System for processing an orbit

Abstract

The present invention relates to a system for processing a track (2) by means of a track construction machine (1) comprising a machine control unit (4) and a working unit (3) driven and controlled thereby, in which a sensor (6) is arranged to monitor the working unit (3). The sensor (6) collects sensor data (S D ) are connected to a data collection module (7) for separately collecting the sensor data (S D ) to the result data (E D ) is connected to a calculation unit (8) in which a first algorithm (P1) for calculating the sensor signal (S S ) by means of a data acquisition module (7) and a calculation unit (8), different evaluations of the work movements can be carried out, independent of the monitoring functions provided.

Description

Technical Field

[0001] The present invention relates to a system for processing a track by a track construction machine including a machine control unit and a work unit driven and controlled thereby, wherein sensors are arranged for monitoring the work unit. The present invention further relates to a method for operating the system.

Background Art

[0002] From Austrian Patent Application Publication No. 520698, a system in the form described at the beginning is known. This system is used for load monitoring of a tamping unit during track processing. For this purpose, sensors are arranged to collect measurement data over a period and transfer it to an evaluation device. From the measurement data, the load-time course of the cyclic working process of the tamping unit is derived. An estimation of the load situation of the tamping unit obtained therefrom is used to set maintenance means or maintenance intervals.

Summary of the Invention

Problems to be Solved by the Invention

[0003] The underlying problem of the present invention is to expand the utilization of the sensors provided in the system in the form described at the beginning. Further, it is desired to provide a correspondingly improved method for operating the system.

Means for Solving the Problems

[0004] These problems are solved by the characteristic configurations of independent claims 1 and 11 according to the present invention. Advantageous embodiments of the present invention are shown in the dependent claims.

[0005] Here, the sensor is connected to a data collection module to collect sensor data separately, and the data collection module is configured to be connected to a calculation unit in which a first algorithm for calculating result data from the sensor data is set. In this way, the system has additional structural components for processing sensor signals. Different evaluations of the working operation can be performed by the data collection module and the calculation unit in which an application-specific algorithm is set, without depending on the provided monitoring function. Specific advantages are obtained by the flexible configuration of sensor data collection and the adaptability of result data calculation.

[0006] In one development form, the calculation unit is configured to calculate at least one characteristic quantity from the sensor data collected during the working process. In particular, the calculation unit is connected to a machine control unit to automatically set optimal working parameters. Thereby, the working process executed by the working unit is continuously improved. The calculated characteristic quantity is adjusted to the working unit used, and the quality of the corresponding working process is characterized by this characteristic quantity. The result of this improvement is the upper control loop at the level of the control system.

[0007] Advantageously, the data collection module is configured for multi-channel data collection and is connected as a slave to a calculation unit configured as a master. With this system architecture, a plurality of sensors can be efficiently connected to the subsystem composed of the data collection module and the calculation unit.

[0008] In another improvement, a monitoring device for collecting sensor data at a sampling rate lower (e.g., 1 Hz) than that of the data collection module (e.g., sampling rate in the kHz range) is arranged to monitor the working unit. Thereby, for monitoring, easy but sufficient data processing is possible. In contrast, for additional sensor evaluation using the calculation unit, a database with high time resolution can be utilized.

[0009] In an advantageous expansion of the system, the computing unit is configured to be coupled to a database via communication means in order to receive program data for changing the first algorithm or for setting the second algorithm. Thereby, the evaluation executed by the computing unit can be easily changed. With the system, a new analysis of the working process can be carried out without the need for structural changes. Furthermore, a new evaluation algorithm can be tested by the system and then the adaptation of the working process can be derived.

[0010] In this case, it is advantageous if the communication means includes a VPN router. Thus, all devices connected to this VPN router can utilize a secure VPN tunnel. This applies to the computing unit and other system components that exchange data with the database. The VPN router integrated into the system extends the possibility of secure transmission of distributed data.

[0011] In another improvement, the computing unit is connected to a storage device for storing sensor data and / or result data. Preferably, the storage device is designed to be large enough so that all result data or, if necessary, all sensor data as well are stored until the end of the set read interval. For example, the read interval corresponds to the maintenance interval of the work unit being monitored. Furthermore, the data stored in the storage device can be called at any time using remote access, preferably via a VPN tunnel. In particular, the transmission of result data via remote access is effective. In contrast, the large data volume of sensor data is stored in the storage device and read out when the system is modified.

[0012] For the result data to be uniformly available, and if necessary the sensor data as well, it is advantageous for the computing unit to be connected to a computer network (cloud) via a modem for data transmission. This enables access to the data at any time via an online application (Web-App).

[0013] An advantageous feature of the system is that it has a tamping unit and / or a stabilizing unit as working units. Such a vibrating tool with working units causes vibrations in the ballast track to be processed. Sensors arranged in the working units can be used to obtain an estimate of the quality of the track ballast bedding and the compaction of the track ballast. Thus, the system can provide information not only about the state of the working units themselves and the way the work is done, but also about the state and treatment of the track.

[0014] Preferably, a motion sensor for detecting the vibration period is arranged as the sensor. In both the tamping unit and the stabilizing unit, the course of motion and the course of force during the vibration period can be utilized to obtain characteristic values for the compaction process.

[0015] In a method of operating the system according to the present invention, a sensor is used to generate a sensor signal for monitoring the working unit, the sensor signal is supplied to a data collection module for separate sensor data collection, and result data is calculated from the sensor data using a first algorithm set in the computing unit. Along with the monitoring of the working unit, result data is derived from the sensor data in parallel during the course of this method. In this case, it is important not only to consider the characteristics or quality of the result data, but also to utilize freely determinable algorithms using system components provided specifically for this purpose. These are the data collection device and the computing unit.

[0016] In an advantageous development of this method, as result data, characteristic values of the working process are calculated and transmitted to the machine control unit. In this effective utilization of the system, the control loop enables an automatic improvement of the working process executed by the working unit.

[0017] This method is improved by an easily executable adaptation of the algorithm, and program data is transmitted to the computing unit to change the first algorithm or to set the second algorithm. This is done by means of a connection via a VPN tunnel or by a direct connection to the computer from which the program data is supplied.

[0018] Advantageously in this case, new program data is loaded into the memory of the computing unit in the first step, and the new program data is activated after a restart of the computing unit in the second step. This two-step update process ensures that system failures do not occur due to program data that may have errors in some cases. Since the new program is only started after the restart, the computing unit (processor) is always in a defined state.

[0019] It is reasonable to transmit the result data from the computing unit to an external computer via a VPN tunnel or via an offline connection. Thus, the data is available centrally or distributedly for subsequent processing, can be used later in various ways, and can also be archived.

[0020] In the following, the present invention will be illustrated by way of example with reference to the accompanying drawings.

Brief Description of the Drawings

[0021]

Figure 1

Figure 2

Figure 3

Figure 4

Embodiments for Carrying Out the Invention

[0022] The system exemplarily includes a tamping machine as a track construction machine 1 for processing track 2. Such a track construction machine 1 has a tamping unit and a lifting and track alignment unit as a working unit 3. Additionally, a stabilizing unit may be arranged as the working unit 3. The working unit 3 is driven and controlled by a machine control unit 4. Further, the track construction machine 1 has a measurement system 5 for collecting the actual state of the track 2.

[0023] In order to monitor the working unit 3 configured as a tamping unit, a sensor 6 is arranged. An exemplary sensor 6 is described in the specification of Austrian Patent Application No. A290 / 2018 of the same applicant. The sensor 6 attached to the tamping unit or another working unit 3 measures the acceleration and / or force acting on the individual unit components. Temperature measurement may also be aimed at for monitoring the state of the unit 3.

[0024] A sensor signal S S is generated by each sensor 6, and these sensor signals S S are detected by a data acquisition module 7 (DAQ, Data Acquisition Modul) and subsequently processed as sensor data S D For this purpose, the data acquisition module 7 is connected to a calculation unit 8. A first algorithm P1 (program) is set in this calculation unit 8 to calculate result data E D from the sensor data S D These result data E D are used to evaluate the working process executed by the working unit 3 or to evaluate the properties of the processed track 2. For this purpose, the result data E DIt includes corresponding characteristic values.

[0025] Advantageously, the calculation unit 8 and the data collection module 7 are interconnected in a master - slave architecture. The data collection module 7 includes, for example, a plurality of DAQ units having 12 to 16 channels to which sensor signals S S are supplied. The data collection module 7 detects the sensor signal S D at a high sampling rate in the region of several kilohertz in order to generate sensor data S S for subsequent processing with high time resolution.

[0026] In contrast, for a pure monitoring function, lower - resolution sensor data S D is sufficient. Generally, in order to track the wear process of unit components and estimate possible maintenance measures, several sensor data S D per unit time (for example, at a sampling rate of 1 Hz) are required. Therefore, it is reasonable to provide a separate data processing unit with a dedicated data collection unit 9 for monitoring purposes. The monitoring device 10 further includes another component, for example, a microprocessor 11 and a modem 12 for transmitting monitoring data U D to a computer network (cloud) 13. Such a monitoring device 10 is described in the Austrian Patent Application Publication No. 520698 of the same applicant.

[0027] It is reasonable that the modem 12 of the monitoring device 10 or a separate modem is also used to transmit the result data E D generated by the calculation unit 8. In this way, the result data E D and the sensor data S D transmitted together as required are made uniformly available in the computer network 13. For example, using a secure online application (Web - App), the data S D ,E Dcan be displayed and processed subsequently (Web-Access).

[0028] The track construction machine 1 includes, as a calculation unit 8, for example, a high-performance Linux (registered trademark) server. As a result, the signal data S collected at a high sampling rate D can be processed in real time. In any case, the result data E D In order to ensure the real-time calculation of, it is reasonable to adjust the sampling rate of the data collection module 7 and the calculation performance of the calculation unit 8 with respect to each other. Thereby, in the track construction machine 1, various characteristic characteristic quantities in the working process can be directly specified.

[0029] Furthermore, it is advantageous if the calculation unit 8 is configured in such a way that the CPU capacity can also be used for the processing of advanced mathematical algorithms. These mathematical algorithms are models and calculation algorithms for the state evaluation of the mechanical part and for adapting the working parameters. All algorithms set in the calculation unit 8 are tasks T1, T2, T n (Process) is executed. Specifically, in the calculation unit 8, a master application M that starts and activates the individual tasks T1, T2, T n operates (FIG. 3).

[0030] In addition to or instead of the transmission of the sensor data S D and the result data E D to the computer network 13, these data S D , E D are stored in the storage device 15 connected to the calculation unit 8. For example, a dedicated processor (server) is implemented in the calculation unit 8, and this processor associates various system variables and stores the desired data S D , E D in the mass storage of the storage device 15. The stored data S D , E DFor example, during the repair of the track construction machine 1, it can be transmitted to the computer 14 via the data interface 16.

[0031] In the embodiment variant shown in FIG. 2, the system comprises communication means 17 for collating program data with the database 18. For example, a VPN router connected to the computing unit 8 is provided for this purpose. In this way, the sensor data S D and the result data E D can also be transmitted via the VPN tunnel 19.

[0032] Advantageously, the VPN tunnel 19 is also used for software updates of the computing unit 8 (FIG. 3). For this purpose, the launched task T n checks whether a new algorithm is prepared in the database 18. For example, for this purpose, a comparison with the latest versions of the running tasks T1, T2 is made. If necessary, the changed algorithm P1 or the new algorithm P2 is loaded and compiled via the VPN tunnel 19 and entered into the task list T. By restarting the computing unit 8, a new task is started and processed.

[0033] Such updates can also be used to analyze the progress in the track construction machine 1, which has not been paid attention to so far. In this case, first, a new algorithm P2 adapted to the problem to be analyzed is loaded and compiled into the computing unit 8. For example, when a set event occurs, the sensor data S of some selected sensors 6 by the corresponding task T2 D is written to the storage device 15. After a sufficient collection duration, the collected data S D , E D is uploaded to the computer network 13 and analyzed.

[0034] The developed form of the system is shown in Figure 4. The working unit 3 is monitored by various sensors 6. Through the data collection module 7, sensor data S D is supplied to the calculation unit 8 by these sensors 6 and another sensor 6 (inertial measurement unit, laser cutting sensor, hydraulic pressure gauge, etc.) arranged on the track construction machine 1. Using various algorithms P1, P2, P n , characteristic quantities related to control are calculated here as result data E D . Each characteristic value is returned to the machine control unit 4 and stored, thereby resulting in an active intervention in the working process.

[0035] For this purpose, the machine control unit 4 (control system of the track construction machine 1) is equipped with a central control unit 20 that coordinates a plurality of distributed subsystems 21. These are, for example, a subsystem 21 for setting the rotational speed of the eccentric drive for vibration generation, a subsystem 21 for the tamping tine opening width of the tamping unit, a subsystem 21 for the penetration automatic device for the tamping tool, and a subsystem 21 for unit positioning.

[0036] Therefore, the physical quantities of the working process that are affected are detected and measured. The detected quantities are supplied to the calculation unit 8 as a data stream, and all tasks T1, T2, T n have overall access to these sensor data S D . When executing tasks T1, T2, T n , characteristic quantities typical of the working process are identified. These characteristic quantities are subsequently fed back to the central control unit 20 to set optimal working parameters for the subsystem 21. Thereby, a higher-level control loop with an observation-based controller is configured at the level of the control system.

[0037] In an advantageous developed form, the calculation of the optimal working parameters is directly performed in the calculation unit 8. For this purpose, the calculation unit 8 is provided with corresponding algorithms P1, P2, P nIt is set. The newly calculated working parameters are set in the central control unit 20. Therefore, the machine control unit 4 itself does not perform parameter calculation. Thus, the requirements regarding the safety applied to the machine control unit 4 are not affected.

[0038] An example of multiple tamping using a tamping unit will be described in detail for setting new working parameters. In multiple tamping, in order to improve ballast compaction, the vibrating tamping tool is sunk into the ballast bed and squeezed at the same location multiple times.

[0039] For parameter optimization, first, sensor data S is collected over a relatively long observation time. D For example, the pressing force and stroke of the squeeze cylinder of the tamping unit are recorded. For each recorded tamping cycle, characteristic quantities are calculated, and these characteristic quantities are used as basic data in the next step.

[0040] The base data collected by the system of the present invention is available offline for training a prediction model. Specifically, the recorded data and each target variable (the number of tamping processes per tamping cycle) are used as training data. The trained prediction model corresponds to a new algorithm P2 that enables prediction of the target variable.

[0041] Through testing and verification, the new algorithm P2 can be further improved. The test data used is different from the training data used previously. The prediction of the target variable is adjusted to a set target value to evaluate the quality of the prediction model. If necessary, the algorithm P2 is made to undergo a training step again to improve the prediction quality.

[0042] With the created algorithm P2, the setting of each working parameter (target variable) is directly and in real time performed on the track construction machine 1. Even when the tamping tool penetrates into the ballast bed, the sensor 6 supplies useful sensor data S for calculating characteristic quantities regarding the properties of the ballast bed. D Anyway, at the end of the first tamping process, sufficient sensor data S D is obtained to calculate the definite result data E. D In this embodiment, regarding whether a further tamping process is necessary at the same location to achieve the desired compaction, the result data E D is set in real time to the machine control unit 4.

[0043] Another advantage of the system of the present invention is obtained in a multi-packing tamping unit having a plurality of tamping units arranged one after another. These tamping units are sunk into the ballast bed together to tamp a plurality of packings simultaneously. Here, the sensor data S collected and processed in real time is used to drive and control each tamping unit separately. Specifically, the properties of the ballast bed identified when the tamping tool penetrates are used for setting different squeeze pressures. If necessary, different squeeze times are also set for each tamping unit. That is, when tamping simultaneously over a plurality of packings, sometimes a problem occurs that the ballast bed has different ballast compactions under each packing in the starting state. D For each tamping unit, the associated sensor data S

[0044] is used. DThe characteristic value calculated from already indicates the respective degree of compaction at the corresponding location of the ballast bed during the penetration process. For each secondary control, an adapted squeeze pressure or, if necessary, an adapted squeeze duration is set by the corresponding algorithm P2. At locations where the degree of compaction is already high, the tamping energy is reduced and introduced into the ballast bed by reducing the squeeze pressure and the squeeze time. However, at penetration locations with a low degree of compaction, squeezing is performed at a high pressure and for a longer duration. This results in uniform compaction of the ballast over the track section processed by the multiple tamping units.

Claims

1. A system for processing a track (2) by a track construction machine (1) comprising a machine control unit (4) and a work unit (3) driven and controlled by the machine control unit (4), wherein a sensor (6) is arranged for monitoring the work unit (3), and sensor data for a monitoring device (10) is collected. In the system, the sensor (6) is connected to a data collection module (7) which is not part of the monitoring device (10) for separately collecting sensor data (S Ｄ ), and the data collection module (7) is connected to a calculation unit (8) in which a first algorithm (P Ｄ ) for calculating result data (E Ｄ ) from the sensor data (S １ ) is set. A system characterized by this.

2. The calculation unit (8) is configured to calculate at least one characteristic quantity from the sensor data (6) collected during the working process, and in particular, the calculation unit (8) is connected to the machine control unit (4) to automatically set optimal working parameters. The system according to claim 1, characterized in that.

3. The data collection module (7) is configured for multi-channel data collection and is connected as a slave to the calculation unit (8) configured as a master. The system according to claim 1 or 2, characterized in that.

4. To monitor the operation unit (3), a monitoring device (10) that collects the sensor data (S Ｄ ) at a sampling rate lower than that of the data collection module (7) is arranged. The system according to any one of claims 1 to 3, characterized in that.

5. For changing the first algorithm (P １ ), or for receiving program data for setting a second algorithm (P ２ ), the calculation unit (8) is connected to a database (18) via communication means (17), the system according to any one of claims 1 to 4.

6. The communication means (17) includes a VPN router. The system according to claim 4, characterized in that.

7. The calculation unit (8) is connected to a storage device (15) for storing sensor data (S Ｄ ), and / or result data (E Ｄ ). The system according to any one of claims 1 to 5, characterized in that.

8. The calculation unit (8) is connected to a computer network (13) via a modem (12) for data transmission. The system according to any one of claims 1 to 6, characterized in that.

9. The working unit (3) is provided with a tamping unit and / or a stabilizing unit. The system according to any one of claims 1 to 7, characterized in that.

10. A motion sensor for detecting the vibration period is arranged as the sensor (6). The system according to claim 8, characterized in that.

11. A method of operating the system according to any one of claims 1 to 10, comprising using the sensor (6) to generate a sensor signal (S Ｓ ) for monitoring the work unit (3), wherein the sensor signal (S Ｓ ) is supplied to the data collection module (7) for separate sensor data collection, and the first algorithm (P １ ) set in the calculation unit (8) is used to calculate result data (E Ｄ ) from the sensor data (S Ｄ ).

12. Result data (E Ｄ ), characterized by calculating characteristic values of the working process and transmitting them to the machine control unit (4), the method according to claim 11.

13. To change the first algorithm (P １ ), or to set the second algorithm (P ２ ), the method according to claim 11 or 12, characterized in that program data is transmitted to the calculation unit (8).

14. In a first step, new program data is loaded into the memory of the calculation unit (8), and in a second step, after restarting the calculation unit (8), the new program data is activated. The method according to claim 13, characterized in that.

15. Transmitting result data (E Ｄ ) from the computing unit (8) to an external computer (14) via a VPN tunnel or via an offline connection, the method according to any one of claims 11 to 14.

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