CN109471803B - Complicated industrial system digital man-machine interface picture configuration method based on human factor reliability - Google Patents
Complicated industrial system digital man-machine interface picture configuration method based on human factor reliability Download PDFInfo
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Abstract
A complicated industrial system digitization human-computer interface picture configuration method based on human factor reliability relates to the digitization human-computer interface and human factor engineering cross technology field, the configuration method includes: 1) based on the priority-time slice dynamic weight double-ratio distribution scheduling method, calling opened pictures in the digital system to enter or call out a buffer pool; 2) dynamically determining the ordering of pictures which have entered a buffer pool in a queue in 1) based on a relevance detection marked queue scheduling method; 3) screening picture prompt information by a screening method based on the weight association degree and displaying related picture prompt information in sequence according to the weight association degree; 4) and determining whether to call the related picture according to the picture prompt information. The invention relates to a picture configuration method based on human factor reliability, which can save cognitive load, psychological pressure and accident recovery time spent by an operator in the picture configuration process and reduce the occurrence of human factor accidents.
Description
Technical Field
The invention relates to the technical field of digital human-computer interfaces and human factor engineering intersection, in particular to a method for configuring a picture of a digital human-computer interface of a complex industrial system based on human factor reliability.
Background
Currently, most industrial systems are using or will use digitizing systems. The widespread use of digitizing systems has transformed the role of operators from the original "operators" to "managers and monitors". The operator does not need to walk around and walk around between the coil platforms, but mainly takes a sitting posture to acquire information and execute accident regulations through some displays. However, the overloaded digital information and pictures make the accident handling process easy to generate human errors, and in order to correctly execute the accident regulations, the monitoring of the whole system is completed, the system state is known in time, all the required information needs to be effectively acquired through picture configuration, and the accident handling is correctly completed. According to survey and interview, a large number of pictures are the main reasons for interfering with information acquisition, accident recovery and handling of operators, and at present, operators generally deal with the problem by enhancing simulation training and improving operation proficiency, however, fundamentally, the picture configuration of a human-computer interface should be optimized as much as possible, and the workload brought to the operators by various pictures in a digital human-computer interface is reduced.
In the design of the human-computer interface layout, a learner thinks that the experience and knowledge of people are considered, the computer technology and the human factor engineering method based on the knowledge are considered, the design method mainly adopts the evolutionary theory, and the thought realizes the breakthrough of the design method. Based on this, many researchers have proposed various interface design methods considering human factors, such as: the human comfort level, the thinking characteristics and the action characteristics of an operator are brought into the functional design of a human-computer interface, or the comfort level, the spatial layout, the operation mode humanization, the visual range, the seat design principle and other aspects are combined, or the human cognitive psychological characteristics and the personnel safety hidden danger problem of a human are considered and the interface is designed by combining a virtual human body model while the physical interface design is completed.
With the emphasis of human factor reliability, recently, research has been proposed on a digitalized human-machine interface evaluation method based on human factor reliability analysis (HRA), which uses a human-based cognitive reliability (HCR) method to identify a risk scene with a high failure probability from the whole event, then uses a cognitive reliability and failure analysis method (CREAM) to determine various failure modes and failure probabilities thereof for the high risk scene, sequences the failure rates, and then establishes a human factor reliability evaluation table according to the characteristics of the digitalized human-machine interface to review the human-machine interface with a high failure rate, so as to observe the defects in the design of the human-machine interface. The research improves the evaluation of the human-computer interface to a high level, because the human factor reliability in the digital system is the key point for designing the human-computer interface, the method provided by the research is a qualitative method, the subjectivity exists, and the deviation exists in the evaluation of the human-computer interface.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a complicated industrial system digital man-machine interface picture configuration method based on human factor reliability, which can save cognitive load, psychological pressure and accident recovery time spent by an operator in the picture configuration process and reduce the occurrence of human factor accidents.
In order to solve the technical problems, the invention adopts the following technical scheme: human factor reliability test system of digital man-machine interface configuration performance includes: the device comprises an input layer, a hidden layer and an output layer, wherein an inlet and an outlet of the hidden layer are respectively connected with the input layer and the output layer;
the input layer is used for determining input parameter factors;
the hidden layer is used for calculating the human factor reliability of the input parameter factors according to the input transfer function of the neural network;
and the output layer is used for calculating a picture configuration performance test result of the input parameter factor based on human factor reliability according to the neural network excitation function.
Further, the input parameter factors include screen configuration performance test evaluation indexes, time spent by an operator in completing a corresponding task, and other influence factors in the test process.
Further, the neural network input transfer function of the hidden layer is:
yb＝f1(netb)
wherein, ybRepresenting a neural network input transfer function; m represents the number of evaluation indexes of the digital human-computer interface for performance test, and is also called as an input variable; v. ofabRepresenting the weight value of the input layer a-th neuron to the hidden layer b-th neuron; c. CaThe a-th input variable value for the performance test evaluation index is represented.
Further, the neural network excitation function of the output layer is:
O＝f2(net)
o is the output layer calculated value, i.e.: a digitized human-computer interface performance result based on human factor reliability; s is the weight number from the hidden layer to the output layer; w is abThe weight of the b-th neuron of the hidden layer to the neuron of the output layer.
Further, with f1(x) Neural network input transfer function representing the hidden layer:
with f2(x) Neural network excitation function representing the output layer:
wherein n represents the number of segments of time spent by an operator in completing a corresponding task when testing the performance of the human-computer interface; Δ i ═ Ti/n，TiThe time spent by an operator in completing the corresponding task when testing the configuration performance of the picture is represented; lambda [ alpha ]jThe parameter values are corresponding to the performance evaluation indexes; r (t) is the maximum delay time allowed for the operator when completing the corresponding task; the function z (x) is a human factor reliability analysis mathematical expression.
As another aspect of the present invention, a method for configuring a digital human-machine interface screen of a complex industrial system based on human reliability, comprises:
1) based on the priority-time slice dynamic weight double-ratio distribution scheduling method, calling opened pictures in the digital system to enter or call out a buffer pool;
2) dynamically determining the ordering of pictures which have entered a buffer pool in a queue in 1) based on a relevance detection marked queue scheduling method;
3) screening the picture prompt information by a screening method based on the weight association degree and displaying the relevant picture prompt information in turn according to the height of the weight association degree;
4) and determining whether to call the related picture according to the picture prompt information.
Further, in 1), the scheduling method based on priority-time slice dynamic weight double-ratio distribution is as follows:
the priority and the time slice are combined to determine the weight ratio of the picture, the picture with high weight ratio enters a human-computer interface buffer pool from a digital system to wait for calling, when the storage space set by the buffer pool is full, the weight ratio of the picture is determined again according to the priority and the time slice, and the picture with low weight ratio in the human-computer interface buffer pool exits the buffer pool to be automatically closed or hidden before being manually closed at a certain moment so as to wait for next awakening or calling.
Still further, in 2), the scheduling method for detecting the identified queue based on the correlation degree is as follows:
designing a queue to identify and temporarily store a plurality of pictures, designing a variable to identify when a certain picture is out of queue or in queue, when the identification variable changes, the relevant importance of each picture is re-determined, the pictures are smoothly arranged from the head of the queue according to the importance, if only one picture information needs to be checked at the same moment, a picture with the maximum relevant importance is generated in a dequeuing mode and displayed on a certain display screen opposite to the moment of an operator, if a plurality of picture information need to be checked at the same moment, a plurality of pictures with larger relevant importance are generated in a dequeuing mode, and displays the picture of the greatest relative importance on a display screen that the operator is facing at that moment, the other pictures are distributed according to the priority principle that the picture with the largest importance degree is displayed on a certain screen with the smallest distance and from left to right.
Further, in 3), the weight association degree is a degree that the main operation procedure and the screen prompt message are closely related at a certain time, and the screen prompt message is filtered when the weight association degree is less than a set threshold value, and the screen prompt message is sequentially displayed according to the height of the weight association degree when the weight association degree is greater than or equal to the set threshold value.
Preferably, the human factor reliability analysis of the performance parameters in the digital human-machine interface configuration process by adopting the human factor reliability test system for the digital human-machine interface configuration performance comprises the following steps:
determining a weight ratio of each picture priority to a time slice in 1) based on the human factor reliability test system;
determining the relative importance of each picture in 2) based on the human factor reliability test system;
and determining the weight association degree of the picture prompt information in the step 3) based on the human factor reliability test system.
In the method for configuring the digital man-machine interface picture of the complex industrial system based on the human factor reliability, three different configuration stages provide three different configuration methods, specifically, when the picture is determined to enter or call out a man-machine interface buffer pool, a scheduling method based on priority-time slice dynamic weight double-ratio distribution is adopted, the picture with high weight ratio enters the man-machine interface buffer pool to wait for calling, and the picture with low weight ratio exits from the man-machine interface buffer pool, so that the storage space of the buffer pool can be fully utilized, an important picture is called for an operator in time, and the picture calling efficiency is improved; when the picture of the calling buffer pool enters a certain display screen, a scheduling method based on the relevancy detection marked queue is adopted to call in a plurality of pictures, so that the redundancy of the pictures can be effectively reduced, the pictures required by an operator can be given in a targeted manner, and the workload of the operator for selecting the pictures is reduced; in addition, when the screen prompt information is screened and displayed, the screen prompt information which is lower than the weight relevance threshold is screened out by adopting a weight-based relevance screening method, otherwise, the screen prompt information is displayed in sequence according to the relevance, the screen prompt information is very important for the relevant operation of an operator, the effective screening method can greatly save the cognitive load of the operator on the screen configuration process, and particularly can reduce the screen data analysis pressure of the operator when abnormal accidents are processed. In summary, the invention can effectively save cognitive load, psychological pressure and accident recovery time spent by an operator in the process of configuring the picture, and reduce the occurrence of human accidents.
In addition, the invention also provides a human factor reliability test system for the configuration performance of the digital human-computer interface, the system performs performance test on important parameters involved in the configuration process of the digital human-computer interface based on the neural network to obtain the human factor reliability result of each parameter, the result can accurately evaluate the configuration method of the human-computer interface, and an operator can be effectively assisted to correctly execute related operations according to the configuration method.
Drawings
FIG. 1 is a block diagram of a human factor reliability testing system for the configuration performance of a digital human-machine interface according to the present invention;
FIG. 2 is a flow chart of a complicated industrial system digitalized human-computer interface picture configuration method based on human factor reliability in the present invention;
FIG. 3 is a flow chart of a priority-time slice dynamic weight based dual rate allocation scheduling method according to the present invention;
FIG. 4 is a flow chart of a scheduling method with identification queues based on relevancy detection in accordance with the present invention;
FIG. 5 is a flowchart of the method for screening prompt information based on weight association according to the present invention.
Detailed Description
In order to facilitate understanding of those skilled in the art, the present invention will be further described with reference to the following examples and drawings, which are not intended to limit the present invention.
The human factor reliability test system of the configuration performance of the digital human-computer interface comprises an input layer, a hidden layer and an output layer, wherein an inlet and an outlet of the hidden layer are respectively connected with the input layer and the output layer; the input layer is used for determining input parameter factors; the hidden layer is used for calculating the human factor reliability of the input parameter factor according to the input transfer function of the neural network; and the output layer is used for calculating a picture configuration performance test result of the input parameter factor based on the human factor reliability according to the neural network excitation function.
As shown in fig. 1, the operational principle of the human factor reliability testing system for the configuration performance of the digital human-computer interface in the above embodiment is specifically as follows:
firstly, determining an input parameter factor at an input layer, wherein the input parameter factor comprises the following steps: evaluation index x of picture configuration performance test1、x2……xnThe time t taken by the operator to complete the corresponding task, and other impact factors f during the test1、f2……fnAnd transmitting the input parameter factors to the hidden layer, and then calculating the human factor reliability of the input parameter factors by the hidden layer according to the following neural network input transfer function:
yb＝f1(netb)
wherein, ybRepresenting a neural network input transfer function; m represents the number of evaluation indexes of the digital human-computer interface for performance test, and is also called as an input variable; v. ofabRepresenting the weight value of the input layer a-th neuron to the hidden layer b-th neuron; c. CaRepresenting the a-th input variable value for the performance test evaluation index;
and finally, calculating a picture configuration performance test result of the input parameter factor based on the human factor reliability according to the following neural network excitation function in an output layer:
O＝f2(net)
o is the output layer calculated value, i.e.: a digitized human-computer interface performance result based on human factor reliability; s is the weight number from the hidden layer to the output layer; w is abThe weight of the b-th neuron of the hidden layer to the neuron of the output layer.
In the human factor reliability test system according to the above embodiment, f is further defined as1(x) Neural network input transfer function representing the hidden layer:
with f2(x) Neural network excitation function representing the output layer:
wherein n represents the number of segments of time spent by an operator in completing a corresponding task when testing the performance of the human-computer interface; Δ i ═ Ti/n，TiThe time spent by an operator in completing the corresponding task when testing the configuration performance of the picture is represented; lambda [ alpha ]jThe parameter values are corresponding to the performance evaluation indexes; r (t) is the maximum delay time allowed for the operator when completing the corresponding task; the function z (x) is a human factor reliability analysis mathematical expression.
It should be noted that the human factor reliability test system tests the performance of the digital human-computer interface image configuration based on the neural network, and there are two main reasons for selecting the neural network technology: firstly, the neural network technology is widely applied at present, and the technology is mature; second, neural network techniques have incomparable advantages over other methods of modifying input parameter factors.
As another aspect of the present invention, a method for configuring a digitized human-machine interface screen of a complex industrial system based on human reliability, as shown in fig. 2, comprises:
1) based on the priority-time slice dynamic weight double-ratio distribution scheduling method, calling opened pictures in the digital system to enter or call out a buffer pool;
2) dynamically determining the ordering of pictures which have entered a buffer pool in a queue in 1) based on a relevance detection marked queue scheduling method;
3) screening the picture prompt information by a screening method based on the weight association degree and displaying the relevant picture prompt information in turn according to the height of the weight association degree;
4) and determining whether to call the related picture according to the picture prompt information.
Regarding the digitized human-computer interface image configuration method 1) related to the above embodiment, mainly, the method determines the human-computer interface buffer pool entering and calling method, and this method mainly solves the method of entering and calling the human-computer interface from the digitized system, that is, a suitable scheduling method is to be found to solve the problem that which images should be called into the human-computer interface at a certain time and which images should exit the human-computer interface in time for temporary hiding or closing. Typical scheduling methods currently include: a first-come-first-serve method, a priority method, an elevator method, a lottery scheduling method, a fair sharing scheduling method, a single-rate scheduling method, a deadline scheduling method, and the like. The embodiment establishes a proper scheduling method by combining with the actual situation, namely: a dynamic weight double-ratio distribution scheduling method based on priority-time slice is proposed according to picture importance and time slice principle, and the method is characterized in that two factors of priority and time slice are effectively combined, pictures with high weight ratio should be kept in a human-computer interface buffer pool as much as possible, and on the other hand, due to the limited storage space of the buffer pool, the pictures kept in the human-computer interface should exit the buffer pool to be automatically closed or hidden before being manually closed at a certain moment so as to wait for next awakening or calling. The key issue of this approach is how to determine the weight ratio of priority to time slices, since the weight ratio largely determines which pictures should enter or exit the buffer pool at a time. The method has the difficulty that how to take the values of the priority and the time slice of the picture at a certain time is difficult, because the procedure, the parameter and the auxiliary information interface executed each time are different, even if the same picture is obtained, when the information of other interfaces or matched processing information matched with the picture at a certain time is inconsistent, the importance and the distribution of the time slice are also different, and the method embodies the dynamic property. The workflow of the method is shown in fig. 3.
Regarding the method for configuring the frames of the digital human-machine interface in the above embodiment, 2) is mainly a method for determining a display mode in which a plurality of frames are randomly arranged according to a correlation importance (also referred to as a time urgency), and the method is to solve a dynamic logical relationship between a plurality of frames presented to an operator when a plurality of frames exist on a display screen on the basis of the above 1), and is different from 1) in that: this section is a method of managing multiple frames that have entered a human-machine interface from a digitizing system. According to the specific situation of the digital human-computer interface and the relevance of specific tasks, a marked queue method based on relevant importance detection is provided. In the method, the relevant importance degree is dynamically changed and is embodied in that: the same picture has different importance levels in different picture sequences, that is, each picture needs to be reassigned its associated importance level whenever the picture sequence changes. On the other hand, the method needs to design a queue to identify and temporarily store a plurality of pictures, when a certain picture is out of queue or in queue, a variable is designed to identify, when the identification variable changes, the picture sequence is changed, the relative importance of each picture needs to be determined again, and the arrangement is smoothly carried out from the head of the team according to the importance degree, if only one picture information needs to be checked at the same time, a picture with the maximum relevant importance degree is generated in a dequeuing mode and displayed on a certain display screen which is faced by an operator at the moment, if a plurality of picture information are required to be viewed at the same moment, similarly, generating a plurality of pictures with larger relative importance by dequeuing, displaying the picture with the largest relative importance on a certain display screen facing the operator at the moment, the other pictures are distributed according to the priority principle that the picture with the largest importance degree is displayed on a certain screen with the smallest distance and from left to right. The workflow of the method is shown in fig. 4.
Regarding the digitized human-machine interface screen configuration method 3) related to the above embodiment, mainly is a screening method for determining screen prompt information in the human-machine interface, and this method further solves the screening of the screen prompt information on the basis of the above 2), so as to avoid too much prompt information to increase the burden of the operator. Currently, there are several screening methods in the world, such as: genetic screening methods, gradient screening methods, hierarchical screening methods, parallel recursive screening methods, linear programming screening methods, mathematical mean sampling point screening methods, and the like. In this embodiment, a method for screening relevance based on weight is adopted, where the relevance of weight refers to the degree of close correlation between the main operation procedure and the screen prompt information at a certain time, and the relevance is screened when the relevance is smaller than a set threshold. The method is characterized in that the method is used for determining the weight, the weight is different from the common weight, and particularly refers to the human factor reliability represented by the correlation between the main operation procedure and the picture prompt information, and the higher the human factor reliability is, the larger the weight is. The workflow of the method is shown in fig. 5.
In the method for configuring a digital human-machine interface screen of a complex industrial system based on human factor reliability according to the above embodiment, specifically, the analysis of human factor reliability on performance parameters in the process of configuring a digital human-machine interface by using the human factor reliability testing system for configuring the performance of the digital human-machine interface may include:
determining a weight ratio of each picture priority to a time slice in 1) based on the human factor reliability test system;
determining the relevant importance of each picture in 2) based on the human factor reliability test system;
and determining the weight association degree of the picture prompt information in the step 3) based on the human factor reliability test system.
The above embodiments are preferred implementations of the present invention, and the present invention can be implemented in other ways without departing from the spirit of the present invention.
Some of the drawings and descriptions of the present invention have been simplified to facilitate the understanding of the improvements over the prior art by those skilled in the art, and some other elements have been omitted from this document for the sake of clarity, and it should be appreciated by those skilled in the art that such omitted elements may also constitute the subject matter of the present invention.
Claims (5)
1. A complicated industrial system digital man-machine interface picture configuration method based on human factor reliability comprises the following steps:
1) based on the priority-time slice dynamic weight double-ratio distribution scheduling method, calling opened pictures in the digital system to enter or call out a buffer pool;
2) dynamically determining the ordering of pictures which have entered a buffer pool in a queue in 1) based on a relevance detection marked queue scheduling method;
3) screening picture prompt information by a screening method based on the weight association degree and displaying related picture prompt information in sequence according to the weight association degree;
4) and determining whether to call the related picture according to the picture prompt information.
2. The human reliability-based digital human-computer interface screen configuration method for the complex industrial system, as claimed in claim 1, wherein: in 1), the scheduling method based on priority-time slice dynamic weight double-ratio distribution is as follows:
the priority and the time slice are combined to determine the weight ratio of the picture, the picture with high weight ratio enters a human-computer interface buffer pool from a digital system to wait for calling, when the storage space set by the buffer pool is full, the weight ratio of the picture is determined again according to the priority and the time slice, and the picture with low weight ratio in the human-computer interface buffer pool exits the buffer pool to be automatically closed or hidden before being manually closed at a certain moment so as to wait for next awakening or calling.
3. The human reliability-based digitized man-machine interface screen configuration method for the complex industrial system according to claim 2, characterized in that: in 2), the scheduling method for detecting the identified queue based on the correlation degree is as follows:
designing a queue to identify and temporarily store a plurality of pictures, designing a variable to identify when a certain picture is out of queue or in queue, when the identification variable changes, the relevant importance of each picture is re-determined, the pictures are smoothly arranged from the head of the queue according to the importance, if only one picture information needs to be checked at the same moment, a picture with the maximum relevant importance is generated in a dequeuing mode and displayed on a certain display screen opposite to the moment of an operator, if a plurality of picture information need to be checked at the same moment, a plurality of pictures with larger relevant importance are generated in a dequeuing mode, and displays the picture with the greatest relevant importance on a certain display screen that the operator is facing at that moment, the other pictures are distributed according to the priority principle that the picture with the largest importance degree is displayed on a certain screen with the smallest distance and from left to right.
4. The human reliability-based digitized man-machine interface screen configuration method for the complex industrial system according to claim 3, characterized in that: in 3), the weight association degree is a degree that the main operation rule and the screen prompt information are closely related at a certain time, when the weight association degree of the screen prompt information is smaller than a set threshold value, the screen prompt information is screened out, and when the weight association degree of the screen prompt information is larger than or equal to the set threshold value, the screen prompt information is displayed in sequence according to the weight association degree.
5. The method for configuring the digitized human-computer interface picture of the complex industrial system based on the human factor reliability as claimed in claim 4, wherein the human factor reliability analysis of the performance in the process of configuring the digitized human-computer interface by adopting the human factor reliability test system of the configuration performance of the digitized human-computer interface comprises the following steps:
determining a weight ratio of each picture priority to a time slice in 1) based on the human factor reliability test system;
determining the relative importance of each picture in 2) based on the human factor reliability test system;
determining the weight association degree of the picture prompt information in the step 3) based on the human factor reliability test system;
the human factor reliability test system comprises: the device comprises an input layer, a hidden layer and an output layer, wherein an inlet and an outlet of the hidden layer are respectively connected with the input layer and the output layer;
the input layer is used for determining input parameter factors;
the hidden layer is used for calculating the human factor reliability of the input parameter factors according to the input transfer function of the neural network;
the output layer is used for calculating a picture configuration performance test result of the input parameter factor based on human factor reliability according to the neural network excitation function;
the input parameter factors comprise picture configuration performance test evaluation indexes, time spent by an operator in completing corresponding tasks and other influence factors in the test process;
the neural network input transfer function of the hidden layer is as follows:
wherein, ybRepresenting a neural network input transfer function; m represents the number of evaluation indexes of the digital human-computer interface for performance test, and is also called as an input variable; v. ofabRepresenting the weight value of the input layer a-th neuron to the hidden layer b-th neuron; c. CaRepresenting the a-th input variable value for the performance test evaluation index;
the neural network excitation function of the output layer is as follows:
o is the output layer calculated value, i.e.: a digitized human-computer interface performance result based on human factor reliability; s is the weight number from the hidden layer to the output layer; w is abThe weight from the b-th neuron of the hidden layer to the neuron of the output layer;
the neural network input transfer function of the hidden layer is denoted by f1 (x):
with f2(x) Neural network excitation function representing the output layer:
wherein n represents the number of segments of time spent by an operator in completing a corresponding task when testing the performance of the human-computer interface; deltai=Ti/n,TiThe time spent by an operator in completing the corresponding task when testing the configuration performance of the picture is represented; lambda [ alpha ]jThe parameter values are corresponding to the performance evaluation indexes; r (t) is the maximum delay time allowed for the operator when completing the corresponding task; the function z (x) is a human factor reliability analysis mathematical expression.
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