KR102644256B1 - Control system for diagnosing and forcasting trouble of safety footboard - Google Patents

Abstract

A safety step failure prediction control system is disclosed that allows the safety step failure to be diagnosed and predicted remotely. The control system includes a motor control unit that controls a motor cylinder installed in response to a safety step and a station control server connected through an internal network; A remote integrated control server connected to the station control server through a communication network including the Internet, 5G, and LTE network; and a terminal connectable to the station control server and the integrated control server through the communication network, wherein the motor control unit includes: a motor driver that controls forward/reverse rotation and rotation speed of the motor of the motor cylinder according to a predetermined motion profile; and a motor control unit that controls the motor driver to control the driving of the motor cylinder and receives feedback of the actual position of the motor cylinder from a position detection sensor.

Description

{Control system for diagnosing and forcasting trouble of safety footboard}

The present invention relates to a failure diagnosis and prediction control system for safety scaffolds, and particularly to technology that allows diagnosis and prediction of failures in safety scaffolds remotely.

Because an excessively wide gap is formed between the train and the platform, safety accidents occur where passengers' feet fall into the gap when getting on and off, so safety footrests are used as facilities to prevent this.

Examples of such safety scaffolds may refer to the applicant's registered patents Nos. 2167171, 1614467, and 1668283.

However, conventionally, in order to check the operating status of the safety step, personnel and equipment must be directly deployed to the site, and furthermore, it is difficult to check for malfunctions while the train is running, which has the disadvantage of limiting work time.

In addition, it is difficult to analyze the failure type of the safety step, so not only is the reliability of the safety step control system not secured, but there is also a problem in that it takes a long time to maintain the safety step.

Looking at the real-time monitoring system for maintenance of railway vehicle safety scaffolds proposed as an alternative to this in Korea Patent No. 1172735, if the safety scaffold is judged to be broken, field workers use a mobile computer such as a laptop or portable industrial computer installed on the vehicle body. Connect the RS-232 cable or USB cable to the RS232C connection terminal or USB connection terminal, which is the expansion interface of the access door control device, and run the analysis program on the mobile computer to analyze the status of the safety step and step control device.

As a result, through the analysis program of the mobile computer, the information transmission and reception status of the footrest control device, the forward and backward status of the safety footrest, the driving current of the motor and vehicle power input value during forward and backward operation, the opening/closing time, and the position of the safety footrest, etc. Information can be checked in real time as digital and analog data.

However, the above system also has the disadvantage of requiring personnel and equipment to be deployed to the site and not being able to monitor it remotely.

In addition, there is a disadvantage that the analysis program can only check the current status of the safety scaffold and control device in real time and cannot predict failure.

Therefore, the purpose of the present invention is to provide a safety step failure diagnosis and prediction control system that can remotely diagnose and predict safety step failure.

Another object of the present invention is to provide a failure diagnosis and prediction control system for safety scaffolding that can minimize the number of people and equipment deployed on site and minimize time limits for failure diagnosis.

The above purpose is a failure diagnosis and prediction control system for safety scaffolding, which includes a motor control unit that controls a motor cylinder installed in response to the safety scaffolding and a station control server connected through an internal network; A remote integrated control server connected to the station control server through a communication network including the Internet, 5G, and LTE network; and a terminal connectable to the station control server and the integrated control server through the communication network, wherein the motor control unit includes: a motor driver that controls forward/reverse rotation and rotation speed of the motor of the motor cylinder according to a predetermined motion profile; and a motor control unit that controls the motor driver to control the driving of the motor cylinder and receives real-time feedback of the actual position of the motor cylinder from a position detection sensor, wherein the station control server includes a data server, and the data server Part information, motion profile according to the rise and fall of the scaffold, deviation data, and failure history information are stored based on the unique identifier of each safety scaffold, and an analysis program for failure diagnosis and prediction is installed in the station control server. This is achieved by a failure diagnosis and prediction control system for the safety step, which is characterized in that it diagnoses and predicts a failure in the operation of the safety step using the actual position received from the position detection sensor.

Preferably, the analysis program includes: a position deviation calculation unit that calculates a position deviation Pe from the position Pc of the motor cylinder according to the motion profile and the actual position Pf of the motor cylinder detected by the position detection sensor; A maximum position deviation calculation unit that calculates the maximum position deviation Pem in one operation section; A position deviation displacement calculation unit that calculates the position deviation displacement Pv occurring in one operation section; and a control unit that stores the detected or calculated deviation data for each motor control unit and uses this to diagnose and predict whether the safety footrest is malfunctioning and report the malfunction.

Preferably, the control unit a) determines that the hinge portion of the safety step is pinched when the maximum position deviation Pem is out of range with only continuous torque without a torque inflection point, and b) determines that the torque inflection point is in the rising section of the safety step. If found, failure of the driving connection part of the safety step is determined. c) If the position deviation displacement Pv occurs upon completion of raising or lowering, failure of the connection part of the driving shaft of the motor cylinder is determined.

Preferably, the position deviation Pe, the maximum position deviation Pem, the position deviation displacement Pv, and the change in torque and failure type are stored in the station control server, and the failure pattern is analyzed and learned through this to generate failure diagnosis data. do.

Preferably, at the request of the station control server, the motor control unit controls zooming, panning, and tilting of the camera to photograph a part diagnosed as having a failure or where a failure is predicted and transmits it to the station control server. Delivers the transmitted video upon a request from the terminal.

According to the present invention, it is possible to remotely check the condition of the safety step as well as diagnose and predict a failure of the safety step.

In addition, because various patterns of failure can be analyzed in advance, the number of people and equipment required on site can be minimized and the time limit for failure diagnosis can be minimized.

In addition, through camera photography, managers can remotely monitor areas where failures are diagnosed or failures are predicted without having to access the site.

Figure 1 shows the network configuration of the safety scaffold failure diagnosis and prediction control system.
Figure 2 shows an example of a safety step.
Figure 3 shows the functional configuration of an analysis program for failure diagnosis and prediction.
Figure 4 is a graph showing the motor speed and torque of the motor cylinder over time during the lifting operation of the scaffold.

It should be noted that the technical terms used in the present invention are only used to describe specific embodiments and are not intended to limit the present invention. In addition, the technical terms used in the present invention, unless specifically defined in a different sense in the present invention, should be interpreted as meanings generally understood by those skilled in the art to which the present invention pertains, and are not overly comprehensive. It should not be construed in a literal or excessively reduced sense.

Hereinafter, the platform safety step device according to the present invention will be described in detail with reference to the attached drawings. Here, the attached drawings are intended to aid understanding of the present invention, and for convenience of explanation, the dimensions of some components may be ignored and may be shown somewhat exaggeratedly.

Figure 1 shows the network configuration of a safety step failure diagnosis and prediction control system, and Figure 2 shows an example of a safety step.

In response to the entrance door of the electric train, a platform screen door (not shown) and a safety step (200) are installed in pairs on the platform, and a motor control unit (100) is installed for each safety step (200) to raise and lower the safety step. control.

Briefly explaining the structure of the safety step 200 with reference to FIG. 2, a frame unit 260 is fixedly installed on the front of the platform 10 to form a basic frame, and is attached to the hinge block 262 of the frame unit 260. The hinge 252 of the scaffold 250 is coupled to enable the scaffold 250 to rotate in the up and down directions.

A plurality of support arms 240 are rotatably coupled to the arm holder 245 coupled to the frame unit 260 via a bearing block (not shown), support the scaffold 250, and Each support arm 240 is connected to a moving bar 220 by an arm lever 230 so that the support arms 240 rotate simultaneously.

Here, each arm lever 230 is rotatably coupled to the moving bar 220 via a bearing block (not shown).

A motor cylinder 210 and a link member 212 are accommodated inside from the front of the platform 10 at the lower part of the frame unit 260, and a support arm 240 is connected to the link member 212 to form a motor cylinder 210. The linear motion of is changed into a rotational movement of the support arm 240 by the link member 212, so that the support arm 240 raises or lowers the scaffold body 250.

The motor cylinder 210 is a combination of a motor, a reducer, and a screw, and refers to a device used to change the rotational motion of the motor into linear motion through the reducer and the screw. In the following description, the control of the motor cylinder is ultimately the control of the motor. means.

The motor control unit 100 consists of a motor control unit 110 and a motor driver 120.

The motor driver 120 controls forward/reverse rotation and rotation speed of the motor according to a determined motion profile under the control of the motor control unit 110.

The motor control unit 110 controls the motor driver 120 to control the driving of the motor cylinder 210 and receives feedback on the actual rotational position of the motor in real time from the position detection sensor 130.

Here, the position detection sensor 130 detects the actual rotational position of the motor constituting the motor cylinder 210 by applying an encoder, for example.

Additionally, the motor control unit 110 receives sensing data detected from a sensor unit including the position detection sensor 130 and receives image information from the camera 140.

The motor control unit 110 is connected to the station control server 300 through the internal network 50 and transmits the collected information along with the unique identifier of the motor control unit 100 to the station control server 300, or At the request of the server 300, connected devices, such as the camera 140 or warning lamps, can be controlled.

In addition to the position detection sensor 130, the sensor unit may include, for example, a sensor that detects the rise and fall of the scaffold 250, a sensor that detects an obstacle, and a sensor that detects a collision.

In addition, the camera 140 can perform basic operations such as zooming, panning, and tilting by the motor control unit 110, and focuses on the area diagnosed as a failure or predicted to have a failure through zooming, panning, and tilting operations. It can be observed.

The station control server 300 is, for example, installed at each station to diagnose or predict failure of the safety scaffolding at the station, has a unique identifier, and is connected to a remote integrated control server (60) through a communication network such as the Internet or 5G and LTE network. 400).

The integrated control server 400 is equipped with an integrated data server 402 and stores all information collected from each station control server 300 based on the unique identifier of the station control server 300.

An administrator permitted to access the station control server 300 can check the operating status of the safety step 200 in real time by accessing the station control server 300 through a wireless terminal 410 such as a mobile phone or a computer device 420. You can.

Alternatively, when a failure occurs, the station control server 300 can send an alarm and failure information to the wireless terminal 410 of an authorized manager in a push method. For example, commercial applications such as Telegram or KakaoTalk can be applied.

According to this configuration, a malfunction that occurs while operating the safety step 200 can be confirmed in real time and the part related to the malfunction can be visually confirmed by filming with the camera 140. In addition, although an actual failure has not occurred, it is possible to predict a failure that is likely to occur based on analysis by the station control server 300 and stored failure patterns. The area where the failure is predicted can be photographed with the camera 140 and viewed through a mobile phone. You can check it in real time.

This process can be equally applied to the integrated control server 400, in which case the operating status of the safety scaffolding at each station can be identified in real time.

The station control server 300 is equipped with a data server 302, and the data server 302 includes component information, motion profile according to the rise and fall of the scaffold, and deviation data for each safety scaffold 200 based on a unique identifier. , and failure history information are stored.

An analysis program for failure diagnosis and prediction is installed in the station control server 300 to predict operational failures of the safety scaffold using data received from a sensor unit including the position detection sensor 130.

Figure 3 shows the functional configuration of an analysis program for failure diagnosis and prediction.

As described above, the data server 302 stores a motion profile for controlling the rise and fall of the scaffold 250, and the control unit 310 controls the motor control unit 110 to control the motor cylinder 210 in motion. It operates based on the profile.

Typically, the motion profile creates a smooth curved transfer trajectory for stable rise and fall of the scaffold 250.

The position deviation calculation unit 320 calculates the position deviation from the position Pc of the motor cylinder 210 according to the motion profile and the actual position Pf of the motor cylinder 210 detected by the position detection sensor 130 such as an encoder.

Position deviation Pe = Commanded position Pc - Actual position Pf

Here, the position of the motor cylinder 210 may be the rotational position of the motor, the moving position of the screw due to motor rotation, or the rotational position of the safety footrest, and are collectively referred to as the position of the motor cylinder 210. The position of the motor cylinder 210 can be easily detected by using an encoder as a position detection sensor, for example, the rotational position of the motor.

The maximum position deviation calculation unit 330 calculates the maximum position deviation Pem in one operation section.

The position deviation displacement calculation unit 340 calculates the displacement Pv of the position deviation occurring in one operation section. Since the raising and lowering of the scaffold 250 is operated according to a set motion profile, the positional deviation displacement Pv also appears within a set range, and it can be predicted that a structural failure occurs from the positional deviation displacement Pv outside the set range.

Additionally, the speed deviation calculation unit 350 calculates the speed deviation Ve by performing a differential operation on the position deviation.

The control unit 310 stores detected or calculated deviation data for each motor control unit and uses this to diagnose and predict failure and notify the failure area.

Hereinafter, the fault diagnosis and prediction process will be described in detail.

Figure 4 is a graph showing the motor speed and torque of the motor cylinder over time during the lifting operation of the scaffold.

As shown, the scaffold 250 exhibits a maximum speed midway through the lifting operation and a minimum speed at the completion of the lift.

The solid line graph is a graph based on operation commands, and the dotted line graph is a graph based on actual operation. There is a time deviation in speed between both graphs, and as a result, there is a position deviation, and there is also an inflection point during the upward operation. It's showing.

The positional deviation appears differently depending on the weight of the scaffold and the characteristics of the mechanical combination of the safety footrest. This positional deviation is converted into data and calculated as a quantitative value. By looking at the trend of this calculated value, any abnormality in the operation of the safety footrest can be detected. can do.

The position deviation calculation unit 320 obtains the position deviation Pe from the command position Pc of the motor and the actual position Pf of the motor.

The position deviation Pe changes by a certain amount. For example, the dotted line graph in Figure 4 shows an inflection point where the change in value appears quite large.

The inflection point of the positional deviation Pe represents an instantaneous change value and is caused by a mechanical obstacle in the safety footrest. In terms of the structure of the footrest, there is a hinge part of the footrest, a link part of the motor cylinder, and a bearing connection part.

In addition, the position deviation Pe should always appear as 0 (zero) when the raising or lowering of the scaffold is completed. In other words, the position deviation Pe cannot exist because the target position has been reached. However, if the position deviation Pe exists when the ascent or descent is completed, the motor does not operate smoothly due to interference or deformation of the scaffold structure, resulting in failure. It can be the cause of and through this, failure can be predicted.

Additionally, the maximum position deviation calculation unit 330 calculates the maximum position deviation Pem that occurs during ascent from the position deviation thus obtained.

The maximum position deviation Pem obtained in this way maintains a constant value because the structure of the safety scaffold does not change and the weight of the scaffold does not change. Therefore, if the change range of the maximum position deviation Pem exceeds the specified value, it can be predicted that a structural problem occurs during operation of the safety step.

The maximum position deviation Pem is equal to the change in motor load, so unless a specific jamming occurs, it can be characterized as the weight of the hinge and footrest that affects the motor load.

For example, looking at Figure 1, the portion where the scaffold 250 is hinged to the frame unit 260 (dotted line circle a) and the bearing block (dotted line a) for coupling the support arm 240 to the arm holder 245 Circle b), and the bearing block connecting the arm lever 230 to the moving bar 220 may all be obstacles, and if the range of change in the maximum position deviation Pem exceeds the specified value, the relevant part must be removed first. You need to check.

The position deviation displacement calculation unit 340 calculates the change value Pv of the position deviation occurring in one operation section.

The position deviation displacement Pv represents the total amount of load that the motor receives in the rising section, and as long as there is no change in the load on the motor, that is, unless there is a change in the structure of the safety footrest, the load amount remains constant without change.

As mentioned above, the symptoms of jamming in the hinge or bearing block are such that the total load continues to be biased to one side. In this case, by monitoring and accumulating the maximum position deviation Pem or position deviation displacement Pv and learning, the rate of change of the bearing and hinge can be estimated. This allows the failure phenomenon to be identified.

Meanwhile, as described above, by performing differential calculation on the position deviation Pe, the actual speed deviation Ve of the motor can be calculated.

By performing differential processing on the speed deviation Ve created in this way, the change in torque generated by the motor can be measured. With the position Pf, it is possible to predict and view the failure phenomenon according to the operating position of the scaffold.

For example, if the maximum position deviation Pem is out of range with only continuous torque without a torque inflection point, pinching of the hinge portion (circle a in Figure 1) of the scaffold 250 can be predicted, and the torque inflection point in the rising section of the scaffold If this is found, failure of the drive connection part of the scaffold (circle b in Figure 1) can be predicted, and if positional deviation displacement Pv occurs at the completion of raising or lowering, problems may occur in the connection part of the drive shaft of the motor cylinder (circle c in Figure 1). can be predicted to occur.

The various values measured above, namely, position deviation Pe, maximum position deviation Pem, speed deviation Ve, position deviation displacement Pv, change in torque, and failure history, are stored in the control server 300, and the failure pattern is analyzed and learned through them. Fault diagnosis data can be generated.

Meanwhile, at the request of the station control server 300, the motor control unit 110 controls the zoom-in, panning, and tilting of the camera 140 to photograph the area diagnosed as a failure or where a failure is predicted and sends the photo to the station control server 300. The station control server 300 transmits the video received to the mobile phone at the request of the manager, allowing the manager to remotely monitor parts diagnosed as malfunctioning or predicted to malfunction without accessing the site.

Although the above description focuses on embodiments of the present invention, it goes without saying that various changes can be made at the level of those skilled in the art. Therefore, the scope of the present invention cannot be construed as limited to the above-described embodiments, and should be interpreted in accordance with the claims set forth below.

100: Motor control unit
110: Motor control unit
120: motor drive
200: safety footrest
300: Station control server
302, 402: Database
410: mobile terminal
420: computer device
60: communication network
400: Remote integrated control server

Claims (5)

As a failure diagnosis and prediction control system for safety scaffolding,
A motor control unit that controls the motor cylinder installed in response to the safety step and a station control server connected through an internal network;
A remote integrated control server connected to the station control server through a communication network including the Internet, 5G, and LTE network; and
It includes a terminal that can connect to the station control server and the integrated control server through the communication network,
The motor control unit includes a motor driver that controls forward/reverse rotation and rotation speed of the motor of the motor cylinder according to a predetermined motion profile, and controls the driving of the motor cylinder by controlling the motor driver, and controls the driving of the motor cylinder in real time from a position detection sensor. It consists of a motor control unit that receives feedback on the actual position of the motor cylinder,
The station control server is provided with a data server, and the data server stores component information, motion profiles according to the rise and fall of the scaffold, deviation data, and failure history information based on the unique identifier of each safety scaffold,
An analysis program for failure diagnosis and prediction is installed in the station control server to diagnose and predict operational failures of the safety scaffold using the actual position received from the position detection sensor,
The analysis program is,
a position deviation calculation unit that calculates a position deviation Pe from the position Pc of the motor cylinder according to the motion profile and the actual position Pf of the motor cylinder detected by the position detection sensor;
A maximum position deviation calculation unit that calculates the maximum position deviation Pem in one operation section;
A position deviation displacement calculation unit that calculates the position deviation displacement Pv occurring in one operation section; and
A failure diagnosis and prediction control system for safety scaffolds, characterized in that it consists of a control unit that stores the detected or calculated deviation data for each motor control unit and uses this to diagnose and predict whether the safety scaffold is broken and notifies the failure part. . delete In claim 1,
The control unit,
a) If the maximum position deviation Pem is out of range with only continuous torque without a torque inflection point, it is determined that the hinge portion of the safety footrest is jammed,
b) If a torque inflection point is found in the rising section of the safety step, failure of the driving connection part of the safety step is determined,
c) A failure diagnosis and prediction control system for a safety scaffold, characterized in that it determines a failure of the connection part of the drive shaft of the motor cylinder when the position deviation displacement Pv occurs at the completion of raising or lowering. In claim 1,
The position deviation Pe, the maximum position deviation Pem, the position deviation displacement Pv, and the change in torque and failure type are stored in the station control server, and the failure pattern is analyzed and learned through this to generate failure diagnosis data. A failure diagnosis and prediction control system for safety scaffolding. In claim 1,
At the request of the station control server, the motor control unit controls zooming, panning, and tilting of the camera to photograph the part diagnosed as a failure or where a failure is predicted and transmits it to the station control server,
The station control server is a safety scaffold failure diagnosis and prediction control system, characterized in that the transmitted video is transmitted upon a request from the terminal.

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