Well logging instrument intelligent detection system

Abstract

The invention belongs to the technical field of automatic detection, and particularly relates to an intelligent detection system for a logging instrument. Comprising a test box body and an upper computer, and the test box body is used for being connected with a tested instrument and connected to the upper computer through a bus interface; the upper computer is used for installing intelligent instrument detection software; the intelligent instrument detection software comprises a data input module; a truth table generation module; a logic relation processing module; an expert diagnosis processing knowledge base is arranged in the fault matching module; and a fault diagnosis module. The invention provides an intelligent detection system for a logging instrument, and aims to solve the problems that an existing detection method for the logging instrument cannot achieve fault detection process standardization, software solidification and record informatization and cannot achieve rapid positioning and diagnosis of instrument faults.

Description

Technical Field

[0001] The present invention belongs to the technical field of automated detection, and in particular relates to an intelligent detection system for well logging instruments. Background Art

[0002] At present, the traditional single-board detection and downhole logging instrument digital detection methods are used for logging instrument maintenance. The principle of these two instrument fault detection methods is to send the signal collected by the logging instrument to the host computer, and judge whether the observation point signal is abnormal based on the collected signal. Then the instrument maintenance personnel manually find the instrument fault point based on the abnormal signal.

[0003] The traditional single-board detection method requires the connection of a signal generator, power supply, and oscilloscope to measure the waveform and other characteristic parameters of the observation point. The on-site instrument maintenance personnel determine the approximate fault area based on the measured signal, and then manually troubleshoot the fault point. This requires the on-site instrument maintenance personnel to have rich professional knowledge and on-site maintenance experience. The digital detection of downhole logging instruments in China is mainly based on portable test benches, and a telemetry short section needs to be connected during detection. Another method generally uses a notebook, a bus conversion box, and a power supply to form a simple detection device, and determines the fault area of ​​the instrument based on the signal uploaded by the instrument. The above-mentioned domestic and foreign fault detection methods remain at the general detection level test, which can only find problems. Maintenance or debugging activities are carried out by experienced operators under the guidance of maintenance manuals or operating instructions, and no intelligent maintenance or debugging solutions are provided.

[0004] The patent number is CN200710099358.4, and the name is "Test unit of well logging instrument maintenance test system", which discloses a test unit of well logging instrument maintenance test system. The test unit only realizes the signal collection and processing of the well logging instrument, and does not have the function of locating the instrument circuit fault point.

[0005] The patent number is CN201110218401.0, and its name is "A petroleum instrument fault diagnosis device and diagnosis method". It discloses a portable fault diagnosis instrument method, but this method requires the design of oscilloscope card interfaces, multimeter card interfaces and digital signal acquisition card interfaces for different instruments. The amount of interactive information is large. At the same time, it is unrealistic to add so many interfaces when testing actual downhole logging instruments, and there are too many factors of human intervention.

[0006] The patent number is CN201710545385.3, and its name is "A method, device and electronic device for online fault diagnosis". Its fault detection adopts a fault tree model, which simply divides the causes of the fault into a single-node hierarchical progressive relationship. However, instrument faults belong to multiple nodes, and one fault contains one or more processing elements, so this diagnostic method cannot comprehensively and accurately locate the fault.

[0007] In view of the problem that the above instrument detection method cannot achieve standardization of fault detection process, software solidification, and record informatization, and cannot achieve rapid location and diagnosis of instrument faults, the present invention proposes a smart detection system for well logging instruments. Summary of the invention

[0008] The purpose of the present invention is to provide an intelligent detection system for well logging instruments, which can achieve standardization of fault detection process, software solidification, and record informatization, better meet the needs of on-site instrument repair and debugging process, realize rapid positioning and diagnosis of instrument faults, and improve maintenance efficiency and quality.

[0009] A well logging instrument intelligent detection system includes a test box and a host computer, wherein the test box is used to be connected to the instrument under test and connected to the host computer through a bus interface; the host computer is used to install intelligent instrument detection software;

[0010] The intelligent instrument detection software includes an expert diagnosis knowledge base for storing fault model data and corresponding processing methods; a data input module for receiving status words collected by a test box; a truth table generation module for binarizing the collected status words, arranging the binarized status words into a truth table, and sending the truth table to a logic relationship processing module; a logic relationship processing module for receiving the truth table sent by the truth table generation module, performing logical "and" and logical "or" logic relationship operations on the binarized status words in the truth table to obtain a fault mask; a fault matching module for matching the fault mask with the fault model code in the expert diagnosis processing knowledge base to obtain a matching result; and a fault diagnosis module for outputting the corresponding processing method in the expert diagnosis processing knowledge base as a diagnosis result according to the obtained matching result.

[0011] Optionally, the binarization processing step is: compare the collected status word with the status word nominal value, if it is within the specified error range, process the status word as logic "1", otherwise, process it as logic "0".

[0012] Optionally, the smart instrument detection software also includes a voice assistant prompt module, which is used to voice guide the user to complete circuit board level fault location and / or instrument troubleshooting based on the diagnosis results.

[0013] Optionally, the method of arranging the binary status words into a truth table is:

[0014] S1. Group the binary status words according to the structure or function of the instrument under test;

[0015] S2. Arrange all the groups according to the first set order to form a truth table.

[0016] Optionally, the truth table generation module performs logical "AND" and logical "OR" operations on the binary state words in the truth table to obtain the fault mask method steps as follows:

[0017] S11, the logic relationship processing module lists all possible fault information of the instrument under test (3) in sequence according to the second set order;

[0018] S12, according to the possible fault information, selecting a group related to the possible fault information in the truth table;

[0019] S13, selecting a binary status word related to possible fault information from the selected group;

[0020] S14. If there are multiple binary status words selected in the selected group, a logical relationship operation is performed on the binary status words selected in the selected group according to the corresponding logical "and" and logical "or" logical relationships stored in the expert diagnosis processing knowledge base to obtain an output result of the selected group. If there is only one binary status word selected in the selected group, the binary status word is used as the output result of the selected group. The output results of the selected groups are arranged in a first set order to obtain a combination code corresponding to the fault information.

[0021] S15. Repeat steps S12-S14 to obtain a combination code corresponding to each piece of fault information, and arrange the combination code corresponding to each piece of fault information in a second set order to obtain a fault mask.

[0022] Optionally, the system includes three modes:

[0023] Smart board detection mode, used to detect circuit board faults;

[0024] Single board positioning one-button detection mode, used to detect instrument single board faults with one button;

[0025] Instrument fault detection mode, used for complex fault detection of instrument circuits.

[0026] Optionally, the expert diagnosis processing knowledge base includes a binary status word group, a logical relationship group, and a diagnostic conclusion group, wherein the binary status word group stores the fault model code for corresponding matching with the fault mask, the logical relationship group stores the logical relationship of the status word logical "AND" and logical "OR", and the diagnostic conclusion group stores the diagnostic results corresponding to the fault code.

[0027] Optionally, the logic relationship processing module constructs logical "and" and logical "or" logical relationships between different status words according to the correlation between different status words and circuit boards or instrument parts, and stores the constructed logical relationships in a logic relationship group in the expert knowledge base.

[0028] Optionally, the test box includes:

[0029] Power module, used to provide stable power supply for the instrument under test and the host computer;

[0030] A signal acquisition module is used to collect the signal of the instrument under test and convert it into a digital signal;

[0031] The bus interface module is used to transmit the digital signal collected by the signal acquisition module to the host computer;

[0032] The instrument interface module is used to connect the instrument under test and the test box.

[0033] Optionally, the host computer also includes,

[0034] A data display unit, used to display the diagnostic results of the smart instrument detection software on the screen in the form of graphics or text;

[0035] The data storage unit is used to store the diagnosis results and related data of the smart instrument detection software in the memory or external storage device.

[0036] The beneficial effects of the present invention are as follows:

[0037] 1. The present invention adopts intelligent instrument detection software, which realizes the rapid location and diagnosis of instrument faults by performing binary processing, logical relationship processing, fault matching and fault diagnosis on status words, thereby improving maintenance efficiency and quality.

[0038] 2. The present invention adopts a test box, which is connected to the instrument under test and to the host computer through a bus interface, thereby realizing the collection and transmission of instrument signals and simplifying the structure and operation of the detection device.

[0039] 3. The present invention adopts a voice assistant prompt module, which improves user convenience and friendliness by guiding users to complete circuit board level fault location and instrument fault troubleshooting according to the diagnosis results.

[0040] 4. The present invention adopts a data display unit and a data storage unit, which realizes the visualization and informatization of the detection data by displaying the diagnostic results of the smart instrument detection software on the screen in the form of graphics or text, and storing the diagnostic results and related data in the memory or external storage device.

[0041] 5. The present invention adopts three modes, namely, intelligent single board detection mode, single board positioning one-key detection mode and instrument fault detection mode, achieving adaptability and flexibility to different types of instrument faults.

[0042] In summary, the present invention has the advantages of fault detection process standardization, software solidification, and record informatization, which is more in line with the requirements of on-site instrument repair and debugging process flow, and achieves the beneficial effect of rapid positioning and diagnosis of instrument faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The drawings constituting a part of the present application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0044] Figure 1 It is a structural schematic diagram of an embodiment of an intelligent detection system for well logging instruments of the present invention.

[0045] Figure 2 It is a schematic diagram of the back structure of an embodiment of an intelligent detection system for well logging instruments of the present invention.

[0046] Figure 3 A schematic diagram of the intelligent instrument detection software structure of an embodiment of an intelligent detection system for well logging instruments of the present invention.

[0047] Figure 4 A flowchart of a method embodiment of an intelligent detection system for well logging instruments according to the present invention.

[0048] Figure 5 This is a flow chart of an embodiment of an intelligent single board detection method for an intelligent detection system of a well logging instrument of the present invention.

[0049] Figure 6 This is a flow chart of an embodiment of a single-board positioning one-key detection method for a well logging instrument intelligent detection system of the present invention.

[0050] Figure 7 This is a flow chart of an embodiment of an instrument fault detection method of an intelligent detection system for a well logging instrument of the present invention.

[0051] Among them: 1-host computer, 2-test box, 3-instrument under test, 4-bus interface. DETAILED DESCRIPTION

[0052] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0053] The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise specified, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art to which the present application belongs. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention.

[0054] like Figure 1-Figure 3 As shown, a well logging instrument intelligent detection system includes:

[0055] A well logging instrument intelligent detection system comprises a test box 2 and a host computer 1, wherein the test box is used to be connected to a tested instrument 3 and is connected to the host computer 1 through a bus interface 4;

[0056] Host computer 1, used to install the smart instrument detection software;

[0057] The intelligent instrument detection software includes an expert diagnosis knowledge base for storing fault model data and corresponding processing methods; a data input module for receiving the status words collected by the test box 2; a truth table generation module for binarizing the collected status words, arranging the binarized status words into a truth table, and sending the truth table to a logic relationship processing module; a logic relationship processing module for receiving the truth table sent by the truth table generation module, performing logical "and" and logical "or" logic relationship operations on the binarized status words in the truth table to obtain a fault mask; a fault matching module for matching the fault mask with the fault model code in the expert diagnosis processing knowledge base to obtain a matching result; and a fault diagnosis module for outputting the corresponding processing method in the expert diagnosis processing knowledge base as a diagnosis result according to the obtained matching result.

[0058] Specifically, the data input module can be connected to the instrument under test 3 through the test box 2, and transmit the status word of the instrument under test 3 to the host computer 1 through the bus interface 4 or other interfaces.

[0059] As a specific example, the test box 2 includes: a power supply module, used to provide stable power supply for the instrument under test 3 and the host computer 1; a signal acquisition module, used to collect signals from the instrument under test 3 and convert them into digital signals; a bus interface 4 module, used to transmit the digital signals collected by the signal acquisition module to the host computer 1; an instrument interface module, used to connect the instrument under test 3 and the test box 2.

[0060] As a specific example, the binarization processing step is: compare the collected status word with the status word nominal value. If it is within the specified error range, the status word is processed as a logic "1", otherwise, it is processed as a logic "0". The status word nominal value refers to the status word value that the instrument under test 3 should have when it is working normally, such as power supply voltage, current, frequency, etc. The specified error range refers to the deviation range between the status word value and the nominal value allowed for the instrument under test 3 to exist when it is working normally, such as ±5%. The truth table generation module performs binarization processing on the collected status word, arranges the binarized status word into a truth table, arranges it according to the various functions and circuit principles of the instrument under test 3, stores the truth table in the memory or external storage device, that is, in the data storage unit, and sends the truth table to the logic relationship processing module.

[0061] As a specific example, the method of arranging the binary state words into a truth table is as follows:

[0062] S1. Group the binary status words according to the structure or function of the device under test 3.

[0063] S2. Arrange all the groups according to the first set order to form a truth table.

[0064] Specifically, the first set order of the groups may be based on the division of the boards, or may be the order initially set by the system, for example, the order may be from small to large according to the number of group status words.

[0065] As a specific example, the logic relationship processing module performs logic "AND" and logic "OR" logic relationship operations on the binary state words in the truth table to obtain the fault mask method steps as follows:

[0066] S11, the logic relationship processing module lists all possible fault information of the instrument under test (3) in sequence according to the second set order;

[0067] S12, according to the possible fault information, selecting a group related to the possible fault information in the truth table;

[0068] S13, selecting a binary status word related to possible fault information from the selected group;

[0069] S14. If there are multiple binary status words selected in the selected group, a logical relationship operation is performed on the binary status words selected in the selected group according to the corresponding logical "and" and logical "or" logical relationships stored in the expert diagnosis and processing knowledge base to obtain an output result of the selected group. If there is only one binary status word selected in the selected group, the binary status word is used as the output result of the selected group. The output results of the selected groups are arranged in a first set order to obtain a combination code corresponding to the fault information.

[0070] S15. Repeat steps S12-S14 to obtain a combination code corresponding to each piece of fault information, and arrange the combination code corresponding to each piece of fault information in a second set order to obtain a fault mask.

[0071] The second setting sequence may be the sequence of initial setting of the system, for example, it may be sorted from small to large probability of failure, and the possible failure information may be a board or function that may fail.

[0072] The output results of the selected groups are arranged in a first set order, which may be arranged in a horizontal direction, and the fault mask may be formed by arranging the combination codes in a vertical direction according to a second set order.

[0073] For the unselected groups that are not related to the fault information in S14, the output result of the selected groups may be empty.

[0074] As a specific example, the logic relationship processing module constructs the logical relationship of logic "AND" and logic "OR" between different state words according to the correlation between different state words and circuit boards or instrument parts, stores the constructed logical relationship in the logic relationship group in the expert knowledge base, and performs the corresponding logical relationship operation of logic "AND" and logic "OR" on the binary state words to obtain the fault mask; the logical relationship may refer to the necessary or sufficient condition relationship between different state words determined according to the fault diagnosis rules and experience in the expert diagnosis processing knowledge base, and the logic relationship processing module extracts the corresponding logical relationship stored in the logic relationship group according to the correlation between different state words and circuit boards or instrument parts, such as A and B, A or B, etc. The fault mask refers to the code representing the fault feature composed of the binary state words and the logical relationship, such as 0101, 1100, etc. The logic relationship processing module can perform the logical relationship operation on the binary state words in the truth table, and store the fault mask obtained after the operation in the memory or external storage device, that is, in the data storage unit, and send the obtained fault mask to the fault matching module.

[0075] As a specific example, the diagnosis result includes a diagnosis diagram, a diagnosis suggestion, a fault cause, a diagnosis report, a fault location information, processing steps and a processing method.

[0076] Diagnostic diagram refers to prompt information displayed on the data display unit in the form of graphics or text based on the cause and solution of the fault in the expert diagnosis processing knowledge base, such as circuit diagram, waveform diagram, flow chart, etc. Diagnostic suggestion refers to the maintenance or debugging plan given in the form of text or voice based on the cause and solution of the fault in the expert diagnosis processing knowledge base, such as replacing the circuit board, adjusting the parameters, etc. Fault cause refers to the cause of abnormality of the instrument under test 3 given in the form of text or voice based on the cause and solution of the fault in the expert diagnosis processing knowledge base, such as unstable power supply, communication line interference, etc. Diagnostic report refers to a document that records the detection process and results of the instrument under test 3 in the form of text or table based on the cause and solution of the fault in the expert diagnosis processing knowledge base, such as detection time, detection personnel, detection items, detection results, etc. Fault location information refers to information indicating abnormality of specific parts or components of the instrument under test 3 given in the form of text or voice based on the cause and solution of the fault in the expert diagnosis processing knowledge base, such as power module, communication acquisition module, etc. The processing steps and processing methods refer to the steps and methods for guiding maintenance or debugging personnel on how to perform operations or repairs in the form of text or voice, such as disassembling circuit boards, replacing components, etc., based on the fault causes and solutions in the expert diagnosis and processing knowledge base. The fault diagnosis module can output the matching results through the data display unit in the host computer 1, and store the output results in the memory or external storage device, that is, in the data storage unit.

[0077] Specifically, the fault matching module is used to match the fault mask with the fault model coding in the expert diagnosis processing knowledge base. The expert diagnosis processing knowledge base refers to a database established based on the summary and induction of the causes and solutions of logging instrument failures by experts or experienced personnel, including fault models, fault causes, fault diagnosis diagrams, diagnostic suggestions, fault location information, processing steps and processing methods. The fault model refers to the correspondence between different fault masks and the fault types encoded in the corresponding fault model according to the fault diagnosis rules and experience in the expert diagnosis processing knowledge base, such as 0101 for power failure, 1100 for communication acquisition failure, etc. The fault matching module can realize the coding comparison of the fault mask and the fault model through the data matching module in the host computer 1, and store the comparison results in the memory or external storage device, that is, in the data storage unit.

[0078] As a specific example, the status word refers to a signal generated by the instrument under test 3 during its working process that indicates its working status. The status word includes: a power status word, which is used to indicate the power status of the instrument under test 3; a communication acquisition status word, which is used to indicate the communication acquisition status of the instrument under test 3; a transmission excitation status word, which is used to indicate the transmission excitation status of the instrument under test 3; a reception conditioning status word, which is used to indicate the reception conditioning status of the instrument under test 3; and a probe status word, which is used to indicate the probe status of the instrument under test 3.

[0079] As a specific example, the expert diagnosis processing knowledge base includes a binary state word group, a logical relationship group, and a diagnosis conclusion group.

[0080] The expert diagnosis processing knowledge base can be set in the fault matching module, and can also be set in the fault diagnosis module at the same time.

[0081] The expert diagnosis and processing knowledge base divides the fault diagnosis module into power supply fault diagnosis and processing module, communication acquisition fault diagnosis and processing module, transmission excitation fault diagnosis and processing module, receiving conditioning fault diagnosis and processing module, and probe fault diagnosis and processing module in the vertical direction, and divides each fault module into module-related status words, auxiliary logic conditions, signal flow node combinations, node fault factor combinations, processing combinations, factor characteristic value combinations, and assistant prompt information combinations in the horizontal direction. The expert diagnosis and processing knowledge base can be a multi-dimensional data structure, which can be queried and matched according to different dimensions. In the vertical direction, the expert diagnosis and processing knowledge base divides the fault diagnosis module according to the different functions or signal processing parts of the instrument under test 3, such as the power supply part, communication acquisition part, transmission excitation part, receiving conditioning part, probe part, etc. In this way, it is convenient to determine the part or module that may have a fault according to the different status words or fault masks of the instrument under test 3. In the horizontal direction, the expert diagnosis processing knowledge base divides each fault diagnosis processing module according to different information or conditions, such as module-related status words, auxiliary logic conditions, signal flow node combinations, node fault factor combinations, processing combinations, factor characteristic value combinations, assistant prompt information combinations, etc. In this way, the specific fault cause and solution can be easily determined according to the different information or conditions of the instrument under test 3.

[0082] The expert diagnosis processing knowledge base can be a data structure composed of three main parts, a binary state word group, a logical relationship group, and a diagnostic conclusion group, wherein the binary state word group stores the fault model code for matching with the fault mask, the logical relationship group stores the logical relationship of the state word logic "and" and the logical "or", and the diagnostic conclusion group stores the diagnostic result of the corresponding fault code. It can be queried and matched according to different inputs and outputs. The binary state word group refers to the binary data stored in the expert diagnosis processing knowledge base that represents the state word value that the instrument under test 3 should have when working normally or abnormally, such as 0101, 1100, etc. The logical relationship group refers to the logical data stored in the expert diagnosis processing knowledge base that represents the necessary or sufficient conditional relationship between different state words, such as A and B, A or B, etc.

[0083] In the logic relationship processing module, the binary state words in the truth table are subjected to logic "AND" and logic "OR" logic relationship operations, and the logic relationship comes from the logic relationship group. The diagnosis conclusion group refers to the text or voice data stored in the expert diagnosis processing knowledge base that represents the fault type and solution determined according to different state words and logical relationships, such as power supply failure, communication acquisition failure, etc. In this way, it is convenient to match the binary state word group in the expert diagnosis processing knowledge base according to the fault mask and output the corresponding diagnosis conclusion group.

[0084] As a preferred example, the smart instrument detection software also includes a voice assistant prompt module, which is used to voice guide the user to complete circuit board level fault location and / or instrument fault troubleshooting based on the diagnosis results.

[0085] Specifically, the host computer 1 may be provided with a voice unit for receiving an audio signal sent by the voice assistant prompt module and making a sound. The voice assistant prompt module may also be provided with a sound making function separately.

[0086] As a preferred example, the host computer 1 further includes:

[0087] A data display unit, used to display the diagnostic results of the smart instrument detection software on the screen in the form of graphics or text;

[0088] The data storage unit is used to store the diagnosis results and related data of the smart instrument detection software in the memory or external storage device.

[0089] As a preferred example, the system includes three modes:

[0090] Smart board detection mode, used to detect circuit board faults;

[0091] Single board positioning one-button detection mode, used to detect instrument single board faults with one button;

[0092] Instrument fault detection mode, used for complex fault detection of instrument circuits.

[0093] According to the different detection objects, the system detection methods can be divided into intelligent single-board detection methods for circuit boards, single-board positioning one-key detection methods for instruments, and instrument fault detection methods.

[0094] The principle of the smart board detection method is: connect the host computer 1 installed with the smart board detection software to the test box 2 through the bus interface 4, complete the signal measurement and upload of the circuit board to be tested, and the host computer 1 will collect the status word combination through the communication link and perform binary processing. If the logical value "and" relationship of these status word combinations is "0", the board can be judged to be abnormal; otherwise, "1", it is normal.

[0095] The principle of the one-button detection method for single-board positioning is that the host computer 1 is connected to the instrument under test 3 through the test box 2. The host computer 1 installed with the intelligent single-board detection software completes the measurement and upload of the instrument logging signal through the bus conversion board of the test box 2, and binarizes the status word and makes a judgment. The difference from the intelligent single-board detection method is that it is necessary to establish a logical AND or OR relationship between the signal combination associated with the single board based on the logical relationship of the board-level positioning. The uploaded status word is binarized and combined with the logical relationship group to form a corresponding diagnostic conclusion. The diagnostic conclusion includes the abnormal circuit troubleshooting suggestions corresponding to the state combination and the logical relationship combination conditions. The operator uses the spare board to verify step by step according to the troubleshooting suggestions, recycles the detection, and finally determines the type and number of the actual faulty single board of the instrument.

[0096] In addition to considering the factors of the circuit board, the instrument fault detection method also considers complex situations such as abnormalities of loose parts such as wiring and skeletons. The source of its status word includes three ways: information uploaded by the instrument under test 3, power supply interaction input information, and node interaction input information. Nodes are set between boards or between functional blocks and boards. The type and quantity are related to the overall state of the status word of the instrument under test 3 and the power supply status word after binarization. After the binary values ​​of the three status words are determined, they are matched with the fault model of the expert diagnosis and processing knowledge base to form an expert troubleshooting plan. Users gradually verify according to the troubleshooting suggestions until all positioning and repairs are completed.

[0097] Embodiment 1, as Figure 4 The method of using this system is shown as follows:

[0098] S1 . Put the instrument under test 3 into the test box 2 . The test box 2 collects the signal of the instrument under test 3 and uploads the signal to the host computer 1 through the bus interface 4 .

[0099] S2. The data input module of the smart instrument detection software receives the signal uploaded by the test box 2, extracts and organizes the information in the signal, obtains the required status word, and transmits the status word to the truth table generation module.

[0100] S3, the truth table generation module compares the status word with the status word nominal value. If it is within the specified error range, it is processed as a logic "1", otherwise, it is processed as a logic "0" and the binarized status word is transmitted to the logic relationship processing module.

[0101] S4. The logic relationship processing module performs corresponding logic relationship operations of logic “AND” and logic “OR” on the binary status word to obtain a fault mask, and sends the fault mask to the fault matching module.

[0102] S5. The fault matching module matches the fault mask with the fault model in the expert diagnosis processing knowledge base to obtain a matching result. The fault diagnosis module outputs the diagnosis result in the expert diagnosis processing knowledge base based on the obtained matching result.

[0103] S6. The voice assistant prompt module guides the user to complete circuit board level fault location and / or instrument fault troubleshooting according to the diagnosis results.

[0104] S7. The host computer 1 generates a corresponding detection report and stores and records the fault information.

[0105] Embodiment 2, as Figure 5 As shown, a smart single board detection method based on the smart single board detection mode comprises the following steps:

[0106] S11 , placing the circuit board under test into the test box 2 , the test box 2 collects signals of the circuit board under test, and uploads the signals to the host computer 1 through the bus interface 4 .

[0107] S12. The data input module of the smart instrument detection software receives the signal uploaded by the test box 2, extracts and organizes the information in the signal, obtains the required status word, and transmits the status word to the truth table generation module.

[0108] S13, the truth table generation module compares the status word with the status word nominal value. If it is within the specified error range, it is processed as a logic "1", otherwise, it is processed as a logic "0" and the binarized status word is transmitted to the logic relationship processing module.

[0109] S14, the logic relationship processing module performs corresponding logic relationship operations of logic "AND" and logic "OR" on the binary status word. If the logic value "AND" relationship of the binary status word combination is "0", it can be judged that the single board is abnormal; otherwise, it is "1", which means it is normal.

[0110] Embodiment 3, as Figure 6 As shown, the single board positioning one-key detection method based on the single board positioning one-key detection mode comprises the following steps:

[0111] S21 , placing the instrument under test 3 into the test box 2 , the test box 2 collects signals from the instrument under test 3 , and uploads the signals to the host computer 1 through the bus interface 4 .

[0112] S22. The data input module of the smart instrument detection software receives the signal uploaded by the test box 2, extracts and organizes the information in the signal, obtains the required status word, and transmits the status word to the truth table generation module.

[0113] S23, the truth table generation module compares the status word with the status word nominal value. If it is within the specified error range, it is processed as a logic "1", otherwise, it is processed as a logic "0", and the binarized status word is transmitted to the logic relationship processing module.

[0114] S24, the logic relationship processing module combines the binary status words associated with the single board to establish a logic AND or OR relationship based on the logic relationship of the board-level positioning, obtains a fault mask, and sends the fault mask to the fault matching module.

[0115] S25. The fault matching module matches the fault mask with the fault model in the expert diagnosis processing knowledge base to obtain a matching result. The fault diagnosis module outputs the diagnosis result in the expert diagnosis processing knowledge base based on the obtained matching result.

[0116] S26. The voice assistant prompt module guides the user by voice according to the diagnosis results to use the spare board for step-by-step verification according to the troubleshooting suggestions, recycles the detection, and finally determines the type and number of the actual faulty boards of the instrument.

[0117] S27, the host computer 1 generates a corresponding detection report and stores and records the fault information.

[0118] Specifically, the diagnosis result includes corresponding abnormal circuit troubleshooting suggestions.

[0119] Embodiment 4, as Figure 7 As shown, the instrument fault detection method based on the instrument fault detection mode comprises the following steps:

[0120] S31, placing the instrument under test 3 into the test box 2, the test box 2 collects the signal of the instrument under test 3, as well as the power supply interaction input information and the node interaction input information, and uploads the collected signal and information to the host computer 1 through the bus interface 4.

[0121] S32. The data input module of the smart instrument detection software receives the signal and information uploaded by the test box 2, extracts and organizes all the information, obtains the required three status words, and transmits the obtained status words to the truth table generation module.

[0122] S33, the truth table generation module compares the status word with the status word nominal value. If it is within the specified error range, it is processed as a logic "1", otherwise, it is processed as a logic "0", and the binarized status word is transmitted to the logic relationship processing module.

[0123] S34, the logic relationship processing module performs corresponding logic relationship operations of logic “AND” and logic “OR” on the binary status word to obtain a fault mask, and sends the fault mask to the fault matching module.

[0124] S35. The fault matching module matches the fault mask with the fault model in the expert diagnosis processing knowledge base to obtain a matching result. The fault diagnosis module outputs the diagnosis result in the expert diagnosis processing knowledge base based on the obtained matching result.

[0125] S36. The voice assistant prompt module guides the user to complete circuit board level fault location and / or instrument fault troubleshooting according to the diagnosis results.

[0126] S37, the host computer 1 generates a corresponding detection report and stores and records the fault information.

[0127] It is known from common technical knowledge that the present invention can be implemented by other embodiments that do not deviate from its spirit or essential features. Therefore, the above disclosed embodiments are only illustrative in all respects and are not exclusive. All changes within the scope of the present invention or within the scope equivalent to the present invention are included in the present invention.

Claims

1. A well logging instrument intelligent detection system, characterized in that: include, The test box (2) is used to be connected to the instrument under test (3) and connected to the host computer (1) via a bus interface (4); Host computer (1), used to install the smart instrument detection software; Smart instrument detection software, including: Expert diagnosis knowledge base, used to store fault model data and corresponding processing methods; A data input module, used for receiving status words collected by the test box (2); A truth table generation module is used to perform binarization processing on the collected status words, arrange the binarized status words into a truth table, and send the truth table to the logic relationship processing module; A logic relationship processing module is used to receive the truth table sent by the truth table generation module, perform logic "AND" and logic "OR" logic relationship operations on the binary status words in the truth table, and obtain a fault mask; A fault matching module is used to match the fault mask with the fault model code in the expert diagnosis processing knowledge base to obtain a matching result; The fault diagnosis module is used to output the corresponding processing method in the expert diagnosis processing knowledge base as the diagnosis result according to the obtained matching result.

2. A well logging instrument intelligent detection system according to claim 1, characterized in that: The binary processing steps are: compare the collected status word with the status word nominal value. If it is within the specified error range, the status word is processed as logic "1", otherwise, it is processed as logic "0".

3. The intelligent detection system for well logging instruments according to claim 1, characterized in that: The smart instrument detection software also includes a voice assistant prompt module, which is used to voice guide users to complete circuit board-level fault location and / or instrument troubleshooting based on the diagnosis results.

4. The intelligent detection system for well logging instruments according to claim 1, characterized in that: The method of arranging the binary state word into a truth table is: S1, grouping the binary status words according to the structure or function of the instrument under test (3); S2. Arrange all the groups according to the first set order to form a truth table.

5. The intelligent detection system for well logging instruments according to claim 4, characterized in that: The logic relationship processing module performs logic "AND" and logic "OR" operations on the binary status words in the truth table to obtain the fault mask method steps as follows: S11, the logic relationship processing module lists all possible fault information of the instrument under test (3) in sequence according to the second set order; S12, according to the possible fault information, selecting a group related to the possible fault information in the truth table; S13, selecting a binary status word related to possible fault information from the selected group; S14, if there are multiple binary status words selected in the selected group, then according to the corresponding logical "and" and logical "or" logical relations stored in the expert diagnosis and processing knowledge base, the binary status words selected in the selected group are subjected to logical relation operations to obtain the output result of the selected group; if there is only one binary status word selected in the selected group, then the binary status word is used as the output result of the selected group, and the output results of the selected groups are arranged in a first set order to obtain a combination code corresponding to the fault information; S15. Repeat steps S12-S14 to obtain a combination code corresponding to each piece of fault information, and arrange the combination code corresponding to each piece of fault information in a second set order to obtain a fault mask.

6. The intelligent detection system for well logging instruments according to claim 1, characterized in that: The system includes three modes, Smart board detection mode, used to detect circuit board faults; Single board positioning one-button detection mode, used to detect instrument single board faults with one button; Instrument fault detection mode, used for complex fault detection of instrument circuits.

7. The intelligent detection system for well logging instruments according to claim 1, characterized in that: The expert diagnosis processing knowledge base includes a binary status word group, a logic relationship group, and a diagnosis conclusion group. The binary status word group stores the fault model code for matching with the fault mask, the logic relationship group stores the logical relationship of the status word logic "AND" and logic "OR", and the diagnosis conclusion group stores the diagnosis result of the corresponding fault code.

8. The intelligent detection system for well logging instruments according to claim 7, characterized in that: The logic relationship processing module constructs the logic "AND" and logic "OR" logic relationships between different status words according to the correlation between different status words and circuit boards or instrument parts, and stores the constructed logic relationships in the logic relationship group in the expert knowledge base.

9. The intelligent detection system for well logging instruments according to claim 1, characterized in that: The test box (2) comprises: A power supply module, used for providing a stable power supply to the instrument under test (3) and the host computer (1); A signal acquisition module, used for acquiring signals from the instrument under test (3) and converting them into digital signals; A bus interface (4) module, used for transmitting the digital signal collected by the signal collection module to the host computer (1); The instrument interface module is used to connect the instrument under test (3) and the test box (2).

10. The intelligent detection system for well logging instruments according to claim 1, characterized in that: The host computer (1) further includes: A data display unit, used to display the diagnostic results of the smart instrument detection software on the screen in the form of graphics or text; The data storage unit is used to store the diagnosis results and related data of the smart instrument detection software in the memory or external storage device.

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