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Статті в журналах з теми "Personal Informatics (PI)":
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Albeladi, Khulood, and Salha Abdullah. "Application of Genetic Algorithm and Personal Informatics in Stock Market." JOIV : International Journal on Informatics Visualization 2, no. 2 (March 3, 2018): 68. http://dx.doi.org/10.30630/joiv.2.2.115.
Анотація:
The financial market is extremely attractive since it moves trillion dollars per year. Many investors have been exploring ways to predict future prices by using different types of algorithms that use fundamental analysis and technical analysis. Many professional speculators or amateurs had been analysing the price movement of some financial assets using these algorithms. The use of genetic algorithms, neural networks, genetic programming combined with these tools in an attempt to find a profitable solution is very common. This study presents a prototype that utilizes genetic algorithms (GAs) and personal informatics system (PI) for short-term stock index forecast. The prototype works according to the following steps. Firstly, a collection of input variables is defined through technical data analysis. Secondly, GA is applied to determine an optimal set of input variables for a one-day forecast. The data is gathered from the Saudi Stock Exchange as being the target market. Thirdly, PI is utilised to create a smart environment, which enables visualisation of stock prices. The outcome indicates that this approach of forecasting the stock price is positive. The highest accuracy obtained is 64.67% and the lowest one is 48.06%.
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Holubova, M., J. Prasko, and H. Klimusova. "Tendency to stigmatization of mentally ill people by university students in the Czech Republic." European Psychiatry 33, S1 (March 2016): s282—s283. http://dx.doi.org/10.1016/j.eurpsy.2016.01.757.
Анотація:
IntroductionMental illness is still surrounded by false myths, stereotypes and prejudices. Stigmatization is a social problem on a national and international level and may lead to discrimination.ObjectivesStigmatization has a negative impact on patient's life, treatment seeking, self-image, adherence and mental health recovery.AimsThe aim of the study was to examined the tendency to stigmatization mentally ill people by university students in the Czech Republic.MethodsThe constructed questionnaire called Tendency to stigmatization TTS (Cronbach's alpha = 0.952), demographic questionnaire and tentative shortened version of personality questionnaire NEO-PI-R were administered on Facebook offered to student groups.ResultsThe statistical analysis of data from 1350 students showed a relatively high tendency to stigmatization depending on age (stigma is lower with age), gender (women have a lower TTS than men), studied university, faculty, educational focus. The lowest rate of stigmatization had students of psychology. Students of economics, management, informatics and engineering disciplines stigmatize in a high degree. Social oriented students had the lowest TTS, technically orientated the highest. The TTS also depends on personal agreeableness (low-friendly students had a higher TTS) and neuroticism (mentally unstable students had slight TTS). Lower TTS had students who attended psychopathological/psychiatric subject at school, also students, who personally met or know somebody with mental disease and students with mental health problems (Table 1).ConclusionsOur study suggests the importance of stigmatization already among university students according to their academic orientation. Understanding the process of stigmatization is important for future efforts to find possible solutions and de-stigmatization of mental illness in society.Disclosure of interestThe authors have not supplied their declaration of competing interest.
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Kim, Jaejoong, Sang Won Lee, Minwook Kwak, Kyueun Lee, and Bumseok Jeong. "Attitudes Formation by Small but Meaningful Personal Information." Psychiatry Investigation 14, no. 3 (2017): 298. http://dx.doi.org/10.4306/pi.2017.14.3.298.
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Aria, Reynald Saevana, Angi Nursetia Putra, and Denny Andreansyah Putra. "Media Live Streaming Berbasis Raspberry Pi Pada Perguruan Tinggi Raharja." CICES 3, no. 1 (February 28, 2017): 98–103. http://dx.doi.org/10.33050/cices.v3i1.432.
Анотація:
Higher Education Prog is a university that focuses konsestrasi in the field of computer and technology, but in the field of penyampaikan information to students remains less efektik because they still use a paper or poster is attached to the wall magazine (Magazine Wall) and his appearance did not attract the students to see and listen information contained campus. The need for an innovation to renew methods penyampaikan user information into a digital form. The authors mebuat Broadcast media based information tool Raspberry Pi utilizing campus facilities like television to show some internal information campuses and as a forum to showcase the work of the Student Video Mavib to display to the Personal Prog.
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HOSSAIN, MD ISMAIL, FATEMA HOQUE SHIKHA, QAMRUZZAMAN HOWLADER, and BIJOY KUMAR DAS. "Production procedure and marketing of ethnic fermented product Nga-pi in South-Eastern region of Bangladesh." Bangladesh Journal of Fisheries 32, no. 1 (July 4, 2020): 115–24. http://dx.doi.org/10.52168/bjf.2020.32.13.
Анотація:
A survey was conducted to collect information on production procedure and marketing of Nga-pi inSouth-Eastern region of Bangladesh (Cox’s Bazar and Bandarban). To collect information questionnaire wasprepared, several visits were made, personal interview of different stakeholders were taken and audio-videorecording was done. Socio-economic condition of different stakeholders of Nga-pi production and businessshowed that most of them were involved in Nga-pi production and business activities generation togeneration. They are mostly people from Rakhine tribe and by religion they are Buddhist. Some of them,especially wholesalers are economically stronger than the producers or retailers. They have access toelectricity, pure drinking water, sanitary latrines and most of them use cell phones for communication. Theinformation on marketing channel of Nga-pi varies depending on the place, and season of the year. Generally,the whole seller and retailer get much profit than the Nga-pi producers. The survey results revealed that in theproduction procedure of Nga-pi in South-Eastern region (Cox’s Bazar and Bandarban) have some points needto be improved to get better quality Nga-pi which may be stored for longer duration.
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Sudarto, Ferry, Eka Purwandari, and Aldien Sora Andrea. "PENGANGKAT BARANG PADA KONDISI BANJIR BERBASIS RASPBERRY PI MELALUI TWITTER SEBAGAI OUTPUT MEDIA INFORMASI." Journal CERITA 1, no. 1 (February 1, 2015): 74–85. http://dx.doi.org/10.33050/cerita.v1i1.202.
Анотація:
Appointment of goods is essential in the operation of the company. Currently forklift with manual or automatic that has not been working efficiently. Especially forklift in flood conditions. So we need tools that work the forklift automatically on flood conditions, the process of appointment, and notify the results of such appointments by personal message via the output of media-based Raspberry Pi Twitter. The circuit uses a forklift Soil Moisture Sensor is used to detect water in the vicinity of the sensor. Raspberry Pi will process the input and give orders to the Motor Servo work to move the hinge table so the table is automatically lifted. Lifting these goods become important in minimizing damage toproperties affected by flooding. So as to improve the efficiency of lifting equipment goods in flood conditions. If the Soil Moisture Sensor exposed to water it will automatically give the data to the Raspberry Pi and processed into information. Once processed, the Raspberry Pi will give two orders to Twitter as output information and the Servo Motor as the physical output will move. The process that is done it does not take long, after the sensor is exposed to water, the appliance works with a period of about 1-2 minutes. Then the items on the table would be safe to avoid flooding with automatic.
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Thomas, Matthew. "University Student and Faculty Opinions on Academic Integrity Are Informed by Social Practices or Personal Values." Evidence Based Library and Information Practice 4, no. 3 (September 21, 2009): 49. http://dx.doi.org/10.18438/b8wk7b.
Анотація:
A Review of:
Randall, Ken, Denise G. Bender and Diane M. Montgomery. “Determining the Opinions of Health Sciences Students and Faculty Regarding Academic Integrity.” International Journal for Educational Integrity 3.2 (2007): 27-40.
Objective – To understand the opinions of students and faculty in physical therapy (PT) and occupational therapy (OT) regarding issues of academic integrity such as plagiarism and cheating.
Design – Q method (a mixed method of qualitative data collection with application of quantitative methods to facilitate grouping and interpretation).
Setting – An urban university-affiliated health sciences facility in the mid-western United States.
Subjects – Thirty-three students and five faculty members of ages 21 to 61 years, 30 associated with the physical therapy program and 8 with occupational therapy, including 6 males and 32 females.
Methods –Initially, 300 opinion statements for, against, or neutral on the subject of academic integrity were gathered from journal articles, editorials and commentaries, Internet sites, and personal web logs, 36 of which were selected to represent a full spectrum of perspectives on the topic. Participants in the study performed a “Q-sort” in which they ranked the 36 statements as more-like or less-like their own values. A correlation matrix was developed based on the participants' rankings to create “factors” or groups of individuals with similar views. Two such groups were found and interpreted qualitatively to meaningfully describe the differing views of each group. Three participants could not be sorted into either group, being split between the factors.
Main Results – Analysis of the two groups, using software specific to the Q method, revealed a good deal of consensus, particularly in being “most unlike” those statements in support of academic dishonesty. The two groups differed primarily in the motivation for academic honesty. Factor one, with 21 individuals, was labeled “Collective Integrity,” (CI) being represented by socially oriented statements such as “I believe in being honest, true, virtuous, and in doing good to all people,” or “My goal is to help create a world where all people are treated with fairness, decency, and respect.” Factor two, with 14 individuals, was described as “Personal Integrity,” (PI), and focused on an internal sense of values and self-modulation, identifying with statements like “Honour means having the courage to make difficult choices and accepting responsibility for actions and their consequences, even at personal cost.” There were also some demographic patterns in the results. Twenty of the 31 students, 20 of the 29 females, and 17 of the 25 participants aged 30 and under were in the CI group, while 3 of the 4 faculty were in PI. Males, occupational therapists, physical therapists, and those over the age of 30 did not belong clearly to one or the other group, having close to equal numbers in both.
Conclusion – Given the two factors, CI and PI, this sample of OT and PT students and faculty can be seen to make academic decisions based on either what they believe society deems correct or what their own internal values tell them. The discovery that more females, students, and those 30 and under were associated with CI resonates with the some key claims in the literature, such as that younger individuals tend to have a more social outlook on academic integrity, or that women's ethic of care is often focused on connections among people. Most importantly, students and faculty appear to share a notable degree of common ground as it relates to their opinions on academic integrity. Additional exploration and the continued use and development of policies promoting academic integrity is called for.
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Bui, Duc, Kang G. Shin, Jong-Min Choi, and Junbum Shin. "Automated Extraction and Presentation of Data Practices in Privacy Policies." Proceedings on Privacy Enhancing Technologies 2021, no. 2 (January 29, 2021): 88–110. http://dx.doi.org/10.2478/popets-2021-0019.
Анотація:
Abstract Privacy policies are documents required by law and regulations that notify users of the collection, use, and sharing of their personal information on services or applications. While the extraction of personal data objects and their usage thereon is one of the fundamental steps in their automated analysis, it remains challenging due to the complex policy statements written in legal (vague) language. Prior work is limited by small/generated datasets and manually created rules. We formulate the extraction of fine-grained personal data phrases and the corresponding data collection or sharing practices as a sequence-labeling problem that can be solved by an entity-recognition model. We create a large dataset with 4.1k sentences (97k tokens) and 2.6k annotated fine-grained data practices from 30 real-world privacy policies to train and evaluate neural networks. We present a fully automated system, called PI-Extract, which accurately extracts privacy practices by a neural model and outperforms, by a large margin, strong rule-based baselines. We conduct a user study on the effects of data practice annotation which highlights and describes the data practices extracted by PI-Extract to help users better understand privacy-policy documents. Our experimental evaluation results show that the annotation significantly improves the users’ reading comprehension of policy texts, as indicated by a 26.6% increase in the average total reading score.
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Singhal, Deepak, Sushant Tripathy, and Sarat Kumar Jena. "Acceptance of remanufactured products in the circular economy: an empirical study in India." Management Decision 57, no. 4 (April 18, 2019): 953–70. http://dx.doi.org/10.1108/md-06-2018-0686.
Анотація:
Purpose Acceptance of remanufactured products by the consumers is highly essential for the success of closed loop supply chain and for achieving the goal of circular economy. However, the literature shows that consumers are reluctant to purchase remanufactured products. Therefore, the study of attitude and purchase intention (PI) of the consumers toward remanufactured products becomes inevitable for popularizing these products. The paper aims to discuss this issue. Design/methodology/approach This research proposes a conceptual model to examine the critical factors influencing the PI of Indian consumers toward remanufactured products. Further, this model is empirically tested, using structural equation modeling technique, based on the data obtained from 1,534 respondents. Findings The findings of this research suggest that PI of consumers is influenced by attitude, personal benefits, remanufactured product knowledge, risk perception, subjective norm and market strategy. However, perceived behavior control and green awareness have a non-significant impact on the PI of Indian consumers. Research limitations/implications The proposed conceptual model is tested only against the data received from the students of Indian universities who possess electronic gadgets. Practical implications The circular economy can be realized through remanufacturing if the attitude of consumers is shaped positively toward remanufactured products through the dissemination of comprehensive product information. Originality/value This research is the first attempt to assess the PI of Indian consumers by developing and testing the conceptual model. Further, this research provides guidelines to remanufacturing firms for attracting the consumers toward the purchase of remanufactured products.
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Choi and Lee. "Effect of Trust in Domain-Specific Information of Safety, Brand Loyalty, and Perceived Value for Cosmetics on Purchase Intentions in Mobile E-Commerce Context." Sustainability 11, no. 22 (November 7, 2019): 6257. http://dx.doi.org/10.3390/su11226257.
Анотація:
In 2016, the safety issues of humidifier disinfectants and some other safety incidents in personal cares caused chemical phobia syndrome in the Korean society. This series of events has created a trend for cosmetic consumers to undermine brand confidence and to self-check the safety of commercial cosmetic formulations through mobile apps. The purpose of this study is to examine the influence of trust in domain specific information on the safety rating of cosmetic ingredients on the perceived value and the purchase intention of the cosmetics. The results of structural equation modeling showed that involvement of skin safety (ISS) had a positive effect on trust in domain specific information on safety (TDSI) and brand loyalty (BL). TDSI showed a positive effect on the perceived safety value (PFV) and the perceived social value (PSV), and BL had a positive effect on the PSV. ISS, TDSI, and PSV had a positive effect on the purchase intention (PI) of green-grade cosmetics (GGC). As hypothesized, BL had an adverse effect on PI of GGC. Given the results, utilizing the signal of the domain specific information may be recommended to new entrants to the cosmetic business or manufacturers with relatively weak brand power.
Дисертації з теми "Personal Informatics (PI)":
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Bitilis, Pavlos. "Electronic Performance And Tracking Systems (EPTS) : Perceptions, Benefits and Challenges of Professional Football Athletes and Training Staff." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-106888.
Анотація:
Personal Informatics (PI) are information systems that allow people to process activities with the usage of information technology, aiming to produce informational products (data) either for themselves or for others. Technologies that enable PI are becoming increasingly popular, assisting people in collecting personally relevant information about their body and their behaviour. In sports industry nowadays, a great variety of PI wearable tools offer support to athletes and training staff to improve their performance. An example of such tool is the Electronic Performance and Tracking Systems (EPTS), which are a combination of hardware and software that facilitates the collection, storage, analysis and management of professional athletes’ fitness and health data. Although significant and broadly used, EPTS have not yet received much attention from researchers and, thus, understudied. Therefore, the master’s thesis explores the perceptions of professional football athletes and training staff regarding the use of EPTS in their everyday training and work. Furthermore, the master’s thesis research explores the benefits and challenges that professional football athletes and training staff experience when using EPTS in their everyday training and work. The master’s thesis study adopts the interpretive paradigm and qualitative ethnographic approach. The research data was collectedthrough direct observations in the field and semi-structured interviews from Greek professional football athletes and Greek training staff that use wearable EPTS in their everyday training and work and was analysed thematically. A theoretical framework, which is built upon relevant literature from the informatics field and along with the theory of sensemaking, is used to understand, interpret and discuss the research findings. The research outcome of the master’s thesis shows that communication is at the core of EPTS enabling football players and training staff to improve individual and team performance. Organizing of every day starts and ends with EPTS analysis and evaluation and better organized and daily evaluated football methodology appears as key benefit for the club. Coaches and trainers are now more data driven and accurate and analysts and trainers that conduct analysisof the data provided by EPTS are new members of the training staff. Evidence provided by EPTS build trust between staff and players and in the training staff. Visualization tools for presenting insights need to be further improved with the addition of in-field monitors and 3D presentations. Furthermore, it is important for training staff members to have ethical and consistent strategy on how data derived from EPTS are used on how data are communicated. The research complements previous research on personal informatics and adjusts them to elite team sport context and adds to the theory of sensemaking regarding how users make sense of PI tools that are related with their everyday routines at work. In addition, it offers football training staff members a model for efficient use of EPTS technology into the everyday football practices and a model of sustainable use aiming the overall improvement of team performance.
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Stenman, Peter, and Mikael Janson. "Talöverföring för trygghetslarm över internet : Voice over IP for personal alarms." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-205349.
Анотація:
During the last couple of years there has been a shift in technology within the Swedish elderly care where the analog personal security alarm is being replaced with personal security alarm that uses internet to communicate. This transition happens due to the ever increasing access to the internet among the elderly and the decreasing availability of analog personal security alarms. This paper describes the work whose purpose is to develop a system that will act as a prototype of a personal security alarm that uses Voice Over IP and the protocol Session Initiation Protocol. The final system is to be comprised by a Raspberry Pi that uses the SIP protocol, a keypad and a soundcard that is built around PCM3060 chip.De senaste åren pågår det ett teknikskifte inom den svenska äldreomsorgen där de analoga trygghetslarmen ersätts av larm som använder internet för att kommunicera. Denna övergång sker på grund av att tillgång till internet ökar hos äldre personer samt att hushåll med analoga anslutningarna blir allt färre. Denna rapport beskriver arbetet med att ta fram ett system som ska fungera som en prototyp för ett trygghetslarm. Detta system använder sig av Voice Over IP och protokollet Session Initiation Protocol. Det slutliga systemet består av en Raspberry Pi som använder sig av SIP protokollet, en knappsats samt ett ljudkort som är byggt runt ett PCM3060 chip.
Частини книг з теми "Personal Informatics (PI)":
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Rastogi, Rohit, Devendra K. Chaturvedi, Parul Singhal, and Mayank Gupta. "Physical Characteristics of Type 1 and 2 Diabetic Subjects." In Advanced Deep Learning Applications in Big Data Analytics, 182–217. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-2791-7.ch010.
Анотація:
The Delhi and NCR healthcare systems are rapidly registering electronic health records, diagnostic information available electronically. Furthermore, clinical analysis is rapidly advancing—large quantities of information are examined and new insights are part of the analysis of this technology—and experienced as big data. It provides tools for storing, managing, studying, and assimilating large amounts of robust, structured, and unstructured data generated by existing medical organizations. Recently, data analysis data have been used to help provide care and diagnose disease. In the current era, systems need connected devices, people, time, places, and networks that are fully integrated on the internet (IoT). The internet has become new in developing health monitoring systems. Diabetes is defined as a group of metabolic disorders affecting human health worldwide. Extensive research (diagnosis, path physiology, treatment, etc.) produces a great deal of data on all aspects of diabetes. The main purpose of this chapter is to provide a detailed analysis of healthcare using large amounts of data and analysis. From the Hospitals of Delhi and NCR, a sample of 30 subjects has been collected in random fashion, who have been suffering from diabetes from their health insurance providers without disclosing any personal information (PI) or sensitive personal information (SPI) by law. The present study aimed to analyse diabetes with the latest IoT and big data analysis techniques and its correlation with stress (TTH) on human health. Authors have tried to include age, gender, and insulin factor and its correlation with diabetes. Overall, in conclusion, TTH cases increase with age in case of males and do not follow the pattern of diabetes variation with age while in the case of female TTH pattern variation (i.e., increasing trend up to age of 60 then decreasing).
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Rastogi, Rohit, Parul Singhal, and Devendra K. Chaturvedi. "Study on South Asian Diabetic Subjects on Different Attributes." In Advanced Deep Learning Applications in Big Data Analytics, 273–310. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-2791-7.ch012.
Анотація:
Diabetes is a serious problem in today's world. Stress TTH (tension type headache) is another epidemic which is growing with a very fast pace. Diabetes is a disease of the body that prevents the metabolism of blood sugar (glucose). This increases the blood glucose to a risky level. The present study aims to analyze diabetes with the latest IoT and big data analysis techniques and its correlation with stress (TTH) on human health. Authors have tried to include age, gender, and insulin factor and its correlation with diabetes. IoT helps us to connect each other, that is, it is known a smart connecting thing (a sort of “universal global neural network” in cloud). It comprises of smart connecting machine with other machine, object, and a lot more. Big data refers to huge sets of data that are also large enough in terms of variety and velocity. Due to this, it becomes more difficult to handle, organise, store, process, and manipulate such data using traditional techniques of storage and processing. Stress especially TTH (tension type headache) is a serious problem in today's world. Now every person in this world is facing headache and stress-related problems in daily life. The authors have collected this big data and studied the people; they have studied their tension level and helped them to cure it. In this chapter, they analyze the correlation between diabetes and stressors. For the analysis, they collected sample of 30 subjects from hospitals of Delhi in random fashion who have been suffering from diabetes from their health insurance providers without disclosing any personal information (PI) or sensitive personal information (SPI) by law. To identify each case sample IDs like S1, S2, etc. has been allotted to the subjects. Sample data has been collected for following parameters: gender, age, diabetes type, insulin dependency, obesity status, CAD status, and CAN status. They have used the Tableau s/w for this analysis. Overall, an interesting observation during the research was that none of the female subjects having diabetes is below 25 years, that is, early age diabetes cases are less comparative to males subjected to the case sampling should not be impacted for age group gender biasing.
Тези доповідей конференцій з теми "Personal Informatics (PI)":
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Sungra, Anshul, and Brian Fabien. "Evaluation of Control Algorithms on Mobile Robots for Collision Avoidance." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23500.
Анотація:
Abstract This paper describes the implementation of various algorithms to control the distance between a lead vehicle and a following (ego) vehicle. The ego robot equipped with a monocular camera and a rotating laser sensor (LDS). The monocular camera used for object detection using the Aggregate Channel Features (ACF) detection algorithm. The width of the bounding box generated by the detection algorithm had used to determine the distance between the lead and the following vehicles. Since this research focused on longitudinal autonomy, the data from the rotating laser sensor downsampled from 360 points to 30 points. These sampled points covered the front view of the vehicle. All data points transformed into a planar world coordinate (two-dimensional plane). The outputs of the camera and laser sensor (LDS) were fused to obtain accurate distance measurements for the lead vehicle. Sensor calibration had achieved by comparing sensor data with the ground truth values. Kalman Filter was used to implementing sensor fusion by combining perception data from the monocular camera and LDS for accurate position and velocity estimation. This calibration provided information about the sensor noise and deviation of sensor data from its ground truth values. These values helped to determine the error covariance matrixes of the Kalman filter. For implementation, the Robot Operating System (ROS)-MATLAB platform used to communicate between robot and host Personal Computer (PC). The experiments evaluated the performance of Proportional Control (P), Proportional-Integral Control (PI), and Model Predictive Control (MPC) in maintaining a minimum distance between the vehicles. For the MPC implementation in MATLAB, Model Predictive Control Quadratic Programming (MPCQP) solver was used to get the optimal solution for control output. The results show that the MPC yields faster response times when compared to P control and PI control. These algorithms evaluated during constant velocity and constant acceleration of the lead vehicle. The steady-state errors of P and PI controllers were around 0.1 meters (m) in both scenarios and 0 to 0.2m for constant velocity and 0 to 0.15m for ramp velocity, respectively. And for MPC, steady-state error varied from −0.05m to 0.05m in both the scenarios. This range in steady-state error was due to varying speed of the ego vehicle with time to maintain the minimum relative distance between the robots, and there was a communication delay in the system that also affected the behavior of the controllers. The MPC was more sensitive to communication delays. However, the effect of this communication delay was negligible to P and PI controllers. This sensitivity resulted in different velocity profiles for the ego vehicle in MPC and P or PI controllers.
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McClintock, Michael, and Kenneth L. Cramblitt. "Combined Cycle Plant Performance Monitoring." In ASME 2004 Power Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/power2004-52070.
Анотація:
Monitoring thermal performance in the current generation of combined cycle power plants is frequently a challenge. The “lean” plant staff and organizational structure of the companies that own and operate these plants frequently does not allow the engineering resources to develop and maintain an effective program to monitor thermal performance. Additionally, in many combined cycle plants the highest priority is responding to market demands rather than maintaining peak efficiency. Finally, in many cases the plants are not designed with performance monitoring in mind, thus making it difficult to accurately measure commonly used indices of performance. This paper describes the performance monitoring program being established at a new combined cycle plant that is typical of many combined cycle plants built in the last five years. The plant is equipped with GE 7FA gas turbines and a GE reheat steam turbine. The program was implemented using a set of easy-to-use spreadsheets for the major plant components. The data for the calculation of indices of performance for the various components comes from the plant DCS system and the PI system (supplied by OSIsoft). In addition to the development of spreadsheets, testing procedures were developed to ensure consistent test results and plant personnel were trained to understand, use and maintain the spreadsheets and the information they produce.
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Kasempong, Surawich, Niyom Kanokwareerat, Boonyalit Tangjitkongpittaya, Sarunyoo Setakornnukul, Apinan Laipanich, and Weerawat Pourwichittham. "Real-Time Ageing and Diagnostic Prediction for Various Hybrid Solar-TEG Power Units by Machine Learning." In International Petroleum Technology Conference. IPTC, 2021. http://dx.doi.org/10.2523/iptc-21202-ms.
Анотація:
Abstract In PTTEP's offshore fields, more than 100 units of hybrid Solar-TEG power with individual VRLA battery banks are installed on wellhead platforms for powering the process. With large number of various equipment in remote locations, traditional maintenance approach highly consuming resources is, thus, not cost effective especially in oil price crisis. In 2019, "Hybrid Power Solar-TEG Predictive Maintenance" project is established to develop a predictive model and transform maintenance process to total predictive maintenance. The project was begun with three platforms as a pilot project. The operating model was built by machine learning using various historical data recorded in PI system, records of maintenance data and other relevant information such as manufacturer manual, international standard and related white papers. The modelled algorithm was embedded in an application which was developed by Python to predict the ageing and performance of battery banks on pilot wellhead platforms. In 2020, the project continues to build the model of Thermo-Electric Generator (TEG) and extend the coverage location for additional thirty-seven (37) platforms. Lower Depth of Discharge (DoD), higher ambient temperature and lower charging performance are signs of battery’s deterioration while lower supplied current from power source is sign of their underperformance. All parameters were ingested to conduct pattern recognition to make algorithm be able to predict the remaining life of the key equipment. The Eyeball method is conducted to train algorithm the various charging patterns by the developers with aim to evaluate the DoD of battery bank. Apart from battery life prediction, DoD is employed to determine the energy left in battery from night operation to indicate the remaining run time duration. By leveraging machine learning, all failure patterns are recognized. The application is operating real?time and provide early alarm to all person-in-charge when failure potential is realized. The results are visualized on PowerBI to provide the latest status of power units of each platforms. From above, the maintenance approach is thus completely converted from Run-to-Failure to Predictive Maintenance. The long lead spare parts e.g. battery cells could be procured in advance. Spare inventory can be optimized per actual demand. In addition, the offshore supervisor could accurately identify the defective battery banks and proactively recover them in time to minimize unplanned shutdown. The modelled algorithm was in-house developed based on technical information and maintenance records. Although the system goes live, the preventive maintenance according to IEEE1188 is still retained for further collecting more field data to improve accuracy of the model. In addition, the model’s analyzed information, such as battery run time and DoD, has revealed the hidden actual design margin of power system. The platform CAPEX can be thus deducted by removing such excess margin.