Method and device for correcting preset position of monitoring camera of transformer substation

Abstract

The invention discloses a method and a device for correcting a preset bit of a monitoring camera of a transformer substation. The method comprises the following steps: acquiring initial preset bit reference parameter data of all equipment in an initial image, and extracting the initial preset bit reference parameter data of any equipment as first initial preset bit reference parameter data; according to the first initial preset bit reference parameter data, reversely calculating to-be-detected preset bit parameter data of other devices in the to-be-detected image; comparing the initial preset bit reference parameter data with the to-be-detected preset bit parameter data, and judging a preset bit offset type; and performing preset bit correction according to the preset bit offset type. According to the technical scheme in the embodiment of the invention, the offset type of the preset bit can be judged, and the preset bit can be corrected.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of substation monitoring, and in particular to a method and device for correcting a preset position of a substation monitoring camera. Background Art

[0002] With the continuous development of the power industry, the continuous expansion of the scale of the power network, the increasingly updated equipment, and the basic formation of the power communication network, the information application of my country's power industry has been continuously deepened many years ago. At present, most substations use "five remote" (telemetry, telecommunication, remote control, remote adjustment, and remote viewing) monitoring, which basically realizes the few-person and unmanned operation, greatly improving the production efficiency of my country's power industry. Directly understand and grasp the situation of each substation and communication station, and can respond to the situation very quickly and timely.

[0003] At present, after installing, configuring and debugging the camera, the PTZ in the substation often saves the camera's shooting position at different angles, focal lengths, exposure and other parameters into the system. However, due to the inherent error of the PTZ transmission structure, the invasion of foreign objects into the PTZ transmission structure, the displacement of the PTZ fixed frame and other factors, the PTZ preset position parameters in the initial state will no longer be applicable, and the PTZ preset position needs to be recalibrated and the preset position parameters updated.

[0004] However, different factors have different effects on the camera, and the correction methods are also different. The transmission error of the gimbal itself is an inherent factor, which should exist throughout the entire gimbal use cycle. In the initial state, the meshing between the gears is relatively sufficient and the error is small. As the running time goes by, the wear between the gears, the loosening of the transmission structure, etc., the error will gradually increase; foreign body intrusion is obviously different from the transmission error of the gimbal. It suddenly intervenes in the system at a certain moment, causing a large error to the system, and due to the irregularity of the foreign body and the random structural characteristics, its impact on each preset position will be different, presenting an irregular error; unlike the above two factors, the offset of the gimbal fixed frame is a fixed offset applied to the gimbal system, which is reflected as a regular error. However, the existing gimbal preset position recalibration method can often only deal with a single influencing factor, resulting in an increase in the misjudgment rate. Therefore, how to achieve more targeted preset position correction and reduce the misjudgment rate has become a problem that needs to be solved in this field. Summary of the invention

[0005] The embodiment of the present invention provides a method and device for correcting the preset position of a substation monitoring camera, which can diagnose the cause of the deviation of the preset position of the substation camera and adopt different re-correction methods for the preset position deviation caused by different reasons.

[0006] In a first aspect, an embodiment of the present invention provides a method for calibrating a preset position of a substation monitoring camera, comprising:

[0007] S1, acquiring initial preset position reference parameter data of all devices in an initial image, and extracting the initial preset position reference parameter data of any device as first initial preset position reference parameter data;

[0008] S2, reversely calculating the to-be-detected preset position parameter data of other devices in the to-be-detected image based on the first initial preset position reference parameter data;

[0009] S3, comparing the initial preset position reference parameter data with the preset position parameter data to be detected, and determining the preset position offset type;

[0010] S4, performing preset position correction according to the preset position offset type.

[0011] Furthermore, the initial preset position reference parameter data includes: horizontal rotation angle, vertical rotation angle and focal length of the device.

[0012] Furthermore, the S1 specifically includes:

[0013] Determining a rotation reference of the initial image in the horizontal direction and the vertical direction;

[0014] Extracting the initial image structural features using SURF algorithm;

[0015] Obtain the inventory data of all equipment in the substation and calculate the corresponding initial preset position benchmark parameter data.

[0016] Furthermore, the S2 specifically includes:

[0017] Extracting the structural features of the image to be detected by using the SURF algorithm, and comparing them with the structural features of the initial image to remove unmatched objects;

[0018] The first initial preset position reference parameter data is substituted into the image to be detected, and the preset position parameter data to be detected of the remaining devices in the image to be detected are reversely calculated.

[0019] Furthermore, the preset position offset types include gimbal fixed frame offset, gimbal transmission error offset and gimbal foreign body intrusion offset.

[0020] Furthermore, the S3 specifically includes:

[0021] respectively calculating the differences between the initial preset position reference parameter data of the remaining devices in the initial image and the preset position parameter data to be detected of the corresponding devices in the image to be detected;

[0022] Obtain the comprehensive calculation results of the corresponding differences of all devices, and determine the preset position offset type according to the comprehensive calculation results:

[0023] If the comprehensive calculation result meets the first preset condition, it is determined that the gimbal fixed frame is offset;

[0024] If the comprehensive calculation result meets the second preset condition, then determine whether the difference calculation results of the individual devices meet the third preset condition:

[0025] When the third preset condition is met, it is determined that the deviation is caused by the transmission error of the gimbal itself; otherwise, it is determined that the deviation is caused by foreign matter intrusion into the gimbal.

[0026] Furthermore, the comprehensive calculation result is:

[0027] ΔDd=Σ(ΔDd Mj 2 +ΔDd Nj ) 2

[0028] Δlr=(ll 0 ) 2 +(rr 0 ) 2

[0029] In the formula, ΔDd Mj , ΔDd Nj are the angle differences between the common device pair in the rows and columns of the initial image and the image to be detected, ΔDd is the square sum of the differences between each device in the rows and columns, and l 0 、r 0 are the angle parameter values ​​of the 0° scale line of the initial image, l and r are the row and column angle values ​​of the 0° scale line of the image to be detected, and Δlr is the sum of squares of the errors between the 0° scale line of the image to be detected and the initial image in rows and columns.

[0030] Furthermore, the first preset condition is ΔDd≤ε 1 And Δlr>ε 2 , the second preset condition is ΔDd>ε 1 And Δlr>ε 2 , where ε 1 and ε 2 These are all pre-set thresholds.

[0031] Furthermore, the third preset condition is:

[0032] ΔDd Mj -ΔDd M1 )∝(M j -M 1

[0033] ΔDd Nj -ΔDd N1 )∝(N j -N1 )

[0034] In the formula, ΔDd M1 , ΔDd N1 are the angle differences between the reference device pair on the rows and columns of the initial image and the image to be detected, (M j ,N j ) is the device pair D j The corresponding image angle parameter value, j≠1, (M 1 ,N 1 ) is the device pair D 1 The corresponding image angle parameter value.

[0035] In a second aspect, an embodiment of the present invention further provides a substation monitoring camera preset position correction device, which is configured to implement the method in the embodiment of the present invention, and the device includes:

[0036] An acquisition unit: used for acquiring the initial preset position reference parameter data of all devices in the initial image, and extracting the initial preset position reference parameter data of any device as the first initial preset position reference parameter data;

[0037] A calculation unit is used to reversely calculate the preset position parameter data to be detected of other devices in the image to be detected according to the first initial preset position reference parameter data;

[0038] A determination unit: used for comparing the initial preset position reference parameter data with the preset position parameter data to be detected, and determining the preset position offset type;

[0039] A correction unit is used to perform preset position correction according to the preset position offset type.

[0040] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0041] at least one processor; and

[0042] a memory communicatively connected to the at least one processor; wherein,

[0043] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the substation monitoring camera preset position correction method described in any embodiment of the present invention.

[0044] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the substation monitoring camera preset position correction method described in any embodiment of the present invention when executed.

[0045] The embodiment of the present invention obtains the initial preset position reference parameter data of all devices from the initial image, extracts the parameter data of one device therefrom as a reference, and then reversely infers the preset position parameter data to be detected of the remaining devices in the image to be detected, and determines the preset position offset type / error type according to the comparison result between the initial preset position reference parameter data and the preset position parameter data to be detected, and then adopts the corresponding correction scheme according to the judgment result. Compared with the prior art, the present invention can perform more targeted preset position correction, effectively improve the accuracy of the preset position correction method, and reduce the misjudgment rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0047] Figure 1 It is a flow chart of a method for calibrating a preset position of a substation monitoring camera provided according to an embodiment of the present invention;

[0048] Figure 2 is a schematic diagram of a 0° scale line of a panoramic image provided according to an embodiment of the present invention;

[0049] Figure 3 is a position relationship diagram between a panoramic image and an image to be detected provided by an embodiment of the present invention;

[0050] Figure 4 It is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0052] Embodiment 1

[0053] Figure 1 A flow chart of the pre-position correction of a surveillance camera in a substation is provided for the first embodiment of the present invention. This embodiment is applicable to the situation of pre-position correction of a surveillance camera. The method can be executed by the pre-position correction device for a surveillance camera in the embodiment of the present invention. The device can be implemented in software and / or hardware and integrated in a computer device. The computer device can be a mobile terminal or a server.

[0054] like Figure 1 As shown, the method specifically comprises the following steps:

[0055] S1, acquiring initial preset position reference parameter data of all devices in an initial image, and extracting the initial preset position reference parameter data of any device as first initial preset position reference parameter data.

[0056] The core of step S1 is to establish an initial preset position reference, wherein the initial image refers to the picture of the remote viewing system camera in the initial state, and the image to be detected in the following text refers to the current remote viewing system camera picture.

[0057] First, an initial image is acquired, and initial preset position reference parameter data of all devices are obtained therefrom, and initial preset position reference parameter data of one device (first initial preset position reference parameter data) is extracted and used as reference data for calculating parameters of the image to be detected in subsequent steps.

[0058] Step S1 specifically includes:

[0059] S11, determining the rotation reference of the initial image in the horizontal direction and the vertical direction.

[0060] Specifically, the core of step S11 is to quantify the initial image preset position, take a specific camera as the object, obtain its panoramic image, and determine the 0° scale lines in the horizontal and vertical directions, so that the camera has a rotation benchmark for reference.

[0061] S12, extracting initial image structural features using SURF algorithm.

[0062] Specifically, the core of step S12 is to extract features from the initial image, extract structural features in the image based on the SURF (Speed ​​Up Robust Features) algorithm, and avoid positioning interference caused by factors such as weather and lighting;

[0063] S13, obtaining the inventory data of all equipment in the substation and calculating the corresponding initial preset position reference parameter data.

[0064] Specifically, the core of step S13 is to calculate the preset reference parameters, and combine the substation equipment ledger data to calculate the initial preset reference parameter data of the equipment within the field of view. The initial preset reference parameter data includes: horizontal rotation angle, vertical rotation angle, focal length, etc. This data is used as the reference control group.

[0065] S2, reversely calculating the to-be-detected preset position parameter data of other devices in the to-be-detected image according to the first initial preset position reference parameter data.

[0066] The core of step S2 is to locate the target in the image to be detected. First, determine the image to be detected and perform the following steps:

[0067] S21, extracting the structural features of the image to be detected by using the SURF algorithm, and comparing them with the structural features of the initial image to remove unmatched objects.

[0068] The core of step S21 is to extract features of the image to be detected, such as extracting structural features in the image to be detected using the SURF algorithm, and comparing them with features extracted from the initial preset position image to remove unmatched objects.

[0069] S22, substituting the first initial preset position reference parameter data into the image to be detected, and reversely calculating the preset position parameter data to be detected of other devices in the image to be detected.

[0070] The core of step S22 is to quantify the preset position of the image to be detected. Taking a certain device determined in step S1 as a reference, the initial preset position reference parameter data of the device is substituted into the image to be detected, that is, the first initial preset position reference parameter data is substituted into the image to be detected, and the preset position parameter data of the remaining devices to be detected are reversely calculated, thereby avoiding the error caused by resetting the reference 0° scale line.

[0071] S3, comparing the initial preset position reference parameter data with the preset position parameter data to be detected, and determining the preset position offset type.

[0072] The core of step S3 is to identify the preset position offset type. Among them, the preset position offset type includes the offset of the gimbal fixed frame, the gimbal's own transmission error offset, and the gimbal foreign body intrusion offset. Before identifying the preset position offset type, first introduce the principles of several offset types / error types:

[0073] (1) The gimbal’s own transmission error offset

[0074] The gimbal achieves horizontal and vertical rotation through motors, gears, belts and other mechanical structures. When the gears are engaged, a certain gap will be generated. This gap will cause a return difference and then cause a preset position deviation. The preset position deviation of this type of camera often starts out very small. As time goes by, the gears, belts and other transmission structures wear out and gradually increase. It is a gradual, approximately linear process.

[0075] (2) PTZ fixed frame offset

[0076] The gimbal fixed structure is affected by various factors, resulting in settlement, deformation, tilt, etc. The camera gimbal fixed on it will inevitably shift accordingly. This type of deviation is a sudden large deviation at a certain moment, and then the deviation no longer changes, which shows a step process.

[0077] (3) Gimbal foreign matter intrusion and deviation

[0078] Foreign objects invade the transmission mechanism such as gears and belts, or the transmission mechanism rusts, causing the transmission mechanism to become stuck and not smooth, and unable to rotate smoothly to the target position. This type of deviation is manifested in that the deviation value of each preset position is not fixed, and it fluctuates, and even affects the visual range of the camera, which manifests as a superposition of noise.

[0079] After understanding the aforementioned preset position offset types, type identification mainly includes two processes: preset position error calculation and deviation type analysis.

[0080] The calculation of the preset position error refers to: S31, respectively calculating the difference between the initial preset position reference parameter data of the remaining devices in the initial image and the preset position parameter data to be detected of the corresponding device in the image to be detected.

[0081] Specifically, the error calculation is performed between the preset position parameters of the horizontal rotation angle and the vertical rotation angle of each device of the image to be detected and the initial reference.

[0082] The deviation type analysis refers to: S32, obtaining a comprehensive calculation result of the corresponding differences of all devices, and determining the preset position offset type according to the comprehensive calculation result.

[0083] Specifically, the preset position error type is analyzed based on the calculated preset position error. The analysis process specifically includes:

[0084] According to the error calculation results of each device, the comprehensive calculation results of the corresponding differences of all devices are obtained: if the comprehensive calculation result meets the first preset condition, it is judged as the offset of the gimbal fixed frame; if the comprehensive calculation result meets the second preset condition, it is judged whether the difference calculation results of each device meet the third preset condition: when the third preset condition is met, it is judged as the gimbal's own transmission error offset, otherwise it is judged as the gimbal foreign body intrusion offset.

[0085] S4, performing preset position correction according to the preset position offset type.

[0086] The core of step S4 is to calibrate the preset position. Step S4 gives the corresponding correction method according to the analysis results in step S32. For errors caused by foreign body intrusion, the camera needs to be disassembled, cleaned, and maintained, and the initial preset position needs to be updated; for the offset error of the pan-tilt structure, the equipment within its field of view needs to be re-evaluated. If it does not affect the observation equipment, the initial preset position is directly updated. Otherwise, the camera needs to be reinstalled and adjusted; for the transmission error of the pan-tilt itself, the initial preset position can be directly updated.

[0087] A specific implementation process of steps S1 to S4 is as follows:

[0088] In order to reasonably set the preset position of the camera, it is first necessary to scale the panoramic image, determine the horizontal and vertical 0° scale lines of the image, and record the pixel row and column values ​​where the scale lines are located (l 0 ,r 0 ),like Figure 2 A schematic diagram of the 0° scale line of a panoramic image is shown in the figure. Based on SURF, the structural feature information in the panoramic image is extracted, and the clear imaging equipment in the panoramic image is classified and sorted according to the data information such as the substation equipment ledger and the equipment field of view, and the horizontal angle, vertical angle and focal length of each device are recorded. SURF has the advantages of scale invariance, and even if the rotation angle, brightness or shooting angle of the image are changed, it can reduce the influence of factors such as weather and lighting on positioning.

[0089] Similarly, the structural features of the image to be detected are extracted. Here, the focal length of the image to be detected must be consistent with the focal length of the image in the initial state, otherwise the correction conditions are not met. The preset position parameters of each device are recorded based on the equipment ledger. For the image to be detected, in order to avoid the error caused by the inconsistent division of the 0° scale line, this embodiment takes one of the devices as the object, extracts the parameter value of the device in the initial image, and reversely calculates the parameter values ​​of each device. The principle is as follows:

[0090] Taking device 1 and device 2 as examples, the parameter value of device 1 in the initial image is (m 1 ,n 1 ), the pixel values ​​of device 1 and device 2 in the image to be detected are p 1 (x 1 ,y 1 ), p 2 (x 2 ,y 2 ), θ is the angle value represented by each unit pixel. Let the parameter value of device 1 (m 1 ,n 1 ) is the reference in the image to be detected, so the parameter value of device 2 (m 2 ,n 2 ) is calculated as follows:

[0091]

[0092] Similarly, the row and column values ​​of the 0° scale line of the image to be detected are reversed as shown below.

[0093]

[0094] Where l and r are the row and column angle values ​​of the 0° scale line of the image to be detected.

[0095] Figure 3 A position relationship diagram between a panoramic image and an image to be detected is provided for an embodiment of the present invention, such as Figure 3 As shown in the figure, the initial panoramic image when the camera is installed and the panoramic image to be detected after running for a period of time are respectively shown.

[0096] For the common device pairs of the initial image and the image to be detected, they are denoted as D i (M i ,N i ), d i (m i ,n i ), (i=1, 2, 3···), where (M i ,N i )、(m i ,n i ) are the device pairs D i d i The corresponding image angle parameter value. Here, the device represented by i=1 is used as the benchmark, and the difference between the initial image and the remaining device parameter values ​​in the image to be detected is calculated as follows:

[0097]

[0098] In the formula, ΔDd Mj , ΔDd Nj are the angle differences of the common device pair on the rows and columns of the initial image and the image to be detected, (M j ,N j )、(m j ,n j ) are the device pairs D j d j The corresponding image angle parameter value.

[0099] The reason for the deviation between the two images is analyzed based on the parameter value difference between each common device pair, as follows:

[0100]

[0101] Where ΔDd is the sum of squares of the differences between rows and columns of each device, reflecting the cumulative error between the two images, l 0 、r 0 are the angle parameter values ​​of the 0° scale line of the initial image, and Δlr is the sum of squares of the errors between the 0° scale line of the image to be detected and the initial image in rows and columns.

[0102] According to formula (4), the comprehensive calculation results are obtained and judged:

[0103] If ΔDd≤ε 1 And Δlr≤ε2 , it can be considered that the camera PTZ preset position deviation is small and can be ignored;

[0104] If ΔDd≤ε 1 And Δlr>ε 2 , it is considered that the PTZ fixed structure is offset, resulting in the offset of the 0° scale line. It is necessary to determine whether the camera needs to be adjusted based on the impact on the observation equipment. If the camera is adjusted, the initial preset position reference value needs to be reset;

[0105] If ΔDd>ε 1 And Δlr>ε 2 , we need to further analyze the causes of the change, where ε 1 , ε 2 For the pre-set threshold:

[0106] If ΔDd Mj , ΔDd Nj Respectively meet:

[0107]

[0108] This indicates that the preset position deviation is the transmission error offset of the PTZ itself, that is, due to the transmission error of the device itself, the gear and belt transmission process are not fully engaged, and the error caused will be linearly accumulated to the offset. During the life cycle of the device, you only need to re-update the preset position parameters with the current parameter values.

[0109] If the relationship reflected by equation (5) is not satisfied, there is an irregular relationship between the preset position error and the rotation angle, and it is determined that there is foreign matter intruding into the camera pan / tilt. The camera needs to be disassembled, repaired, and reinstalled to set the preset position.

[0110] The technical solution of the embodiment of the present invention records images at different times, compares them with the preset position images in the initial state, analyzes the offset direction and offset amount of the preset position images at different positions, summarizes the regularity analysis, determines the cause of the offset, and guides the pre-position re-calibration work of the substation camera.

[0111] Embodiment 2

[0112] This embodiment provides a substation surveillance camera preset position correction device, which can be applicable to the situation of surveillance camera preset position correction. The device can be implemented in software and / or hardware and integrated in a computer device. The system can be integrated in any device that provides the function of substation surveillance camera preset position correction. The substation surveillance camera preset position correction device specifically includes:

[0113] An acquisition unit: used for acquiring the initial preset position reference parameter data of all devices in the initial image, and extracting the initial preset position reference parameter data of any device as the first initial preset position reference parameter data;

[0114] A calculation unit is used to reversely calculate the preset position parameter data to be detected of other devices in the image to be detected according to the first initial preset position reference parameter data;

[0115] A determination unit: used for comparing the initial preset position reference parameter data with the preset position parameter data to be detected, and determining the preset position offset type;

[0116] A correction unit is used to perform preset position correction according to the preset position offset type.

[0117] Furthermore, the initial preset position reference parameter data includes a horizontal rotation angle, a vertical rotation angle, a focal length, and the like.

[0118] Furthermore, the acquisition unit is also specifically used for:

[0119] Determine the rotation reference of the initial image in the horizontal and vertical directions;

[0120] Use SURF algorithm to extract initial image structural features;

[0121] Obtain the inventory data of all equipment in the substation and calculate the corresponding initial preset position benchmark parameter data.

[0122] Furthermore, the calculation unit is also specifically used for:

[0123] The SURF algorithm is used to extract the structural features of the image to be detected, and compared with the structural features of the initial image to remove mismatched objects;

[0124] The first initial preset position reference parameter data is substituted into the image to be detected, and the preset position parameter data to be detected of the remaining devices in the image to be detected are reversely calculated.

[0125] Furthermore, the preset position offset types include gimbal fixed frame offset, gimbal transmission error offset, gimbal foreign body intrusion offset, and the like.

[0126] Furthermore, the discrimination unit is also specifically used for:

[0127] Calculate the difference between the initial preset position reference parameter data of the remaining devices in the initial image and the preset position parameter data of the corresponding devices in the image to be detected; obtain the comprehensive calculation result of the corresponding difference values ​​of all devices, and determine the preset position offset type according to the comprehensive calculation result:

[0128] If the comprehensive calculation result meets the first preset condition, it is determined that the gimbal fixed frame is offset;

[0129] If the comprehensive calculation result meets the second preset condition, then determine whether the difference calculation results of a single device meet the third preset condition:

[0130] When the third preset condition is met, it is determined that the gimbal is offset due to transmission error of the gimbal itself; otherwise, it is determined that the gimbal is offset due to foreign matter intrusion.

[0131] Furthermore, the comprehensive calculation results are:

[0132] ΔDd=Σ(ΔDd Mj 2 +ΔDd Nj ) 2

[0133] Δlr=(ll 0 ) 2 +(rr 0 ) 2

[0134] In the formula, ΔDd Mj , ΔDd Nj are the angle differences between the common device pair in the rows and columns of the initial image and the image to be detected, ΔDd is the square sum of the differences between each device in the rows and columns, and l 0 、r 0 are the angle parameter values ​​of the 0° scale line of the initial image, l and r are the row and column angle values ​​of the 0° scale line of the image to be detected, and Δlr is the sum of squares of the errors between the 0° scale line of the image to be detected and the initial image in rows and columns.

[0135] Furthermore, the first preset condition is ΔDd≤ε 1 And Δlr>ε 2 , the second preset condition is ΔDd>ε 1 And Δlr>ε 2 , where ε 1 and ε 2 These are all pre-set thresholds.

[0136] Furthermore, the third preset condition is:

[0137] ΔDd Mj -ΔDd M1 )∝(M j -M 1

[0138] ΔDd Nj -ΔDd N1 )∝(N j -N 1 )

[0139] In the formula, ΔDd M1 , ΔDdN1 are the angle differences between the reference device pair on the rows and columns of the initial image and the image to be detected, (M j ,N j ) is the device pair D j The corresponding image angle parameter value, j≠1, (M 1 ,N 1 ) is the device pair D 1 The corresponding image angle parameter value.

[0140] The above-mentioned product can execute the method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0141] The technical solution of the embodiment of the present invention analyzes the causes of the differences between the current remote viewing system camera image and the image in the initial state by comparing the differences between the two, and proposes different solutions accordingly, thereby providing a new reference basis for the recalibration of the substation remote viewing system.

[0142] Embodiment 3

[0143] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0144] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0145] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0146] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, for example, implementing the substation monitoring camera preset position correction method provided in the above embodiment of the present invention:

[0147] Acquire initial preset position reference parameter data of all devices in the initial image, and extract the initial preset position reference parameter data of any device as first initial preset position reference parameter data;

[0148] According to the first initial preset position reference parameter data, reversely infer the preset position parameter data to be detected of the remaining devices in the image to be detected;

[0149] Compare the initial preset position reference parameter data with the preset position parameter data to be detected to determine the preset position offset type;

[0150] Perform preset position correction according to the preset position offset type.

[0151] In some embodiments, the substation surveillance camera preset position correction method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the substation surveillance camera preset position correction method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the substation surveillance camera preset position correction method in any other appropriate manner (for example, by means of firmware).

[0152] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0153] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0154] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0155] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0156] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0157] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0158] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0159] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for calibrating a preset position of a substation monitoring camera, characterized in that: include: S1, acquiring initial preset position reference parameter data of all devices in an initial image, and extracting the initial preset position reference parameter data of any device as first initial preset position reference parameter data; S2, reversely calculating the to-be-detected preset position parameter data of other devices in the to-be-detected image based on the first initial preset position reference parameter data; S3, comparing the initial preset position reference parameter data with the preset position parameter data to be detected, and determining the preset position offset type; S4, performing preset position correction according to the preset position offset type.

2. The method according to claim 1, characterized in that The initial preset position reference parameter data includes: horizontal rotation angle, vertical rotation angle and focal length of the device.

3. The method according to claim 1, characterized in that The S1 specifically includes: Determining a rotation reference of the initial image in the horizontal direction and the vertical direction; Extracting the initial image structural features using SURF algorithm; Obtain the inventory data of all equipment in the substation and calculate the corresponding initial preset position benchmark parameter data.

4. The method according to claim 1, characterized in that: The S2 specifically includes: Extracting the structural features of the image to be detected by using the SURF algorithm, and comparing them with the structural features of the initial image to remove unmatched objects; The first initial preset position reference parameter data is substituted into the image to be detected, and the preset position parameter data to be detected of the remaining devices in the image to be detected are reversely calculated.

5. The method according to claim 1, characterized in that The preset position offset types include gimbal fixed frame offset, gimbal transmission error offset and gimbal foreign body intrusion offset.

6. The method according to claim 1, characterized in that The S3 specifically includes: respectively calculating the differences between the initial preset position reference parameter data of the remaining devices in the initial image and the preset position parameter data to be detected of the corresponding devices in the image to be detected; Obtain the comprehensive calculation results of the corresponding differences of all devices, and determine the preset position offset type according to the comprehensive calculation results: If the comprehensive calculation result meets the first preset condition, it is determined that the gimbal fixed frame is offset; If the comprehensive calculation result meets the second preset condition, then determine whether the difference calculation results of the individual devices meet the third preset condition: When the third preset condition is met, it is determined that the deviation is caused by the transmission error of the gimbal itself; otherwise, it is determined that the deviation is caused by foreign matter intrusion into the gimbal.

7. The method according to claim 6, characterized in that The comprehensive calculation result is: ΔDd=∑(ΔDd Mj 2 +ΔDd Nj ) 2 Δlr= ( l-l 0) 2 + ( r-r 0) 2 In the formula, ΔDd Mj , ΔDd Nj are the angular differences between the common device pairs in the rows and columns of the initial image and the image to be detected, ΔDd is the sum of the squares of the differences of each device in the rows and columns, l0 and r0 are the angle parameter values ​​of the 0° scale line of the initial image, l and r are the angle values ​​of the row and column where the 0° scale line of the image to be detected is located, Δlr is the sum of the squares of the errors between the 0° scale line of the image to be detected and the initial image in the rows and columns.

8. The method according to claim 6, characterized in that The first preset condition is ΔDd≤ε1 and Δlr>ε2, and the second preset condition is ΔDd>ε1 and Δlr>ε2, wherein ε1 and ε2 are both preset thresholds.

9. The method according to claim 6, characterized in that The third preset condition is: (ΔDd Mj -ΔDd M1 ) ∝ ( M j -M1 ) (ΔDd Nj -ΔDd N1 ) ∝ ( N j -N1 ) In the formula, ΔDd M1 , ΔDd N1 are the angle differences between the reference device pair on the rows and columns of the initial image and the image to be detected, ( M j ,N j ) For device pair D j The corresponding image angle parameter value, j≠1, ( M1,N1 ) It is the image angle parameter value corresponding to the device pair D1.

10. A substation monitoring camera preset position correction device, characterized in that: include: An acquisition unit: used for acquiring initial preset position reference parameter data of all devices in the initial image, and extracting the initial preset position reference parameter data of any device as first initial preset position reference parameter data; A calculation unit is used to reversely calculate the preset position parameter data to be detected of other devices in the image to be detected according to the first initial preset position reference parameter data; A determination unit: used for comparing the initial preset position reference parameter data with the preset position parameter data to be detected, and determining the preset position offset type; A correction unit is used to perform preset position correction according to the preset position offset type.

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