Displacement sensor and condition monitoring method

Abstract

To provide a displacement sensor and a state monitoring method which can appropriately determine an abnormality type.SOLUTION: A displacement sensor 10 comprises: a light emission unit 110 which emits light to an inspection area; a light reception unit 120 which receives light reflected on the inspection area to output a received light waveform; a storage unit 140 in which there is preliminarily stored abnormality type information associating a plurality of pieces of feature information included in the received light waveform and a plurality of abnormality types predicted from the plurality of pieces of feature information with each other; a feature information extraction unit 131 which extracts at least two or more pieces of feature information on the basis of the received light waveform outputted from the light reception unit; an abnormality type determination unit 132 which determines one or more abnormality types out of the plurality of abnormality types in the abnormality type information preliminarily stored in the storage unit, on the basis of the at least two or more pieces of feature information extracted; and an output unit 133 which outputs the determined abnormality types.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a displacement sensor and a condition monitoring method. [Background technology]

[0002] Conventionally, a displacement sensor using an optical system has been used as a device for measuring the displacement of a workpiece without contact. However, such a displacement sensor may not be able to measure the workpiece properly due to deterioration of the displacement sensor over time, contamination due to the adhesion of foreign matter such as dust, and influences from the surrounding environment.

[0003] Patent Document 1 discloses a technology related to a detection device that detects a symptom of an abnormality in a detection sensor before the abnormality occurs in the detection sensor. Specifically, the detection device disclosed in Patent Document 1 acquires the amount of light received by a light receiving unit at regular intervals when a workpiece passes a detection position, and generates a received light waveform based on the acquired result. The detection device then compares a reference waveform with the received light waveform to determine whether or not there is a symptom of an abnormality in the detection sensor. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2012-78175 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, the detection device disclosed in Patent Document 1 determines whether or not there is a sign of abnormality in the detection sensor, but even if a sign of abnormality is detected, it cannot distinguish the cause and details of the abnormality. Therefore, there is a problem that the user cannot grasp what specific measures need to be taken after that.

[0006] SUMMARY OF THE PRESENT EMBODIMENTS Accordingly, an object of the present invention is to provide a displacement sensor and a condition monitoring method that are capable of appropriately determining the type of abnormality. [Means for solving the problem]

[0007] 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 the light reflected by the inspection area and outputs a received-light waveform, a storage unit that stores in advance abnormality type information in which a plurality of pieces of feature information included in the received-light waveform are associated with a plurality of abnormality types predicted from the plurality of pieces of feature information, a feature information extracting unit that extracts at least two or more types of feature information based on the received-light waveform output by the light-receiving unit, an abnormality type determining unit that determines at least one or more types of abnormality types among the plurality of abnormality types in the abnormality type information prestored in the storage unit based on the at least two or more types of extracted feature information, and an output unit that outputs the determined abnormality type. Here, the received-light waveform is generated as a waveform indicating the amount of light received by each pixel for the light received by the image sensor of the light-receiving unit.

[0008] According to this aspect, the feature information extraction unit extracts at least two pieces of feature information based on the received light waveform, and the abnormality type determination unit can appropriately determine at least one type of abnormality type among the multiple abnormality types in the abnormality type information pre-stored in the memory unit based on the feature information.

[0009] In the above aspect, the anomaly type determination unit may determine the type of anomaly for the extracted characteristic information by using at least one or more monitoring methods among the difference amount from a reference value, the amount of change over a specified period of time, and information contained in the received light waveform at a certain point in time.

[0010] According to this aspect, the abnormality type determination unit determines the abnormality type using a plurality of types of monitoring methods, and therefore, can more appropriately determine the abnormality type.

[0011] In the above aspect, among the plurality of abnormality types in the abnormality type information stored in advance in the storage unit, the abnormality types that can be determined according to the monitoring method may be classified.

[0012] According to this aspect, in the abnormality type information, the abnormality types that can be determined are classified according to the monitoring method, so that an appropriate monitoring method can be used in determining the abnormality type according to each abnormality type.

[0013] In the above aspect, the characteristic information may include at least two of the amount of received light, a parameter for adjusting the amount of received light, a width value of the waveform of received light, the number of faces of the waveform of received light, a total area of ​​the waveform of received light, and a background level.

[0014] According to this aspect, the characteristic information extracted from the received light waveform includes at least two of the amount of received light, the light amount adjustment parameter, the width value of the received light waveform, the number of faces of the received light waveform, the total area of ​​the received light waveform, and the background level, so that the type of abnormality can be determined more specifically based on these.

[0015] In the above aspect, the abnormality type determination unit may determine the abnormality type based on a combination of at least two or more of the amount of received light, a light receiving amount adjustment parameter, a width value of the received light waveform, the number of faces of the received light waveform, the total area of ​​the received light waveform, and a background level.

[0016] According to this aspect, the abnormality type determination unit determines each abnormality type by appropriately combining a plurality of pieces of characteristic information, and therefore can more appropriately determine the abnormality type.

[0017] In the above aspect, among the multiple abnormality types in the abnormality type information pre-stored in the storage unit, the abnormality type that can be determined may be classified according to a combination of at least two or more of the amount of received light, the amount of received light adjustment parameter, the width value of the received light waveform, the number of faces of the received light waveform, the total area of ​​the received light waveform, and the background level.

[0018] According to this aspect, the abnormality type information classifies determinable abnormality types according to a combination of at least two or more of the amount of received light, the amount of received light adjustment parameter, the width value of the received light waveform, the number of faces of the received light waveform, the total area of ​​the received light waveform, and the background level, so that when determining the abnormality type, characteristic information can be appropriately combined according to each abnormality type.

[0019] In the above aspect, among the multiple abnormality types in the abnormality type information pre-stored in the storage unit, an abnormality type that can be determined depending on the presence or absence of a workpiece and a base in the inspection area may be classified. Note that the workpiece is a measurement target that is measured by the displacement sensor, and the base is a base on which the workpiece is placed.

[0020] According to this aspect, the type of abnormality can be appropriately determined depending on the presence or absence of a workpiece and a base in the inspection area.

[0021] In the above aspect, the output unit may output a measure or a presumed cause corresponding to the determined abnormality type.

[0022] According to this embodiment, the user can directly and specifically grasp what measures should be taken.

[0023] A condition monitoring method according to one embodiment of the present invention is a condition monitoring method executed by a displacement sensor including a processor, and includes a light projection step of projecting light onto an inspection area, a light receiving step of receiving light reflected from the inspection area and outputting a received-light waveform, a feature information extraction step of extracting at least two or more types of feature information based on the received-light waveform output in the light receiving step, an abnormality type determination step of determining at least one or more abnormality types from among multiple abnormality types in abnormality type information that is pre-stored in a memory and that corresponds multiple pieces of feature information included in the received-light waveform with multiple abnormality types predicted from the multiple pieces of feature information, based on the at least two or more types of extracted feature information, and an output step of outputting the determined abnormality type.

[0024] According to this aspect, at least two pieces of feature information are extracted based on the received light waveform in the feature information extraction step, and at least one type of abnormality can be appropriately determined from the multiple abnormality types in the abnormality type information pre-stored in the memory based on the feature information in the abnormality type determination step. Effect of the Invention

[0025] According to the present invention, it is possible to provide a displacement sensor and a condition monitoring method capable of appropriately determining the type of abnormality. [Brief description of the drawings]

[0026] [Figure 1] 1 is a perspective view showing the appearance of a sensor head of a displacement sensor 10 according to an embodiment of the present invention. [Diagram 2] 1 is a block diagram showing the functions constituting a displacement sensor 10 according to an embodiment of the present invention. [Diagram 3] 1 is a block diagram showing a control unit 130 involved in a process of determining an abnormality type and each of the functional configurations related thereto in a displacement sensor 10 according to an embodiment of the present invention. [Figure 4] 11A and 11B are diagrams illustrating an example of feature information extracted from a received light waveform. [Diagram 5] 11 is a diagram showing an example of abnormality type information in which characteristic information is associated with an abnormality type predicted from the characteristic information; FIG. [Figure 6A] FIG. 13A is a diagram showing an example of determining sensor contamination. [Figure 6B] FIG. 1B is a diagram showing an example of determining deterioration of a light source. [Figure 6C] FIG. 13C is a diagram showing an example of determining narrow space measurement. [Figure 6D] FIG. 1D is a diagram showing an example of determining multiple reflections. [Figure 6E] FIG. 10E is a diagram showing an example of determining mutual interference. [Figure 6F] FIG. 10F is a diagram showing an example of determining disturbance light. [Figure 7]11 is a diagram showing an example in which an abnormality type is displayed on a display unit 150 provided in the amplifier unit. FIG. [Figure 8] FIG. 11 is a diagram illustrating an example of error codes and countermeasures associated with abnormality types. [Figure 9] 11 is a flowchart showing the process flow of a condition monitoring method M10 for monitoring the condition of the displacement sensor 10 and its surrounding environment, including determining the type of abnormality, while the displacement sensor 10 measures a workpiece W. [Figure 10] 10 is a flowchart showing a specific process flow of an abnormality type determination method M100 executed in steps S15 to S18 in FIG. [Figure 11] 6 is a diagram showing an example of an abnormality type that cannot be determined depending on the presence or absence of a workpiece and a base in an inspection area, among the abnormality types in FIG. 5; [Figure 12] 11 is a diagram showing an example of abnormality type information in which characteristic information used and predicted abnormality types are associated with each other for each monitoring method. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0027] Hereinafter, an embodiment of the present invention will be specifically described with reference to the drawings. Note that the embodiment described below is merely a specific example for carrying out the present invention, and is not intended to limit the interpretation of the present invention. In addition, in order to facilitate understanding of the description, the same reference numerals are used as far as possible for the same components in each drawing, and duplicated descriptions may be omitted.

[0028] <One embodiment> [Displacement sensor configuration] 1 is a perspective view showing the appearance of a sensor head of a displacement sensor 10 according to one embodiment of the present invention. The displacement sensor 10 includes a sensor head 100 and an auxiliary housing (not shown) called an amplifier unit that is connected via a cable 11.

[0029] 1, the displacement sensor 10 projects laser light L1 from a sensor head 100 onto a workpiece W placed on a base B, and receives reflected light L2 of the laser light L1 from the workpiece W, thereby measuring the amount of displacement of the surface of the workpiece W based on the principle of triangulation. Note 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.

[0030] As described above, the displacement sensor 10 is normally a measuring device that projects laser light onto the workpiece W to measure the amount of displacement of the surface of the workpiece W. However, in this embodiment, for example, when the workpiece W is not present and the inspection area is equipment such as an assembly robot or the surrounding environment, condition monitoring may be performed by projecting laser light and receiving reflected light from the inspection area.

[0031] Fig. 2 is a block diagram showing the functions 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. The light projecting unit 110 includes a light emitting element 111 and a light projection control circuit 112, and the light receiving unit 120 includes an image sensor 121, a signal processing circuit 122, and an A / D conversion circuit 123.

[0032] 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. 1, and the display unit 150, the operation unit 160 and the input / output interface 170 are provided in the amplifier unit. However, it is not always necessary to separate the sensor head 100 from the amplifier unit, and all of the components shown in Fig. 2 may be provided in a single housing.

[0033] The light-projecting unit 110 projects light onto an inspection area (for example, a workpiece W). Specifically, the light-projecting unit 110 has a laser diode (LD) as a light-emitting element 111, and the light-emitting element 111 is driven to project light while the light-emitting intensity and light-emitting time of the light-emitting element 111 are adjusted by a light-projection control circuit 112. The light-projection control circuit 112 operates based on a command from the control unit 130.

[0034] The light receiving unit 120 receives light reflected from the inspection area and outputs a received light waveform. Specifically, the light receiving unit 120 has a CMOS including a plurality of pixels as an image sensor 121, and further has a signal processing circuit 122 and an A / D conversion circuit 123 for processing an image signal generated by the image sensor 121. The signal processing circuit 122 controls the operation timing of the image sensor 121 based on a command from the control unit 130, and also captures an image generated by the image sensor 121 and outputs it to the A / D conversion circuit 123. Then, the image analog-digitally converted by the A / D conversion circuit 123 is input to the control unit 130 for measurement processing.

[0035] The control unit 130 is, for example, a CPU, and based on a program and setting data stored in the storage unit 140, causes the light projecting unit 110 to emit laser light L1, and operates the light receiving unit 120 in accordance with the timing of the emission, to receive reflected light L2 from the workpiece W. Then, the control unit 130 measures the amount of displacement of the workpiece W by various processes based on the received light waveform output by the light receiving unit 120.

[0036] The control unit 130 also extracts feature information contained in the received light waveform based on the received light waveform output by the light receiving unit 120, and determines the type of abnormality estimated from the extracted feature information. Details of the process of determining the type of abnormality in the displacement sensor 10 will be described later.

[0037] 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 abnormality type information used in the process of determining the abnormality type described below. It is also set as a buffer function for storing data such as the received light waveform output by the light receiving unit 120 and feature information extracted from the received light waveform, which are used in the process of determining the abnormality type described below.

[0038] The display unit 150 is composed of, for example, a liquid crystal display or an organic EL display, and displays information to be notified to the user, such as the measurement values ​​from the control unit 130 described above, the abnormality types described below, measures to be taken to address the abnormality types, and other settings and states related to the displacement sensor 10.

[0039] The operation unit 160 is composed of a button, a dial, a touch panel, or the like, and is used to allow the user to, for example, turn on and off the power supply of the displacement sensor 10, and to switch between various settings and operation modes.

[0040] The input / output interface 170 is connected to an external device such as a PC (personal computer) and a PLC (programmable logic controller). When connected to an external device, it becomes possible to perform operations on the external device similar to those executed on the operation unit 160. For example, operations on the displacement sensor 10 may be performed on the PC, and measurement results obtained by the displacement sensor 10 may be displayed on the screen of the PC.

[0041] [Anomaly type determination process] Next, a detailed description will be given of the abnormality type determination process performed by the displacement sensor 10. Here, the abnormality type determination process is a function of detecting an abnormality or a symptom thereof that makes it impossible to properly measure the workpiece W or the like due to, for example, aging deterioration of the displacement sensor 10, contamination due to adhesion of foreign matter such as dust, and influences from the surrounding environment.

[0042] 3 is a block diagram showing the control unit 130 and each related functional configuration related to the abnormality type determination process in the displacement sensor 10 according to one embodiment of the present invention. As shown in FIG. 3, the control unit 130 includes a feature 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 outputs the determined abnormality type to the display unit 150.

[0043] 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 feature information extraction unit 131 extracts a plurality of pieces of feature information (described later) based on the received light waveform continuously output by the light receiving unit 120, and accumulates them in the storage unit 140.

[0044] Fig. 4 is a diagram showing an example of feature information extracted from the received light waveform. In the diagram, the pixel position indicates the position in the baseline direction in triangulation with respect to the pixel on the image sensor 121, and the LSB indicates the average amount of received light of the pixel corresponding to the pixel position. As shown in Fig. 4, (1) amount of received light, (2) light-receiving amount adjustment parameter, (3) width value, (4) number of faces, (5) total area of ​​received light waveform, and (6) background level are extracted from the received light waveform.

[0045] In addition, (1) the amount of received light is the amount of light received by the light receiving unit 120, and (2) the light receiving amount adjustment parameter is the adjustment (e.g., gain, exposure time, etc.) required to output as a received light waveform according to the amount of light received by the light receiving unit 120. (3) The width value is, for example, the width (half-width) of the received light waveform at 50% of the peak amount of received light, and indicates the spread of the received light waveform. (4) The number of faces is, for example, the number of peaks of the received light waveform, and indicates the number of light components. (5) The total area of ​​the received light waveform is, for example, the total area occupied by the received light waveform shown in FIG. 4, and (6) The background level indicates the amount of received light due to ambient light received by the light receiving unit 120 without the displacement sensor 10 projecting measurement light. The width value is not limited to the width (half-width) of the received light waveform at 50% of the peak received light amount, but may be, for example, the width value of the received light waveform at 40% or 60% of the peak received light amount, as long as it indicates the spread of the received light waveform.

[0046] As described above, in this embodiment, the feature information extraction section 131 extracts the above-mentioned six pieces of feature information (1) to (6) from the received light waveform output by the light receiving section 120.

[0047] The abnormality type determination unit 132 determines at least one abnormality type among the multiple abnormality types in the abnormality type information stored in advance in the storage unit 140, based on at least two or more types of characteristic information extracted by the characteristic information extraction unit 131. Specifically, the abnormality type determination unit 132 determines the abnormality type based on the above-mentioned characteristic information (1) to (6) by time-series changes and combinations of these. Here, the storage unit 140 stores in advance abnormality type information in which multiple pieces of characteristic information included in the received light waveform are associated with multiple abnormality types predicted from the multiple pieces of characteristic information. 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 above-mentioned characteristic information (1) to (6).

[0048] Fig. 5 is a diagram showing an example of abnormality type information in which characteristic information is associated with an abnormality type predicted from the characteristic information. As shown in Fig. 5, six abnormality types, namely (a) sensor dirt, (b) light source deterioration, (c) narrow space measurement, (d) multiple reflections, (e) mutual interference, and (f) disturbance light, are determined according to the above-mentioned (1) amount of received light, (2) light-receiving amount adjustment parameter, (3) width value, (4) number of faces, (5) total area of ​​received light waveform, and (6) background level value, time series change, and combinations thereof.

[0049] Furthermore, there is association as to what monitoring method is used when the abnormality type determination unit 132 determines the above-mentioned abnormality types (a) to (f) based on the above-mentioned characteristic information (1) to (6). The monitoring method includes, for example, a method of monitoring (A) the amount of difference from a reference value, (B) the amount of change in a predetermined period, and (C) information contained in a received light waveform at a certain point in time for the above-mentioned characteristic information (1) to (6), and at least one of these monitoring methods is used.

[0050] (A) The 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 value), (B) the amount of change in a specified period is monitored by monitoring the amount of change in a short period of, for example, several ms to several hundred ms, and (C) the information contained in the received light waveform at a certain point in time is detected by detecting information contained in a temporary waveform of the received light waveform.

[0051] The following describes the abnormality types (a) to (f) in detail, giving specific examples.

[0052] Fig. 6A is a diagram showing an example of determining sensor contamination (a). As shown in Fig. 6A, when there is sensor contamination, the amount of received light, the light-receiving amount adjustment parameter, and the width value change (sudden change in a short time). Furthermore, when the range of the reference value (threshold value) that allows the displacement sensor 10 to perform appropriate measurement of the workpiece is exceeded, the abnormality type determination unit 132 determines that there is sensor contamination. Note that if a noise component is included in the received light waveform, the total area of ​​the received light waveform and the background level may also change, and this characteristic information may also be used to determine sensor contamination.

[0053] Fig. 6B is a diagram showing an example of determining (b) light source degradation. As shown in Fig. 6B, when there is light source degradation, the displacement sensor 10 is in a state where the amount of received light decreases and the gain, which is a parameter for adjusting the amount of received light, is increased. For example, when the initial reference value of the displacement sensor 10 (a value detected by teaching when first used) is compared with the initial reference value (a value detected by teaching when first used) of the displacement sensor 10, and the range of reference values ​​(threshold values) that allow appropriate measurement of the workpiece is exceeded, the abnormality type determination unit 132 determines that the light source has deteriorated.

[0054] FIG. 6C is a diagram showing an example of judging (c) narrow space measurement. As shown in FIG. 6C, when there is a narrow space measurement, the displacement sensor 10 may be in a state where the amount of received light becomes unstable, causing the received light waveform to fluctuate up and down, or the amount of received light decreases, causing the gain, which is a parameter for adjusting the amount of received light, to be increased. Here, the difference from the above-mentioned (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 workpiece moves out of the narrow space position), the amount of received light and the parameter for adjusting the amount of received light return to their original state. In other words, when there is a narrow space measurement, if the change in the amount of received light and the parameter for adjusting the amount of received light are temporary, the abnormality type judgment unit 132 judges it to be a narrow space measurement.

[0055] Fig. 6D is a diagram showing an example of determining (d) multiple reflections. As shown in Fig. 6D, when there are multiple reflections, a change occurs in which the number of faces increases (a short-term sudden change). When the measurement value that allows the displacement sensor 10 to perform appropriate measurement of the workpiece and the parameters (width value, number of faces, etc.) extracted from the received light waveform exceed the range of reference values ​​(threshold values), the abnormality type determination unit 132 determines that there are multiple reflections. Furthermore, there are cases where the amount of received light decreases (the light receiving amount adjustment parameter increases), and such characteristic information may also be used to determine sensor contamination.

[0056] 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 faces increases, and for example, if the interference light periodically blinks, the peak waveform does not change and the number of faces changes repeatedly (short-term sudden change). In such a case, the anomaly type determination unit 132 determines that there is mutual interference. Furthermore, there are cases where the amount of received light and the light receiving amount adjustment parameter change, and the background level also changes, and this characteristic information may also be used to determine mutual interference.

[0057] Fig. 6F is a diagram showing an example of determining disturbance light (f). As shown in Fig. 6F, when disturbance light is present, changes occur in the amount of received light, the light-receiving-amount adjustment parameter, the width value, the total area of ​​the received light waveform, and the background level (short-term sudden change). In particular, the background level may increase but may also decrease, which is different from the above-mentioned (a) sensor dirt in this respect. Then, when the range of the reference value (threshold value) that allows the displacement sensor 10 to perform appropriate measurement of the workpiece is exceeded, the abnormality type determination unit 132 determines that disturbance light has occurred.

[0058] The determination of the type of abnormality is not limited to the conditions described here. For example, if the type of abnormality can be determined using conditions other than those described here, other conditions may be used for the determination. Similarly, if the type of abnormality can be determined using combinations of feature information other than those described here, other combinations may be used for the determination.

[0059] Here, the abnormality type determination unit 132 determines the abnormality types (a) to (f) using the monitoring methods (A) to (C) based on the feature information (1) to (6), but is not limited to these. For example, the abnormality types may include seepage, head tilt, transparent body detection, etc., and the feature information may include information on the tilt or center of gravity of the received light waveform, or other feature information that can be extracted from the received light waveform. Furthermore, the monitoring method may be, for example, a continuous monitoring method, an intermittent or periodic (long-term and short-term) monitoring method, etc. Furthermore, it is not necessary to apply all of the above-mentioned abnormality types, feature information, and monitoring methods, and they may be appropriately selected so that the abnormality type can be appropriately determined according to the abnormality type, accuracy, performance, etc. desired by the user.

[0060] As described above, the abnormality type determining unit 132 determines the abnormality type.

[0061] The output unit 133 outputs the abnormality type determined by the abnormality type determination unit 132. For example, the output unit 133 may output the abnormality type so as to display it on the display unit 150, or may output the abnormality type so as to notify it to a PC or a PLC connected as an external device.

[0062] Fig. 7 is a diagram showing an example of an abnormality type displayed on the display unit 150 provided in the amplifier unit. As shown in Fig. 7, the abnormality type "sensor dirt" is displayed. This allows the user to recognize the sensor dirt and take action.

[0063] The contents displayed on the display unit 150 are not limited to the type of abnormality, and may be, for example, "Check if the sensor is dirty" or "Replace the light source" or other measures or estimated causes corresponding to the type of abnormality. This allows the user to directly and specifically understand what measures should be taken.

[0064] Fig. 8 is a diagram showing an example of error codes and countermeasures associated with the abnormality types. For example, a correspondence table as shown in Fig. 8 may be stored in advance in the storage unit 140, and the output unit 133 may refer to the correspondence table in accordance with the abnormality type determined by the abnormality type determination unit 132, and output one or more of the abnormality type, the error code, and the countermeasures.

[0065] In addition, when the display screen of display unit 150 is small, for example, an error code associated with the type of abnormality can be displayed, and the user can understand what measures should be taken in response to the displayed error code by, for example, referring to a previously prepared table in which error codes are associated with types of abnormalities and countermeasures.

[0066] Furthermore, the contents output by the output unit 133 and the contents displayed by the display unit 150 may be switched depending on the situation, such as when the displacement sensor 10 is inspected periodically and when the workpiece W is actually being measured. For example, when an abnormality type that may affect the measurement result is determined during operation in which the workpiece W is being measured, the output unit 133 may output a warning signal and replace the measurement result with an indefinite value or an error, and may further display that fact on the display unit 150. Furthermore, when detailed information on the abnormality type is required, continuous time series data and waveforms, etc. may be displayed based on the data of the received light waveform or characteristic information stored in the storage unit 140.

[0067] [Status monitoring method] Next, a status monitoring method for monitoring the status of the displacement sensor 10 and its surrounding environment, including determining the type of abnormality, will be described.

[0068] 9 is a flowchart showing the process flow of a condition monitoring method M10 for monitoring the conditions of the displacement sensor 10 and its surrounding environment, including determining the type of abnormality, while the displacement sensor 10 measures the workpiece W. As shown in FIG 9, the condition monitoring method M10 includes steps S11 to S19, and each step is executed by a processor included in the displacement sensor 10.

[0069] In step S11, as described using FIG. 1, the displacement sensor 10 measures the amount of displacement of the surface of the workpiece W by projecting laser light L1 onto the workpiece W and receiving reflected light L2 from the workpiece W in response to the laser light L1.

[0070] In step S12, the light receiving section 120 receives the light reflected by the workpiece W (inspection area) and outputs a received light waveform.

[0071] In step S13, at least two types of feature information are extracted by feature information extraction unit 131 in control unit 130 based on the received light waveform output in step S12. As specific examples, (1) the amount of received light, (2) a parameter for adjusting the amount of received light, (3) a width value, (4) the number of faces, (5) a total area of ​​the received light waveform, and (6) a background level, which are described with reference to Fig. 4, are extracted as the feature information.

[0072] In step S14, the control unit 130 stores in the storage unit 140 the feature information extracted in step S13.

[0073] In steps S15 to S18, the abnormality type determination unit 132 in the control unit 130 determines the abnormality type based on the characteristic information accumulated in step S14 while referring to the abnormality type information previously stored in the memory. As a specific example, as described with reference to Fig. 5, the abnormality type determination unit 132 determines six abnormality types, namely, (a) sensor dirt, (b) light source deterioration, (c) narrow space measurement, (d) multiple reflections, (e) mutual interference, and (f) disturbance light, for six pieces of characteristic information, namely, (1) amount of received light, (2) light-receiving-amount-adjustment parameter, (3) width value, (4) number of faces, (5) total area of ​​received light waveform, and (6) background level, using three monitoring methods, namely, (A) reference value difference, (B) short-term sudden change, and (C) received light waveform at a certain point in time.

[0074] In step S19, the abnormality type determined in steps S15 to S18 is output by the output unit 133 in the control unit 130. As a specific example, the abnormality type is displayed on the display unit 150.

[0075] The series of processes relating to abnormality type determination in steps S13 to S19 may be executed for each measurement period, or may be executed appropriately as necessary.

[0076] Fig. 10 is a flowchart showing a specific process flow of the abnormality type determination method M100 executed in steps S15 to S18 in Fig. 9. As shown in Fig. 10, the abnormality type determination method M100 includes steps S101 to S116, and each step is executed by a processor included in the displacement sensor 10.

[0077] Here, the abnormality type determination unit 132 determines the abnormality type by monitoring a short-term sudden change (increase or decrease) in each characteristic information and whether or not it is within a reference value range (above or below). The processing in each of these steps will be specifically described.

[0078] In step S101, if (1) the amount of received light falls below the initial reference value and (2) the light receiving amount adjustment parameter exceeds the initial reference value (Yes in step S101), the abnormality type determination unit 132 determines that (b) the light source has deteriorated (step S102).

[0079] Here, the initial reference value is set based on a value detected by teaching when the displacement sensor 10 is purchased and used for the first time, in other words, for grasping the amount of change (difference) in (1) the amount of received light and (2) the light-receiving amount adjustment parameter from the first time the displacement sensor 10 is used. 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 light-receiving amount adjustment parameter.

[0080] If teaching is not performed and an initial reference value is not set when the displacement sensor 10 is purchased and used for the first time, the abnormality type determination unit 132 may not be able to determine (b) light source deterioration. 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 a user setting it.

[0081] In step S103 (No in step S101), the abnormality type determining unit 132 determines whether (4) the number of faces has increased and exceeded the reference value.

[0082] Here, the reference value is set based on a value detected by teaching, for example, at the start of work when the displacement sensor 10 is operated, in other words, for grasping the amount of change (difference) in the characteristic information from the start of work when the displacement sensor 10 is operated. The reference value is preferably set within a range in which the displacement sensor 10 can appropriately measure the workpiece with respect to the characteristic information (including the characteristic information described below). The reference value may be updated for each teaching, or if teaching is not performed at the start of work when the displacement sensor 10 is operated, a value preset in the displacement sensor 10 may be used or may be set by the user.

[0083] In step S104 (Yes in step S103), if (4) the number of faces does not decrease and is not within the reference value range (No in step S104), the abnormality type determining unit 132 determines that (d) multiple reflection has occurred (step S105).

[0084] In step S106 (Yes in step S104), if (4) the number of faces repeatedly increases and decreases (Yes in step S106), the abnormality type determining unit 132 determines that (e) mutual interference has occurred (step S107).

[0085] In step S108 (No in step S103), the abnormality type determination unit 132 determines whether (1) the amount of received light has decreased and fallen below the reference value, or (2) the parameter for adjusting the amount of received light has increased and exceeded the reference value.

[0086] In step S109 (Yes in step S108), if (3) the width value has increased (Yes in step S109), the abnormality type determining unit 132 determines that the abnormality is (a) sensor contamination (step S110).

[0087] In step S111 (No in step S109), if (1) the amount of received light increases and (2) the light-receiving amount adjustment parameter decreases (Yes in step S111), the abnormality type determination unit 132 determines that (c) measurement is in a narrow space (step S112).

[0088] In step S113 (No in step S108), the abnormality type determination unit 132 determines whether (1) the amount of received light has increased and exceeded the reference value, or (2) the parameter for adjusting the amount of received light has decreased and fallen below the reference value.

[0089] In step S114 (Yes in step S113), the abnormality type determining unit 132 determines whether (5) the total area of ​​the received light waveform has increased and exceeded the reference value, and (6) the background level has increased and exceeded the reference value.

[0090] In step S115 (Yes in step S114), if (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 (Yes in step S115), the abnormality type determination unit 132 determines that the abnormality is ambient light (step S116).

[0091] In this way, the abnormality type determination unit 132 determines six abnormality types: (a) sensor contamination, (b) light source degradation, (c) narrow space measurement, (d) multiple reflections, (e) mutual interference, and (f) disturbance light.

[0092] As described above, according to the displacement sensor 10 and the condition monitoring method M10 according to one embodiment of the present invention, the feature information extraction unit 131 extracts a plurality of pieces of feature information from the received light waveform, and the abnormality type determination unit 132 can determine, based on the plurality of pieces of feature information, at least one or more abnormality types among the plurality of abnormality types in the abnormality type information pre-stored in the storage unit 140. As a result, the abnormality type can be appropriately determined, and the user can take measures corresponding to the abnormality type.

[0093] In this embodiment, the abnormality types (a) to (f) shown in FIG. 5 are judged. However, the abnormality types that can be judged may differ depending on the state of the inspection area.

[0094] Fig. 11 is a diagram showing an example of an abnormality type that cannot be judged depending on the presence or absence of a workpiece and a base in the inspection area, among the abnormality types in Fig. 5. As shown in Fig. 11, for the abnormality types (a) to (f), when a workpiece is present in the inspection area, it is possible to appropriately judge, but when a workpiece and a base are not present in the inspection area, it may not be possible to appropriately judge (a) sensor contamination, (c) narrow space measurement, and (d) multiple reflection.

[0095] In this way, depending on the conditions of the inspection area, there are abnormality types that can be appropriately determined and abnormality types that may not be appropriately determined. Therefore, for example, such information may be included in the abnormality type information stored in advance in the memory unit 140.

[0096] As a result, for example, when the abnormality type determination unit 132 determines that the measurement is (c) narrow space measurement, the display unit 150 may display a message saying "When no workpiece is present, appropriate determination may not be possible" or a similar notice may be given to have the user confirm the message. Also, to allow the user to appropriately determine the abnormality type desired, the abnormality type to be determined or the conditions for appropriate determination for each abnormality type may be displayed in advance on the display unit 150 to have the user confirm the condition.

[0097] Furthermore, the user may input a time period that satisfies an appropriate condition (for example, in this embodiment, a work and a base are present) via the operation unit 160. This makes it clear that the abnormality type determined in that time period is an appropriate determination result.

[0098] In the present embodiment, the abnormality type information stored in the storage unit 140 is exemplified by a table in which characteristic information used for determining an abnormality type and a monitoring method are associated with each abnormality type as shown in Fig. 5, but the present invention is not limited to this. For example, a table in which characteristic information and an abnormality type are associated with each monitoring method may be used.

[0099] Fig. 12 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. As shown in Fig. 12, in the monitoring methods (A) to (C), it is possible to grasp which of the characteristic information (1) to (6) is monitored to determine the abnormality types (a) to (f). Here, there are cases where the abnormality type can be uniquely determined by a combination of the monitoring method and the characteristic information, and further, cases where the abnormality type can be determined by a combination of these.

[0100] When a reference value difference is used as the monitoring method, a reference value needs to be set in advance. However, when a short-term sudden change and a received light waveform at a certain point in time are used, the type of abnormality can be determined by comparison with data accumulated in the memory unit 140 and changes, etc., so that it may be possible to determine the type of abnormality even if a reference value is not set in advance.

[0101] In this way, the format of the abnormality type information to be stored in the storage unit 140 may be determined according to the type of the displacement sensor 10, the abnormality type desired by the user, and the specific determination process procedure in the abnormality type determination unit 132. Furthermore, the storage unit 140 may store abnormality type information in a plurality of formats, or may store abnormality type information in a format other than the abnormality type information shown in Figs. 5 and 12.

[0102] The above-described embodiments are intended to facilitate understanding of the present invention, and are not intended to limit the present invention. The elements of the embodiments, as well as their arrangements, materials, conditions, shapes, sizes, etc., are not limited to those shown as examples and can be changed as appropriate. In addition, configurations shown in different embodiments can be partially substituted or combined with each other.

[0103] [Appendix] a light projecting unit (110) that projects light onto an inspection area; a light receiving section (120) that receives light reflected from the inspection area and outputs a received light waveform; a storage unit (140) in which abnormality type information in which a plurality of pieces of characteristic information included in the received light waveform are associated with a plurality of abnormality types predicted from the plurality of pieces of characteristic information is stored in advance; a feature information extraction unit (131) that extracts at least two types of feature information based on a received light waveform output by the light receiving unit; an abnormality type determination unit (132) that determines at least one abnormality type among a plurality of abnormality types in the abnormality type information pre-stored in the storage unit based on the at least two or more types of extracted characteristic information; an output unit (133) that outputs the determined abnormality type; A displacement sensor (10). [Explanation of symbols]

[0104] 10...displacement sensor, 11...cable, 100...sensor head, 110...light-projecting unit, 111...light-emitting element, 112...light-projection control circuit, 120...light-receiving unit, 121...imaging element, 122...signal processing circuit, 123...A / D conversion circuit, 130...control unit, 131...characteristic 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 light, L2...reflected light, B...base, W...work, M10...condition monitoring method, S11 to S19...each step of condition monitoring method M10, M100...abnormality type determination method, S101 to S116...each step of abnormality type determination method M100

Claims

1. a light projection unit that projects light onto an inspection area; a light receiving section that receives light reflected from the inspection area and outputs a received light waveform; a storage unit that stores in advance abnormality type information in which a plurality of pieces of characteristic information included in the received light waveform are associated with a plurality of abnormality types predicted from the plurality of pieces of characteristic information; a feature information extraction unit that extracts at least two types of feature information based on a received light waveform output by the light receiving unit; an abnormality type determination unit that determines at least one abnormality type among a plurality of abnormality types in the abnormality type information pre-stored in the storage unit based on the extracted at least two or more types of characteristic information; an output unit that outputs the determined abnormality type; A displacement sensor comprising:

2. the abnormality type determination unit determines an abnormality type for the extracted characteristic information by using at least one of a difference amount from a reference value, an amount of change in a predetermined period, and information included in a received light waveform at a certain point in time; The displacement sensor according to claim 1 .

3. Among a 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 is classified. The displacement sensor according to claim 2 .

4. The characteristic information includes at least two of the amount of received light, a light-receiving amount adjustment parameter, a width value of the received light waveform, a number of faces of the received light waveform, a total area of ​​the received light waveform, and a background level. The displacement sensor according to claim 1 .

5. the abnormality type determination unit determines an abnormality type according to a combination of at least two or more of the amount of received light, the light-receiving amount adjustment parameter, a width value of the received light waveform, a number of faces of the received light waveform, a total area of ​​the received light waveform, and the background level; The displacement sensor according to claim 4.

6. Among the multiple abnormality types in the abnormality type information pre-stored in the storage unit, the abnormality types that can be determined are classified according to a combination of at least two or more of the amount of received light, the light receiving amount adjustment parameter, the width value of the received light waveform, the number of faces of the received light waveform, the total area of ​​the received light waveform, and the background level. The displacement sensor according to claim 5 .

7. Among the multiple abnormality types in the abnormality type information pre-stored in the storage unit, abnormality types that can be determined depending on the presence or absence of a workpiece and a base in the inspection area are classified. The displacement sensor according to claim 1 .

8. The output unit outputs a countermeasure or an estimated cause corresponding to the determined abnormality type. A displacement sensor according to any one of claims 1 to 7.

9. 1. A condition monitoring method implemented by a displacement sensor including a processor, comprising: a light projection step of projecting light onto an inspection area; a light receiving step of receiving light reflected from the inspection area and outputting a received light waveform; a feature information extracting step of extracting at least two types of feature information based on the received light waveform output in the light receiving step; an abnormality type determination step of determining, based on the extracted at least two or more types of characteristic information, at least one or more types of abnormality among a plurality of abnormality types in abnormality type information, which is stored in advance in a memory and in which a plurality of pieces of characteristic information included in the received light waveform are associated with a plurality of abnormality types predicted from the plurality of pieces of characteristic information; an output step of outputting the determined abnormality type; A condition monitoring method comprising:

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