Anomaly prediction device, transmission device, and anomaly prediction method

Abstract

To predict gear abnormalities more appropriately.SOLUTION: An abnormality detector of the present disclosure includes a drive unit; a gear connected to the drive unit; and a detection unit that detects a position of a medium in response to a drive of the gear, and is used for transmitting the medium that intermittently transmits media. This abnormality predictor acquires detection information regarding an amount of medium to be transmitted based on a position of the medium detected over time by the detection unit, and decomposes acquired detection information into a trend component related to a moving average of the gear, a periodic component based on a gear cycle, and a random component obtained by excluding the trend component and the periodic component, and obtains a degree of abnormality of the gear based on the periodic component obtained by decomposition, and outputs the obtained degree of abnormality.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] This specification discloses an anomaly prediction device, a sending device, and an anomaly prediction method. [Background technology]

[0002] Conventionally, a feeding device has been a tape feeder that intermittently feeds a tape on which components are arranged. As a device related to this tape feeder, for example, an imaging unit that captures an image of a component removal section of the tape feeder and a characteristic inspection device that measures the tape feed position based on the image data and evaluates the characteristics of the tape feeder by ranking based on the measurement results have been proposed (see, for example, Patent Document 1, etc.). This device is said to enable more rational use of the feeder by detecting the characteristics (individual differences). As such a feeding device, a device has been proposed that performs various feeder diagnoses while applying a torque load by sliding a brake pad against the rotor of the tape feeding mechanism, thereby performing feeder diagnosis under the same or similar conditions as when the tape is not attached to the tape feeder (see, for example, Patent Document 2, etc.). This device is said to be able to perform tape feeder diagnosis well and with high reliability. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2009-123895 A [Patent Document 2] JP 2009-302475 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the above-mentioned Patent Document 1, the characteristics (individual differences) of the feeder are simply detected, and the detection and prediction of abnormalities are not performed. Also, in Patent Document 2, although a diagnosis similar to that when using tape can be performed without using tape, it is difficult to detect and predict abnormalities when actually using tape.

[0005] The present disclosure has been made in consideration of such problems, and has as its main object to provide an abnormality prediction device, a sending device, and an abnormality prediction method that can more appropriately predict gear abnormalities. [Means for solving the problem]

[0006] In this disclosure, the following means are taken to achieve the above-mentioned main object.

[0007] The abnormality prediction device of the present disclosure is 1. An abnormality prediction device for use in a medium delivery device that includes a drive unit, a gear connected to the drive unit, and a detection unit that detects a position of a medium delivered in response to driving of the gear, the abnormality prediction device comprising: a control unit that acquires detection information relating to the amount of the medium fed out based on the position of the medium detected over time by the detection unit, decomposes the acquired detection information into a trend component relating to a moving average of the gear, a periodic component based on the cycle of the gear, and a random component obtained by excluding the trend component and the periodic component, determines a degree of abnormality of the gear based on the periodic component obtained by the decomposition, and outputs the determined degree of abnormality; It is equipped with the following:

[0008] In this abnormality prediction device, detection information on the amount of medium sent based on the position of the medium detected over time is decomposed into a trend component related to the moving average of the gear, a periodic component based on the gear period, and a random component obtained by excluding the trend component and the periodic component. Then, this abnormality prediction device calculates the degree of abnormality of the gear based on the periodic component obtained by the decomposition, and outputs the calculated degree of abnormality. The periodic component obtained by decomposing the detection information is a component that is strongly influenced by, for example, deterioration and wear of the gear, so that the gear abnormality can be more appropriately predicted. Here, the "medium" refers to something sent out by the sending device, and for example, in a printing device, a printing medium such as paper is included, and in a mounting device, a tape material that supplies components is included. In addition, the "gear abnormality" includes not only deterioration and wear of the gear, but also breakage and misalignment of the rotation axis.

[0009] In the abnormality prediction device of the present disclosure, the control unit may obtain a difference value between a maximum value and a minimum value of the periodic component for each predetermined period as the abnormality degree. Since the value of the periodic component changes depending on the rotation period of the gear, the abnormality prediction device can more appropriately predict the gear abnormality by using the difference value of the periodic component.

[0010] In the abnormality prediction device disclosed herein, the control unit may acquire the detection information in which one or more of the position of the medium detected by the detection unit, the actual measurement value of the feed amount calculated based on the position of the medium, and the error between the actual measurement value and the feed amount per step of intermittently feeding the medium are associated with the time at which the position of the medium is detected. This abnormality prediction device can resolve periodic components using the position of the medium, the actual measurement value of the feed amount, the error in the feed amount, etc.

[0011] In the anomaly prediction device of the present disclosure, the control unit may determine the degree of accidental anomaly of the gear based on the time-dependent change of the trend component obtained by decomposition. This anomaly prediction device can more appropriately predict anomalies related to the gear by using components other than the periodic component.

[0012] In the anomaly prediction device disclosed herein that calculates the degree of accidental abnormality, the control unit may calculate the difference between the maximum and minimum values ​​of the trend component for each predetermined period as the degree of accidental abnormality. Since the maximum and minimum values ​​of the trend component may be caused by an accidental abnormality of the gear, the anomaly prediction device can more appropriately predict the gear abnormality by using the difference value of the trend component.

[0013] The sending device of the present disclosure includes a drive unit, a gear connected to the drive unit, a detection unit that detects the position of the medium sent out in response to the driving of the gear, and any of the abnormality prediction devices described above. Since the sending device includes any of the abnormality prediction devices described above, it is possible to obtain an effect according to the aspect in which it is adopted.

[0014] The abnormality prediction method of the present disclosure includes: 1. An abnormality prediction method executed by a computer for use in a medium delivery device that has a drive unit, a gear connected to the drive unit, and a detection unit that detects a position of a medium delivered in response to driving of the gear, the medium delivery device intermittently delivering the medium, the method comprising: (a) acquiring detection information regarding an amount of the medium fed out based on a position of the medium detected over time by the detection unit; (b) decomposing the detection information acquired in the step (a) into a trend component related to a moving average of the gear, a periodic component based on the cycle of the gear, and a random component obtained by excluding the trend component and the periodic component; (c) determining an abnormality degree of the gear based on the periodic components obtained by the decomposition in the step (b); It includes.

[0015] Like the above-mentioned anomaly prediction device, this anomaly prediction method can more appropriately predict gear anomalies by using periodic components that are strongly influenced by gear deterioration, wear, etc. Note that this anomaly prediction method may employ various aspects of the above-mentioned anomaly prediction device, or may include additional steps that realize the functions of the above-mentioned anomaly prediction device. [Brief description of the drawings]

[0016] [Figure 1] FIG. 1 is a schematic diagram illustrating an example of a processing system 10. [Diagram 2] FIG. 4 is an explanatory diagram showing an example of information stored in a storage unit 35. [Diagram 3] FIG. 4 is an explanatory diagram showing an example of position detection of the medium 12. [Figure 4] 10 is a flowchart showing an example of a medium sending processing routine. [Diagram 5] FIG. 4 is an explanatory diagram showing an example of detected data and each separated component. [Figure 6] 5 is a flowchart showing an example of a deterioration abnormality prediction processing routine. [Figure 7] FIG. 4 is an explanatory diagram showing an example of an abnormality degree display screen 50. [Figure 8] 11 is a flowchart showing an example of an accidental abnormality detection processing routine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] The present embodiment will be described below with reference to the drawings. Fig. 1 is a schematic explanatory diagram showing an example of a processing system 10 according to the present disclosure. Fig. 2 is an explanatory diagram showing an example of information stored in a storage unit 35. Fig. 3 is an explanatory diagram showing an example of position detection of a medium 12.

[0018] The processing system 10, for example, intermittently sends out a sheet-like member and performs a predetermined process. The processing system 10 may be, for example, a printing device that sends out a print medium as the medium 12 and performs a print process on the print medium. The processing system 10 may also be a mounting device that sends out components attached to or contained on a tape-like backing as the medium 12 and supplies the components to a mounting head. The processing system 10 includes a sending device 20, an abnormality prediction device 30, and a management device 40.

[0019] The sending device 20 performs a process of sending out the medium 12. The sending device 20 includes a control unit 21, a drive unit 22, a gear mechanism 23, a sending member 26, a communication unit 27, and an operation panel 28. The control unit 21 is a controller, and is configured as, for example, a microprocessor centered on a CPU, and controls the entire device. In this processing system 10, the control unit 21 is described as controlling the sending device 20 and the abnormality prediction device 30, that is, as being used for both, but the abnormality prediction device 30 may have a separate control unit and may be controlled by separate control units. The control unit 21 includes a time management unit (not shown) and is configured to be able to grasp the date and time when the process is being performed. The drive unit 22 is a motor to which the gear mechanism 23 is connected. The drive unit 22 generates a drive force to intermittently send out the medium 12, and may be, for example, a stepping motor that operates intermittently, or a motor that operates continuously and is intermittently driven and controlled. The gear mechanism 23 transmits the rotational driving force of the drive unit 22 to the feed member 26, and has, for example, a first gear 24 and a second gear 25. The first gear 24 is fixed to the rotation shaft of the drive unit 22. The second gear 25 is fixed to the rotation shaft of the feed member 26. The first gear 24 meshes with the second gear 25. The feed member 26 is a feed roller that contacts the surface of the medium 12 to feed the medium 12. The communication unit 27 is an interface that exchanges information with an external device such as the management device 40. The operation panel 28 includes a display unit that displays information and an operation unit that allows an operator to input operations. This operation panel 28 may be, for example, a touch panel.

[0020] The abnormality prediction device 30 is a device that predicts and detects an abnormality in the sending device 20. The abnormality prediction device 30 includes a control unit 21, a storage unit 35, and a detection unit 38. The control unit 21 controls the entire abnormality prediction device 30. The control unit 21 includes, as functional blocks, an information acquisition unit 31, a component decomposition unit 32, a periodic component processing unit 33, and a trend component processing unit 34. These functional blocks are realized by the control unit 21 executing a routine described below. The information acquisition unit 31 acquires detection information regarding the sending amount based on the position of the medium 12 detected over time by the detection unit 38. The component decomposition unit 32 decomposes the acquired detection information into a trend component related to the moving average of the gears included in the gear mechanism 23, a periodic component based on the period of the gears, and a random component obtained by excluding the trend component and the periodic component. The periodic component processing unit 33 calculates the deterioration abnormality degree of the gears of the gear mechanism 23 based on the periodic component obtained by the decomposition. The periodic component processing unit 33 may obtain the difference between the maximum and minimum values ​​of the periodic component obtained for each predetermined period as the degree of deterioration abnormality. The trend component processing unit 34 determines whether or not an accidental abnormality has occurred in the gear based on the change over time of the trend component obtained by decomposition. The trend component processing unit 34 may obtain the difference between the maximum and minimum values ​​of the trend component for each predetermined period as the degree of accidental abnormality.

[0021] The storage unit 35 is a large-capacity storage medium such as a HDD or a flash memory that stores various application programs and various data files. The storage unit 35 is also used as a storage unit for the sending device 20, but the sending device 20 may have a separate storage unit. The storage unit 35 stores detection information 36 and abnormality degree information 37. As shown in FIG. 2, the storage unit 35 stores, for example, the detection information 36 and the abnormality degree information 37. The detection information 36 is information that associates one or more of the following with the time at which the position of the medium 12 is detected: the position of the medium 12 detected by the detection unit 38, the actual measurement value of the sending amount calculated based on the position of the medium 12, and the error between the actual measurement value and the sending amount per step of intermittently sending out the medium 12. The detection information 36 includes changes over time of the medium 12 sent out by the sending device 20. The abnormality level information 37 is a record of the degree of deterioration abnormality of the gears included in the gear mechanism 23 determined from the detection information 36 over time, and associates the degree of deterioration abnormality with the time of a predetermined period.

[0022] The detection unit 38 is a sensor that detects the position of the medium 12, and may be, for example, a contact sensor or a non-contact sensor. A non-contact sensor may be, for example, a sensor that detects the position of the medium 12 by detecting the reflection of a laser, or a sensor that detects the position of the medium 12 by capturing an image of the medium 12 and processing the image. As shown in Fig. 3, a marker may be provided on the medium 12, and the position of the marker may be recognized to detect the position of the medium 12.

[0023] The management device 40 is configured as a server that stores and manages the usage status and usage state of each device in the processing system 10. The management device 40 includes a display unit 41 and an input device 42. The display unit 41 is a display that displays a screen. The input device 42 includes a keyboard, a mouse, etc., through which an operator inputs.

[0024] Next, the operation of the processing system 10 of this embodiment thus configured will be described, firstly, the process in which the sending device 20 sends out the medium 12. FIG. 4 is a flow chart showing an example of a medium sending process routine executed by the control unit 21 of the sending device 20. This routine is stored in the memory unit 35 of the sending device 20, and is executed after an instruction to start the execution of the sending process of the medium 12 is received from an operator. When this routine is started, the control unit 21 drives the drive unit 22 to send out the medium 12 (S100). When the drive unit 22 is a stepping motor, the first gear 24 rotates together with the rotating shaft by a set angle, for example, 360°÷60=6° when the number of steps is 60, and the sending member 26 rotates in response to the rotation to send out the medium 12.

[0025] Next, the control unit 21 obtains position information from the detection unit 38, which detects the position of the medium 12 (S110), calculates the actual measurement value of the delivery amount of the medium 12, and calculates the error of the delivery amount (S120). The detection unit 38 detects the position of the medium 12 from the leading end of the medium 12 or a marker attached to the medium 12, for example, by image processing, and outputs the position information to the control unit 21. The control unit 21 obtains the actual measurement value of the delivery amount from the difference between the position detected this time and the position detected last time, and calculates the error from the difference between a preset delivery amount setting value and this actual measurement value. Next, the control unit 21 associates the position information, the actual measurement value of the delivery amount, and the error with the date and time of detection, and stores them in the storage unit 35 as detection information 36 (S130). In this way, the control unit 21 performs a process of updating information regarding the position of the medium 12 as detection information 36 over time in accordance with the delivery of the medium 12.

[0026] Next, the control unit 21 judges whether or not a predetermined period has elapsed (S140). The control unit 21 can make this judgment based on, for example, every day at startup, at a preset time, for a preset period, when the medium 12 has been sent out a preset number of steps, when a preset number of pieces of data has been reached, and the like. The judgment of the elapse of this period can be set in advance by the operator. Here, the control unit 21 judges that the predetermined period has elapsed when a preset number of pieces of data, for example, 600 pieces of data (cycle 60 x set value 10) are newly accumulated. If the predetermined period has not elapsed, the control unit 21 judges whether or not all of the sending processes have been completed (S180), and if all of the sending processes have not been completed, executes the processes from S100 onward.

[0027] On the other hand, when the predetermined period has elapsed in S140, the detection information 36 within the predetermined period is read out, and a process of decomposing the detection information 36 into a trend component, a periodic component, and a random component is performed (S150). In the decomposition process, the trend component is a component based on a moving average of the data of the number of gears of the first gear 24 and the second gear 25. The periodic component is a component based on an average of each periodic element whose period is the number of gears of the first gear 24 and the second gear 25. The control unit 21 may separate periodic components for each gear of the gear mechanism 23, such as the periodic component of the first gear 24 and the periodic component of the second gear 25. The random component is a component obtained by removing the trend component and the periodic component from the position data (original data) in the detection information 36. This component decomposition is implemented, for example, by the decompose function of the statistical function R, and may use the contents specified in "Decomposition of a time series into components" described in the "R Basic Statistical Function Manual."

[0028] FIG. 5 is an explanatory diagram showing an example of detected data and each separated component. From the top, the first row is position data, the second row is trend component, the third row is periodic component, and the fourth row is random component. FIG. 5 shows an example of 3,000 pieces of position data decomposed into components with a period of 10. The periodic component shows fluctuations corresponding to the gear period. If the gear behaves ideally, the trend component, periodic component, and random component show flat lines. If deterioration such as wear occurs in the gear, the corresponding fluctuations will be reflected in one of the components.

[0029] After performing component decomposition in S150, the control unit 21 performs degradation abnormality prediction processing based on the periodic component (S160), and performs accidental abnormality detection processing based on the trend component (S170).Then, the control unit 21 determines whether or not all transmission processing has been completed (S180), and if not, performs processing from S100 onward, and ends this routine when all transmission processing has been completed.

[0030] Here, the deterioration abnormality prediction process of S160 will be described. FIG. 6 is a flowchart showing an example of a deterioration abnormality prediction process routine executed by the control unit 21. This routine is stored in the storage unit 35 of the sending device 20 and is executed in S160 of the medium sending process routine. When this routine is started, the control unit 21 acquires periodic components within a predetermined period from the detection information 36 (S200) and calculates the fluctuation width of the periodic components (S210). For example, the control unit 21 sets the difference value between the maximum value and the minimum value of the periodic components obtained for each predetermined period as the deterioration abnormality degree. Then, the control unit 21 stores the obtained fluctuation width (difference value) in the abnormality degree information 37 as the deterioration abnormality degree for that predetermined period, and outputs this abnormality degree information 37 (S220). The control unit 21 may display and output the deterioration abnormality degree on the display unit of the operation panel 28 of the processing system 10, for example, or may output the abnormality degree information 37 to the management device 40 and display and output the deterioration abnormality degree on the display unit 41.

[0031] 7 is an explanatory diagram showing an example of an abnormality level display screen 50 displayed on the display unit 41 of the management device 40. This abnormality level display screen 50 shows the change over time in the degree of deterioration abnormality recorded in the abnormality level information 37, with the horizontal axis representing the time of a predetermined period and the vertical axis representing the degree of deterioration abnormality. An operator can check the abnormality level display screen 50 and determine that maintenance of the gear mechanism 23 or the like is required if the degree of deterioration abnormality exceeds a predetermined threshold value or if the degree of deterioration abnormality has increased significantly from the previous value.

[0032] After S220, the control unit 21 judges whether the obtained deterioration abnormality degree is within a predetermined allowable range (S230), and if the deterioration abnormality degree is within the predetermined allowable range, the control unit 21 ends this routine as it is. On the other hand, if the deterioration abnormality degree is not within the predetermined allowable range, the control unit 21 judges that a deterioration abnormality has occurred, outputs information to that effect (S240), and ends this routine. The control unit 21 may judge that a deterioration abnormality of the gear has occurred when the abnormality degree of the periodic component exceeds a predetermined allowable threshold. Alternatively, the control unit 21 may judge that a deterioration abnormality of the gear has occurred when the abnormality degree of the periodic component has increased beyond a predetermined allowable threshold compared to the abnormality degree obtained last time. The allowable range or the allowable threshold may be empirically determined to be, for example, a range in which an abnormal operation of the gear mechanism 23 has a large effect on the sending process of the medium 12. The control unit 21 may also display and output the occurrence of the deterioration abnormality of the gear mechanism 23 on the operation panel 28, or may display and output the occurrence of the deterioration abnormality of the gear mechanism 23 on the display unit 41 of the management device 40. A worker who has confirmed this information will stop using the corresponding gear mechanism 23 and replace the gear or perform other operations.

[0033] Next, the accidental abnormality detection process of S170 will be described. FIG. 8 is a flowchart showing an example of an accidental abnormality detection process routine executed by the control unit 21. This routine is stored in the storage unit 35 of the sending device 20 and is executed in S170 of the medium sending process routine. When this routine is started, the control unit 21 acquires trend components within a predetermined period from the detection information 36 (S300) and calculates the fluctuation range of the trend components (S310). For example, the control unit 21 sets the difference value between the maximum value and the minimum value of the trend components obtained for each predetermined period as the accidental abnormality degree. Then, the control unit 21 determines whether the obtained accidental abnormality degree is within a predetermined allowable range (S320). Note that the control unit 21 may determine whether the accidental abnormality degree of the trend component exceeds a predetermined allowable threshold value to determine whether the accidental abnormality degree exceeds a predetermined allowable range. Alternatively, the control unit 21 may determine whether the accidental abnormality degree of the trend component has increased beyond a predetermined allowable threshold compared to the previously obtained abnormality degree, thereby determining whether the accidental abnormality degree exceeds a predetermined allowable range. The allowable range and allowable threshold may be empirically determined to be a range that has a large effect on a predetermined process (e.g., printing process) in the sending process of the medium 12, for example. When the accidental abnormality degree is within the allowable range, the control unit 21 ends this routine. On the other hand, when the accidental abnormality degree is not within the allowable range, the control unit 21 outputs information to that effect that an accidental abnormality has occurred (S330) and ends this routine. For example, the control unit 21 may display and output the fact that an accidental abnormality has occurred on the display unit of the operation panel 28, or may output it to the management device 40. After confirming this, the worker performs, for example, maintenance of the sending device 20.

[0034] Here, the correspondence between the components of this embodiment and those of the present disclosure will be clarified. The driving unit 22 of this embodiment corresponds to the driving unit of the present disclosure, the first gear 24 and the second gear 25 of the gear mechanism 23 correspond to the gears, the detection unit 38 corresponds to the detection unit, the control unit 21 corresponds to the control unit, the sending device 20 corresponds to the sending device, and the abnormality prediction device 30 corresponds to the abnormality prediction device. Note that in this embodiment, an example of the abnormality prediction method of the present disclosure is also clarified by explaining the operation of the abnormality prediction device 30.

[0035] The abnormality prediction device 30 of the present embodiment described above decomposes detection information 36 relating to the amount of medium feed based on the position of the medium 12 detected over time into a trend component relating to the moving average of the gears of the gear mechanism 23, a periodic component based on the gear cycle, and a random component obtained by excluding the trend component and periodic component. The abnormality prediction device 30 then determines the degree of deterioration abnormality of the gears based on the periodic component obtained by the decomposition, and outputs the determined degree of deterioration abnormality to the management device 40. The periodic component obtained by decomposing the detection information 36 is a component that is strongly influenced by, for example, gear deterioration or wear, and therefore gear abnormalities can be more appropriately predicted.

[0036] Furthermore, the control unit 21 obtains the difference value between the maximum value and the minimum value of the periodic component as the degree of deterioration abnormality for each predetermined period. Since the value of the periodic component changes depending on the rotation period of the gear, the abnormality prediction device 30 can more appropriately predict the abnormality of the gear by using the difference value of the periodic component. Furthermore, the control unit 21 stores the position of the medium 12 detected by the detection unit 38, the actual measurement value of the delivery amount obtained based on the position of the medium 12, and the error between the delivery amount per step of intermittently delivering the medium 12 and the actual measurement value, as the detection information 36, in association with the time when the position of the medium 12 is detected. The abnormality prediction device 30 can decompose the periodic component by using the position of the medium 12, the actual measurement value of the delivery amount, the error of the delivery amount, and the like. Furthermore, the control unit 21 may obtain the degree of accidental abnormality of the gear based on the change over time of the trend component obtained by the decomposition. The abnormality prediction device 30 can more appropriately predict the abnormality of the gear by using components other than the periodic component. In addition, the control unit 21 obtains the difference between the maximum and minimum values ​​of the trend component for each predetermined period as the degree of accidental abnormality. Since the maximum and minimum values ​​of the trend component may be caused by accidental gear abnormalities, the abnormality prediction device 30 can more appropriately predict gear abnormalities by using the difference value of the trend component.

[0037] It goes without saying that the present disclosure is in no way limited to the above-described embodiment, and can be embodied in various forms as long as it falls within the technical scope of the present disclosure.

[0038] For example, in the above embodiment, the difference between the maximum and minimum values ​​of the periodic component is calculated as the deterioration abnormality degree for each predetermined period, but the present invention is not limited to this as long as the periodic component is used. For example, the amplitude value of the periodic component for each step within a predetermined period may be calculated, and the average of these may be used as the deterioration abnormality degree. This abnormality prediction device can also use the periodic component to more appropriately predict gear abnormality.

[0039] In the above embodiment, the detection information 36 includes the position of the medium 12, the actual measured value of the delivery amount, and the error of the delivery amount, but is not limited to this and may include one or more of these. If any of these is present, the control unit 21 can determine the degree of deterioration abnormality.

[0040] In the above-described embodiment, when the deterioration abnormality degree exceeds a predetermined allowable range, the deterioration abnormality is judged and displayed, but the present invention is not limited to this, and the process of judging the deterioration abnormality may be omitted. The worker can also judge the situation of the deterioration abnormality by, for example, checking the contents of the abnormality degree display screen 50 or the abnormality degree information 37. In addition, in the above-described embodiment, when the accidental abnormality degree exceeds a predetermined allowable range, the accidental abnormality is judged and displayed, but the present invention is not limited to this, and the process of judging the accidental abnormality may be omitted. For example, if the control unit 21 stores data on the accidental abnormality degree in the storage unit 35, the worker can also judge the situation of the accidental abnormality by checking the contents.

[0041] In the above embodiment, the difference between the maximum and minimum values ​​of the trend component is calculated as the accidental abnormality degree for each predetermined period, but the present invention is not limited to this, as long as the trend component is used. For example, the amplitude of the trend component may be calculated, and the average of the amplitude may be calculated as the accidental abnormality degree. This abnormality prediction device 30 can also detect an abnormality in the transmission device 20 using the trend component. Alternatively, in the above embodiment, the control unit 21 calculates the accidental abnormality degree of the gear based on the trend component, but the present invention is not limited to this, and this process may be omitted. This abnormality prediction device 30 can also more appropriately predict an abnormality in the gear because the deterioration abnormality degree is calculated using the periodic component.

[0042] In the above-described embodiment, the gear mechanism 23 has the first gear 24 and the second gear 25, but is not limited thereto and may further include one or more gears other than these. The control unit 21 may separate the periodic components for each gear.

[0043] In the above-described embodiment, the sending device 20 is described as having the functions of the anomaly prediction device of the present disclosure, but this is not particularly limited, and the functions of the anomaly prediction device of the present disclosure may be provided by an external device such as a management device 40.

[0044] In the above-described embodiment, the present disclosure has been described as an abnormality prediction device 30, but is not particularly limited thereto, and may be an abnormality prediction method, or may be a program executed by a computer to execute this abnormality prediction method. [Industrial Applicability]

[0045] The abnormality prediction device, the sending device, and the abnormality prediction method disclosed herein can be used in implementation fields related to methods for detecting and predicting abnormalities in machines that send out members using gears. [Explanation of symbols]

[0046] 10 processing system, 12 medium, 20 sending device, 21 control unit, 22 drive unit, 23 gear mechanism, 24 first gear, 25 second gear, 26 sending member, 27 communication unit, 28 operation panel, 30 anomaly prediction device, 31 information acquisition unit, 32 component decomposition unit, 33 periodic component processing unit, 34 trend component processing unit, 35 memory unit, 36 detection information, 37 anomaly degree information, 38 detection unit, 40 management device, 41 display unit, 42 input device, 50 anomaly degree display screen.

Claims

1. 1. An abnormality prediction device for use in a medium delivery device that includes a drive unit, a gear connected to the drive unit, and a detection unit that detects a position of a medium delivered in response to driving of the gear, the abnormality prediction device comprising: a control unit that acquires detection information related to the amount of the medium fed out based on the position of the medium detected over time by the detection unit, decomposes the acquired detection information into a trend component related to a moving average of the gear, a periodic component based on the cycle of the gear, and a random component obtained by excluding the trend component and the periodic component, determines a degree of abnormality of the gear based on the periodic component obtained by the decomposition, and outputs the determined degree of abnormality, The control unit determines, as the degree of abnormality, a difference value between a maximum value and a minimum value of the periodic component for each predetermined period.

2. 1. An abnormality prediction device for use in a medium delivery device that includes a drive unit, a gear connected to the drive unit, and a detection unit that detects a position of a medium delivered in response to driving of the gear, the abnormality prediction device comprising: a control unit that acquires detection information related to the amount of the medium fed out based on the position of the medium detected over time by the detection unit, decomposes the acquired detection information into a trend component related to a moving average of the gear, a periodic component based on the cycle of the gear, and a random component obtained by excluding the trend component and the periodic component, determines a degree of abnormality of the gear based on the periodic component obtained by the decomposition, and outputs the determined degree of abnormality, the drive unit is a stepping motor, The control unit determines, as the degree of abnormality, an average of amplitude values ​​of periodic components for each step within a predetermined period.

3. The abnormality prediction device of claim 1 or 2, wherein the control unit acquires the detection information in which one or more of the position of the medium detected by the detection unit, the actual measured value of the feed amount calculated based on the position of the medium, and the error between the actual measured value and the feed amount per step in which the medium is intermittently fed, are associated with the time at which the position of the medium is detected.

4. 2. The abnormality prediction device according to claim 1, wherein the control unit determines, based on the change over time of the trend component obtained by the decomposition, a difference value between a maximum value and a minimum value of the trend component for each predetermined period as the degree of accidental abnormality of the gear.

5. The abnormality prediction device according to claim 2 , wherein the control unit determines an average of the amplitude of the trend component based on the change over time of the trend component obtained by the decomposition as the degree of accidental abnormality of the gear.

6. A drive unit; A gear connected to the drive unit; a detection unit that detects a position of the medium fed in response to the driving of the gear; The abnormality prediction device according to any one of claims 1 to 5, A sending device comprising:

7. 1. A method for predicting an anomaly that is used in a medium delivery device that includes a drive unit, a gear connected to the drive unit, and a detection unit that detects a position of a medium delivered in response to driving of the gear, and that is executed by a computer, the method comprising: (a) acquiring detection information regarding an amount of the medium fed out based on a position of the medium detected over time by the detection unit; (b) decomposing the detection information acquired in the step (a) into a trend component related to a moving average of the gear, a periodic component based on the cycle of the gear, and a random component obtained by excluding the trend component and the periodic component; (c) determining, based on the periodic components obtained by the decomposition in the step (b), a difference value between a maximum value and a minimum value of the periodic components for each predetermined period as an abnormality degree of the gear; The abnormality prediction method includes:

8. 1. An abnormality prediction method executed by a computer for use in a medium delivery device that has a stepping motor as a drive unit, a gear connected to the drive unit, and a detection unit that detects a position of a medium delivered in response to driving of the gear, the method comprising: (a) acquiring detection information regarding an amount of the medium fed out based on a position of the medium detected over time by the detection unit; (b) decomposing the detection information acquired in the step (a) into a trend component related to a moving average of the gear, a periodic component based on the cycle of the gear, and a random component obtained by excluding the trend component and the periodic component; (c) calculating an average of amplitude values ​​of the periodic components for each step within a predetermined period based on the periodic components obtained by the decomposition in the step (b) as an abnormality degree of the gear; The abnormality prediction method includes:

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