic index FRI is in the range of [1.6, 2.5), the current freeze erosion level is divided into L3 level, i.e. moderate freeze; When the freeze erosion characteristic index FRI is in the range of [2.5, 3.8), the current freeze erosion level is divided into L4 level, i.e. high freeze; When the freeze erosion characteristic index FRI is greater than 3.8, the current freeze erosion level is divided into L5 level, i.e. extreme freeze.

[0011] Preferably, S3 further includes S32; S32. Based on the preliminary comparative evaluation results, the freezing erosion is classified into different levels, and corresponding preliminary control strategies are implemented. Furthermore, the sealing perturbation dynamic response mechanism is triggered based on the freezing erosion classification results. The specific preliminary control strategies implemented for each freezing erosion level are as follows: When classified as L1, no intervention is required to fully respond and start the hydraulic system; When classified as L2 level, a 2-second warm-up delay is performed before a soft start. When classified as Level L3, the hydraulic pressurization rate is limited to 50%. When classified as L4, the preheating time is delayed by 4 seconds, and the hydraulic pressurization rate is limited to 25%. When classified as L5, startup is prohibited, and a freeze alarm signal is issued. Simultaneously, when the freezing erosion level is ≥L3 but not L5, the sealing perturbation dynamic response mechanism is triggered.

[0012] Preferably, S4 includes S41; S41. After triggering the dynamic response mechanism of sealing perturbation, extract the freezing erosion characteristic index FRI(t) at the current time t, combine it with the micro-vibration frequency response Fvib and the instantaneous pressure rise ratio ΔP to calculate and output the sealing perturbation response index SPI to measure the damage state of the sealing lip when the large hydraulic platform is cold started. The sealing perturbation response index (SPI) is calculated and output using the following algorithm formula; ; Always, Seal represents the ultimate safe stress of the sealing lip, which is set by the user and is a dimensionless value.

[0013] Preferably, S4 further includes S42; S42. Based on the obtained sealing perturbation response index SPI and freezing erosion characteristic index FRI, a comprehensive calculation is performed to output the start-up control composite response index CCI, which serves as the basis for the final control strategy switching. The startup control composite response index (CCI) is calculated and output using the following algorithm formula; ; In the formula, "tidle" represents the resting time.

[0014] Preferably, S5 includes S51 and S52; S51. Based on the user setting control interval thresholds, the control interval thresholds include a first control threshold F1, a second control threshold F2, and a third control threshold F3. The control interval thresholds are compared and evaluated with the activation control composite response index (CCI). Based on the comparison and evaluation results, the risk status after the initial control strategy is executed is analyzed. The specific evaluation content is as follows. When the initial control composite response index CCI is less than the first control threshold F1, it indicates that the initial control strategy is successful, and the hydraulic system is started at full speed. When the first control threshold F1 ≤ the activation control composite response index CCI < the second control threshold F2, it indicates that there is a level one risk after the initial control strategy is implemented; When the first control threshold F2 ≤ the initial control composite response index CCI < the second control threshold F3, it indicates that there is a secondary risk after the initial control strategy is implemented; When the initial control composite response index (CCI) is greater than or equal to the second control threshold (F3), it indicates that there is a level 3 risk after the initial control strategy is implemented. Wherein, the first control threshold F1 < the second control threshold F2 < the third control threshold F3; S52. Based on the comparative evaluation results, analyze the risk status after the implementation of the preliminary control strategy, and trigger the final execution strategy. The specific content of the final execution strategy is as follows: If the risk level is classified as Level 1, the initial control strategy will be delayed by 3 seconds and the current output power will be limited to 70%. If the risk level is classified as Level 2, then based on the current preliminary control strategy, the current output power will be limited to 50%, and a linear increase in hydraulic pressure of 10% will be initiated. If the risk level is classified as Level 3, startup will be prohibited, a freeze alarm signal will be issued, and the system will be forced into maintenance mode.

[0015] A safety control system for a hydraulic lifting platform includes a sensing layout module, a freeze erosion analysis module, a freeze erosion classification module, a sealing disturbance response module, and a composite control module. The sensing layout module sets key points on the large hydraulic lifting platform and sets sensing devices within the key points to collect sensing data from the large hydraulic lifting platform in real time and transmit the sensing data to the safety control server. The freeze erosion analysis module preprocesses the sensing data in the security control server to obtain a standardized sensing dataset and calculates and outputs the freeze erosion characteristic index (FRI). The freezing erosion classification module classifies freezing erosion based on the output of the freezing erosion characteristic index FRI, then initiates a corresponding preliminary control strategy based on the freezing erosion classification results, and triggers a sealing perturbation dynamic response mechanism when the freezing erosion classification exceeds L3 level. The sealing disturbance response module calculates based on the Freeze-Induced Erosion (FRI) characteristic index after triggering the sealing disturbance dynamic response mechanism, outputs the sealing disturbance response index SPI, and then calculates and outputs the start-up control composite response index CCI. The composite control module compares and evaluates the control interval threshold with the start control composite response index (CCI) to trigger the final execution strategy.

[0016] This invention provides a safety control method and system for a hydraulic lifting platform. It has the following beneficial effects: (1) This method deploys a sensing network including key points A1 to A4 on a large hydraulic lifting platform, collects sensing data and other parameters, and uploads them to the safety control server via a communication module based on the LoRaWAN protocol to form a standardized sensing dataset. Using Z-score standardization and the derived estimated ice crystal aggregation density (Pice), a freezing erosion characteristic index (FRI) is constructed, enabling comprehensive identification and quantitative assessment of the freezing risk of the lifting platform's sealing structure under low-temperature static conditions. Through freezing erosion level classification L1–L5 and differentiated control strategies, the method effectively avoids stress concentration and cracking of the sealing lip caused by direct start-up, improving the protective performance of the hydraulic cylinder sealing structure in extreme environments.

[0017] (2) This method sets five control thresholds in the classification of freezing erosion levels, and further triggers the sealing perturbation dynamic response mechanism when the freezing erosion level reaches L3 or above. The freezing erosion characteristic index FRI is fused with the micro-vibration frequency response Fvib and instantaneous pressure rise ratio ΔP collected during cold start to calculate and output the sealing perturbation response index SPI. The SPI can quantify whether the sealing area enters a micro-crack sensitive state under cold start impact. Then, the start-up control composite response index CCI is calculated by jointly calculating the sealing perturbation response index SPI and the freezing erosion characteristic index FRI to express the overall risk intensity. According to the segmented relationship between the CCI value and the control interval threshold, the platform can execute the final strategies such as delayed start, power limiting, linear voltage boost or alarm, accurately match the field status, and realize the intelligent closed-loop process of control response from freezing assessment, sealing perturbation identification and response level switching.

[0018] (3) This method constructs a startup control composite response index (CCI) to achieve a synergistic quantitative assessment of the icing trend and sealing vulnerability of hydraulic lifting platforms under cold start conditions. At the control strategy level, multi-level response behaviors are set. For example, when the startup control composite response index (CCI) ≥ 2.8, it enters an extremely high-risk level, prohibiting startup and issuing a freezing warning; in the range of 1.0 ≤ startup control composite response index (CCI) < 2.8, a progressive strategy of "delay, pressure limiting, and linear pressure increase" is activated. Through dynamic tracking and hierarchical management of the CCI, the method significantly reduces system emergency stops, abnormal startups, or unplanned maintenance problems caused by ice crystal damage, lowering the platform failure rate and maintenance burden. It is particularly suitable for high-risk application scenarios such as unmanned operation or extremely short operating windows, such as northern oilfields and polar research stations. This method provides a systematic and intelligent solution for the safe startup of hydraulic lifting platforms in extreme cold conditions through closed-loop control logic of data fusion, risk assessment, and response execution. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the safety control method steps for a hydraulic lifting platform according to the present invention; Figure 2 This is a schematic diagram of the safety control system of a hydraulic lifting platform according to the present invention; Figure 3 This is a diagram showing the hierarchical relationship of freezing erosion. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1 Please see Figure 1 and Figure 3 This invention provides a safety control method for a hydraulic lifting platform. To achieve the above objectives, this invention employs the following technical solution, comprising the following steps: S1. Set key points on the large hydraulic lifting platform and install sensing devices within the key points to collect sensing data from the large hydraulic lifting platform in real time and transmit the sensing data to the safety control server. S2. Preprocess the sensing data in the security control server to obtain a standardized sensing dataset and calculate and output the Freeze Erosion Feature Index (FRI). S3. Based on the output of the freezing erosion characteristic index FRI, the freezing erosion is classified, and then the corresponding preliminary control strategy is initiated based on the freezing erosion classification results. When the freezing erosion classification exceeds L3 level, the sealing perturbation dynamic response mechanism is triggered. S4. After triggering the sealing perturbation dynamic response mechanism, calculate based on the freezing erosion characteristic index FRI, output the sealing perturbation response index SPI, and then calculate and output the start-up control composite response index CCI. S5. Set the control interval threshold and compare it with the start control composite response index (CCI) to trigger the final execution strategy.

[0022] In this embodiment, the method uses multiple sensing devices installed at key locations on the hydraulic lifting platform to monitor environmental parameters around the platform in real time, including humidity condensation and accumulation rate, heat flux density, micro-vibration frequency response, and instantaneous pressure rise ratio. This data is transmitted to a safety control server for processing, and Z-score standardization is used to eliminate the influence of dimensions. Based on this, an algorithm is used to derive the Freeze Erosion Characteristic Index (FRI) and the Estimated Ice Crystal Accumulation Density (Pice), and these data are combined to generate a standardized sensing dataset. Secondly, based on the output of the Freeze Erosion Characteristic Index (FRI), the safety control server classifies the freeze erosion risk of the hydraulic lifting platform into five levels. When the freeze erosion level exceeds L3, a sealing perturbation dynamic response mechanism is triggered, and the sealing perturbation response index (SPI) is calculated by combining the micro-vibration frequency and pressure rise ratio. Next, the activation control composite response index (CCI) is calculated based on the SPI value. This index comprehensively considers multiple factors such as ambient temperature, settling time, ice crystal formation, and sealing perturbation, ultimately outputting a comprehensive risk assessment value. Finally, a control interval threshold was set and compared with the Composite Response Index (CCI) value for startup control. Based on different preliminary control strategies, corresponding final control strategies were triggered, including delayed startup, current limiting, and limiting the pressurization rate, to ensure the safety and reliability of the hydraulic lifting platform during startup in extremely cold environments. Through this method, the present invention can not only accurately assess the freezing and corrosion risk of the hydraulic lifting platform's sealing system in extremely cold environments, but also dynamically adjust the startup control strategy, effectively avoiding seal damage and system failure caused by ice crystal breakage while ensuring startup efficiency. This method significantly improves the stability of the hydraulic lifting platform in low-temperature environments, reduces the frequency of failures, and lowers maintenance costs. By implementing this safety control method, the hydraulic lifting platform can operate more safely and reliably in extremely cold environments, making it particularly suitable for long-term operations in special environments such as polar scientific expeditions and northern oil fields.

[0023] Example 2 Please see Figure 1 Specifically: S1 includes S11 and S12; S11. Set up 4 key points on the large hydraulic lifting platform and install sensing devices in each key point to collect real-time sensing data of the large hydraulic lifting platform in the cold environment. Key points include A1 key point, A2 key point, A3 key point, and A4 key point; Sensing devices include thin-film capacitive humidity sensors, thin-film heat flow sensors, thermocouple arrays, acoustic emission sensors, and responsive piezoelectric pressure sensors. Sensing data includes humidity condensation and accumulation rate Rhumid, heat flux density Qdissip, micro-vibration frequency response Fvib, instantaneous pressure rise ratio ΔP, and temperature Tenv; The A1 key point is to use the capacitance change of a thin-film capacitive humidity sensor located on the inner surface of the top and outer metal layer of the cabin to respond to the change in water vapor content in the air. It collects the relative humidity of the air inside the cabin where the multi-point hydraulic lifting platform is located within 1 minute, and calculates the rate of change to obtain the humidity condensation accumulation rate Rhumid, which represents the rate of change of relative humidity per unit time, and is used to predict condensation trends. The A2 key point involves using a thin-film heat flux sensor and a thermocouple array on the surface of the metal cavity wall in the near-sealed area inside the hydraulic cylinder barrel to collect the surface temperature Tenv based on Fourier's law. The temperature Tenv at different locations is obtained based on the thermocouple matrix, and the temperature gradient is calculated. The temperature gradient is then combined with the thermal conductivity of the metal material to infer the heat dissipation per unit time, and the heat dissipation flux density Qdissip is obtained, which represents the rate of heat loss per unit area of ​​the sealed inner wall of the hydraulic cylinder and is used to measure the possibility of local freezing. The A3 key point is set on the outer shell of the hydraulic cylinder, close to the sealing area. It utilizes the elastic waves released when the material undergoes micro-cracks. The instantaneous pulse signal with a frequency range of 50-500kHz is captured by an acoustic emission sensor. The micro-vibration characteristic frequency is extracted. Then, FFT fast Fourier analysis is performed to extract the main peak frequency and obtain the micro-vibration frequency response Fvib, which represents the small high-frequency vibration of the sealing component caused by the change of internal stress at the moment of cold start. The A4 key point is set at the hydraulic pump outlet and the pipeline interface before entering the hydraulic cylinder. It uses a responsive piezoelectric pressure sensor to output a charge signal proportional to the external pressure. The sampling frequency is above 10kHz, which is suitable for detecting rapid pressure changes in a short time. The central difference method is used to calculate the rate of change of the pressure values ​​between two consecutive samplings. The instantaneous pressure rise ratio ΔP represents the rate of change of the pressure in the hydraulic system per unit time during the initial stage of cold start. S12. Based on the communication modules built into all sensing devices, the LoRa physical layer and LoRaWAN network protocol stack are set up to work together to connect the communication modules of the sensing devices to the security control server end-to-end. After the end-to-end connection is established, the sensing data acquired in real time is transmitted to the security control server.

[0024] In this embodiment, the method sets up multiple key points on the hydraulic lifting platform and installs high-precision sensing devices to collect and transmit sensing data to the safety control server in real time, thereby dynamically monitoring and controlling the freezing risk and sealing system status during the platform's cold start process. Specific implementation includes: setting up four key points on the platform, each equipped with a humidity sensor, heat flux sensor, thermocouple array, acoustic emission sensor, and piezoelectric pressure sensor, to collect multi-dimensional environmental parameters such as humidity condensation accumulation rate (Rhumid), heat flux density (Qdissip), micro-vibration frequency response (Fvib), instantaneous pressure rise ratio (ΔP), and temperature (Tenv). This data is transmitted in real time to the safety control server via a built-in LoRa communication module, where it is standardized and the freezing erosion characteristic index (FRI) is derived. This method, through precise data acquisition from sensing devices, provides prediction and real-time monitoring of icing phenomena during the cold start of the hydraulic lifting platform, solving the shortcomings of traditional methods in effectively predicting and responding to ice crystal formation in extremely cold environments. Through standardized data processing and ice crystal derivation, the safety control system can implement a graded control strategy based on the platform's current freezing erosion risk. When the freezing erosion level reaches L3 or above, the dynamic response mechanism for seal perturbation is triggered, further enhancing safety during startup. By dynamically adjusting the hydraulic startup rate and startup mode, the risk of damage to the sealing system caused by excessively rapid pressure increase or ice crystal rupture is reduced.

[0025] Example 3 Please see Figure 1 and Figure 3 Specifically: S2 includes S21; S21. Preprocess the sensing data in the security control server to obtain a standardized sensing dataset; Pretreatment includes standardization and ice crystal derivation; Standardization is performed by using Z-score standardization to standardize the perceived data, eliminating the influence of the dimensions of all parameters in the perceived data; Ice crystal derivation is performed by deriving the estimated ice crystal aggregation density Pice based on the humidity condensation aggregation rate Rhumid, heat flux density Qdissip, and temperature Tenv. The estimated ice crystal aggregation density Pice is then combined with the sensing data to obtain a standardized sensing dataset. The estimated ice crystal aggregation density, Pice, is derived using the following algorithmic formula: Pice = f(Rhumiud, tiel, Tenv, Qdissip), where f represents a function estimator that maps multiple environmental variables to aggregation density, and tiel represents the settling time, which is dimensionless and reflects the cumulative condensation time window, determining the time field for ice crystal formation. The standardized sensing dataset includes the humidity condensation aggregation rate Rhumid, heat flux density Qdissip, micro-vibration frequency response Fvib, instantaneous pressure rise ratio ΔP, and estimated ice crystal aggregation density Pice.

[0026] S2 also includes S22; S22. Extract the humidity condensation aggregation rate Rhumid, heat flux density Qdissip, and estimated ice crystal aggregation density Pice from the standardized sensing dataset, calculate and output the freezing erosion characteristic index FRI, and measure the surface icing phenomenon of the sealing structure of a large hydraulic lifting platform after a long period of stillness in a cold environment due to the effects of temperature and humidity. The Freeze Erosion Characteristic Index (FRI) is calculated and output using the following algorithm formula; ; In the formula, log represents the logarithmic function; The derivation logic of the formula: The intensity of the induced risk of freezing is used to analyze whether ice crystals are easy to form. The higher the humidity, especially the faster the change, the stronger the condensation. Secondly, the longer the standing time, the larger the freezing time window. Therefore, the square enhancement is used. Another point is that the smaller the heat loss, the more difficult it is for heat to dissipate, and the more stable the freezing. In the denominator, a constant +1 is added to avoid division by zero, which also reflects that the freezing rate increases when the heat loss approaches zero. This indicates the stability of the formed ice crystals and is used to analyze whether the ice crystals have been stably attached and are more difficult to peel off. If the time after the ice crystals have formed is short, they may not be frozen solid. The heavier the ice crystals and the higher the density, the more severe the condensation. A short standing time will result in loose surface ice crystals, resulting in less harm. Logarithmic suppression is used to suppress excessive amplification, making this part an adjustment term. The physical meaning of the formula is to comprehensively judge whether the current environment has a tendency to form ice crystals and whether the formed ice crystals pose a structural threat, and finally output a continuous value for security strategy classification judgment.

[0027] In this embodiment, the method preprocesses the real-time collected sensing data in the safety control server to obtain a standardized sensing dataset. The preprocessing process includes two parts: First, the sensing data is standardized using the Z-score standardization method to eliminate the influence of dimensions; second, the estimated ice crystal accumulation density (Pice) is calculated using a derivation method based on the humidity condensation accumulation rate (Rhumid), heat flux density (Qdissip), and temperature (Tenv). This parameter can measure the risk of ice crystal accumulation on the surface of the sealing components of the hydraulic lifting platform. The derived ice crystal accumulation density (Pice) is combined with the sensing data to generate a standardized sensing dataset. Key parameters in this dataset are further extracted, and the Freeze-Induced Erosion Indicator (FRI) is calculated and output to assess the risk of surface icing of the hydraulic lifting platform in cold environments due to temperature and humidity. The formula for the Freeze-Induced Erosion Indicator (FRI) quantitatively describes the formation intensity and stability of ice crystals based on factors such as ambient humidity, settling time, and heat loss, providing a basis for safety control strategies. The beneficial effects of this method lie in its ability to monitor and quantify the freezing risk of hydraulic lifting platforms in extremely cold environments in real time through standardized processing and ice crystal derivation, enabling early warning and intelligent control of potential freezing hazards. By accurately predicting ice crystal accumulation and sealing risks, differentiated start-up strategies can be adopted based on the Freezing Intensity Index (FRI), effectively avoiding problems such as seal damage, leakage, and pressure imbalance caused by cold starts. This not only improves the operational safety of hydraulic lifting platforms in low-temperature environments and extends the service life of sealing components, but also significantly reduces equipment maintenance and operating costs, and enhances the reliability and stability of the platform in extreme environments.

[0028] Example 4 Please see Figure 1 and Figure 3 Specifically: S3 includes S31; S31. Based on the output of the Freezing Indicator (FRI), a preliminary comparative assessment is conducted, and based on the preliminary comparative assessment results, the freezing erosion is classified. The specific assessment content is as follows: When the Freezing Indicator (FRI) is less than 0.8, the current Freezing Indicator is classified as Level L1, which is considered safe. When the freezing erosion characteristic index FRI∈[0.8,1.6), the current freezing erosion level is classified as L2, i.e., slight freezing; When the freezing erosion characteristic index FRI∈[1.6,2.5), the current freezing erosion level is classified as L3, i.e., moderate freezing. When the freezing erosion characteristic index FRI∈[2.5,3.8), the current freezing erosion level is classified as L4, which is highly frozen; When the Freezing Erosion Characteristic Index (FRI) is greater than 3.8, the current freezing erosion level is classified as L5, which is extreme freezing.

[0029] S3 also includes S32; S32. Based on the preliminary comparative evaluation results, the freezing erosion is classified into different levels, and corresponding preliminary control strategies are implemented. Furthermore, the sealing perturbation dynamic response mechanism is triggered based on the freezing erosion classification results. The specific preliminary control strategies implemented for each freezing erosion level are as follows: When classified as L1, no intervention is required to fully respond and start the hydraulic system; When classified as L2 level, a 2-second warm-up delay is performed before a soft start. When classified as Level L3, the hydraulic pressurization rate is limited to 50%. When classified as L4, the preheating time is delayed by 4 seconds, and the hydraulic pressurization rate is limited to 25%. When classified as L5, startup is prohibited, and a freeze alarm signal is issued. Simultaneously, when the freezing erosion level is ≥L3 but not L5, the sealing perturbation dynamic response mechanism is triggered.

[0030] In this embodiment, the method dynamically assesses the freezing risk during the cold start process of a hydraulic lifting platform based on the Freeze Erosion Characteristic Index (FRI) and formulates corresponding control strategies according to different freeze erosion levels. Specifically, in a safety control server, the output results of the FRI are initially compared and evaluated, and categorized into five levels: L1 Safe, L2 Slight Freeze, L3 Moderate Freeze, L4 High Freeze, and L5 Extreme Freeze. For each level, a corresponding start-up control strategy is adopted according to the risk level to ensure the safety of the hydraulic system. By accurately assessing the freezing risk during the environmental cold start process, this method can intelligently adjust the start-up strategy of the hydraulic lifting platform under different freeze erosion levels, ensuring that failures caused by low-temperature icing and seal damage are minimized during platform start-up. By dynamically adjusting the hydraulic pressurization rate and preheating time during start-up, this method effectively avoids seal damage caused by ice crystal accumulation, thereby extending the service life of the hydraulic platform, improving the reliability and safety of the platform in extremely cold environments, significantly reducing the failure rate, and lowering equipment maintenance costs.

[0031] Example 5 Please see Figure 1 Specifically: S4 includes S41; S41. After triggering the dynamic response mechanism of sealing perturbation, extract the freezing erosion characteristic index FRI(t) at the current time t, combine it with the micro-vibration frequency response Fvib and the instantaneous pressure rise ratio ΔP to calculate and output the sealing perturbation response index SPI to measure the damage state of the sealing lip when the large hydraulic platform is cold started. The Seal Perturbation Response Index (SPI) is calculated and output using the following algorithm formula; ; Always, Seal represents the ultimate safe stress of the sealing lip, which is set by the user and is a dimensionless value; The derivation logic and physical meaning of the formula: The vibration-pressure ratio is used to analyze the dynamic disturbance intensity of the hydraulic structure. The stronger the micro-vibration, the more likely the structure may enter a nonlinear micro-crack state. The faster the pressure rise, the higher the risk. This item comprehensively judges whether the rapid pressure rise of the platform and the surge in vibration frequency indicate that the sealed structure is unstable due to impact. The instantaneous pressure rise ratio ΔP+1 is to ensure the stability of the control system and prevent the denominator from being 0. The quadratic term of the micro-vibration frequency response Fvib reflects the nonlinear amplification effect of vibration intensity on structural damage. This indicates an amplification of environmental ice crystal erosion. The more severe the freezing environment, the more fragile the sealing structure; the lower the sealing limit strength, the weaker the impact resistance. This item plays a role in amplifying environmental risks. If the current environmental ice intrusion risk is high, even if the disturbance is small, it should be handled with caution. The formula is based on the following: microcracks initially manifest as high-frequency micro-vibration fluctuations. If the hydraulic speed is increased too quickly during a cold start, the impact will be enormous. Ice crystal adhesion will weaken the flexibility of the sealing material, causing it to enter the stress response state prematurely. The amplitude of micro-vibration is proportional to the stress gradient. If it is close to the critical stress point, a small disturbance may break through the micro-crack zone. Therefore, high-frequency vibration should be used as a predictive variable and the judgment boundary should be controlled in combination with environmental amplification factors.

[0032] S4 also includes S42; S42. Based on the obtained sealing perturbation response index SPI and freezing erosion characteristic index FRI, a comprehensive calculation is performed to output the start-up control composite response index CCI, which serves as the basis for the final control strategy switching. The composite response index (CCI) for startup control is calculated and output using the following algorithm formula; ; In the formula, tiele represents the resting time; The derivation logic and physical meaning of the formula: The main component representing the risk perception of ice intrusion and structural disturbance is FRI, which assesses the trend of ice crystal formation and freezing. SPI reflects whether there are micro-perturbation anomalies in the structural response during cold start. The SPI is nonlinearly enhanced by squaring to reflect its destructive sensitivity. The overall average is then taken to maintain the magnitude balance and avoid the dominance of a single indicator. This represents the coupling amplification adjustment term for the interaction of time and environmental factors. The longer the resting time (tidle), the more severe the icing. The lower the Tenv temperature, the faster the freezing. Adding 0.45 is to prevent the denominator from being 0. Its actual function is to convert the negative temperature into a positive range. The larger the overall term, the more unfavorable the environment, and the more cautious one should be in starting it.

[0033] In this embodiment, the method effectively improves the cold start safety of the hydraulic lifting platform in extremely cold environments by introducing a sealing perturbation dynamic response mechanism and a comprehensive calculation of the startup control composite response index (CCI). The specific implementation includes: after triggering the sealing perturbation dynamic response mechanism, the sealing perturbation response index (SPI) is calculated and output by extracting the freezing erosion characteristic index (FRI), the micro-vibration frequency response (Fvib) during the hydraulic pressurization process, and the instantaneous pressure rise ratio (ΔP) in real time. This index measures the damage state of the sealing lip of the hydraulic system during cold starts, thus providing a basis for subsequent startup control strategies. The calculation formula for the sealing perturbation response index (SPI) integrates the vibration pressure ratio, reflecting the dynamic perturbation intensity of the hydraulic structure and the amplification term of environmental ice crystal erosion. It also reflects the destructive impact of micro-vibrations on the sealing structure through a nonlinear enhancement square term of the vibration frequency. The environmental risk amplification term considers the vulnerability of the sealing material to the low-temperature freezing environment, ensuring that even with small perturbations, potential structural damage can be carefully handled. Based on this, the Start-up Control Composite Response Index (CCI) outputs a unified control index by comprehensively calculating the Freeze-Invasion Characteristic Index (FRI) and the Seal Perturbation Response Index (SPI), which is used to dynamically adjust the hydraulic system startup strategy. The CCI value is adjusted in conjunction with the settling time (tidle) and temperature (Tenv), reflecting the increase in freezing risk and structural disturbance over time and with temperature changes. This ensures strict control of the startup process in high-risk environments, preventing equipment damage caused by ice crystal accumulation and structural fragility. This invention achieves precise cold-start risk assessment and control through this series of steps, improving the operational safety of hydraulic lifting platforms in extremely cold environments. Through intelligent freeze assessment and structural condition monitoring, the system can dynamically adjust the hydraulic pressurization rate, preheating time, and startup mode during the startup process according to the actual environment, significantly reducing system failures or downtime caused by ice crystal damage and seal damage.

[0034] Example 6 Please see Figure 1 Specifically: S5 includes S51 and S52; S51. Based on the user, set the control interval threshold, which includes the first control threshold F1, the second control threshold F2 and the third control threshold F3. Compare and evaluate the control interval threshold with the activation control composite response index (CCI). Analyze the risk status after the initial control strategy is implemented based on the comparison and evaluation results. The specific evaluation content is as follows: When the initial control composite response index CCI is less than the first control threshold F1, it indicates that the initial control strategy is successful, and the hydraulic system is started at full speed. When the first control threshold F1 ≤ the activation control composite response index CCI < the second control threshold F2, it indicates that there is a level one risk after the initial control strategy is implemented; When the first control threshold F2 ≤ the initial control composite response index CCI < the second control threshold F3, it indicates that there is a secondary risk after the initial control strategy is implemented; When the initial control composite response index (CCI) is greater than or equal to the second control threshold (F3), it indicates that there is a level 3 risk after the initial control strategy is implemented. Wherein, the first control threshold F1 < the second control threshold F2 < the third control threshold F3; S52. Based on the comparative evaluation results, analyze the risk status after the implementation of the preliminary control strategy, and trigger the final execution strategy. The specific content of the final execution strategy is as follows: If the risk level is classified as Level 1, the initial control strategy will be delayed by 3 seconds and the current output power will be limited to 70%. If the risk level is classified as Level 2, then based on the current preliminary control strategy, the current output power will be limited to 50%, and a linear increase in hydraulic pressure of 10% will be initiated. If the risk level is classified as Level 3, startup will be prohibited, a freeze alarm signal will be issued, and the system will be forced into maintenance mode.

[0035] In this embodiment, the method achieves refined risk management and adaptive start-up control of the hydraulic lifting platform during cold start by setting multi-level control interval thresholds and comparing them with the start-up control composite response index (CCI). Specifically, the user sets control interval thresholds according to actual needs and compares the start-up control CCI with these thresholds to determine the potential risk status of the hydraulic equipment during cold start. Based on the evaluation results, the system is divided into three risk levels and corresponding preliminary control strategies are adopted. Through this dynamic adjustment based on risk levels, the system can flexibly respond to potential dangers under different cold start conditions, ensuring the safety of the hydraulic lifting platform in extremely cold environments. Compared with traditional full-speed start or single-limitation methods, the multi-level risk assessment and adaptive control strategy of this invention significantly improves the safety of the hydraulic system and reduces failures caused by freezing and seal rupture. This method, through intelligent risk control, not only improves the start-up stability of the equipment in low-temperature environments but also reduces maintenance costs, ensuring the efficient and reliable operation of the hydraulic lifting platform in extremely cold environments.

[0036] Example 7 Please see Figure 1 and Figure 2 Figure 2 A safety control system for a hydraulic lifting platform includes a sensing layout module, a freeze erosion analysis module, a freeze erosion classification module, a sealing disturbance response module, and a composite control module. The perception layout module sets key points on the large hydraulic lifting platform and installs sensing devices within these key points to collect real-time perception data from the large hydraulic lifting platform and transmit the perception data to the safety control server. The Freeze Erosion Analysis Module preprocesses the sensing data in the security control server to obtain a standardized sensing dataset and calculates and outputs the Freeze Erosion Feature Index (FRI). The freezing erosion classification module classifies freezing erosion based on the output of the freezing erosion characteristic index FRI, then initiates the corresponding preliminary control strategy based on the freezing erosion classification results, and triggers the sealing perturbation dynamic response mechanism when the freezing erosion classification exceeds L3 level. The sealing disturbance response module calculates based on the freezing erosion characteristic index FRI after triggering the sealing disturbance dynamic response mechanism, and outputs the sealing disturbance response index SPI. Then, it calculates and outputs the start-up control composite response index CCI. The composite control module compares and evaluates the control interval threshold with the start control composite response index (CCI) to trigger the final execution strategy.

[0037] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A safety control method for a hydraulic lifting platform, characterized in that: Includes the following steps: S1. Set key points on the large hydraulic lifting platform and install sensing devices within the key points to collect sensing data from the large hydraulic lifting platform in real time and transmit the sensing data to the safety control server. S2. Preprocess the sensing data in the security control server to obtain a standardized sensing dataset and calculate and output the Freeze Erosion Feature Index (FRI). S3. Based on the output of the freezing erosion characteristic index FRI, the freezing erosion is classified, and then the corresponding preliminary control strategy is initiated based on the freezing erosion classification results. When the freezing erosion classification exceeds L3 level, the sealing perturbation dynamic response mechanism is triggered. S4. After triggering the sealing perturbation dynamic response mechanism, calculate based on the freezing erosion characteristic index FRI, output the sealing perturbation response index SPI, and then calculate and output the start-up control composite response index CCI. S5. Set the control interval threshold and compare it with the start control composite response index (CCI) to trigger the final execution strategy.

2. The safety control method for a hydraulic lifting platform according to claim 1, characterized in that: S1 includes S11 and S12; S11. Set up 4 key points on the large hydraulic lifting platform and install sensing devices in each key point to collect real-time sensing data of the large hydraulic lifting platform in the cold environment. The key points include key point A1, key point A2, key point A3, and key point A4; The sensing devices include thin-film capacitive humidity sensors, thin-film heat flow sensors, thermocouple arrays, acoustic emission sensors, and responsive piezoelectric pressure sensors. The sensed data includes humidity condensation and accumulation rate Rhumid, heat flux density Qdissip, micro-vibration frequency response Fvib, instantaneous pressure rise ratio ΔP, and temperature Tenv; S12. Based on the communication modules built into all sensing devices, the LoRa physical layer and LoRaWAN network protocol stack are set up to work together to connect the communication modules of the sensing devices to the security control server end-to-end. After the end-to-end connection is established, the sensing data acquired in real time is transmitted to the security control server.

3. The safety control method for a hydraulic lifting platform according to claim 2, characterized in that: S2 includes S21; S21. Preprocess the sensing data in the security control server to obtain a standardized sensing dataset; The pretreatment includes standardization and ice crystal derivation; The standardization process is performed by using Z-score standardization to standardize the perceived data, thereby eliminating the influence of the dimensions of all parameters in the perceived data. The ice crystal derivation is based on the humidity condensation and aggregation rate Rhumid, the heat flux density Qdissip, and the temperature Tenv to obtain the estimated ice crystal aggregation density Pice. The estimated ice crystal aggregation density Pice is then combined with the sensing data to obtain a standardized sensing dataset. The estimated ice crystal aggregation density, Pice, is derived using the following algorithm: Pice = f(Rhumiud, timel, Tenv, Qdissip), where f represents a function estimator that maps multiple environmental variables to aggregation density, and timel represents the settling time, which is dimensionless. The standardized sensing dataset includes the humidity condensation aggregation rate Rhumid, heat flux density Qdissip, micro-vibration frequency response Fvib, instantaneous pressure rise ratio ΔP, and estimated ice crystal aggregation density Pice.

4. The safety control method for a hydraulic lifting platform according to claim 3, characterized in that: S2 further includes S22; S22. Extract the humidity condensation aggregation rate Rhumid, heat flux density Qdissip, and estimated ice crystal aggregation density Pice from the standardized sensing dataset, calculate and output the freezing erosion characteristic index FRI, and measure the surface icing phenomenon of the sealing structure of a large hydraulic lifting platform after a long period of stillness in a cold environment due to the effects of temperature and humidity. The Freeze Erosion Characteristic Index (FRI) is calculated and output using the following algorithm formula; ； In the formula, log represents the logarithmic function.

5. The safety control method for a hydraulic lifting platform according to claim 4, characterized in that: S3 includes S31; S31. Based on the output of the Freezing Indicator (FRI), a preliminary comparative assessment is conducted, and based on the preliminary comparative assessment results, the freezing erosion is classified. The specific assessment content is as follows: When the Freezing Indicator (FRI) is less than 0.8, the current Freezing Indicator is classified as Level L1, which is considered safe. When the freezing erosion characteristic index FRI∈[0.8,1.6), the current freezing erosion level is classified as L2, i.e., slight freezing; When the freezing erosion characteristic index FRI∈[1.6,2.5), the current freezing erosion level is classified as L3, i.e., moderate freezing. When the freezing erosion characteristic index FRI∈[2.5,3.8), the current freezing erosion level is classified as L4, which is highly frozen; When the Freezing Erosion Characteristic Index (FRI) is greater than 3.8, the current freezing erosion level is classified as L5, which is extreme freezing.

6. The safety control method for a hydraulic lifting platform according to claim 5, characterized in that: S3 further includes S32; S32. Based on the preliminary comparative evaluation results, the freezing erosion is classified into different levels, and corresponding preliminary control strategies are implemented. Furthermore, the sealing perturbation dynamic response mechanism is triggered based on the freezing erosion classification results. The specific preliminary control strategies implemented for each freezing erosion level are as follows: When classified as L1, no intervention is required to fully respond and start the hydraulic system; When classified as L2 level, a 2-second warm-up delay is performed before a soft start. When classified as Level L3, the hydraulic pressurization rate is limited to 50%. When classified as L4, the preheating time is delayed by 4 seconds, and the hydraulic pressurization rate is limited to 25%. When classified as L5, startup is prohibited, and a freeze alarm signal is issued. Simultaneously, when the freezing erosion level is ≥L3 but not L5, the sealing perturbation dynamic response mechanism is triggered.

7. The safety control method for a hydraulic lifting platform according to claim 6, characterized in that: S4 includes S41; S41. After triggering the dynamic response mechanism of sealing perturbation, extract the freezing erosion characteristic index FRI(t) at the current time t, combine it with the micro-vibration frequency response Fvib and the instantaneous pressure rise ratio ΔP to calculate and output the sealing perturbation response index SPI to measure the damage state of the sealing lip when the large hydraulic platform is cold started. The sealing perturbation response index (SPI) is calculated and output using the following algorithm formula; ； Always, Seal represents the ultimate safe stress of the sealing lip, which is set by the user and is a dimensionless value.

8. The safety control method for a hydraulic lifting platform according to claim 7, characterized in that: S4 further includes S42; S42. Based on the obtained sealing perturbation response index SPI and freezing erosion characteristic index FRI, a comprehensive calculation is performed to output the start-up control composite response index CCI, which serves as the basis for the final control strategy switching. The startup control composite response index (CCI) is calculated and output using the following algorithm formula; ； In the formula, "tidle" represents the resting time.

9. A safety control method for a hydraulic lifting platform according to claim 8, characterized in that: S5 includes S51 and S52; S51. Based on the user setting control interval thresholds, the control interval thresholds include a first control threshold F1, a second control threshold F2, and a third control threshold F3. The control interval thresholds are compared and evaluated with the activation control composite response index (CCI). Based on the comparison and evaluation results, the risk status after the initial control strategy is executed is analyzed. The specific evaluation content is as follows. When the initial control composite response index CCI is less than the first control threshold F1, it indicates that the initial control strategy is successful, and the hydraulic system is started at full speed. When the first control threshold F1 ≤ the activation control composite response index CCI < the second control threshold F2, it indicates that there is a level one risk after the initial control strategy is implemented; When the first control threshold F2 ≤ the initial control composite response index CCI < the second control threshold F3, it indicates that there is a secondary risk after the initial control strategy is implemented; When the initial control composite response index (CCI) is greater than or equal to the second control threshold (F3), it indicates that there is a level 3 risk after the initial control strategy is implemented. Wherein, the first control threshold F1 < the second control threshold F2 < the third control threshold F3; S52. Based on the comparative evaluation results, analyze the risk status after the implementation of the preliminary control strategy, and trigger the final execution strategy. The specific content of the final execution strategy is as follows: If the risk level is classified as Level 1, the initial control strategy will be delayed by 3 seconds and the current output power will be limited to 70%. If the risk level is classified as Level 2, then based on the current preliminary control strategy, the current output power will be limited to 50%, and a linear increase in hydraulic pressure of 10% will be initiated. If the risk level is classified as Level 3, startup will be prohibited, a freeze alarm signal will be issued, and the system will be forced into maintenance mode.

10. A safety control system for a hydraulic lifting platform, applied to the safety control method for a hydraulic lifting platform as described in any one of claims 1-9, characterized in that: It includes a sensing layout module, a freezing erosion analysis module, a freezing erosion classification module, a sealing disturbance response module, and a composite control module; The sensing layout module sets key points on the large hydraulic lifting platform and sets sensing devices within the key points to collect sensing data from the large hydraulic lifting platform in real time and transmit the sensing data to the safety control server. The freeze erosion analysis module preprocesses the sensing data in the security control server to obtain a standardized sensing dataset and calculates and outputs the freeze erosion characteristic index (FRI). The freezing erosion classification module classifies freezing erosion based on the output of the freezing erosion characteristic index FRI, then initiates a corresponding preliminary control strategy based on the freezing erosion classification results, and triggers a sealing perturbation dynamic response mechanism when the freezing erosion classification exceeds L3 level. The sealing disturbance response module calculates based on the Freeze-Induced Erosion (FRI) characteristic index after triggering the sealing disturbance dynamic response mechanism, outputs the sealing disturbance response index SPI, and then calculates and outputs the start-up control composite response index CCI. The composite control module compares and evaluates the control interval threshold with the start control composite response index (CCI) to trigger the final execution strategy.

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