Integrated system and method for carrying multiple sensors for inspection robot

Abstract

The method comprises the following steps: acquiring environmental parameter data, position parameter data, real-time video data, sound data and basic monitoring data collected by a preset sensor in the inspection process of a target inspection robot, and according to the above data, acquiring a plurality of sensors in the target inspection robot; obtaining the real-time dynamic state of the target inspection robot, and predicting an inspection instruction of the inspection robot in combination with a preset algorithm; and controlling the inspection robot to inspect according to the inspection instruction. By carrying multiple sensors, the integrated system can comprehensively and detailedly collect various parameters of the environment and the robot, the capability of sensing and understanding the environment of the inspection robot is greatly improved, and the inspection robot can more accurately judge the state of the inspection robot and the change of the surrounding environment. A large amount of collected data are analyzed and processed through a preset algorithm, and the next optimal action of the inspection robot, namely an inspection instruction, can be predicted.

Description

Technical Field

[0001] The present invention relates to the technical field of substation inspection robots, and in particular to an integrated system and method for an inspection robot equipped with multiple sensors. Background Art

[0002] Existing substation inspection robot systems usually rely on a single or a small number of sensors for data collection, which limits the comprehensiveness and accuracy of inspections. At the same time, the strategy for processing sensor data and the ability to adjust strategies to deal with emergencies are weak, and they are often unable to generate dynamic inspection strategies based on real-time environmental changes or equipment status.

[0003] In addition, the intelligence level of power management in the prior art is not high. When the power reserve is insufficient, the inspection path or strategy cannot be adjusted in time to ensure the completion of the inspection task. Therefore, the prior art needs to be improved and enhanced. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides an integrated system and method for an inspection robot equipped with multiple sensors, which can solve the problems mentioned in the background technology.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides an integrated system equipped with multiple sensors for an inspection robot, comprising: a real-time data acquisition unit, an integrated control unit, an inspection execution unit communication unit, a power supply unit, and a server unit;

[0009] The real-time data acquisition and processing unit is used to acquire real-time data during the inspection process of the target inspection robot, pre-process the real-time data, and transmit the pre-processed real-time data to the integrated control unit through the communication unit;

[0010] The integrated control unit is used to obtain the real-time data processed by the real-time data acquisition and processing unit, and judge the real-time status of the target inspection robot according to the preset judgment algorithm logic, and set the inspection robot to be operated instructions, and transmit the to-be-operated instructions to the inspection execution unit through the communication unit;

[0011] The inspection execution unit is used to receive the pending operation instructions transmitted by the integrated control unit, control the inspection robot to perform the inspection operation according to the pending operation instructions, and perform real-time inspection execution operation rationality judgment at the same time, and after obtaining the judgment result, transmit the result to the server unit through the communication unit;

[0012] The communication unit is used to control the communication connection between different modules;

[0013] The power supply unit is used to supply power to different modules and determine whether the remaining power is sufficient to complete the inspection task;

[0014] The server unit is used to structure the data generated by different units during different inspection tasks, and to provide data to be retrieved to different modules, and to send different warnings to the inspection personnel according to the judgment results transmitted by the inspection execution unit.

[0015] As a preferred solution of the integrated system equipped with multiple sensors for the inspection robot of the present invention, the real-time data acquisition unit includes: a sensor integration module, a first data preprocessing module and an edge computing module;

[0016] The sensor integration module is used to obtain environmental parameter data, infrared parameter data, gas parameter data, acoustic parameter data and visual parameter data, and transmit the obtained data to the first data preprocessing module, the first data preprocessing module performs a first processing on the environmental parameter data, infrared parameter data, and gas parameter data received from the sensor integration module, performs a second processing on the acoustic parameter data, and performs a third processing on the visual parameter data, and transmits the results of the first processing, the second processing and the third processing to the edge computing module and the integrated control unit, the edge computing module performs a first type of edge computing on the result of the first processing, performs a second type of edge computing on the result of the second processing, and performs a third type of edge computing on the results of the three processings, and transmits the first type of edge computing, the second type of edge computing and the third type of edge computing to the integrated control unit through the communication unit respectively;

[0017] The sensor integration module, the first data preprocessing module and the edge computing module are connected in a unidirectional communication sequence;

[0018] The first data preprocessing module and the edge computing module are communicatively connected to the integrated control unit via a communication unit.

[0019] As a preferred solution of the integrated system equipped with multiple sensors for the inspection robot of the present invention, the integrated control unit includes: a second data preprocessing module, a logic judgment module, an intelligent decision-making module and an instruction generation module;

[0020] The second data preprocessing module is communicatively connected with the first data preprocessing module and the edge computing module through a communication unit, and performs a fourth processing on the acquired data, and transmits the result of the fourth processing to the logic judgment module, and the logic judgment module judges the state of the inspection robot according to the fourth processing result combined with a preset judgment logic;

[0021] The logic judgment module transmits the determined inspection robot state to the intelligent decision-making module, and the intelligent decision-making module generates an inspection strategy based on the inspection robot state and the results transmitted by the first data preprocessing module and the edge computing module, combined with a preset inspection strategy model;

[0022] The intelligent decision-making module transmits the generated inspection strategy to the instruction generation module, and the instruction generation module generates corresponding instructions according to the inspection strategy;

[0023] The second data preprocessing module, the logic judgment module, the intelligent decision-making module and the instruction generation module are communicatively connected in sequence.

[0024] As a preferred solution of the integrated system equipped with multiple sensors for the inspection robot of the present invention, the intelligent decision-making module includes: a first inspection strategy generation unit, a second inspection strategy generation unit and a third inspection strategy generation unit;

[0025] The first inspection strategy generating unit is used to generate an inspection strategy according to the inspection robot state and the results transmitted by the first data preprocessing module and the edge computing module, combined with a preset inspection strategy model;

[0026] The second inspection strategy generating unit is used to regenerate the inspection strategy according to the unreasonable judgment result transmitted by the inspection execution unit, that is, to regenerate the inspection strategy after taking the unreasonable judgment result transmitted by the inspection execution unit as a new constraint condition;

[0027] The third inspection strategy generating unit is used to regenerate the inspection strategy according to the instruction of re-planning of insufficient margin transmitted by the power supply unit, that is, to regenerate the inspection strategy after taking the instruction of re-planning of insufficient margin transmitted by the power supply unit as a new constraint condition.

[0028] As a preferred solution of the integrated system equipped with multiple sensors for the inspection robot of the present invention, the inspection execution unit includes: an instruction acquisition module, a rationality judgment module and an execution module;

[0029] The instruction acquisition module is used to acquire instructions transmitted from the instruction generation module, and the instruction acquisition module is communicatively connected with the instruction generation module via a communication unit;

[0030] The rationality judgment module is used to judge the rationality of the instructions obtained by the instruction acquisition module. If the instructions are reasonable, the corresponding instructions are transmitted to the execution module, and the inspection robot performs the inspection operation according to the corresponding instructions. If the instructions are unreasonable, the unreasonable results are transmitted to the second inspection strategy generation unit to regenerate the inspection strategy.

[0031] The instruction acquisition module, rationality judgment module and execution module are communicatively connected in sequence.

[0032] As a preferred solution of the integrated system equipped with multiple sensors for the inspection robot described in the present invention, the rationality judgment module includes: making rationality judgment on the acquired instructions according to a preset rationality judgment logic, and the rationality judgment logic includes rationality judgment of the operating environment, rationality judgment of the operating displacement, rationality judgment of the operating action and rationality judgment of the operating time.

[0033] As a preferred solution of the integrated system equipped with multiple sensors for the inspection robot of the present invention, the power supply unit includes: a main power supply module, a backup power supply module, a power judgment module and a remaining power operation module;

[0034] The power judgment module is used to judge whether the remaining power meets the requirements for the inspection robot to perform a complete inspection strategy according to the generated inspection strategy, and the remaining power includes the sum of the power of the main power module and the backup power module;

[0035] If it is satisfied, the surplus operation module does not operate;

[0036] If not, the margin operation module sends the margin information and an instruction for re-planning due to insufficient margin to the third inspection strategy generation unit, and regenerates the inspection strategy.

[0037] In a second aspect, the present invention provides an integration method for carrying multiple sensors on an inspection robot, comprising:

[0038] Acquire environmental parameter data, position parameter data, real-time video data, sound data and basic monitoring data collected by preset sensors of the target inspection robot during the inspection process, wherein the basic monitoring data at least includes temperature data, infrared data, gas data and inclination data;

[0039] According to the environmental parameter data, position parameter data, real-time video data, sound data and basic monitoring data, the real-time dynamics of the target inspection robot are obtained, and the inspection instructions of the inspection robot are predicted in combination with a preset algorithm;

[0040] The inspection robot is controlled to perform inspection according to the inspection instruction.

[0041] In a third aspect, the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method when executing the computer program.

[0042] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the method described above when executed by a processor.

[0043] Compared with the prior art, the invention has the following beneficial effects: the invention proposes an integrated system and method for an inspection robot equipped with multiple sensors, which obtains environmental parameter data, position parameter data, real-time video data, sound data and basic monitoring data collected by preset sensors of the target inspection robot during the inspection process, wherein the basic monitoring data at least includes temperature data, infrared data, gas data and inclination data; obtains the real-time dynamics of the target inspection robot according to the environmental parameter data, position parameter data, real-time video data, sound data and basic monitoring data, and predicts the inspection instructions of the inspection robot in combination with a preset algorithm; controls the inspection robot to perform inspections according to the inspection instructions. By carrying multiple sensors, the integrated system can comprehensively and in detail collect various parameters of the environment and the robot, greatly improving the inspection robot's ability to perceive and understand the environment, so that it can more accurately judge its own state and changes in the surrounding environment. By analyzing and processing the large amount of collected data through a preset algorithm, the next best action of the inspection robot, i.e., the inspection instruction, can be predicted. The need for human intervention is reduced, and the inspection efficiency and accuracy are improved. In summary, this application realizes the in-depth utilization of data and intelligent decision-making, improves the efficiency, accuracy and safety of inspections, and is of great significance for promoting the development of inspection robot technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0045] Figure 1 A schematic diagram of the system structure of an integrated system and method for an inspection robot equipped with multiple sensors provided by an embodiment of the present invention;

[0046] Figure 2 A method flow chart of an integrated system and method for an inspection robot equipped with multiple sensors provided by one embodiment of the present invention;

[0047] Figure 3An internal structural diagram of a computer device of an integrated system and method for an inspection robot equipped with multiple sensors provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0049] Example 1

[0050] Reference Figure 1-Figure 3 , which is the first embodiment of the present invention, provides an integrated system and method for an inspection robot equipped with multiple sensors, including:

[0051] In the related technology, inspection robots usually rely on single or limited sensors for environmental perception and decision-making when performing tasks, which limits their adaptability to complex environments and inspection efficiency.

[0052] The present application provides an effective solution to the above-mentioned problems. Next, multiple embodiments will be combined to explain in detail how to implement the integrated system equipped with multiple sensors for the inspection robot;

[0053] Figure 1 The system structure diagram of an integrated system and method for an inspection robot equipped with multiple sensors is shown, including:

[0054] Among them, the real-time data acquisition unit 100, the integrated control unit 200, the inspection execution unit 300, the communication unit 400, the power supply unit 500 and the server unit 600;

[0055] Specifically, the real-time data acquisition and processing unit 100 is used to collect real-time data during the inspection process of the target inspection robot, pre-process the real-time data, and transmit the pre-processed real-time data to the integrated control unit 200 through the communication unit 400;

[0056] Furthermore, the integrated control unit 200 is used to obtain the real-time data processed by the real-time data acquisition and processing unit 100, and judge the real-time state of the target inspection robot according to the preset judgment algorithm logic, and set the inspection robot to be operated instructions, and transmit the to-be-operated instructions to the inspection execution unit 300 through the communication unit 400;

[0057] Furthermore, the inspection execution unit 300 is used to receive the pending operation instructions transmitted by the integrated control unit 200, control the inspection robot to perform the inspection operation according to the pending operation instructions, and perform a real-time inspection execution operation rationality judgment at the same time, and after obtaining the judgment result, transmit the result to the server unit 600 through the communication unit 400;

[0058] Furthermore, the communication unit 400 is used to control the communication connection between different modules;

[0059] Furthermore, the power supply unit 500 is used to supply power to different modules and determine whether the remaining power is sufficient to complete the inspection task;

[0060] Furthermore, the server unit 600 is used to structure the data generated by different units during different inspection tasks, and provide data to be retrieved to different modules, and send different warnings to the inspection personnel according to the judgment results transmitted by the inspection execution unit 300.

[0061] In the embodiment of the present application, the real-time data acquisition unit 100 includes: a sensor integration module 101, a first data preprocessing module 102 and an edge computing module 103;

[0062] The sensor integration module 101 is used to obtain environmental parameter data, infrared parameter data, gas parameter data, acoustic parameter data and visual parameter data, and transmit the obtained data to the first data preprocessing module 102. The first data preprocessing module 102 performs a first processing on the environmental parameter data, infrared parameter data and gas parameter data received from the sensor integration module 101, performs a second processing on the acoustic parameter data, and performs a third processing on the visual parameter data, and transmits the results of the first processing, the second processing and the third processing to the edge computing module 103 and the integrated control unit 200. The edge computing module 103 performs a first type of edge computing on the result of the first processing, performs a second type of edge computing on the result of the second processing, and performs a third type of edge computing on the results of the three processings, and transmits the first type of edge computing, the second type of edge computing and the third type of edge computing to the integrated control unit 200 through the communication unit 400 respectively.

[0063] The sensor integration module 101, the first data preprocessing module 102 and the edge computing module 103 are connected in unidirectional communication in sequence;

[0064] The first data preprocessing module 102 and the edge computing module 103 are communicatively connected with the integrated control unit 200 via the communication unit 400 .

[0065] In an embodiment of the present application, environmental parameter data includes temperature, humidity, wind speed and weather data, which are acquired through built-in sensors, infrared parameter data are acquired through built-in infrared sensors, and gas parameter data are acquired through built-in gas sensors.

[0066] In the embodiment of the present application, the first processing includes data cleaning and data normalization, removing invalid values ​​and outliers, and reducing the data to the range of [0, 1]; the specific steps of the first type of edge computing are to use the sliding window method to monitor the data flow, define the window size as w, and calculate the mean of the data in the window. and standard deviation σ w , if the new data point X new Satisfy the conditions It is marked as abnormal, where k is a constant, k=3 in this application, and linear regression is used to predict the parameter value at the next moment. Let X t is the current value, then the predicted value It can be expressed as X t +1 p =aX t +b, where a and b are the regression coefficients.

[0067] In the embodiment of the present application, the second processing includes time-frequency transformation and energy spectral density calculation, using short-time Fourier transform STFT to convert the time series signal into the frequency domain, and calculating the energy spectral density of each frequency band. The second type of edge computing includes noise suppression and time recognition, applying an adaptive filtering algorithm to reduce background noise and using an improved machine learning model to identify specific acoustic events, wherein the improved machine learning model in the present application is specifically constructed as follows:

[0068] Input layer: Receives audio data, usually audio features represented in the form of spectrograms, i.e., the second processed data.

[0069] CNN layer: Three convolutional layers are used to extract local features, and each convolutional layer is followed by a pooling layer to reduce the dimension and further extract features.

[0070] LSTM layers: Three or more LSTM layers are used to capture dependencies in time series.

[0071] Fully connected layers: used for final classification, may include Dropout layers to reduce overfitting.

[0072] Output layer: Use the Softmax activation function to output the probability of each category.

[0073] Improve the loss function of the machine learning model. Use a composite loss function to perform detailed identification of substation faults and spark sounds. The specific expression is as follows:

[0074] L total =L WCE +λL FL

[0075] Here, λ is a balancing parameter used to adjust the relative importance between weighted cross entropy loss and focal loss.

[0076] Among them, let w i is the weight of the i-th class, y i is the true label (for multi-classification tasks, y i is a one-hot vector), p i is the probability predicted by the model, then the weighted cross entropy loss can be expressed as:

[0077]

[0078] Where C is the total number of categories and weight w i It can be set according to the distribution of categories in the training data, usually set to the inverse of the category frequency or a more complex adjustment scheme.

[0079] L FL =-α t (1-p t ) γ log(p t )

[0080] Among them, α t is the balancing factor for class t, γ is the focusing parameter, and p t is the model's predicted probability for category t. When γ>0, the focal loss pays more attention to samples with lower predicted probabilities, that is, samples that are more difficult to classify.

[0081] Weight setting: In this application, for substation fault and spark sound recognition, w can be set according to the proportion of fault and normal operation sounds in the training set. i ;

[0082] Focal loss parameter: α t The values ​​of γ and γ need to be determined based on experiments. Usually γ is set between 2 and 4, and α t It can be set to 1 minus the frequency of the class in the training set.

[0083] Balance parameter λ: The value of λ also needs to be determined through cross-validation to find the best balance between weighted cross entropy loss and focal loss.

[0084] In the embodiment of the present application, the third processing includes image preprocessing and feature extraction, performing histogram equalization on the image, enhancing contrast, and applying convolutional neural network CNN to extract image feature vectors. The third type of edge computing includes target detection and behavior analysis, applying target detection algorithms such as YOLO and using improved behavior recognition models to analyze target behavior. The improved behavior recognition model in this application is to identify whether any equipment in the substation appears in a non-original position, that is, when a device at a certain place in the substation does not appear at the position where it should originally appear or the state of the device is different from the preset normal comparison state, then its abnormality is identified and recorded. The specific representation of the improved behavior recognition model can be as follows:

[0085] Assume that we use the pre-trained CNN model f CNN To extract the features of image I, it can be expressed as:

[0086] f CNN (I)=Feature Vector

[0087] Furthermore, using RNN or Transformer models RNN or Trans To integrate features on time series:

[0088] f RNN (f CNN (I1),f CNN (I2),...,f CNN (I n ))=Temporal Feature

[0089] or

[0090] f Trans (f CNN (I1),f CNN (I2),...,f CNN (I n ))=Temporal Feature

[0091] Furthermore, using the classifier f Classify To determine whether the device is in an abnormal state or position:

[0092] f Classify (Temporal Feature)=P abnormal

[0093] Among them, P abnormal is the probability that the device is in an abnormal state;

[0094] If P abnormal If it exceeds a certain threshold value θ, the device status is considered abnormal.

[0095] Step 4: Decision making and documentation

[0096] If the device status is abnormal, record the timestamp, device location and status information, and may trigger an alarm

[0097] Record(t,Position,State)

[0098] In the training phase, the loss function can be cross entropy loss, which is used for classification tasks in supervised learning. For each sample, if the true label is y (abnormal or normal) and the probability distribution predicted by the model is p, the loss function is:

[0099]

[0100] Where N is the number of samples.

[0101] It should be noted that the above steps can effectively handle complex scenarios in substation monitoring, including different lighting conditions, equipment diversity, and behavioral patterns in time series. The improved model can capture local features in the image and dynamic behaviors in the time series, while the composite loss function ensures the model's sensitivity to each category, especially the minority category, and reduces classification bias.

[0102] In the embodiment of the present application, the integrated control unit 200 includes: a second data preprocessing module 201, a logic judgment module 202, an intelligent decision module 203 and an instruction generation module 204;

[0103] The second data preprocessing module 201 is connected to the first data preprocessing module 102 and the edge computing module 103 through the communication unit 400, and performs a fourth processing on the acquired data, and transmits the result of the fourth processing to the logic judgment module 202. The logic judgment module 202 judges the state of the inspection robot according to the fourth processing result combined with the preset judgment logic;

[0104] The logic judgment module 202 transmits the determined inspection robot state to the intelligent decision-making module 203. The intelligent decision-making module 203 generates an inspection strategy based on the inspection robot state and the results transmitted by the first data preprocessing module 102 and the edge computing module 103, combined with the preset inspection strategy model;

[0105] The intelligent decision-making module 203 transmits the generated inspection strategy to the instruction generation module 204, and the instruction generation module 204 generates corresponding instructions according to the inspection strategy;

[0106] The second data preprocessing module 201, the logic judgment module 202, the intelligent decision-making module 203 and the instruction generation module 204 are communicatively connected in sequence.

[0107] In an embodiment of the present application, the fourth processing is used to perform structured classification on the data acquired by the first data preprocessing module 102 according to the calculation results of the edge computing module 103, that is, to classify the original data corresponding to the edge classification results calculated by the edge computing module 103, so as to facilitate the subsequent preset judgment logic to judge the status of the inspection robot.

[0108] In an embodiment of the present application, the preset judgment logic includes environmental safety judgment, setting the safety judgment threshold of the corresponding parameters, and ensuring that no harm is caused to the equipment or personnel by monitoring environmental parameters such as temperature, humidity, gas concentration, etc. If the data processed by the first data preprocessing module 102 proves that the environment is unsafe at this time, the inspection robot state is an unknown safety state. At this time, the inspection robot does not operate and needs to wait on the spot for inspection personnel to handle it.

[0109] Equipment health judgment: Set the equipment health judgment threshold of the corresponding parameters, and judge whether the equipment is operating normally through equipment status data, such as temperature, vibration, sound, etc., to detect potential faults in time. If the data processed by the first data preprocessing module 102 proves that the equipment is unhealthy at this time, the inspection robot state is the second-level alarm state. At this time, the inspection robot sends a certain equipment failure warning to the inspection personnel, and sends a second-level sound alarm on the spot to remind nearby personnel to leave in an orderly manner;

[0110] Operation compliance judgment: set the operation compliance judgment threshold of the corresponding parameter, and ensure that all operations comply with safety regulations by checking the switch position, operation process, etc. If the data processed by the first data preprocessing module 102 proves that the operation is not compliant at this time, the inspection robot state is a first-level alarm state. At this time, the inspection robot sends an operation non-compliance warning to the inspection personnel and determines whether a recovery operation can be performed. If a recovery operation can be performed, an emergency operation warning is sent to the inspection personnel to notify the inspection personnel to perform a remote recovery operation.

[0111] In the embodiment of the present application, the intelligent decision-making module 203 includes: a first inspection strategy generation unit 203a, a second inspection strategy generation unit 203b and a third inspection strategy generation unit 203c;

[0112] The first inspection strategy generating unit 203a is used to generate an inspection strategy according to the inspection robot state and the results transmitted by the first data preprocessing module 102 and the edge computing module 103, combined with a preset inspection strategy model;

[0113] The second inspection strategy generating unit 203b is used to regenerate the inspection strategy according to the unreasonable judgment result transmitted by the inspection execution unit 300, that is, to regenerate the inspection strategy after taking the unreasonable judgment result transmitted by the inspection execution unit 300 as a new constraint condition;

[0114] The third inspection strategy generating unit 203c is used to regenerate the inspection strategy according to the insufficient margin re-planning instruction transmitted from the power supply unit 500, that is, to regenerate the inspection strategy after taking the insufficient margin re-planning instruction transmitted from the power supply unit 500 as a new constraint condition.

[0115] In the embodiment of the present application, the first inspection strategy generating unit 203a sets the environmental parameter set as E={e1, e2, ..., e n}, where e i Represents the i-th environmental parameter (such as temperature, humidity, gas concentration, etc.).

[0116] The set of security thresholds is T = {t1, t2, ..., t n},t i for e i safety threshold.

[0117] Environmental adaptability evaluation function f env (E,T) is expressed as:

[0118]

[0119] Among them, l i and u i Yes i lower and upper limits.

[0120] Equipment health parameter set H = {h1,h2,...,h m},h j Represents the health parameter of the jth device.

[0121] Health threshold set V = {v1,v2,...,v m},v j h j health threshold.

[0122] Equipment health status evaluation function f dev (H,V) is expressed as:

[0123]

[0124] Among them, k j and w j Yes j lower and upper limits.

[0125] Operation compliance parameter set O = {o1, o2, ..., o p},o k Represents the compliance parameters of the k-th operation.

[0126] Compliance threshold set S = {s1, s2, ..., s p},s k for o k compliance threshold.

[0127] Operation compliance evaluation function f opr (O,S) is expressed as:

[0128]

[0129] Among them, g k and r k Yes k lower and upper limits.

[0130] Furthermore, the device layout matrix L, where L ij Indicates the distance from device i to device j.

[0131] Path generation function f path (L) The shortest path between devices should be considered, and the Dijkstra algorithm or other path planning algorithms can be used.

[0132] Comprehensive constraint function f con (f emv ,f dev ,f opr ) is expressed as:

[0133] f con (f env ,f dev ,f opr )=min(f env ,f dev ,f opr )

[0134] Strategy generation function f strat (f con ,L) Integrate constraints and path planning to generate inspection strategies.

[0135] The unreasonableness judgment result R in the second inspection strategy generation unit (203b), where R = {r1, r2, ..., r q}, r1 represents the lth unreasonable judgment.

[0136] Update the constraint function and modify f according to R con The threshold value in, i.e., f con (f emv ,f dev ,f opr , f update )

[0137] The power set P in the third inspection strategy generation unit (203c) is {p1, p2}, where p1 is the power of the main power supply, p2 is the power of the backup power supply, and the total power P tot =p1+p2;

[0138] Power demand for inspection tasks D.

[0139] Low battery response function f pouver (P tot ,D) is expressed as:

[0140]

[0141] Update constraint function, i.e. f con (f emv ,f dev ,f opr , f update , f pouver ).

[0142] In the embodiment of the present application, the inspection execution unit 300 includes: an instruction acquisition module 301, a rationality judgment module 302 and an execution module 303;

[0143] The instruction acquisition module 301 is used to acquire instructions transmitted from the instruction generation module 204, and the instruction acquisition module 301 is connected to the instruction generation module 204 through the communication unit 400;

[0144] The rationality judgment module 302 is used to judge the rationality of the instruction acquired by the instruction acquisition module 301. If it is reasonable, the corresponding instruction is transmitted to the execution module 303, and the inspection robot performs the inspection operation according to the corresponding instruction. If it is unreasonable, the unreasonable result is transmitted to the second inspection strategy generation unit 203b to regenerate the inspection strategy;

[0145] The instruction acquisition module 301 , the rationality judgment module 302 and the execution module 303 are communicatively connected in sequence.

[0146] The rationality judgment module 302 includes: performing rationality judgment on the acquired instructions according to a preset rationality judgment logic, wherein the rationality judgment logic includes rationality judgment on the operating environment, rationality judgment on the operating displacement, rationality judgment on the operating action and rationality judgment on the operating time.

[0147] In the embodiment of the present application, the rationality judgment of the operating environment mainly focuses on whether the current operation is suitable for the given environmental conditions. Assuming there is an environmental parameter set E and a corresponding safety range set R, for any environmental parameter e∈E, the mathematical judgment of its rationality can be expressed as:

[0148]

[0149] Among them, R e is a reasonable range for parameter e.

[0150] The rationality judgment of the operation displacement involves the feasibility of the robot moving to the target position. Assume that D is the distance from the current position of the robot to the target position, and D max is the maximum allowable displacement of the robot, then the rationality judgment can be expressed as:

[0151]

[0152] The rationality judgment of the operation action ensures that the action performed by the robot does not exceed its physical or operational limitations. Let A be the action performed by the robot, and A set is the set of all possible reasonable actions, then the rationality judgment can be expressed as:

[0153]

[0154] The reasonableness judgment of operation time ensures that the operation is completed within the given time. Assume that T req is the time required to complete the operation, and T avail is the available time, then the rationality judgment can be expressed as:

[0155]

[0156] It should be noted that in the embodiment of the present application, judgment is performed in the order of judging the rationality of the operating environment, judging the rationality of the operating displacement, judging the rationality of the operating action, and judging the rationality of the operating time.

[0157] In the embodiment of the present application, the power supply unit 500 includes: a main power supply module 501, a backup power supply module 502, a power determination module 503 and a residual power operation module 504;

[0158] The power judgment module 503 is used to judge whether the remaining power is sufficient for the inspection robot to perform a complete inspection strategy according to the generated inspection strategy, and the remaining power includes the sum of the power of the main power module 501 and the backup power module 502;

[0159] If satisfied, the remaining amount operation module 504 does not perform any operation;

[0160] If not, the margin operation module 504 sends the margin information and the margin insufficient re-planning instruction to the third inspection strategy generation unit 203 c , and regenerates the inspection strategy.

[0161] This embodiment also provides an integration method for a patrol robot equipped with multiple sensors, including:

[0162] S101, obtaining environmental parameter data, position parameter data, real-time video data, sound data and basic monitoring data collected by preset sensors of the target inspection robot during the inspection process, where the basic monitoring data at least includes temperature data, infrared data, gas data and inclination data;

[0163] S102, obtaining the real-time dynamics of the target inspection robot according to the environmental parameter data, the position parameter data, the real-time video data, the sound data and the basic monitoring data, and predicting the inspection instructions of the inspection robot in combination with the preset algorithm;

[0164] S103, controlling the inspection robot to perform inspection according to the inspection instruction.

[0165] In summary, the present invention proposes an integrated system and method for an inspection robot equipped with multiple sensors, which obtains environmental parameter data, position parameter data, real-time video data, sound data and basic monitoring data collected by preset sensors of the target inspection robot during the inspection process, wherein the basic monitoring data at least includes temperature data, infrared data, gas data and inclination data; obtains the real-time dynamics of the target inspection robot according to the environmental parameter data, position parameter data, real-time video data, sound data and basic monitoring data, and predicts the inspection instructions of the inspection robot in combination with a preset algorithm; and controls the inspection robot to perform inspections according to the inspection instructions. By carrying multiple sensors, the integrated system can comprehensively and in detail collect various parameters of the environment and the robot, greatly improving the inspection robot's ability to perceive and understand the environment, so that it can more accurately judge its own state and changes in the surrounding environment. By analyzing and processing the large amount of collected data through a preset algorithm, the next best action of the inspection robot, i.e., the inspection instruction, can be predicted. The need for human intervention is reduced, and the inspection efficiency and accuracy are improved. In summary, this application realizes the in-depth utilization of data and intelligent decision-making, improves the efficiency, accuracy and safety of inspections, and is of great significance for promoting the development of inspection robot technology.

[0166] The above-mentioned unit modules may be embedded in or independent of the processor in the computer device in the form of hardware, or may be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0167] This embodiment also provides a computer device, which may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 3As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for integrating multiple sensors for an inspection robot is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0168] This embodiment further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0169] Obtain environmental parameter data, position parameter data, real-time video data, sound data and basic monitoring data collected by preset sensors of the target inspection robot during the inspection process. The basic monitoring data includes at least temperature data, infrared data, gas data and inclination data;

[0170] According to the environmental parameter data, location parameter data, real-time video data, sound data and basic monitoring data, the real-time dynamics of the target inspection robot are obtained, and the inspection instructions of the inspection robot are predicted in combination with the preset algorithm;

[0171] Control the inspection robot to perform inspection according to the inspection instructions.

[0172] Example 2

[0173] Reference Figure 1-Figure 3 , which is an embodiment of the present invention, provides an integrated system and method for an inspection robot equipped with multiple sensors. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through experiments.

[0174] The experimental setup is as follows: Two different configurations of inspection robots are used in the experiment, one is the integrated system with multiple sensors proposed by the present invention, and the other is a traditional single sensor inspection robot as a comparison reference. The experimental environment simulates a complex industrial environment, including different temperatures, humidity, gas composition and terrain changes.

[0175] During the experiment, the two inspection robots worked according to the preset inspection routes, collecting environmental parameter data, location parameter data, real-time video data, sound data, and basic monitoring data. At the same time, the remaining power of the power supply unit was monitored through the power judgment module to verify the response of the remaining power operation module when the power was insufficient.

[0176] Experimental results show that the inspection robot using the integrated system of the present invention can more accurately predict and execute inspection instructions, and its prediction accuracy is more than 30% higher than that of traditional robots. In the case of insufficient power, the remaining power operation module can send remaining power information in time and re-plan the inspection strategy, ensuring the continuity and integrity of the inspection task. In addition, due to the ability to fully perceive the environment, the robot's adaptability and safety in the face of complex environmental changes are also significantly enhanced.

[0177] In the comparative experiment, the traditional single-sensor inspection robot showed deficiencies in the comprehensiveness of data collection, response to environmental changes, and power management. Its inspection efficiency and accuracy were relatively low, and it was slow to respond to power warnings and strategy adjustments.

[0178] Table 1: Experimental results.

[0179]

[0180]

[0181] Through the above experiments, it can be concluded that the integrated system and method for the inspection robot equipped with multiple sensors proposed in the present invention improves the efficiency, accuracy and safety of inspection by comprehensively collecting and intelligently processing multi-dimensional data, which has significant practical significance for optimizing the performance of the inspection robot and promoting the development of related technologies.

[0182] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0183] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0184] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0185] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0186] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0187] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0188] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. An integrated system with multiple sensors for inspection robots. It is characterized in that include: A real-time data acquisition unit (100), an integrated control unit (200), an inspection execution unit (300), a communication unit (400), a power supply unit (500), and a server unit (600); The real-time data acquisition and processing unit (100) is used to acquire real-time data during the inspection process of the target inspection robot, pre-process the real-time data, and transmit the pre-processed real-time data to the integrated control unit (200) through the communication unit (400); The integrated control unit (200) is used to obtain the real-time data processed by the real-time data acquisition and processing unit (100), and judge the real-time state of the target inspection robot according to a preset judgment algorithm logic, and set the inspection robot waiting for operation instructions, and transmit the waiting for operation instructions to the inspection execution unit (300) through the communication unit (400); The inspection execution unit (300) is used to receive the pending operation instruction transmitted by the integrated control unit (200), control the inspection robot to perform the inspection operation according to the pending operation instruction, and simultaneously perform a real-time inspection execution operation rationality judgment, and after obtaining the judgment result, transmit the result to the server unit (600) through the communication unit (400); The communication unit (400) is used to control the communication connection between different modules; The power supply unit (500) is used to supply power to different modules and determine whether the remaining power is sufficient to complete the inspection task; The server unit (600) is used for structured storage of data generated by different units during different inspection tasks, and for providing data to be retrieved to different modules, while sending different warnings to inspection personnel according to the judgment results transmitted by the inspection execution unit (300).

2. The integrated system equipped with multiple sensors for the inspection robot according to claim 1, It is characterized in that The real-time data acquisition unit (100) comprises: a sensor integration module (101), a first data preprocessing module (102) and an edge computing module (103); The sensor integration module (101) is used to obtain environmental parameter data, infrared parameter data, gas parameter data, acoustic parameter data and visual parameter data, and transmit the obtained data to the first data preprocessing module (102); the first data preprocessing module (102) performs a first process on the environmental parameter data, infrared parameter data and gas parameter data received from the sensor integration module (101), performs a second process on the acoustic parameter data and performs a third process on the visual parameter data, and transmits the results of the first process, the second process and the third process to the edge computing module (103) and the integrated control unit (200); the edge computing module (103) performs a first type of edge computing on the result of the first process, performs a second type of edge computing on the result of the second process, and performs a third type of edge computing on the results of the three processes, and transmits the first type of edge computing, the second type of edge computing and the third type of edge computing to the integrated control unit (200) through the communication unit (400); The sensor integration module (101), the first data preprocessing module (102), and the edge computing module (103) are connected in a one-way communication sequence; The first data preprocessing module (102) and the edge computing module (103) are communicatively connected to the integrated control unit (200) via a communication unit (400).

3. The integrated system equipped with multiple sensors for the inspection robot as claimed in claim 2, It is characterized in that The integrated control unit (200) comprises: a second data preprocessing module (201), a logic judgment module (202), an intelligent decision-making module (203) and an instruction generation module (204); The second data preprocessing module (201) is connected to the first data preprocessing module (102) and the edge computing module (103) in communication via a communication unit (400), and performs a fourth process on the acquired data, and transmits the result of the fourth process to the logic judgment module (202), and the logic judgment module (202) judges the state of the inspection robot according to the fourth process result combined with a preset judgment logic; The logic judgment module (202) transmits the judged inspection robot state to the intelligent decision-making module (203), and the intelligent decision-making module (203) generates an inspection strategy based on the inspection robot state and the results transmitted by the first data preprocessing module (102) and the edge computing module (103), combined with a preset inspection strategy model; The intelligent decision-making module (203) transmits the generated inspection strategy to the instruction generation module (204), and the instruction generation module (204) generates corresponding instructions according to the inspection strategy; The second data preprocessing module (201), the logic judgment module (202), the intelligent decision-making module (203) and the instruction generation module (204) are communicatively connected in sequence.

4. The integrated system equipped with multiple sensors for the inspection robot as claimed in claim 3, It is characterized in that The intelligent decision-making module (203) comprises: a first inspection strategy generating unit (203a), a second inspection strategy generating unit (203b) and a third inspection strategy generating unit (203c); The first inspection strategy generating unit (203a) is used to generate an inspection strategy based on the inspection robot status and the results transmitted by the first data preprocessing module (102) and the edge computing module (103), combined with a preset inspection strategy model; The second inspection strategy generating unit (203b) is used to regenerate the inspection strategy according to the unreasonable judgment result transmitted by the inspection execution unit (300), that is, to regenerate the inspection strategy after taking the unreasonable judgment result transmitted by the inspection execution unit (300) as a new constraint condition; The third inspection strategy generating unit (203c) is used to regenerate the inspection strategy according to the instruction for re-planning due to insufficient margin transmitted from the power supply unit (500), that is, to regenerate the inspection strategy after taking the instruction for re-planning due to insufficient margin transmitted from the power supply unit (500) as a new constraint condition.

5. The integrated system equipped with multiple sensors for the inspection robot as claimed in claim 4, It is characterized in that The inspection execution unit (300) comprises: an instruction acquisition module (301), a rationality judgment module (302) and an execution module (303); The instruction acquisition module (301) is used to acquire instructions transmitted from the instruction generation module (204), and the instruction acquisition module (301) is communicatively connected with the instruction generation module (204) via a communication unit (400); The rationality judgment module (302) is used to judge the rationality of the instruction acquired by the instruction acquisition module (301); if it is reasonable, the corresponding instruction is transmitted to the execution module (303), and the inspection robot performs the inspection operation according to the corresponding instruction; if it is unreasonable, the unreasonable result is transmitted to the second inspection strategy generation unit (203b) to regenerate the inspection strategy; The instruction acquisition module (301), the rationality judgment module (302) and the execution module (303) are connected in communication in sequence.

6. The integrated system equipped with multiple sensors for the inspection robot as claimed in claim 5, It is characterized in that The rationality judgment module (302) includes: performing rationality judgment on the acquired instructions according to a preset rationality judgment logic, wherein the rationality judgment logic includes rationality judgment of the operating environment, rationality judgment of the operating displacement, rationality judgment of the operating action and rationality judgment of the operating time.

7. The integrated system equipped with multiple sensors for the inspection robot as claimed in claim 6, It is characterized in that The power supply unit (500) comprises: a main power supply module (501), a backup power supply module (502), a power quantity determination module (503) and a residual quantity operation module (504); The power judgment module (503) is used to judge whether the remaining power is sufficient for the inspection robot to execute a complete inspection strategy according to the generated inspection strategy, and the remaining power includes the sum of the power of the main power module (501) and the backup power module (502); If satisfied, the surplus operation module (504) does not perform any operation; If not, the margin operation module (504) sends the margin information and the margin shortage re-planning instruction to the third inspection strategy generation unit (203c), and regenerates the inspection strategy.

8. An integration method for an inspection robot equipped with multiple sensors, It is characterized in that include: Acquire environmental parameter data, position parameter data, real-time video data, sound data and basic monitoring data collected by preset sensors of the target inspection robot during the inspection process, wherein the basic monitoring data at least includes temperature data, infrared data, gas data and inclination data; According to the environmental parameter data, position parameter data, real-time video data, sound data and basic monitoring data, the real-time dynamics of the target inspection robot are obtained, and the inspection instructions of the inspection robot are predicted in combination with a preset algorithm; The inspection robot is controlled to perform inspection according to the inspection instruction.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program. It is characterized in that When the processor executes the computer program, the steps of the method according to claim 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the steps of the method according to claim 8 are implemented.

Images