Safety detection system for electromechanical installation

Abstract

The invention relates to the technical field of electrical equipment detection, in particular to a safety detection system for electromechanical installation, which comprises a mechanical data acquisition module, an electrical data acquisition module, a comprehensive analysis module and an alarm display module, according to the invention, the detection precision and reliability of the electromechanical equipment are improved, feature extraction and data analysis are carried out by integrating laser detection, ultrasonic flaw detection, electrical data spectrum analysis and other technologies, and the safety, performance and reliability detection precision of the equipment in the electromechanical installation process is improved; the control standard of electromechanical installation quality detection is unified; according to the safety detection system provided by the invention, the non-uniformity of quality standards and the quality control difficulty caused by differentiated interpretation and execution of the standards by constructors are reduced through a standardized detection process and logic judgment; characteristic value quantification is carried out through real-time data acquisition and analysis, potential data are fully utilized, and the efficiency and effect of quality control are improved.

Description

Technical Field

[0001] The invention relates to the technical field of electrical equipment detection, in particular to a safety detection system for electromechanical installation. Background Art

[0002] Electrical equipment testing technology is a technology that monitors and tests the safety, performance and reliability of electrical equipment by adopting various scientific testing methods and techniques during the manufacturing, installation, operation and maintenance of electrical equipment.

[0003] At present, the quality control of electromechanical installation construction faces many challenges. With the continuous expansion of the scale of engineering projects and the increasing complexity of engineering projects, traditional quality control methods, such as manual inspection, are highly dependent on the operator's experience and subjective judgment, and it is difficult to ensure the uniformity and accuracy of the inspection results. In addition, the complex and changeable construction environment and unpredictable weather conditions pose a great challenge to the accuracy and stability of equipment installation.

[0004] In addition, the lack of uniformity in quality standards and the different interpretations and implementations of standards by construction personnel further increase the difficulty of quality control. Such differences may not only lead to uneven construction quality, but also cause safety hazards.

[0005] At the same time, although modern instrumentation technology provides new and more advanced monitoring methods for quality control, such as laser detection, ultrasonic monitoring and electrical data spectrum analysis, the integration and application of these technologies have not yet been widely popularized. This has resulted in a large amount of valuable potential data not being fully mined and utilized, thus affecting the efficiency and effectiveness of quality control.

[0006] In view of the above problems, it is necessary to propose a safety detection system for electromechanical installation. Summary of the invention

[0007] The purpose of the present invention is to solve the problems existing in the background technology and to provide a safety detection system for electromechanical installation.

[0008] The purpose of the present invention can be achieved through the following technical solutions:

[0009] A safety detection system for electromechanical installation comprises a mechanical data acquisition module, an electrical data acquisition module, a comprehensive analysis module and an alarm display module.

[0010] The mechanical data acquisition module detects electromechanical equipment through laser scanners and ultrasonic flaw detectors to obtain quantitative characteristic values ​​of tiny defects on the surface and inside of the electromechanical equipment shell.

[0011] Define the laser inspection process:

[0012] A laser scanner is used to emit pulsed light perpendicular to the surface of the outer shell of the electromechanical device, and the reflected pulsed light is obtained at the same time. The time difference Δt from the emission of the pulsed light to the reception of the reflected pulsed light is recorded, and the optical path distance d from the laser emitter to the surface of the electromechanical device is calculated by the formula d=(K×Δt+μ) / 2, where K is a preset influencing factor and μ is a preset error parameter. The laser scanner is moved along the preset detection path on the surface of the electromechanical device outer shell, and the optical path distance d is calculated in real time and the movement stroke S of the laser scanner along the preset detection path is synchronously recorded. A two-dimensional image of the optical path distance d changing with the movement stroke S is generated with the optical path distance d as the vertical axis and the movement stroke S as the vertical axis, i.e., an optical path distance-movement stroke diagram. The fitting function expression d=f(S) of the image is obtained.

[0013] Extract feature values ​​from the optical path distance-travel diagram, obtain discontinuity points in the image, record them as distance mutation points, and number each distance mutation point, the number symbol is i, i = 1, 2, 3, ..., n. Where n is the total number of distance mutation points. Obtain the horizontal coordinate Si and vertical coordinate di corresponding to each distance mutation point.

[0014] By formula The first eigenvalue C1 and the second eigenvalue C2 are calculated. Where f'(S) is the first-order derivative of the optical path distance-movement travel map fitting function f(S), and f"(S) is the second-order derivative of the optical path distance-movement travel map fitting function f(S).

[0015] After the electromechanical equipment is installed, data is acquired and calculated through a laser detection process to obtain a first eigenvalue C1 and a second eigenvalue C2.

[0016] Define the ultrasonic flaw detection process:

[0017] The transmitting probe of the ultrasonic flaw detector is perpendicular to the surface of the electromechanical equipment shell and parallel scanned, and ultrasonic waves are transmitted to the electromechanical equipment shell along the preset detection path on the surface of the electromechanical equipment. The amplitude A of the reflected ultrasonic wave is recorded by the receiving probe, and the movement stroke S of the transmitting probe along the preset detection path is synchronously recorded. With the amplitude A as the vertical axis and the movement stroke S as the horizontal axis, a two-dimensional image of the amplitude A changing with the movement stroke S is generated, i.e., the amplitude-movement stroke diagram. The fitting function expression A=g1(S) of the image is obtained.

[0018] As a preferred mode of the present invention, the actual working environment is simulated, and a preset temperature and a preset vibration load are applied to the installed electromechanical equipment, and the preset test time T is maintained. Subsequently, on this basis, data is captured and calculated again through the laser detection process and the ultrasonic flaw detection process to obtain the first characteristic value C1' after simulating the actual working environment, the second characteristic value C2' after simulating the actual working environment, and the fitting function expression A=g2(S) of the amplitude-movement stroke diagram obtained after simulating the actual working environment.

[0019] By formula Calculate the first detection parameter E2 and the second detection parameter E2, where K1 and K2 are preset weight factors. Send the first detection parameter E2 and the second detection parameter E2 to the comprehensive analysis module.

[0020] The electrical data acquisition module passes a preset input current through the installed electromechanical equipment and obtains the basic electrical data of the electromechanical equipment at preset time intervals t, including the operating voltage X1(t), operating current X2(t), grounding resistance X3(t) and power factor X4(t).

[0021] Every preset statistical period N×T, the basic electrical data obtained is statistically acquired and a data sequence of the basic electrical data over time is generated, including: an operating voltage data sequence: X1(t)=X1(1), X1(2), X1(3), ..., X1(N); an operating current data sequence: X2(t)=X2(1), X2(2), X2(3), ..., X2(N); a grounding resistance data sequence: X3(t)=X3(1), X3(2), X3(3), ..., X3(N) and a power factor data sequence X4(t)=X4(1), X4(2), X4(3), ..., X4(N), wherein N is the preset statistical period base, i.e., the number of basic electrical data contained in a data sequence.

[0022] As a preferred embodiment of the present invention, the operating voltage, operating current, grounding resistance and power factor are feature extracted by discrete Fourier transform, and each basic electrical data is decomposed from the time domain to the frequency domain. The discrete Fourier transform formula is:

[0023] Wherein ΩXp(η) is the decomposition value of the basic electrical data Xp at the frequency η, η is the frequency value and the upper limit is the preset statistical period base N, η=1, 2, 3, ..., N; Wherein Xp(t) is the data sequence of the basic electrical data, specifically Xp(t)=X1(t), X2(t), X3(t), X4(t), p=1, 2, 3, 4; Wherein Indicates the frequency A complex function of a combination of a sine wave and a cosine wave, where j is an imaginary unit and j×j=-1.

[0024] The decomposition values ​​of the data sequence of basic electrical data obtained after discrete Fourier transform operation at frequency η=1, 2, 3, ..., N are recorded, including the decomposition value of the working voltage at frequency η ΩX1(η)=ΩX1(1), ΩX1(2), ..., ΩX1(N); the decomposition value of the working current at frequency η ΩX2(η)=ΩX2(1), ΩX2(2), ..., ΩX2(N); the decomposition value of the grounding resistance at frequency η ΩX3(η)=ΩX3(1), ΩX3(2), ..., ΩX3(N) and the decomposition value of the power factor at frequency η ΩX4(η)=ΩX4(1), ΩX4(2), ..., ΩX4(N).

[0025] By formula Calculate the spectrum entropy of the decomposition values ​​of the working voltage, working current, grounding resistance and power factor at the frequency η, including the working voltage spectrum entropy HX1, the working current spectrum entropy HX2, the grounding resistance spectrum entropy HX3 and the power factor spectrum entropy HX4. Where PXp(η) is the frequency distribution probability.

[0026] The operating voltage spectrum entropy HX1, the operating current spectrum entropy HX2, the grounding resistance spectrum entropy HX3 and the power factor spectrum entropy HX4 are sent to the comprehensive analysis module.

[0027] The comprehensive analysis module receives the first detection parameter E1 and the second detection parameter E2 sent by the mechanical data acquisition module, and receives the working voltage spectrum entropy HX1, working current spectrum entropy HX2, grounding resistance spectrum entropy HX3 and power factor spectrum entropy HX4 sent by the electrical data module.

[0028] Then input E1, E2, HX1, HX2, HX3 and HX4 into the logic judgment process to carry out logical operations.

[0029] As a preferred embodiment of the present invention, the logic judgment process is as follows:

[0030] Set the value of the first judgment factor M1 to 0 and enter the first logical judgment

[0031] First logical judgment: judge whether the working voltage spectrum entropy HX1 is less than the preset judgment threshold HX1max. If yes, directly enter the second logical judgment; if not, generate a voltage abnormality signal and increase the value of the first judgment factor M1 by 1, and then enter the second logical judgment;

[0032] Second logical judgment: judge whether the working current spectrum entropy HX2 is less than the preset judgment threshold HX2max. If yes, directly enter the third logical judgment; if not, generate a current abnormality signal and increase the value of the first judgment factor M1 by 1, and then enter the third logical judgment;

[0033] The third logical judgment: judge whether the ground resistance spectrum entropy HX3 is less than the preset judgment threshold HX3max. If so, directly enter the fourth logical judgment; if not, generate a current abnormality signal and increase the value of the first judgment factor M1 by 1, and then enter the fourth logical judgment;

[0034] Fourth logical judgment: judge whether the power factor spectrum entropy HX34 is less than the preset judgment threshold HX4max. If so, set the value of the second judgment factor M2 equal to 1 and enter the fifth logical judgment; if not, generate a power factor abnormal signal and increase the value of the first judgment factor M1 by 1, then set the value of the second judgment factor M2 equal to 1 and enter the fifth logical judgment;

[0035] The fifth logical judgment: judge whether the product of the first detection parameter E1 and the second detection parameter E2 is less than the product of the judgment factor M and the preset judgment base δ1; if so, enter the sixth logical judgment; if not, increase the value of the judgment factor M by 1 and re-perform the fifth logical judgment until the judgment result is yes;

[0036] The sixth logical judgment: judge whether the condition is met: the value of the first judgment factor M1 is equal to 0 and the value of the second judgment factor M2 is less than the minimum threshold M2min; if so, output True and end the logical judgment; if not, enter the seventh logical judgment;

[0037] The seventh logical judgment: judge whether the conditions are met: the first judgment factor M1 is greater than 1 or the second judgment factor M2 is greater than the maximum threshold M2max; if so, generate a serious defect signal and output False; if not, generate a general defect signal, output False and end the logical judgment;

[0038] After the logical judgment is completed, the output result True or False and all generated signals are sent to the alarm display module.

[0039] The alarm display module displays an alarm based on the received output results and signals. If the output result is True, it is determined that there is no safety hazard in the electromechanical equipment; if the output result is False, it is determined that there is a safety hazard in the electromechanical equipment and all received signals are output through the display screen, including voltage abnormality signals, current abnormality signals, grounding protection abnormality signals, power factor abnormality signals, general defect signals or verification defect signals.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] (1) The present invention improves the detection accuracy and reliability of electromechanical equipment. By integrating laser detection, ultrasonic flaw detection and electrical data spectrum analysis technologies for feature extraction and data analysis, the accuracy of safety, performance and reliability detection of equipment during electromechanical installation is significantly improved, and the subjectivity and uncertainty of manual detection are reduced.

[0042] (2) The present invention unifies the control standards for electromechanical installation quality inspection; the proposed safety inspection system reduces the difficulty of quality control caused by the inconsistency of quality standards and the differentiated interpretation and implementation of standards by construction personnel through standardized inspection processes and logical judgments; the inspection results are automatically generated through logical judgment operations, which reduces the subjectivity of human judgment and ensures the consistency and accuracy of quality control;

[0043] (3) The present invention enhances data utilization and real-time performance, quantifies characteristic values ​​through real-time data collection and analysis, fully utilizes potential data, and improves the efficiency and effectiveness of quality control. The basic electrical data is decomposed from the time domain to the frequency domain through discrete Fourier transform, achieving more detailed monitoring of the equipment status. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to facilitate the understanding of those skilled in the art, the present invention is further described below with reference to the accompanying drawings:

[0045] Figure 1 is a system block diagram of the present invention;

[0046] Figure 2 The optical path distance-movement travel diagram of the present invention;

[0047] Figure 3 It is a logic judgment flow chart of the present invention. DETAILED DESCRIPTION

[0048] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] See also Figure 1 As shown, a safety detection system for electromechanical installation includes a mechanical data acquisition module, an electrical data acquisition module, a comprehensive analysis module and an alarm display module.

[0050] The mechanical data acquisition module detects electromechanical equipment through laser scanners and ultrasonic flaw detectors to obtain quantitative characteristic values ​​of tiny defects on the surface and inside of the electromechanical equipment shell.

[0051] Define the laser inspection process:

[0052] A laser scanner is used to emit pulsed light perpendicular to the surface of the outer shell of the electromechanical device, and the reflected pulsed light is obtained at the same time. The time difference Δt from the emission of the pulsed light to the reception of the reflected pulsed light is recorded, and the optical path distance d from the laser emitter to the surface of the electromechanical device is calculated by the formula d=(K×Δt+μ) / 2, where K is a preset influencing factor and μ is a preset error parameter. The laser scanner is moved along the preset detection path on the surface of the electromechanical device outer shell, and the optical path distance d is calculated in real time and the movement stroke S of the laser scanner along the preset detection path is synchronously recorded. A two-dimensional image of the optical path distance d changing with the movement stroke S is generated with the optical path distance d as the vertical axis and the movement stroke S as the vertical axis, i.e., an optical path distance-movement stroke diagram. The fitting function expression d=f(S) of the image is obtained.

[0053] See also Figure 2 As shown, feature value extraction is performed in the optical path distance-movement travel diagram to obtain discontinuity points in the image, which are recorded as distance mutation points, and each distance mutation point is numbered, and the number symbol is i, i = 1, 2, 3, ..., n. Where n is the total number of distance mutation points. The horizontal coordinate Si and the vertical coordinate di corresponding to each distance mutation point are obtained.

[0054] By formula The first eigenvalue C1 and the second eigenvalue C2 are calculated. Where f'(S) is the first-order derivative of the optical path distance-movement travel map fitting function f(S), and f"(S) is the second-order derivative of the optical path distance-movement travel map fitting function f(S).

[0055] After the electromechanical equipment is installed, data is acquired and calculated through a laser detection process to obtain a first eigenvalue C1 and a second eigenvalue C2.

[0056] Define the ultrasonic flaw detection process:

[0057] The transmitting probe of the ultrasonic flaw detector is perpendicular to the surface of the electromechanical equipment shell and parallel scanned, and ultrasonic waves are transmitted to the electromechanical equipment shell along the preset detection path on the surface of the electromechanical equipment. The amplitude A of the reflected ultrasonic wave is recorded by the receiving probe, and the movement stroke S of the transmitting probe along the preset detection path is synchronously recorded. With the amplitude A as the vertical axis and the movement stroke S as the horizontal axis, a two-dimensional image of the amplitude A changing with the movement stroke S is generated, i.e., the amplitude-movement stroke diagram. The fitting function expression A=g1(S) of the image is obtained.

[0058] Furthermore, the actual working environment is simulated, and a preset temperature and a preset vibration load are applied to the installed electromechanical equipment, and the preset test time T is maintained. Subsequently, on this basis, data is captured and calculated again through the laser detection process and the ultrasonic flaw detection process, and the first eigenvalue C1' after simulating the actual working environment, the second eigenvalue C2' after simulating the actual working environment, and the fitting function expression A=g2(S) of the amplitude-movement stroke diagram obtained after simulating the actual working environment are obtained.

[0059] It should be noted that the first eigenvalue reflects the flatness of the continuous plane on the surface of the electromechanical equipment shell and the overall displacement of the electromechanical equipment, and the second eigenvalue reflects the number of cracks on the surface of the electromechanical equipment shell. The fitting function expression A=g(S) of the amplitude-movement travel diagram reflects the number, shape and distribution of cracks inside the electromechanical equipment. Under ideal conditions, the shell of the electromechanical equipment meets the requirements of the use conditions in terms of materials, structure and process, and can effectively disperse and resist the vibration stress and temperature stress from the inside, without obvious deformation and cracks. Moreover, under the condition that the electromechanical equipment has a solid foundation and meets the use requirements, the electromechanical equipment will not produce obvious displacement with vibration. Reflected in the specific values, before and after simulating the actual working environment, the specific data of the first eigenvalue and the second eigenvalue will not change significantly; at the same time, the fitting function expression A=g2(S) of the amplitude-movement travel diagram will not change significantly.

[0060] By formula Calculate the first detection parameter E2 and the second detection parameter E2, where K1 and K2 are preset weight factors. Send the first detection parameter E2 and the second detection parameter E2 to the comprehensive analysis module.

[0061] The electrical data acquisition module passes a preset input current through the installed electromechanical equipment and obtains the basic electrical data of the electromechanical equipment at preset time intervals t, including the operating voltage X1(t), operating current X2(t), grounding resistance X3(t) and power factor X4(t).

[0062] Every preset statistical period N×T, the basic electrical data obtained is statistically acquired and a data sequence of the basic electrical data over time is generated, including: an operating voltage data sequence: X1(t)=X1(1), X1(2), X1(3), ..., X1(N); an operating current data sequence: X2(t)=X2(1), X2(2), X2(3), ..., X2(N); a grounding resistance data sequence: X3(t)=X3(1), X3(2), X3(3), ..., X3(N) and a power factor data sequence X4(t)=X4(1), X4(2), X4(3), ..., X4(N), wherein N is the preset statistical period base, i.e., the number of basic electrical data contained in a data sequence.

[0063] The operating voltage, operating current, grounding resistance and power factor are extracted by discrete Fourier transform, and each basic electrical data is decomposed from the time domain to the frequency domain. The discrete Fourier transform formula is:

[0064] Wherein ΩXp(η) is the decomposition value of the basic electrical data Xp at the frequency η, η is the frequency value and the upper limit is the preset statistical period base N, η=1, 2, 3, ..., N; Wherein Xp(t) is the data sequence of the basic electrical data, specifically Xp(t)=X1(t), X2(t), X3(t), X4(t), p=1, 2, 3, 4; Wherein Indicates the frequency A complex function of a combination of a sine wave and a cosine wave, where j is an imaginary unit and j×j=-1.

[0065] The decomposition values ​​of the data sequence of basic electrical data obtained after discrete Fourier transform operation at frequency η=1, 2, 3, ..., N are recorded, including the decomposition value of the working voltage at frequency η ΩX1(η)=ΩX1(1), ΩX1(2), ..., ΩX1(N); the decomposition value of the working current at frequency η ΩX2(η)=ΩX2(1), ΩX2(2), ..., ΩX2(N); the decomposition value of the grounding resistance at frequency η ΩX3(η)=ΩX3(1), ΩX3(2), ..., ΩX3(N) and the decomposition value of the power factor at frequency η ΩX4(η)=ΩX4(1), ΩX4(2), ..., ΩX4(N).

[0066] By formula Calculate the spectrum entropy of the decomposition values ​​of the working voltage, working current, grounding resistance and power factor at the frequency η, including the working voltage spectrum entropy HX1, the working current spectrum entropy HX2, the grounding resistance spectrum entropy HX3 and the power factor spectrum entropy HX4. Where PXp(η) is the frequency distribution probability.

[0067] The operating voltage spectrum entropy HX1, the operating current spectrum entropy HX2, the grounding resistance spectrum entropy HX3 and the power factor spectrum entropy HX4 are sent to the comprehensive analysis module.

[0068] The comprehensive analysis module receives the first detection parameter E1 and the second detection parameter E2 sent by the mechanical data acquisition module, and receives the working voltage spectrum entropy HX1, working current spectrum entropy HX2, grounding resistance spectrum entropy HX3 and power factor spectrum entropy HX4 sent by the electrical data module.

[0069] Then input E1, E2, HX1, HX2, HX3 and HX4 into the logic judgment process to carry out logical operations.

[0070] See also Figure 3 As shown, the logical judgment process is as follows:

[0071] Set the value of the first judgment factor M1 to 0 and enter the first logical judgment

[0072] First logical judgment: judge whether the working voltage spectrum entropy HX1 is less than the preset judgment threshold HX1max. If yes, directly enter the second logical judgment; if not, generate a voltage abnormality signal and increase the value of the first judgment factor M1 by 1, and then enter the second logical judgment;

[0073] Second logical judgment: judge whether the working current spectrum entropy HX2 is less than the preset judgment threshold HX2max. If yes, directly enter the third logical judgment; if not, generate a current abnormality signal and increase the value of the first judgment factor M1 by 1, and then enter the third logical judgment;

[0074] The third logical judgment: judge whether the ground resistance spectrum entropy HX3 is less than the preset judgment threshold HX3max. If so, directly enter the fourth logical judgment; if not, generate a current abnormality signal and increase the value of the first judgment factor M1 by 1, and then enter the fourth logical judgment;

[0075] Fourth logical judgment: judge whether the power factor spectrum entropy HX34 is less than the preset judgment threshold HX4max. If so, set the value of the second judgment factor M2 equal to 1 and enter the fifth logical judgment; if not, generate a power factor abnormal signal and increase the value of the first judgment factor M1 by 1, then set the value of the second judgment factor M2 equal to 1 and enter the fifth logical judgment;

[0076] The fifth logical judgment: judge whether the product of the first detection parameter E1 and the second detection parameter E2 is less than the product of the judgment factor M and the preset judgment base δ1; if so, enter the sixth logical judgment; if not, increase the value of the judgment factor M by 1 and re-perform the fifth logical judgment until the judgment result is yes;

[0077] The sixth logical judgment: judge whether the condition is met: the value of the first judgment factor M1 is equal to 0 and the value of the second judgment factor M2 is less than the minimum threshold M2min; if so, output True and end the logical judgment; if not, enter the seventh logical judgment;

[0078] The seventh logical judgment: judge whether the conditions are met: the first judgment factor M1 is greater than 1 or the second judgment factor M2 is greater than the maximum threshold M2max; if so, generate a serious defect signal and output False; if not, generate a general defect signal, output False and end the logical judgment;

[0079] After the logical judgment is completed, the output result True or False and all generated signals are sent to the alarm display module.

[0080] The alarm display module displays an alarm based on the received output results and signals. If the output result is True, it is determined that there is no safety hazard in the electromechanical equipment; if the output result is False, it is determined that there is a safety hazard in the electromechanical equipment and all received signals are output through the display screen, including voltage abnormality signals, current abnormality signals, grounding protection abnormality signals, power factor abnormality signals, general defect signals or verification defect signals.

[0081] It should be understood that the terms "include" and "comprising" used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0082] It should also be understood that the terms used in this disclosure are only for the purpose of describing specific embodiments and are not intended to limit the disclosure. As used in this disclosure and the claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in this disclosure and the claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations;

[0083] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A safety detection system for electromechanical installation, comprising an electrical data acquisition module, a mechanical data acquisition module and a comprehensive analysis module, characterized in that: The mechanical data acquisition module detects the electromechanical equipment through a laser scanner and an ultrasonic flaw detector to obtain quantitative characteristic values ​​of tiny defects on the surface and inside of the electromechanical equipment shell; after the electromechanical equipment is installed, the laser detection process is used to obtain and calculate data to obtain a first characteristic value C1 and a second characteristic value C2; ​​after the electromechanical equipment is installed, the ultrasonic flaw detection process is used to obtain and calculate data to obtain an amplitude-movement stroke diagram and a fitting function expression A=g1(S) of the image; simulate the actual working environment, apply a preset temperature and a preset vibration load to the installed electromechanical equipment, and maintain a preset test time T; then, on this basis, the laser detection process and the ultrasonic flaw detection process are used again to capture and calculate data to obtain a first characteristic value C1' after simulating the actual working environment, a second characteristic value C2' after simulating the actual working environment, and a fitting function expression A=g2(S) of the amplitude-movement stroke diagram obtained after simulating the actual working environment; by performing comprehensive operations on the data generated before and after simulating the actual working environment, the first detection parameter E2 and the second detection parameter E2 are obtained; The electrical data acquisition module applies a preset input current to the installed electromechanical equipment, and obtains the basic electrical data of the electromechanical equipment at preset time intervals t, including the working voltage X1(t), working current X2(t), grounding resistance X3(t) and power factor X4(t). The spectrum entropy of the working voltage HX1, the spectrum entropy of the working current HX2, the spectrum entropy of the grounding resistance HX3 and the spectrum entropy of the power factor HX4 are obtained through data sequence generation and spectrum analysis operations. The comprehensive analysis module generates a detection signal and a detection result by analyzing the logical operation process of the first detection parameter E2, the second detection parameter E3, the working voltage spectrum entropy HX1, the working current spectrum entropy HX2, the grounding resistance spectrum entropy HX3 and the power factor spectrum entropy HX4.

2. A safety detection system for electromechanical installation according to claim 1, characterized in that: It also includes an alarm display module; The alarm display module displays an alarm based on the received output results and signals. If the output result is True, it is determined that there is no safety hazard in the electromechanical equipment; if the output result is False, it is determined that there is a safety hazard in the electromechanical equipment and all received signals are output through the display screen, including voltage abnormality signals, current abnormality signals, grounding protection abnormality signals, power factor abnormality signals, general defect signals or verification defect signals.

3. A safety detection system for electromechanical installation according to claim 1, characterized in that: The laser detection process is as follows: The laser scanner is used to emit pulse light perpendicular to the surface of the shell of the electromechanical device, and the reflected pulse light is obtained at the same time; the time difference Δt from the emission of the pulse light to the reception of the reflected pulse light is recorded, and the optical path distance d from the laser emitter to the surface of the electromechanical device is calculated by the formula d=(K×Δt+μ) / 2, wherein K is a preset influencing factor and μ is a preset error parameter; the laser scanner is moved along a preset detection path on the surface of the electromechanical device shell, the optical path distance d is calculated in real time, and the moving stroke S of the laser scanner along the preset detection path is synchronously recorded; a two-dimensional image of the optical path distance d changing with the moving stroke S is generated with the optical path distance d as the vertical axis and the moving stroke S as the vertical axis, i.e., an optical path distance-moving stroke diagram; and a fitting function expression d=f(S) of the image is obtained; Extract feature values ​​from the optical path distance-movement travel diagram, obtain discontinuity points in the image, record them as distance mutation points, and number each distance mutation point, the number symbol is i, i = 1, 2, 3, ..., n; where n is the total number of distance mutation points; obtain the horizontal coordinate Si and the vertical coordinate di corresponding to each distance mutation point; By formula Calculate the first eigenvalue C1 and the second eigenvalue C2; ​​wherein f'(S) is the first-order derivative of the optical path distance-movement travel diagram fitting function f(S), and f"(S) is the second-order derivative of the optical path distance-movement travel diagram fitting function f(S).

4. A safety detection system for electromechanical installation according to claim 1, characterized in that: The specific process of ultrasonic flaw detection is as follows: The transmitting probe of the ultrasonic flaw detector is placed perpendicularly to the surface of the electromechanical equipment housing for parallel scanning, and ultrasonic waves are transmitted to the electromechanical equipment housing along the preset detection path on the surface of the electromechanical equipment; the amplitude A of the reflected ultrasonic wave is recorded by the receiving probe, and the moving stroke S of the transmitting probe along the preset detection path is simultaneously recorded; A two-dimensional image of amplitude A changing with movement stroke S, ie, amplitude-movement stroke diagram, is generated with amplitude A as the vertical axis and movement stroke S as the horizontal axis; and a fitting function expression A=g1(S) of the image is obtained.

5. A safety detection system for electromechanical installation according to claim 1, characterized in that: The specific process of comprehensive calculation of the data generated before and after simulating the actual working environment is as follows: By formula Calculate the first detection parameter E2 and the second detection parameter E2, wherein K1 and K2 are preset weight factors; send the first detection parameter E2 and the second detection parameter E2 to the comprehensive analysis module.

6. A safety detection system for electromechanical installation according to claim 1, characterized in that: The specific process of data sequence generation is as follows: Every preset statistical period N×T, the basic electrical data obtained is statistically acquired and a data sequence of the basic electrical data over time is generated, including: an operating voltage data sequence: X1(t)=X1(1), X1(2), X1(3), ..., X1(N); an operating current data sequence: X2(t)=X2(1), X2(2), X2(3), ..., X2(N); a grounding resistance data sequence: X3(t)=X3(1), X3(2), X3(3), ..., X3(N) and a power factor data sequence X4(t)=X4(1), X4(2), X4(3), ..., X4(N), wherein N is the preset statistical period base, i.e., the number of basic electrical data contained in a data sequence.

7. A safety detection system for electromechanical installation according to claim 1, characterized in that: The specific process of spectrum analysis operation is as follows: The operating voltage, operating current, grounding resistance and power factor are extracted by discrete Fourier transform, and each basic electrical data is decomposed from the time domain to the frequency domain. The discrete Fourier transform formula is: Wherein ΩXp(η) is the decomposition value of the basic electrical data Xp at the frequency η, η is the frequency value and the upper limit is the preset statistical period base N, η=1, 2, 3, ..., N; Wherein Xp(t) is the data sequence of the basic electrical data, specifically Xp(t)=X1(t), X2(t), X3(t), X4(t), p=1, 2, 3, 4; Wherein Indicates the frequency A complex function of a sine wave and a cosine wave, where j is an imaginary unit and j×j=-1; Record the decomposition values ​​of the data sequence of basic electrical data obtained after discrete Fourier transform operation at frequency η = 1, 2, 3, ..., N, including the decomposition value of the working voltage at frequency η ΩX1(η) = ΩX1(1), ΩX1(2), ..., ΩX1(N); the decomposition value of the working current at frequency η ΩX2(η) = ΩX2(1), ΩX2(2), ..., ΩX2(N); the decomposition value of the grounding resistance at frequency η ΩX3(η) = ΩX3(1), ΩX3(2), ..., ΩX3(N) and the decomposition value of the power factor at frequency η ΩX4(η) = ΩX4(1), ΩX4(2), ..., ΩX4(N); through the formula Calculate the spectrum entropy of the decomposition values ​​of the working voltage, working current, grounding resistance and power factor at the frequency η, including the working voltage spectrum entropy HX1, the working current spectrum entropy HX2, the grounding resistance spectrum entropy HX3 and the power factor spectrum entropy HX4; where PXp(η) is the frequency distribution probability.

8. A safety detection system for electromechanical installation according to claim 1, characterized in that: The specific process of logical operation flow analysis is as follows: Set the value of the first judgment factor M1 to 0 and enter the first logical judgment; First logic judgment: judge whether the working voltage spectrum entropy HX1 is less than the preset judgment threshold HX1max; if so, directly enter the second logic judgment; if not, generate a voltage abnormality signal and increase the value of the first judgment factor M1 by 1, and then enter the second logic judgment; Second logic judgment: judge whether the working current spectrum entropy HX2 is less than the preset judgment threshold HX2max; if so, directly enter the third logic judgment; if not, generate a current abnormality signal and increase the value of the first judgment factor M1 by 1, and then enter the third logic judgment; The third logic judgment: judge whether the ground resistance spectrum entropy HX3 is less than the preset judgment threshold HX3max; if so, directly enter the fourth logic judgment; if not, generate a current abnormality signal and increase the value of the first judgment factor M1 by 1, and then enter the fourth logic judgment; Fourth logical judgment: judge whether the power factor spectrum entropy HX34 is less than the preset judgment threshold HX4max; if so, set the value of the second judgment factor M2 equal to 1 and enter the fifth logical judgment; if not, generate a power factor abnormal signal and increase the value of the first judgment factor M1 by 1, then set the value of the second judgment factor M2 equal to 1 and enter the fifth logical judgment; The fifth logical judgment: judging whether the product of the first detection parameter E1 and the second detection parameter E2 is less than the product of the judgment factor M and the preset judgment base δ1; If yes, proceed to the sixth logical judgment; if no, increase the value of the judgment factor M by 1 and repeat the fifth logical judgment until the judgment result is yes; The sixth logical judgment: judging whether the condition is met: the value of the first judgment factor M1 is equal to 0 and the value of the second judgment factor M2 is less than the minimum threshold M2min; If yes, output True and end the logic judgment; if no, enter the seventh logic judgment; The seventh logical judgment: judge whether the conditions are met: the first judgment factor M1 is greater than 1 or the second judgment factor M2 is greater than the maximum threshold M2max; if so, generate a serious defect signal and output False; if not; Generate a general defect signal, output False and end the logic judgment; After the logical judgment is completed, the output result True or False and all generated signals are sent to the alarm display module.

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