An intelligent load balancing control system for an automotive lift

Abstract

The present invention relates to the technical field of automobile lifts, and specifically to an intelligent load balancing control system for automobile lifts. The system includes a data acquisition and analysis module, a load status assessment module, a load balancing adjustment module, a lift monitoring module, and a safety protection control module. The present invention, by collecting pressure sensor and vehicle weight data in real time, can reflect the load conditions of each fulcrum, and conduct in-depth analysis based on this, identifying the load differences between the fulcrums and the overall balance state of the vehicle, thereby automatically calculating the pressure value required for adjustment. Combined with the precise adjustment of the servo motor, the dynamic management efficiency of the load is greatly improved. The real-time monitoring and feedback mechanism can instantly identify load deviations exceeding the threshold, automatically trigger a safety warning, and take necessary adjustment measures to ensure the absolute safety of the lifting process. Especially when handling heavy vehicles, it not only improves operational safety, but also ensures the efficiency and accuracy of maintenance operations.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automobile lift, in particular to an intelligent load balancing control system for automobile lift. BACKGROUND

[0002] The automobile lift mainly relates to the equipment for lifting the vehicle to carry out the maintenance and the inspection, the equipment can be mechanical, hydraulic or electric, so that the vehicle can be safely lifted in the air, thereby providing enough space for the technician to carry out the maintenance work of chassis, tire and vehicle bottom, the design of the automobile lift considers the load bearing capacity, stability and safety, ensures that the vehicle keeps balance and stability during the lifting process.

[0003] Among them, the intelligent load balancing control system for automobile lift is a system integrated with sensors and control algorithms, which is used for automatically monitoring and adjusting the load distribution on the lift, the main purpose is to ensure that the weight of the vehicle is evenly distributed on each support point during the lifting of the automobile, prevent mechanical failure or safety accident caused by the center of gravity deviation, the use of the system can significantly improve the maintenance efficiency and safety, especially in the case of heavy vehicles.

[0004] The prior art has obvious short board in load monitoring and dynamic adjustment, lacks real-time data support and automatic feedback mechanism, leading to the dependence of the operator's judgment in the stability and overload protection of the lift in dealing with complex or irregular load, to a certain extent, increases the operation risk and the potentiality of mechanical failure, for example, in the case of no real-time monitoring system, any abnormal load of the support point is not discovered in time, leading to the damage of the lift structure or serious safety accident, such as vehicle sliding or overturning, not only affects the service life of the lift, but also endangers the safety of the maintenance personnel, especially in emergency, the reaction speed and processing accuracy of the existing system are difficult to meet the needs of modern automobile maintenance. SUMMARY

[0005] The purpose of the present application is to solve the shortcomings in the prior art, and an intelligent load balancing control system for automobile lift is proposed.

[0006] In order to achieve the above purpose, the present application adopts the following technical scheme: an intelligent load balancing control system for automobile lift, the system comprises:

[0007] The data acquisition and analysis module obtains the pressure sensor data and vehicle weight data installed on the support point of the lift, receives the data stream through the lift control system, analyzes the pressure sensor and vehicle weight data, and establishes a real-time load data set;

[0008] The load state assessment module compares the load data of each support point based on the real-time load data set, identifies the load distribution that deviates from the normal range, and analyzes the load difference between the overall load center of the vehicle and each support point to obtain load offset analysis information;

[0009] The load balancing adjustment module adjusts the force of the lifting fulcrum based on the load offset analysis information and compares it with the current balance threshold of the lift. If a deviation outside the normal range is detected, the pressure adjustment value is automatically recalculated and the lift servo motor is controlled to adjust the fulcrum pressure to obtain the balance state parameters.

[0010] The lift monitoring module monitors the balance state parameters, collects the adjusted pressure sensor data, and compares it with the original state in real time. If the error exceeds the design allowable range, it automatically triggers a safety warning, records the relevant data, and obtains a load adjustment feedback log.

[0011] The present invention has the following improvements: the real-time load data set includes pressure value, total weight, and acquisition time; the load offset analysis information includes offset value, balance assessment result, and difference index; the balance state parameters include adjustment pressure, threshold comparison information, and adjustment index; and the load adjustment feedback log includes error results, deviation amount, and warning mark.

[0012] The present invention is improved in that the data acquisition and analysis module includes:

[0013] The data acquisition submodule acquires data from the pressure sensor installed at the lift fulcrum and the vehicle weight data, parses and extracts the measured values, removes abnormal data through unit conversion and data correction, and generates accurate sensor and vehicle data;

[0014] The load state calculation submodule analyzes the deviation between the sensor pressure data and the vehicle weight based on the accurate sensor and vehicle data, using the formula:

[0015] ;

[0016] Calculating Load Error Percentage , get the current load state of the lift, where Representative The pressure value of a pressure sensor, represents the normalized vehicle weight value, Represents the number of sensors;

[0017] The load data establishment submodule continuously monitors the load changes of the lift based on the current load status of the lift and combines the timestamp recorded data to establish a real-time load data set.

[0018] The load state evaluation module comprises:

[0019] The load data comparison submodule compares the load data of each support point based on the real-time load data set, screens the load data deviating from the normal range, and calculates the difference between the support point load and the global load average to obtain abnormal load data;

[0020] The load center analysis submodule identifies the overall load center of the vehicle based on the abnormal load data, and uses the formula:

[0021] ;

[0022] And

[0023] ;

[0024] Obtain the lateral coordinate of the load center And the longitudinal coordinate of the load center , and analyze the load difference between multiple support points to obtain the vehicle balance state, wherein, represents the load data of the th support point, and represent the coordinate position of the th support point, represents the number of support points;

[0025] The load offset calculation submodule calls the vehicle balance state, calculates the difference between the load center coordinates and the theoretical symmetry center of the vehicle, analyzes the offset of each support point, and obtains load offset analysis information.

[0026] The load balance adjustment module comprises:

[0027] The support point pressure adjustment submodule adjusts the force of the lifting support point according to the load offset analysis information, calculates the current pressure value of each support point, and compares it with the current balance threshold of the lifting machine to screen the support point pressure data deviating from the normal range, and obtains the out-of-limit support point pressure data;

[0028] The pressure deviation calculation submodule recalculates the pressure adjustment value and corrects the deviation based on the out-of-limit support point pressure data, and uses the formula:

[0029] ;

[0030] Obtain the pressure adjustment value of the th support point , and obtain the support point pressure adjustment parameter, wherein, represents the current pressure of the th support point, Represents the current balance threshold of the lift. Representative The pressure of other fulcrums, Represents the number of fulcrums, It means that in the summation process, all The pressure on all other fulcrums except include in;

[0031] The servo motor control submodule sends a control instruction to the lift servo motor according to the fulcrum pressure adjustment parameter, adjusts the pressure of each fulcrum to match the expected load balance state, and obtains the balance state parameter.

[0032] The present invention is improved in that the lift monitoring module includes:

[0033] The equilibrium state monitoring submodule monitors the equilibrium state parameters, collects the adjusted pressure sensor data and real-time pressure data, and calls the original state pressure data for comparison to obtain the pressure change value;

[0034] The regulation error analysis submodule analyzes the regulation error and regulation deviation based on the pressure change value, using the formula:

[0035] ;

[0036] Calculate the adjustment error value , analyze whether it exceeds the allowable range of the lift design and obtain the error judgment result, among which, Representative The pressure after the fulcrum is adjusted, Representative The pressure of the fulcrum in its original state, Represents the number of fulcrums;

[0037] The safety warning triggering submodule calls the error determination result. If the adjustment error exceeds the design allowable range, a safety warning is automatically triggered, and related data is recorded to obtain a load adjustment feedback log.

[0038] The present invention is improved in that the system further comprises:

[0039] The safety protection control module analyzes the pressure change data of the lifting fulcrum based on the load adjustment feedback log, calculates the stability of the load distribution, and determines whether it is an abnormal state. If abnormal, it adjusts the working state of the lift and limits its lifting height to obtain a lifting safety state;

[0040] The lifting safety status includes operation restrictions, status adjustments, and height limit indicators.

[0041] The present invention is improved in that the security protection control module includes:

[0042] The pressure change analysis submodule analyzes the pressure change data of the lifting fulcrum based on the load adjustment feedback log, calculates the pressure change trend, and obtains the fulcrum pressure change value;

[0043] The load stability calculation submodule calls the fulcrum pressure change value to analyze the stability of the load distribution using the formula:

[0044] ;

[0045] Calculate load stability factor , determine whether it is an abnormal state and obtain the stability judgment result, where, Representative The pressure after the fulcrum is adjusted, Represents the average value of the fulcrum pressure, represents the standard deviation of the pivot pressure, Represents the total number of pivot points;

[0046] The lifting safety adjustment submodule calls the stability determination result, and if it is determined to be an abnormal state, adjusts the working state of the lift, limits the lifting height, and obtains a lifting safety state.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are:

[0048] In the present invention, by collecting pressure sensor and vehicle weight data in real time, it is possible to reflect the load conditions of each fulcrum, and conduct in-depth analysis based on this, identify the load differences between the fulcrums and the overall balance state of the vehicle, and automatically calculate the pressure value that needs to be adjusted. Combined with the precise adjustment of the servo motor, the dynamic management efficiency of the load is greatly improved. The real-time monitoring and feedback mechanism can instantly identify load deviations that exceed the threshold, and automatically trigger safety warnings, take necessary adjustment measures, and ensure the absolute safety of the lifting process. Especially when handling heavy vehicles, it not only improves operational safety, but also ensures the efficiency and accuracy of maintenance operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a system flow chart of the present invention;

[0050] Figure 2 This is a flow chart of the data acquisition and analysis module in the present invention;

[0051] Figure 3 is a flow chart of the load status evaluation module in the present invention;

[0052] Figure 4 This is a flow chart of the load balancing adjustment module in the present invention;

[0053] Figure 5Flow chart of the lifting machine monitoring module in the present application;

[0054] Figure 6 Flow chart of the safety protection control module in the present application. DETAILED DESCRIPTION

[0055] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0056] In the description of the present application, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the present application and simplify the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. In addition, in the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise explicitly and specifically limited. EMBODIMENT

[0057] Please refer to Figure 1 The present application provides a technical solution: an intelligent load balancing control system for an automobile lifting machine, comprising:

[0058] The data acquisition and analysis module acquires pressure sensor data and vehicle weight data installed at the lifting machine fulcrum, receives data streams through the lifting machine control system, analyzes the pressure sensor and vehicle weight data, determines the current load state of the lifting machine, and establishes a real-time load data set;

[0059] The load state evaluation module compares the load data of each fulcrum based on the real-time load data set, identifies the load distribution deviating from the normal range, analyzes the overall load center of the vehicle and the load difference between each fulcrum, determines the balance state of the vehicle, and obtains load offset analysis information;

[0060] The load balancing adjustment module adjusts the force of the lifting fulcrum according to the load offset analysis information, compares it with the current balance threshold of the lifting machine, and if a deviation beyond the normal range is detected, automatically recalculates the pressure adjustment value and controls the lifting machine servo motor to adjust the fulcrum pressure to match the expected load balance and obtain the balance state parameter;

[0061] The lifting machine monitoring module monitors the balance state parameter, collects the adjusted pressure sensor data, compares in real time with the original state, analyzes the adjustment error and adjustment deviation, if the error exceeds the design allowable range, automatically triggers a safety warning, records the associated data, and obtains the load adjustment feedback log;

[0062] The safety protection control module analyzes the pressure change data of the lifting fulcrum based on the load adjustment feedback log, calculates the stability of the load distribution, judges whether it is an abnormal state, if it is abnormal, adjusts the working state of the lifting machine, limits its lifting height, and obtains the lifting safety state.

[0063] The real-time load data set includes pressure value, total weight, collection time, load offset analysis information includes offset value, balance evaluation result, difference index, balance state parameter includes adjustment pressure, threshold comparison information, adjustment index, load adjustment feedback log includes error result, deviation, warning mark, lifting safety state includes operation restriction, state adjustment, height restriction index.

[0064] Please refer to Figure 2 , the data collection and analysis module comprises:

[0065] The data collection submodule obtains the pressure sensor data and vehicle weight data installed on the lifting machine fulcrum, analyzes and extracts the measurement value, removes abnormal data through unit conversion and data correction, and generates accurate sensor and vehicle data;

[0066] During reading, the collected pressure value is unit converted, the data of each pressure sensor is converted into a standard unit, for example, if the sensor output is mV / V, it needs to be converted into N or kgf, and data storage is performed, at the same time, the vehicle weight data is collected, a weighing sensor or a weighbridge device is used, and a standard unit of vehicle weight value is obtained, in the data processing stage, preliminary data screening is performed, and abnormal values appearing in the collection process are removed, for example, sensor data mutation, outliers or obviously unreasonable data points, by setting a threshold range, for example, for a lifting machine with a rated load of 10000N, if the pressure data of a single sensor exceeds ±20% of this range, it is determined as abnormal data, after excluding abnormal data, the remaining data is standardized, for example, using the maximum and minimum normalization method, the data is normalized to the [0, 1] interval, to ensure the comparability of different sensor data, at the same time, noise filtering processing is performed, for example, using mean filtering or Kalman filtering method, to reduce the data fluctuation caused by environmental interference, to improve data accuracy, after all data is screened, standardized and filtered, accurate sensor and vehicle data is generated.

[0067] The load state calculation submodule analyzes the deviation between the sensor pressure data and the vehicle weight based on the accurate sensor and vehicle data, using the formula:

[0068] ;

[0069] Load error percentage , the current load state of the lift is obtained, wherein, represents the pressure value of the th pressure sensor, represents the standardized vehicle weight value, represents the number of sensors;

[0070] The data of all pressure sensors are summed to calculate the total pressure value on the fulcrum of the lift, that is , secondly, the difference between the total pressure value and the standardized vehicle weight value is calculated, and the absolute value calculation method is used to ensure that the error is always positive, finally, in order to quantify the error degree, the error value is divided by the standardized vehicle weight value and multiplied by 100% to obtain the load error percentage , the pressure data measured by the four sensors of a certain lift are 2300N, 2500N, 2400N and 2350N, and the standardized weight of the vehicle is 9500N, then the total pressure , the load error percentage is calculated as follows:

[0071] ;

[0072] The calculation result shows that the current load error of the lift is 0.526%, if the safety range set by the system is ±5%, the error value is within the acceptable range, therefore it can be judged that the current load state of the lift is normal.

[0073] The load data establishment submodule continuously monitors the load change of the lift based on the current load state of the lift and the timestamp record data, and establishes a real-time load data set;

[0074] When new data is collected each time, the current time information is obtained, for example, the data is recorded in Unix timestamp format, to ensure that the data can be arranged in chronological order, then the collected pressure sensor data, vehicle weight data and calculated load error percentage are stored in the database or real-time data stream to form a data sequence, at the same time, the time interval of data recording is set, for example, data is collected every second, when subsequent data analysis is performed, the change trend of the load error percentage can be calculated, for example, the average load error in each minute is calculated using a sliding window, to monitor the load change, during the continuous data recording process, an abnormal monitoring threshold can also be set, for example, if the load error percentage exceeds ±5% for 10 consecutive times, an alarm is triggered, in this way, a real-time load data set is established.

[0075] Referring to Figure 3 , the load state evaluation module comprises:

[0076] The load data comparison submodule compares the load data of each support point based on the real-time load data set, filters the load data deviating from the normal range, and calculates the difference between the support point load and the global load average to obtain abnormal load data;

[0077] The load data of each support point is compared. First, the load data of each support point in different time periods is obtained, and the load data of all support points is summarized. The load average of each support point in a specific time is calculated to determine the reference load level. For load data deviating from the normal range, the load fluctuation range needs to be set first. This range can be obtained based on historical data statistics. For example, the normal range is determined by calculating the load average and the standard deviation of all support points . The load data exceeding this range is filtered out as abnormal data. In actual application, assuming that the load data of a lifting machine support point is 520kg, 510kg, 530kg, 600kg and 490kg, and the average of other support points is 515kg, and the standard deviation is 20kg, the data of 600kg of this support point is abnormal load data. To further analyze the difference between the support point load and the global load average, the load average of each support point needs to be calculated and compared with the global average . For example, if the load average of a support point is 490kg and the global average is 515kg, the deviation is -25kg. All abnormal load data is filtered out.

[0078] The load center analysis submodule identifies the overall load center of the vehicle based on the abnormal load data, using the formula:

[0079] ;

[0080] and

[0081] ;

[0082] The transverse coordinate of the load center and the longitudinal coordinate of the load center are obtained, and the load difference between multiple support points is analyzed to obtain the vehicle balance state, wherein, represents the load data of the th support point, and represent the coordinate position of the th support point, represents the number of support points;

[0083] The vehicle has four support points, whose coordinates are , , and , and the load data are 500kg, 520kg, 480kg and 510kg respectively. Then the load center coordinates are calculated as follows:

[0084] Calculate the horizontal coordinate:

[0085] ;

[0086] ;

[0087] Calculate the vertical coordinate:

[0088] ;

[0089] ;

[0090] The obtained load center coordinates are . By the position of the load center, the balance state of the vehicle can be further analyzed, for example, compared with the design symmetry center of the vehicle to determine whether it is offset.

[0091] The load offset calculation submodule calls the vehicle balance state, calculates the difference between the load center coordinates and the theoretical symmetry center of the vehicle, analyzes the offset of each support point, and obtains the load offset analysis information;

[0092] The vehicle balance state is called to calculate the difference between the load center coordinates and the theoretical symmetry center of the vehicle. First, set the theoretical symmetry center of the vehicle as a reference value, calculate the load center coordinate offset , , and then calculate the overall offset: In actual calculation, assuming that the theoretical symmetry center of the vehicle is , the offset is calculated as follows: , , and the overall offset is calculated as:

[0093] ;

[0094] The result shows that the load center of the vehicle is offset by 0.028m relative to the theoretical symmetry center. Through this value, it can be further determined whether the offset is within an acceptable range, for example, if the maximum allowed offset is set to 0.05m, then the current offset is within the acceptable range, otherwise the load distribution needs to be adjusted to reduce the unbalanced state, and the load offset analysis information is obtained.

[0095] Please refer toFigure 4 The load balancing adjustment module comprises:

[0096] The fulcrum pressure adjustment submodule adjusts the force of the lifting fulcrum according to the load offset analysis information, calculates the current pressure value of each fulcrum, and compares it with the current balancing threshold of the lifting machine to screen the fulcrum pressure data that exceeds the normal range and obtain the out-of-limit fulcrum pressure data.

[0097] Real-time load offset analysis information of the lifting machine fulcrum is obtained, which is calculated from pressure data collected by sensors. For example, when lifting a 2000kg equipment with four fulcrums, each fulcrum should bear about 500kg load, but due to uneven distribution of equipment mass, there is deviation in the pressure of each fulcrum. Assuming that the pressure value of a fulcrum is 550kg, and the other three fulcrums are 490kg, 505kg and 455kg respectively, the pressure distribution is uneven at this time and needs to be adjusted. Then, the force data of the lifting fulcrum is called to analyze the pressure applied to each fulcrum and calculate the current actual pressure value of the fulcrum. The pressure sensor measures the force of each fulcrum and obtains the corresponding pressure value. For example, at fulcrum A, the sensor detects a pressure of 550kg, i.e. The pressures of fulcrums B, C and D are 490kg, 505kg and 455kg respectively, i.e. , , Then, the current balancing threshold of the lifting machine is calculated, which is usually set as the theoretical balanced load that each fulcrum should bear. In this example, the ideal state is that the pressure of each fulcrum should be 500kg, i.e. Next, compare each fulcrum pressure value with the balancing threshold to determine whether it exceeds the normal range. Assuming that the deviation of the normal range is set to ±5%, i.e. the pressure value is allowed to be between [475kg, 525kg], then It exceeds the threshold and needs to be further adjusted. Finally, all the fulcrum pressure data that exceeds the range is screened out, for example, in this case, fulcrum A (550kg) and fulcrum D (455kg) exceed the range, generating out-of-limit fulcrum pressure data.

[0098] The pressure deviation calculation submodule recalculates the pressure adjustment value and corrects the deviation based on the out-of-limit fulcrum pressure data, using the formula:

[0099] ;

[0100] The pressure adjustment value of the first fulcrum is obtained , and the fulcrum pressure adjustment parameter is obtained, where represents the current pressure of the first fulcrum, representing the current balance threshold of the lift, representing the pressure of the first other support point, representing the number of support points, means that in the summation process, the pressure of all other support points except the first support point is included;

[0101] If the current pressure of support point A is , the current pressure of support point D is , and the balance threshold is set to , the pressure adjustment value needs to be calculated, and the pressure adjustment value of support point A is calculated as:

[0102] ;

[0103] ;

[0104] The sum of the pressures of support points B, C, and D is calculated as:

[0105] , , ;

[0106] ;

[0107] The mean term is calculated as:

[0108] ;

[0109] ;

[0110] The result is:

[0111] ;

[0112] ;

[0113] Therefore, the pressure adjustment value of support point A is -116.67 kg, indicating that this support point needs to reduce the pressure by 116.67 kg.

[0114] The pressure adjustment value of support point D is calculated as:

[0115] ;

[0116] ;

[0117] The sum of the pressures of support points A, B, and C is calculated as:

[0118] , ,​ ;

[0119] ;

[0120] Calculate the mean term:

[0121] ;

[0122] ;

[0123] The result of the calculation is:

[0124] ;

[0125] ;

[0126] Therefore, the pressure adjustment value of fulcrum D is 105 kg, indicating that the fulcrum needs to increase 105 kg of pressure, the pressure adjustment value of fulcrum A is -116.67 kg, indicating that the pressure of fulcrum A needs to be reduced by 116.67 kg, and the pressure adjustment value of fulcrum D is 105 kg, indicating that the pressure of fulcrum D needs to be increased by 105 kg, and the adjustment value will be used for subsequent servo motor control to perform actual pressure adjustment operation.

[0127] The servo motor control submodule sends control instructions to the lifting machine servo motor according to the fulcrum pressure adjustment parameters, adjusts the pressure of each fulcrum to match the expected load balance state, and obtains the balance state parameters;

[0128] Call the fulcrum pressure adjustment parameters, in the foregoing calculation, fulcrum A needs to reduce 250 kg of pressure, fulcrum D needs to increase 408.33 kg of pressure, the adjustment range of lifting machine servo motor is usually between ± 500 kg, ensure that the adjustment parameters are within the executable range, then send adjustment signal to servo motor, control the action of each fulcrum oil pressure regulator, for example, for fulcrum A, reduce the oil pressure flow to reduce the pressure by 250 kg, while fulcrum D increases the hydraulic support to increase the pressure by 408.33 kg, assuming that the current hydraulic system adjustment accuracy is ± 5 kg, after execution, the pressure of fulcrum A should be adjusted to about 500 ± 5 kg, and the pressure of fulcrum D should be adjusted to 500 ± 5 kg, finally, the sensor re-measures the pressure of each fulcrum to confirm whether the adjusted state matches the target value, if the error exceeds the allowed range, repeat the pressure adjustment process until the balance state parameters are obtained.

[0129] Please refer to Figure 5 , the lifting machine monitoring module comprises:

[0130] The balance state monitoring submodule monitors the balance state parameters, collects the adjusted pressure sensor data and real-time pressure data, and calls the original state pressure data for comparison to obtain the pressure change value;

[0131] The adjusted pressure data is collected by the pressure sensor, and the real-time pressure data is obtained and compared with the original state pressure data. The adjusted pressure data is provided by the pressure sensors of each support point of the lifting machine, the real-time pressure data is continuously updated during the operation of the lifting machine, and the original state pressure data is stored in the system database. After the data is obtained, the adjusted pressure data is compared with the original state pressure data point by point, and the pressure change of each support point is calculated. For example, a lifting machine has 4 support points, and the support point pressure under the original state is 120 kPa, 130 kPa, 125 kPa and 128 kPa, and the adjusted pressure data is 118 kPa, 135 kPa, 123 kPa and 130 kPa, respectively. The pressure change value is -2 kPa, +5 kPa, -2 kPa and +2 kPa, respectively. By comparing and analyzing the pressure change data, the system can identify the trend of pressure adjustment and judge whether abnormal fluctuations occur, and obtain the pressure change value.

[0132] The adjustment error analysis submodule analyzes the adjustment error and adjustment deviation based on the pressure change value, and uses the formula:

[0133] ;

[0134] The adjustment error value is calculated , and whether it exceeds the design allowable range of the lifting machine is analyzed to obtain the error determination result, wherein represents the adjusted pressure of the th support point, represents the pressure of the th support point under the original state, represents the number of support points;

[0135] If the adjusted pressure of the 4 support points is 118 kPa, 135 kPa, 123 kPa and 130 kPa, and the original state pressure is 120 kPa, 130 kPa, 125 kPa and 128 kPa, respectively, then

[0136] ;

[0137] ;

[0138] ;

[0139] The calculated adjustment error value is , and the system compares the error value with the design allowable range of the lifting machine. If the maximum allowable error of the lifting machine is 0.05, the error is within the allowable range. If the calculation result is greater than the value, the system will mark the adjustment as abnormal and generate the error determination result.

[0140] The safety warning trigger submodule calls the error judgment result. If the adjustment error exceeds the design allowable range, it will automatically trigger a safety warning, record the related data, and obtain the load adjustment feedback log;

[0141] The error judgment result is called. If the adjustment error exceeds the design allowable range, a safety warning will be automatically triggered. The safety warning can be triggered by sound alarm, light signal or system notification. At the same time, the system will record the related data of abnormal pressure adjustment and store it in the load adjustment log. For example, if the error judgment result exceeds the threshold of 0.05, the system will send an alarm to the maintenance personnel and record the abnormal data, including the pressure values ​​before and after adjustment of each fulcrum, error value, adjustment time and other information, to obtain the load adjustment feedback log.

[0142] See also Figure 6 , the security protection control module includes:

[0143] The pressure change analysis submodule analyzes the pressure change data of the lifting fulcrum based on the load regulation feedback log, calculates the pressure change trend, and obtains the fulcrum pressure change value;

[0144] Extract the pressure data of all lifting fulcrums at different time points, including the pressure change values ​​before, during and after lifting. The pressure data of the lifting fulcrum can be collected by pressure sensors. The sensors are usually installed at the bottom or connection parts of the lifting fulcrum. The collected data will be transmitted to the data processing unit and combined with the feedback log for time series analysis to ensure the accuracy of the pressure data. Next, the data at different time points are sorted and stored in time series. The pressure change rate of each fulcrum in different time intervals is calculated using the pressure change rate calculation formula: ,in, Indicates the The pressure change rate of each support point, Indicates the pressure value at the current moment, Indicates the pressure value at the previous moment, Represents the time interval. Assuming that the pressure at a certain point changes from 120kPa to 140kPa and the time interval is 10s, the pressure change rate is calculated as follows: , perform the same calculation on all supports to obtain the global pressure change trend. Then, normalize the pressure change rate data to facilitate the subsequent calculation of load stability. The normalization method uses minimum-maximum normalization: ,in, represents the normalized pressure change rate, and They represent the minimum and maximum pressure change rates in the batch of data respectively, and the fulcrum pressure change values ​​of all fulcrums are obtained.

[0145] Load stability calculation sub-module calls the fulcrum pressure change value, analyzes the stability of load distribution, and uses the formula:

[0146] ;

[0147] Calculate the load stability coefficient , to determine whether it is an abnormal state, and get the stability determination result, wherein, represents the adjusted pressure of the th fulcrum, represents the average value of the fulcrum pressure, represents the standard deviation of the fulcrum pressure, represents the total number of fulcrums;

[0148] There are 4 fulcrums, and their pressure values are 140kPa, 135kPa, 145kPa and 138kPa, respectively. The mean value is calculated as follows:

[0149] ;

[0150] The pressure deviation of the above 4 fulcrums is calculated as follows:

[0151] ;

[0152] ;

[0153] Then, the load stability coefficient is calculated, and the numerical calculation is as follows:

[0154] ;

[0155] ;

[0156] ;

[0157] The calculated load stability coefficient , indicating that the current load distribution of the lifting machine is close to an equilibrium state, and has not reached the abnormal state threshold, so there is no need to adjust the lifting machine working state, when , the hydraulic system needs to be adjusted or the lifting height needs to be limited according to the calculation result, and the calculation result directly determines the system adjustment measures. The numerical result is related to the set threshold of the lifting safety state, and further indicates the necessity of safety adjustment.

[0158] The lifting safety adjustment sub-module calls the stability determination result, and if it is judged to be an abnormal state, the lifting machine working state is adjusted, the lifting height is limited, and the lifting safety state is obtained;

[0159] Call the stability judgment result. If the abnormal state is established, adjust the working state of the lift. The adjustment methods include reducing the hydraulic system pressure, reducing the lifting speed or directly limiting the maximum lifting height of the lift. The choice of adjustment method is based on the load stability coefficient The value range of If the value is between 1.0 and 1.2, adjust the hydraulic system pressure to 90% of the original setting value. If the load stability coefficient is calculated as 1.2, the maximum lifting height of the lift is limited to 80% of the initial setting height. Assuming that the initial maximum lifting height of the lift is 2.5m, if the load stability coefficient is calculated as , then the adjusted height is: ,like If it exceeds 1.5, the lifting operation will be completely stopped and a warning signal will be issued. In addition, the adjusted lifting data will be recorded and new lifting safety status data will be formed for subsequent stability monitoring to obtain the lifting safety status.

[0160] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. An intelligent load balancing control system for a car lift, characterized in that: The system comprises: The data acquisition and analysis module obtains data from the pressure sensors installed at the lift fulcrum and the vehicle weight data, receives the data stream through the lift control system, analyzes the pressure sensor and vehicle weight data, and establishes a real-time load data set; The load state assessment module compares the load data of each support point based on the real-time load data set, identifies the load distribution that deviates from the normal range, and analyzes the load difference between the overall load center of the vehicle and each support point to obtain load offset analysis information; The load balancing adjustment module adjusts the force of the lifting fulcrum based on the load offset analysis information and compares it with the current balance threshold of the lift. If a deviation outside the normal range is detected, the pressure adjustment value is automatically recalculated and the lift servo motor is controlled to adjust the fulcrum pressure to obtain the balance state parameters. The load balancing adjustment module includes: The fulcrum pressure adjustment submodule adjusts the force of the lifting fulcrum based on the load offset analysis information, calculates the current pressure value of each fulcrum, compares it with the current balance threshold of the lift, filters out the fulcrum pressure data that exceeds the normal range, and obtains the over-limit fulcrum pressure data; The pressure deviation calculation submodule recalculates the pressure adjustment value and corrects the deviation based on the over-limit support pressure data, using the formula: ； Get the Pressure adjustment value of each fulcrum , get the pivot pressure adjustment parameter, where, Representative The current pressure of the pivot point, Represents the current balance threshold of the lift. Representative The pressure of other fulcrums, Represents the number of fulcrums, It means that in the summation process, except for the The pressure on all other fulcrums except include it in; The servo motor control submodule sends a control instruction to the lift servo motor according to the fulcrum pressure adjustment parameter, adjusts the pressure of each fulcrum to match the expected load balance state, and obtains the balance state parameter; The lift monitoring module monitors the balance state parameters, collects the adjusted pressure sensor data, and compares it with the original state in real time. If the error exceeds the design allowable range, it automatically triggers a safety warning and records the relevant data to obtain a load adjustment feedback log; The lift monitoring module includes: The equilibrium state monitoring submodule monitors the equilibrium state parameters, collects the adjusted pressure sensor data and real-time pressure data, and calls the original state pressure data for comparison to obtain the pressure change value; The regulation error analysis submodule analyzes the regulation error and regulation deviation based on the pressure change value, using the formula: ； Calculate the adjustment error value , analyze whether it exceeds the allowable range of the lift design and obtain the error judgment result, among which, Representative The pressure after the fulcrum is adjusted, Representative The pressure of the fulcrum in its original state, Represents the number of fulcrums; The safety warning triggering submodule calls the error determination result. If the adjustment error exceeds the design allowable range, a safety warning is automatically triggered, and related data is recorded to obtain a load adjustment feedback log.

2. The intelligent load balancing control system for a car lift according to claim 1, characterized in that: The real-time load data set includes pressure value, total weight, and collection time; the load offset analysis information includes offset value, balance assessment result, and difference index; the balance state parameters include adjustment pressure, threshold comparison information, and adjustment index; and the load adjustment feedback log includes error results, deviation amount, and warning mark.

3. The intelligent load balancing control system for a car lift according to claim 1, characterized in that: The data acquisition and analysis module includes: The data acquisition submodule acquires data from the pressure sensor installed at the lift fulcrum and the vehicle weight data, parses and extracts the measured values, removes abnormal data through unit conversion and data correction, and generates accurate sensor and vehicle data; The load state calculation submodule analyzes the deviation between the sensor pressure data and the vehicle weight based on the accurate sensor and vehicle data, using the formula: ； Calculating Load Error Percentage , get the current load state of the lift, where Representative The pressure value of a pressure sensor, represents the normalized vehicle weight value, Represents the number of sensors; The load data establishment submodule continuously monitors the load changes of the lift based on the current load status of the lift and combines the timestamp recorded data to establish a real-time load data set.

4. The intelligent load balancing control system for a car lift according to claim 1, characterized in that: The load status assessment module includes: The load data comparison submodule compares the load data of each fulcrum based on the real-time load data set, filters out the load data that deviates from the normal range, and calculates the difference between the fulcrum load and the global load mean to obtain abnormal load data; The load center analysis submodule identifies the overall load center of the vehicle based on the abnormal load data using the formula: ； and ； Get the horizontal coordinate of the load center and the longitudinal coordinate of the load center , and analyze the load differences between multiple support points to obtain the vehicle equilibrium state, where Representative Load data of each support point, and Representative The coordinate position of the pivot point, Represents the number of fulcrums; The load offset calculation submodule calls the vehicle balance state, calculates the difference between the load center coordinates and the vehicle theoretical symmetry center, analyzes the offset of each support point, and obtains load offset analysis information.

5. The intelligent load balancing control system for a car lift according to claim 1, characterized in that: The system further comprises: The safety protection control module analyzes the pressure change data of the lifting fulcrum based on the load adjustment feedback log, calculates the stability of the load distribution, and determines whether it is an abnormal state. If abnormal, it adjusts the working state of the lift and limits its lifting height to obtain a lifting safety state; The lifting safety status includes operation restrictions, status adjustments, and height limit indicators.

6. The intelligent load balancing control system for a car lift according to claim 5, characterized in that: The security protection control module includes: The pressure change analysis submodule analyzes the pressure change data of the lifting fulcrum based on the load adjustment feedback log, calculates the pressure change trend, and obtains the fulcrum pressure change value; The load stability calculation submodule calls the fulcrum pressure change value to analyze the stability of the load distribution using the formula: ； Calculate load stability factor , determine whether it is an abnormal state and obtain the stability judgment result, where, Representative The pressure after the fulcrum is adjusted, Represents the average value of the fulcrum pressure, represents the standard deviation of the pivot pressure, Represents the total number of pivot points; The lifting safety adjustment submodule calls the stability determination result, and if it is determined to be an abnormal state, adjusts the working state of the lift, limits the lifting height, and obtains a lifting safety state.

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