JP2013147315A - Speed measurement device for elevator, and elevator - Google Patents

Abstract

PROBLEM TO BE SOLVED: To reduce an effect on environment in measuring elevator speed.SOLUTION: A speed measurement device for an elevator includes: an imaging part that supports a car and images an image in a dark view filed of a support member moving according to the movement of the car; and a calculation part that calculates the speed of the car based on the image in the dark view field.

Description

  The present invention relates to a technique for measuring the speed of an elevator.

  As a technique for measuring the speed of a car in an elevator, a contact type speed sensor and a non-contact type speed sensor are known. Although the structure of the contact type speed sensor is simple, an error due to slip may occur. On the other hand, no error due to slip occurs in the non-contact type speed sensor. As a non-contact type speed sensor, a technique for measuring speed using an image photographed by a camera provided on an outer wall surface of a car is known (for example, Patent Documents 1, 2, and 3).

Japanese Patent Laid-Open No. 6-127851 JP 2002-274765 A JP 2011-73885 A

  In the techniques as described above, the quality of the captured image and the speed obtained are affected by the environment. The environment that affects the image is, for example, illumination light, disturbance light when the hoistway is transparent, reflection of light by an oil film on the surface of the guide rail, or the like.

  The present invention has been made to solve the above-described problems, and an object of the present invention is to provide a technique for reducing the influence of the environment in measuring the speed of an elevator.

  In order to solve the above-described problem, an elevator speed measurement device according to the present invention includes a photographing unit that captures a dark field image of a support member that supports a car and moves as the car moves, and the dark field image. And a calculating unit that calculates the speed of the car.

  The elevator according to the present invention is based on a car, a support member that supports the car and moves as the car moves, a photographing unit that captures a dark field image of the support member, and the dark field image. And a calculator for calculating the speed of the car.

  ADVANTAGE OF THE INVENTION According to this invention, in the measurement of the speed of an elevator, the influence of an environment can be reduced.

It is a mimetic diagram showing the structure of the elevator in a first embodiment. It is a schematic diagram which shows the structure of a monitoring part. It is a flowchart which shows a speed measurement process. It is a flowchart which shows a rope breakage detection process. It is a schematic diagram which shows the structure of the monitoring part in 3rd embodiment. It is a perspective view which shows the structure of a perimeter photography part. It is a horizontal sectional view showing the composition of the photographing part in a third embodiment. It is a schematic diagram which shows a rope when a wear trace generate | occur | produces. It is a flowchart which shows a wear trace detection process. It is a flowchart which shows a diameter thinning detection process. It is a flowchart which shows a strand cutting detection process. It is a schematic diagram which shows the case where the cutting | disconnection of the strand of a rope surface generate | occur | produced. It is a schematic diagram which shows the twist collapse of the strand by the cutting | disconnection of the strand inside a rope. It is a flowchart which shows a shape-loss detection process. It is a schematic diagram which shows the deterioration area | region of a rope. It is a flowchart which shows a deterioration detection process. It is a flowchart which shows an abrasion powder detection process. It is a flowchart which shows a vibration detection process. It is a flowchart which shows an imaging | photography part abnormality detection process. It is a table | surface which shows the comparison result of the velocity vector obtained from each imaging | photography part. It is a schematic diagram which shows the position of the mark provided in the rope. It is a schematic diagram which shows the mark provided in the rope. It is a schematic diagram which shows the structure of the monitoring part in 14th embodiment.

  Embodiments of the present invention will be described below with reference to the drawings.

(First embodiment)
Here, an embodiment for measuring the speed of a car based on a dark field image of a rope will be described.

  First, the structure of the elevator 1 of this embodiment is demonstrated.

  Drawing 1 is a mimetic diagram showing the structure of elevator 1 in a first embodiment. The elevator 1 in this embodiment is provided at the uppermost part of the hoistway and is driven to rotate by a driving unit (not shown), a rope 70 hung on a groove around the pulley 210, and one end of the rope 70 A car 200 for loading people and luggage, and a weight 220 connected to the other end of the rope 70 and having a weight equivalent to the weight of the car 200. The elevator 1 further includes a monitoring unit 2 that is fixed in the vicinity of the pulley 210 in the hoistway and monitors the state of the rope 70. The rope 70 supports the car 200 and moves as the car 200 moves. The monitoring unit 2 is fixed to the hoistway. The position of the monitoring unit 2 is between the position where the rope 70 contacts the pulley 210 above the car 200 and the end of the rope 70 on the car 200 side when the car 200 is located at the uppermost end of the hoistway.

  FIG. 2 is a schematic diagram illustrating the configuration of the monitoring unit 2. The monitoring unit 2 includes an imaging unit 10 that captures an image of the rope 70 and a control unit 40 that controls the imaging unit 10 and processes an image from the imaging unit 10. The control unit 40 includes, for example, a memory and a microprocessor. In this case, the microprocessor executes a speed measurement process or the like according to a program stored in advance in the memory. Information stored in the memory may be stored in a storage device such as an HDD (Hard Disk Drive) or may be stored in an external storage device via a network.

  Here, a region facing the monitoring unit 2 on the surface of the rope 70 is set as a target region. The imaging unit 10 includes a light source 30 that performs dark field illumination of a target region, and an image sensor 20 having an opening facing the surface of the rope 70. The image sensor 20 may have a lens or the like. The light source 30 is arranged so that the reflected light from the target area is directed out of the opening of the image sensor 20. The light source 30 may include a lens or the like. Accordingly, the image sensor 20 receives the scattered light from the target area and captures a dark field image of the target area. When the rope 70 is stationary, the opening of the image sensor 20 is separated from the rope 70 by a predetermined distance. The image sensor 20 is, for example, a CCD image sensor or a CMOS image sensor.

  The photographing unit 10 can photograph most of the rope 70 by being installed in the vicinity of the pulley 210. The portion of the rope 70 that is not photographed by the photographing unit 10 is the portion from the end of the rope 70 on the weight 220 side to the photographing unit 10 when the car 200 is located at the lowermost end of the hoistway, and the car 200 is the hoistway. This is a portion from the end of the rope 70 on the side of the car 200 to the photographing unit 10 when located at the uppermost end.

  Next, speed measurement processing by the control unit 40 will be described.

  FIG. 3 is a flowchart showing the speed measurement process. First, the control unit 40 causes the imaging unit 10 to capture a first dark field image that is an image of the target region at time t0, and obtains a first dark field image from the imaging unit 10 (S10). Next, similarly, the control unit 40 causes the imaging unit 10 to capture the second dark field image that is the image of the target region at time t1 after Δt from the time t0, and acquires the second dark field image from the imaging unit 10. (S20). Δt is determined based on the desired velocity resolution.

  Next, the control unit 40 calculates an optical flow from the first dark field image and the second dark field image (S30), calculates a three-dimensional velocity vector of the rope 70 from the calculated optical flow (S40), End the flow. Further, the control unit 40 repeats this flow. Here, in the dark field image, when the width direction of the rope 70 is the X axis, the length direction of the rope 70 is the Y axis, and the depth direction is the Z axis, the Y axis component indicates the car speed in the calculated speed vector. , The X-axis component indicates the blur speed in the width direction of the rope 70, and the Z-axis component indicates the blur speed in the depth direction of the rope 70. Note that the velocity vector calculation method is not limited to the optical flow. Further, the control unit 40 stores the detected velocity vector in the memory. Further, the control unit 40 may transmit information regarding the calculated velocity vector to a management device (not shown). Further, the management device may notify the manager of the elevator 1 by displaying information on the speed vector. Note that the control unit 40 may calculate only the car speed in the Y-axis direction.

(Second embodiment)
Here, an embodiment for detecting a rope break in addition to the speed measurement process will be described.

  The configuration of the elevator 1 of this embodiment is the same as that of the first embodiment.

  Next, the rope breakage detection process will be described.

  FIG. 4 is a flowchart showing the rope breakage detection process. The control unit 40 performs a rope breakage detection process after performing the speed measurement process at least twice. First, the control unit 40 reads a plurality of car speeds stored in the memory (S100), and calculates a change in the car speed, that is, an acceleration (S110). Next, the control unit 40 determines whether or not sudden acceleration has occurred based on the calculated acceleration (S120). That is, the control unit 40 determines whether or not the calculated acceleration exceeds a preset rated acceleration.

  When it is determined that the rapid acceleration has not occurred (S120, N), the control unit 40 determines whether or not the calculated car speed exceeds a preset rated speed (S130).

  When it is determined that the car speed does not exceed the rated speed (S130, N), the control unit 40 determines whether a free fall has occurred based on the calculated acceleration (S140). That is, the control unit 40 determines whether or not the calculated acceleration exceeds a preset free fall threshold.

  When it determines with the free fall not having generate | occur | produced (S140, N), the control part 40 determines with the rope break not having generate | occur | produced, and complete | finishes this flow.

  If it is determined in S120 that sudden acceleration has occurred (S120, Y), if it is determined in S130 that the car speed has exceeded the rated speed (S130, Y), or it is determined in S140 that a free fall has occurred. If it is determined (S140, Y), the control unit 40 determines that the rope break has occurred, notifies the management device of information indicating the rope break (S150), and ends this flow. Moreover, the management apparatus may notify the manager of the elevator 1 by displaying information indicating the rope breakage, or may perform control such as emergency stop of the car 200.

(Third embodiment)
Here, an embodiment in which the target region is the entire circumference of the rope 70 will be described.

  The elevator 1 of this embodiment has a monitoring unit 3 instead of the monitoring unit 2. FIG. 5 is a schematic diagram illustrating the configuration of the monitoring unit 3 in the third embodiment, and FIG. 6 is a perspective view illustrating the configuration of the all-around photographing unit 80. The monitoring unit 3 includes an all-around photographing unit 80 that surrounds the target region of the rope 70 and captures an image of the target region, and a control unit 90 that performs control of the all-around photographing unit 80 and image processing. 5 is a horizontal cross section.

  The all-around photographing unit 80 includes a plurality of photographing units 10 p disposed along the outer periphery of the rope 70. When the rope 70 is stationary, the plurality of imaging units 10p are separated from the rope 70 by a predetermined distance. The control unit 90 has a memory and a microprocessor. The microprocessor executes speed measurement processing and the like according to a program stored in advance in the memory.

  FIG. 7 is a horizontal sectional view showing a configuration of the imaging unit 10p in the third embodiment. Similar to the imaging unit 10, the imaging unit 10 p includes a light source 30 that performs dark field illumination of a part of the target region, and an image sensor 20 having an opening facing the surface of the rope 70.

  The control unit 90 instructs the all-around photographing unit 80 to perform photographing. Upon receiving this instruction, the omnidirectional imaging unit 80 captures a plurality of dark field images simultaneously by the plurality of imaging units 10p. The control unit 90 generates a single all-around dark field image indicating the entire circumference of the rope 70 by combining a plurality of dark field images. That is, the all-around dark field image is an image continuous in the circumferential direction of the rope 70. The synthesis of a plurality of images is performed by a method such as projection, and a shift near a boundary between the plurality of images is corrected.

  In addition, the control unit 90 may perform speed measurement processing based on two all-around dark field images having different shooting times. Moreover, the control part 90 may perform a rope breakage detection process based on the result of several speed measurement processes. In addition, the control unit 90 may instruct photographing periodically.

(Fourth embodiment)
Here, an embodiment will be described in which a wear scar on the rope 70 is detected based on the all-around dark field image.

  The configuration of the elevator 1 of this embodiment is the same as that of the third embodiment.

  FIG. 8 is a schematic diagram showing the rope 70 when wear marks are generated. The all-around dark field image shows a twist pattern on the surface of the rope 70 as shown in FIG. In the example of FIG. 8, wear marks 115 appear in the twist pattern. Therefore, the wear mark 115 can be detected from the difference between the all-around dark field image when the wear mark 115 is not generated and the all-around dark field image when the wear mark 115 is generated.

  Next, the wear mark detection process will be described.

  FIG. 9 is a flowchart showing wear mark detection processing. First, the control unit 90 creates an all-around dark field image generated from a first all-around dark field image, which is an all-around dark field image generated in the past and stored in the memory, and an imaging result after the first all-around dark field image. An alignment process for aligning the position with the second all-around dark field image that is the field image is performed (S200). Here, the control unit 90 may read out the first all-around dark field image and the second all-around dark field image from the memory, instruct the all-around imaging unit 80 to perform imaging, and determine the second all-around circle from the imaging result. A dark field image may be generated. Further, in the alignment process, the control unit 90 causes the first all-around dark field so that the pattern represented in the first all-around dark field image and the pattern represented in the second all-around dark field image overlap as much as possible. The relative position between the image and the second all-around dark field image is calculated.

  Next, the control unit 90 calculates a difference image indicating a difference between the first all-around dark field image and the second all-around dark field image that are aligned with each other (S210).

  Next, the control unit 90 determines whether or not wear marks have occurred based on the difference image (S220). Here, the control unit 90 is a region in which the value of any of the pixels in the difference image exceeds a predetermined pixel value threshold, or a region in which pixels exceeding the predetermined pixel value threshold among the pixels in the difference image are continuous. When the size of the detected area exceeds a predetermined size threshold, it is determined that wear marks have occurred.

  When it is determined that no wear mark is generated (S220, N), the control unit 90 ends this flow.

  On the other hand, if it is determined that a wear mark has occurred (S220, Y), the control unit 90 notifies the management device of information indicating the wear mark (S230), and ends this flow. Moreover, the management apparatus may notify the administrator of the elevator 1 by displaying information indicating the wear scar, or may perform control such as emergency stop of the car 200.

  The first all-around dark field image may be an all-around dark field image generated by the previous shooting and stored in the memory, or may be generated by shooting at a preset time and stored in the memory. Alternatively, an all-around dark field image may be used. Moreover, the calculation of the relative position between the first all-round dark field image and the second all-around dark field image is, for example, a position where the cross-correlation is maximized. In addition, each pixel in the difference image may indicate the magnitude of the difference in luminance between corresponding pixels in the two images.

(Fifth embodiment)
Here, an embodiment will be described in which the diameter of the rope 70 is detected based on the all-around dark field image.

  The configuration of the elevator 1 of this embodiment is the same as that of the third embodiment.

  Next, the diameter loss detection process will be described.

  FIG. 10 is a flowchart showing the diameter loss detection process. In this diameter thinning detection process, first, the control unit 90 extracts surface irregularities of the target region from the all-around dark field image (S300). Irregularities on the surface of the target area appear as shadows in the entire dark field image. Next, the control unit 90 estimates the depth of each of the extracted irregularities (S310). The depth of the extracted unevenness appears as the thickness of the shadow in the entire dark field image.

  Next, the control unit 90 estimates the circumferential length, which is the circumferential length of the rope 70, based on all the circumferential depths (S320), and calculates the diameter of the rope 70 based on the circumferential length (S330). ). Next, the control unit 90 determines whether or not the calculated diameter is smaller than the diameter reference value that is the reference value (S330). The diameter reference value is set to 90% or 92% of the initial value based on, for example, a value determined by the Building Standard Law.

  When the diameter is equal to or larger than the diameter reference value (S330, N), the control unit 90 determines that no diameter loss has occurred and ends this flow.

  On the other hand, when the diameter is smaller than the diameter reference value (S330, Y), the control unit 90 determines that the diameter loss has occurred, notifies the management device of information indicating the diameter loss (S340), and ends this flow. . Moreover, the management apparatus may notify the manager of the elevator 1 by displaying information indicating the diameter loss, or may perform control such as an emergency stop of the car 200.

(Sixth embodiment)
Here, an embodiment in which the strand cutting of the rope 70 is detected based on the all-around dark field image will be described.

  The configuration of the elevator 1 of this embodiment is the same as that of the third embodiment.

  Next, the strand cutting detection process will be described.

  FIG. 11 is a flowchart showing the strand cutting detection process. First, the control unit 90 searches for discontinuous boundaries of the strands on the surface of the rope 70 in the all-around dark field image (S400). FIG. 12 is a schematic diagram showing a case where the strands on the surface of the rope 70 are cut. In this case, the control unit 90 detects the occurrence location 142 of the strand cut on the surface of the rope 70 as a discontinuous boundary of the strand on the surface. Next, the control unit 90 determines whether or not a discontinuous boundary of the surface strand is detected (S410).

  When the discontinuous boundary of the surface strand is not detected (S410, N), the control unit 90 determines that the surface strand is not cut and ends this flow.

  On the other hand, when the discontinuous boundary of the surface strand is detected (S410, Y), the control unit 90 determines that the surface strand is cut (S420), and the strand region from the all-around dark field image Is extracted (S430). FIG. 13 is a schematic diagram showing the breakage of the strand twist due to the cutting of the strands inside the rope 70. In this case, the control unit 90 detects the occurrence location 144 of the strand twist break due to the cutting of the strand inside the rope 70 as a discontinuous boundary of the strand region. Next, the control unit 90 determines whether or not a discontinuous boundary exists in the strand region (S440).

  When it is determined that the discontinuous boundary does not exist in the strand region (S440, N), the control unit 90 notifies the management device of information indicating that the strand cut has occurred (S460), and ends this flow. .

  On the other hand, when it is determined that the discontinuous boundary is present in the strand region (S440, Y), the control unit 90 searches for the discontinuous boundary search result of the surface strand in S410 and the discontinuous boundary of the S440 strand region. Information on the combination with the result is notified to the management apparatus (S450), and this flow is terminated. In addition, the management device may notify the administrator of the elevator 1 by displaying information indicating that the strand cut has occurred or information on the combination, or performing control such as an emergency stop of the car 200. Also good.

(Seventh embodiment)
Here, an embodiment will be described in which a shape collapse (kink) of the rope 70 is detected based on the all-around dark field image.

  The configuration of the elevator 1 of this embodiment is the same as that of the third embodiment.

  Next, the deformation detection process will be described.

  FIG. 14 is a flowchart showing the deformation detection process. In this deformed shape detection process, the process to which the same code | symbol as the process of the abrasion trace detection process was attached | subjected shows the same or equivalent process. First, the control unit 90 performs the alignment process by S200 similar to the wear mark detection process.

  Next, the control unit 90 compares the first omnidirectional dark field image and the second omnidirectional dark field image whose positions are aligned with each other (S510). In this comparison, the difference between the two images may be calculated by pattern matching between the first all-around dark field image and the second all-around dark field image, or the feature amount of the region cut out from the first all-around dark field image And the feature amount of the corresponding region in the second all-around dark field image may be calculated. Next, based on the difference obtained from the comparison result, the control unit 90 determines whether or not a deformation has occurred (S520). Here, for example, the control unit 90 determines that the shape has changed when the calculated magnitude of the difference exceeds a predetermined threshold.

  When it is determined that no deformation has occurred (S520, N), the control unit 90 ends this flow.

  On the other hand, when it is determined that the deformed shape has occurred (S520, Y), the control unit 90 notifies the management apparatus of information indicating the deformed shape (S530), and ends this flow. In addition, the management device may notify the administrator of the elevator 1 by displaying information indicating the deformation, or may perform control such as an emergency stop of the car 200.

  The first all-around dark field image may be an all-around dark field image generated by the previous shooting and stored in the memory, or may be generated by shooting at a preset time and stored in the memory. Alternatively, an all-around dark field image may be used.

(Eighth embodiment)
Here, an embodiment in which deterioration of the rope 70 is detected based on the all-around dark field image will be described.

  The configuration of the elevator 1 of this embodiment is the same as that of the third embodiment.

  Next, the deterioration detection process will be described.

  FIG. 15 is a schematic diagram showing a deteriorated region 162 of the rope 70. Here, the deterioration of the rope 70 is a state in which the rust is generated on the rope 70, a state in which the oil applied to the rope 70 is partially altered, or the like. FIG. 16 is a flowchart showing the deterioration detection process. First, the control unit 90 performs filtering of the all-around dark field image (S600). This filtering suppresses the component indicating the pattern of the rope 70 in the all-around dark field image, and extracts the component indicating the deteriorated region 162. This filtering removes, for example, the linear components of strands and strands. Thereby, the orthogonal component of a linear component is detectable among the degradation areas 162. Next, the control unit 90 determines whether or not a component indicating the degradation region 162 is detected by filtering (S610). Here, the control unit 90 determines that a component indicating the deteriorated region 162 has been detected, for example, when the size of the orthogonal component region exceeds a predetermined size threshold.

  When it is determined that the component indicating the degradation region 162 has not been detected (S610, N), the control unit 90 determines that no degradation has occurred and ends this flow.

  When it is determined that a component indicating the deteriorated region 162 is detected (S610, Y), the control unit 90 interpolates the component indicating the deteriorated region 162 and performs a labeling process on the deteriorated region 162 (S620). In the labeling process, for example, a continuous region having a pixel value within a predetermined range is determined as the degradation region 162. Next, the control unit 90 calculates the area of the degradation region 162 that has been subjected to the labeling process, notifies the management device of information indicating this area (S630), and ends this flow. Moreover, the management apparatus may notify the administrator of the elevator 1 by displaying information indicating the area, or may perform control such as an emergency stop of the car 200 depending on the size of the area.

(Ninth embodiment)
Here, an embodiment will be described in which wear powder or the like of the rope 70 is detected based on the all-around dark field image.

  The configuration of the elevator 1 of this embodiment is the same as that of the third embodiment.

  Next, the wear powder detection process will be described.

  Here, the wear powder detection process can detect foreign matter adhering to the rope 70 in addition to the wear powder. FIG. 17 is a flowchart showing wear powder detection processing. First, the control unit 90 performs labeling processing of the all-around dark field image (S700), and determines each type of the plurality of regions based on the areas of the plurality of regions extracted by the labeling processing (S710).

  When it determines with the area | region not showing the foreign material or abrasion powder in S710 (S710, none), the control part 90 complete | finishes this flow.

  If it is determined in S710 that the area indicates a foreign object (S710, foreign object), the control unit 90 determines that a foreign object has been detected, notifies the management apparatus of information indicating the foreign object (S720), and executes this flow. finish.

  When it is determined in S710 that the area indicates wear powder (S710, wear powder), the control unit 90 calculates the total area of wear powder that is the sum of the areas of the areas indicating wear powder (S740). The wear powder density is calculated from the area of the peripheral dark field image and the total wear powder area (S750), information indicating the wear powder is notified to the management device (S760), and this flow is terminated.

  In S710, if the area of the extracted region is within the preset wear powder area, the control unit 90 determines that the region indicates the wear powder, and the extracted region area is preset. If it is within the range of the area of the foreign object, it is determined that the area indicates the foreign object. Further, the area of the foreign matter is larger than the area of the wear powder. In addition, the management device may notify the administrator of the elevator 1 by displaying information indicating foreign matter or wear powder, or may perform control such as emergency stop of the car 200.

  Moreover, the control part 90 may detect the area | region which shows abrasion powder and the area | region which shows a foreign material from the extracted several area | region.

(Tenth embodiment)
Here, an embodiment in which the vibration of the rope 70 is detected based on the all-around dark field image will be described.

  The configuration of the elevator 1 of this embodiment is the same as that of the third embodiment.

  Next, the vibration detection process will be described.

  Here, the vibration detection process can detect an earthquake, a disconnection of the rope 70, and the like. FIG. 18 is a flowchart showing the vibration detection process. First, the control unit 90 calculates a velocity vector having X, Y, and Z components from the first all-around dark field image and the second all-around dark field image in the same manner as the velocity measurement process of the first embodiment ( S800). Next, the control unit 90 calculates the vibration pattern of the rope 70 based on the calculated speed vector and the current position of the car 200 (S810). Next, the control unit 90 searches for a vibration pattern similar to the calculated vibration pattern from a plurality of vibration patterns registered in advance in the vibration pattern database in the memory (S820). It is determined whether it is similar to any of the registered vibration patterns (S830). In the vibration pattern database, the vibration pattern of the rope 70 that is the initial tremor of the earthquake and whose main component is caused by the horizontal P wave, and the rope 70 that is the main wave of the earthquake and whose main component is caused by the S wave in the vertical direction. A vibration pattern, a vibration pattern of the rope 70 resulting from long-period ground motion in which a weak acceleration lasts for a long time, a vibration pattern indicating a rampage of the rope 70 when the rope 70 is cut, and the like are registered in advance.

  When the calculated vibration pattern is not similar to any of the registered vibration patterns (S830, N), the control unit 90 determines that no abnormal vibration has occurred, and ends this flow.

  On the other hand, when the calculated vibration pattern is similar to any of the registered vibration patterns (S830, Y), the control unit 90 determines that an abnormal vibration has occurred and determines the type of the detected vibration. The information indicating the determined type of vibration is notified to the management device (S840), and this flow ends. Moreover, the management apparatus may notify the administrator of the elevator 1 by displaying information indicating the type of vibration, or may perform control such as an emergency stop of the car 200.

(Eleventh embodiment)
Here, an embodiment will be described in which an abnormality of the photographing unit 10p is detected based on a velocity vector obtained from each of the plurality of photographing units 10p.

  The configuration of the elevator 1 of this embodiment is the same as that of the third embodiment.

  Next, the imaging unit abnormality detection process will be described.

  FIG. 19 is a flowchart illustrating the imaging unit abnormality detection process. First, the control unit 90 performs speed measurement processing using each of the plurality of imaging units 10p (S900). As a result, a plurality of velocity vectors respectively corresponding to the plurality of imaging units 10p are calculated. Next, the control unit 90 compares the calculated plurality of velocity vectors (S910) and determines whether or not the comparison result is abnormal (S920).

  For example, if the magnitude of the difference between the two velocity vectors is equal to or smaller than the threshold value, the control unit 90 determines that the imaging units 10p corresponding to the two velocity vectors are normal. In addition, if the magnitude of the difference between the two velocity vectors exceeds the threshold value, the control unit 90 determines that any one of the imaging units 10p corresponding to the two velocity vectors is abnormal. Furthermore, the control unit 90 determines an abnormal imaging unit 10p by performing determination on all combinations of two velocity vectors. FIG. 20 is a table showing comparison results of velocity vectors obtained from the respective imaging units 10p. Each of the plurality of imaging units 10p is assigned a unique imaging unit identifier A, B, C, D in advance. This table shows the imaging unit identifier of the imaging unit 10p selected as the reference, and the imaging unit identifier of the imaging unit 10p determined to be abnormal by comparing with the reference. In this example, the control unit 90 determines the B imaging unit 10p having the highest number of times determined to be abnormal as the abnormal imaging unit 10p. In other words, the velocity vector obtained from A, C, and D is within the predetermined variation range, and the velocity vector obtained from B is outside the variation range. Instead of comparing the speed vectors, some components of the speed vectors may be compared, such as comparing the car speed.

  Further, the control unit 90 may determine that the values of the plurality of velocity vectors are normal when the values are within a predetermined variation range. The control unit 90 may determine that the imaging unit 10p corresponding to one speed vector is abnormal when one speed vector is out of the variation range among the plurality of speed vectors.

  When it is determined that the comparison result is normal (S920, N), this flow ends.

  On the other hand, when it is determined that the comparison result is abnormal (S920, Y), the control unit 90 notifies the management apparatus of information indicating the abnormal photographing unit 10p (S930), and ends this flow. Moreover, the management apparatus may notify the administrator of the elevator 1 by displaying information indicating the type of vibration, or may perform control such as an emergency stop of the car 200.

(Twelfth embodiment)
Here, an embodiment will be described in which an abnormality of the rope 70 is detected based on all the images in the shootable range of the rope 70.

  The configuration of the elevator 1 of this embodiment is the same as that of the third embodiment.

  The control unit 90 synthesizes the all-around dark field image captured while the car 200 moves between the uppermost end and the lowermost end of the hoistway in the length direction of the rope 70, so A whole image showing all is generated. The control unit 90 may generate an entire image at the time of installation by storing the elevator 1 and store it in a memory. In addition, the control unit 90 may generate a whole image for each day by shooting at a predetermined time every day, and store it in the memory. In addition, the control unit 90 may generate an entire image for each month and store the image in a memory by shooting at a predetermined time every month. Further, the control unit 90 may generate an entire image at the time of the periodic inspection and store it in the memory by taking an image at the time of the periodic inspection.

  Thus, by comparing the entire images stored at different times, it is possible to easily detect the elongation of the rope. Further, the entire image at the time of the periodic inspection can be evidence that the periodic inspection has been performed. Further, the entire image at the time of the periodic inspection is compared with the entire image at the time of the previous periodic inspection, so that a difference due to the passage of time can be easily detected.

(Thirteenth embodiment)
Here, an embodiment will be described in which an abnormality of the rope 70 is detected based on a mark previously attached to the rope 70.

  The configuration of the elevator 1 of this embodiment is the same as that of the third embodiment.

FIG. 21 is a schematic diagram illustrating the positions of the marks 530 and 531 provided on the rope 70, and FIG. 22 is a schematic diagram illustrating the mark 530 provided on the rope 70. For example, the marks 530 and 531 may be provided at positions corresponding to positions where a final limit switch that is one of safety switches of the elevator 1 operates. In this case, the mark 530 provided near the upper end of the shootable range of the rope 70 corresponds to the final limit switch on the lowest floor, and the mark 531 provided near the lower end of the shootable range of the rope 70 is Corresponds to the final limit switch on the top floor. Thereby, the monitoring part 3 can provide the function equivalent to a safety switch.

  Further, the marks 530 and 531 may indicate the same pattern or different patterns. Further, these patterns may be figures or characters.

  When the marks 530 and 531 indicate the same pattern, the control unit 90 recognizes whether the moving direction of the car 200 is the vertical direction based on the sign of the Y component of the velocity vector. When the controller 90 detects the pattern on the rope 70 in a state where the moving direction of the car 200 is recognized as the downward direction, the controller 90 determines that the detected pattern is the mark 530. Further, when the control unit 90 detects the pattern on the rope 70 in a state where the moving direction of the car 200 is recognized as the upward direction, the control unit 90 determines that the detected pattern is the mark 531.

  On the other hand, when the marks 530 and 531 indicate different patterns, the control unit 90 can determine which of the marks 530 and 531 is the detected pattern without using the moving direction.

  Further, by providing a plurality of patterns on the surface of the rope 70, the position of the car 200 can be detected.

(14th embodiment)
Here, an embodiment in which an abnormality is detected based on a dark field image of a piston rod will be described.

  The elevator 1p of this embodiment is a hydraulic type, has a piston rod 600 instead of the rope 70, the pulley 210, and the weight 220, and has a monitoring unit 3p instead of the monitoring unit 3. FIG. 23 is a schematic diagram illustrating a configuration of the monitoring unit 3p according to the fourteenth embodiment. In the monitoring unit 3p, elements denoted by the same reference numerals as those of the monitoring unit 3 indicate the same or corresponding elements. The monitoring unit 3p includes an all-around imaging unit 80p that surrounds the target area of the piston rod 600 and captures an image of the target area, and a control unit 90 that controls the entire circumference imaging unit 80p and performs image processing. The all-around photographing unit 80 includes a plurality of photographing units 10p along the outer periphery of the piston rod 600. The plurality of imaging units 10p are separated from the piston rod 600 by a predetermined distance. The piston rod 600 is driven up and down by a hydraulic cylinder (not shown).

  When the control unit 90 performs the same process as the process for detecting the abnormality of the rope 70 described above, it is possible to detect damage to the piston rod 600, oil leakage from the hydraulic cylinder, and the like.

  According to each of the above-described embodiments, by measuring the speed of the elevator 1 and detecting an abnormality based on the dark field image, the illumination light, disturbance light when the hoistway is transparent, and the guide rail surface The influence of the environment such as light reflection by the oil film can be reduced.

  The elevator speed measuring device described in the claims corresponds to, for example, the monitoring units 2, 3, and 3p. Moreover, the support member described in the claims corresponds to, for example, the rope 70 and the piston rod 600. Moreover, the calculation part described in the claim corresponds to the control parts 40 and 90, for example.

  The light source 30 is a laser light emitting element, an LED, or the like. By using the laser light emitting element, the resolution of the dark field image can be increased.

  The control unit 90 may periodically generate an all-around dark field image by causing the all-around imaging unit 80 to periodically capture a dark field image.

  Moreover, although the schematic diagram etc. which show the surface of the rope 70 showed the case where the rope 70 was a normal twist, the form of another twist may be sufficient.

1, 1p: Elevators 2, 3, 3p: Monitoring unit 10, 10p: Imaging unit 20: Image sensor 30: Light source 40, 90: Control unit 70: Rope 80, 80p: All-around imaging unit 80p: All-around imaging unit 200 : Car 210: Pulley 220: Weight 530, 531: Mark 600: Piston rod

Claims (11)

An elevator speed measuring device,
An imaging unit that captures a dark field image of a support member that supports the cage and moves as the cage moves,
A calculation unit for calculating the speed of the car based on the dark field image,
Elevator speed measurement device. The imaging unit captures two dark field images at different times,
The calculation unit calculates the speed of the car based on the two dark field images.
The elevator speed measuring apparatus according to claim 1. A plurality of photographing units including the photographing unit;
The plurality of photographing units are provided around the support member and are arranged in a circumferential direction of the support member,
The calculation unit detects an abnormality of the support member based on a plurality of dark field images respectively captured by the plurality of imaging units.
The elevator speed measuring apparatus according to claim 1 or 2. The plurality of imaging units respectively shoot a plurality of second dark field images after shooting a plurality of first dark field images,
The calculation unit detects an abnormality of the support member based on the plurality of first dark field images and the plurality of second dark field images.
The elevator speed measuring apparatus according to claim 3. The plurality of photographing units photograph the plurality of dark field images simultaneously,
The calculation unit generates a continuous image in the circumferential direction of the support member by combining the plurality of dark field images, and detects the abnormality based on the images.
The elevator speed measuring apparatus according to any one of claims 3 and 4. The support member is a rope;
The abnormalities are the wear scar of the rope, the diameter of the rope, the cutting of the strand of the rope, the deformation of the rope, the deterioration of the rope, the foreign matter on the rope, the earthquake, Either cutting of the rope,
The elevator speed measuring device according to any one of claims 3 to 5. The plurality of photographing units are fixed to a hoistway above the cage side end of the rope,
The elevator speed measuring apparatus according to claim 6. The calculation unit detects an abnormality in the plurality of imaging units based on a plurality of dark field images captured by the plurality of imaging units, respectively.
The elevator speed measuring device according to any one of claims 3 to 7. The imaging unit captures the dark field image of a pattern provided on a part of the support member,
The calculation unit calculates the position of the car based on the dark field image.
The elevator speed measuring apparatus according to any one of claims 1 to 8. A light source for performing dark field illumination on the support member;
The elevator speed measuring device according to any one of claims 1 to 9. Car and
A support member that supports the car and moves as the car moves;
A photographing unit for photographing a dark field image of the support member;
A calculation unit for calculating the speed of the car based on the dark field image,
elevator.

Images