CN113581962B - Fault monitoring system of elevator hall door - Google Patents
Fault monitoring system of elevator hall door Download PDFInfo
- Publication number
- CN113581962B CN113581962B CN202110911676.6A CN202110911676A CN113581962B CN 113581962 B CN113581962 B CN 113581962B CN 202110911676 A CN202110911676 A CN 202110911676A CN 113581962 B CN113581962 B CN 113581962B
- Authority
- CN
- China
- Prior art keywords
- door
- elevator
- hall door
- data
- fault
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0006—Monitoring devices or performance analysers
- B66B5/0018—Devices monitoring the operating condition of the elevator system
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0006—Monitoring devices or performance analysers
- B66B5/0018—Devices monitoring the operating condition of the elevator system
- B66B5/0025—Devices monitoring the operating condition of the elevator system for maintenance or repair
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/02—Applications of checking, fault-correcting, or safety devices in elevators responsive to abnormal operating conditions
Landscapes
- Maintenance And Inspection Apparatuses For Elevators (AREA)
Abstract
The invention relates to the field of elevator control, in particular to a fault monitoring system for an elevator hall door. The fault monitoring system includes: the system comprises a hall sensor, a signal transmission module, a data relay processor, a communication module and a cloud server. Wherein, hall sensor includes inertial measurement unit and displacement measurement unit. The signal transmission module transmits the detection signal of the hall sensor to a data relay processor. The communication module is used for realizing bidirectional communication between the data relay processing and a cloud server. The cloud server comprises an elevator hall door fault detection model. And the data relay processor is used for acquiring the state data of the hall sensor, sending the state data to the cloud server, and sending an adjusting instruction to the elevator control system according to the detection result of the failure state of the elevator hall door fed back by the cloud server. The invention solves the problems of dependence on manual work, poor monitoring effect, low efficiency and insufficient real-time performance of elevator hall door state monitoring.
Description
Technical Field
The invention relates to the field of elevator control, in particular to a fault monitoring system for an elevator hall door.
Background
The hoistway door is one of the most important parts of an elevator, and is also the most frequently used part that is most vulnerable to external impact or extrusion in a working environment. The national standard GB-7588 Elevator manufacturing and installation safety Specification separately provides design and installation requirements for the safety performance of the landing door. However, according to incomplete statistics, about 70% of casualty accidents of the elevator are caused by elevator hall doors, so that the hall doors play an extremely important role in protecting the safety of people and the normal operation of the elevator.
In daily use, the landing door frequently fails due to a plurality of reasons, such as foreign matters on the doorsill, the loss of an emergency guide device, external impact, the failure of a device for preventing people from being clamped by the door, and the like. In order to solve the problem, the conventional technical scheme only can continuously shorten the maintenance period of the elevator and improve the inspection frequency of managers. Although maintenance personnel can regularly maintain the elevator, the maintenance personnel cannot monitor the state of the elevator hall door in real time. And for the high-rise high-speed group control elevator group, the number of the landing doors of a single group of elevators can reach thirty or more, and maintenance personnel are difficult to master the running state of each landing door at any time and any place.
Disclosure of Invention
Based on the situation, the problem that the existing elevator hall door state monitoring depends on manual work, the monitoring effect is poor, the efficiency is low, the real-time performance is insufficient, and further the elevator faults are frequent is solved; provided is a failure monitoring system for hoistway doors.
The invention provides a fault monitoring system of elevator hall doors, which is used for identifying the motion state of the hall doors in each layer of elevator and monitoring various faults in the opening and closing state of the elevator hall doors in time. The fault monitoring system includes: the system comprises a hall sensor, a signal transmission module, a data relay processor, a communication module and a cloud server.
Wherein the hall sensor includes an inertia measuring unit and a displacement measuring unit. The inertial measurement unit comprises three single-axis acceleration sensors and three single-axis gyroscopes; the inertia measurement unit is used for measuring speed signals, acceleration signals and angular speed signals of the independent three axes. The displacement measurement unit comprises three single-axis displacement sensors and is used for measuring displacement signals of independent three axes. The hall sensors are respectively arranged on the hall doors of each floor of the elevator.
The signal transmission module is used for transmitting the detection signal of the hall sensor to a data relay processor.
The data relay processor is installed on the top of the elevator car and is in communication connection with the control system of the elevator. The data relay processor is configured to: (1) after the switching control command of any one hall door sent by the elevator control system is inquired, the detection signal of the hall door sensor in the hall door on the layer is obtained, and the corresponding detection signal is converted into characteristic data reflecting the movement state change of the elevator hall door. And drawing a motion state curve reflecting the change of the motion state of the elevator hall door according to the characteristic data, and sending out the characteristic data of the motion state. (2) After receiving the fault type of a certain floor of elevator hall door sent by a cloud server; and sending a control command for stopping the operation of the landing door and an alarm signal for indicating the stop of the operation of the landing door to an elevator control system. (3) When the elevator control system responds to the switch control command of any one elevator hall door, the displacement signals detected in the rest elevator hall doors are obtained. And when the displacement in any direction of any other hall door exceeds the preset displacement limit, sending an early warning signal for representing the hall door fault to be checked.
The communication module is used for realizing two-way communication between the data relay processing and a cloud server.
The cloud server comprises a trained elevator hall door fault detection model. And the cloud server is used for inputting the acquired characteristic data of the motion state of the hall door of any floor into the elevator hall door fault detection model to obtain a fault state detection result of the hall door of the floor. And after identifying the type of failure of the hall door, sends out the identification result of the type of failure.
As a further improvement of the invention, the signal transmission module is a wireless signal transmission module based on a Bluetooth module; the communication module employs a communication module based on a communication network of a mobile operator.
As a further improvement of the invention, the data relay processor comprises an instruction transceiving unit and a computing unit; the command receiving and sending unit is used for inquiring the switch control command of any landing door generated by the elevator control system or sending a control command and an alarm signal for stopping the operation of the landing door on a certain floor to the elevator control system; and the computing unit is used for converting the acquired sensing signals of the hall door sensor into characteristic data reflecting the motion state change of the elevator hall door.
As a further improvement of the invention, the relay processor also comprises a storage unit which is used for storing the receiving and transmitting signals of the command receiving and transmitting unit and the calculation result of the calculation unit as the data backup of the elevator running state.
As a further improvement of the invention, the fault monitoring system also comprises a local data server and a local application server; all data received and generated in the cloud server are stored in the local data server; the local application server is used for responding to the request of the manager and providing the manager with the access service of all data in the local data server.
As a further improvement of the invention, the local data server also comprises a failure probability database; the data in the fault probability database is used for representing the occurrence frequency of various faults in the whole life cycle of the elevator hall door.
As a further improvement of the present invention, the data relay processor feeds back the determination result of the hall door state to the local data server after receiving the determination result of the hall door state every time, and the local data server updates the failure probability database.
As a further improvement of the invention, the elevator hall door fault detection model is a network model based on a machine learning algorithm, the input of the elevator hall door fault detection model is the characteristic data of the motion state of the elevator hall door in a switching period, and the output of the elevator hall door fault detection model is the fault type judgment result of the current elevator hall door.
As a further improvement of the invention, the training process of the elevator hall door fault detection model is as follows:
(1) obtaining typical motion state curves of the elevator hall door in a normal state and different fault type states;
(2) collecting characteristic data of the elevator hall door in an actual switch motion state, and drawing a corresponding sample motion state curve;
(3) comparing the sample motion state curve with a typical motion state curve, determining the state type of the hall door corresponding to each curve, manually marking, and taking the collected characteristic data and the corresponding manual mark as sample data of a sample data set; sampling according to the occurrence rates of different fault types to form a sample data set;
(4) dividing the sample data set into a training set and a testing set, training the elevator hall door fault detection model through the training set, and verifying the training effect of the model by using the testing set; until the elevator hall door fault detection model reaches the requirements of the training phase.
As a further improvement of the invention, in the data set used in the training process, the collected fault types include: the locking state caused by the threshold foreign matter, the loosening state of a door system change gear and the missing state of a door guide shoe; the sample data reflecting the three samples has the same occupation ratio in the training set and the test set.
The invention provides a fault monitoring system of a hoistway door, which has the following beneficial effects:
1. the elevator hall door sensor is arranged on the elevator hall door, the running state of the elevator hall door is monitored in real time, and whether the elevator hall door breaks down or not is judged according to the acquired characteristic data reflecting the motion state of the elevator hall door. The monitoring mode can replace manual work, realizes 24h uninterrupted monitoring, has better real-time performance, and can find and process in time at the beginning of a fault. The personal safety or property loss caused by the failure of the elevator hall door is reduced. In addition, the scheme of the invention can realize centralized management of large-scale group control elevators and obviously improve the efficiency of elevator safety monitoring.
2. The invention completes the identification of the state of the elevator hall door through the network model based on the machine learning algorithm, and can obviously improve the training effect of the network model based on a large amount of real data. Meanwhile, in practical application, more effective training samples can be accumulated through manual rechecking of the recognition result, and the training effect and the recognition accuracy of the network model are further improved.
3. Besides the operation fault of the elevator hall door, the invention can also timely detect the external force impact on the elevator hall door, timely provide a processing scheme according to the damage degree of the impact on the elevator hall door, close the hall door on the related layer and inform technical personnel to arrange maintenance.
4. The invention can also accumulate the data of the elevator in the running process and provide prospective feedback and suggestions for the production and manufacture of the elevator hall door according to the problems reflected in the accumulated data. And meanwhile, technical support is provided for the daily operation management of the elevator.
Drawings
Fig. 1 is a block schematic diagram of a failure monitoring system for hoistway doors provided in embodiment 1 of the present invention;
fig. 2 is a schematic view of a topology of a failure monitoring system for hoistway doors provided in embodiment 1 of the present invention;
fig. 3 is a schematic view of a topology of a failure monitoring system for hoistway doors provided in embodiment 2 of the present invention;
fig. 4 is a comparison graph of a motion state curve of a hoistway door in a threshold foreign matter and normal state in embodiment 2 of the present invention;
fig. 5 is a comparison graph of the moving state curves of the hoistway door in the roller releasing and normal states in embodiment 2 of the present invention;
fig. 6 is a comparison graph of the movement state curve of the elevator hall door in the loosening and normal states of the hall guide shoes in embodiment 2 of the invention;
fig. 7 is a flowchart of a method for automatically identifying a failure of a hoistway door according to embodiment 3 of the present invention;
fig. 8 is a picture of an apparatus for an elevator hall door in a state of a threshold foreign matter in embodiment 3 of the present invention;
fig. 9 is a picture of the device of the hoistway door in the roller-released state in embodiment 3 of the present invention;
fig. 10 is a picture of the device for elevator hall doors in the state of loose hall guide shoes in embodiment 3 of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "or/and" includes any and all combinations of one or more of the associated listed items.
Example 1
The embodiment provides a fault monitoring system for elevator hall doors, which is used for identifying the motion state of the hall doors in each layer of elevator and realizing the timely monitoring of various types of faults. As shown in fig. 1, the fault monitoring system includes: the system comprises a hall sensor, a signal transmission module, a data relay processor, a communication module and a cloud server. The topology of the system is shown in figure 2.
Wherein, hall sensor includes inertial measurement unit and displacement measurement unit. The inertial measurement unit comprises three single-axis acceleration sensors and three single-axis gyroscopes; the inertia measurement unit is used for measuring speed signals, acceleration signals and angular speed signals of the independent three axes. The displacement measurement unit comprises three single-axis displacement sensors and is used for measuring displacement signals of independent three axes. The hall sensors are respectively arranged on the hall doors of each floor of the elevator.
The signal transmission module is used for transmitting the detection signal of the hall sensor to a data relay processor. The signal transmission module is mainly used for sending the detection result of the hall sensor to the data relay processor, so that the module can realize data transmission between a large number of modules (hall sensors) and a single module (data relay processor). In this embodiment, data transmission is realized by using one-to-many master-slave bluetooth modules, and considering that the hall sensor does not need to receive data, in this embodiment, each bluetooth slave module of the master-slave bluetooth modules is installed at the hall sensor side, and the bluetooth master module is installed at the data relay processor side. The master and slave bluetooth modules operate in a one-way data transfer mode, i.e. data is only allowed to be transferred from the bluetooth slave to the bluetooth master.
Of course, in other embodiments, other data transmission modules may be added to solve the problem of real-time data transmission. The characteristic data for identifying the failure state of the elevator hall door in the embodiment only needs to be collected and transmitted when the elevator car reaches the corresponding hall door, and the bluetooth module in the embodiment just can meet the transmission requirement of the data. In addition, the bluetooth module adopted in this embodiment also has the characteristics of wireless transmission, strong confidentiality (the matching connection between the master module and the slave module needs to be completed in advance), and low power consumption.
The data relay processor is installed on the top of the elevator car and is in communication connection with the control system of the elevator. The data relay processing is a black box for installing the elevator car roof. The data relay processor in this embodiment is configured to:
(1) after the switching control command of any one hall door sent by the elevator control system is inquired, the detection signal of the hall door sensor in the hall door on the layer is obtained, and the corresponding detection signal is converted into characteristic data reflecting the movement state change of the elevator hall door. And drawing a motion state curve reflecting the change of the motion state of the elevator hall door according to the characteristic data, and sending out the characteristic data of the motion state.
(2) After receiving the fault type of a certain floor of elevator hall door sent by a cloud server; and sending a control command for stopping the operation of the landing door of the floor and an alarm signal for indicating the stop of the operation of the landing door of the floor to an elevator control system.
(3) When the elevator control system responds to the switch control command of any one elevator hall door, the displacement signals detected in the rest elevator hall doors are obtained. And when the displacement in any direction of any other hall door exceeds the preset displacement limit, sending an early warning signal for representing the hall door fault to be checked.
Specifically, the data relay processor comprises an instruction transceiving unit and a computing unit; the command transceiving unit is used for inquiring the switch control command of any hall door generated by the elevator control system or sending a control command for stopping the operation of the hall door on a certain floor and an alarm signal to the elevator control system. And the computing unit is used for converting the acquired sensing signals of the hall door sensor into characteristic data reflecting the motion state change of the elevator hall door. The data relay processor also comprises a storage unit which is used for storing the receiving and transmitting signals of the command receiving and transmitting unit and the calculation result of the calculation unit as the data backup of the elevator running state.
The communication module is used for realizing bidirectional communication between the data relay processing and a cloud server. Specifically, the communication module in the present embodiment adopts a communication module based on a communication network of a mobile operator. The communication module supports 2G, 3G, 4G or 5G networks of three major operators in the mainstream. And the communication module sends the characteristic data obtained from the data relay processor during the movement of the elevator hall door to the cloud server end for fault identification, and sends the fault type identified by the cloud server end back to the data relay processor.
The cloud server comprises a trained elevator hall door fault detection model; the model is the hoistway door fault detection model which is trained in the embodiment 1. And the cloud server is used for inputting the acquired characteristic data of the motion state of the hall door of any floor into the elevator hall door fault detection model to obtain a fault state detection result of the hall door of the floor. And after identifying the type of failure of the hall door, sends out the identification result of the type of failure.
In this embodiment, the hoistway door fault detection model running in the cloud server is a network model based on a machine learning algorithm, the input of the hoistway door fault detection model is feature data of a motion state of the hoistway door in a switching cycle, and the output of the hoistway door fault detection model is a fault type discrimination result of the current hoistway door.
The training process of the elevator hall door fault detection model in the embodiment is as follows:
(1) obtaining typical motion state curves of the elevator hall door in a normal state and different fault type states;
(2) collecting characteristic data of the elevator hall door in an actual switch motion state, and drawing a corresponding sample motion state curve;
(3) comparing the sample motion state curve with a typical motion state curve, determining the state type of the hall door corresponding to each curve, manually marking, and taking the collected characteristic data and the corresponding manual mark as sample data of a sample data set; sampling according to the occurrence rates of different fault types to form a sample data set;
(4) dividing the sample data set into a training set and a testing set, training the elevator hall door fault detection model through the training set, and verifying the training effect of the model by using the testing set; until the elevator hall door fault detection model reaches the requirements of the training phase.
In a data set used in the model training process, the collected fault types include: the locking state caused by the threshold foreign matter, the loosening state of a door system change gear and the missing state of a door guide shoe; the sample data reflecting the three samples has the same occupation ratio in the training set and the test set.
Example 2
The present embodiment provides a failure monitoring system for a hoistway door, which is different from embodiment 1 in that: as shown in fig. 3, the system in this embodiment further includes a local data server and a local application server; all data received and generated in the cloud server are stored in the local data server; the local application server is used for responding to the request of the manager and providing the manager with the access service of all data in the local data server.
Specifically, in this embodiment, the manager opens a browser in the local application server to access the server with the fixed domain name, or inputs a password in software to log in a corresponding account, so as to obtain data in the local data server, and browse the movement state of the hall door of each elevator. And at the local application server end, the real-time motion states of all elevators are displayed in a motion state curve mode. The manager can not only check the real-time status data of the current elevator hall door, but also inquire the historical data of any hall door. And manually rechecking the identification result of the hall door fault state according to the hall door motion state curve of the browsing interface. In order to facilitate the manual review process, a curve of the movement state of the hoistway door in the normal state can be generated in the local data server and used as a reference. Specifically, fig. 4 to 6 show graphs comparing a curve of a state of motion of the hall door with a curve of a normal state in three states of a threshold foreign matter, a roller release, and a looseness of the hall door shoe, respectively.
The local data server also comprises a failure probability database; the data in the fault probability database is used for representing the occurrence frequency of various faults in the whole life cycle of the elevator hall door.
In this embodiment, the data relay processor feeds back the determination result of the state of the hall door to the local data server after receiving the determination result of the state of the hall door every time, and the local data server updates the fault probability database. After the elevator manufacturer or the maintenance enterprise obtains the data in the corresponding fault probability database, the most common faults encountered in the operation process of the elevator hall door can be known, and further, the performance of the corresponding elevator component can be enhanced, and the effect of reducing the fault rate is achieved. Meanwhile, the maintenance company can increase the maintenance frequency of corresponding parts of the elevator according to various frequent faults and accordingly ensure the safe operation of the elevator.
Example 3
In the method for automatically identifying a failure of a hoistway door provided in this embodiment, the hoistway door failure monitoring system in embodiment 1 or 2 implements a process of monitoring a state of the hoistway door by using the method, and as shown in fig. 7, the method for automatically identifying a failure includes the following steps:
s1: constructing a hoistway door fault detection model based on a machine learning algorithm; the input of the hoistway door fault detection model is characteristic data of a motion state of the hoistway door in one switching cycle, and specifically, in the present embodiment, the input of the hoistway door fault detection model is three axial speeds, angular speeds and accelerations of the elevator door. And the output of the elevator hall door fault detection model is the judgment result of the fault type of the current elevator hall door.
S2: and collecting motion state data of the elevator hall door in a normal state and various different fault type states, wherein the motion state data is input required by the elevator hall door fault detection model in a training or identification stage. The related characteristic data are also plotted into corresponding motion state curves in the embodiment. The purpose of drawing the motion state curve is mainly to facilitate manual marking of the motion state of the elevator hall door according to the motion state curve and distinguish different types of motion faults.
The types of faults that can be identified in this embodiment mainly include: the locking state caused by threshold foreign bodies, the loosening state of a door system change gear, the missing state of a door guide shoe and the like. Fig. 8 shows a device picture in the threshold foreign matter state; FIG. 9 shows a picture of the device with the roller released; fig. 10 shows pictures of the apparatus in a state where the hall guide shoes are loosened, respectively.
The three faults are the most frequently occurring types of hall door faults in practical application, and data collection can be performed on other types of hall door faults, so that the three faults are used for training the model in the embodiment. And for elevator hall door fault types except the three types of fault types, the addition is completed according to the proportion of the fault types in practical application. That is, when the probability of occurrence of a new fault type is higher, the proportion of the fault type in the training data set is properly increased, and the optimal recognition effect on the problem is further ensured.
The motion state data of the hall door collected in this embodiment includes three-axis velocity, angular velocity, acceleration, and displacement in three axial directions. The three-axis speed, the angular speed and the acceleration are obtained through an inertia measuring unit, and the displacement in the three axial directions is obtained through a displacement sensor. The data acquired by the inertia measuring unit is characteristic data for identifying the failure of the hall door, and the data measured by the displacement sensor is used for judging whether the hall door is deformed due to the action of external force when the hall door is in a static state, wherein the structural deformation is a precursor of the failure of the hall door. In many cases, just because the hoistway door is damaged by external force, the opening and closing state of the hoistway door is abnormal, and further, a safety accident is caused.
S3: manually marking the states of the hall doors represented by the drawn motion state curves; in the sampling data, the number ratio of the fault state to the normal state is 1:1, and the number ratio of various fault types is the same. And forming a data set by using the characteristic data corresponding to the marked motion state curve and the data of the fault type, and taking the data set as the data set of model training. The data set in the embodiment can well reflect the proportion of various faults in the actual situation, and further achieve a better model training effect.
The manual labeling process for the data set is as follows: drawing typical motion state curves of the elevator hall door under various different state types according to the acquired feature data of the motion states of the elevator hall door under the normal state and various different fault type states; then comparing a sample motion state curve drawn by the acquired sample data with a typical motion state curve, and determining the state type of the elevator hall door corresponding to each sample motion state curve; and completing manual marking according to the judgment result of the state type.
S4: the data set is divided into a training set and a test set according to the same sampling proportion as the previous step. Wherein the ratio of the data volume in the training set to the data volume in the test set is 8: 2. Training the constructed elevator hall door fault detection model through a training set, and verifying the training effect of the model by using a test set; until the elevator hall door fault detection model reaches the requirements of the training phase.
S5: when a landing door switch command is received every time, acquiring characteristic data of the motion state of a landing door corresponding to an elevator layer, drawing a corresponding real-time motion state curve, and simultaneously inputting the characteristic data into a trained elevator landing door fault detection model to obtain the identification result of the landing door state of the layer; and the corresponding real-time motion state curve and the corresponding recognition result are reserved.
When the failure of the elevator hall door at a certain floor is identified, the embodiment also sends an alarm signal to the manager; and sending a control instruction for stopping the operation of the landing door to the elevator control system until the corresponding fault is removed.
According to the scheme in the embodiment, when the corresponding hoistway door is detected to have a fault, the corresponding hoistway door can be closed in time, casualty events are avoided, meanwhile, an alarm can be sent to a manager, and technicians are waited to maintain and process the corresponding fault.
The real-time motion curve of the elevator hall door in each identification and detection process is drawn, the purpose of drawing the curve is to facilitate manual rechecking of the identification result of the network model when necessary, and retrain the machine-learned network model according to the rechecking result at the later stage, wherein the result of the network model identification error can be supplemented into a training set after being manually marked, and the network model is retrained, so that the training effect of the model is improved.
In the embodiment, when any hall door switch instruction is received, the motion state data of the hall doors of other layers are also obtained, whether the hall doors have the change of speed, acceleration, angular velocity or displacement in each axial direction is detected, if yes, a control instruction for stopping the operation of the hall doors of the layer is sent to an elevator control system, and meanwhile, an early warning signal is sent to a manager to remind the manager to check.
The generation method of the early warning signal comprises the following steps: setting a threshold value of the axial speed, the acceleration or the angular speed of the landing door and a threshold value of the axial displacement, wherein the threshold values of the axial speed, the acceleration or the angular speed and the axial displacement are respectively the minimum values of the speed, the acceleration or the angular speed and the displacement change of the landing door of the elevator in a non-switching state, and when the speed, the acceleration, the angular speed or the displacement change of any one layer of the landing door of the elevator in the non-switching state is larger than the threshold values of the axial speed, the acceleration, the angular speed or the axial displacement, judging that the landing door of the layer in the elevator is in a fault early warning state, and waiting for the confirmation of a manager.
Normally, the elevator will only stop at one of the floors at the same time, and when the elevator is in an open or closed state at one of the landing doors, the remaining landing doors should remain closed. However, if it is detected that any one of the other hoistway doors has a displacement greater than the safety limit, it is considered that the hoistway door on the floor may be broken or damaged by external force, and at this time, the hoistway door on the floor must be closed and locked in time, and a technician is waited to perform fault checking and problem handling.
In order to solve the problem of identifying the failure of the hoistway door, the method comprises the steps of firstly obtaining characteristic data reflecting the change of the door state in the hoistway door, drawing the related data into different types of curves, simultaneously training a network based on a machine learning algorithm by using the characteristic data, and further taking a trained network model as a failure detection model of the hoistway door required by the invention for automatically identifying the state of the hoistway door.
Compared with the traditional manual detection method, the method has the advantages of higher efficiency and capability of synchronously detecting the states of a plurality of elevator hall doors simultaneously, and effectively solves the problem of insufficient real-time monitoring of the states of the elevator hall doors. Meanwhile, the index significance of the state data acquired by the embodiment is strong, and the autonomous learning capability of the neural network is strong, so that the reliability of the fault automatic identification result is better, and the requirement of fault monitoring on the elevator hall door can be met. Even in some cases, the elevator hall door fault detection model provided by the embodiment can identify faults which are difficult to find by manual detection, or find hidden dangers in time at the initial stage of fault occurrence.
In addition, in step S5, after the corresponding real-time motion state curve and the identification result thereof are retained each time, a failure probability database for indicating the frequency of various failures occurring in the whole life cycle of the hoistway door is updated, and the failure probability database is used for guiding the elevator production and maintenance process. After the elevator manufacturer or the maintenance enterprise obtains the data in the corresponding fault probability database, the most common faults encountered in the operation process of the elevator hall door can be known, and further, the performance of the corresponding elevator component can be enhanced, and the effect of reducing the fault rate is achieved. Meanwhile, the maintenance company can increase the maintenance frequency of corresponding parts of the elevator according to various frequent faults and the safe operation of the elevator is guaranteed.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is specific and detailed, but not to be construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.
Claims (10)
1. A failure monitoring system of elevator hall doors is used for identifying the motion state of the hall doors in each layer of elevator and monitoring various failures in the opening and closing state of the elevator hall doors in time; the method is characterized in that: the fault monitoring system includes:
a hall sensor including an inertia measuring unit and a displacement measuring unit; the inertial measurement unit comprises three single-axis acceleration sensors and three single-axis gyroscopes, and is used for measuring speed signals, acceleration signals and angular speed signals of independent three axes; the displacement measuring unit comprises three single-axis displacement sensors and is used for measuring displacement signals of independent three axes; the hall door sensors are respectively arranged on hall doors of each layer of the elevator;
a signal transmission module for transmitting the detection signal of the hall sensor to a data relay processor;
a data relay processor mounted on top of a car of the elevator, the data relay processor in communication with an elevator control system; the data relay processor is to: (1) after a switching control command of any one of the hall doors sent by the elevator control system is inquired, the detection signal of the hall door sensor in the hall door of the corresponding layer is immediately acquired, the corresponding detection signal is converted into characteristic data reflecting the change of the motion state of the elevator hall door, and a curve reflecting the change of the motion state of the elevator hall door is drawn according to the characteristic data; sending the characteristic data to a cloud server; (2) after receiving the fault type of the elevator landing door on a certain floor sent by a cloud server, sending a control command for stopping the operation of the landing door on the fault floor and an alarm signal for representing the stop of the landing door on the fault floor to the elevator control system; (3) when the elevator control system responds to a switch control command of one elevator hall door, displacement signals detected in other elevator hall doors are obtained; when the displacement in any direction of any other hall door exceeds the preset displacement limit, sending an early warning signal for representing that the displacement exceeds the preset displacement limit layer and the hall door fault is to be checked;
a communication module for enabling bidirectional communication between the data relay processor and one of the cloud servers; and
a cloud server comprising a trained hoistway door fault detection model; and the cloud server is used for inputting the acquired characteristic data of the hall door of any layer into the elevator hall door fault detection model to obtain a fault state detection result of the hall door of the layer, and sending out the identification result of the fault type after identifying the fault type of the hall door.
2. The system for monitoring the failure of a hoistway door of claim 1, wherein: the signal transmission module is a wireless signal transmission module based on a Bluetooth module; the communication module is a communication module based on a communication network of a mobile operator.
3. The system for monitoring the failure of a hoistway door of claim 1, wherein: the data relay processor comprises an instruction transceiving unit and a computing unit; the command transceiver unit is used for inquiring the switch control command of any landing door generated by the elevator control system or sending a control command and an alarm signal for stopping the operation of the landing door on a certain floor to the elevator control system; and the computing unit is used for converting the acquired sensing signals of the hall door sensor into characteristic data reflecting the motion state change of the elevator hall door.
4. The failure monitoring system for hoistway doors according to claim 3, wherein: the data relay processor also comprises a storage unit which is used for storing the transmitting and receiving signals of the command transmitting and receiving unit and the calculation result of the calculation unit as the data backup of the elevator running state.
5. The system for monitoring the failure of a hoistway door of claim 1, wherein: the fault monitoring system also comprises a local data server and a local application server; all data received and generated in the cloud server are stored in the local data server; the local application server is used for responding to the request of a manager and providing access service of all data in the local data server for the manager.
6. The system for monitoring the failure of a hoistway door of claim 5, wherein: the local data server also comprises a failure probability database; the data in the fault probability database is used for representing the occurrence frequency of various faults in the whole life cycle of the elevator hall door.
7. The system for monitoring the failure of a hoistway door of claim 6, wherein: and the data relay processor feeds back the judgment result of the state of the elevator hall door to the local data server after receiving the judgment result of the state of the elevator hall door every time, and the local data server updates the fault probability database.
8. The system for monitoring the failure of a hoistway door of claim 1, wherein: the elevator hall door fault detection model is a network model based on a machine learning algorithm, the input of the elevator hall door fault detection model is characteristic data of the motion state of the elevator hall door in a switching period, and the output of the elevator hall door fault detection model is a fault type judgment result of the current elevator hall door.
9. The system for monitoring the failure of a hoistway door of claim 8, wherein: the training process of the elevator hall door fault detection model is as follows:
(1) obtaining typical motion state curves of the elevator hall door in a normal state and different fault type states;
(2) collecting characteristic data of the elevator hall door in an actual switch motion state, and drawing a corresponding sample motion state curve;
(3) comparing the sample motion state curve with a typical motion state curve, determining the state type of the hall door corresponding to each curve, manually marking, and taking the collected characteristic data and the corresponding manual mark as sample data of a sample data set; sampling according to the occurrence rates of different fault types to form a sample data set;
(4) dividing the sample data set into a training set and a test set, training the hoistway door fault detection model through the training set, and verifying the training effect of the model by using the test set; until the elevator hall door fault detection model meets the requirements of a training phase.
10. The system for monitoring the failure of a hoistway door of claim 9, wherein: in a sample data set used in the training process, the step of collecting fault types comprises the following steps: a blocking state caused by a threshold foreign body, a loose state of a door system change gear and a missing state of a door guide shoe; and the sample data reflecting the three samples accounts for the same ratio in the training set and the testing set.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110911676.6A CN113581962B (en) | 2021-08-10 | 2021-08-10 | Fault monitoring system of elevator hall door |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110911676.6A CN113581962B (en) | 2021-08-10 | 2021-08-10 | Fault monitoring system of elevator hall door |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113581962A CN113581962A (en) | 2021-11-02 |
| CN113581962B true CN113581962B (en) | 2022-09-20 |
Family
ID=78256736
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110911676.6A Active CN113581962B (en) | 2021-08-10 | 2021-08-10 | Fault monitoring system of elevator hall door |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113581962B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114634073B (en) * | 2022-03-04 | 2023-12-19 | 苏州汇川控制技术有限公司 | Elevator car control system and elevator system |
| CN116873690B (en) * | 2023-09-06 | 2023-11-17 | 江苏省特种设备安全监督检验研究院 | Elevator safety monitoring data processing system |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008156092A (en) * | 2006-12-26 | 2008-07-10 | Toshiba Elevator Co Ltd | Elevator control system, two-way door elevator control system, and emergency elevator control system |
| CN102085990A (en) * | 2011-02-10 | 2011-06-08 | 重庆和航科技有限公司 | Intelligent warning system for abnormal opening of lift door and safety detecting method thereof |
| CN105645211A (en) * | 2016-04-13 | 2016-06-08 | 尼森科技（湖北）有限公司 | Initiative elevator self-inspection device and initiative elevator self-inspection system |
| GB2567451B (en) * | 2017-10-11 | 2022-09-07 | Avire Ltd | An elevator system, test system, door blockage detection system, emergency call handler system, caller unit, monitoring system, and associated methods |
| JP6806725B2 (en) * | 2018-03-23 | 2021-01-06 | 株式会社日立ビルシステム | External opening jig, elevator system, inspection method and mobile terminal |
| AU2018100635A4 (en) * | 2018-05-14 | 2018-07-05 | Yan Wu | Feedback method for abnormal door-opening conditions of elevator and elevator |
| JP6997680B2 (en) * | 2018-06-01 | 2022-01-18 | 株式会社日立ビルシステム | Elevator abnormality monitoring system and elevator abnormality monitoring method |
| US20210221644A1 (en) * | 2018-12-21 | 2021-07-22 | Shenzhen Technology University | Method and apparatus for monitoring elevator door-opening operation fault |
| CN209835328U (en) * | 2019-03-26 | 2019-12-24 | 重庆航天职业技术学院 | Elevator monitoring system based on Internet of things |
| CN110143504A (en) * | 2019-04-09 | 2019-08-20 | 广东碧桂园物业服务股份有限公司 | A kind of elevator rescue channel based on fault pre-alarming mechanism |
-
2021
- 2021-08-10 CN CN202110911676.6A patent/CN113581962B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN113581962A (en) | 2021-11-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113581962B (en) | Fault monitoring system of elevator hall door | |
| CN111562096B (en) | Real-time online health state monitoring system of escalator | |
| CN108529380B (en) | Elevator safety prediction method and system | |
| CN111650919A (en) | Multi-dimensional monitoring escalator fault prediction and health management method and system | |
| CN110143504A (en) | A kind of elevator rescue channel based on fault pre-alarming mechanism | |
| KR20190049602A (en) | IoT based elevator pervasive autonomous system and method | |
| EP3674242B1 (en) | Enhancing elevator sensor operation for improved maintenance | |
| CN110294398B (en) | Escalator remote monitoring control system and method | |
| US20220388810A1 (en) | Method, device, and early warning system for monitoring elevator health state | |
| JP2020104611A (en) | Platform door state diagnosis system, platform door and platform door state diagnosis method | |
| CN110015601A (en) | Analyze the tele-control system and method for elevator faults reason | |
| CN113581961B (en) | Automatic fault identification method for elevator hall door | |
| CN109973804A (en) | Elevator fuel tank fuel quantity remote monitoring system and method | |
| CN110255310B (en) | Remote elevator monitoring system and method for cooperatively monitoring property data | |
| CN115724314A (en) | Elevator fault detection early warning system and method | |
| CN209740441U (en) | active safety elevator | |
| CN106081834A (en) | A kind of mine vertical shaft elevator unmanned control system and control method thereof | |
| CN112408143A (en) | Elevator thing networking operation monitoring system based on cloud platform | |
| CN211741892U (en) | Multi-dimensional state online monitoring system for escalator | |
| CN111302176A (en) | Lifting device monitored control system for building | |
| CN108516432A (en) | A kind of elevator reparing maintenance system based on Internet of Things | |
| KR102545137B1 (en) | Control board for escalator and remote integrated control system including the same | |
| CN212623713U (en) | Shuttle vehicle monitoring device and system and shuttle vehicle | |
| CN112093605B (en) | Elevator car running state recognition system and recognition method thereof | |
| CN209481003U (en) | A kind of elevator prediction fault diagnosis and monitoring system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |