WO2022185743A1

WO2022185743A1 - Displacement sensor, and state monitoring method

Info

Publication number: WO2022185743A1
Application number: PCT/JP2022/001363
Authority: WO
Inventors: 祐太鈴木; 義宏金谷; 雄介飯田
Original assignee: オムロン株式会社
Priority date: 2021-03-01
Filing date: 2022-01-17
Publication date: 2022-09-09
Also published as: TW202235823A; JP7662997B2; TWI802234B; JP2022132827A; CN116888428A

Abstract

Provided are a displacement sensor and a state monitoring method with which it is possible for an abnormality type to be appropriately determined. A displacement sensor 10 is provided with: a light projecting unit 110 for projecting light onto an inspection region; a light receiving unit 120 for receiving light reflected by the inspection region and outputting a received light waveform; a storage unit 140 for storing, in advance, abnormality type information associating a plurality of items of feature information included in the received light waveform and a plurality of abnormality types predicted from the plurality of items of feature information; a feature information extracting unit 131 for extracting at least two types of feature information on the basis of the received light waveform output by the receiving unit; an abnormality type determining unit 132 for determining at least one abnormality type, from among the plurality of abnormality types in the abnormality type information stored in advance in the storage unit, on the basis of the at least two types of extracted feature information; and an output unit 133 for outputting the determined abnormality type.

Description

Displacement sensor and condition monitoring method

The present invention relates to a displacement sensor and a state monitoring method.

Conventionally, a displacement sensor using an optical system has been used as a non-contact device for measuring the displacement of a workpiece. With such a displacement sensor, there is a risk that the workpiece cannot be measured properly due to deterioration over time of the displacement sensor, contamination due to adherence of foreign matter such as dust, influence of the surrounding environment, and the like.

Patent Document 1 discloses a technique related to a detection device that detects signs of an abnormality in a detection sensor before an abnormality occurs in the detection sensor. Specifically, the detection device disclosed in Patent Document 1 acquires the amount of light received by the light receiving unit when the workpiece passes through the detection position at regular intervals, and generates a light reception waveform based on the acquisition result. do. Then, the detection device determines whether or not there is a sign of abnormality in the detection sensor by comparing the reference waveform and the received light waveform.

JP 2012-78175 A

However, in the detection device disclosed in Patent Document 1, although it is determined whether or not there is a sign of abnormality in the detection sensor, even if a sign of abnormality is detected, the cause and details are classified. I haven't been able to. For this reason, there is a problem that the user cannot grasp what concrete countermeasures need to be taken thereafter.

Therefore, an object of the present invention is to provide a displacement sensor and a state monitoring method that can appropriately determine the type of abnormality.

A displacement sensor according to an aspect of the present invention includes a light projecting unit that projects light onto an inspection area, a light receiving unit that receives light reflected by the inspection area and outputs a received light waveform, and a plurality of sensors included in the received light waveform. a storage unit in which abnormality type information in which the characteristic information and a plurality of abnormality types predicted from the plurality of characteristic information are associated in advance; A feature information extraction unit for extracting the above feature information, and at least one or more of a plurality of abnormality types in the abnormality type information pre-stored in the storage unit based on at least two or more extracted feature information. and an output unit for outputting the determined abnormality type. Here, the received light waveform is generated as a waveform indicating the amount of light received by each pixel of the light received by the imaging device of the light receiving unit.

According to this aspect, the characteristic information extraction unit extracts at least two pieces of characteristic information based on the received light waveform, and the abnormality type determination unit detects abnormality type information pre-stored in the storage unit based on the characteristic information. It is possible to appropriately determine at least one type of abnormality among the plurality of types of abnormality in .

In the above aspect, the abnormality type determination unit monitors the feature information to be extracted by at least one of the amount of difference from a reference value, the amount of change in a predetermined period, and the information included in the received light waveform at a certain point in time. may be used to determine the abnormality type.

According to this aspect, the abnormality type determination unit uses a plurality of types of monitoring methods to determine the abnormality type, so that the abnormality type can be determined more appropriately.

In the above aspect, among the plurality of abnormality types in the abnormality type information pre-stored in the storage unit, an abnormality type that can be determined according to the monitoring method may be classified.

According to this aspect, in the abnormality type information, the abnormality types that can be determined according to the monitoring method are classified. Therefore, in determining the abnormality type, an appropriate monitoring method can be used according to each abnormality type.

In the above aspect, the feature information may include at least two of the amount of received light, the parameter for adjusting the amount of received light, the width value of the received light waveform, the number of surfaces of the received light waveform, the total area of the received light waveform, and the background level. .

According to this aspect, for the feature information extracted from the received light waveform, at least two of the received light amount, the received light amount adjustment parameter, the width value of the received light waveform, the number of surfaces of the received light waveform, the total area of the received light waveform, and the background level. Since more than one type is included, the abnormality type can be determined more specifically based on these.

In the above-described aspect, the abnormality type determination unit determines the amount of received light, the parameter for adjusting the amount of received light, the width value of the received light waveform, the number of surfaces of the received light waveform, the total area of the received light waveform, and the background level. The type of abnormality may be determined by

According to this aspect, the abnormality type determination unit appropriately combines a plurality of pieces of feature information to determine each abnormality type, so it is possible to more appropriately determine the abnormality type.

In the above aspect, among the plurality of abnormality types in the abnormality type information pre-stored in the storage unit, the received light amount, the received light amount adjustment parameter, the width value of the received light waveform, the number of surfaces of the received light waveform, the total area of the received light waveform, and Abnormality types that can be determined may be classified according to a combination of at least two types of background levels.

According to this aspect, the abnormality type information includes a combination of at least two of the amount of received light, the parameter for adjusting the amount of received light, the width value of the received light waveform, the number of surfaces of the received light waveform, the total area of the received light waveform, and the background level. Since the types of abnormality that can be determined are classified according to the type of abnormality, it is possible to appropriately combine feature information according to each type of abnormality in determining the type of abnormality.

In the above aspect, among the plurality of abnormality types in the abnormality type information pre-stored in the storage unit, an abnormality type that can be determined may be classified according to the presence or absence of a workpiece and a base in the inspection area. The work is an object to be measured by the displacement sensor, and the base is a base on which the work is placed.

According to this aspect, the abnormality type can be appropriately determined according to the presence or absence of the work and base in the inspection area.

In the above aspect, the output unit may output countermeasures or presumed causes corresponding to the determined abnormality type.

According to this aspect, the user can directly and specifically grasp what kind of measures should be taken.

A state monitoring method according to an aspect of the present invention is a state monitoring method executed by a displacement sensor including a processor, comprising: a light projecting step of projecting light onto an inspection area; a light receiving step of outputting a light receiving waveform; a feature information extracting step of extracting at least two types of feature information based on the light receiving waveform output in the light receiving step; out of the plurality of abnormality types in the abnormality type information stored in advance in the memory, in which the plurality of characteristic information included in the received light waveform and the plurality of abnormality types predicted from the plurality of characteristic information are associated with each other , an abnormality type determination step of determining at least one type of abnormality type, and an output step of outputting the determined abnormality type.

According to this aspect, in the feature information extraction step, at least two pieces of feature information are extracted based on the received light waveform, and in the abnormality type determination step, based on the feature information, the abnormality type information pre-stored in the memory At least one type of abnormality among the plurality of types of abnormality can be appropriately determined.

According to the present invention, it is possible to provide a displacement sensor and a state monitoring method that can appropriately determine the type of abnormality.

1 is a perspective view showing the appearance of a sensor head of a displacement sensor 10 according to an embodiment of the invention; FIG. It is a block which shows each function which comprises the displacement sensor 10 which concerns on one Embodiment of this invention. FIG. 3 is a block diagram showing a control unit 130 involved in abnormality type determination processing and each functional configuration related thereto in the displacement sensor 10 according to one embodiment of the present invention. It is a figure which shows an example of the characteristic information extracted from a light reception waveform. It is a figure which shows an example of the abnormality classification information in which characteristic information and the abnormality classification predicted from the said characteristic information are matched. (a) It is a figure which shows an example which determines sensor contamination. (b) It is a figure which shows an example which determines light source deterioration. (c) It is a figure which shows an example which determines narrow space measurement. (d) A diagram showing an example of determining multiple reflections. (e) A diagram showing an example of determining mutual interference. (f) It is a figure which shows an example which determines disturbance light. FIG. 5 is a diagram showing an example of displaying an abnormality type on a display unit 150 provided in an amplifier unit; It is a figure which shows an example of the error code matched with abnormality classification, and countermeasure. 4 is a flow chart showing the flow of processing of a state monitoring method M10 for monitoring the state of the displacement sensor 10 and its surrounding environment, including abnormality type determination, while the displacement sensor 10 measures the workpiece W. FIG. FIG. 10 is a flow chart showing a specific process flow of an abnormality type determination method M100 executed in steps S15 to S18 in FIG. 9; FIG. FIG. 6 is a diagram showing an example of an abnormality type that cannot be determined according to the presence or absence of a workpiece and a base in an inspection area among the abnormality types in FIG. 5 ; FIG. 10 is a diagram showing an example of abnormality type information in which characteristic information used and predicted abnormality types are associated with each monitoring method;

Hereinafter, embodiments of the present invention will be specifically described with reference to the drawings. It should be noted that the embodiments described below are merely specific examples for carrying out the present invention, and are not intended to limit the interpretation of the present invention. Also, in order to facilitate understanding of the description, the same reference numerals are given to the same constituent elements in each drawing as much as possible, and redundant description may be omitted.

<One embodiment>
[Configuration of displacement sensor]
FIG. 1 is a perspective view showing the appearance of a sensor head of a displacement sensor 10 according to one embodiment of the invention. The displacement sensor 10 includes a sensor head 100 and an auxiliary housing (not shown) called an amplifier unit connected via a cable 11 .

As shown in FIG. 1, the displacement sensor 10 emits a laser beam L1 from the sensor head 100 onto the workpiece W placed on the base B, and reflects the laser beam L1 from the workpiece W. is received, the amount of displacement of the surface of the work W is measured based on the principle of triangulation. It should be noted that what is measured as the amount of displacement is the distance from the sensor head 100 to the surface of the workpiece W, and the distance can be output as detection data.

As described above, the displacement sensor 10 is normally a measuring device that projects a laser beam onto the work W and measures the amount of displacement of the surface of the work W. In the present embodiment, for example, the work W If it does not exist, condition monitoring may be performed by projecting a laser beam and receiving reflected light from the inspection area, using equipment such as an assembly robot and the surrounding environment as the inspection area.

FIG. 2 is a block showing each function constituting the displacement sensor 10 according to one embodiment of the present invention. As shown in FIG. 2, the displacement sensor 10 includes a light projecting unit 110, a light receiving unit 120, a control unit 130, a storage unit 140, a display unit 150, an operation unit 160, and an input/output interface 170. Prepare. Note that the light projecting unit 110 includes a light emitting element 111 and a light projecting control circuit 112 , and the light receiving unit 120 includes an imaging device 121 , a signal processing circuit 122 and an A/D conversion circuit 123 .

Note that, for example, the light projecting unit 110, the light receiving unit 120, the control unit 130, and the storage unit 140 are incorporated in the sensor head 100 shown in FIG. provided in the department. However, it is not always necessary to separate the sensor head 100 and the amplifier section, and the entire configuration shown in FIG. 2 may be provided in one housing.

The light projecting unit 110 projects light onto the inspection area (for example, the workpiece W). Specifically, the light projection unit 110 has a laser diode (LD) as the light emitting element 111, and the light emitting element 111 is driven while the light emission intensity and light emission time of the light emitting element 111 are adjusted by the light projection control circuit 112. to emit light. It should be noted that the light projection control circuit 112 operates based on commands from the control section 130 .

The light receiving unit 120 receives the light reflected by the inspection area and outputs a received light waveform. Specifically, the light receiving unit 120 has a CMOS including a plurality of pixels as the image sensor 121, and further includes a signal processing circuit 122 for processing image signals generated by the image sensor 121 and an A/D converter. It has a circuit 123 . The signal processing circuit 122 controls the timing of the operation of the imaging device 121 based on commands from the control unit 130 , takes in an image generated by the imaging device 121 , and outputs the image to the A/D conversion circuit 123 . The image analog-to-digital converted by the A/D conversion circuit 123 is input to the control section 130 for measurement processing.

The control unit 130 is, for example, a CPU, and causes the light projecting unit 110 to emit the laser light L1 based on a program, setting data, and the like stored in the storage unit 140, and receives light in accordance with the emission timing. The part 120 is operated to receive the reflected light L2 from the workpiece W. Then, the control unit 130 measures the amount of displacement of the workpiece W through various processes based on the received light waveform output by the light receiving unit 120 .

Also, based on the received light waveform output by the light receiving unit 120, the control unit 130 extracts feature information included in the received light waveform, and determines an abnormality type estimated from the extracted feature information. The details of the process of determining the abnormality type in the displacement sensor 10 will be described later.

The storage unit 140 is, for example, a non-volatile memory such as an EEPROM, and stores programs, setting data for defining various operations controlled by the control unit 130, and an abnormality type used in processing for determining an abnormality type described later. information is stored. It is also set as a buffer function for accumulating data such as the received light waveform output by the light receiving unit 120 and the characteristic information extracted from the received light waveform, which are used in the process of determining the type of abnormality described later.

The display unit 150 is composed of, for example, a liquid crystal display or an organic EL display, and displays the values measured by the control unit 130 described above, the abnormality type described later, countermeasures corresponding to the abnormality type, and other settings related to the displacement sensor 10. and information to be notified to the user, such as status, etc., are displayed.

The operation unit 160 is composed of buttons, a dial, a touch panel, or the like, and is used, for example, to allow the user to turn on/off the power of the displacement sensor 10, make various settings, switch operation modes, and the like.

The input/output interface 170 is connected to external devices such as a PC (personal computer) and a PLC (programmable logic controller). When connected to an external device, the same operation as that performed by the operation unit 160 can be performed on the external device. For example, the displacement sensor 10 may be operated on the PC, or the measurement results obtained by the displacement sensor 10 may be displayed on the screen of the PC.

[Abnormality type determination processing]
Next, the abnormality type determination processing performed by the displacement sensor 10 will be described in detail. Here, the abnormality type determination processing is, for example, an abnormality that makes it impossible to properly measure the workpiece W or the like due to aged deterioration of the displacement sensor 10, contamination due to the adhesion of foreign matter such as dust, or the influence of the surrounding environment. It is a function to detect symptoms.

FIG. 3 is a block diagram showing the control unit 130 involved in abnormality type determination processing and each functional configuration related thereto in the displacement sensor 10 according to one embodiment of the present invention. As shown in FIG. 3, the control unit 130 includes a characteristic information extraction unit 131, an abnormality type determination unit 132, and an output unit 133, and determines the abnormality type while referring to the storage unit 140, and displays the result on the display unit. Output to 150.

The feature information extraction unit 131 extracts at least two types of feature information based on the received light waveform output by the light receiving unit 120 . Specifically, the characteristic information extraction unit 131 extracts a plurality of pieces of characteristic information, which will be described later, based on the received light waveform continuously output by the light receiving unit 120 , and accumulates them in the storage unit 140 .

FIG. 4 is a diagram showing an example of feature information extracted from the received light waveform. In the figure, the pixel position indicates the position in the base line direction in triangulation with respect to the pixel on the image sensor 121, and the LSB indicates the average value of the amount of received light of the pixel corresponding to the pixel position. As shown in FIG. 4, from the received light waveform, (1) received light amount, (2) received light amount adjustment parameter, (3) width value, (4) number of surfaces, (5) received light waveform total area, and (6) A background level is extracted.

Note that (1) the amount of received light is the amount of light received by the light receiving unit 120, and (2) the parameter for adjusting the amount of received light is a received light waveform corresponding to the amount of light received by the light receiving unit 120. Adjustments (for example, gain, exposure time, etc.) necessary for output. (3) The width value is, for example, the width (half width) of the received light waveform at 50% of the peak received light amount, and indicates the spread of the received light waveform. (4) The number of planes is the received light waveform. is the number of peaks in , indicating the number of light components. (5) The total area of the received light waveform is, for example, the total area of the range occupied by the received light waveform shown in FIG. It indicates the amount of ambient light received by the light receiving unit 120 . The width value is not limited to the width (half width) of the received light waveform at 50% of the peak received light amount. It may be a width value of the received light waveform in % or the like.

Thus, in the present embodiment, the feature information extraction unit 131 extracts the six feature information items (1) to (6) described above from the received light waveform output by the light receiving unit 120 .

The abnormality type determination unit 132 determines at least one of a plurality of abnormality types in the abnormality type information pre-stored in the storage unit 140 based on at least two types of feature information extracted by the feature information extraction unit 131. The above abnormality types are determined. Specifically, the abnormality type determination unit 132 determines the abnormality type based on the feature information (1) to (6) described above, based on the time-series changes, combinations thereof, and the like. Here, the storage unit 140 stores in advance abnormality type information in which a plurality of characteristic information included in the received light waveform and a plurality of abnormality types predicted from the plurality of characteristic information are associated with each other. The abnormality type determination unit 132 determines the abnormality type while referring to the abnormality type information stored in the storage unit 140 based on the characteristic information (1) to (6) described above.

FIG. 5 is a diagram showing an example of abnormality type information in which feature information and an abnormality type predicted from the feature information are associated with each other. As shown in FIG. 5, there are six types of abnormalities: (a) sensor contamination, (b) light source deterioration, (c) narrow space measurement, (d) multiple reflection, (e) mutual interference, and (f) ambient light. is the above-mentioned (1) received light amount, (2) received light amount adjustment parameter, (3) width value, (4) number of planes, (5) received light waveform total area, and (6) background level value, time series change and a combination thereof.

Furthermore, when the abnormality type determination unit 132 determines the abnormality types (a) to (f) based on the feature information (1) to (6), what monitoring method is used? It is associated with whether it is determined using In the monitoring method, for example, for the feature information (1) to (6) described above, (A) the amount of difference from the reference value, (B) the amount of change in a predetermined period, and (C) the received light waveform at a certain point Methods of monitoring the information contained are included, of which at least one or more monitoring methods are used.

(A) The amount of difference from the reference value is compared with the initial value of the displacement sensor 10 (for example, the value at the time of shipment from the factory, at the time of purchase, or at the start of work) as a reference value (threshold), and (B) the change in a predetermined period The amount is, for example, the amount of change in a short period of several ms to several hundreds of ms is monitored, and (C) the information contained in the received light waveform at a certain time is the information contained in the temporary waveform among the received light waveforms. It detects.

Below, the abnormality types (a) to (f) will be described in detail with specific examples.

FIG. 6A is a diagram showing an example of determining (a) sensor contamination. As shown in FIG. 6A, when the sensor is dirty, the amount of received light, the parameter for adjusting the amount of received light, and the width value change (rapidly change in a short time). Further, when the displacement sensor 10 exceeds the range of the reference value (threshold value) in which appropriate measurement is possible for the workpiece, the abnormality type determination unit 132 determines that the sensor is dirty. If noise components are included in the received light waveform, the total area of the received light waveform and the background level may change, and the characteristic information of these may also be used for the determination of sensor contamination.

FIG. 6B is a diagram showing an example of determining (b) light source deterioration. As shown in FIG. 6B, when there is light source deterioration, the displacement sensor 10 is in a state where the amount of received light decreases and the gain, which is the parameter for adjusting the amount of received light, is increased. For example, if the displacement sensor 10 exceeds the reference value (threshold value) range that enables proper measurement of the workpiece compared with the initial reference value (the value detected by teaching when used for the first time), , the abnormality type determination unit 132 determines that the light source has deteriorated.

FIG. 6C is a diagram showing an example of determining narrow space measurement (c). As shown in FIG. 6C, when there is narrow space measurement, the displacement sensor 10 becomes unstable and the received light waveform fluctuates up and down. It may become a state to increase the gain which is a parameter. Here, the difference from the above-described (b) light source deterioration is that, in the case of narrow space measurement, for example, when the state of the inspection area (workpiece) changes (when the narrow space position is deviated), the amount of received light and the amount of received light adjustment parameter is the point to return to. In other words, when there is narrow-space measurement, if the change in the amount of received light and the parameter for adjusting the amount of received light is temporary, the abnormality type determination unit 132 determines narrow-space measurement.

FIG. 6D is a diagram showing an example of determining (d) multiple reflections. As shown in FIG. 6D, when there is multiple reflection, a change such as an increase in the number of faces occurs (rapid change for a short time). Then, when the displacement sensor 10 exceeds the range of the reference value (threshold value) of the parameters (width value, number of surfaces, etc.) extracted from the measured value and the received light waveform that can appropriately measure the workpiece , the abnormality type determination unit 132 determines multiple reflection. Furthermore, the amount of received light may decrease (the parameter for adjusting the amount of received light increases), and this characteristic information may also be used for determining whether the sensor is dirty.

FIG. 6E is a diagram showing an example of determining (e) mutual interference. As shown in FIG. 6E, when there is mutual interference, the number of surfaces increases. sudden change in a short time). In such a case, the abnormality type determination unit 132 determines mutual interference. Furthermore, the amount of light received and the parameter for adjusting the amount of light received may change, and the background level may also change, and the feature information of these may also be used for determining mutual interference.

FIG. 6F is a diagram showing an example of determining (f) disturbance light. As shown in FIG. 6F, when there is ambient light, the amount of received light, the parameter for adjusting the amount of received light, the width value, the total area of the received light waveform, and the background level change (sudden change in a short time). In particular, the background level may increase but may also decrease, which differs from (a) sensor contamination discussed above. Then, when the displacement sensor 10 exceeds the range of the reference value (threshold value) in which appropriate measurement is possible for the workpiece, the abnormality type determination unit 132 determines that it is disturbance light.

The determination of the abnormality type is not limited to the conditions described here. For example, if the abnormality type can be determined under conditions other than those described here, other conditions may be used for determination. It does not matter, and other combinations of feature information may be used for determination as long as the abnormality type can be determined using combinations other than the combinations described here.

Further, here, the abnormality type determination unit 132 uses the monitoring methods (A) to (C) for the abnormality types (a) to (f) based on the feature information (1) to (6). However, it is not limited to these. For example, the abnormality type may include penetration, head tilt, and transparent object detection, etc., and the feature information may include information on the tilt or the center of gravity of the received light waveform, or other information that can be extracted from the received light waveform. Feature information may be included. Furthermore, as for the monitoring method, for example, a continuous monitoring method, an intermittent or periodic (long-term and short-term) monitoring method, and the like may be used. In addition, it is not necessary to apply all of these, including the above-described abnormality type, feature information, and monitoring method, and it is possible to appropriately determine the abnormality type according to the abnormality type, accuracy, performance, etc. desired by the user. You can choose.

As described above, the abnormality type determination unit 132 determines the abnormality type.

The output unit 133 outputs the abnormality type determined by the abnormality type determining unit 132. For example, the output unit 133 may output to display the abnormality type on the display unit 150, or may output to notify a PC or PLC connected as an external device.

FIG. 7 is a diagram showing an example of displaying an abnormality type on the display section 150 provided in the amplifier section. As shown in FIG. 7, the abnormality type "sensor dirt" is displayed. This allows the user to recognize sensor contamination and deal with it.

Note that the content displayed on the display unit 150 is not limited to the type of abnormality. It is also possible to display countermeasures or presumed causes corresponding to . This allows the user to directly and specifically grasp what countermeasures should be taken.

FIG. 8 is a diagram showing an example of error codes associated with anomaly types and countermeasures. For example, a correspondence table as shown in FIG. Either one or more of the error code and countermeasures may be output.

In addition, when the display screen of the display unit 150 is small, an error code associated with an abnormality type is displayed. By referring to the table in which countermeasures and the like are associated with each other, it is possible to grasp what kind of countermeasures should be taken according to the displayed error code.

Further, the content output by the output unit 133 and the content displayed by the display unit 150 are switched depending on the situation such as when the displacement sensor 10 is periodically inspected or when the workpiece W is actually measured. I don't mind. For example, when an abnormality type that affects the measurement result is determined during operation while measuring the workpiece W, the output unit 133 outputs a warning signal and replaces the measurement result with an indefinite value or an error. In addition, a message to that effect may be displayed on the display unit 150 . Further, when detailed information on the type of abnormality is required, continuous time-series data, waveforms, etc. may be displayed based on the received light waveforms or characteristic information data accumulated in the storage unit 140. do not have.

[Status monitoring method]
Next, a state monitoring method for monitoring the state of the displacement sensor 10 and its surrounding environment including abnormality type determination will be described.

FIG. 9 is a flow chart showing the process flow of a state monitoring method M10 for monitoring the state of the displacement sensor 10 and its surrounding environment, including abnormality type determination, while the displacement sensor 10 measures the workpiece W. As shown in FIG. 9, the condition monitoring method M10 includes steps S11 to S19, each step being executed by a processor included in the displacement sensor 10. FIG.

In step S11, as described with reference to FIG. 1, the displacement sensor 10 projects the laser beam L1 onto the work W and receives the reflected light L2 from the work W with respect to the laser beam L1. , the amount of displacement of the surface of the work W is measured.

In step S12, light reflected by the workpiece W (inspection area) is received by the light receiving unit 120, and a received light waveform is output.

In step S13, at least two types of feature information are extracted by the feature information extraction unit 131 in the control unit 130 based on the received light waveform output in step S12. Specific examples are (1) received light amount, (2) received light amount adjustment parameter, (3) width value, (4) number of planes, (5) received light waveform total area, and (6) described with reference to FIG. The background level is extracted as feature information.

In step S14, the feature information extracted in step S13 is accumulated in the storage unit 140 by the control unit 130.

In steps S15 to S18, the abnormality type determination unit 132 in the control unit 130 determines the abnormality type based on the feature information accumulated in step S14 while referring to the abnormality type information stored in advance in the memory. . As a specific example, as described with reference to FIG. 5, the abnormality type determination unit 132 includes (1) received light amount, (2) received light amount adjustment parameter, (3) width value, (4) number of surfaces, and (5) For the six characteristic information of the total area of the received light waveform and (6) the background level, using three monitoring methods of (A) the reference value difference, (B) a sudden change in a short time, and (C) the received light waveform at a certain point, Six types of abnormalities are determined: (a) sensor contamination, (b) light source deterioration, (c) narrow space measurement, (d) multiple reflection, (e) mutual interference, and (f) ambient light.

In step S19, the output unit 133 in the control unit 130 outputs the abnormality type determined in steps S15 to S18. As a specific example, an abnormality type is displayed on the display unit 150 .

It should be noted that the series of processes related to the abnormality type determination in steps S13 to S19 may be executed for each measurement cycle, or may be executed appropriately as necessary.

FIG. 10 is a flow chart showing a specific process flow of the abnormality type determination method M100 executed in steps S15 to S18 in FIG. As shown in FIG. 10, the abnormality type determination method M100 includes steps S101 to S116, and each step is executed by the processor included in the displacement sensor 10. FIG.

Here, as processing in each step, the abnormality type determination unit 132 monitors a short-time sudden change that is a change (increase or decrease) of each feature information and whether or not it is within the range of the reference value (above or below). By doing so, the type of abnormality is determined. Processing in each of these steps will be specifically described.

In step S101, if (1) the received light amount is below the initial reference value and (2) the received light amount adjustment parameter is above the initial reference value (Yes in step S101), (b) the light source Deterioration is determined (step S102).

Here, the initial reference value is, for example, set based on a value detected by teaching when the displacement sensor 10 is purchased and used for the first time. 2) This is for grasping the amount of change (difference) from when the displacement sensor 10 is used for the first time with respect to the parameter for adjusting the amount of received light. The initial reference value is preferably set within a range in which the displacement sensor 10 can appropriately measure the workpiece with respect to the amount of received light and the parameter for adjusting the amount of received light.

If the initial reference value is not set without teaching when the displacement sensor 10 is purchased and used for the first time, the abnormality type determination unit 132 may be unable to determine (b) the deterioration of the light source. be. In this case, the abnormality type determination unit 132 may determine (b) light source deterioration by using a value preset in the displacement sensor 10 or by setting by the user.

In step S103 (No in step S101), the abnormality type determination unit 132 (4) determines whether the number of pages has increased and exceeds the reference value.

Here, the reference value is, for example, set based on a value detected by teaching at the start of work when the displacement sensor 10 is operated. This is for grasping the amount of change (difference) from the start of work or the like. The reference value is preferably set within a range in which the displacement sensor 10 can appropriately measure the workpiece with respect to the feature information (including feature information described later). The reference value may be updated for each teaching. If teaching is not performed at the start of work when the displacement sensor 10 is to be operated, a value preset in the displacement sensor 10 may be used, It may be set by the user.

In step S104 (Yes in step S103), the abnormality type determination unit 132 (4) determines that the number of surfaces does not decrease and is not within the reference value range (No in step S104), (d) multiple reflection. (Step S105).

At step S106 (Yes at step S104), the abnormality type determination unit 132 determines (e) mutual interference if (4) the number of planes repeats rising and falling (Yes at step S106) (step S107).

In step S108 (No in step S103), the abnormality type determination unit 132 determines whether (1) the received light amount has decreased and is below the reference value, and (2) the received light amount adjustment parameter has increased and exceeded the reference value. judge.

At step S109 (Yes at step S108), the abnormality type determination unit 132 (3) determines that the sensor is dirty (step S110) if the width value has increased (Yes at step S109).

In step S111 (No in step S109), the abnormality type determination unit 132 (1) increases the amount of received light and (2) decreases the parameter for adjusting the amount of received light (Yes in step S111). It is determined that the measurement is performed (step S112).

In step S113 (No in step S108), the abnormality type determination unit 132 determines whether (1) the received light amount has increased and exceeded the reference value, and (2) the received light amount adjustment parameter has decreased and fallen below the reference value. judge.

In step S114 (Yes in step S113), the abnormality type determination unit 132 determines whether (5) the total area of the received light waveform has increased and exceeds the reference value, and (6) the background level has increased and exceeded the reference value. judge.

In step S115 (Yes in step S114), the abnormality type determination unit 132 determines whether (5) the total area of the received light waveform has decreased and is below the reference value, and (6) the background level has decreased and is below the reference value. Otherwise (Yes in step S115), it is determined as disturbance light (step S116).

In this way, the abnormality type determination unit 132 determines six types of (a) sensor contamination, (b) light source deterioration, (c) narrow place measurement, (d) multiple reflection, (e) mutual interference, and (f) disturbance light. It judges two types of anomalies.

As described above, according to the displacement sensor 10 and the state monitoring method M10 according to the embodiment of the present invention, the feature information extraction unit 131 extracts a plurality of feature information from the received light waveform, and the abnormality type determination unit 132 detects the plurality of feature information. At least one type of abnormality among a plurality of types of abnormality in the abnormality type information pre-stored in the storage unit 140 can be determined based on the feature information. As a result, the abnormality type can be appropriately determined, and the user can take countermeasures corresponding to the abnormality type.

It should be noted that, in the present embodiment, it has been described that the abnormality types (a) to (f) shown in FIG. 5 are determined, but the types of abnormality that can be determined may differ depending on the state of the inspection area.

FIG. 11 is a diagram showing an example of an abnormality type that cannot be determined according to the presence or absence of a workpiece and a base in the inspection area, among the abnormality types in FIG. As shown in FIG. 11, the abnormality types (a) to (f) can be appropriately determined when the workpiece exists in the inspection area, but when the workpiece and the base do not exist in the inspection area, (a) sensor contamination, (c) narrow space measurement, and (d) multiple reflection may not be determined appropriately.

As described above, depending on the conditions of the inspection area, there are abnormality types that can be appropriately determined and abnormality types that cannot be determined appropriately. It may be included in the information.

As a result, for example, when the abnormality type determination unit 132 determines that (c) narrow space measurement is performed, the display unit 150 displays a message stating "If there is no workpiece, appropriate determination may not be possible." It is also possible to make the user confirm by sending a notice similar to this. In addition, in order to appropriately determine the type of abnormality desired by the user, the type of abnormality to be determined or the conditions for appropriately determining each type of abnormality are displayed on the display unit 150 in advance so that the user can confirm. You can leave it as is.

Furthermore, the user may input, via the operation unit 160, a time period that satisfies appropriate conditions (for example, in this embodiment, a work and a base exist). As a result, it can be seen that the abnormality type determined in the relevant time period is the result of an appropriate determination.

Further, in this embodiment, as the abnormality type information stored in the storage unit 140, a table in which characteristic information used for abnormality type determination and a monitoring method are associated with each abnormality type as shown in FIG. Although it is mentioned as an example, it is not limited to this. For example, a table in which feature information and an abnormality type are associated with each monitoring method may be used.

FIG. 12 is a diagram showing an example of abnormality type information in which feature information used and predicted abnormality types are associated with each monitoring method. As shown in FIG. 12, in the monitoring methods (A) to (C), when any one of the feature information (1) to (6) is monitored, the abnormality types (a) to (f) are detected. It is possible to grasp whether it is possible to judge. Here, there are cases where the abnormality type can be uniquely determined by combining the monitoring method and the feature information, and cases where the abnormality type can be determined by combining a plurality of these.

When the reference value difference is used as the monitoring method, the reference value must be set in advance. Since the determination can be made by comparison with the data obtained, the change, etc., there are cases where the abnormality type can be determined even if the reference value is not set in advance.

As described above, the type of the displacement sensor 10, the user's desired abnormality type, and the abnormality type determination unit 132 may be adopted in accordance with the specific determination processing procedure in . In addition, the storage unit 140 may store the abnormality type information in a plurality of formats, or may store the abnormality type information in a format other than the abnormality type information shown in FIGS. I do not care.

The embodiments described above are for facilitating understanding of the present invention, and are not for limiting interpretation of the present invention. Each element included in the embodiment and its arrangement, materials, conditions, shape, size, etc. are not limited to those illustrated and can be changed as appropriate. Also, it is possible to partially replace or combine the configurations shown in different embodiments.

[Appendix]
a light projecting unit (110) for projecting light onto an inspection area;
a light receiving unit (120) for receiving light reflected by the inspection area and outputting a received light waveform;
a storage unit (140) storing in advance abnormality type information in which a plurality of characteristic information included in the received light waveform and a plurality of abnormality types predicted from the plurality of characteristic information are associated;
a feature information extraction unit (131) for extracting at least two types of feature information based on the received light waveform output by the light receiving unit;
Based on the extracted at least two types of feature information, an abnormality type determination unit ( 132) and
an output unit (133) that outputs the determined abnormality type;
a displacement sensor (10).

DESCRIPTION OF SYMBOLS 10... Displacement sensor 11... Cable 100... Sensor head 110... Light projecting part 111... Light emitting element 112... Light emitting control circuit 120... Light receiving part 121... Imaging element 122... Signal processing circuit 123... A/D conversion circuit 130 control unit 131 feature information extraction unit 132 abnormality type determination unit 133 output unit 140 storage unit 150 display unit 160 operation unit 170 input/output interface , L1... laser beam, L2... reflected light, B... base, W... workpiece, M10... condition monitoring method, S11 to S19... each step of condition monitoring method M10, M100... abnormality type determination method, S101 to S116... abnormality type Each step of the determination method M100

Claims

a light projecting unit that projects light onto an inspection area;
a light receiving unit that receives the light reflected by the inspection area and outputs a received light waveform;
a storage unit pre-stored with abnormality type information in which a plurality of characteristic information included in the received light waveform and a plurality of abnormality types predicted from the plurality of characteristic information are associated with each other;
a feature information extraction unit that extracts at least two types of feature information based on the received light waveform output by the light receiving unit;
an abnormality type determination unit that determines at least one type of abnormality among a plurality of types of abnormality in the abnormality type information pre-stored in the storage unit, based on the extracted at least two types of characteristic information; ,
an output unit that outputs the determined abnormality type;
A displacement sensor.
The abnormality type determination unit uses at least one monitoring method for the extracted feature information from among the amount of difference from a reference value, the amount of change in a predetermined period, and information included in a received light waveform at a certain point in time. to determine the type of anomaly,
The displacement sensor according to claim 1.
Among a plurality of abnormality types in the abnormality type information stored in advance in the storage unit, an abnormality type that can be determined according to the monitoring method is classified.
3. The displacement sensor according to claim 2.
The feature information includes at least two of the amount of received light, the parameter for adjusting the amount of received light, the width value of the received light waveform, the number of surfaces of the received light waveform, the total area of the received light waveform, and the background level.
A displacement sensor according to any one of claims 1 to 3.
The abnormality type determination unit selects at least two of the received light amount, the received light amount adjustment parameter, the width value of the received light waveform, the number of surfaces of the received light waveform, the total area of the received light waveform, and the background level. Determine the type of abnormality according to the combination,
5. The displacement sensor according to claim 4.
Among the plurality of abnormality types in the abnormality type information stored in advance in the storage unit, the received light amount, the received light amount adjustment parameter, the width value of the received light waveform, the number of surfaces of the received light waveform, and the total area of the received light waveform , and of the background levels, at least two types of abnormality types that can be determined are classified according to the combination,
The displacement sensor according to claim 5.
Among a plurality of abnormality types in the abnormality type information stored in advance in the storage unit, an abnormality type that can be determined according to the presence or absence of a work and a base in the inspection area is classified.
A displacement sensor according to any one of claims 1 to 6.
The output unit outputs countermeasures or presumed causes corresponding to the determined abnormality type,
A displacement sensor according to any one of claims 1 to 7.
A condition monitoring method performed by a displacement sensor including a processor, comprising:
a light projection step for projecting light onto an inspection area;
a light receiving step of receiving the light reflected by the inspection area and outputting a received light waveform;
a feature information extraction step of extracting at least two types of feature information based on the received light waveform output in the light receiving step;
Based on the extracted at least two types of feature information, a plurality of feature information included in the received light waveform stored in advance in a memory and a plurality of abnormality types predicted from the plurality of feature information are associated with each other. an abnormality type determination step of determining at least one type of abnormality among a plurality of types of abnormality in the obtained abnormality type information;
an output step of outputting the determined abnormality type;
A method of condition monitoring, comprising: