JP2005243008A - Diagnostic system, diagnostic method, tool and component - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a diagnostic system with a programmable controller (PLC) capable of preventing the influence on the performance of the PLC by giving a determination logic to a component (equipment located on the downstream of the PLC) side. <P>SOLUTION: This diagnostic system comprises the component 33 performing at least either one of transmission or reception of control data (ON/OFF, analog) with the PLC 10; and a tool device 20 directly or indirectly connected to the component. The tool has the setting function of setting a diagnostic algorithm to be executed in the component and setting a parameter based on a parameter sheet paired with the diagnostic algorithm. The component performs diagnosis according to the diagnostic algorithm and parameter set by the tool, and has the function of outputting a diagnostic result by itself in a case of matching with a reporting condition such as abnormality regulated by the parameter. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to a diagnostic system, a diagnostic method, a tool, and a component, and more specifically, to a component that transmits and receives control data (ON / OFF, analog) to and from a programmable controller. The present invention relates to a technique for making a diagnosis.

  PLC (programmable controller) used in FA (factory automation) inputs ON / OFF information of input devices such as switches and sensors, and performs logical operations according to a sequence program (user program) written in a ladder language. Execute. The PLC is controlled by outputting a signal of ON / OFF information to an output device such as a relay, a valve, or an actuator according to the obtained calculation result. The input device and the output device may be directly connected to an IO unit or the like constituting the PLC, or may be indirectly connected through various networks.

  On the other hand, in a system including this PLC, a monitor function may be incorporated in order to monitor various states. As a monitoring device for realizing this monitoring function, the CPU unit I / O memory is accessed via the communication unit or externally via the CPU unit serial communication port, and stored in the IO memory. Some of them read data or write predetermined data to the IO memory. Examples of this type of device include various monitor tools and programmable displays. Further, in the monitor tool and the programmable display device, the data stored in the IO memory is periodically collected at a predetermined timing, and the collected data is sequentially stored and stored, so that the PLC history (IO Some of them can check the history of how the data has changed. By confirming this history, it is possible to know the history of the operating state of the PLC and the control history of the controlled device.

  Furthermore, in recent systems, in addition to managing and monitoring the current control content using the monitoring function described above, it is desired to monitor and monitor non-control information such as maintenance information, system status information, and maintenance information. There is a request. In order to realize such a request, conventionally, since input data and output data exist in the memory of the PLC, a predetermined program is incorporated on the PLC side. The PLC CPU unit executes the program to obtain maintenance information based on the input / output data stored in the memory. More specifically, the operation time of the device and the time required until the I / O information becomes different may be measured.

  Furthermore, there is a remote IO system as a system including a PLC. The remote IO system includes a master unit connected to the CPU unit of the PLC and a slave connected to the master unit via a communication cable, and performs IO slave communication of IO data. Input devices and output devices are connected to the slave. The master unit receives OUT data from the CPU unit and outputs it to the slave. The slave outputs the OUT data to the output device. Further, the slave captures the state of the input device as IN data, and transmits the IN data in response to a request from the master unit. The master unit receives the IN data and sends it to the CPU unit. By doing so, control data (IO data) can be transferred between the CPU unit of the PLC and the input and output devices. Some remote IO system slaves incorporate a threshold diagnosis algorithm. This slave has a built-in timer and measures the time from when the OUT terminal connected to a preset actuator is turned on until the IN terminal connected to the sensor is turned on. Comparison is made to determine whether there is an abnormality in the actuator. Note that maintenance information such as the presence or absence of an actuator abnormality detected by the slave is transmitted to the PLC (that is, the CPU unit) by master-slave communication.

  The various techniques described above are disclosed in Patent Document 1 and the like. Further, as a data collection unit having a function of collecting apparatus movement data, there is a technique disclosed in Patent Document 2.

JP 2003-295914 A JP 2000-207318 A

  However, the conventional system described above has various problems as described below, and is not satisfactory for the user. That is, it is not preferable to acquire various types of information using a program (user program) incorporated in the PLC, because the load on the user program is applied and there is a risk of affecting the control that is the original function of the PLC. Furthermore, since a user program is usually configured in a ladder language, which is a programming language that is not good at collecting and processing information, it takes a lot of labor to create such a program.

  In addition, the function of determining the presence or absence of an abnormality on the slave side disclosed in Patent Document 1 can set a threshold or the like, but determines the presence or absence of an abnormality, and other algorithms for collecting information and processing data. They couldn't be customized or added, and could only make judgments within a limited range.

  Furthermore, the conventional apparatus disclosed in each of the above-mentioned patent documents, etc., realizes functions in a discrete manner, and the FA system that is actually operating in a series of processes that improve quality and productivity. Searching for an algorithm for information (data) to be monitored that is suitable for monitoring and collecting information and diagnosing information based on that data, such as slaves, input devices, and output devices connected to the PLC It could not be incorporated into the component side.

  This invention has a series of processes that improve the quality and productivity executed by the user as a system, so that it is not necessary to create a complicated user program created by the user, and the judgment logic is provided on the component side. It is an object of the present invention to provide a diagnostic system, a diagnostic method, a tool, and a component that do not affect the performance of the PLC.

  The diagnostic system according to the present invention includes a component that transmits and / or receives control data such as ON / OFF, analog, and the like with a programmable controller, and a tool that is directly or indirectly connected to the component. The tool has a setting function of setting a diagnostic algorithm to be executed by the component and setting a parameter based on a parameter sheet that is paired with the diagnostic algorithm. Diagnosis is performed according to the diagnosis algorithm and parameters set by the tool, and a function is provided for outputting the diagnosis result by itself when the notification conditions such as abnormality defined by the parameters are met. In the embodiment, the diagnosis algorithm corresponds to a knowledge determination algorithm.

  Here, the “component” is a device located downstream of the PLC in the network configuration, and refers to an input device, an output device, and the like, not the main body that executes the PLC control program. In the embodiment, a slave, a temperature controller, a sensor, a camera, a counter, and the like correspond to components. “Control data” is data used when the user program of the programmable controller is executed, and is data relating to control of the programmable controller. For example, IN data which is an input signal from a component having an input function, an output signal to a component having an output function, and OUT data. “ON” data and “OFF” data correspond to components of input / output devices that perform ON / OFF operations, and analog data corresponds to components that handle analog signals. Since the control data is communicated from the programmable controller side to the component side and from the component side to the programmable controller side, the control data also includes control data that is specified without distinguishing between the programmable controller and the component. In some components such as a temperature controller, there is also control data handled only on the component side, and such control data is included. In addition, as a connection form between the component and the tool, direct connection means that, for example, the tool is connected to the communication interface 33d of the component 33 in the embodiment via a communication cable or the like, or the same control system network 32 as the component 33 is used. In some cases, a component is directly connected to the component via the control system network 32. In addition, as an indirect connection, communication may be performed via the PLC 10 in the middle as in the embodiment. Of course, connection forms other than those exemplified are possible. Note that the connection to the control system network 32 may be regarded as indirect.

  Further, the “diagnostic algorithm” corresponds to a “knowledge determination algorithm” in the embodiment. In the embodiment, “diagnostic algorithm setting” means selecting a knowledge judgment algorithm (diagnostic algorithm) stored in a component or tool (if the tool is stored in the tool, download the selected algorithm) If the existing algorithm does not exist, obtain it from the outside, create a new algorithm (including the case of using some existing algorithms), or combine multiple existing algorithms Processing such as creating.

  In the embodiment, the function of outputting the diagnosis result corresponds to the function of notifying the PLC 10 of the abnormality from the component 33 side when the notification condition such as abnormality is satisfied, and the processing of ST11 and ST12 in FIG. It corresponds to the function that realizes.

  On the premise of such an invention, a data collection device that collects control data from the component is provided, and the tool acquires control data collected by the data collection device and displays data based on the acquired control data Thus, it is preferable that a diagnostic algorithm suitable for a system in which the component is incorporated can be set. Of course, it is not necessary to provide a data collection device. In the embodiment, the data collection device is a data collection unit incorporated in the programmable controller, but may be a separate device from the programmable controller, or conversely, a programmable controller such as a CPU unit is configured as an inner board or the like. It may be mounted in another unit. In short, it is only necessary to collect desired data. Further, “data based on acquired control data” displayed by the tool corresponds to “data displayed with meaning” in the embodiment. Of course, the data displayed with meanings are not limited to those exemplified in the embodiment. For example, the data about the same contact and the same location obtained by acquiring at different times, Some are displayed in association with each other so that changes over time are easy to understand.

  A series of processes for displaying quality points related to quality, productivity (improving yield), etc. related to the FA system to be monitored, and displaying diagnostic data and numerical values, and incorporating diagnostic algorithms into components By providing the user with the above, it is possible to realize an improvement in production efficiency under a large development efficiency. Here, “Quality Point” is a point as to whether it is possible to predict an abnormality of the FA system or the equipment device or an abnormality can be detected by seeing which signal of the monitoring target changes.

  More specifically, it has been found from experience that that an equipment device has a sign of an abnormal stop, and the sign has a causal relationship with changes in the operation of the equipment device over time. The operation of the equipment is related to the operation signal, and the operation signal is related to the control data of the programmable controller. Therefore, if the time-dependent change etc. of the control data of a programmable controller are monitored, the abnormality detection or abnormality prediction of an installation apparatus can be performed. The Quality Point is a monitoring target point that is the key. Specifically, it is a change point of control data of the programmable controller and a change point of IO data of the component, and is change information of one contact point in the control of the programmable controller. In the case of an analog processing component, it is an analog value, and in the case of an ON / OFF processing component, it is information on the change timing of the ON / OFF signal, is an ON time (OFF time), or is ON / OFF of multiple contacts. Various things such as the time required based on this are included.

  A tool according to the present invention suitable for realizing the above diagnostic system is a tool that communicates with a component that performs at least one of transmission and reception of control data with a programmable controller, and is executed by the component. And a function for setting parameters based on a parameter sheet paired with the diagnostic algorithm.

  Further, the component according to the present invention suitable for realizing the above-described diagnostic system is a component that performs at least one of transmission and reception of control data to and from the programmable controller, and a diagnostic algorithm set by a tool and Storage means for storing parameters corresponding thereto, a function for executing diagnosis according to the diagnosis algorithm and parameters stored in the storage means, and a diagnosis result obtained by executing the diagnosis are defined by the parameters When it meets the notification conditions such as abnormality, it has a function to output the diagnosis result by itself.

  Furthermore, in the diagnostic method according to the present invention, the parameter is set based on the setting of the diagnostic algorithm executed by the component that performs at least one of transmission and reception of control data to and from the programmable controller and the parameter sheet paired with the diagnostic algorithm. The component performs diagnosis according to the diagnostic algorithm and parameters set by the tool during system operation, and the diagnosis result obtained by the diagnosis is an abnormality defined by the parameters. When a notification condition such as the above is met, the diagnosis result is output by itself.

  And on the premise of such an invention, a data collection device for collecting control data from the component is provided, and the diagnosis algorithm and parameter setting performed by the tool are determined based on data collected by the data collection device. Good.

  Further, on the premise of each of the above methods, one or a plurality of the diagnostic algorithms and corresponding parameter sheets are stored in advance in the component, and the diagnostic algorithm setting process performed in the tool is stored in the component. It is preferable to include a process for setting the predetermined diagnosis algorithm to be executable.

  In addition, a plurality of sets of the diagnostic algorithm and corresponding parameter sheets are stored in the database of the tool, and the diagnostic algorithm setting process executed by the component in the tool is accessed and stored in the database. It is also possible to include a process of selecting a desired one from the plurality of diagnosed algorithms and then sending the selected diagnostic algorithm to the component.

  The tool acquires a pair of a diagnosis algorithm and a parameter sheet from the outside via a network such as the Internet, arbitrarily sets a parameter for the acquired parameter sheet, and then the diagnosis algorithm acquired from the outside A process of sending a pair of parameter sheets in which parameters are set to the component may be performed.

  On the other hand, various methods can be adopted as a diagnostic algorithm setting method in the above-described diagnostic system. As an example, one or a plurality of the diagnostic algorithms and corresponding parameter sheets are stored in advance in the component, and the setting of the diagnostic algorithm executed by the component in the tool is a predetermined stored in the component. The diagnostic algorithm can be set to be executable.

  Further, a plurality of sets of the diagnostic algorithms and corresponding parameter sheets are stored in the database of the tool, and settings of diagnostic algorithms to be executed by the components in the tool are stored in the plurality of diagnostic algorithms stored in the database. It is also possible to select a desired one from among them and send it to the component.

  Further, the tool has a function of acquiring a pair of a diagnosis algorithm and a parameter sheet from the outside via a network such as the Internet, and arbitrarily sets parameters for the acquired parameter sheet, and then performs the diagnosis. It is also possible to send a pair of parameter sheets in which an algorithm and parameters are set to the component.

  Furthermore, the tool can create a new diagnostic algorithm based on an existing diagnostic algorithm, and send the created new diagnostic algorithm to the component. Here, for creating a new diagnostic algorithm based on an existing diagnostic algorithm, for example, when a part of one diagnostic algorithm is modified or a new one is created by processing such as addition / deletion There are various types, for example, when a new diagnostic algorithm is created by combining a plurality of existing diagnostic algorithms.

  The tool sets a diagnostic algorithm and parameters (parameter sheet) for the component, and the component performs an operation for performing normal control and executes diagnosis according to the set diagnostic algorithm parameter. When the diagnosis result matches a notification condition such as abnormality, the component side notifies the diagnosis result. In this way, since the diagnosis is performed on the component side, the user program of the programmable controller is not loaded, and the user program can be operated for the original control. Furthermore, since the diagnosis result is notified from the component side, the programmable controller does not need to make an inquiry about the diagnosis result to the component. Not only that, the load is reduced, but if the condition is met, it can be reduced as much as possible. It becomes possible to notify early. Further, since the diagnostic algorithm to be executed is set by the tool, an appropriate diagnosis can be performed by setting a diagnostic algorithm according to the situation.

  According to the present invention, diagnosis can be performed efficiently while reducing the load on the programmable controller as much as possible.

  FIG. 1 shows an example of a network system to which the present invention is applied. As shown in FIG. 1, a PLC 10 that controls a production line, a tool device 20, and a display (programmable display: PT) 30 are connected via an information network 31 such as Ethernet (registered trademark). Yes. Various components 33 are also connected to the PLC 10.

  The tool device 20 is realized by being installed in a personal computer. Specific functions of the tool device 20 include downloading a user program to the PLC 10, setting various parameters and other information, and setting various parameters and other information to the component 33. In addition to a normal tool function described above, the information collected by a data collection unit (in this embodiment, one unit constituting the PLC 10) described later is given meaning, that is, in the state change and the repetition cycle of the change. It has a function of processing information so that changes over time can be seen and displaying it on the display screen 20a, and a function of generating information about the knowledge judgment algorithm and downloading it to the component 33.

  Here, the knowledge judgment algorithm is a management diagnosis algorithm that performs the presence / absence or prediction of abnormality / failure, and operates in combination with a parameter sheet that describes parameters necessary for executing the algorithm (program). The parameter sheet is configured in the form of an electronic file by electronically describing parameters. As will be described later, in the present embodiment, a plurality of knowledge judgment algorithms for various diagnoses and a parameter sheet related to the knowledge judgment algorithm are prepared in the tool device 20, and an algorithm suitable for each component is prepared. The selected parameter sheet is set with specific parameters and downloaded to the component 33.

  The component 33 performs at least one of transmission and reception of control data (ON / OFF data / analog data) with the PLC 10, and an input component, an output component, and an input / output component having both functions are provided. is there. The input component captures a signal from the connected input device and outputs control data to the PLC 10, and the output component receives control data from the PLC 10 and outputs the control data to the connected output device. . The input / output component is connected to an input device and an output device, and transmits and receives control data to and from the PLC 10. The device itself may be integrated with a component function.

  In relation to the present invention, the knowledge judgment algorithm downloaded from the tool device 20 is executed in parallel with the original function (communication of the above control data, etc.) of the component 33 itself, and notification conditions such as abnormality are set. When it is satisfied, it has a function of notifying the PLC 10 of an abnormality from the component 33 side.

  The PLC 10 is composed of a plurality of units. In the example shown in the figure, a CPU unit 11 that executes a user program, cyclically executes I / O refresh and peripheral processing, a communication unit 12 that communicates with other nodes, a device net (registered trademark), and the like. A master unit 13 for communicating data with various input components 33 connected via the control system network 32 and a data collecting unit 15 for collecting data. As other units, a power supply unit that supplies power to each unit constituting the PLC, a master unit for performing master-slave communication, an output unit for connecting output devices, an input unit for connecting input devices, etc. The number of units to be connected is increased or decreased as necessary.

  Each unit is composed of a box and is electrically and mechanically connected via a connector formed on the side surface, or the back of each unit is attached to a connecting unit (board) and the connecting unit ( There is also a backplane connection that connects the units via a base unit or a backplane board). Each unit is bus-connected by a PLC bus built in the connecting unit, and data can be transmitted and received directly between the units and / or indirectly through the CPU unit.

  The CPU unit 11 cyclically executes user program operations, I / O refresh, peripheral processing, etc., and the data in the IO memory (input / output device ON / OFF data and analog data detected by the measuring instrument) Etc.) are updated sequentially.

  The data collection unit 15 reads the data stored in the IO memory of the CPU unit 11, that is, the control data of each component 33 via the PLC bus, collects the data periodically (every PLC cycle time), and collects the collected data. Has a function of storing and storing the information and transmitting it to other devices. In the present embodiment, the data collection period is matched to the cycle time in the CPU unit 11. As a result, data is collected (sampled) at each cycle time, and predetermined processing is performed.

  In order to be able to perform this processing, the data collection unit 15 collects (samples) all IO data every cycle time of the PLC. More specifically, the data collection unit 15 includes a PLC bus driver and is connected to the PLC bus. The data collection unit 15 can acquire all the data stored in the IO memory of the CPU unit 11 by bus cyclic communication. The bus cyclic communication is uniquely controlled in the data collection unit 15 and is a data communication process performed by the data collection unit 15 with the CPU unit 11 via the PLC bus. The processing in the unit 11 is performed during the peripheral processing in the cyclic processing. The data collection unit 15 itself issues a data access request to the IO memory of the CPU unit 11 via the PLC bus using this bus cyclic communication, and the CPU unit 11 reacts to the request in the peripheral processing. A response including data in the IO memory is returned to the data collection unit 15. The data collection unit 15 performs real-time processing and time sharing processing within one cycle of the cycle time. The real-time process is a process in which the data collection unit 15 collects all the IO data of the CPU unit, and the time share process is a process in which all the collected data can be written in the recording memory. When the CPU unit 11 enters the cyclic processing peripheral processing period, the CPU unit 11 returns IO data in a predetermined area of the IO memory as a response to the data collection unit 15 based on a data request from the data collection unit 15. . The data collection unit 15 stores all IO data obtained from the CPU unit 11 in a buffer (not shown) as temporary recording information. By repeating such processing, the data collection unit 15 can collect (sample) all IO data every cycle time. Note that this is a function that the data collection unit 15 has as a premise. In practice, all IO data is sampled once, the sampling result is compared with a predetermined collection condition, and only necessary information ( Some IO data) is recorded.

  For example, as shown in FIG. 2, considering the control in which the cylinder rod 40a of the air cylinder 40 opens the valve 41 from the standby state shown in the figure and the air pressure is applied and the cylinder rod 40a moves forward to the operating end. The timing is as shown in FIG. That is, when the activation signal is turned ON, the valve is opened in response to this and the state is maintained. When the cylinder rod 40a moves forward and the tip of the cylinder rod 40a reaches the operating end, the sensor installed near the operating end detects the tip of the cylinder rod 40a, so that the operating end signal (sensor output) is turned on. . If the air pressure is the same pressure A and the air cylinder is in the same state, the time T from when the start signal is turned on to when the operation end signal is turned on should have the same value. In other words, if the calculated time T is longer than that in the normal state, it can be estimated that there is a possibility that problems such as catching in the air cylinder 40, running out of oil, and air leakage may occur.

  Therefore, when the air pressure (analog data) detected by the pressure sensor that detects the air pressure is the desired value A, the start signal and the ON / OFF data of the operation end signal are collected, and the time is based on the collected two data. A knowledge determination algorithm can be used in which an abnormality is determined when T is greater than or equal to a predetermined value.

  By the way, in the actual FA system, the operating time T varies within a certain range even in a normal state. Therefore, it is necessary to display the data collected by the data collection unit 15 on the tool device 20, specify the normal range, and determine a threshold value as a reference for notification.

  Therefore, in the present embodiment, the collected control data of the component 33 is given meaning and displayed so that it can be seen how the change of the FA system operation changes with time. The function to display with meaning is to monitor and monitor the operation pattern every time when the same operation is repeated, and display it so that you can see how the operation changes over time. means. As an example, as shown in FIG. 4, it is displayed in a state where time charts for each recorded operation are overlapped, that is, in a state where they are overlapped on the basis of the first rising timing. The horizontal axis represents time change, and the vertical axis represents operation change (on at rising / off at falling). From this, it can be seen that the operation change timings of the solid line operation and the two-dot chain line operation are shifted. Thereby, a change point and deviation can be easily found. In addition, as shown in FIG. 5, a plurality of pieces of data of the same contact can be displayed in a state where the first rising timings on the horizontal axis which is a time axis are aligned and shifted vertically. In this way, it can be easily understood whether or not there is a shift in operation over time. For example, in the display form shown in FIG. 4, by detecting a contact or the like having a deviation and making the display form shown in FIG. It is possible to easily and quickly determine whether or not there is a deviation at the point of time. Moreover, the range of deviation in the normal state can be easily recognized.

  When a problem occurs in a part of a certain device as described above, the control data of the component 33 is collected and accumulated for information regarding the operation and the behavior of the device, and the result is obtained from a time chart or distribution diagram. By narrowing down the items to be identified and repeating the collection and accumulation of information to find out the cause as a result of the narrowing down, the cause of the abnormality can be identified.

  As described above, the function of displaying the collected data with meaning can be realized by being incorporated in the tool device 20, for example. In this way, the user collects and stores the control data of the component 33 related to quality and production in the data collection unit by placing the data collection unit 15 in the system, and the collected control data is displayed with meaning. Using a tool that has a function to perform quality and production quality points (such as control data for the component 33 that is necessary and suitable for determining the presence or absence of abnormalities), the user can easily determine the parameters of the knowledge determination algorithm Can be set. QualityPoint is information necessary to determine whether or not the change in the operation of the FA system over time is abnormal, and is information related to the control data of the component 33 corresponding to the operation. Specifically, it is information regarding whether or not a change in which signal of which component can be monitored to predict an abnormality related to a deviation in the operation of the FA system.

  Next, a specific configuration / function of each device for realizing the above processing will be described. FIG. 6 shows the internal structure of the tool device 20. The tool device 20 stores a processor (MPU) 21 that controls the entire tool, a communication interface 22 for communicating with the PLC 10, the component 33, the data collection unit 15, and the like, and data received from the data collection unit 15. A memory 23, a database 24, an input unit 25, and a display unit 26.

  The database 24 stores and holds a plurality of types of knowledge judgment algorithms and corresponding parameter sheets. Furthermore, a parameter sheet corresponding to the newly created / acquired knowledge judgment algorithm can be added and stored. Further, as shown in FIG. 7, the knowledge determination algorithm is divided into four groups such as a time measurement system, a count system, a quantity measurement system, and a logical system.

  The input unit 25 is a keyboard or a pointing device such as a mouse. The display unit 26 is a display. A meaning of the data acquired from the data collection unit 15, a knowledge judgment algorithm setting screen, a parameter sheet setting screen, and the like are displayed.

  FIG. 8 is a diagram showing an internal configuration of the component 33. As shown in FIG. 8, a processor 33a, a memory 33b, an IO terminal 33c, and a communication interface 33d are provided. The processor 33a executes the original function of the component 33 and the knowledge determination algorithm. For example, when the component 33 is a slave, an input device or an output device is connected to the IO terminal 33c, and is connected to the master unit via a communication cable via the I / F 33d. The processor 33a has a function of capturing an IN signal from an input device connected to an IO terminal, a master slave communication function with a master unit (a function of transmitting an IN signal to the master unit, a function of receiving an OUT signal from the master unit), It has a function of outputting a signal to an output device in accordance with an OUT signal from the master unit and a function of executing a knowledge judgment algorithm.

  When the component 33 is a temperature controller, a thermistor for measuring temperature, a heating device such as a heater for controlling temperature, a cooling device, etc. are connected to the IO terminal 33c, and a master is connected via the I / F 33d. Connect the unit with a communication cable. The processor 33a measures the current temperature of the temperature control object with a thermistor, and controls the temperature control object to have a predetermined target temperature value. At the time of heating control, control is performed so that a current flows through the heater. The processor 33a has a function of communicating information related to temperature control and parameter information for performing temperature control with the master unit, a function of executing a knowledge determination algorithm, and the like.

  When the component 33 is a camera, a lighting device may be connected to the IO terminal 33c, or there may be no IO terminal 33c equivalent. The processor 33a has control of camera shutter speed, zoom control, capture control, control of capturing image data, a function of transmitting image data to a master or PLC, a function of executing a knowledge determination algorithm, and the like.

  When the component 33 is a counter, a counting target is connected to the IO terminal 33c, and a counting target signal or a reset signal is input. The processor 33a has a function of performing count increment processing, reset processing, etc., communicating signals related to count control between masters, and executing a knowledge determination algorithm.

  The memory 33b stores system programs and IO data for operating various components 33 themselves. Further, a knowledge judgment algorithm and a parameter sheet (parameter values already entered) downloaded from the tool device 20 are also stored.

  When the component 33 is a photoelectric sensor, a light projecting element or a light receiving element is provided instead of the IO terminal. The processor 33a performs light projection control, light reception signal processing, sensing processing related to the presence or absence of an object, and the like, and also has a function of transmitting a sensing signal to a master and a function of executing a knowledge determination algorithm.

  The communication interface 33d is connected to the control network 32 and transmits or receives control data to / from the PLC 10 via the control network 32. Furthermore, this communication interface 33d is also used when outputting the execution result of the knowledge judgment algorithm. Further, although not specifically shown, the tool device 20 can be directly connected to the communication interface 33d, and various settings such as knowledge judgment algorithm and parameter sheet download can be performed.

  FIG. 9 shows the selection of a knowledge judgment algorithm suitable for the system based on the collected data. After setting necessary information (parameters), the knowledge judgment algorithm is downloaded to the component 33 and the downloaded component receives the knowledge judgment algorithm. An overall execution flowchart of execution is shown. The functions of each device will be further described while explaining this flowchart.

  First, the data collection unit 15 collects production / quality information being used (ST1). The collected data is sent to the tool device 20, where the data is given meaning and displayed (ST2). That is, for example, as shown in FIGS. 3 and 4, the tool device 20 processes the same data into a state in which the fluctuation / shift is easily understood and displays the same data on the display screen 20 a of the tool device 20. . Based on the meaningful data displayed on the display screen 20a, the quality point (quality point) related to the product / quality, that is, which signal change is likely to predict the abnormality of the equipment / device It is determined whether or not a point has been found (ST3). This determination is made by the user who sees the meaningful data. The tool device 20 determines whether or not it has been found based on the input from the user given through the input unit 25.

  While changing the type of the displayed data or referring to data collected at different times, ST1 to ST3 are repeatedly executed until a Quality Point is found. This is preprocessing.

  If the Quality Point can be found, the tool device 20 shifts to the knowledge determination algorithm setting mode (ST4). Specifically, a list of knowledge judgment algorithms stored in the database 24, that is, an algorithm selection screen is displayed. Then, a knowledge judgment algorithm related to Quality Point is selected from the knowledge judgment algorithms displayed on the selection screen (ST5, 6).

  That is, in this embodiment, since four types of algorithms of a time measurement system, a count system, a quantity measurement system, and a logic system are prepared, the user can operate the mouse or the like to display the algorithm on the display screen. One of the four types is selected (ST5), and then the tool device 20 displays a list of algorithms belonging to the selected type on the display screen, and selects an algorithm to be actually used (STEP). ST6).

  Next, a parameter sheet corresponding to the selected knowledge determination algorithm is read from the database 24 and displayed on the display screen 20a, and a specific parameter value which is blank is set (ST7). Based on this parameter setting screen, the input unit 25 is operated to input parameters (data to be monitored, threshold value serving as a reference for notifying abnormality / failure prediction, communication destination information about the communication destination, etc.).

  As a result, the knowledge judgment algorithm and parameters to be used are determined, so the tool device 20 compiles into an execution object executable by the target component 33 (ST8), and the compiled knowledge judgment algorithm (with parameter sheet) Is downloaded to the target component (ST9). The processing from ST4 to ST9 is a processing function executed by the tool device 20.

  Upon obtaining the downloaded knowledge determination algorithm, the component 33 executes the algorithm based on the parameter information of the parameter sheet, and diagnoses the input information of the monitoring target data (ST10). Then, the diagnosis result is compared with the corresponding reference threshold value to determine whether or not there is an abnormality (ST11). If there is no abnormality, a diagnosis based on the next input information is performed. When it is detected that the reference threshold for abnormality notification has been exceeded, the component 33 voluntarily outputs an abnormality (including failure prediction) or when it has been detected that the reference threshold for failure prediction has been exceeded. The component 33 voluntarily outputs a failure prediction (ST12). In other words, a component such as a slave usually receives an instruction from the master unit and notifies an abnormality as a response to the instruction.In this embodiment, even if it is a slave, if the condition is met, the master's The notification is made from the component 33 side without receiving an instruction. These ST10 to ST12 are processing functions executed by the component 33.

  The component 33 notifies itself without receiving a request from the master, but in order to realize such processing, the component 33 knows the destination information (address, etc.) about the notification destination (the tool device 20 or the display device 30). It is stored and held in the parameter sheet of the algorithm, and when an abnormality is notified, an abnormality notification is output to a predetermined notification destination according to the destination information.

  Since this abnormality notification is sent to the tool device 20 or the display 30 via the PLC 10, the tool device 20 or the like that has acquired the abnormality notification displays the abnormality and notifies the user (ST13).

  FIG. 10 is a flowchart of functions focusing on the component 33. First, it is determined whether an algorithm change request has been received (ST21). If there is a change request, the knowledge determination algorithm and parameter sheet sent from the tool device 20 are stored in the memory 33b, and a new knowledge determination algorithm is activated (ST22).

  After this activation or when there is no change request, communication processing with the outside is performed (ST23). That is, communication with the host is performed via the communication interface 33d. Next, input processing is performed via the I / O terminal 33c (ST24). Here, processing for taking in signals from input devices such as switches and sensors connected to the component 33 is performed.

  Then, after performing the original control process for the component 33 (ST25), a knowledge determination algorithm is executed (ST26), and it is determined whether or not the calculated value exceeds the threshold value (ST27). If the determination result does not exceed the threshold value, the output process to the device connected via the I / O terminal 33c is performed as it is (ST29). If the threshold value is exceeded, the algorithm result is output. That is, an abnormality (failure prediction) notification is performed (ST28). These processes are executed by the processor 33a of the component 33.

  Next, a specific example of the knowledge determination algorithm will be described. For example, in the case of “stopping the apparatus and preventing deterioration of machining quality due to the substrate (work) feed rampage”, prevention / diagnosis can be performed by a knowledge judgment algorithm of a count system. That is, for example, the conveyance surface of the conveyance conveyor that conveys the workpiece is flat, and it is normal to convey the workpiece while maintaining the horizontal posture. In this normal state, the workpiece is also conveyed without vibrating up and down. Therefore, by detecting the bouncing (fine vibration, vertical fluctuation) of the workpiece sent by the transfer conveyor with the displacement sensor, fatigue of the mechanical part in the transfer conveyor and “distortion” of the workpiece feed, that is, placing the workpiece Check whether the secular change related to misalignment and deterioration / deterioration of machining quality in workpiece machining equipment is progressing. Then, by carrying out appropriate maintenance based on the notification of the check result, the apparatus is stopped and the processing quality is prevented from being deteriorated.

  Looking at the actual operation state of the conveyor at the actual site, a slight vibration is generated even in a normal state, so that the surface position of the workpiece detected by the displacement sensor is also displaced vertically. Therefore, for example, as shown in FIG. 11, the number of peaks where the measured value of the displacement sensor exceeds a certain value (for example, “5000”) within a certain time T (for example, “100 ms”) is counted. Monitoring can be performed by a knowledge determination algorithm that notifies when a set value (for example, “5 times”) is exceeded.

  Each value in the algorithm is set as a parameter. Specifically, the parameter sheet shown in FIG. 12 is used, and each column (monitored IO data identification information, monitoring start condition: threshold, monitoring end condition: fixed time T, abnormality determination condition: It is set by inputting a specific numerical value (setting of parameter) to (setting value related to counting).

  The knowledge judgment algorithm paired with this parameter sheet starts timing when the monitoring start condition (in this case, the data exceeds the threshold value 5000) is satisfied, and until the monitoring end condition (in this case, 100 ms has elapsed). In this case, it is determined whether or not the abnormality determination condition (in this case, the threshold value: the number of times of peaking exceeding 5000 is 5) is satisfied. It should be noted that the timing for outputting the abnormality notification may be the moment when it reaches 5 times or after the end of the fixed time T.

  In addition, as another knowledge judgment algorithm, there are provided an upper threshold value 5500 and a lower threshold value 4000, the number of times that the lower threshold value is exceeded and the upper threshold value is exceeded, and the upper threshold value. An alarm (abnormality notification) may be made when the total number of times exceeding the lower threshold value across the number exceeds a certain number.

  Further, as a knowledge judgment algorithm for a quantity system, for example, a maximum value of a numerical difference between extreme points (slope = 0) of fluctuations within a time T is obtained, and an alarm is issued if the obtained difference is equal to or greater than a certain value. is there. Similarly to setting the count type parameter sheet on the tool device 20 side, the parameter type knowledge determination algorithm parameter sheet includes the IO data identification information to be monitored, the monitoring start condition, the monitoring end condition: a fixed time T, Abnormality determination condition: A specific numerical value is set as a setting value relating to the calculated result amount = the difference between the maximum values of the numerical differences of the extreme points of fluctuation within the time T. Also set communication destination information to notify abnormalities or failure prediction.

  Further, as a knowledge determination algorithm of the time measurement system, for example, as shown in FIG. 13, a solenoid (valve) by a deviation of time t from the valve opening (solenoid ON) to the movement toward the reverse end (reverse end SW ON) is started. ) To predict failure. The parameter sheet in this case is as shown in FIG. That is, using this parameter sheet, monitoring target IO data identification information, monitoring start condition (in this case, solenoid ON), monitoring end condition (in this case, reverse SW is ON), abnormality determination condition (in this case, 50 ms) Set. Furthermore, communication destination information for notifying abnormality or failure prediction is also set. As a result, the knowledge determination algorithm outputs an abnormal output A when the condition is satisfied.

  In addition, as an example of a logic knowledge judgment algorithm, a logical operation is performed on a plurality of input signals to obtain a logical sum of them to determine abnormality or failure prediction, or in what order the plurality of input signals rise It is conceivable to determine abnormality or failure prediction by determining whether the combination of the input signal and the output signal changes, or to determine abnormality or failure prediction. In addition, a logical operation is performed on the combination of the count system result and the volume system result, or a malfunction or failure prediction is determined by performing a logical operation on a combination of the time measurement system result and the volume system result. Can be considered.

  In the above-described embodiment, the knowledge determination algorithm and the parameter sheet are stored in the database 24 of the tool device 20 in advance. However, the present invention is not limited to this. For example, the user can program the tool device 20 with the tool device 20. A new knowledge determination algorithm may be generated and downloaded to the component 33. The new knowledge determination algorithm includes both a case where it is created based on an existing knowledge determination algorithm and a case where it is newly created. In other words, when creating an algorithm related to quality points and thresholds, a new knowledge judgment algorithm can be created by cascading existing knowledge judgment algorithms when a single algorithm is not sufficient, but can be realized by a combination of built-in algorithms. It will be. The new knowledge determination algorithm created in this way is registered in the database 24 as a new algorithm and used thereafter. On the other hand, if it cannot be realized by the built-in knowledge determination algorithm, a new knowledge determination algorithm is created using various programming languages and registered in the database 24.

  In addition, the knowledge determination algorithm that can be used in the component 33 and the parameter sheet corresponding to the component 33 are stored and held in the component 33, and the tool device 20 can actually use the component 33 from a plurality of knowledge determination algorithms prepared in advance. The knowledge determination algorithm to be used is selected, the selected knowledge determination algorithm is notified to the component, the parameter sheet is read, and a necessary value is set. As a result, the component 33 subsequently executes the designated knowledge determination algorithm.

  As described above, the function of the tool device 20 in the case of using the knowledge determination algorithm prepared on the component 33 side and the parameter sheet corresponding thereto, implements the flowchart shown in FIG. This flowchart 15 is equivalent to a flowchart obtained by replacing ST4 to ST9 in the flowchart shown in FIG.

  The processing steps from ST1 to ST3 are the same as those shown in FIG. If the Quality Point can be found, the target component 33 is accessed and the knowledge judgment algorithm stored therein is referred to (ST30). That is, a list of knowledge judgment algorithms stored in the component is displayed on the display screen 20a as a selection screen. The user selects an appropriate knowledge determination algorithm related to Quality Point from a plurality of knowledge determination algorithms displayed on the selection screen (ST31). In response to this selection, the tool device 20 sets the selected knowledge determination algorithm to be activated by the component (ST32), and further stores a parameter sheet (template is stored in the component 33) related to the selected knowledge determination algorithm. The necessary parameters are set (ST33). Then, the setting contents are downloaded from the tool device 20 to the target component 33 (ST34).

  Thereafter, the target component 33 executes a knowledge determination algorithm selected according to the parameters (ST10), and when the component 33 detects an abnormality, the component 33 outputs an abnormality notification (ST11, ST12). Then, the tool device 20 or the display device 30 that has received the abnormality notification issues a predetermined alarm based on the acquired abnormality notification and notifies the user (ST13).

  As another method for obtaining the knowledge judgment algorithm, a knowledge judgment algorithm (with a parameter sheet) stored in an external server or the like is obtained via the Internet or the like, and setting for the component 33 is performed based on the obtained knowledge judgment algorithm. Can also be performed.

  A specific function of the tool for performing such processing is to add a function for executing the flowchart shown in FIG. The flowchart of FIG. 16 is inserted between ST4 and ST5 in the flowchart shown in FIG.

  In other words, when the mode shifts to the mode for setting the knowledge determination algorithm in ST4, it is determined whether or not there is an appropriate knowledge determination algorithm related to the Quality Point in the database 24 (ST40). Access to an external server (ST41). Then, the knowledge determination algorithm stored in the server is searched (ST42). This search process is repeated until an appropriate knowledge determination algorithm has been extracted (Yes in the branch determination in ST43) or until the user gives up searching and ends (Yes in the branch determination in ST44).

  If an appropriate knowledge determination algorithm can be extracted, the extracted knowledge determination algorithm is downloaded together with the corresponding parameter sheet (ST45) and stored in its own database 24 (ST46). Thereafter, the process returns to ST5 in FIG. 9, and thereafter, predetermined processing is executed.

It is a figure which shows an example of a system. It is a figure explaining the operation | movement principle of suitable one Embodiment of a data collection unit. It is a figure explaining the operation | movement principle of suitable one Embodiment of a data collection unit. It is a figure which shows an example of the meaningful data which a tool apparatus displays. It is a figure which shows an example of the meaningful data which a tool apparatus displays. It is a figure which shows an example of the internal structure of a tool apparatus. It is a figure which shows an example of the data structure of a database. It is a figure which shows an example of the internal structure of a component. It is a flowchart explaining the function and effect | action of the whole system. It is a flowchart which shows the function of a component. It is a figure which shows an example of a knowledge judgment algorithm. It is a figure which shows an example of a parameter sheet. It is a figure which shows an example of a knowledge judgment algorithm. It is a figure which shows an example of a parameter sheet. It is a flowchart explaining the function and effect | action of the whole system. It is a flowchart which shows an example of the function of a tool apparatus.

Explanation of symbols

10 PLC
11 CPU unit 12 Communication unit 13 Master unit 15 Data collection unit 20 Tool device 20a Display screen 21 Processor 22 Communication interface 23 Memory 24 Database 25 Input unit 26 Display unit 30 Display 31 Network 32 Control system network 33 Component 33a Processor 33b Memory 33c I / O terminal 33d Communication interface

Claims (13)

A component that performs at least one of transmission and reception of control data to and from the programmable controller;
A diagnostic system comprising a tool connected directly or indirectly to the component;
The tool has a setting function for setting a parameter based on the setting of a diagnostic algorithm to be executed by the component and a parameter sheet paired with the diagnostic algorithm,
The component has a function of performing diagnosis according to a diagnosis algorithm and parameters set by the tool and outputting a diagnosis result by itself when it meets a notification condition such as abnormality defined by the parameters. Diagnostic system featuring. A data collection device for collecting control data from the component;
The tool obtains control data collected by the data collection device and displays data based on the obtained control data, thereby enabling setting of a diagnostic algorithm suitable for a system in which the component is incorporated. The diagnostic system according to claim 1. A tool for communicating with a component that performs at least one of transmission and reception of control data with a programmable controller,
A function for setting a diagnostic algorithm to be executed by the component;
A tool comprising a function for setting parameters based on a parameter sheet paired with the diagnostic algorithm. A component that performs at least one of transmission and reception of control data with a programmable controller,
Storage means for storing the diagnostic algorithm set by the tool and the corresponding parameter;
A function of executing diagnosis according to the diagnosis algorithm and parameters stored in the storage means;
A component having a function of outputting a diagnostic result by itself when a diagnostic result obtained by executing the diagnosis matches a notification condition such as abnormality defined by the parameter. The tool sets the parameters based on the parameter sheet that is paired with the diagnostic algorithm and the diagnostic algorithm that is executed by the component that transmits and receives control data to and from the programmable controller.
The component performs diagnosis according to the diagnosis algorithm and parameters set by the tool during system operation,
A diagnostic method comprising: outputting a diagnostic result by itself when a diagnostic result obtained by the diagnosis matches a notification condition such as abnormality defined by the parameter. A data collection device for collecting control data from the component;
6. The diagnosis method according to claim 5, wherein the diagnosis algorithm and parameter setting performed by the tool are determined based on data collected by the data collection device. One or more of the diagnostic algorithms and corresponding parameter sheets are stored in advance in the component,
The diagnosis system according to claim 1 or 2, wherein the setting of the diagnostic algorithm to be executed by the component in the tool is set so that a predetermined diagnostic algorithm stored in the component can be executed. A plurality of sets of the diagnostic algorithm and the corresponding parameter sheets are stored and held in the tool database,
The diagnostic algorithm to be executed by the component in the tool is to select a desired one from a plurality of diagnostic algorithms stored in the database and send it to the component. The diagnostic system according to 1 or 2. The tool has a function of acquiring a pair of a diagnostic algorithm and a parameter sheet from the outside via a network such as the Internet,
9. The parameter sheet is arbitrarily set for the acquired parameter sheet, and then a pair of the parameter sheet in which the diagnosis algorithm and the parameter are set is sent to the component. The diagnostic system according to any one of the above.   10. The tool according to claim 1, wherein the tool creates a new diagnostic algorithm based on an existing diagnostic algorithm and sends the created new diagnostic algorithm to the component. The diagnostic system of Claim 1. One or more of the diagnostic algorithms and corresponding parameter sheets are stored in advance in the component,
7. The diagnostic method according to claim 5, wherein the diagnostic algorithm setting process performed in the tool includes a process of setting a predetermined diagnostic algorithm stored in the component to be executable. A plurality of sets of the diagnostic algorithm and the corresponding parameter sheets are stored and held in the tool database,
The diagnostic algorithm setting process executed by the component in the tool accesses the database, selects a desired one from a plurality of diagnostic algorithms stored therein, and then selects the selected diagnostic algorithm. The diagnostic method according to claim 5, further comprising a process of sending to the component. The tool acquires a pair of a diagnostic algorithm and a parameter sheet from the outside via a network such as the Internet,
Set the parameters arbitrarily for the acquired parameter sheet,
13. The diagnosis method according to claim 5, further comprising a process of sending a pair of the parameter sheet set with the diagnosis algorithm and parameters acquired from the outside to the component. 13.

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