A super-large lifting capacity construction lift

Abstract

The present invention discloses an elevator for construction with super-large lifting capacity, which is an elevator suitable for large-scale building construction. The load condition of the elevator is monitored in real time by a load sensor and a load distribution sensor, and the acceleration, braking force and driving power of the elevator are dynamically adjusted in combination with an intelligent control algorithm, thereby realizing intelligent adjustment of the load and maintaining the balance state and stable operation of the elevator. At the same time, the output power of each driving mechanism is optimized by an adaptive particle swarm optimization algorithm, so that the load distribution is more balanced, the imbalance and wear of the elevator operation are reduced, and the service life of the equipment is increased. In addition, the technical solution realizes intelligent monitoring and adjustment of the elevator, reduces the need for manual operation, improves the flexibility and efficiency of operation, and helps to improve the safety and construction efficiency of the construction site. The present invention solves the problems existing in the traditional elevator system and has high practical value and market competitiveness.

Description

Technical Field

[0001] The invention relates to building construction equipment, in particular to a construction elevator with super-large lifting capacity. Background Art

[0002] In the field of construction, traditional elevators are relatively small. However, for high-power elevators, the cabin is generally large and the load weight changes greatly. Traditional elevator systems usually lack intelligent control mechanisms for load changes. Due to the large area of ​​the cabin, there are also cases where the load is small in size but heavy in weight, resulting in unbalanced loads, leading to the following problems in the elevator:

[0003] Load adjustment is not timely: The control strategy of traditional elevator systems is usually fixed and cannot be adjusted according to real-time changes in load. This results in the acceleration, braking force and other parameters of the elevator not being able to be adjusted in time when the load changes, which can easily lead to unstable operation and increase safety hazards at the construction site.

[0004] Uneven load distribution: As traditional lift systems cannot effectively monitor and adjust load distribution, the load distribution is uneven during operation. This will cause the lift to run unbalanced, increase equipment wear, reduce service life, and increase safety risks at the construction site.

[0005] Inflexible manual operation: Traditional elevator systems usually require manual operation, and operators need to adjust the operating parameters of the elevator based on experience, which leads to inflexible operation and slow response. This results in low operating efficiency of the elevator and is unable to adapt to the changing load requirements of the construction site. Summary of the invention

[0006] The purpose of the present invention is to provide a construction elevator with super large lifting capacity.

[0007] To achieve the above object, the present invention is implemented according to the following technical solutions:

[0008] The high-power construction elevator of the present invention comprises an elevator and an electric control system, wherein the elevator is provided with a load sensor and a load distribution sensor, the signal output ends of the load sensor and the load distribution sensor are connected to the signal input end of the electric control system, and the control signal output end of the electric control system is connected to the control signal input end of the elevator;

[0009] The electronic control system adjusts the acceleration and braking force of the elevator in combination with the real-time load feedback from the load sensor;

[0010] The electric control system adjusts the driving power of the elevator in combination with the real-time load feedback from the load distribution sensor to maintain balance;

[0011] The electric control system has a human-machine interaction interface and an alarm system, which provide real-time operation information and alarms to the operator. The real-time operation information includes the load weight information monitored by the load sensor. When the load weight information is abnormal, an alarm is issued to the operator through the alarm system.

[0012] Furthermore, the elevator includes a guide rail frame, a supporting device, a wall-mounted frame, a bottom buffer device, a car, and a driving mechanism. There are multiple guide rail frames, and the lower ends of the multiple guide rail frames are fixedly connected to the ground through a foundation. There are multiple driving mechanisms, and one driving mechanism is arranged at the upper end of each guide rail frame. The upper end of each driving mechanism is connected to the top of the building through a wall-mounted frame. Two adjacent guide rail frames are fixedly connected through the supporting device. The car is slidably connected to the multiple guide rail frames. The bottom buffer device is arranged below the car. The driving ends of the multiple driving mechanisms are respectively connected to the upper ends of the edges of the car. The load sensor and the load distribution sensor are arranged at the bottom of the car, and the control signal output end of the electric control system is connected to the driving mechanism.

[0013] Preferably, the load sensor is a pressure sensor, and the load distribution sensor is a balance sensor.

[0014] The electronic control system adjusts the acceleration and braking force of the elevator in combination with the real-time load feedback from the load sensor as follows: first, collect the real-time data of the load sensor; second, establish a mapping model between the load and the acceleration and braking force, and construct an adaptive adjustment algorithm; finally, the electronic control system outputs the optimal acceleration and braking force instructions to the drive mechanism based on the adaptive adjustment algorithm according to the real-time load conditions.

[0015] The beneficial effects of the present invention are:

[0016] The present invention is a construction elevator with an ultra-large lifting capacity. Compared with the prior art, the present invention combines a load sensor, a load distribution sensor and an intelligent control algorithm, and has the following technical effects:

[0017] Intelligent load adjustment: The load sensor monitors the load weight in real time and the load distribution sensor monitors the load distribution. Combined with the intelligent control algorithm, the acceleration, braking force and driving power of the elevator are dynamically adjusted, so that the elevator can achieve intelligent load adjustment and ensure its balanced state and stable operation under different load conditions.

[0018] Load distribution balance: Adaptive particle swarm optimization algorithm is used to optimize the output power of each drive mechanism to minimize the imbalance of load distribution and achieve load distribution balance. This can effectively reduce the imbalance and wear of the elevator operation and increase the service life of the equipment.

[0019] Intelligent operation: Through the intelligent control algorithm of the electric control system, intelligent monitoring and adjustment of the lift are realized, reducing the need for manual operation and improving the flexibility and efficiency of operation. This helps to improve the safety and efficiency of the construction site and reduce the risks brought by manual operation.

[0020] To sum up, this technical solution has a significant effect of improving the operating efficiency of the elevator and ensuring construction safety. It can effectively solve the problems existing in the traditional elevator system and has high practical value and market competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a front structural schematic diagram of the present invention;

[0022] Figure 2 It is a side structural schematic diagram of the present invention.

[0023] In the figure: guide rail frame 1, supporting device 2, wall frame 3, bottom buffer device 4, car 5, driving mechanism 6. DETAILED DESCRIPTION

[0024] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. The illustrative embodiments and descriptions of the present invention are used to explain the present invention but are not intended to limit the present invention.

[0025] like Figure 1 , 2 As shown: The high-power construction elevator of the present invention comprises an elevator and an electric control system, wherein the elevator is provided with a load sensor and a load distribution sensor, the signal output ends of the load sensor and the load distribution sensor are connected to the signal input end of the electric control system, and the control signal output end of the electric control system is connected to the control signal input end of the elevator;

[0026] The electronic control system adjusts the acceleration and braking force of the elevator in combination with the real-time load feedback from the load sensor;

[0027] The electric control system adjusts the driving power of the elevator in combination with the real-time load feedback from the load distribution sensor to maintain balance;

[0028] The electric control system has a human-machine interaction interface and an alarm system, which provide real-time operation information and alarms to the operator. The real-time operation information includes the load weight information monitored by the load sensor. When the load weight information is abnormal, an alarm is issued to the operator through the alarm system.

[0029] Furthermore, the elevator includes a guide rail frame 1, a supporting device 2, a wall-mounted frame 3, a bottom buffer device 4, a car 5, and a driving mechanism 6. There are multiple guide rail frames 1, and the lower ends of the multiple guide rail frames 1 are fixedly connected to the ground through a foundation. There are multiple driving mechanisms 6, and a driving mechanism 6 is arranged at the upper end of each guide rail frame 1. The upper end of each driving mechanism 6 is connected to the top of the building through a wall-mounted frame 3. Two adjacent guide rail frames 1 are fixedly connected through the supporting device 2. The car 5 is slidably connected to the multiple guide rail frames 1. The bottom buffer device 4 is arranged below the car 5. The driving ends of the multiple driving mechanisms 6 are respectively connected to the upper ends of the edges of the car 5. The load sensor and the load distribution sensor are arranged at the bottom of the car 5, and the control signal output end of the electric control system is connected to the driving mechanism 6.

[0030] Preferably, the load sensor is a pressure sensor, and the load distribution sensor is a balance sensor.

[0031] The electronic control system adjusts the acceleration and braking force of the elevator in combination with the real-time load feedback from the load sensor as follows: first, collect the real-time data of the load sensor; second, establish a mapping model between the load and the acceleration and braking force, and construct an adaptive adjustment algorithm; finally, the electronic control system outputs the optimal acceleration and braking force instructions to the drive mechanism 6 according to the real-time load conditions based on the adaptive adjustment algorithm;

[0032] The mapping model between the load and the acceleration and braking force is as follows: the total load weight W of the elevator is taken as input; a mapping function is set to map the load weight to the corresponding acceleration adjustment force F 加速度 and brake force adjustment force F 制动力 ;

[0033] Build an adaptive adjustment algorithm:

[0034] Set the initial acceleration and braking force parameters, and obtain the current load weight W at each time step 当前 , according to the mapping model Calculate the desired acceleration adjustment force and brake force adjustment ; The model-based reference adaptive control algorithm is used to compare the expected adjustment force with the actual adjustment force, and the parameters are adjusted to approach the expected value;

[0035] The model reference adaptive control algorithm:

[0036] Assume that the dynamic model of the elevator can be expressed as:

[0037]

[0038] in, is the state vector, is the control input; A and B Respectively represent the state transfer matrix and input matrix of the system;

[0039] Assume that the following reference model represents the desired dynamic behavior of the elevator:

[0040]

[0041] in, is the state vector of the reference model, is the reference input;

[0042] Controller Design:

[0043]

[0044] in K is the controller gain, is the reference input;

[0045] The update rule of the adaptive law is expressed as:

[0046]

[0047] in, is the state error, is the observation error covariance matrix, is a positive definite matrix;

[0048] Update acceleration and braking force parameters to adapt them to the current load situation.

[0049] The electric control system adjusts the driving power of the elevator in combination with the real-time load feedback from the load distribution sensor to maintain balance by: monitoring the load distribution on the car 5 in real time through the load distribution sensor, and dynamically adjusting the output power of each driving mechanism in combination with the load distribution through the control algorithm to maintain the balance state of the elevator;

[0050] The control algorithm is:

[0051] Load distribution monitoring: Use load distribution sensors to monitor the load distribution on the car in real time and obtain load distribution data, expressed as a vector ,in Indicates The load at each drive mechanism;

[0052] Balance status assessment:

[0053] The balance of the load distribution vector W is calculated as an evaluation index. The balance is defined as the sum of the squares of the differences between the loads of each drive mechanism, that is:

[0054]

[0055] in, is the average value of the load distribution;

[0056] Control strategy: The output power of each drive mechanism 6 is adjusted by the electronic control system to minimize the balance index. ;

[0057] Optimization goal: balance index As the optimization target, construct the optimization problem ,

[0058] in is the output power vector of each drive mechanism;

[0059] Optimization algorithm: Adaptive particle swarm optimization algorithm is used to solve the optimization problem;

[0060] Controller update: According to the optimization results, the output power of each drive mechanism 6 is updated to make the load distribution more uniform, thereby maintaining the balance state of the elevator.

[0061] Specifically, the adaptive particle swarm optimization algorithm includes the following steps:

[0062] S1: Initialization: Initialize the position of the particle swarm and speed , set the adaptability factor of each particle and and inertia weight ;

[0063] S2: Evaluate fitness: calculate the fitness of each particle, that is, the balance of load distribution;

[0064] S3: Update speed and position:

[0065] For each particle:

[0066]

[0067] in: is the best position achieved by the particle in the historical iteration;

[0068] is the best position achieved in the entire particle swarm in historical iterations;

[0069] is a random number in the range [0,1];

[0070] S4: Update the adaptability factor and inertia weight: Dynamically adjust the adaptability factor based on the performance of historical iterations , and inertia weight ;

[0071] S5: Repeat iteration: repeat steps S2 and S3 until the condition of stopping iteration is met, that is, reaching the maximum number of iterations or reaching a satisfactory balance;

[0072] S6: Output the optimal solution: Output the best position found , which is the corresponding optimal driving power allocation scheme.

[0073] When the elevator is running, the load sensor and load distribution sensor monitor the weight and distribution of the load in real time. The electronic control system dynamically adjusts the operation state of the elevator based on this data to ensure that it can maintain balance and stability under different load conditions. The following is a detailed explanation of the working principle of the invention:

[0074] Load Regulation:

[0075] The load sensor monitors the weight of the load on the lift in real time, while the load distribution sensor monitors the distribution of the load. The electronic control system collects data from these sensors and calculates the expected acceleration and braking force based on a pre-set mapping model between load and acceleration and braking force. Using an algorithm based on model reference adaptive control, the electronic control system compares the expected acceleration and braking force with the actual acceleration and braking force, and dynamically adjusts the parameters so that the actual effect is close to the expected value.

[0076] Drive power adjustment: The load distribution sensor monitors the load distribution on the car in real time. Based on the monitored load distribution, the electronic control system optimizes the output power of each drive mechanism through the adaptive particle swarm optimization algorithm to minimize the imbalance of load distribution. The adaptive particle swarm optimization algorithm continuously adjusts the output power of each drive mechanism until the optimal drive power distribution scheme is found, so that the elevator can maintain a balanced state under different load distribution conditions.

[0077] Human-machine interface and alarm system: The electronic control system also has a human-machine interface and an alarm system to provide real-time operation information and alarms to operators. Real-time operation information includes load weight information monitored by the load sensor. Once the load weight is abnormal, the alarm system will alert the operator through an alarm.

[0078] Through the above working principle, the present invention can realize intelligent control and monitoring of the elevator, ensure that the elevator always remains balanced and stable during the construction process, and improve construction safety and efficiency.

[0079] Example: Intelligent lifts in large-scale building construction

[0080] At a construction site of a large building, an efficient and safe lift is needed to transport building materials and workers. In order to improve construction efficiency and ensure construction safety, the technical solution of the present invention is introduced.

[0081] Implementation steps:

[0082] Install sensors: Install load sensors and load distribution sensors inside the elevator car to monitor load weight and distribution in real time.

[0083] System integration: Connect the sensor to the electronic control system to ensure that the sensor data can be transmitted to the electronic control system in real time for processing and analysis.

[0084] Parameter initialization: Initialize the parameters in the control algorithm according to the actual situation of the construction site, including adaptability factor, inertia weight, etc.

[0085] Operation monitoring: Start the lift and let it run up and down on the construction site. The electronic control system monitors the sensor data in real time and controls and adjusts according to the monitored load conditions.

[0086] Dynamic adjustment: Based on the data from the load sensor, the electronic control system uses the MRAC algorithm to dynamically adjust the acceleration and braking force of the elevator to ensure smooth operation of the elevator.

[0087] Drive power optimization: Based on the load distribution monitored by the load distribution sensor, the electronic control system uses the APSO algorithm to optimize the output power of each drive mechanism to minimize the imbalance of load distribution.

[0088] Real-time monitoring and alarm: The electronic control system provides real-time operation information and alarms to operators through the human-machine interface and alarm system. Once abnormal load or other problems are found, an alarm will be issued in time to remind the operator.

[0089] Through the implementation of the present invention, the operation of elevators at large construction sites is more stable and efficient. Real-time monitoring and dynamic adjustment ensure the balance of the elevator under different load conditions, improve construction safety and efficiency, and reduce the need for manual operation and the risk of human error.

[0090] The technical solution of the present invention is not limited to the above-mentioned specific embodiments. All technical variations made according to the technical solution of the present invention fall within the protection scope of the present invention.

Claims

1. A construction lift with extra-large lifting capacity, characterized by: It comprises an elevator and an electric control system, wherein the elevator is provided with a load sensor and a load distribution sensor, the signal output ends of the load sensor and the load distribution sensor are connected to the signal input end of the electric control system, and the control signal output end of the electric control system is connected to the control signal input end of the elevator; The electronic control system adjusts the acceleration and braking force of the elevator in combination with the real-time load feedback from the load sensor: First, collect real-time data from the load sensor; second, establish a mapping model between the load and the acceleration and braking force, and construct an adaptive adjustment algorithm; finally, the electronic control system outputs the optimal acceleration and braking force instructions to the drive mechanism based on the adaptive adjustment algorithm according to the real-time load conditions (6); The mapping model between the load and the acceleration and braking force: the total load weight W of the elevator is taken as input; Mapping function, mapping the load weight to the corresponding acceleration adjustment force F 加速度 and brake force adjustment force F 制动力 ; Build an adaptive adjustment algorithm: Set the initial acceleration and braking force parameters, and obtain the current load weight W at each time step 当前 , calculate the desired acceleration adjustment force according to the mapping model f(W) and brake force adjustment The model-based reference adaptive control algorithm is used to compare the expected adjustment force with the actual adjustment force, and the parameters are adjusted to approach the expected value; The model reference adaptive control algorithm: Assume that the dynamic model of the elevator can be expressed as: x=Ax+Bu Where x is the state vector, u is the control input; A and B represent the state transfer matrix and input matrix of the system respectively; Assume that the following reference model represents the desired dynamic behavior of the elevator: x r =A r x r +B r r Among them, x r is the state vector of the reference model, r is the reference input; Controller Design: u=-K(x-x r )+u r Where K is the controller gain, u r is the reference input; The update rule of the adaptive law is expressed as: K=-ΓeP T Where e is the state error, P is the observation error covariance matrix, and Γ is a positive definite matrix; Update acceleration and braking force parameters to adapt them to the current load conditions; The electric control system adjusts the driving power of the elevator in combination with the real-time load feedback from the load distribution sensor to maintain balance; The electric control system has a human-machine interaction interface and an alarm system, which provide real-time operation information and alarms to the operator. The real-time operation information includes the load weight information monitored by the load sensor. When the load weight information is abnormal, an alarm is issued to the operator through the alarm system.

2. The super-large lifting capacity construction elevator according to claim 1, characterized in that: The elevator comprises a guide rail frame (1), a supporting device (2), a wall-mounted frame (3), a bottom buffer device (4), a car (5), and a driving mechanism (6). There are a plurality of guide rail frames (1), the lower ends of the plurality of guide rail frames (1) are fixedly connected to the ground through a foundation. There are a plurality of driving mechanisms (6), one driving mechanism (6) is arranged at the upper end of each guide rail frame (1), the upper end of each driving mechanism (6) is connected to the top of a building through a wall-mounted frame (3), two adjacent guide rail frames (1) are fixedly connected through the supporting device (2), the car (5) is slidably connected to the plurality of guide rail frames (1), the bottom buffer device (4) is arranged below the car (5), the driving ends of the plurality of driving mechanisms (6) are respectively connected to the upper ends of the edges of the car (5), the load sensor and the load distribution sensor are arranged at the bottom of the car (5), and the control signal output end of the electric control system is connected to the driving mechanism (6).

3. The super-large lifting capacity construction elevator according to claim 2, characterized in that: The load sensor is a pressure sensor, and the load distribution sensor is a balance sensor.

4. The super-large lifting capacity construction elevator according to claim 3, characterized in that: The electric control system adjusts the driving power of the elevator in combination with the real-time load feedback from the load distribution sensor to maintain balance by: monitoring the load distribution on the car (5) in real time through the load distribution sensor, and dynamically adjusting the output power of each driving mechanism in combination with the load distribution through a control algorithm to maintain the balance state of the elevator; The control algorithm is: Load distribution monitoring: Use load distribution sensors to monitor the load distribution on the car in real time and obtain load distribution data, which is represented by a vector w = [w1, w2, ..., w n ], where w n represents the load at the nth drive mechanism; Balance status assessment: The balance of the load distribution vector W is calculated as an evaluation index. The balance is defined as the sum of the squares of the differences between the loads of each drive mechanism, that is: in, is the average value of the load distribution; Control strategy: adjusting the output power of each driving mechanism (6) through the electronic control system to minimize the balance index E(w); Optimization goal: Take the balance index E(w) as the optimization goal and construct the optimization problem min u E(w), where u=[u1,u2,...,u n ] is the output power vector of each driving mechanism; Optimization algorithm: Adaptive particle swarm optimization algorithm is used to solve the optimization problem; Controller update: According to the optimization result, the output power of each driving mechanism (6) is updated to make the load distribution more uniform, thereby maintaining the balance state of the elevator.

5. The super-large lifting capacity construction elevator according to claim 4, characterized in that: The adaptive particle swarm optimization algorithm The following steps are involved: S1: Initialization: Initialize the position of the particle swarm X = [x1, x2, ..., x N ] and speed V=[v1,v2,...,v N ], set the adaptability factors c1 and c2 and inertia weight w of each particle; S2: Evaluate fitness: calculate the fitness of each particle, that is, the balance of load distribution; S3: Update speed and position: For each particle i: Where: p best,i is the best position achieved by particle i in the historical iteration; g best is the best position achieved in the entire particle swarm in historical iterations; rand() is a random number in the range [0,1]; S4: Update the adaptability factor and inertia weight: Dynamically adjust the adaptability factors c1, c2 and the inertia weight w according to the performance of historical iterations; S5: Repeat iteration: repeat steps S2 and S3 until the condition of stopping iteration is met, that is, reaching the maximum number of iterations or reaching a satisfactory balance; S6: Output the optimal solution: Output the best position g found best , which is the corresponding optimal driving power allocation scheme.

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