Patent Application
20240385082
The present invention relates to a management device for a power transmission mechanism, a management method for a power transmission mechanism, and a management system.
For example, various kinds of industrial equipment such as an injection molding machine and press apparatus can be cited as apparatus in which power is supplied from a power source to some kind of load-side device through a power transmission mechanism. When description is made by taking the injection molding machine as an example, equipment is known that obtains an optional molded object by injecting a soft viscous material such as a resin, metal fiber, or a mixed material of them into a mold in which a predetermined shape is made, through an optional power transmission mechanism with use of a rotating electrical machine (motor) as a power source.
As one example, the injection molding machine will be cited and the configuration and operation thereof will be described. The injection molding machine is configured to obtain a desired molded object by transmitting, by a power transmission mechanism, power of an electric motor as a drive source (in some cases, rotational force or horizontal power like a linear motor) as power for injection into a mold for injection molding and injecting a soft viscous component into a predetermined mold. As a more specific example, an injection shaft integrated with a nut component that is mechanically connected directly or indirectly to a power conversion mechanism such as a ball screw that converts a rotational drive force of the electric motor to linear motion, and screws to linear power of the ball screw that is such a power transmission mechanism is configured to press the soft viscous component against the predetermined mold.
In apparatus typified by the injection molding machine and the press apparatus, managing an abnormality of the whole of a load-side device with a drive source (drive source itself, workpiece mechanism of the load-side device, and so forth) is an important factor that deeply affects the quality of the final molded object. Furthermore, the abnormality causes overload of equipment or a part, and causes also an environmental problem such as the energy efficiency and a problem in terms of business, such as manufacturing stop due to damage to equipment. Thus, it can be said that managing the abnormality of equipment is an issue whose social influence is also large.
Patent document 1 discloses a technique to estimate the state of equipment as a technique relating to such abnormality detection. Specifically, a technique is disclosed that includes an electric motor as a drive source and motor control means that controls it, creates motor control internal values of the motor control means, and estimates an abnormality of equipment through comparison with them. It is a technique that can sense the deterioration of the equipment (load-side device and workpiece component that accompanies it) by monitoring the internal values of the motor control.
Moreover, patent document 2 discloses an abnormality diagnosis device of a power transmission mechanism that executes transmission of power from an electric motor as a drive source, and an abnormality diagnosis method thereof. More specifically, in patent document 2, in a configuration in which the power of the electric motor is connected to a machine facility as a load through a pulley belt and a gear chain, an abnormality of the pulley belt and the gear chain is diagnosed by obtaining a current spectrum waveform from a value transmitted from a current sensor connected to the electric motor, and counting the number of sideband waves other than ones in the frequency bands of the pulley belt and the gear chain generated in association with the rotation speed, on the basis of a spectral peak calculated by analysis from the current spectrum waveform.
In apparatus typified by the injection molding machine and the press apparatus, the power transmission mechanism functions as an intermediary between the power source and an element on which a load is directly generated, such as a mold. Thus, maintenance of the performance of the power transmission mechanism deeply affects the quality (degree of perfection) of a molded object that is the final product, and it is important to manage it.
Here, consideration will be made about abnormality (deterioration) detection of the power transmission mechanism. Regarding the load-side device, the way of application of a load thereto is not uniform in many cases and a part at which the load applied to the power transmission mechanism becomes high and a part at which the load becomes low exist in a mixed manner in many cases. That is, a ball screw, pulley belt, gear chain, or the like is cited as an example of the power transmission mechanism, and a bias is caused in the place at which deterioration occurs in them depending on the load status of the load-side device.
Regarding this point, in the abnormality diagnosis technique of the power transmission mechanism disclosed by the above-described patent document 2, in which an abnormality of the power transmission mechanism is sensed by monitoring the spectral peal from the current spectrum waveform and the sideband waves that accompany it, a problem remains that the sensitivity of sensing of an abnormality lowers when the deterioration of the power transmission mechanism is small or when the deterioration is at the initial stage. That is, when the current spectrum of the electric motor is merely analyzed with respect to the deterioration of the power transmission mechanism, an abnormal value attributed to the deterioration of the power transmission mechanism appears only as an extremely slight swing in many cases, and distinguishing whether this swing is temporary current noise in normal times or a swing attributed to an abnormality involves difficulty. Thus, with only monitoring of the state of the mere current spectrum, an issue remains in the precision of abnormality detection.
Furthermore, abnormal values vary compared with normal values depending on the deterioration of the power transmission mechanism, and it is thought that it is also possible to execute deterioration determination by determining also this variation.
Thus, a technique that senses abnormality detection on the power transmission mechanism with higher precision and probability is desired.
In order to solve the above-described problem, configurations are made as follows.
A management device for a power transmission mechanism that transmits a driving force from an electric motor to a load-side device includes a current acquiring section that acquires a current value of the electric motor per unit process in which the power transmission mechanism is driven, a feature calculating section that divides the unit process into a plurality of zones, and calculates an average current value obtained by averaging the current value of each of the zones, and a diagnosis section that executes abnormality detection. The diagnosis section calculates a state amount estimation value on the basis of the average current value of the plurality of zones and executes abnormality sensing in the unit process on the basis of the state amount estimation value.
Furthermore, a management method for a power transmission mechanism that transmits a driving force from an electric motor to a load-side device includes a current acquisition step of acquiring a current value per unit process in which the power transmission mechanism is driven, an average current value calculation step of dividing the unit process into a plurality of zones and calculating an average current value obtained by averaging the current value of each of the zones, and an abnormality detection step of executing abnormality detection. The abnormality detection step calculates a state amount estimation value on the basis of the average current value of the plurality of zones and executes abnormality sensing in the unit process on the basis of the state amount estimation value.
According to the present invention, a management device, a management method, and a management system that can sense abnormality (deterioration) detection on a power transmission mechanism with higher precision and probability can be implemented.
In particular, according to the present invention, there is an effect of improvement in the precision and the probability with which sensing as an abnormality is allowed even when an abnormality (deterioration) of the power transmission mechanism is small or even when an abnormality (deterioration) is at the initial stage.
Other problems, configurations, and effects of the present invention will become apparent from the following description.
Modes for carrying out the present invention will be described in detail below with use of the drawings.
In
First, the mechanical configuration and operation of the injection molding machine 1 will be described. The injection molding machine 1 converts rotation of a plurality of motors to linear motion to drive a single linear movement component and, at this time, synchronously operates the plurality of motors in such a manner that the progression positions thereof are aligned. The configuration to which the present invention can be applied may be a configuration in which a driving force is supplied to a plurality of power transmission mechanisms through gears by a single motor or a configuration in which a driving force is supplied to a single power transmission mechanism by a single motor.
In the injection molding machine 1, a molten resin is poured from a hole 11 provided in a fixed mold 12B of a mold 12, and a resin molded object according to the shape of a gap that exists between the movable mold 12A and the fixed mold 12B can be fabricated. The mold 12 having the movable mold 12A and the fixed mold 12B is one example of a load-side device.
The mold includes the fixed mold 12B fixed to a casing and the movable mold 12A that moves forward and rearward. The injection molding machine 1 includes a motor 13 that is an electric motor, a pulley 14 made to adhere to an output shaft of the motor 13, a driven pulley 15, a timing belt 16 that transmits rotation of the drive pulley 14 to the driven pulley 15, a ball screw mechanism 20 as a power transmission mechanism that converts rotation of the pulley 15 to linear motion and transmits the linear motion to the movable mold 12A, and the controller 30.
The motor 13 includes an encoder (not illustrated) that outputs a motor position signal S2 indicating the progression position thereof (equivalent to the progression position of the ball screw mechanism 20). The injection molding machine 1 controls driving of the motor 13 through reception, by the controller 30, of a speed command signal S0 from an upper-level device that is not illustrated.
When the motor 13 is driven, the rotation thereof is transmitted to a screw shaft 17 of the ball screw mechanism 20 through the drive pulley 14, the timing belt 16, and the driven pulley 15, and a nut part 18 that screws to grooves thereof with the interposition of balls converts the rotational force to linear motion. The movable mold 12A is integrated with or mechanically coupled to the nut part 18, and the movable mold 12A also linearly moves according to the linear motion of the nut part 18. As a result, the movable mold 12A gets closer to or further away from the fixed mold 12B. A resin is poured and molded after the movable mold 12A is brought into contact with the fixed mold 12B. Then, after having solidified through cooling, the molded object is taken out by separating the movable mold 12A from the fixed mold 12B.
For example, the controller 30 is configured to have a microcomputer for embedded equipment including CPU, ROM, RAM, EEPROM, various I/O interfaces, and so forth, and executes various functions by cooperation with a program. The controller 30 executes control of the injection molding machine 1 to execute control of the whole of the molding processes such as plasticization operation, injection operation, mold opening-closing operation, and ejection operation. The present invention is not limited to the present embodiment and part thereof may be configured by an analog circuit.
Subsequently, the controller 30 will be described as a functional configuration.
In
An inverter 40 is controlled by a motor control section 41 to which a commonly called vector control system is applied. The motor control section 41 acquires pieces of information such as the motor current, the motor voltage, position information of a rotor, and the rotation speed from the inverter 40 or the motor 13, and creates a voltage command value for driving the motor 13 on the basis of these pieces of information in response to a command from an upper-level controller. Then, the motor control section 41 gives the created voltage command value to the inverter 40.
An external data acquiring section 47 is configured from a sensor or the like installed on a component other than the motor 13 and the inverter 40, and acquires the temperature of the equipment, the ambient temperature, an upper-level command value of the equipment, and so forth.
A state estimating section 42 includes a control internal value creating section 43 that creates internal values of the motor control, and a state calculating section 44 that calculates features and a state amount relating to the injection molding machine 1 on the basis of the internal values of the motor control created by the control internal value creating section 43.
The control internal value creating section 43 creates the internal values of the motor control that are state variables in the motor control section 41 and relate to the state of the injection molding machine 1, on the basis of time-series data acquired by a current sensor, a voltage sensor, and a position sensor independently installed on an input part or an output part of the motor 13 separately from ones for the motor control section 41, and the data acquired by the external data acquiring section 47. The control internal value creating section 43 corresponds to the current acquiring section.
The state calculating section 44 has a state estimation model, and calculates the state amount indicating the state of the equipment system, that is, the state of the equipment itself and the state (quality and so forth) of a manufactured object manufactured by the equipment, by using the state estimation model on the basis of the motor control internal values created by the motor control internal value creating section 43. That is, the data acquired by the above-described respective sensors and the external data acquiring section 47 is input to the state estimating section 42, and the state estimating section 42 creates the internal values of the motor control created from the input data and outputs the state amount calculated based on the created internal values of the motor control or information relating to the state of the injection molding machine 1 indicated by this state amount (hereinafter, referred to as “estimated state”). The estimated state output from the state estimating section 42 is transmitted to an information transmitting section 45 and a motor control updating section 46 to be described later. The information transmitting section 45 is also the display section.
According to the estimated state output from the state estimating section 42, the information transmitting section 45 notifies a worker who uses the equipment system or an administrator of the equipment system of information relating to the state of the injection molding machine 1, for example, features of the equipment itself (deterioration determination of the screw shaft 17 that will be described later, or the like) or information relating to the quality of the manufactured object or a change therein, by a display, sound, lamp, vibration, or the like. This can alleviate the work burden in grasping of the maintenance timing of the equipment, grasping of the status at the time of change in the quality, equipment adjustment work, and so forth.
The motor control updating section 46 changes the motor control section 41, that is, a control command, a control parameter, or control software, on the basis of the estimated state output from the state estimating section 42. For example, when the quality of the manufactured object has changed, the motor control updating section 46 changes the motor control section 41 so as to suppress the change in the quality. This allows automation of adjustment work of the injection molding machine 1 and thus the work burden is alleviated.
Next, further details will be described about the motor control section 41 and the state estimating section 42.
In
As illustrated in
When the speed command ω* is input to a torque command creating section 102, the torque command creating section 102 creates and outputs the torque command Trq* on the basis of the difference between a speed (rotation speed) feedback value ωm actually measured by the sensor and the speed command ω*.
When the torque command Trq* is input to a current command creating section 103, the current command creating section 103 creates and outputs current commands on the dq-axes in a rotating coordinate system, that is, a d-axis current command Id* and a q-axis current command Iq*, on the basis of the torque command Trq*.
When the d-axis current command Id* and the q-axis current command Iq* are input to a voltage command creating section 104, the voltage command creating section 104 creates and outputs voltage commands on the dq-axes, that is, a d-axis voltage command Vd* and a q-axis voltage command Vq*, on the basis of the difference between a d-axis current feedback value Id and the d-axis current command Id* and the difference between a q-axis current feedback value Iq and the q-axis current command Iq*.
Here, the d-axis current feedback value Id and the q-axis current feedback value Iq are obtained by executing, by a three-phase/two-phase transformation section 106, three-phase/two-phase transformation of a U-phase current feedback value Iu, a V-phase current feedback value Iv, and a W-phase current feedback value Iw of the motor actually measured by the sensor.
When the d-axis voltage command Vd* and the q-axis voltage command Vq* are input to a two-phase/three-phase transformation section 105, the two-phase/three-phase transformation section 105 transforms the d-axis voltage command Vd* and the q-axis voltage command Vq* to a U-phase voltage command Vu*, a V-phase voltage command Vv*, and a W-phase voltage command Vw* and outputs these voltage commands to the inverter 40.
Next, the state estimating section 42 will be described.
As described above (see
In
As illustrated in
In
By the configuration illustrated in
In the present embodiment, θ*, θm, ω*, ωm, Trq*, Id*, Iq*, Id, Iq, Vd*, Vq*, Vu*, Vv*, Vw*, Vu, Vv, Vw, Iu, Iv, and Iw, which are state variables of the motor control section 41, the difference between the command value and the actual measurement value, and output values of a proportion section, an integration section, and a derivation section that configure a control section are the internal values of the motor control. That is, any one or a plurality of these motor control internal values in the motor control section 41 are created by the control internal value creating section 43.
In the present embodiment, state variables that are created and used in the process of processing by the motor control section 41 and are not output from the motor control section 41 (for example, Id*, Iq*, Id, Iq, Vd*, Vq*) in the state variables of the motor control section 41 can also be created by the control internal value creating section 43 illustrated in
As described above, the state calculating section 44 (see
X1 to Xn in
The kind and quantity of the internal values of the motor control and the information acquired by the external data acquiring section 47 input to the state calculating section 44 are set according to the configuration (for example, statistical model to be described later) of the state calculating section 44.
In
In the configuration example of
The internal value Xn and the information Zn are input to the feature calculating section 121 and the feature calculating section 121 calculates a feature (explanatory variable) Cn to be used as an input to the computing section 122 on the basis of the input Xn and Zn. The feature calculating section 121 outputs instantaneous data of Xn and Zn directly as the feature Cn without processing the data or outputs a result (amplitude, phase, and so forth) of frequency analysis of the instantaneous data of Xn and Zn in a predetermined time zone, the effective value, average value (current average value or the like), standard deviation, maximum value, or minimum value in a predetermined time zone, or the overshoot amount or the peak value in a predetermined time zone. The number of features Cn may be either single or multiple depending on the regression expression.
Moreover, the feature calculating section 121 may output a predetermined quantity computed from the internal value of the motor control, for example, active power, reactive power, or the like, as the feature. Furthermore, disturbance torque or the like estimated by a commonly called observer may be employed as the feature. These features may be output after frequency analysis, statistical calculation (average), or the like is further executed for them.
The features C1 to Cn output from the feature calculating section 121 are input to the computing section 122, and the computing section 122 calculates state amount estimation values (Ya, Yb) on the basis of the features C1 to Cn.
Here, description will be made about calculation of the feature relating to the power transmission mechanism (in particular, screw shaft 17 of the ball screw mechanism 20) by the injection molding machine 1 and an abnormality determination method of the equipment, which are one of characteristics of the present embodiment.
As above, the feature calculating section 121 can sense the deterioration of the screw shaft 17 by monitoring the change in the current value from the start position (start time) to the end position (end time).
However, there is a problem that generally it is remarkably difficult to determine change in the current, for example, in the case in which deterioration is at the initial stage or in the case of a swing of noise or the like in the current value. That is, this is because the difference from the normal current value becomes slight in these cases.
Thus, in the present embodiment, the process in which the ball screw mechanism 20 reaches the end point from the start point is divided into a predetermined plurality of regions and the average value of the current value in each region is calculated. The difference value between the average value of the current when the state of the ball screw mechanism 20 has been defined as the normal state in advance and the average value of the current at the time of diagnosis is calculated regarding each region. Thereafter, the maximum value of the calculated difference value of each region is extracted as the feature. By comparing this feature and the threshold defined in advance, whether or not deterioration of the screw shaft 17 exists and the degree of deterioration are determined.
In
The feature calculating section 121 and the computing section 122 measure current values equal to or smaller than a threshold (normal values) in current values sensed at predetermined time intervals in each zone and the number of current values equal to or smaller than the threshold, and calculate the average thereof. Similarly, the feature calculating section 121 and the computing section 122 measure current values larger than the threshold (abnormal values) in the current values sensed at the predetermined time intervals in each zone and the number of current values larger than the threshold, and calculates the average thereof. Thereafter, the feature calculating section 121 and the computing section 122 output these results to the state estimating section 42.
In
In
In contrast, it turns out that, in the case of executing the above-described deterioration determination processing illustrated in
As above, according to the present embodiment, one process is divided into a plurality of zones, the average values of the normal value and the abnormal value of each zone are calculated, and the value of the highest abnormal value average among them is deemed as the target of deterioration determination. Thus, deterioration detection on the power transmission mechanism can be sensed with higher precision and probability. In particular, according to the present invention, an effect of improvement in the precision and the probability with which sensing as an abnormality is allowed even when deterioration of the power transmission mechanism is small or even when deterioration is at the initial stage can be expected.
Here, the abnormal value often varies compared with the normal value depending on deterioration of the power transmission mechanism, and it is thought that it is also possible to execute deterioration determination by determining also this variation.
By determining the above-described variation, abnormality detection on the power transmission mechanism can be sensed with higher precision and probability.
In this case, a state amount E increases while fluctuating from the date and time to toward the date and time t3. However, the state amount E makes the transition with normal fluctuation width (variation). Regarding the period from the date and time t3 to t4, the fluctuation width (variation) of the state amount E is larger than the fluctuation width (variation) of the period from the date and time t0 to t3 and it can be determined that an abnormality has occurred.
The difference (absolute value) between pk1 (maximum average current value) that is the feature of the maximum value in the region in which the difference is positive and pk2 (minimum average current value) that is the feature of the minimum value in the region in which the difference is negative is deemed as the state amount estimation value, and whether or not an abnormality has occurred can be determined from this state amount estimation value.
The “reference current value serving as the basis” used for the feature calculation may be generated by the state estimating section 42 or may be prepared as a profile by the user in advance. Furthermore, it is also possible that the user obtains an average current value and sets it as the reference value in advance.
In a step S1 in
In the step S3, whether or not the calculated feature is smaller than the minimum feature is determined. When the calculated feature is smaller than the minimum feature, the processing proceeds to a step S4 and the calculated feature is defined as the minimum feature, and the processing proceeds to a step S5. When the calculated feature is larger than the minimum feature in the step S3, the processing proceeds to the step S5.
In the step S5, the minimum feature is subtracted from the maximum feature to make the state amount estimation value.
Determination of abnormality occurrence can be executed through comparing the obtained state amount estimation value with a normal state amount estimation value defined in advance. The determination of abnormality occurrence is executed in the computing section 122 and the result thereof can be displayed on the information transmitting section 45. Furthermore, it is also possible to display, on the information transmitting section 45, the graph illustrated in
The management method of the present invention is a management method for a power transmission mechanism that transmits a driving force from an electric motor to a load-side device, and includes a current acquisition step of acquiring the current value per unit process in which the power transmission mechanism is driven, an average current value calculation step of dividing the unit process into multiple zones and calculating the average current value obtained by averaging the current value of each zone, and an abnormality detection step of executing abnormality detection. The abnormality detection step calculates the state amount estimation value on the basis of the average current value of the multiple zones and executes abnormality sensing in the unit process on the basis of the state amount estimation value.
According to embodiment example 1 of the present invention, one process (time zone) is divided into multiple zones, the difference between the average value of the current value of each zone and the normal value is calculated, and the maximum value among them is defined as the feature. Furthermore, the variation (pk-pk value) in the feature in multiple processes (multiple time zones) is calculated as the state amount estimation value, and an abnormality of the power transmission mechanism is determined based on the calculated state amount estimation value.
Thus, it is possible to implement a management device and a management method that can sense abnormality (deterioration) detection on the power transmission mechanism with higher precision and probability. In particular, according to the present invention, there is an effect of improvement in the precision and the probability with which sensing as an abnormality is allowed even when an abnormality (deterioration) of the power transmission mechanism is small or even when an abnormality (deterioration) is at the initial stage.
Next, embodiment example 2 of the present invention will be described.
The overall configuration of embodiment example 2 of the present invention is similar to that of embodiment example 1, and therefore illustration and detailed description are omitted.
In the above-described embodiment example 1, the configuration in which the peak value and the peak value of the features are sensed and the state amount estimation value (pk-pk value) is calculated as illustrated in
In contrast, in embodiment example 2, the average value of the features in the region in which the current value difference from a reference current value Io indicated at the center of the ordinate axis of the graph of
Then, determination of an abnormality is executed by using the state amount estimation value (abs(FVave1−FVave2)).
In a step S10 in
When the feature is smaller than 0 in the step S10, the processing proceeds to a step S13. In the step S13, cumulative addition of the second average current value group is executed (FVsigma2←FVsigma2+feature). Then, the processing proceeds to a step S14, n2+1 is employed as n2, and the processing proceeds to the step S15.
In the step S15, whether or not n is the last value is determined. When n is not the last value, the processing ends.
When n is the last value in the step S15, the processing proceeds to a step S16 and derivation (calculation) of the first average current value group average value is executed (FVave1←FVsigma1/n1). Then, the processing proceeds to a step S17 and derivation (calculation) of the second average current value group average value is executed (FVave2←FVsigma2/n2). Then, the processing proceeds to a step S18, the state amount estimation value is set to abs(FVave1−FVave2), and the processing is ended.
Also in embodiment example 2 of the present invention, effects similar to those of embodiment example 1 can be obtained.
Next, embodiment example 3 of the present invention will be described.
The overall configuration of embodiment example 3 of the present invention is similar to that of embodiment example 1, and therefore illustration and detailed description are omitted.
In embodiment example 1, the configuration in which the peak value (positive side) and the peak value (negative side) of the features are sensed and the state amount estimation value (pk-pk value) is calculated as illustrated in
In contrast, in embodiment example 3, as illustrated in
In the step S22, the number N1 of features in the time zones in which the feature is positive and the number N2 of features in the time zones in which the feature is negative are calculated. Then, in a step S23, whether or not the number N1 is larger than the number N2 is determined. When the number N1 is larger than the number N2, the processing proceeds to a step S24, the value with which the absolute value of the difference becomes the maximum is calculated from the data group CL1 about which the feature is positive, and the processing proceeds to a step S26.
When the number N1 is not larger than the number N2 in the step S23, the processing proceeds to a step S25, the value with which the absolute value of the difference becomes the maximum is calculated from the data group CL2 about which the feature is negative, and the processing proceeds to the step S26.
In the step S26, the state amount estimation value is calculated, and the processing is ended.
Also in embodiment example 3 of the present invention, effects similar to those of embodiment example 1 can be obtained. In addition, there is an effect of improvement in the precision and the probability with which sensing as an abnormality is allowed in abnormality diagnosis (abnormality sensing) of the power transmission mechanism in which load fluctuation is frequently large or the power transmission mechanism in a transient state.
Next, embodiment example 4 of the present invention will be described.
The overall configuration of embodiment example 4 of the present invention is similar to that of embodiment example 1, and therefore illustration and detailed description are omitted.
In embodiment example 4, as illustrated in
In a step S30 in
In the step S31, whether or not the calculated feature is larger than feature max is determined. When the calculated feature is larger than feature max, the processing proceeds to a step S32, the calculated feature is defined as the maximum feature (feature max), and the processing proceeds to a step S33. When the calculated feature is equal to or smaller than feature max in the step S31, the processing proceeds to the step S33.
In the step S33, whether or not the calculated feature is smaller than feature min is determined. When the calculated feature is smaller than feature min, the processing proceeds to a step S34, the calculated feature is defined as the minimum feature (feature min), and the processing proceeds to a step S35. When the calculated feature is equal to or larger than feature min in the step S33, the processing proceeds to the step S35.
In the step S35, feature min is subtracted from feature max to make the state amount estimation value.
Also in embodiment example 4 of the present invention, effects similar to those of embodiment example 1 can be obtained. In addition, there is an effect of improvement in the precision and the probability with which sensing as an abnormality is allowed in abnormality diagnosis (abnormality sensing) in the power transmission mechanism in which noise is frequently large.
Next, embodiment example 5 of the present invention will be described.
The overall configuration of embodiment example 5 of the present invention is similar to that of embodiment example 1, and therefore illustration and detailed description are omitted.
Embodiment example 5 is an example in which an abnormality such as mixing with foreign matter occurs in the power transmission mechanism and the occurrence of the abnormality and the abnormality place can be sensed. Embodiment example 5 is an example that can be applied in addition to the abnormality sensing in embodiment examples 1 to 4.
In
In the time from the start of the abnormality diagnosis to the end of the diagnosis, in the case in which an abnormality such as mixing with foreign matter has occurred, the current value changes in a pulsed manner as illustrated by a dashed line. In this case, similarly to the current waveform in abnormal times, the feature also suddenly rises and thereafter falls down in a short time, as illustrated by a dashed line, when the abnormality such as mixing with foreign matter has occurred. The amount of rise of the feature is a state amount estimation value. Furthermore, the position at which the abnormality such as mixing with foreign matter has occurred corresponds to the timing when the feature has risen up and fallen down between the time position of the rotation start of the motor 13 and the end time. A position X of the motor 13 at this time can be extracted and a position corresponding to it, for example, the position of the screw shaft 17, can be extracted.
As illustrated in
In a step S40 in
In the step S42, whether or not the feature is smaller than an abnormality threshold (negative side) is determined. When the feature is smaller than the abnormality threshold (negative side), in a step S43, the feature is employed as a state amount estimation value m and a position Xm of the screw shaft 17 at the time of abnormality occurrence is issued. Then, the processing is ended. Furthermore, the processing is ended also when the feature is not smaller than the abnormality threshold (negative side) in the step S42.
Also in embodiment example 5 of the present invention, effects similar to those of embodiment examples 1 to 4 can be obtained. In addition, when an abnormality such as mixing with foreign matter has occurred in the power transmission mechanism, the occurrence of the abnormality and the abnormality place can be sensed and issued.
In the above-described embodiment examples 1 to 4, each of the graphs illustrated in
Moreover, the present invention can implement a management system including the above-described management device 30 and the power transmission mechanism. The power transmission mechanism in the management system can include the drive pulley 14, the driven pulley 15, the timing belt 16, the ball screw mechanism 20, and the nut part 18. However, the power transmission mechanism applied to the management system of the present invention is not limited to the above-described example and can be applied also to a power transmission mechanism such as a gear mechanism, for example.
Furthermore, it goes without saying that the present invention is not limited to the above-described various configurations and functions, and various kinds of changes and replacement can be made in such a range as not to depart from the gist thereof. For example, the injection molding machine 1 is employed as an application example in the above-described embodiment. However, the present invention can be applied to what transmits power of a motor that is a drive source of a load-side device to load-side equipment through a power transmission mechanism, such as press apparatus and cutting apparatus, as already described.
Moreover, in the above-described embodiment, the deterioration determination based on the feature is executed regarding the screw shaft 17 of the ball screw mechanism 20 as the power transmission mechanism. However, it is also possible to apply the present invention to the deterioration determination of the timing belt 16 or a chain or the like instead of it as the power transmission mechanism.
Furthermore, in the above-described embodiment, the ball screw mechanism 20 is applied as the power transmission mechanism. However, the present invention can be applied also to a screw mechanism composed of a screw bolt and a nut without the interposition of balls.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2021-210040 | Dec 2021 | JP | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/JP2022/021182 | 5/24/2022 | WO |
