Microcrystal phosphor copper ball digital internet-of-things monitoring method

Abstract

The invention provides a microcrystal phosphor copper ball digital Internet of Things monitoring method, which comprises the following steps of S1, acquiring video shooting data shot by a camera, and acquiring video parameters of the video shooting data according to the video shooting data; s2, generating new video shooting data according to the video shooting data and the video parameters; s3, uploading the new video shooting data to a monitoring platform; s4, after the monitoring platform receives the new video shooting data, obtaining the video shooting data shot by the camera according to the new video shooting data received by the monitoring platform; and S5, storing video shooting data shot by the camera in a monitoring platform. According to the invention, the production process of the microcrystal phosphor copper balls can be monitored and uploaded safely, and subsequent checking of monitoring videos is guaranteed.

Description

Technical Field

[0001] The invention relates to the field of digital monitoring technology, and in particular to a digital Internet of Things monitoring method for microcrystalline phosphor copper balls. Background Art

[0002] Phosphor copper balls are raw materials for electroplating of various products such as PCB circuit boards, LED components, hardware parts, etc. Microcrystalline phosphor copper balls have fine and uniform grain structure, which can exert better electroplating performance and are usually used for electroplating of advanced circuit boards. In the process of producing microcrystalline phosphor copper ball products, the production process should be monitored to facilitate subsequent inspection and monitoring. Summary of the invention

[0003] The present invention aims to at least solve the technical problems existing in the prior art, and in particular innovatively proposes a digital Internet of Things monitoring method for microcrystalline phosphor copper balls.

[0004] In order to achieve the above-mentioned purpose of the present invention, the present invention provides a digital Internet of Things monitoring system for microcrystalline phosphor copper balls, including a camera installed in a factory building for producing microcrystalline phosphor copper balls, and also including a microcrystalline phosphor copper ball monitoring platform, which securely uploads the video data captured by the camera to the monitoring platform through the Internet of Things.

[0005] In a preferred implementation of the present invention, the video data captured by the camera is uploaded to the monitoring platform via the 10 Gigabit network port.

[0006] In a preferred embodiment of the present invention, the camera is a wide-angle ultra-high-definition camera.

[0007] The present invention also discloses a digital Internet of Things monitoring method for microcrystalline phosphor copper balls, comprising the following steps:

[0008] S1, obtaining video shooting data shot by a camera, and obtaining video parameters of the video shooting data according to the video shooting data;

[0009] S2, generating new video shooting data according to the video shooting data and video parameters;

[0010] S3, upload the new video data to the monitoring platform;

[0011] S4, after the monitoring platform receives the new video shooting data, the video shooting data shot by the camera is obtained according to the new video shooting data received by the monitoring platform;

[0012] S5, storing the video data captured by the camera in the monitoring platform for use in monitoring the video.

[0013] In a preferred embodiment of the present invention, the video parameters include one or any combination of frame rate, resolution and duration.

[0014] In a preferred embodiment of the present invention, the method for generating new video shooting data according to the video shooting data and the video parameters in step S2 comprises the following steps:

[0015] S21, generating the number of images P according to the frame rate and duration;

[0016] S22, converting the video shooting data into P images, and naming the P images in sequence as the first image, the second image, the third image, ..., the Pth image in a playback order;

[0017] S23, converting the video shooting data into a video data string using a video conversion algorithm;

[0018] S24, generating P new video images using the video data string and the P images;

[0019] S25, generating new video shooting data from the P new video images in sequence, and using the video data string as the video name of the new video shooting data.

[0020] In a preferred embodiment of the present invention, the method for generating the number of images according to the frame rate and duration in step S21 is:

[0021] P = fps × T,

[0022] Among them, fps represents the frame rate of video shooting data;

[0023] T represents the duration of the video shooting data;

[0024] P represents the number of images of the video shooting data.

[0025] In a preferred embodiment of the present invention, the method of generating P new video images using the video data string and P images in step S24 is:

[0026]

[0027] Among them, (Q j (x,y) R ,Q j (x,y) G ,Q j (x,y) B ) represents the color value of the jth image at the pixel point (x, y); (Q′ j (x,y) R ,Q′ j (x,y) G ,Q′ j (x,y) B ) represents the new color value of the j-th image at the pixel point (x, y);

[0028] j=1, 2, 3, ..., P, where P represents the number of images of the video shooting data;

[0029] x=1, 2, 3, ..., X, y=1, 2, 3, ..., Y, X×Y represents the resolution of the video shooting data;

[0030] ω represents a data string operator;

[0031] Videostring 1～ε Indicates the data string from bit 1 to bit ε in the video data string; ε indicates the color depth;

[0032] Videostring ε+1～2ε Represents the data string from ε+1 to 2ε in the video data string;

[0033] Videostring 2ε+1～3ε Represents the data string from the 2ε+1th to the 3εth bits in the video data string.

[0034] In a preferred embodiment of the present invention, the method of converting the video shooting data into a video data string using a video conversion algorithm in step S23 is:

[0035] Videostring=Video conversion method(picstring),

[0036] Wherein, Videostring represents the video data string;

[0037] Video conversion method() represents the video conversion algorithm;

[0038] picstring represents the image stitching data string;

[0039] Videostring j =Video conversion method(Q j ),

[0040] Among them, Videostring j represents the j-th image data string;

[0041] Video conversion method() indicates the video conversion algorithm; preferably, a digest algorithm is used; SHA-2 is the best;

[0042] Q j represents the j-th image; j=1, 2, 3, ..., P, where P represents the number of images of the video shooting data;

[0043] picstring=Videostring1-Videostring2-Videostring3-…-Videostring P

[0044] Among them, picstring represents the image stitching data string;

[0045] Videostring j represents the j-th image data string; j=1, 2, 3, ..., P, where P represents the number of images of the video shooting data;

[0046] - indicates the data string concatenation character;

[0047] Videostring1 represents the first video data string;

[0048] Videostring2 represents the second image data string;

[0049] Videostring3 represents the third video data string;

[0050] Videostring P Represents the Pth image data string.

[0051] In a preferred embodiment of the present invention, the rule of the data string operator ω in step S24 is:

[0052]

[0053] A1 is 0 or 1, A2 is 0 or 1, and A3 is 0 or 1.

[0054] The present invention also discloses a computer system, comprising:

[0055] processor;

[0056] a memory for storing processor-executable instructions;

[0057] Wherein, the processor is configured to implement the microcrystalline phosphor copper ball digital Internet of Things monitoring method when executing the executable instructions.

[0058] The present invention also discloses a computer-readable storage medium, comprising:

[0059] a memory having a computer program stored thereon;

[0060] A processor is used to execute the program in the memory to implement the microcrystalline phosphor copper ball digital Internet of Things monitoring method.

[0061] In summary, due to the adoption of the above technical solution, the present invention can monitor the production process of microcrystalline phosphor copper balls and upload it safely, ensuring the subsequent viewing of the monitoring video.

[0062] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0064] Figure 1 It is a schematic block diagram of the process of the present invention. DETAILED DESCRIPTION

[0065] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0066] The invention discloses a digital Internet of Things monitoring system for microcrystalline phosphor copper balls, comprising a camera installed in a plant for producing microcrystalline phosphor copper balls, and a microcrystalline phosphor copper ball monitoring platform, wherein video data captured by the camera is securely uploaded to the monitoring platform via the Internet of Things.

[0067] In a preferred implementation of the present invention, the video data captured by the camera is uploaded to the monitoring platform via the 10 Gigabit network port.

[0068] In a preferred embodiment of the present invention, the camera is a wide-angle ultra-high-definition camera.

[0069] The present invention also discloses a digital Internet of Things monitoring method for microcrystalline phosphor copper balls, such as Figure 1 As shown, the following steps are included:

[0070] S1, obtaining video shooting data shot by a camera, and obtaining video parameters of the video shooting data according to the video shooting data, where the video parameters include frame rate, resolution and duration;

[0071] S2, generating new video shooting data according to the video shooting data and video parameters;

[0072] S3, upload the new video data to the monitoring platform;

[0073] S4, after the monitoring platform receives the new video shooting data, the video shooting data shot by the camera is obtained according to the new video shooting data received by the monitoring platform;

[0074] S5, storing the video data captured by the camera in the monitoring platform for use in monitoring the video.

[0075] In a preferred embodiment of the present invention, the method for generating new video shooting data according to the video shooting data and the video parameters in step S2 comprises the following steps:

[0076] S21, generating the number of images P according to the frame rate and duration;

[0077] S22, converting the video shooting data into P images, and naming the P images in sequence as the first image, the second image, the third image, ..., the Pth image in a playback order;

[0078] S23, converting the video shooting data into a video data string using a video conversion algorithm;

[0079] S24, generating P new video images using the video data string and the P images;

[0080] S25, generating new video shooting data from the P new video images in sequence, and using the video data string as the video name of the new video shooting data.

[0081] In a preferred embodiment of the present invention, the method for generating the number of images according to the frame rate and duration in step S21 is:

[0082] P = fps × T,

[0083] Among them, fps represents the frame rate of video shooting data;

[0084] T represents the duration of the video shooting data;

[0085] P represents the number of images of the video shooting data.

[0086] In a preferred embodiment of the present invention, the method of converting the video shooting data into a video data string using a video conversion algorithm in step S23 is:

[0087] Videostring=Video conversion method(picstring),

[0088] Wherein, Videostring represents the video data string;

[0089] Video conversion method() indicates the video conversion algorithm; preferably, a digest algorithm is used; SHA-2 is the best;

[0090] picstring represents the image stitching data string;

[0091] Videostring j =Video conversion method(Q j ),

[0092] Among them, Videostring j represents the j-th image data string;

[0093] Video conversion method() represents the video conversion algorithm; preferably, a digest algorithm is used; SHA-2 (SHA256) is the best; and its binary number is 256 bits.

[0094] Q j represents the j-th image; j=1, 2, 3, ..., P, where P represents the number of images of the video shooting data;

[0095] picstring=Videostring1-Videostring2-Videostring3-…-Videostring P

[0096] Among them, picstring represents the image stitching data string;

[0097] Videostring j represents the j-th image data string; j=1, 2, 3, ..., P, where P represents the number of images of the video shooting data;

[0098] - indicates the data string concatenation character;

[0099] Videostring1 represents the first video data string;

[0100] Videostring2 represents the second image data string;

[0101] Videostring3 represents the third video data string;

[0102] Videostring P Represents the Pth image data string.

[0103] For example, Videostring1=1011011100, Videostring1=10100111011, Videostring1=10110001100, Videostring1=101110111010, then P=4, picstring=10110111001010011101110110001100101110111010.

[0104] In a preferred embodiment of the present invention, the method of generating P new video images using the video data string and P images in step S24 is:

[0105]

[0106] Among them, (Q j (x,y) R ,Q j (x,y) G ,Q j (x,y) B ) represents the color value of the jth image at the pixel point (x, y); (Q′ j (x,y) R ,Q′ j (x,y) G ,Q′ j (x,y) B ) represents the new color value of the j-th image at the pixel point (x, y);

[0107] j=1, 2, 3, ..., P, where P represents the number of images of the video shooting data;

[0108] x=1, 2, 3, ..., X, y=1, 2, 3, ..., Y, X×Y represents the resolution of the video data; X is the number of horizontal pixels in the resolution, and Y is the number of vertical pixels in the resolution;

[0109] ω represents a data string operator;

[0110] Videostring 1～ε Represents the data string from the 1st bit to the ε bit in the video data string; ε represents the color depth; wherein, the number of binary value bits of the red pixel value, green pixel value and blue pixel value in the color value should be consistent with ε. If they are inconsistent, add 0 in front of the binary value to make it consistent.

[0111] Videostring ε+1～2ε Represents the data string from ε+1 to 2ε in the video data string;

[0112] Videostring 2ε+1～3ε Represents the data string from the 2ε+1th to the 3εth bits in the video data string.

[0113] In a preferred embodiment of the present invention, the rule of the data string operator ω in step S24 is:

[0114]

[0115] A1 is 0 or 1, A2 is 0 or 1, and A3 is 0 or 1. A1, A2, and A3 are the values ​​involved in the calculation.

[0116] For example, Q j (x,y) R =10011110,Videostring=001101111011010100011001000011110111110010011111101 1100110001110011001110001100001000100101100001111111011001001010111100000 1110000000101101000100101011001010101111100100001010011110110000010011000100110000010101010100010101010111101101011001100010101011100011, the corresponding Videostring 1～8 =00110111, then Q′ j (x,y) R =1010110 or 01010110;

[0117] For example, Q j (x,y) G =1010010,Videostring=0011011110110101000110010000111101111100100111111011 1001100011100110011100011000010001001011000011111110110010010101111000001 110000000101101000100101011001010101111100100001010011110110000010011000100110000010101010100010101010111101101011001100010101011100011, the corresponding Videostring 9～16 =10110101, then Q′ j (x,y) G =11000 or 00011000.

[0118] In a preferred embodiment of the present invention, obtaining the video shooting data shot by the camera according to the new video shooting data received by the monitoring platform in step S4 includes the following steps:

[0119] S41, acquiring video parameters of the received new video shooting data according to the received new video shooting data, where the video parameters include frame rate, resolution and duration;

[0120] S42, generating the number of images P′ according to the frame rate and duration;

[0121] S42, converting the received new video shooting data into P′ platform images, and naming the P′ images in sequence as the first platform image, the second platform image, the third platform image, ..., the P′ platform image in the playback order;

[0122] S44, obtaining the video name of the received new video shooting data;

[0123] S45, generating P platform video images using the video name and the P platform images;

[0124] S46, generating platform video data from the P platform video images in sequence.

[0125] In a preferred embodiment of the present invention, the method for generating the number of images P′ according to the frame rate and duration in step S42 is:

[0126] P′=fps′×T′,

[0127] Wherein, fps′ represents the frame rate of the new video shooting data received;

[0128] T′ represents the duration of the new video shooting data received;

[0129] P′ represents the number of images of the received new video capture data.

[0130] In a preferred embodiment of the present invention, the method of generating P platform video images using the video name and P images in step S45 is:

[0131]

[0132] Among them, (Q″′ j′ (x′,y′) R ,Q″ j′ (x′,y′) G ,Q″ j′ (x′,y′) B ) represents the color value of the j′th platform image at the pixel point (x′, y′);

[0133] (Q″′ j (x′,y′) R ,Q″′ j (x′,y′) G,Q″′ j (x′,y′) B ) represents the new color value of the j′th platform image at the pixel point (x′, y′);

[0134] j′=1, 2, 3, ..., P′, where P′ represents the number of images of the received new video capture data;

[0135] x′=1, 2, 3, ..., X′, y′=1, 2, 3, ..., Y′, where X′×Y′ represents the resolution of the received new video capture data;

[0136] ω represents a data string operator;

[0137] Video string′ 1～ε′ Indicates the data string from the 1st to ε′ bits in the video name; ε′ indicates the color depth;

[0138] Video string′ ε′+1～2ε′ Represents the data string from ε′+1 to 2ε′ in the video name;

[0139] Video string′ 2ε′+1～3ε′ Indicates the data string from the 2ε′+1th to the 3ε′th digit in the video name.

[0140] In a preferred embodiment of the present invention, step S47 is further included to determine whether the platform video data string is the same as the video name:

[0141] If the platform video data string is the same as the video name, the platform video data is the video shooting data captured by the camera;

[0142] If the platform video data string is different from the video name, the platform video data is not the video data shot by the camera. The calculation method of the platform video data string is:

[0143] Video string′ j′ =Video conversion method(Q″′ j′ ),

[0144] Among them, Videostring′ j′ represents the j′th platform image data string;

[0145] Video conversion method() indicates the video conversion algorithm; preferably, a digest algorithm is used; SHA-2 is the best;

[0146] Q″′ j′represents the j′th platform image; j′=1, 2, 3, ..., P′, P′ represents the number of images of the received new video shooting data;

[0147] picstring′=Videostring′1-Videostring″2-Videostring′3-…-Videostring′ P′

[0148] Among them, picstring′ represents the platform image stitching data string;

[0149] Video string′ j′ represents the j′th platform image data string; j′=1, 2, 3, ..., P′, P′ represents the number of images of the received new video shooting data;

[0150] - indicates the data string concatenation character;

[0151] Videostring′1 represents the first platform image data string;

[0152] Videostring′2 represents the second platform image data string;

[0153] Videostring′3 represents the third platform image data string;

[0154] Video string′ P′ represents the P′th platform image data string;

[0155] Videostring′=Video conversion method(picstring′),

[0156] Wherein, Videostring′ represents the platform video data string;

[0157] Video conversion method() indicates the video conversion algorithm; preferably, a digest algorithm is used; SHA-2 is the best;

[0158] picstring′ represents the platform image stitching data string.

[0159] The present invention also discloses a computer system, comprising:

[0160] processor;

[0161] a memory for storing processor-executable instructions;

[0162] Wherein, the processor is configured to implement the microcrystalline phosphor copper ball digital Internet of Things monitoring method when executing the executable instructions.

[0163] The present invention also discloses a computer-readable storage medium, comprising:

[0164] a memory having a computer program stored thereon;

[0165] A processor is used to execute the program in the memory to implement the microcrystalline phosphor copper ball digital Internet of Things monitoring method.

[0166] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A digital Internet of Things monitoring system for microcrystalline phosphor copper balls, comprising a camera installed in a plant for producing microcrystalline phosphor copper balls, and a microcrystalline phosphor copper ball monitoring platform, characterized in that: The video data captured by the camera is securely uploaded to the monitoring platform through the Internet of Things.

2. According to the microcrystalline phosphor copper ball digital Internet of Things monitoring system of claim 1, it is characterized in that: The video data captured by the camera is uploaded to the monitoring platform through the 10 Gigabit network port.

3. According to the microcrystalline phosphor copper ball digital Internet of Things monitoring system of claim 1, it is characterized in that: The camera is a wide-angle ultra-clear camera.

4. A digital Internet of Things monitoring method for microcrystalline phosphor copper balls, characterized in that: The following steps are involved: S1, obtaining video shooting data shot by a camera, and obtaining video parameters of the video shooting data according to the video shooting data; S2, generating new video shooting data according to the video shooting data and video parameters; S3, upload the new video data to the monitoring platform; S4, after the monitoring platform receives the new video shooting data, the video shooting data shot by the camera is obtained according to the new video shooting data received by the monitoring platform; S5, storing the video data captured by the camera in the monitoring platform for use in monitoring the video.

5. The digital Internet of Things monitoring method for microcrystalline phosphor copper balls according to claim 4 is characterized in that: The video parameters include one or any combination of frame rate, resolution and duration.

6. The digital Internet of Things monitoring method for microcrystalline phosphor copper balls according to claim 4 is characterized in that: The method for generating new video shooting data according to the video shooting data and the video parameters in step S2 comprises the following steps: S21, generating the number of images P according to the frame rate and duration; S22, converting the video shooting data into P images, and naming the P images in sequence as the first image, the second image, the third image, ..., the Pth image in a playback order; S23, converting the video shooting data into a video data string using a video conversion algorithm; S24, generating P new video images using the video data string and the P images; S25, generating new video shooting data from the P new video images in sequence, and using the video data string as the video name of the new video shooting data.

7. The digital Internet of Things monitoring method for microcrystalline phosphor copper balls according to claim 4 is characterized in that: The method for generating the number of images according to the frame rate and duration in step S21 is: P = fps × T, Among them, fps represents the frame rate of video shooting data; T represents the duration of the video shooting data; P represents the number of images of the video shooting data.

8. The digital Internet of Things monitoring method for microcrystalline phosphor copper balls according to claim 4 is characterized in that: In step S24, the method of generating P new video images using the video data string and P images is as follows: Among them, (Q j (x,y) R ,Q j (x,y) G ,Q j (x,y) B ) represents the color value of the jth image at the pixel point (x, y); (Q j ′(x,y) R ,Q j ′(x,y) G ,Q j ′(x,y) B ) represents the new color value of the j-th image at the pixel point (x, y); j=1, 2, 3, ..., P, where P represents the number of images of the video shooting data; x=1,2,3,...,X, y=1,2,3,...,Y, ω represents a data string operator; Videostring 1～ε Represents the data string from bit 1 to bit ε in the video data string; Videostring ε+1～2ε Represents the data string from ε+1 to 2ε in the video data string; Videostring 2ε+1～3ε Represents the data string from the 2ε+1th to the 3εth bits in the video data string.

9. A computer system, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to implement the microcrystalline phosphor copper ball digital Internet of Things monitoring method as described in any one of claims 4 to 8 when executing the executable instructions.

10. A computer-readable storage medium, characterized in that: include: a memory having a computer program stored thereon; A processor is used to execute the program in the memory to implement the microcrystalline phosphor copper ball digital Internet of Things monitoring method as described in any one of claims 4 to 8.

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