JP6184772B2 - Conversion abnormality determination analysis apparatus and program - Google Patents

Description

  The present invention relates to a technique for determining whether or not an abnormality has occurred in a switching operation of a turning machine.

  2. Description of the Related Art An electrical switch using a motor as a servo motor is known. For example, in Patent Document 1, the number of pulses proportional to the number of rotations of a motor is obtained from an encoder attached to a servo motor, and the load of the motor is measured, whereby the motor torque for a series of conversion operations (conversion strokes). The point from which the graph showing (conversion torque) is obtained is described. In addition, a technique for determining whether or not an abnormality has occurred in a conversion operation is described based on a motor torque (conversion torque) with respect to a series of conversion operations (conversion strokes).

JP 2009-083577 A

  The technique of Patent Document 1 determines that the peak of torque in a series of conversion operations is normal when the upper limit value and the lower limit value are within a set allowable range, and determines that it is abnormal when the value is outside the allowable range. . The cause of the abnormality is the presence of foreign matter when the upper limit is exceeded, and the component parts are worn or dropped when the lower limit is exceeded.

  However, there are other causes of abnormalities in the switching operation, such as an increase in branch load, excessive or low adhesion, an increase in internal resistance such as grease due to environmental temperature changes, an abnormality due to disconnection or short circuit of the electric circuit, etc. There are various factors. Therefore, as in the technique of Patent Document 1, it cannot be ensured that there is no abnormality in the conversion operation simply because the torque peak is within the normal range. This is because there is a possibility of an abnormality even if the torque peak is normal depending on the factor. In addition, it is not possible to uniformly determine that the cause of the torque peak exceeding the upper limit is inclusion of foreign matter. Therefore, if the abnormality for each factor can be determined, it can be a significant conversion abnormality determination.

  The present invention has been devised in view of the above circumstances, and the object thereof is to realize a technique that can determine the abnormality of the switching operation of the turning machine using the servo motor and the cause thereof. .

The first invention for solving the above-described problems is
Data acquisition means (for example, FIG. 1) for acquiring conversion torque data related to a series of conversion operations of the switching machine that performs the conversion operation by the driving force of a servo motor (for example, the servo motor 12 in FIG. 1) by constant rotation speed control. Torque data acquisition unit 210),
Maximum torque extraction means (for example, peak analysis unit 221 in FIG. 1) for extracting the maximum torque in each of the unlocking process, the converting process and the locking process in a series of converting operations from the converted torque data;
Determination means (for example, the conversion of FIG. 1) that determines the switching abnormality of the switch and the factor thereof using at least whether or not the maximum torque of each of the processes is within the normal distribution range of the maximum torque in each of the processes. An abnormality factor determination unit 230);
Is a conversion abnormality determination and analysis device.

As another invention,
Computer
Data acquisition means for acquiring conversion torque data related to a series of conversion operations of the switching machine that performs conversion operation by the driving force of the servo motor by constant rotation speed control,
A maximum torque extraction means for extracting the maximum torque in each of the unlocking process, the converting process and the locking process in a series of converting operations from the converted torque data;
Determination means for determining whether or not the switching abnormality of the switch and the factor thereof, using at least whether or not the maximum torque of each of the steps is within a normal distribution range of the maximum torque in each of the steps;
It is good also as comprising the program (For example, the conversion abnormality factor determination part 230 of FIG. 1) for functioning as.

  According to the first invention and the like, it is possible to determine the switching abnormality of the turning machine and the factor thereof. That is, at least using whether or not the maximum torque in each step of the unlocking process, the converting process and the locking process in the series of converting operations is within the normal distribution range of the maximum torque in each process, the conversion abnormality and its factor Determine. Since the process in which the torque abnormality appears depends on the cause of the conversion abnormality, it is possible to determine whether or not there is a conversion abnormality for each factor.

As a second invention, in the first invention,
Storage means for accumulating and storing the converted torque data determined to be normal by the determination means (for example, accumulated torque data 330 in FIG. 1);
Normal distribution range determining means (for example, a conversion abnormality factor determining unit 230 in FIG. 1) for determining the normal distribution range of each of the steps based on the stored and converted torque data;
It is good also as comprising the conversion abnormality determination analyzer provided further.

  According to the second aspect of the invention, the conversion torque data determined to be normal can be accumulated and stored, and can be used for determination criteria data for the next and subsequent times. According to the first invention, it is possible to determine the conversion abnormality according to various factors. For this reason, in the second invention, when it is determined to be normal, there is no abnormality corresponding to all of these factors, and the data for subsequent determination criteria can be used.

As a third invention, in the second invention,
Further comprising an average torque curve calculating means for calculating an average torque curve based on the stored and stored conversion torque data (for example, the approximation analysis unit 222 in FIG. 1);
The determination means includes an approximation degree calculation means (for example, an approximation degree analysis unit 222 in FIG. 1) for calculating an approximation degree between the torque curve of the converted torque data acquired by the data acquisition means and the average torque curve. , By further using the calculated degree of approximation, to determine the conversion abnormality of the switch and its factor,
A conversion abnormality determination / analysis apparatus may be configured.

  According to the third aspect of the invention, the average torque curve of the conversion torque data that has been determined to be normal is calculated, and the degree of approximation between the average torque card and the conversion torque data to be determined is calculated. And the conversion abnormality and its factor are determined using the degree of approximation. Depending on the cause of the conversion abnormality, the torque does not suddenly become an abnormal value, and the torque may become abnormal throughout the conversion operation. Also in this case, it can be determined that the conversion is abnormal.

The functional block diagram of a conversion abnormality determination apparatus. An example of conversion torque data. Explanatory drawing of the production | generation of average torque data. Explanatory drawing of calculation of the degree of approximation of conversion torque data and average torque data. Explanatory drawing of calculation of the maximum variation | change_quantity and maximum torque value in conversion torque data. The data structural example of a conversion abnormality factor table. Explanatory drawing of the setting of a peak normal distribution range. The data structural example of accumulated torque data. The flowchart of a conversion abnormality determination process.

[Function configuration]
FIG. 1 is a functional configuration of the conversion abnormality determination device 1 of the present embodiment. The conversion abnormality determination device 1 is installed in, for example, an equipment room and is connected to an electric switch (hereinafter simply referred to as a “switching machine”) 10, and various signals (operations) are transmitted from the switch 10. Current, load torque, conversion state, conversion direction, etc.) are received and the state of the rolling machine 10 is monitored. Moreover, while determining whether the conversion abnormality has generate | occur | produced from the load torque at the time of the conversion operation of the switch machine 10, the conversion abnormality factor is determined. The switch 10 includes a servo motor 12 as a point change drive source, and the servo motor 12 is controlled at a constant rotational speed to keep the rotational speed constant by controlling the operating current. That is, the load torque is obtained from the operating current of the servo motor 12. When the servo motor 12 outputs a load torque value, the process of calculating the load torque from the operating current can be omitted. Further, since the servo motor 12 operates at a constant rotation speed, the stroke position (conversion position) of the operation can be obtained from the rotation speed and the rotation angle.

  As shown in FIG. 1, the conversion abnormality determination device 1 includes an operation unit 110, a display unit 120, an audio output unit 130, a communication unit 140, a processing unit 200, and a storage unit 300. It is a computer system.

  The operation unit 110 is an input device realized by, for example, a keyboard, a mouse, a touch panel, various switches, and the like, and outputs an input signal corresponding to the operation input to the processing unit 200. The display unit 120 is a display device realized by, for example, an LCD (Liquid Crystal Display), an ELD (Electro-Luminescence Display), or the like, and performs various screen displays based on display signals from the processing unit 200. The audio output unit 130 is an audio output device realized by, for example, a speaker and performs various audio outputs based on the audio signal from the processing unit 200. The communication unit 140 is a communication device realized by, for example, a wireless communication module, a router, a modem, a wired communication cable jack, or a control circuit, and performs predetermined data communication with an external device.

  The processing unit 200 is realized by an arithmetic device such as a CPU (Central Processing Unit), for example, and performs overall control of the conversion abnormality determination device 1 based on programs, data, and the like stored in the storage unit 300. The processing unit 200 includes a torque data acquisition unit 210, a torque data analysis unit 220, and a conversion abnormality factor determination unit 230, and performs conversion abnormality determination processing (see FIG. 9) according to the conversion abnormality determination program 310. Do.

  The torque data acquisition unit 210 acquires conversion torque data related to one conversion operation of the switching machine 10. Specifically, the load torque is calculated from the operating current of the servomotor 12 of the switch 10 and the stroke position (converting position) of the operation can be calculated from the rotation speed of the servomotor 12. And the conversion torque data which shows the change of the load torque in each stroke position are produced | generated.

  FIG. 2 is an example of conversion torque data. FIG. 2 shows a torque curve (torque waveform) in one conversion operation with the horizontal axis representing time t and the vertical axis representing load torque T. Since the servo motor 12 operates with constant rotation speed control, the elapsed time (time t) from the start of conversion indicates the stroke position (conversion position). Considering ease of understanding, the following description will be made using the time t as appropriate instead of the stroke position. Further, in the present embodiment, one of the features is that the stroke position is divided into three process ranges of an unlocking process (first half), a conversion process (middle half), and a locking process (second half). It is said.

  The torque data analysis unit 220 includes a peak analysis unit 221, an approximation analysis unit 222, and a change amount analysis unit 223, and analyzes the converted torque data acquired by the torque data acquisition unit 210.

  The peak analysis unit 221 performs “peak analysis” for calculating the peak value of the conversion torque data. That is, as shown in FIG. 2, the maximum value of the load torque in each of the three process ranges (unlock / convert / lock) in the conversion torque data is set as a peak P in the corresponding process range.

  The approximation analysis unit 222 performs “approximation analysis” for calculating the approximation (correlation value) between the converted torque data and the average torque data. The average torque data is torque data obtained by averaging a plurality of past normal conversion torque data (that is, no conversion abnormality has occurred). Specifically, from the accumulated torque data 330, which is a set of past normal conversion torque data, data having the same conversion torque data, turning machine, and conversion direction is extracted.

すなわち、時刻ｔにおけるトルクＴｉ（ｔ）と平均トルクＴａ（ｔ）との二乗平均平方根を工程範囲Ｒに亘って時間平均した値を、当該工程範囲における転換トルクデータと平均トルクデータとの近似度Ｄとする。 Next, as shown in FIG. 3, the average value of the torque Ti (t) at each time t is calculated for each of a plurality (N) of accumulated torque data 330 that has been extracted and used as average torque data. Then, as shown in FIG. 4, the combined conversion start time t _0, by obtaining the difference of the torque between the average torque data and conversion torque data to be analyzed, to calculate the approximation degree. At this time, the degree of approximation is obtained for each of the three process ranges. The degree of approximation is calculated according to, for example, equation (1).

That is, a value obtained by time-averaging the root mean square of the torque Ti (t) and the average torque Ta (t) at the time t over the process range R is used as an approximation degree between the converted torque data and the average torque data in the process range. D.

  The change amount analysis unit 223 performs “change amount analysis” for calculating a sudden torque change in the converted torque data. That is, as shown in FIG. 5, in the conversion torque data, the load torque change amount ΔT at a predetermined short-time interval Δt (about 0.05 seconds) is calculated, and the largest one of these is the maximum change amount. To do. Further, “maximum torque analysis” is performed to obtain the maximum value Tm of the load torque over the entire period. The maximum torque analysis may be performed by the peak analysis unit 221 selecting the maximum value from the peaks P in each process range.

  The conversion abnormality factor determination unit 230 determines whether or not there is a conversion abnormality of the switching machine 10 based on the analysis result of the conversion torque data by the torque data analysis unit 220. Determine the cause of the abnormality. Specifically, with reference to the conversion abnormality factor table 320, the analysis results of each of the four types of analysis items (peak analysis, approximation analysis, change amount analysis, and maximum torque analysis) are the conditions for determining the conversion abnormality. It is determined whether or not a certain abnormality determination condition is satisfied, and the presence / absence of a conversion abnormality of the switch 10 and an abnormality factor are determined based on a combination of these determination results.

  FIG. 6 is a diagram illustrating an example of a data configuration of the conversion abnormality factor table 320. As shown in FIG. 6, the conversion abnormality factor table 320 stores an abnormality determination condition 322 and a conversion abnormality factor 323 in association with each of the four analysis items 321. Causes of abnormalities in the switching operation of the switch 10 include foreign matter, increased branch load, excessive or low adhesion, increased internal resistance such as grease due to environmental temperature changes, disconnection or short circuit of the electric circuit, etc. There are various factors such as.

  Empirically, it is known that the change in the conversion torque curve varies depending on the type of the generated factor, and the cause of the conversion abnormality occurring from the characteristics of the conversion torque curve can be estimated.

First, the abnormality determination using the analysis result of “peak analysis” is performed by setting an abnormality determination condition if one or more of the peaks P in each of the three process ranges that are the peak analysis results are outside the peak normal distribution range. It is determined that it satisfies.

The peak normal distribution range is a distribution range of the peak P in normal conversion torque data, and is generated with reference to the accumulated torque data 330. That is, from the accumulated torque data 330, data having the same conversion torque data, turning machine, and conversion direction is extracted. Next, as shown in FIG. 7, the peaks P of the respective process ranges obtained as the peak analysis results of the extracted cumulative torque data 330 are plotted on the coordinate plane defining the conversion torque data. Then, the peak normal distribution range E is determined so as to include a set of these plotted peaks P. If one or more peaks out of the peaks P of the three process ranges are outside the normal peak distribution range E, it is determined that the abnormality determination condition is satisfied.

In the abnormality determination using the analysis result of the “approximation analysis”, one or more of the approximation degrees of the three process ranges, which are the approximation analysis results, are determined by the torque of the conversion torque data and the average torque data. If it is equal to or greater than a predetermined threshold value that is regarded as “a large difference” between curves, it is determined that the abnormality determination condition is satisfied.

  Abnormality determination using the analysis result of “variation amount analysis” is performed when the maximum amount of change that is the variation amount analysis result is equal to or greater than a predetermined threshold value that the torque curve is considered to change rapidly. It is determined that

  The abnormality determination using the analysis result of “maximum torque analysis” determines that the abnormality determination condition is satisfied if the maximum torque value, which is the analysis result of the maximum torque analysis, is equal to or greater than a predetermined torque limit value.

And if abnormality determination conditions are satisfy | filled about one or more analysis items among these analysis items, it will determine with conversion abnormality existing. When it is determined that there is a conversion abnormality, a conversion abnormality factor is determined based on a combination of analysis items that satisfy the abnormality determination condition. Further, it is determined in which process range of the three process ranges the abnormality determination condition is satisfied, and it is estimated in which process of the series of conversion operations the conversion abnormality has occurred.

  The torque data management unit 240 manages the acquired conversion torque data. That is, when it is determined by the conversion abnormality factor determination unit 230 that there is no conversion abnormality, the conversion torque data is converted into the switching machine ID, the conversion direction, the acquisition date, the conversion torque, which is identification information of the corresponding switching machine. Data is accumulated and stored as new accumulated torque data 330 in association with the analysis result of the torque data analysis unit 220 for the data.

  FIG. 8 is a diagram illustrating an example of a data configuration of the accumulated torque data 330. According to FIG. 8, the accumulated torque data 330 is generated for each conversion torque data, and stores data ID 331, turning machine ID 332, conversion direction 333, conversion torque data 334, and analysis result data 335. ing.

  The analysis result data 335 stores an analysis result in association with each analysis item.

  The storage unit 300 stores a system program for realizing various functions for the processing unit 200 to control the conversion abnormality determination device 1 in an integrated manner, a program, data, and the like for realizing the present embodiment, Used as a work area of the processing unit 200, operation data from the operation unit 110 and the like are temporarily stored. In the present embodiment, the storage unit 300 stores a conversion abnormality determination program 310, a conversion abnormality factor table 320, and accumulated torque data 330.

[Process flow]
FIG. 9 is a flowchart for explaining the flow of the conversion abnormality determination process. The conversion abnormality determination process is realized by the processing unit 200 executing the conversion abnormality determination program 310. First, the torque data acquisition unit 210 acquires conversion torque data from the switch 10 (step S1). Next, the torque data analysis unit 220 performs analysis processing on the acquired conversion torque data. That is, the peak analysis unit 221 performs “peak analysis” for calculating the maximum value (peak) of each torque in the process range in the converted torque data (step S3). Further, the approximation analysis unit 222 calculates average torque data obtained by averaging past normal conversion data based on the accumulated torque data 330 (step S5). Then, for each process range, “approximation analysis” is performed to calculate the approximation between the converted torque data and the average torque data (step S7). Further, the change amount analysis unit 223 performs “change amount analysis” and “maximum torque analysis” for calculating the maximum change amount and the maximum torque in the converted torque data (step S9).

  Subsequently, the conversion abnormality factor determination unit 230 performs a conversion abnormality determination process based on the analysis result. That is, the peak analysis unit 221 calculates the peak normal distribution range E based on the accumulated torque data 330 that is conversion torque data at the normal time (step S11). Then, whether or not there is a conversion abnormality is determined depending on whether or not the analysis results of the peak analysis, the approximation analysis, the change amount analysis, and the maximum torque analysis satisfy the abnormality determination conditions defined in the conversion abnormality factor table 320. (Step S13).

  As a result, if it is determined that there is a conversion abnormality (step S15: YES), the conversion abnormality factor is determined based on the combination of analysis conditions that satisfy the abnormality determination condition with reference to the conversion abnormality factor table 320 ( Step S17), the location where the conversion abnormality has occurred is specified (step S19). If it is determined that there is no conversion abnormality (step S15: NO), the conversion torque data is additionally stored as new accumulated torque data 330 together with the analysis result (step S23).

  Then, a conversion abnormality determination result such as presence / absence of abnormality, abnormality factor, and abnormality location is displayed and output on the display unit 120, for example (step S21). When the above processing is performed, this processing ends.

[Function and effect]
As described above, according to the conversion abnormality determination device 1 of the present embodiment, a plurality of analyzes such as peak analysis, approximation analysis, change amount analysis, and maximum torque analysis are performed on the conversion torque data acquired from the switch 10. The presence or absence of conversion abnormality and its factor can be determined from these analysis results. In particular, in the present embodiment, conversion is performed using whether the peak value of torque in each step of the unlocking process, the converting process, and the locking process in the series of converting operations is within the peak normal distribution range in each process. Determine abnormalities and their causes. Since the process in which the torque abnormality appears depends on the cause of the conversion abnormality, it is possible to determine whether or not there is a conversion abnormality for each factor.

  It should be noted that embodiments to which the present invention can be applied are not limited thereto, and can be appropriately changed without departing from the spirit of the present invention. For example, the load torque described above may be replaced with a load torque rate that is a load torque with respect to a predetermined maximum torque, and the load torque or the load torque rate is in an equal range.

DESCRIPTION OF SYMBOLS 10 Switching machine, 12 Servo motor 1 Conversion abnormality determination apparatus 110 Operation part, 120 Display part, 130 Voice output part, 140 Communication part 200 Processing part 210 Torque data acquisition part 220 Torque data analysis part 221 Peak analysis part, 222 Approximation Degree analysis unit, 223 Change amount analysis unit 230 Conversion abnormality factor determination unit, 240 Torque data management unit 300 Storage unit 310 Conversion abnormality determination program 320 Conversion abnormality factor table, 330 Cumulative torque data

Claims (4)

Data acquisition means for acquiring conversion torque data relating to a series of conversion operations of a switching machine (hereinafter referred to as “target switching machine”) that performs a conversion operation by a driving force of a servo motor by constant rotation speed control;
A maximum torque extracting means for extracting the maximum torque in each of the unlocking process, the converting process and the locking process in a series of converting operations from the converted torque data;
When the first conversion abnormality condition is satisfied when the maximum torque of each of the steps is outside the normal distribution range of the maximum torque in each of the steps relating to the target turning machine, the first conversion abnormality is satisfied. A determination means for determining that there is a conversion abnormality with the factor associated with the determination condition as an abnormality factor ;
Storage means for accumulating and storing conversion torque data of the target turning machine determined to have no conversion abnormality by the determination means;
Normal distribution range determining means for determining the normal distribution range of each of the steps related to the target switch based on the maximum torque of each of the steps related to the conversion torque data of the target switch stored and stored. When,
A conversion abnormality determination and analysis device. Data acquisition means for acquiring conversion torque data relating to a series of conversion operations of the switching machine that performs the conversion operation by the driving force of the servo motor by constant rotation speed control;
A maximum torque extracting means for extracting the maximum torque in each of the unlocking process, the converting process and the locking process in a series of converting operations from the converted torque data;
When the maximum torque of each step is outside the normal distribution range of the maximum torque in each of the steps , the first conversion abnormality determination condition is associated with the first conversion abnormality determination condition. A determination means for determining that there is a conversion abnormality with the factor as an abnormal factor ;
Storage means for accumulating and storing the conversion torque data determined by the determination means as having no conversion abnormality;
An average torque curve calculating means for calculating an average torque curve based on the stored and converted torque data;
Equipped with a,
The determination means includes approximation degree calculation means for calculating an approximation degree between the torque curve of the conversion torque data acquired by the data acquisition means and the average torque curve, and a second conversion based on the calculated approximation degree. When the abnormality determination condition is satisfied, it is determined that there is a conversion abnormality with the factor associated with the second conversion abnormality determination condition as an abnormality factor.
Conversion abnormality judgment analyzer. Computer
Data acquisition means for acquiring conversion torque data relating to a series of conversion operations of a switching machine (hereinafter referred to as “target switching machine”) that performs a conversion operation by a driving force of a servo motor by constant rotation speed control;
A maximum torque extraction means for extracting the maximum torque in each of the unlocking process, the converting process and the locking process in a series of converting operations from the converted torque data;
When the first conversion abnormality condition is satisfied when the maximum torque of each of the steps is outside the normal distribution range of the maximum torque in each of the steps relating to the target turning machine, the first conversion abnormality is satisfied. A determination means for determining that there is a conversion abnormality with the factor associated with the determination condition as an abnormality factor ,
Storage control means for accumulating and storing in the storage unit conversion torque data of the target turning machine determined to have no conversion abnormality by the determination means,
Normal distribution range determining means for determining the normal distribution range of each of the steps related to the target switch based on the maximum torque of each of the steps related to the conversion torque data of the target switch stored and stored. ,
Program to function as. Computer
Data acquisition means for acquiring conversion torque data related to a series of conversion operations of the switching machine that performs conversion operation by the driving force of the servo motor by constant rotation speed control,
A maximum torque extraction means for extracting the maximum torque in each of the unlocking process, the converting process and the locking process in a series of converting operations from the converted torque data;
When the maximum torque of each step is outside the normal distribution range of the maximum torque in each of the steps , the first conversion abnormality determination condition is associated with the first conversion abnormality determination condition. A determination means for determining that there is a conversion abnormality with the factor as an abnormality factor ,
Storage control means for accumulating and storing the conversion torque data determined to have no conversion abnormality by the determination means in a storage unit,
An average torque curve calculating means for calculating an average torque curve based on the stored and converted torque data;
A program for functioning as,
The determination means includes approximation degree calculation means for calculating an approximation degree between the torque curve of the conversion torque data acquired by the data acquisition means and the average torque curve, and a second conversion based on the calculated approximation degree. When the abnormality determination condition is satisfied, it is determined that there is a conversion abnormality with the factor associated with the second conversion abnormality determination condition as an abnormality factor.
Program .

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